PROCEEDINGS VOL. 4 INDUSTRIAL INFORMATIC INDUSTRIAL MANAGEMENT
ISSN 1310-3946 26 (212)
SCIENTIFIC PRO CE E DI NGS OF THE SCIENTIFIC TECHNICAL UNION OF MECHANICAL ENGINEERING Year XXIV
Volume 26/212
SEPTEMBER 2016
XIII INTERNATIONAL SCIENTIFIC CONGRESS
MACHINES. TECHNOLОGIES. MATERIALS. 2016 SUMMER SESSION 14–17.09.2016 VARNA, BULGARIA
VOLUME IV SECTION “INDUSTRIAL INFORMATIC 2016” SECTION “INDUSTRIAL MANAGEMENT 2016”
ISSN 1310-3946
INTERNATIONAL EDITORIAL BOARD Chairman: Prof. DHC Georgi Popov
Vice Chair: Prof. Dr. Eng. Tsanka Dikova
Members: Acad. Ivan Vedyakov, RU Acad. Yurij Kuznetsov, UA Prof. Aleksander Mihaylov , UA Prof. Anatoliy Kostin, RU Prof. Adel Mahmud , IQ Prof. Ahmet Ertas, TR Prof. Andrzej Golabczak, PL Prof. Boncho Bonev, BG Prof. Gennady Bagluk, UA Prof. Detlef Redlich, DE Prof. Dipten Misra, IN Prof. Dmitry Kaputkin, RU Prof. Eugene Eremin, RU Prof. Ernest Nazarian , AM Prof. Juan Alberto Montano, MX Prof. Esam Husein, KW Prof. Ivo Malakov, BG Prof. Krasimir Marchev, USA Prof. Leon Kukielka, PL Prof. Lyudmila Ryabicheva, UA Prof. Milan Vukcevic, ME
Prof. Mladen Velev, BG Prof. Mohamed El Mansori, FR Prof. Movlazade Vagif Zahid, AZ Prof. Nikolay Dyulgerov, BG Prof. Oana Dodun, RO Prof. Olga Krivtsova, KZ Prof. Peter Kostal, SK Prof. Raul Turmanidze, GE Prof. Renato Goulart, BR Prof. Roumen Petrov, BE Prof. Sasho Guergov, BG Prof. Seiji Katayama, JP Prof. Sergej Dobatkin, RU Prof. Sergej Nikulin, RU Prof. Stefan Dimov, UK Prof. Svetan Ratchev, UK Prof. Svetlana Gubenko, UA Prof. Tale Geramitchioski, MK Prof. Vadim Kovtun, BY Prof. Viktor Vaganov, RU Prof. William Singhose, USA Prof. Yasar Pancar , TR
CONTENTS THE NUMERICAL-ANALYTIC SUBSTANTIATION OF THE POSSIBILITY OF AUTOMATED MOTION CONTROL OF AN AUTONOMOUS RIGID BODY WITHOUT ITS OWN PROPULSION SYSTEM IN INCOMPRESSIBLE STRATIFIED VISCOUS FLUID Postgraduate Kuznetcova L.V., Prof., Dr. Tech. Sci. Firsov A.N. ....................................................................................................................... 4 NUMERICALLY-ANALYTICAL SOLUTION OF THE TRANSPORTATION PROBLEM FOR THE VISCOUS WEAKLY COMPRESSIBLE LIQUID, MOVING THROUGH THE PIPELINE WITH NON-STATIONARY BOUNDARY CONDITIONS Ph.D. Student Sorokina N. .................................................................................................................................................................................... 7 NUMERICAL-ANALYTICAL METHOD FOR SOLVING THE INVERSE PROBLEM OF STABILITY FOR TECHNICAL SYSTEMS WITH MULTIPLE UNCERTAIN PARAMETERS Postgraduate Bulkina E., Prof., Dr. Tech. Sci. Firsov A. ................................................................................................................................... 10 ПОДХОД ЗА УПРАВЛЕНИЕ И ДИАГНОСТИКА НА ПРОИЗВОДСТВЕНА СТАНЦИЯ FESTO MPS PROCESSING-ЧАСТ I Христо Карамишев, Георги Попов ................................................................................................................................................................. 13 CONSTRAINED SIMILARITY OF 2-D TRAJECTORIES BY MINIMIZING THE H1 SEMI-NORM OF THE TRAJECTORY DIFFERENCE PhD Student Filipov S., Assoc. Prof. Atanassov A., Senior Lecturer Gospodinov I. .........................................................................................17 ONTOLOGY-BASED DATA ACCESS AND MODEL TRANSFORMATIONS FOR ENTERPRISE INTEROPERABILITY Assist. Prof. Dr. Gocheva D. G., Prof. Dr. Batchkova I. A., Prof. D.Sc. Popov G. T. ....................................................................................... 20 A MAPREDUCE SOLUTION FOR HANDLING LARGE DATA EFFICIENTLY M.Sc. K. Al-Barznji PhD Student, Assoc. Prof. Dr. A. Atanassov .................................................................................................................... 24 THE METHOD OF SPIRAL DESIGN MODEL FOR THE AUTOMATED DESIGN OF ANALOG IP-CORES IN COMPUTING Student Gavrilova N.M., Prof. Dr. Tech. Sci. Molodyakov S.A. ....................................................................................................................... 28 ADVANCED CREATING OF 3D DENTAL MODELS IN BLENDER SOFTWARE Phd Tihomir Dovramadjiev ................................................................................................................................................................................ 32
MOLECULAR MODELING AND CREATING 3D MODELS OF CHEMICAL COMPOUNDS IN BLENDER SOFTWARE USING THE RESOURCES OF CHEMSPIDER AND OPEN BABEL Phd Tihomir Dovramadjiev ................................................................................................................................................................................ 34 МУЛТИМОДАЛНО ПРЕДСТАВЯНЕ НА РЕЗУЛТАТИ ОТ ИНЖЕНЕРНИ (CAE) АНАЛИЗИ В СРЕДА НА ВИРТУАЛНА РЕЛНОСТ MULTIMODAL PRESENTATION OF ENGINEERING (CAE) ANALYSIS RESULTS IN VIRTUAL REALITY ENVIRONMENT гл. ас. Бъчваров, А. Г., проф. д-р Малешков, С. Б., гл. ас. д-р Чотров, Д. И. ............................................................................................. 36 THE PROBLEM OF OVERLAPPING PROJECT ACTIVITIES WITH INTERDEPENDENCY Prof. Gurevich G., Prof. Keren B., Prof. Laslo Z. .............................................................................................................................................. 40 IMPROVING PROCEDURES OF TRAINANG EMPLOYEES BY IMPLEMENTING GUIDANCE CARDS SAFE METHODS AND TECHNIQUES OF WORK Associate Professor of the Department of industrial safety and environmental protection, Ph.D. Afanasyeva I.V. Graduate student of the Department of industrial safety and environmental protection Fatkhutdinov R. I. ...................................................... 44 SUMMARY OF INNOVATION MODELS ON A COMPANY LEVEL – CREATING A FRAMEWORK FOR AN INNOVATION MODEL THAT WILL INCREASE A COMPANY’S INNOVATION ACTIVITY M.Sc. Stefanovska Ceravolo LJ., Prof. PhD. Polenakovikj R., Prof. PhD Dzidrov M. ..................................................................................... 47 MATHEMATICS INDUSDTRY ECONOMY – MICRO-FOUNDRY Bushev St. PhD. assoc. prof. eng. ....................................................................................................................................................................... 51 ЭЛЕКТРОННАЯ КОММЕРЧЕСКАЯ ДЕЯТЕЛЬНОСТЬ КАК СРЕДСТВО УДЛИНЕНИЯ ЦЕПОЧКИ ДОБАВЛЕННОЙ СТОИМОСТИ Post Gr Student, Shepitko G., Post Gr Studet Beloborodjko V. ......................................................................................................................... 54 ВЛИЯНИЕ ИЗМЕНЕНИЯ ДОЛИ ГОСУДАРСТВЕННОЙ СОБСТВЕННОСТИ НА ЭКОНОМИЧЕСКУЮ БЕЗОПАСНОСТЬ ГОСУДАРСТВА As. Prof., dr. Yegorova-Gudkova Т. .................................................................................................................................................................. 56 ПРОДОВОЛЬСТВЕННАЯ БЕЗОПАСНОСТЬ ГОСУДАРСТВА И СМЕНА СОБСТВЕННОСТИ НА ЗЕМЕЛЬНЫЕ РЕСУРСЫ Post Gr Student, Zverkov 0. ............................................................................................................................................................................... 58 ИССЛЕДОВАНИЕ ЭМЕРДЖЕНТНЫХ СВОЙСТВ ТЕНЕВОЙ ЭКОНОМИКИ Post Gr Student, Bojko M. .................................................................................................................................................................................. 60 ИЗМЕНЕНИЯ В ГЛОБАЛЬНОЙ ЭКОНОМИКЕ В УСЛОВИЯХ СТАНОВЛЕНИЯ ЮАНЯ МИРОВОЙ РЕЗЕРВНОЙ ВАЛЮТОЙ As. Prof., dr. Yegorova-Gudkova Т, Student Panj Li ........................................................................................................................................ 62 СИСТЕМА ФИНАНСОВОГО КОНТРОЛЯ ГОСУДАРСТВА КАК ИНСТРУМЕНТ ДЕТЕНИЗАЦИИ ЭКОНОМИКИ Honored Economist of Ukraine, Karabanov A., Post Gr Student, Krygin A., Director Tetlezkij J. .................................................................. 64
THE NUMERICAL-ANALYTIC SUBSTANTIATION OF THE POSSIBILITY OF AUTOMATED MOTION CONTROL OF AN AUTONOMOUS RIGID BODY WITHOUT ITS OWN PROPULSION SYSTEM IN INCOMPRESSIBLE STRATIFIED VISCOUS FLUID ЧИСЛЕННО-АНАЛИТИЧЕСКОЕ ОБОСНОВАНИЕ ВОЗМОЖНОСТИ АВТОМАТИЗИРОВАННОГО УПРАВЛЕНИЯ ДВИЖЕНИЕМ АВТОНОМНОГО ТВЕРДОГО ТЕЛА БЕЗ СИЛОВОЙ УСТАНОВКИ В СТРАТИФИЦИРОВАННОЙ ВЯЗКОЙ НЕСЖИМАЕМОЙ ЖИДКОСТИ Postgraduate Kuznetcova L.V.1, Prof., Dr. Tech. Sci. Firsov A.N.2 Peter the Great St.Petersburg Polytechnic University – St.Petersburg, Russia E-mail:,
[email protected],
[email protected] Abstract: The report presents a mathematical model of the motion control of an autonomous solid body moving in incompressible stratified viscous fluid and analytical and numerical analysis of this model. It is assumed that the body does not have its own propulsion system, but is equipped with controlled rudders - wings of finite span. It is moved by the influence of the buoyancy force and wings lift. The control is produced by the angle of attack of the wing change for ensuring access to the given point by this solid body. This body motion is considered to be plane-parallel motion. This paper results are based on the mathematical model which was presented by the authors at XII MTM Congress held in September 2015 and XIII MTM Congress held in March 2016. KEYWORDS: MOTION OF SOLIDS IN A FLUID, TRAFFIC COTROL, BUOYANCY FORCE, ENSURING ACCESS TO THE GIVEN POINT, WINGS OF FINITE SPAN, WINGS LIFT The motion of submersible craft is assumed to happen in a limitless borehole bottom reservoir with an ideal incompressible non-conducting stratified liquid with viscosity effect. The viscosity is taken into account as a Stokes' drag force. It is also assumed that each layer has own density, which is known. Furthermore, liquid in each layer can move rectilinearly and uniformly with known velocity along the horizontal axis, which is perpendicular to a wingspread.
1. Introduction The effectiveness of observations and measurements obtained in the study of the underwater world via underwater vehicles, in particular, unmanned, depends on minimizing the impact of these submersible crafts to surrounding underwater environment. First of all, it refers to a moving apparatus, which movement is carried out by various power plants (screw propeller or other propulsion). Therefore, the reduction or elimination of such effects is an important application. The ideal situation would obviously be the complete lack of engine. This means that movement control of the body can be carried out only by natural hydrodynamic forces, for instance, the Archimedes buoyancy or an wing lift effect (the body can be equipped with wing). Basic terminology and classical results for the body’s motion in continuum can be found in the books [1, 2].
2. Accepted assumptions As an autonomous rigid body, the authors propose to consider a research submersible – a uniform sphere-shaped rigid body with two similar symmetrically located around the ball centre wings (fig. 1). Actually other modifications of mutual bracing of the sphere-shaped body and wings are possible. However, the proposed mathematical model can be taken as a basis for whole these alternatives.
Fig. 2. Double-layer continuum figure. In this paper the authors consider plane-parallel motion of submersible craft case. At the initial time this body is located in stationary state at a predetermined depth (fig. 2). It is necessary to define the obtaining solution algorithm in a double-layer liquid for building a similar solution in stratified liquid. It is usually understood that an inverse problem is a problem of control synthesis which use leads to achievement of the defined preselected value. The goal of this research is a substantiation of existence of well-defined problem description in concerned field. There is considered to be a problem of submersible craft appearance in surface in small neighborhood of given point.
Fig. 1. Schematic submersible craft image.
4
Then appropriate motion trajectories of the submarine craft can be calculated by solving the system (1) with zero initial conditions (fig. 4).
3. Mathematical model At the previous authors paper [3] mathematical model of the submersible craft plane-parallel motion was constructed. It allows controlling the body through wings angle of attack modifications: 2 𝑑 2𝑥 (1) (2) ⎧�𝑚 + 𝜌𝜋𝑅 3� 2 = 𝐹𝑎𝑟𝑐ℎ − 2𝐹𝑖 cos𝛿 − �𝐹𝑑𝑟𝑎𝑔 + 2𝐹𝑑𝑟𝑎𝑔 � cos𝛿 − 2𝐹𝑙𝑖𝑓𝑡 sin𝛿 − 𝐹𝑔 ; 3 𝑑𝑡 2 𝑑 2𝑦 ⎨ (1) (2) �𝑚 + 𝜌𝜋𝑅 3� 2 = −2𝐹𝑖 sin𝛿 − �𝐹𝑑𝑟𝑎𝑔 + 2𝐹𝑑𝑟𝑎𝑔 � sin𝛿 − 2𝐹𝑙𝑖𝑓𝑡 cos𝛿. ⎩ 3 𝑑𝑡 (𝑗)
(𝑗)
Here 𝐹𝑎𝑟𝑐ℎ – is the buoyancy force, 𝐹𝑑𝑟𝑎𝑔 = 𝐶𝑋 𝑆 (𝑗)
𝜌𝑣 2
– the head
2
resistance force for a sphere (j=1) and wings (j=2), 𝐹𝑙𝑖𝑓𝑡 = 𝜌𝑣 2 𝑆
𝑘𝛼
𝜌
– the wing lift, 𝐹𝑖 = 𝑣 2 𝑆
1+𝜇0
2
𝜇0
�
2𝑘𝛼
2𝑘 1+𝜇0
2
� – the induced drag
force (details can be found in [3]). The analysis of constructed mathematical model in terms of the possibility of motion trajectory control of the submersible craft by the attack angle continuous variation is produced at this paper. A term "motion trajectory of the submersible craft" means motion trajectory of gravity center of the submersible craft (the sphere center). As a rule, it is supposed that an attack angle is a small quantity [4]. Authors also allow this assumption. The attack angle smallness necessitates the angle δ smallness. Therefore, we can accept sin𝛿 ≈ 𝛿, cos𝛿 ≈ 1. Using the standard change of variables: 𝑥 = 𝑧1 𝑦 = 𝑧3 𝑥̇ = 𝑧1̇ = 𝑧2 𝑦̇ = 𝑧3̇ = 𝑧4 , initial mathematical model is reduced to the nonlinear differential equation system: 𝑧1̇ = 𝑧2 , ⎧ 𝑧2̇ ∙ 𝑏0 = 𝑏1 − (𝑏2 ∙ 𝛼 2 + 𝑏3 + 2𝑏4 ) ∙ (𝑧2 2 + 𝑧4 2 ) − ⎪ ⎪ −2𝑏5 ∙ 𝛼 ∙ 𝑧4 ∙ �𝑧2 2 + 𝑧4 2 , (1) 𝑧3̇ = 𝑧4 + 𝑤, ⎨ 2 ⎪𝑧4̇ ∙ 𝑏0 = −(𝑏2 ∙ 𝛼 + 𝑏3 + 2𝑏4 ) ∙ 𝑧4 ∙ �𝑧2 2 + 𝑧4 2 + ⎪ ⎩ +2𝑏5 ∙ 𝛼 ∙ (𝑧2 2 + 𝑧4 2 ). Here coefficients are defined as: 2
𝑏0 = 𝑚 + 𝜌𝜋𝑅3 ,
𝑐0_𝑠𝑝ℎ
3
𝜌𝜋𝑅2 2
𝑏1 = 𝜌𝑔𝑉 − 𝑚𝑔,
, 𝑏4 = 𝑐0_𝑤
𝜌𝑆𝑤 2
, 𝑏5 = 𝜌𝑆𝑘𝑝
𝑘
2𝑘𝜇
𝑏2 = 𝜌𝑆𝑘𝑝 (1+𝜇 0)2,
1+𝜇0
.
0
Fig. 3. Cases of the variation law of attack angle of the submarine craft in homogeneous fluid.
𝑏3 =
A motion trajectory of the submarine craft can be modified by the wing attack angle α values variations. For instance, in this paper the following assumptions are considered: 1) The attack angle is able to change at a constant speed, which equals 0.5 degrees per second; 2) Attack angle threshold requirements are ±15 degrees; 3) The attack angle at the initial time equals 0.
Fig. 4. Motion trajectories of the submarine craft for different cases of the variation law of attack angle in homogeneous fluid.
4.2. Double-layer liquid Motion of the submersible craft in STRATIFIED (doublelayer) ideal incompressible viscous fluid with shear flow in the line of horizontal axis is considered. Authors examine three cases of the variation law of attack angle (fig. 5): 1) α = 0; 0.5 ∙ 𝑡, 𝑖𝑓 0 ≤ 𝑡 ≤ 30 < 𝑡̂ , ⎧ ⎪ 15, 𝑖𝑓 30 ≤ 𝑡 ≤ 𝑡̂ , 2) 𝛼 = ⎨15 − 0.5 ∙ (𝑡 − 𝑡̂ ), 𝑖𝑓 𝑡̂ ≤ 𝑡 ≤ 𝑡̂ + 60, ⎪ −15, 𝑖𝑓 𝑡̂ + 60 ≤ 𝑡. ⎩ −0.5 ∙ 𝑡, 𝑖𝑓 0 ≤ 𝑡 ≤ 30 < 𝑡̂ , ⎧ ⎪ −15, 𝑖𝑓 30 ≤ ≤< 𝑡̂ , 3) 𝛼 = ⎨−15 + 0.5 ∙ (𝑡 − 𝑡̂ ), 𝑖𝑓 𝑡̂ ≤ 𝑡 ≤ 𝑡̂ + 60, ⎪ 15, 𝑖𝑓 𝑡̂ + 60 ≤ 𝑡. ⎩ ̂ Here 𝑡 – is an ascent time of the submarine craft in bottom layer. Then appropriate motion trajectories of the submarine craft can be calculated by solving the system (1) (fig. 6). The differential equation system is sequentially solved for each layer starting with
4. Numerical examples Fourth-order of accuracy Runge-Kutta method was applied for numerical solution of the differential equation system (1). Software called MATLAB 7.10.0 (R2010A) is used.
4.1. Homogeneous liquid Motion of the submersible craft in homogeneous (singlelayer) ideal incompressible viscous fluid with shear flow in the line of horizontal axis is considered. Authors examine three cases of the variation law of attack angle (fig. 3): 1) α = 0; 0.5 ∙ 𝑡, 𝑖𝑓 0 ≤ 𝑡 ≤ 30, 2) 𝛼 = � 15, 𝑖𝑓 30 < 𝑡. −0.5 ∙ 𝑡, 𝑖𝑓 0 ≤ 𝑡 ≤ 30, 3) 𝛼 = � −15, 𝑖𝑓 30 < 𝑡.
5
the bottom layer. Its initial conditions are supposed zero conditions. For other layers initial conditions are recalculated depending on coordinates of inertia center of the submarine craft at the transitional point from layer to layer.
that neighbourhood, for each point of which can be set an inverse well-defined problem, is obtained.
6. Literature 1.
2.
3.
4.
Fig. 5. Cases of the variation law of attack angle of the submarine craft in double-layer fluid.
Fig. 6. Motion trajectories of the submarine craft for different cases of the variation law of attack angle in double-layer fluid. At these examples, the following values of quantities are offered. The diameter of the surfaced body (ball) is 1 meter; its mass is calculated like 𝑚 = 0.98𝜌𝑉, where ρ is averaged body density. It is assumption to consider rectangular wings with wingspan 1 meter, aspect ratio of the wing 5 and relative maximum thickness 16 %. An initial immersion depth H1 equals 200 meters. In case of homogeneous liquid its density is supposed to be 1038 kg/m3, shear flow velocity – |𝑤 ��⃗| = 0.1 m/s. shear flow velocity. The second layer depth H2 is 70 meters. Liquid densities in different layers equals ρ1= 1050 kg/m3 and ρ2=1025 kg/m3. Shear ����⃗| �����⃗| flows have velocities |𝑤 1 = 0.15 m/s and |𝑤 2 = 0.1 m/s.
5. Conclusion
At this paper the motion trajectory of the submarine craft calculation algorithm is presented. Mentioned body can rise up under the influence of the Archimedes buoyancy and a wing lift effect. The continuously varying wing attack angle control possibility of the submarine craft movement is analyzed. Besides
6
Vallander S.V. Lekcii po gidroaeromehanike [Lectures on hydrodynamics]. – St. Petersburg, St. Petersburg Univ. Press, 2005. 304 p. (In Russian) Kochin N.E., Kibel' I.A., Roze N.V. Teoreticheskaja gidromehanika [Theoretical Hydromechanics]. Moskow, Fizmatlit Publ., 1963. Vol. 1-2. (In Russian) Firsov A. N., Kuznetsova L. V., Sorokina N. V. The solution of the inverse problem of motion control of a rigid body, popup in a stratified incompressible viscous fluid under the influence of the Archimedes force // XII International Congress “Machines, Technologies, Materials” (Varna, Bulgaria, 16-19.09.2015). Proceedings, Vol. 3. – P. 3-7. (2015) Martinov A. K. Experimental Aerodynamics. Moskow, Oborongiz, 1950. 475 p. (In Russian)
NUMERICALLY-ANALYTICAL SOLUTION OF THE TRANSPORTATION PROBLEM FOR THE VISCOUS WEAKLY COMPRESSIBLE LIQUID, MOVING THROUGH THE PIPELINE WITH NON-STATIONARY BOUNDARY CONDITIONS Ph.D. Student Sorokina N. Institute of Computer Science And Technology – Peter the Great Saint-Petersburg Polytechnic University, Russia
ЧИСЛЕННО-АНАЛИТИЧЕСКОЕ РЕШЕНИЕ ЗАДАЧИ О ТРАНСПОРТИРОВКЕ ВЯЗКОЙ СЛАБОСЖИМАЕМОЙ ЖИДКОСТИ ПО ТРУБОПРОВОДУ ПРИ НЕСТАЦИОНАРНЫХ КРАЕВЫХ УСЛОВИЯХ Аспирант Сорокина Н. Институт компьютерных наук и технологий – Санкт-Петербургский политехнический университет Петра Великого, Россия Abstract: In the paper we solve the problem of transporting viscous weakly compressible liquid through the pipeline of the circular cross-section under non-stationary conditions. This paper is based on previous author's results, presented on WS of XIII MTM Congress. The Navier-Stokes equations are the basis for mathematical model. The liquid kinematic viscosity and its density are considered to be weakly changing with time. The non-stationarity is caused by specific boundary conditions, depending on time. The obtained results allow to optimize the control of a viscous weakly compressible liquid flows in the pipeline systems. Keywords: EQUATIONS
WEAKLY
COMPRESSIBLE
LIQUID,
PIPELINE,
HYDRODYNAMICS,
NAVIER-STOKES
Consider the flow along the horizontal pipe axis ( z axis), neglecting mass forces ( F = 0 ). Based on these assumptions, rewrite the system (1) as follows:
1. Introduction Physical and chemical properties of the fluids, transported through pipeline systems, define the project and operating parameters of pipelines in many ways. Considering oil industry, pipelines are used for the transportation of a wide spectrum of hydrocarbons and its mixtures, that greatly differing in chemical and physical properties: products of oil refining (gasoline, jet fuel, kerosene, diesel fuel, fuel oil, etc.), petrochemical raw materials (benzene, styrene, propylene, etc.), aromatic hydrocarbons (xylene, toluene, cumene, etc.), liquefied petroleum fuel (liquefied natural gas, liquefied petroleum gas) and so on. Information about fluid physical properties is considered both when choosing the type of the mathematical model, and when defining coefficients (parameters) of corresponding elements of this model. Changing, these parameters may have influence on the flow character. Previously we have studied the effect of the variable dynamic viscosity, depending on a small parameter, on the liquid velocity in the pipeline [1]. In this paper we consider the case, when the liquid density is not constant; for example, hydrocarbons, generally, are weakly compressible liquid, which density depends on pressure and temperature [2]. We assume, that the density is changing with time according to the known manner. Also, we consider non-stationary conditions at the pipe edges (in terms of variable pressure).
∂υ z dρ 0, dt + ρ ∂z = ∂τ ρ ∂υ + υ ∂υ = ∂τ x + y + ∂τ z . z ∂t ∂z ∂x ∂y ∂z
(1′)
Project the second equation of the system ( 1′ ) on the axes of the corresponding Cartesian coordinate system: ∂τ yx ∂τ zx ∂υ ∂τ ∂υ x ; + υ z x = xx + + ∂z ∂x ∂y ∂z ∂t ∂υ ∂τ ∂τ ∂τ ∂υ ρ y + υ z y = xy + yy + zy ; t z x y ∂ ∂ ∂ ∂ ∂z ∂τ ∂υ ∂τ ∂τ ∂υ ρ z + υ z z = xz + yz + zz . ∂z ∂x ∂y ∂z ∂t
ρ
Taking into account the assumptions, made above, we obtain the following expressions: ∂ 2υ ∂p , (λ + µ ) z = ∂z∂x ∂x ∂ 2υ ∂p , (λ + µ ) z = ∂y∂z ∂y
2. Formulation of the problem The task is to obtain the equation of a viscous weakly compressible liquid motion through the cylindrical pipe with nonstationary boundary conditions. We take the system of equations of a viscous liquid dynamics as a basis [3]: dρ 0, dt + ρ divυ = ∂τ ρ dυ = ρ F + ∂τ x + y + ∂τ z , dt ∂x ∂y ∂z
NON-STATIONARY
∂ 2υ z ∂ 2υ z ∂ 2υ z ∂υ z ∂υ z + υz = µ 2 + 2 + 2 ∂z ∂y ∂z ∂t ∂x
ρ
∂p ∂ 2υ + λ 2z , − ∂z ∂z
where p = p ( t,z ) – pressure, λ – the bulk viscosity coefficient,
µ – the dynamic viscosity coefficient. The first two equations yield the following: ∂υ z p + F1 ( y,z,t ) , ( λ + µ ) ∂z = ( λ + µ ) ∂υ z = p + F2 ( x,z,t ) . ∂z
(1)
– continuity equation and motion equation. Here υ – velocity, ρ – density, F – mass forces vector, τ x , τ y , τ z – vectors,
Hence F= F= F ( z,t ) and, as a result: 1 ( y,z,t ) 2 ( x,z,t )
corresponding to the stress tensor lines [3].
7
∂υ z − F ( z,t ) . ( 2) ∂z From the continuity equation the velocity z derivative can be expressed: ∂υ z 1 dρ ; = − ( 3) ρ dt ∂z then ∂ 2υ dρ ∂υ ∂ 2υ ∂ 2υ ∂p ∂ 2υ ρ z − υ z = µ 2z + 2z + 2z − + λ 2z . ( 4 ) dt ∂t ∂y ∂z ∂z ∂z ∂x
where
p= (λ + µ )
µ2
∞ − n2 (τ − s ) 2ξ µ µ G2 (τ − s,ξ ,η ) = e N J0 n ξ J0 n η , ∑ 2 2 N J µ ( ) N N n =1 n 1
ψ i (ξ , χ ) =
Since we noted at the beginning, that the liquid density is ∂ 2υ z = 0 (according to equation (3)). changing only with time, then ∂z 2 ∂p From (2) we obtain for : ∂z ∂F ( z,t ) ∂p = − . ∂z ∂z Hence the pressure variation along the pipeline length is described ∂F ( z,t ) . by some function f ( t,z ) = − ∂z Turning to the cylindrical coordinate system in equation (4) and taking into account the last obtained relations, we write the equation for determining the viscous compressible liquid velocity in the pipeline: ∂υ z ∂ 2υ ν ( t ) ∂υ z 1 d ρ (t ) 1 υz + f ( z,t ) , = ν ( t ) 2z + + r ∂r ρ ( t ) dt ρ (t ) ∂t ∂r
µ2
i − n2 (τ −τ min ) µn µn 2ξ e N J0 ξ J0 η , 2 2 N N n =1 N J1 ( µ n )
∞
G1 (τ ,ξ ,η ) = ∑
d
ν
γ i ( s, χ ) =
e − aiτ min ϕ i (ξ , χ ) , i
i d 3 f ( s, χ )
ν2
ρm
,
i i τ ∈ τ min ,τ max ) , i = 1,h .
As an example, we build the solution in case, when velocity doesn’t depend on z . We take the Poiseuille velocity distribution as an initial condition [3], set the linear law of density variation, and linear change in pressure at the pipe outlet: a ρ (= t) t + ρ0 , (7) T z p − p0 z p ( t,z ) = − + 1 pН + k t + p0 . (8) L T L We pay special attention to the oil transportation, and oil density kg kg [5]; assume ρ 0 = 830 . 3 as an may vary within 730 − 940 3 m m initial value of the density.
( 5)
where t ∈ [ 0 ,T ] , r ∈ [ 0 ,R ] . For the equation (5) we formulate the
6
initial-boundary problem: find the υ z ( t,r,z ) function, which is a
r=0 r=0.2
5
solution of the equation (5), at the initial time turns into the given function υ z ( 0 ,r,z ) = ϕ ( r,z ) (in other words, the initial
4
υ, m/s
distribution), and satisfies the boundary condition υ z ( t,R,z ) = 0 at all times. If we need to provide predetermined velocity values υ z ( t,r,0 ) and υ z ( t,r,L ) at the pipe inlet and outlet respectively,
3
then the f ( t,z ) function will be determined, based on these
2
requirements, during the solution process. However, for simplicity, in this paper we will assume, that the function f ( t,z ) is given, and,
1
hence, we may omit the conditions at the pipe edges.
0
0
500
1000
1500
3. The solution
2000
2500
3000
3500
t, s
Fig. 1. Liquid velocity dependence on time at different distances from the pipe axis
The equation (5) is a non-homogeneous heat equation with variable coefficients. If we reduce all the relations to dimensionless form, we will obtain the following equation: ∂u ∂ 2u 1 ∂u = + + a (τ ) u + γ (τ , χ ) , ( 5′) ∂τ ∂η 2 η ∂η 1 dρ where τ ∈ 0,T , η ∈ [ 0,N ] , a (τ ) = . This equation is ρ (τ ) dτ
6 t=0 t=1800
5 4
υ, m/s
more convenient to solve, because there is only one variable coefficient. We assume that the density is weakly changing with time. We divide the time period 0,T in h small intervals, so that we may
3 2
consider the density and hence the a (τ ) coefficient to be constant over each interval. Then we get h equations of the form ( 5′ ), the solution of each of which has the form: u i (τ ,η , χ ) =
1 0
τ N N ( 6) e aiτ ∫ G1 (τ ,ξ ,η )ψ i (ξ , χ ) dξ + ∫ ∫ G2 (τ − s,ξ ,η ) γ i ( s, χ ) dξ ds , i 0 0 τ min
8
0
0.1
0.3
0.2
0.4
0.5
r, m
Fig. 2. Liquid velocity dependence on radial coordinate at different moments of time
It is interesting to see, how much effect does the variable density have on flow velocity. To do this we plot υ z ( t,0 ) , one for
weakly changing in time, and non-stationarity is dictated by the boundary conditions at the ends of the pipeline. The numericallyanalytical solution, described with equation (6), was obtained. Comparison of the solution obtained with a solution for the case of constant density (fig.3) allows us to say, that if the liquid density is weakly changing in time, it has no significant effect on the motion velocity. These results will allow, in perspective, to solve the problem of optimizing the control of viscous weakly compressible liquids flows through the pipeline systems.
kg , and the second one for the density, varying m3 according to the equation (7) (fig.3).
the ρ = 830
6
ρ=const ρ=ρ(t)
5
5. References
υ, m/s
4
[1] Sorokina N. The solution of the problem of one-parameter perturbation of the viscous incompressible liquid motion through straight round pipe/ Sorokina N// Machines. Technologies. Materials. – 2016. – Issue 4/2016. – P.20-22
3 2
[2] Davidson V.E. Fundamentals of fluid dynamics in examples^ Tutorial for high school students. – M.: Izdat.. centr. «Akademiya», 2008. – 320 p.
1 0
0
500
1000
1500
2000
2500
3000
[3] Vallander, S.V. Lectures on hydroaeromechanics. – L.: Izd-vo Leningr. un-ta, 1973, 296 p. (in Russian)
3500
t, s
[4] Sorokina N., Firsov A. The problem of viscous incompressible liquid motion through the cylindrical round pipe with non-stationary boundary conditions. In. III international scientific and technical conference “Technics. Technologies. Education. Safety”: Proceedings, Vol.2. Veliko Tarnovo, Bulgaria, 28-29 May 2015, P.9-10 (in Russian)
Fig. 3. Flow velocity dependence on time at the pipe axis
4. Conclusion In this paper the problem of a viscous weakly compressible liquid motion through the horizontal pipe of circular cross-section with non-stationary boundary conditions is solved. The density is
[5] Physical quantities: Handbook / I.S. Grigoriev, E.Z. Meilikh. – M.: Energoatomizdat, 1991. – 1232 p. (in Russian)
9
NUMERICAL-ANALYTICAL METHOD FOR SOLVING THE INVERSE PROBLEM OF STABILITY FOR TECHNICAL SYSTEMS WITH MULTIPLE UNCERTAIN PARAMETERS
ЧИСЛЕННО-АНАЛИТИЧЕСКИЙ МЕТОД РЕШЕНИЯ ОБРАТНОЙ ЗАДАЧИ УСТОЙЧИВОСТИ ДЛЯ ТЕХНИЧЕСКИХ СИСТЕМ С НЕСКОЛЬКИМИ НЕОПРЕДЕЛЕННЫМИ ПАРАМЕТРАМИ Postgraduate Bulkina E.1, Prof., Dr. Tech. Sci. Firsov A.2 Peter the Great St.Petersburg Polytechnic University – St.Petersburg, Russia E-mail:
[email protected],
[email protected] Аспирант Булкина Е.А. 1, Проф., д.т.н. Фирсов А.Н.2 Санкт-Петербургский Политехнический Университет Петра Великого E-mail: 1bulkina.e.a @gmail.com,
[email protected] Abstract: The paper considers the problem of determining the boundaries of possible changes of parameters of dynamic system whilst preserving stability of the system. The proposed method for determining such bounders is based on the research on the perturbation theory of matrix eigenvalues which depend on several perturbation parameters (by Ji-guang Sun). The results of this paper are based on the results presented by the authors at III TTOS Conference in May 2015. KEYWORDS: TECHNICAL SYSTEMS WITH UNCERTAIN PARAMETERS, INVERSE PROBLEM OF STABILITY, NUMERICAL ALGORITHM
Though an n-dimentional cube Q with the center coinciding with the center of the n-dimentional sphere can be placed into the sphere. Thus the edges of the cube are parallel to the coordinate axes. The next statement is based on this fact. Lemma 1. Let (−ε i , ε i ), ε i > 0 is the interval, for which all
1. Introduction One of the main concerns of analysis of properties of dynamic system (technical, economic, biological, etc.), or design of such systems is an appraisal of the conditions for the preservation of the properties of the system when small changes to the system parameters occur. In particular, this information is important in assessing the degree of maintainability of the system when changes to various structural components of the system occur. Due to the complexity and sometimes impossibility to provide the necessary and sufficient allowable ranges of the respective parameters, presentation of at least a sufficient assessment can be of great interest. On the other hand, experience shows that availability of universal theoretical results, as a rule, leads to great difficulties in applying these results to solve specific problems. We believe that such considerations should be taken into account when preparing theoretical structures to address specific practical problems. However, this line of thought does not exclude the use of formal logic as the basis of the arguments, which relate to the application of mathematical methods and designs. Suppose that the preservation of a system’s property (properties) ), which we are interested to preserve, is determined by the requirement of fulfilling the following m conditions with respect to n parameters {ε j }, j = 1, 2,..., n , associated with this system: f i (ε1 , ε 2 ,..., ε n ) < 0, i = 1, 2,..., m .
points ε are the solutions of the inequality f i (ε , ε ,..., ε ) < − δ 2 . Then n- dimentional cube m Q= {(ε1 , ε 2 ,..., ε n ) : ε j ∈ (−ε , ε = ) (−ε i , ε i ); = j 1, 2,..., n} is i =1
the one of the solutions of the system of inequalities (3). This lemma allows us to propose the following method (seethe Section 2 below) to solve the problem of sufficient conditions for the preservation of stability of a linear dynamic system stability properties when possible (previously unknown, and in particular, random) changes to its parameters occur. The need for such evaluation may be a critical issue, for example, in a situation of replacement of certain structural elements of the technical system during its repair: when the ranges of values for the components being substituted and the ones that are used as substitution are always not known precisely.
2. Preserving stability of a linear dynamic system with uncertain perturbations of its parameters
(1)
Assuming, that each function f i (ε1 , ε 2 ,..., ε n ) is continuous (as will be seen below, it can even be considered as continuously differentiable) in the relevant field Ωi ⊂ R n , and m (2) 0 ∈ Ωi , 0 ≡ (0,0,...,0) ∈ R n .
So, let’s assume that a dynamic system is given by the following system of differential equations: dZ (t ) = AZ (t ), dt (4) = A (= aij )in, j =1 , Z (t ) ( z1 (t ), z2 (t ),..., zn (t ))T .
in the point 0 the inequality
λ j , j = 1, 2,..., n are different and their real part is negative. In this
i =1
Also suppose that for all f i
f i (0) ≤ −δ exist for δ > 0 .
With A is a known constant matrix and all its eigenvalues
case, as it is know, the system (4) is stable. However, if the matrix A is replaced with matrix A =+ A E, E = (ε ij )in, j =1 , where ε ij are
Thus there is an n-dimensional sphere Dρ of some non-zero radius ρ centered at 0 for all points of which the inequality listed below is fulfilled: (3) f i (ε1 , ε 2 ,..., ε n ) < − δ 2 , i = 1, 2,..., m .
unknown «perturbations» of the elements of the original matrix, then the question of the stability of a "perturbed" system dZ (t ) = AZ (t ) becomes relevant, and can be resolved on the basis dt
10
of Lemma 1. In this case you must first prove that the eigenvalues of matrix A= A + E are sufficiently λk ( E ) ≡ λk (ε ij ), k = 1, 2,..., n
matrix X T AX is symmetrical by the symmetry of the matrix A , the expression (8) takes the following form: 01×( n −1) λi X T AX = (9) , A2i 0( n −1)×1
smooth functions of the parameters ε ij , i, j = 1, 2, ..., n in the vicinity of zero. For the case of a single disturbance parameter, this problem was solved in the second half of the XXth century, primarily in the works of T. Kato (see, for example, [1]). For the case of several disturbance parameters, the problem was much tougher, and substantive results were achieved mainly in the works of Ji-guang Sun [2, 3, 4]. It is these last results, that we will use hereinafter. Lemma 2. [2, 3, 4]. Let p ∈ C N , A( p ) ∈ C n× n be a real analytic function of p in some vicinity of U (0) of the origin, and A(0) is symmetrical. Suppose that λi is a simple eigenvalue of A(0) , and xi is associated eigenvectors satisfying the relations A(0) xi = λi xi , xiT A(0) = λi xiT . Then: 1) There exits a simple eigenvalue λi ( p ) of A( p ) , which is an analytic function of p in some vicinity U (0) of the origin, and λi (0) = λi ; 2) The eigenvector xi ( p ) of matrix A( p ) corresponding to the eigenvalue may be defined to be analytic function of p inside U (0) , and xi (0) = xi . The proof of this lemma uses the fact that there is a matrix X 2i ∈ C n×( n −1) such that the matrix X = ( xi , X 2i ) is not singular and satisfies the following equations 01×( n −1) λi (5) X T X = I n , X T A(0) X = A2i 0 ( n −1)×1
q.e.d.. We have the following fundamental result: Theorem (Ji-g. Sun, [3, 4, 5]). Let’s suppose that λi is a simple eigenvalue of A(0) , and xi is associated to its eigenvectors T that satisfy xi = 1 . Let ε ≡ ( ε11 ,..., ε1n ,..., ε n1 ,..., ε nn ) , and n . A= (ε ) A(0) + E , where the matrix "perturbation" is E = ( ε ij ) i , j =1 Then matrix A(ε ) corresponding to the conditions of Lemma 2 and the following statement is true: 3 λi (ε ) = λi + xiT Exi + xiT EX 2i (λi I − A2i ) −1 X 2Ti Exi + O( E ) , (10) where matrix X 2i is defined early. This result allows us to apply in this situation the argument listed in the Section 1 of this paper, i.e. take the first three terms on the right side of the formula (10) of this work, as a function f i (ε ) . We demonstrate the application of the methodology described above in the example shown in the Section 3 of this paper.
3. A numerical example Let matrix A(0) take the form
1 0 -1,27 0,25 0,25 -3,16 0 1,1 , A(0) = 1 0 −2,6 1 1,1 1 −6, 2 0
Where I n is the identity matrix of size n × n , and A2i - is the identity matrix of size (n − 1) × (n − 1) .
We recall that in this paper we can consider A(0) a symmetric matrix. Below is a variant of constructing of the corresponding matrix X . It is easy to show that for X we can take the matrix X = ( xi , X 2i ) , where xi a unit eigenvector of symmetric matrix A ∈ С n× n , corresponding to the eigenvalue λi , and the
(11)
and the "perturbation" matrix is 0 ε14 ε11 0 0 0 ε ε E = 21 22 ε 31 0 ε 33 0 0 0 ε 42 0 The vector of eigenvalues of matrix (11) equates to
λ = ( -6,7049 -3,0383 -2,7402 -0,6466 ) . All the eigenvalues
are vectors which are columns of the matrix X 2i ∈ C n×( n −1) orthogonal to vector xi and aren’t eigenvectors of matrix A.
T
are simple. The real part of the eigenvalues in the left part is a coordinate axis and, consequently, the unperturbed system (4) is stable.. Applying the method proposed above for estimating the value of perturbations of matrix А, during which the stability property of the perturbed matrix A(ε )= A + E is preserved. Here the appropriate algorithm is demonstrated on the example of the first eigenvalue λ1 = -6,7049 . The corresponding its eigenvector is T x1 = ( 0,0574 -0,2909 -0,2392 0,9246 ) . Matrix X 1 = ( x1 , X 21 ) :
Indeed, let’s take a closer look at the expression X T A : a11 a12 ... a1n ... a2 n a a T , (6) X T A = ( xi y1 ... yn −1 ) 21 22 ... ... ... ... an1 ... ... ann where aij ∈ R , xi is the eigenvector corresponding to eigenvalue λi , and vectors y= j 1,...,(n − 1) are the vectors, which are j , orthogonal to vector xi . Since the matrix A is symmetric, and xi is its eigenvectors, then the condition xiT A = λi x iT is true. Therefore, it is easy to see that the expression (6) will be as follows: λ xiT (7) XTA = i ∗ , A where λi xiT is a row vector, and A∗ ∈ C ( n −1)× n . Thus λi x iT X T AX = = ( xi y1 ... yn −1 ) ∗ A , (8) λ ⋅ ( x , x ), λ ⋅ ( x , y ),..., λi ⋅ ( xi , yn −1 ) = i i i i i ∗1 A2 Here ( x , y ) is a scalar product. Due to the fact that xi = 1 , ( xi , y j ) = 0 by virtue of the respective orthogonal vectors and the
0,0574 -0,2909 X1 = -0,2392 0,9246
1 0 0 0
0 1 0 0
0 0 1 0
(12)
Applying to the Gram-Schmidt orthogonalization to the matrix (12), we obtain for X1: 0 0 0.057 -0.998 -0.291 -0.017 0.957 0 X1 = -0.239 -0.014 -0.073 0.968 0.925 0.053 0.282 0.25 Now we can find the matrix X 1T A(0) X 1 :
11
Solving the system of inequalities {λi (ε ) < 0} , i = 1, 2,..., 4 , we
0 0 0 −6.7049 0 -1.252 -0.1664 -0.9697 , X T A(0) X = 0 -0.1664 -2.8385 0.271 0 -0.9697 0.271 -2.3346
obtain a sufficient condition for preserving the stability of the perturbed system in the form of:
ε jk ∈ (− 6.995, 0.395),
j, k = 1, 2,3, 4
However, given that equation (10) suggests a relative
where the block of size 3x3 is the matrix A21 . It is now possible to use the formula (10) for drawing up the inequalities of the type (3). The following expression of the form (10) can be compiled for λ1 (ε ) : λ1 (ε ) = 0.00329ε11 + 0.0531ε14 − 0.0167ε 21 + 0.0846ε 22 −
3
2
smallness of the disturbance matrices E: E E , the interval of possible values of the parameters ε jk has to be specified, for example, such as ε jk ∈ ( − 0.05, 0.05), j , k = 1, 2,3, 4 .
−0.0137ε 31 − 0.269ε 42 + 0.0572ε 33 − 0.01ε11ε14 +
4. Conclusion
+0.0137ε11ε 21 − 0.00006ε11ε 22 + 0.0509ε14ε 21 +
The paper presents and substantiates the method for estimating acceptable ranges of small perturbations of several parameters of a dynamic system, which ensure the preservation of stability of the system.
+0.0419ε14ε 31 − 0.0076ε14ε 33 − 0.0006ε 21ε 31 − −0.0002ε11ε 42 − 0.0004ε 22ε 31 + 0.0022ε 21ε 33 + +0.0045ε 22ε 33 + 0.0021ε14ε 42 − 0.0107ε 21ε 42 + +0.0583ε 22ε 42 + 0.0052ε 31ε 33 + 0.0032ε 31ε 42 −
5. References
2 −0.0107ε 33ε 42 − 0.0006ε112 + 0.0011ε142 − 0.00003ε 21 − 2 2 −0.0201ε 22 − 0.00051ε 312 − 0.0129ε 332 + 0.0178ε 42
1. Kato T. A Short Introduction to Perturbation Theory for Linear Operators, N.-Y.: Springer-Verlag, 1982 2. Sun Ji-guang. Eigenvalues and eigenvectors of a matrix dependent on several parameters. J. Comput. Math., 3, 351-364 (1985) 3. Sun Ji-guang. Sensitivity analysis of multiple eigenvalues (I). J. Comput. Math., 6, 28-38 (1988) 4. Sun Ji-guang. Sensitivity analysis of multiple eigenvalues (II). J. Comput. Math., 6, 131-141 (1988) 5. Horn R., Johnson C.R. Matrix analysis.- 2nd ed., Cambridge Univ. Press, 2013
The next step based on Lemma 1 is replacing all ε ij to ε :
λ1 (ε ) = 0,1226ε 2 − 0,1012ε − 6,7049 . Doing the same for the rest of the eigenvalues, we obtain the following equations: λ2 (ε ) = −0, 2333ε 2 + 0, 9831ε − 3,0383,
λ3 (ε ) = −0,1254ε 2 + 0, 4785ε − 2,7401, λ4 (ε ) = −0,0146ε 2 + 1, 6395ε − 2,7401.
12
ПОДХОД ЗА УПРАВЛЕНИЕ И ДИАГНОСТИКА НА ПРОИЗВОДСТВЕНА СТАНЦИЯ FESTO MPS PROCESSING – ЧАСТ I APPROACH FOR CONTROL AND DIAGNOSTIC OF STATION FESTO MPS PROCESSING – PART I Христо Карамишев, Георги Попов Технически Университет – София, МТФ, България
[email protected],
[email protected]
Abstract: Using the IEC 61499 standard permits the development of a system for control, diagnostics and reconfiguration of industrial systems. In this paper we present an approach for control and diagnostics of Drill Module on Station Festo MPS Processing. Keywords: IEC 61499 Standard, Control, Diagnostic, Function Block
1. Увод
Станцията се състои от следните основни модули: 1. Делителна шестпозиционна въртяща се маса – четири от позициите са работни (A÷D) и две свободни (E, F);
Управлението на индустриалните системи чрез програмируеми контролери все още се изпълнява основно на езиците, дефинирани в стандарта IEC 61131-3 [1], които са подходящи за системи с един процесор или малки конфигурации [2]. За по-големи конфигурации, както и за такива с разпределени функционалности, е подходящо използването на новия стандарт IEC 61499 [3]. Чрез референтните модели, дефинирани в стандарта, могат да се проектират разпределени системи за управление [3, 4, 5].
2. Тестващ модул, предназначен за проверка на отвора на детайла; 3. Обработващ модул – симулира механично обработване на детайла; 4. Фиксиращ модул – за фиксиране на детайла в обработващата позиция С;
Целта на доклада е да представи начален етап в разработката на комплексна система за управление, диагностика и реконфигуриране на индустриална система.
5. Модул за преместване на обработения детайл. Позициите на станцията са: Поз. A – Първа (входна) позиция на масата. В позицията е монтиран сензор PART_AV, отчитащ наличие на постъпил нов детайл върху станцията.
2. Производствена станция Festo MPS Processing
Поз. B – Втора (контролна) позиция. Тук освен тестващия модул е монтиран и сензор B1, регистриращ постъпил детайл в позицията.
Производствената станция на FESTO (фиг.1) може да се включи в различни конфигурации индустриални системи за сортиране, механично обработване на фамилия детайли и т.н.
Поз. C – Трета (обработваща) позиция. Наличните компоненти са обработващ модул/пробивна глава, фиксиращ модул и сензор за постъпил детайл B2. Поз. D - Четвърта (изходна) позиция на масата. Монтиран е изтласкващ модул за преместване на готовия детайл върху следващата станция. Поз. E – Пета позиция е свободна. Поз. F – Шеста позиция. Монтиран е сензор B3 за точно позициониране на делителната маса. Б) Пробивен модул на станцията Пробивният модул, даден на фиг. 2, изпълнява следните функции:
Фиг. 1: Производствена станция Festo MPS Processing A) Устройство на станцията Festo MPS Processing
13
•
Механично обработване на детайла, чрез пробивната глава;
•
Линейно вертикално преместване на пробивната глава с две крайни позиции – горно изходно положение и долно положение при обработен детайл.
• DRILL_UNIT_in_LowerPos - пробивната глава е в крайно долно положение (сензор 1В2); • DRILL_UNIT_in_UpperPos - достигане на пробивната глава в изходно горно положение (сензор 1В1); • DRILL_UNIT_MAIN_FAULT - неизправност в задвижването на главния превод и • DRILL_UNIT_FEED_FAULT - неизправност в задвижването на подавателния превод. Изходните събития на блока са: • INITO - потвърждение за инициализацията на ФБ; • FIX_DET - фиксиране/затягане на детайла; • RUN_SPINDLE - включване на главното движение на рязане;
Фиг. 2: Обработващ (пробивен) модул [6] Пробивният модул е съставен от следните компоненти: 1.
Режещ инструмент, изпълняващ главното движение на рязане;
2.
Пробивна глава, осигуряваща главното движение;
3.
Изключвател за крайно горно положение на пробивната глава;
4.
Елементи от вертикалната линейна ос за подавателното движение на инструмента;
5.
Изключвател за крайно горно положение на пробивната глава;
6.
Постояннотоков електромотор за задвижване на линейната ос.
• RUN_DRILL_UNIT_DOWN - включване на подавателното движение за преместване на пробивната глава към детайла за извършване на обработването; • RUN_DRILL_UNIT_UP - включване на подавателното движение за преместване на пробивната глава в изходно горно положение; • DET_DONE - детайлът е обработен; • STOP_SPINDLE - спиране на главното движение на рязане; • FAULT_M_DRIVE - генерира се при настъпване на грешка/неизправност в задвижването на главния превод; • FAULT_F_DRIVE - генерира се при настъпване на неизправност в задвижването на подавателния превод.
3. IEC 61499-базирано управление и диагностика на пробивния модул на станция Festo MPS Processing За управление и диагностика на пробивния модул на производствената станция са разработени модели на IEC 61499-базирани функционални блокове. А) IEC 61499-базиран функционален блок за управление с диагностични функции на пробивния модул на производствена станция Festo MPS Processing
Фиг.4: Граф за изпълнение на управлението на ФБ „FESTO_DRILL_UNIT_CTRL“
Интерфейсът на функционалния блок за управление с диагностични функции на пробивния модул „FESTO_DRILL_UNIT_CTRL“ е представен на фиг. 3.
На фиг. 4 е даден графа за изпълнение на управлението (ГИУ) на основен ФБ за управление на пробивния модул. При постъпване на детайла в обработващата позиция, сензор В2 създава сигнал, представляващ входно събитие DET_in_DRILL_POS. Активира се състоянието DET_Arrived_in_DrillPos и се генерират последователно събитията: FIX_DET, RUN_SPINDLE и RUN_DRILL_ UNIT_DOWN. При достигане на пробивната глава в крайно долно положение, сензор 1В2 изключва подавателното движение и настъпва входното събитие DRILL_UNIT_in_LowerPos. Активира се състояние DET_DRILLED и се генерира изходно събитие RUN_DRILL_UNIT_UP за връщане на пробивната глава в изходно горно положение. При достигането му, сензор 1В1 изключва подавателното движение. Настъпва входното събитие DRILL_UNIT_ in_UpperPos. Активира се състояние DRILL_UNIT_HOME и се генерират събитията DET_DONE и STOP_SPINDLE. При настъпване на входното събитие DRILL_UNIT_MAIN_FAULT се активира състоянието FAULT_MAIN_UNIT и се генерира изходното събитие FAULT_M_DRIVE. При настъпване на събитието DRILL_UNIT_FEED_FAULT се активира състоянието
Фиг.3: Интерфейс на ФБ „FESTO_DRILL_UNIT_CTRL“ Функционалният блок се активира при настъпване на входните събития: • INIT - инициализация на ФБ; • DET_in_DRILL_POS - постъпване на детайл в обработващата позиция (поз. С).
14
FAULT_FEED_DRIVE и се генерира изходното събитие FAULT_F_DRIVE.
• WP_is_unfix - детайла не е фиксиран в работната позиция (поз. С);
В табл. 1 е представена симулацията на блока. При натискане на софтуерен бутон съответстващ на входно събитие се активира свързаното с него изходно събитие.
• WP_is_fix - детайла е фиксиран в работната позиция; • WP_not_worked - пробивния модул не е обработил детайла;
Табл.1: Симулация на ФБ „FESTO_DRILL_UNIT_CTRL” Входно събитие
Фигура
DET_in_ DRILL_ POS
• Drill_Unit_unreached_UppPos - пробивната глава не е достигнала изходно горно положение;
Изходно събитие
• Drill_Unit_unreached_EndPos - пробивната глава не е достигнала крайно долно положение.
- FIX_DET, RUN_SPIND LE и RUN_ DRILL_ UNIT_ DOWN
Изходните събития на блока са: • Fault_IndexingTable - неизправност в делителната маса; • Fault_Fix_Unit - неизправност в фиксиращия механизъм; • Fault_Main_Drive - неизправност в главния превод;
DRILL_ UNIT_in _Lower Pos
RUN_ DRILL_ UNIT_UP
DRILL_ UNIT_ in_Upper Pos
DET_DONE, STOP_ SPINDLE
DRILL_ UNIT_ MAIN_ FAULT
FAULT_ M_ DRIVE
DRILL_ UNIT_ FEED_ FAULT
• Fault_Feed_Drive - неизправност в подавателния превод.
Фиг.6: Граф за изпълнение на управлението на ФБ „FESTO_DrillUnit_Diag“ На фиг. 6 е показан ГИУ на ФБ за диагностика на пробивния модул на производствената станция на Фесто. При липса на детайл в поз. С се активира входното събитие Lack_WP, настъпва състоянието Det_not_arrived и се генерира изходното събитие Fault_IndexingTable, отчитащ неизправност в делителната маса на станцията. При неизправност във фиксиращия механизъм настъпват входните събития WP_is_unfix или WP_is_fix, като се активират съответно състоянията Det_is_unfixed или Det_is_fixed и се генерира изходното събитие Fault_Fix_Unit. При необработен детайл в поз. С (пробивната глава не е достигнала крайно долно положение, съответно сензор 1В2) се активира входно събитие WP_not_worked, случва се състоянието WP_is_not_processed и се генерира изходно събитие Fault_Main_Drive, регистриращо неизправност в главния превод. При неизправност в подавателния превод се генерира изходното събитие Fault_Feed_Drive, което настъпва при недостигане на пробивната глава в горно или долно положение, съответно се активират входни събития на Drill_Unit_unreached_UppPos или Drill_Unit_unreached_ EndPos.
FAULT_ F_ DRIVE
Б) IEC 61499-базиран функционален блок за диагностика на пробивния модул на производствената станция
Фиг.5: Интерфейс на ФБ „FESTO_DrillUnit_Diag“ Интерфейсът на ФБ „FESTO_DrillUnit_Diag“ е представен на фиг. 5. Входните събития на диагностичния ФБ са: • Lack_WP - липсва детайл в поз. С;
15
Табл.5: Симулация на ФБ „FESTO_DrillUnit_Diag” Входно събитие
Фигура
Изходно събитие
Lack_ WP
Fault_ IndexingTable
WP_is_ unfix
Fault_Fix_ Unit
WP_is_ fix
Fault_Fix_ Unit
Фиг.7: IEC 61499-приложение за управление и диагностика на пробивния модул Входовете и изходите съответстват на тези на включените блокове. Изводите на приложението представят информационни връзки (за данни) и събитийни връзки. Подприложенията представляват екземпляри от тип подприложение, които подобно на приложенията се състоят от мрежа от ФБ. Наименованията на приложенията, подприложенията и на екземплярите на ФБ могат да се използват за създаване на йерархия от идентификатори, които да могат да идентифицират всеки екземпляр на ФБ в една система. Едно приложение може да бъде разпределено между няколко ресурса в същото или друго устройство.
4. Заключение WP_not_ worked
Fault_Main_ Drive
Drill_ Unit_un reached_ UppPos
Fault_Feed_ Drive
Drill_ Unit_un reached_ EndPos
В софтуерната средата fbdk са разработени модели на IEC 61499-базирани основни функционални блокове за управление и диагностика на пробивния модул на производствената станция Festo MPS Processing. Изпълнена е симулация на функционалните блокове, за проверка на работата им. Създадените модели са свързани в приложение за управление и диагностика на пробивния модул. Това е първи етап при разработване на цялостна система за управление, диагностика и реконфигуриране на станцията.
5. Литература 1. Карамишев Хр., Г. Попов, И. Бачкова – Обзор на стандартите за индустриално управление IEC 61131 и IEC 61499, IX Международен Конгрес „Машини, Технологии, Материали“, 19-21 септември, 2012, Варна, стр. 142145.
Fault_Feed_ Drive
2. Lewis R, Modelling Control Systems using IEC 61499 – Applying function blocks to distributed systems, “The Institution of Electrical Engineers”, London, United Kingdom, 2001. 3. IEC 61499-1, Function Blocks for Industrial-Process Measurement and Control Systems – Part 1: Architecture, 2003.
В табл. 5 е дадена симулацията на функционалния блок „FESTO_DrillUnit_Diag“, която се изпълнява в средата на софтуерният инструмент fbdk [7].
4. Fisher, J., Th. Boucher, Workbook for Designing Distributed Control Applications using Rockwell Automation’s Holobloc Prototyping Software, Working Paper N 05-017.
В) IEC 61499-приложение за управление и диагностика на пробивния модул
5. Vyatkin V., “IEC 61499 Function blocks for embedded and distributed control systems design”, Second Edition, Aucland Universiry, New Zealand, pp. 260, 2012.
На фиг. 7 е представено приложението за управление и диагностика на пробивния модул на станцията Festo MPS Processing. Моделът на IEC 61499-базираното приложение се състои от свързани помежду си в логическа последователност в зависимост от логиката на управление ФБ.
6. Festo Didactic, http://www.festo-didactic.com 7. fbdk – Function www.holobloc.com.
16
Block
Development
Kit,
Online:
CONSTRAINED SIMILARITY OF 2-D TRAJECTORIES BY MINIMIZING THE H1 SEMI-NORM OF THE TRAJECTORY DIFFERENCE PhD Student Filipov S., Assoc. Prof. Atanassov A., Senior Lecturer Gospodinov I. Department of Computer Science – University of Chemical Technology and Metallurgy, Bulgaria
[email protected] Abstract: This paper defines constrained functional similarity between 2-D trajectories via minimizing the H1 semi-norm of the difference between the trajectories. An exact general solution is obtained for the case wherein the components of the trajectories are meshfunctions defined on a uniform mesh and the imposed constraints are linear. Various examples are presented, one of which features application to mechanics and two-point boundary value problems. A MATLAB code is given for the solution of one of the examples. The code could easily be adjusted to other cases. Keywords: SIMILARITY OF TRAJECTORIES, H1 SEMI-NORM MINIMIZATION In order to use the formulas derived in [3] we denote xi=ui, yi=uN+i, x*i=u*i, and y*i=u*N+i, for i=1,2,…,N and introduce the two vectors u=[x1,…,xN, y1,…,yN]T and u*=[x*1,…,x*N,y*1,…,y*N]T. The minimum of I is sought subject to M linear constraints:
1. Introduction Suppose a trajectory is given and a new trajectory is sought that meets a number of imposed constraints and is as similar in behaviour to the original trajectory as possible without necessarily being close [1] to it. Such shape optimisation problems may have wide range of applications in many engineering fields [2] such as mechanics, fluid mechanics, aerodynamics, general transport phenomena, design and engineering of machines and equipment, etc. In [3] the authors have introduced constrained functional similarity between real-valued functions of one real variable via minimizing the H1 semi-norm [4] of the difference between the functions. An exact general solution for mesh-functions has been presented. The similarity of trajectories in two and more dimensions is as important. This work defines constrained similarity between 2D trajectories and provides an exact solution to the discretized case. Application to mechanics and two-point boundary value problems [5] is presented the Results section.
2N
∑A i =1
A11 A 21 A= . AM 1
2
b
∫
a
f (t ) x * (t )dt = 1 or
∫
b
a
i =1
(4)
(5)
M ∂J = −2((u *2 −u *1 ) − (u 2 − u1 )) − ∑ λ j A j1 = 0 ∂u *1 j =1 M ∂J = 2((u * N −u * N −1 ) − (u N − u N −1 )) − ∑ λ j A jN = 0 ∂u * N j =1
(6)
M ∂J = −2((u * N + 2 −u * N +1 ) − (u N + 2 − u N +1 )) − ∑ λ j A j ( N +1) = 0 ∂u * N +1 j =1
M ∂J = 2((u *2 N −u *2 N −1 ) − (u 2 N − u 2 N −1 )) − ∑ λ j A j ( 2 N ) = 0 ∂u *2 N j =1
Partitioning the interval t∈[a,b] by N mesh points into N−1 intervals of equal size defines a uniform mesh on the interval: {ti=a+(i−1)h, i=1,2,…,N, h=(b−a)/(N−1)}, where h is the step-size of the mesh. Let the trajectory r be defined on the mesh, i.e. {ri =r(ti), i=1,2,…,N}. In order to define constrained similarity between the trajectories r* and r expression (1) is discretized using the forward finite differences (x*i+1−x*i)/h, etc. for the respective derivatives dx*/dt, etc. at ti, i =1,2,…,N−1 and the integral is replaced by a sum. The constant h is omitted because constant factors do not affect the minimization. Thus, the following objective function is obtained:
i =1
. A1( 2 N ) c1 c . A2 ( 2 N ) , c= 2 . . . . AM ( 2 N ) c M
k = 2,.., N − 1, N + 2,..,2 N − 1
3. Exact solution for discretized trajectories under linear constraints
N −1
. . . .
M ∂J = 2((u *k −u *k −1 ) − (u k − u k −1 )) − 2((u *k +1 −u *k ) − (u k +1 − u k )) − ∑ λ j A jk = 0, ∂u *k j =1
2
g (t ) y * (t )dt = 1 , etc.
N −1
AM 2
. . . .
is introduced, where λj, j=1,2,…,M are the Lagrange’s undetermined coefficients. Then, the derivatives of J with respect to u*k, k=1,2,…,2N are equated to zero:
and at the same time satisfies the constrains in question. The constraints that r* satisfies must be linear in x* and y*. For example, linear combinations of functional values x*(ti) and y*(ti) at certain points ti, integral constraints like b
A12 A22 .
M 2N J = I + ∑ λ j (c j − ∑ A ji u *i ) j =1 i =1
2 (1) dy * dy dx * dx dr * dr r * −r H = ∫ − dt − dt + ∫ − dt = ∫ 1 dt dt dt dt dt dt a a a b
(3)
and u* is the 2N×1 column-vector of the unknowns. To find the minimum of I subject to constraints (3) the Lagrange’s method of the undetermined coefficients [6] is used. First, the Lagrangian
Let r*(t)=(x*(t),y*(t)) and r(t)=(x(t),y(t)) be two radius vectors whose components are real-valued functions of a real independent variable t∈[a,b]. The functions r* and r define two 2-D trajectories. The trajectory r* will be similar to r, under certain given constraints, if r* minimizes the square of the H1 semi-norm of the difference r*−r: 2
j = 1,2,..., M < 2 N .
u *i = c j ,
The constraints (3) can be written in a matrix form as Au*=c, where
2. Constrained similarity of 2-D trajectories
b
ji
The system of equations (6) is rearranged so that only terms containing u*i remain on the left-hand side. Then, the system is written in a matrix form as: L u* = L u −
1 T A λ, 2
(7)
where λ is the M×1 column-vector of the undetermined coefficients and L is the following 2N×2N matrix:
I = ∑ (( x *i +1 − x *i ) − ( xi +1 − xi )) 2 + ∑ (( y *i +1 − y *i ) − ( yi +1 − yi )) 2 (2)
17
− 1 1 0 1 1 −2 0 1 −2 0 . . 0 . . L= . . 0 0 . . . . 0 . . 0 . . 0
0
.
.
.
.
.
.
.
.
.
0 1 .
. . . .
. .
. .
. .
. .
. .
. .
. . .
. . . .
. .
. .
. .
. .
. .
0 0 1 .
. . . .
. . . 1 −2 1 0 1 −1
. .
. .
. . . .
. . . .
. . .
. . .
.
. . . .
. . .
. .
. .
−1 1 0 1 −2 1 0 1 −2
. . .
0 0 0 . . . . . 0 . . 0 . . 0 . . 0 . . 0 . . . 1 − 2 1 0 1 − 1
. . .
. .
. .
. .
. .
. .
.
.
. .
. .
Example 2 Consider the trajectory r defined by {ri =(xi,yi), xi= ti−2sin(ti), yi=1−2cos(ti), i=1,2,…,N } on a uniform mesh with a=−π, b=3π, and N=101. The trajectory r* similar to r and satisfying the following boundary constraints ( x *1 , y *1 ) = ( x1 , y1 ) + (∆x1 , ∆y1 ),
( x *N , y *N ) = ( x N , y N ) + (∆x N , ∆y N )
is found for several values of (∆x1, ∆y1) and (∆xN, ∆yN) (see fig.2). 6
6
r*
5
y3 2
In order to remove the singularity of L at least one of the equations for the constraints needs to be added to one of the first N equations in (7) and at least one of the equations for the constraints needs to be added to one of the second N equations in (7). For this reason a 2N×2N matrix A is introduced whose first row is any row of the matrix A (say row j) that corresponds to an x-constraint and whose row N+1 is any row of the matrix A (say row m) that corresponds to a y-constraint. The rest of the elements of A are zeros. A 2N×1 column-vector c with only non-zero components c (1) = c( j ) and c ( N + 1) = c(m) is also introduced. If necessary, more equations from A can be included in A . Now, the results for u* and λ, derived in [3], can be used:
−1
i
i =1
i =1
i
+ ∆S x ,
∑ y* = ∑ y i
i =1
i =1
i
y3 2
1
r
1
y
r*
1
-1 -1
0
0.5
1
1.5
-1 -1
(c)
(d) 0
4
8
N
N
∑x* = ∑x i
i =1
0
0.5
x
x
(a)
(b)
12
16
20
24
28
32
36
40
i =1
N
1
1.5
-1 -1
N
i
i
i =1
i
i =1
N
N
i =1
i
i
i =1
i =1
i
N
i
− a)(t i − b) y *i = ∑ (t i − a )(t i − b) yi + ∆Ty , i =1
x *1 − x * N = 0, y *1 − y *N = 0
(13)
is found for several values of ∆Ty (see fig.3). 1
1
1
r
r
0
0
0
y -1
y -1
y -1
-2
-2 -1
-0.5
0
(a)
0.5
1
1.5
r*
r*
r*
r
-1.5
-2 -1
-0.5
0
0.5
1
1.5
-1.5
-1
-0.5
0
x
x
(b)
(c)
0.5
1
1.5
Fig.3. The original trajectory r and the similar to it trajectory r* satisfying constraints (13) for (a) ∆Ty=0; (b) ∆Ty=50; and (c) ∆Ty=100.
r* r
-0.5
N
∑ y* = ∑ y ,
+ 10,
i
∑ t x * = ∑ t x , ∑ (t
Example 4 A mass point, initially at rest, travels 2 seconds under the influence of the gravitational potential U=gy, g=9.8 (m/s2). Placing the origin of the coordinate system at the initial position of the point and partitioning the time interval t∈[0,2] by N=11 equally separated mesh-points the following discretized trajectory r is obtained: {ri=(xi,yi), xi=0, yi=−gti2/2, ti=(i−1)h, i=1,2,…,N, h=0.2 (s)}. The trajectory r* similar to r and satisfying the following boundary constraints:
-0.5 -0.5
(b)
12
Example 3 Consider the trajectory r defined by {ri=(xi,yi), xi=sin(2ti), yi=(1−sin(ti))sin(ti), i=1,2,…,N} on a uniform mesh with a=0, b=2π, and N=101. The trajectory r* similar to r and satisfying the following four integral and two difference constraints:
0
-0.5
-0.5
(a)
8
Fig.2. The original trajectory r and the similar to it trajectory r* satisfying constraints (12) for (a) (∆x1, ∆y1)=(1,3), (∆xN, ∆yN)=(1,3); (b) (∆x1, ∆y1)=(5,3), (∆xN, ∆yN)=(−1,3) ; (c) (∆x1, ∆y1)=(1,1), (∆xN, ∆yN)=(−9,3); and (d) (∆x1, ∆y1)=(0,3), (∆xN, ∆yN)=(30,3).
(10)
y 0
-0.5
x
x
0.5
y 0
4
x
x
0.5
0.5
0
x
0
-1.5
1.5
r
-1 -4
12
r
-1 -4
+ ∆S y , x *k − x * N −k +1 = 0 (11)
1.5
r*
8
4
0
1
is found for several values of ∆Sx, ∆Sy, and k (see fig.1). 1.5
0
-1 -4
12
4
Example 1 Consider the trajectory r defined by {ri=(xi,yi), xi=sin(2ti), yi=sin(3ti), i=1,2,…,N} on a uniform mesh with boundaries a=0, b=π, and number of mesh-points N=101. Using (9) and (10), the trajectory r*, i.e. {r*i=(x*i,y*i), i=1,2,…,N}, similar to r and satisfying the following two integral and one difference constraints
∑x* = ∑x
8
4
r*
5
In this paragraph several examples are presented with three types of constraints: boundary, difference, and integral constraints. The last example describes an application to mechanics and twopoint boundary value problems. In addition, at the end of the paragraph, a MATLAB code for the solution of one of the examples is given in the Appendix. The code could easily be adjusted to other cases.
N
0
6
4. Results
N
1
0
0
r
2
1
-1 -4
where L is defined in (8) . The right-hand side of (10) contains only known quantities. Once the column vector λ is calculated it is substituted into (9) and the sought u*i, i=1,2,…,2N are found.
N
y3
r
2
(9)
λ = 2(A( L + A ) −1 AT ) (Au − c − A( L + A ) −1 ( A u − c ) ) ,
N
4
y3
r
r*
5
4
4
(8)
6
r*
5
1
1 u* = u − ( L + A ) −1 AT λ + A u − c , 2
(12)
0
0.5
1
1.5
x
(c)
Fig.1. The original trajectory r and the similar to it trajectory r* satisfying constraints (11) for (a) ∆Sx=50, ∆Sy=30, k=1; (b) ∆Sx=50, ∆Sy=0, k=4; and (c) ∆Sx=0, ∆Sy=30, k=7.
18
( x *1 , y *1 ) = (0,0), ( x * N , y * N ) = ( xb , yb ),
A(1,i)=1; A(2,N+i)=1; A(3,i)=t(i); A(4,N+i)=(t(i)-a)*(t(i)-b); end
(14)
is found for several values of (xb,yb) (see fig.4). The obtained trajectory r* describes exactly the motion of a point travelling for 2 seconds between points (0,0) and (xb,yb) under the influence of the given potential. If the force field is not homogenous the trajectory r* will describe the motion of the point only approximately. Then, however, r* could be incorporated into a ‘shooting-projection’ iterative procedure to obtain the exact solution to the two-point boundary value problem [5].
10
10
10
5
5
5
0
0
0
y-5
r*
-10
r*
-10
r
-15 -20 -5
y-5
0
5
10 15 20 25
c(1)=Sx+10; c(2)=Sy; c(3)=Tx; c(4)=Ty+100; c(5)=0; c(6)=0;
r*
for i=1:N A_(1,i)=A(1,i); A_(N+1,N+i)=A(2,N+i); end
y-5 -10
r
-15 -20 -5
A(5,1)=1; A(5,N)=-1; A(6,N+1)=1; A(6,2*N)=-1;
0
x
(a)
r
-15
5
10 15 20 25
-20 -5
0
5
10 15 20 25
x
x
(b)
(c)
c_(1)=c(1); c_(N+1)=c(2); L_(1,1)=-1; L_(1,2)=1; L_(N,N-1)=1; L_(N,N)=-1; L_(N+1,N+1)=-1; L_(N+1,N+2)=1; L_(2*N,2*N-1)=1; L_(2*N,2*N)=-1;
Fig.4. The original trajectory r and the similar to it trajectory r* satisfying constraints (14) for (a) (xb,yb)=(−10,15) (m); (b) (xb,yb)=(−10,20) (m); and (c) (xb,yb)=(6,20) (m). The coordinates x and y are measured in meters (m).
for i=2:N-1 L_(i,i-1)=1; L_(i,i)=-2; L_(i,i+1)=1; L_(N+i,N+i-1)=1; L_(N+i,N+i)=-2; L_(N+i,N+i+1)=1; end
5. Conclusion This work defined constrained similarity of 2-D trajectories via minimizing the H1 semi-norm of the difference between the trajectories and presented an exact solution to the discreized case. The results obtained agree with what is expected from similarity of trajectories under imposed constraints. The last example suggests possible application to mechanics and two-point boundary value problems.
H=inv(L_+A_); d=A_*u-c_; l=(A*H*A')\(A*u-c-A*H*d)*2; us=u-H*(A'*l/2+d); for i=1:N xs(i)=us(i); ys(i)=us(N+i); end
6. Appendix In this appendix a MATLAB code for solving Example 3(c) is presented. The variables A_, c_, and L_ are used for A , c and L , while xs, ys, and us are used for x*, y* and u*. The variable l is used for λ . To define the needed vectors and matrices, first the corresponding vectors and matrices composed of zeros and having the required size are defined.
1. Yan, Xin, Linear Regression Analysis: Theory and Computing, World Scientific, ISBN 9789812834119, 2009.
function main
2. Antoniou, A., Wu-Sheng Lu, Practical Optimization Algorithms and Engineering Applications, Springer, 2007.
plot(x,y,'o',xs,ys,'*'); end
7. References
3. Filipov, S., Atanasov, A., Gospodinov, I. Constrained Functional Similarity by Minimizing the H1 Seminorm and Applications to Engineering Problems, Journal of Chemical Technology and Metallurgy, 2016.
N=101; M=6; a=0; b=2*3.141593; h=(b-a)/(N-1);
4. Adams, R. Sobolev Spaces, Academic Press, ISBN 978-0-12044150-1, 1975.
t=zeros(N,1); x=zeros(N,1); y=zeros(N,1); u=zeros(2*N,1); A=zeros(M,2*N); c=zeros(M,1); A_=zeros(2*N,2*N); c_=zeros(2*N,1); L_=zeros(2*N,2*N);
5. Filipov, S., Gospodinov, I., Angelova, J., Solving Two-Point Boundary Value Problems for Integro-Differential Equations Using the Simple Shooting-Projection Method, Numerical Methods and Applications, pp.169-177, Springer, 2015.
for i=1:N t(i)=a+(i-1)*h; x(i)=sin(2*t(i)); u(i)=x(i); y(i)=(1-sin(t(i)))*sin(t(i)); u(N+i)=y(i); end
6. Arfken, G. Mathematical Methods for Physicists, 3rd ed. Orlando, FL: Academic Press, 1985.
Sx=0; Sy=0; Tx=0; Ty=0; for i=1:N Sx=Sx+x(i); Sy=Sy+y(i); Tx=Tx+t(i)*x(i); Ty=Ty+(t(i)-a)*(t(i)-b)*y(i); end for i=1:N
19
ONTOLOGY-BASED DATA ACCESS AND MODEL TRANSFORMATIONS FOR ENTERPRISE INTEROPERABILITY ОНТОЛОГИЧНО БАЗИРАНИ ДОСТЪП ДО ДАННИ И ТРАНСФОРМАЦИЯ НА МОДЕЛИ ЗА ОПЕРАТИВНА СЪВМЕСТИМОСТ НА ПРЕДПРИЯТИЯТА Assist. Prof. Dr. Gocheva D. G.1, Prof. Dr. Batchkova I. A.1, Prof. D.Sc. Popov G. T.2 1 Dept. of Industrial Automation, University of Chemical Technology and Metallurgy Bul. Kl. Ohridski 8, Sofia, Bulgaria 2 Dept. Technology of Machine Tools and Manufacturing, Technical University – Sofia, Bul. Kl. Ohridski 8, Sofia, Bulgaria
[email protected],
[email protected],
[email protected] Abstract: Enterprise interoperability is the ability of disparate and diverse information and control systems to work together efficiently towards mutually beneficial common goals. Some of the main tasks for achieving enterprise interoperability are connected with data and knowledge access and sharing and by use of model transformation. In this paper are presented and discussed several model transformations between different Technological Spaces: RDB, UML and OWL in order to enable ontology-based access to different models of enterprise data. At the core of the approach is the usage of reference models, based on the standard for enterprise integration ISO/IEC 62264. Keywords: ONTOLOGY, INFORMATION, INTEGRATION, OWL, UML UML and OWL 2: XML-based transformations and transformations built upon meta-models using transformation languages (ATL, QVT-R). In this paper we introduced transformation rules in order to provide semantic descriptions of the object models proposed in ISO/IEC62264 standard, which use only few UML modeling elements. The suggested rules are built upon the meta-models of the UML class diagrams and the language OWL 2. The paper [8] also investigates providing semantic descriptions for particular enterprise models with limited UML elements, in order to promote system interoperability, enterprise information integration and information retrieval.
1. Introduction Information access and data retrieval from distributed heterogeneous data sources are important, but difficult tasks in the modern industrial enterprises. Some of the possibilities in this direction are standard frameworks and data models, based on the best practices, which separate the information and knowledge from specific commercial products and methods of implementation. In this context, the ISO/IEC 62264 standard [1] (former ANSI/ISA S95) provides common terminology and consistent reference models that represent the best practices for integration, applicable the entire life cycle of enterprises. The reference models, provided by the standard, are built on a high level of abstraction, independent from the specific industry and might be used as a basis for development of any enterprise systems as well as for standard compliant interfaces between the legacy systems.
Relational databases are considered as one of the most popular storage solutions for various kinds of data. But according to Honeywell Process Solutions [9] relational data models can be very complex, difficult to report, inflexible. The variety of DBMS implies synchronization across data sources. Using data warehouses duplicates data and is not suitable for real time. Contrariwise, semantic data models are easier to understand, easier to report, flexible and can merge any data without replication; they are able to perform true federation: support structural change and system discovery across data sources [9]. The problem of bridging the gap between relational databases and semantic web ontologies has attracted the interest, and has been recognized as a key factor in generating huge amounts of data for Semantic Web applications based on standards RDF, OWL, SPARQL [10]. Transforming structured data sources into universal description model, as RDF aspires to be, enables seamless integration of their contents with information already represented in RDF [10]. A lot of methods and tools, classified in Knowledge Extraction Tools Survey Ontology (KETSO) are analyzed in [11]. Since data management according to the relational data model is still an order of magnitude faster than RDF data management and RDBs are the dominant data storage solution for enterprise data, relational data management will be prevalent in the next years.
A major trend in enterprise systems over the last decade has shifted from the traditional programming of imperative code to the creation of rich, interchangeable representations of information and knowledge [2]. Two significant paradigms (also known as Technological Spaces (TS) in [3]) have emerged in recent years to support this activity, each with its own terminology, standards bodies, research communities and flagship language: Model Driven Development (MDD) evolved primarily in the software engineering community and has the OMG’s Unified Modeling Language (UML) [4] as its flagship language. The other is the so-called ontology engineering paradigm that places ontologies at the center of the development process. Ontology engineering primarily evolved from the artificial intelligence community and has the W3C’s Web Ontology Language (OWL) [5] as its flagship language. Several publications discuss the relation of UML and OWL in general and the transformations of UML class diagrams into OWL ontologies. In [6] the authors investigate whether and how conceptual models written in UML can be automatically transformed into models written in OWL 2. Differences and similarities of various model elements in static UML data models and OWL 2 ontologies are shown and a transformation for similar elements is provided, indicating that data models written in UML can be represented as OWL ontologies quite well. But the different extent of the metamodels clearly suggests that OWL provides much more complex means of modelling already, so the transformation of general ontologies in UML data models is not always possible [6]. The transformation into an OWL 2 ontology allowed to check the consistency of the UML models and the data [6]. In [7] we discussed the two different approaches for a transformation between
Compared with relational databases, object data models are easier to understand and also can merge measurement’s data [9]. The Object-Relational Mapping (ORM) enables transformations between object models and relational databases. For application development it is easy to start from creating the model by using the UML Class Diagram to generate the executable persistence layer for the model. By Model Driven Development (MDD) approach using models at different levels of abstraction and applying model transformation to code generation, it is useful also and to modify the Entity Relational (ER) model, which comes from reverse engineering of an existing database, transform into object model
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and generate persistence layer. Mutual software tools automate the Object-Relational Mapping enabling the MDD of different software systems.
meta-ontology (Fig.1) is comprised of 103 classes, structured in four categories of resources: Personnel, Equipment, Material and ProcessSegment (marked on the figure) and five main interface classes, defining the relations Production-Process-Product: ProductDefinition, ProductionCapability, ProductionSchedule, ProcessSegmentCapability and ProductionPerformance. Based on the main resources, ProductDefinition information indicates what must be defined to make a product, ProductionCapability information defines what resources are available, ProductionSchedule information defines what actual production will be executed and ProductionPerformance information states what actual production was achieved.
The aim of the paper is to present and discuss several model transformations between the three Technological Spaces (TS): the DBMS TS (with a representative RDB), the Model Driven Architecture TS (with a representative UML) and the Ontology Engineering TS (with a representative OWL) in order to enable ontology-based access to different models of enterprise data. The basis of the approach is the usage of a standard for information integration during all phases of the life cycle of systems. The paper is organized in 5 parts. In part 2 a short overview of the basic technologies and tools used in the approach is given. The third part of the paper discusses the approach for ontology based data access and information retrieval. In Part 4 the applicability of the suggested approach is illustrated. Finally some conclusions are made.
The meta-ontology has the following favourable features: (i) it establishes clearly defined standardized terminology and structure for general enterprise systems; (ii) it is independent of specific industry or technology; (iii) it facilitates building domain models. The meta-ontology might be used for design of new enterprise systems or reengineering the legacy systems ensuring the interoperability or integration of these systems.
2. Basic technologies and tools used in the approach 2.1. Web ontologies Web ontologies are used to model and share knowledge among various applications in a specific domain facilitating interoperability between different systems. The Web Ontology Language OWL 2 [5] accepted as a World Wide Web Consortium (W3C) is a powerful knowledge representation language; it has been applied successfully for knowledge modelling in many application areas. As a descriptive language, OWL 2 is used to express expert knowledge in a formal way, and as a logical language, it is used to draw conclusions from this knowledge. Every OWL 2 ontology is a machine - processable formal description of a domain of interest and consists of the following three different syntactic categories: Entities, Expressions and Axioms. Entities, such as classes, properties, and individuals are identified by IRIs. They form the primitive terms of an ontology and constitute the basic elements of the ontology. Expressions represent complex concepts in the domain being described. Axioms are statements that are asserted to be true in the domain being described and allow relationships to be established between Expressions. The ability to infer additional knowledge is of great importance for designing and deploying OWL ontologies. Sound and complete OWL 2 reasoning is of high complexity, but the OWL 2 new profiles (OWL 2 EL, OWL 2 QL, OWL 2 RL), known also as lightweight ontology languages, restrict the used syntactic categories to improve complexity and practical performance [12]. The profile OWL 2 RL enables the implementation of polynomial time reasoning algorithms using rule-extended database technologies operating directly on RDF triples [12]. As any OWL 2 Ontology can be mapped to RDF, for ontology-based data access can be used SPARQL - a query language across diverse data sources, whether the data is stored natively as RDF or viewed as RDF for RDF models [13].
Figure.1: Meta-ontology, based on ISO/IEC 62264 2.3. Software tools, used in the approach MDD guarantee that business functionality is complete and correct, end-user needs are met and program design supports requirements for scalability, robustness, security, extendibility, and other characteristics, before implementation in code. The process of gathering and analyzing an application's requirements, and incorporating them into a program design, is a complex one and the industry currently supports many methodologies that define formal procedures specifying how to go about it. One characteristic of UML - in fact, the one that enables the widespread industry support that the language enjoys - is that it is methodology-independent. And, using XMI (XML Metadata Interchange), transfer the UML model from one tool into a repository, or into another tool for refinement or the next step in the development process. The so called Object-Relational Mapping (ORM) serves as a bridge between object models, data models and relational databases to automate the transformation between object models and relational data models. The IDE Visual Paradigm 13.0 (https://www.visualparadigm.com/) features all the UML diagrams and Entity Relational Diagrams (ERD) tools essentially in system and database design. Visual Paradigm provides a model driven platform for application development; allows not only to start from creating the models by using UML Class Diagram or Entity Relationship Diagram (ERD) to generating the executable persistence layer from the models, but also to modify the ER model which comes from reverse engineering of an existing database, transform into object model and generate persistence layer. The IDE supports a wide range of databases, including Oracle, DB2, Microsoft SQL Server, PostgreSQL, MySQL and more.
2.2. A standard for information integration ISO/IEC 62264 is a multi-part standard that defines the interface content between enterprise activities and control activities [1]. This standard is an agreement between leading companies to create a common framework, and guidelines for design and integration of systems providing common models and terminology for structuring and describing the exchanged information. The standard provides UML models, which are the basis for the development of information systems and standard compliant interfaces between different systems.
TopBraid Composer Maestro Edition (TBC-ME) (http://www.topquadrant.com/) combines world’s leading semantic web modeling capabilities with the most comprehensive data conversion options and is a powerful IDE for building, managing and testing configurations of ontologies, for operations on ontologies (merging, alignment, integration, inference, etc.), for automated conversion of spreadsheets, Excel, UML and other data sources, for dynamic connections to relational databases, or running SPARQL queries over relational data.
The semantic approach, presented in this paper, uses the models and terminology, provided by the standard ISO/IEC 62264 together with a meta-ontology [14], conceptualizing knowledge embedded in the standard as a target OWL ontology in order to use together data presented in different data models. The mapping rules between UML class diagrams (provided by the standard) and OWL elements of the meta-ontology are presented in [15]. The standard conformed
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The D2RQ Platform (http://d2rq.org/), integrated in TBC-ME is a matured system for accessing relational databases as virtual, readonly RDF graphs. It offers RDF-based access to the content of relational databases without having to replicate it into an RDF store. The system includes a SPARQL-to-SQL rewriter that can evaluate SPARQL queries over the mapped database.
interoperability between OWL ontologies, relational databases and UML models (Fig.2). At the core of the approach is the usage of reference models, based on the standard for enterprise integration ISO/IEC 62264. One of the benefits is using in a maximum degree the legacy data and data models (relational data models, UML models, Excel data sheets, documents, etc.) presenting them as RDF/OWL structures. Thus the basic advantages of the ontology based system development might be used: intelligent integration, semantic in data management, reasoning upon data and data models, reusable reference models, etc.
3. Description of the suggested approach The approach, suggested in this paper aims to transform, represent and integrate different data and data models into the technological space of ontology engineering for achieving
OWL 2
1
RDB
3
UML
3
4
4
Figure.2: Illustration of the suggested approach The presented approach is realized with two mutual commercial software IDEs for automatic and personalized model transformations: Visual Paradigm 13.0 for UML and ERD transformations and Top Braid Composer ME 4.2.0 used for ontology engineering. As a DBMS mySQL is used and the data connection is done with the free software tool to handle the administration of MySQL over the Web: phpMyAdmin (https://www.phpmyadmin.net/). The approach states on the usage of a reference standard based meta-ontology as a target ontology based on the models and terminology, provided by the standard ISO/IEC 62264.
(Figure 3). The transformation is not still personalized, the names of the classes and properties are generated automatically.
Figure.3: Transformation from UML class diagram to OWL ontology
4. Applicability of the suggested approach
4.2. Relational database to OWL ontology
The realized model transformations are pointed on the figures with the numbers 1-4.
The transformation of a relational database (PhpMyAdmin) to OWL ontology (TopBraid Composer) is pointed with (2) on Figure 2. The transformation is done (Figure 4) with the integrated D2RQ mapping language in the TopBraid Composer ME 4.2.0.
4.1. UML class diagram to OWL ontology The transformation from UML class diagram (Visual Paradigm) to OWL ontology (TopBraid Composer) is pointed with (1) on Figure 2. One of the main resource models of ISO/IEC 62264 is used as it is presented in the standard – the Personnel model. The Personnel model contains the information about specific personnel, classes of personnel, and qualifications of personnel. The PersonnelClass is a class to describe a grouping of persons with similar characteristics. Each PersonnelClass may have zero or more recognized properties. The class Person represents a specifically identified individual. A person may be a member of zero or more personnel classes. These specify the current property values of the person for the associated personnel property. A qualification test specification may be associated with a personnel class property or person property. A qualification test result records the results from a qualification test for a specific person. Using a model-based transformation approach, implemented in TopBraid Composer ME 4.2.0, based on SPARQL Rules, XMI model of the UML Personnel model, created in Visual Paradigm 13.0 is converted to OWL
Figure.4: Transformation from relational database to OWL ontology A sample mySQL database for Inventory/Orders/Customers system - northwind.sql is used and with D2RQ mapping language a static import of schema and dynamic import of data is done. The schema and the data from the used database might be used along with a domain ontology which can be integrated into the meta-
22
ontology for PersonnelModel or ProductionSchedulingModel, or a suitable mapping directly to the meta-ontology might be done. SPARQL queries to the content of the relational database can be performed without having to replicate it in ontology data store.
the stereotype , the physical ERD data model and the created relationships in the target relational database in PhpMyAdmin tool are shown on Figure 5. The transformation of an relational database (PhpMyAdmin) to ERD data model (Visual Paradigm) and to UML class diagram (Visual Paradigm) is pointed with (4) on Figure 2. In this case, the same sample mySQL database for Inventory/Orders/Customers system - northwind.sql is used in PhpMyAdmin, the corresponding ER model is created and the new object model is created according the mapping rules. Figure 6 presents the automatic transformations; additional personalization might be done in both cases: object to relational or relational to object mappings.
4.3. Object-Relational Mapping The transformation of an UML class diagram (Visual Paradigm) to ERD data model (Visual Paradigm) and to MySQL (PhpMyAdmin) is pointed with (3) on Figure 2. One of the main resource models of ISO/IEC 62264 is used as it is presented in the standard – the Personnel model. The UML Personnel model, created in Visual Paradigm 13.0 is converted to ERD physical model and a database Personnel.sql is generated. The UML class diagram, represented by
Figure 5.: Transformation from UML class diagram to ERD data model and to MySQL database
Figure 6.: Transformation from relational database to ERD data model and to UML class diagram 6.
5. Conclusions The suggested approach, based on the joint use of standards for integration, relational databases, UML models and OWL ontologies aims to reduce the effort, cost, and errors during the design, implementation and integration of systems. Ontologies ensure easy merging, extending and sharing of heterogeneous data models, rich semantics, and reusable modules. Semantics shows enormous potential in making software systems more efficient, adaptive and intelligent. Ontology-based systems allow humans and computer systems to exchange knowledge without ambiguity and also makes it possible to use logical deduction to infer additional information from the facts stated explicitly in ontologies.
7.
8.
9.
10.
6. References 1. 2. 3.
4.
11.
ISO/IEC 62264, Enterprise-control system integration, Part 1: Models and terminology, Part 2: Object model attributes, 2015. K. Kiko and C. Atkinson, “A Detailed Comparison of UML and OWL,” Mannheim, 2008, technical report. Kurtev I., Bézivin J., Aksit M., Technological Spaces: an initial appraisal, CoopIS, DOA'2002 Federated Conferences, Industrial track, Irvine, 2002. OMG (2014), Unified Modeling Language, Superstructure, Version 2.4, http://www.omg.org/spec/UML/2.4.1/Superstructure/pdf.
12.
13. 14.
5. W3C OWL Working Group, OWL 2 Web Ontology Language: Structural Specification and Functional-Style Syntax (Second Edition) W3C Recommendation, 11 December 2012, http://www.w3.org/TR/owl2-syntax.
15.
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Zedlitz, J., & Luttenberger, N. (2014). Conceptual Modelling in UML and OWL-2. International Journal on Advances in Software, 7(1), 182196. D. Gocheva, I. Batchkova (2014), Transformation of UML class diagram to OWL ontology, International Conference “Automatics and Informatics’2014”, 03-05 October, Sofia. Viademonte S., Cui Z., Deriving OWL Ontologies from UML Models: an Enterprise Modelling Approach, on-line available on: http://www.researchgate/profile/Sergio_Viademonte. Jay Funnell, J., Dickson, D., Chacon, J., Demystifying the Intuition Semantic Model, Control Engineering, 25 March 2012, http://www.controlengeurope.com Spanos, D. E., Stavrou, P., & Mitrou, N. (2012). Bringing relational databases into the semantic web: A survey. Semantic Web, 3(2), 169209. Unbehauen, J, Hellmann, S., Auer, S., Stadler, C., Knowledge Extraction from Structured Sources, in Stefano Ceri & Marco Brambilla, ed., Search Computing Broadening Web Search, Springer, pp. 34-52, 2012. Krötzsch, M., OWL 2 Profiles: An Introduction to Lightweight Ontology Languages, Proc. 8th Reasoning Web Summer School, LNCS 7487, Springer, pp. 112–183, 2012. SPARQL 1.1 Overview W3C Recommendation 21 March 2013 http://www.w3.org/TR/sparql11-overview. Dobrev, M., Gocheva, D., Batchkova, I., An ontological approach for planning and scheduling in primary steel production, In Proceedings of the 4-th International IEEE Conference on Intelligent Systems, Vol.1, pp.6-14: 6-19, Varna, Bulgaria, September 6-8, 2008. Gocheva D, Batchkova I. (2014), Transformation of UML class diagram to OWL ontology, International Conference “Automatics and Informatics’2014”, 03-05 October, Sofia.
A MAPREDUCE SOLUTION FOR HANDLING LARGE DATA EFFICIENTLY M.Sc. K. Al-Barznji PhD Student, Assoc. Prof. Dr. A. Atanassov Department of Computer Science, University of Chemical Technology and Metallurgy, Sofia, Bulgaria
[email protected] ,
[email protected] Abstract: Big data is large volume, heterogeneous, distributed data. Big data applications where data collection has grown continuously, it is expensive to manage, capture or extract and process data using existing software tools. With increasing size of data in data warehouse it is expensive to perform data analysis. In recent years, numbers of computation and data intensive scientific data analyses are established. To perform the large scale data mining analyses so as to meet the scalability and performance requirements of big data, several efficient parallel and concurrent algorithms got applied. For data processing, Big data processing framework relay on cluster computers and parallel execution framework provided by MapReduce. MapReduce is a parallel programming model and an associated implementation for processing and generating large data sets. In this paper, we are going to work around MapReduce, use a MapReduce solution for handling large data efficiently, its advantages, disadvantages and how it can be used in integration with other technology. Keywords: DATA MINING; BIG DATA; CLUSTERING; PARALLEL PROCESSING; HADOOP; HDFS; MAPREDUCE;
1. Introduction
Data intensive processing is fast and currently becoming a necessity to handle the large databases efficiently. It is required to design algorithms that must be capable of scaling to real world datasets. MapReduce is a programming model which is inspired by functional programming which allows expressing distributed computations on massive amounts of data. It is designed for large scale data processing as it allows running on clusters of commodity hardware [8]. MapReduce is a powerful parallel programming technique for distributed processing of vast amount of data on clusters [9].
Data Mining is analyzing the data from different perspectives and summarizing it into useful information that can be used for business solutions and predicting the future trends. Mining the information helps organizations to make knowledge driven decisions. Data mining (DM), also called Knowledge Discovery in Databases (KDD), is the process of searching large volumes of data automatically for patterns such as association rules. It applies many computational techniques from statistics, information retrieval, machine learning and pattern 1recognition. Data mining extract only required patterns from the database in a short time span. Based on the type of patterns to be mined, data mining tasks can be classified into summarization, classification, clustering, association and trends analysis [1]. Among several techniques in data mining, clustering is the main considerable point which is used to retrieve the essential knowledge from the very huge collection of data. Clustering can handle both the complicated and very large datasets which can be of diverse data types. To classify the large data sets clustering is the vital solution [2]. Big Data is a new term used to identify the data sets that are of large size and have grater complexity [3]. Big data is defined as large amount of data which requires new technologies and architectures to make possible to extract value from it by capturing and analysis process [4].
2. Background In this section, we review the Apache Hadoop Fundamentals (HDFS and MapReduce) Explained with a Diagram: 2.1. Hadoop Framework Apache Hadoop is an open source Java framework for processing and querying vast amounts of data on large clusters of commodity hardware. With a significant technology investment by Yahoo!, Apache Hadoop has become an enterprise ready cloud computing technology. It is becoming the industry defacto framework for Big Data processing. Hadoop is impact can be boiled down to four salient characteristics. Hadoop enables scalable, costeffective, flexible, fault tolerant solutions [10]. Hadoop was derived from Google's MapReduce and Google File System (GFS) [11]. Hadoop has two primary components, namely, HDFS and MapReduce programming framework. The most significant feature of Hadoop is that HDFS and MapReduce are closely related to each other. Therefore, the storage system is not physically separated from the processing system [12]. The following figure 2 shows the Hadoop framework main components [13].
Over the last few years, MapReduce has emerged as the most popular computing paradigm for parallel, batch style and analysis of large amounts of data. Many areas where massive data analysis is required, MapReduce are used. There are evolving numbers of applications that handle big data, but to handle such huge collection of data is a very challenging problem today. Here, we got the MapReduce or its open source equivalent Hadoop which is a powerful tool for building such applications [5]. MapReduce divides the computational flow into two main phases: Map and Reduce. By simply designing Map and Reduce functions, developers are able to implement parallel algorithms that can be executed across the cluster [6]. The steps involved in working of MapReduce can be shown in as figure 1 [7]:
Fig.2. Hadoop Framework
2.1.1. HDFS (Hadoop Distributed File System) HDFS stands for Hadoop Distributed File System, it is the
Fig.1. Steps in MapReduce to process the database
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• This provides a clear abstraction for programmers. They have to just implement two functions: map and reduce. • The data are fed into the map function as key value pairs to produce intermediate key/value pairs • Once the mapping is done, all the intermediate results from various nodes are reduced to create the final output • JobTracker keeps track of all the MapReduces jobs that are running on various nodes. This schedules the jobs, keeps track of all the map and reduce jobs running across the nodes. If any one of those jobs fails, it reallocates the job to another node, etc. In simple terms, JobTracker is responsible for making sure that the query on a huge dataset runs successfully and the data is returned to the client in a reliable manner. • TaskTracker performs the map and reduce tasks that are assigned by the JobTracker. TaskTracker also constantly sends a hearbeat message to JobTracker, which helps JobTracker to decide whether to delegate a new task to this particular node or not.
storage system used by Hadoop. The following is a high level architecture that explains how HDFS works(see figure 3) [21].
Fig.3. HDFS Diagram.
• In the above diagram, there is one NameNode, and multiple DataNodes(servers). b1, b2, indicates data blocks. • When you dump a file (or data) into the HDFS, it stores them in blocks on the various nodes in the hadoop cluster. HDFS creates several replications of the data blocks and distributes them accordingly in the cluster in way that will be reliable and can be retrieved faster. A typical HDFS block size is 128MB. Each and every data block is replicated to multiple nodes across the cluster. • Hadoop will internally make sure that any node failure will never results in a data loss. • There will be one NameNode that manages the file system metadata. • There will be multiple DataNodes (These are the real cheap commodity servers) that will store the data blocks. • When you execute a query from a client, it will reach out to the NameNode to get the file metadata information, and then it will reach out to the DataNodes to get the real data blocks • Hadoop provides a command line interface for administrators to work on HDFS. • The NameNode comes with an in-built web server from where you can browse the HDFS filesystem and view some basic cluster statistics.
3. Mapreduce Architecture In most computation related to high data volumes, it is observed that two main phases are commonly used in most data processing components this is shown in below figure 5. Map Reduce created an abstraction phases of Map Reduce model called mappers and reducers. When it comes to processing large data sets, for each logical record in the input data it is often required to use a mapping function to create intermediate key value pairs. Then another phase called reduce to be applied to the data that shares the same key, to derive the combined data appropriately [14].
2.1.2. MapReduce Framework MapReduce is a software framework introduced by Google in 2004 to support distributed computing on large data sets on clusters of computers. MapReduce is a programming model for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs and a reduce function that merges all intermediate values associated with the same intermediate key [11]. MapReduce is designed to be used by programmers, rather than business users. It is a programming model, not a programming language. It has gained popularity for its easiness, efficiency and ability to control Big Data in a timely manner [7]. Google proposed the MapReduce programming framework based on functional programming. The framework divides the work into independent tasks and parallelizes the computation flow across large scale clusters of machines, taking care of communications among them and possible failures, and efficiently handling network bandwidth and disk usage [6]. The following is a high-level architecture that explains how MapReduce works (see figure 4) [21].
Fig.5. MapReduce Architecture
Mapper The mapper is applied to every input key-value pair to generate an arbitrary number of intermediate key-value pairs. The standard representation of this is as follows: map(inKey,inValue)list(intermediateKey, intermediateValue). The purpose of the map phase is to organize the data in preparation for the processing done in the reduce phase. The input to the map function is in the form of key-value pairs, even though the input to a MapReduce program is a file or file(s). By default, the value is a data record and the key is generally the offset of the data record from the beginning of the data file. The output consists of a collection of key-value pairs which are input for the reduce function. The content of the key-value pairs depends on the specific implementation. For example, a common initial program implemented in MapReduce is to count words in a file. The input to the mapper is each line of the file, while the output from each mapper is a set of key-value pairs where one word is the key and the number 1 is the value. map: (k1 , v1 ) → [(k2 , v2 )] The file_name and the file_content which is denoted by k1 and v1. So, with in the map function user may emit the any arbitrary key/value pair as denoted in the list [k2, v2]. To optimize the processing capacity of the map phase, MapReduce can run several identical mappers in parallel. Since every mapper is the same, they produce the same result as running one map function. Reducer The reducer is applied to all values associated with the same intermediate key to generate output key-value pairs.
Fig.4. MapReduce Diagram
• MapReduce is a parallel programming model that is used to retrieve the data from the Hadoop cluster • In this model, the library handles lot of messy details that programmers doesn’t need to worry about. For example, the library takes care of parallelization, fault tolerance, data distribution, load balancing, etc. • This splits the tasks and executes on the various nodes parallely, thus speeding up the computation and retriving required data from a huge dataset in a fast manner.
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reduce(intermediateKey,list(intermediateValue))--> list(outKey, outValue) Each reduce function processes the intermediate values for a particular key generated by the map function and generates the output. Essentially there exists a one-one mapping between keys and reducers. Several reducers can run in parallel, since they are independent of one another. The number of reducers is decided by the user. By default, the number of reducers is 1. Since we have an intermediate group by operation, the input to the reducer function is a key value pair where the key- k2 is the one which is emitted from mapper and a list of values [v2] with shares the same key. reduce: (k2 , [v2 ]) → [(k3 , v3 )] .
// key: document name // value: document contents for each word w in value: EmitIntermediate(w, "1"); reduce(String key, Iterator values): // key: a word // values: a list of counts int result = 0; for each v in values: result += ParseInt(v); Emit(AsString(result)); The map function emits each word plus an associated count of occurrences (just ‘1’ in this simple example). The reduce function sums together all counts emitted for a particular word. In addition, the user writes code to fill in a mapreduce specification object with the names of the input and output files, and optional tuning parameters. The user then invokes the MapReduce function, passing it the specification object. The user’s code is linked together with the MapReduce library (implemented in Java) [16].
4. Programming Model MapReduce is a programming model designed for processing large volumes of data in parallel by dividing the work into a set of independent tasks. The nature of this programming model and how it can be used to write programs which run in the Hadoop environment is explained by this model. Hadoop is an open source implementation of this environment [15]. The computation takes a set of input key/value pairs, and produces a set of output key/value pairs. The user of the MapReduce library expresses the computation as two functions: map and reduce. Map, written by the user, takes an input pair and produces a set of intermediate key/value pairs. The MapReduce library groups together all intermediate values associated with the same intermediate key I and passes them to the reduce function. The reduce function, also written by the user, accepts an intermediate key I and a set of values for that key. It merges these values together to form a possibly smaller set of values. Typically just zero or one output value is produced per reduce invocation. The intermediate values are supplied to the user’s reduce function via an iterator. This allows us to handle lists of values that are too large to fit in memory. MapReduce [22] requires that the operations performed at the reduce task to be both associative and commutative. This two stage processing structure is illustrated in Figure 6:
4.2 Types Even though the previous pseudocode is written in terms of string inputs and outputs, conceptually the map and reduce functions supplied by the user have associated types. map (k1,v1) →list(k2,v2) reduce (k2,list(v2)) →list(k3,v3). That is, the input keys and values are drawn from a different domain than the output keys and values. Furthermore, the intermediate keys and values are from the same domain as the output keys and values. Finally we can say the Input and Output types of a MapReduce job as: (input) -> map -> -> combine -> > reduce -> (output).
5. Problem Formulation MapReduce over traditional DBMS: Our traditional DBMSs have adopted such strategies which are not appropriate for solving extremely large scale data processing tasks. There has been a need for some special purpose data processing tools that are adapted for solving such problems[17]. While MapReduce is referred to as a new way of processing big data in data center computing, it is also criticized as a “major step backwards” in parallel data processing in comparison with DBMS [18]. However, many MapReduce proponents in industry argue that MapReduce is not a DBMS and such between them is not a just [19]. Although Hadoop won the 1st position in GraySort benchmark test for 100 TB sorting (1 trillion 100-byte records) in 2009, its winning was achieved with over 3,800 nodes. MapReduce or Hadoop would not be a cheap solution if the cost for constructing and maintaining a cluster of that size was considered [20]. Analysis of 10-months of MR logs from Yahoo’s M45 Hadoop cluster and MapReduce usage statistics at Google are also available. The studies exhibit a clear tradeoff between efficiency and fault-tolerance. MapReduce increases the fault tolerance of long-time analysis by frequent checkpoints of completed tasks and data replication. However, the frequent I/Os required for fault tolerance reduce efficiency. Parallel DBMS aims at efficiency rather than fault tolerance. DBMS actively exploits pipelining intermediate results between query operators. However, it causes a potential danger that a large amount of operations need be redone when a failure happens. With this fundamental difference, we describe some advantages and limitations of MapReduce framework [5].
Fig.6. MapReduce simplified flowchart
Map and Reduce are two functions. The main job of these two functions are sorting and filtering input data. During Map phase data is distributed to mapper machines and by parallel processing the subset it produces pairs for each record. Next shuffle phase is used to repartition and sorting that pair within each partition. So the value corresponding same key grouped into {v1, v2,….} values. Last during Reduce phase reducer machine process subset pairs parallel in the final result is written to distributed file system [15]. A Hadoop MapReduce program also has a component called the Driver. The driver is responsible for initializing the job with its configuration details, specifying the mapper and the reducer classes for the job, informing the Hadoop platform to execute the code on the specified input file(s) and controlling the location where the output files are placed [14].
6. Advantages of Mapreduce MapReduce is simple and efficient for computing aggregate. Thus, it is often compared with “filtering then group-by aggregation” query processing in a DBMS. Here are major advantages of the MapReduce framework for data processing. For the huge data processing task, the key advantages of the MapReduce framework are as [5]:
4.1 Example Consider the problem of counting the number of occurrences of each word in a large collection of documents. The user would write code similar to the following pseudocode. map(String key, String value):
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• Simple and easy to use: The MapReduce model is simple but expressive. A programmer defines his task by using only Map and Reduce functions. There is no need for him to specify the physical distribution of his work across nodes. • Flexible MapReduce: It does not have any dependency on data model and schema. A programmer can deal with irregular or unstructured data more easily than they do with DBMS. • Independent of the storage: It is independent from underlying storage layers. Thus, MapReduce can work with different storage layers such as Big Table and others. • Fault tolerance: It is highly fault-tolerant. It is reported that MapReduce can continue to work in spite of an average of 1.2 failures per analysis job at Google. • High scalability: The best advantage of using MapReduce is high scalability. Yahoo! reported that their Hadoop gear could scale out more than 4,000 nodes in 2008. MapReduce is simple and efficient tool for query processing in a DBMS. Thus, due to these major advantages of MapReduce, we have integrated it with one of the advance technique of data processing from large databases. The increasing interest and popularity of MapReduce has led some relational DBMS vendors to support MapReduce functions inside the DBMS. This capability not only offers the benefits outlined above for deploying user defined functions, but also adds the advantages of MapReduce to the relational DBMS environment, i.e., the ability to process multistructured data using SQL. It also brings the maturity of relational DBMS technology to MapReduce processing. The Teradata Aster Database is an example of a product that supports MapReduce [18].
effortlessly scales from a single machine to thousands, providing fault tolerant & high performance.
References [1] R. Gupta, “Journey from Data Mining to Web Mining to Big Data,” Int. J. Comput. Trends Technol., vol. 10, no. 1, pp. 18– 20, 2014. [2] S. Maitrey and C. K. Jha, “An integrated approach for CURE clustering using map-reduce technique,” Proc. Elsevier, ISBN 978-81- 910691-6-3,2nd, pp. 630–637, 2013. [3] A. Bifet, “Mining big data in real time,” Inform., vol. 37, no. 1, pp. 15–20, 2013. [4] S. Lenka Venkata, “A Survey on Challenges and Advantages in Big Data,” vol. 8491, pp. 115–119, 2015. [5] S. Maitrey, C. K. Jha, and C. K. Jha, “Handling big data efficiently by using map reduce technique,” Proc. - 2015 IEEE Int. Conf. Comput. Intell. Commun. Technol. CICT 2015, pp. 703–708, 2015. [6] A. Bechini, F. Marcelloni, and A. Segatori, “A MapReduce solution for associative classification of big data,” Inf. Sci. (Ny)., vol. 332, pp. 33–55, 2016. [7] S. Maitrey and C. K. Jha, “MapReduce: Simplified Data Analysis of Big Data,” Procedia Comput. Sci., vol. 57, pp. 563– 571, 2015. [8] J. Dean and S. Ghemawat, “MapReduce: Simplied Data Processing on Large Clusters,” Proc. 6th Symp. Oper. Syst. Des. Implement., pp. 137–149, 2004. [9] K. U. . Jaseena and J. M. David., “Issues, Challenges, and Solutions: Big Data Mining,” Comput. Sci. Inf. Technol., pp. 131–140, 2014. [10] V. Prajapati, Big Data Analytics with R and Hadoop, First publ. BIRMINGHAM - MUMBAI: Packt Publishing Ltd., 2013. [11] A. B. Patel, M. Birla, and U. Nair, “Addressing big data problem using Hadoop and Map Reduce,” 3rd Nirma Univ. Int. Conf. Eng. NUiCONE 2012, pp. 6–8, 2012. [12] I. A. T. Hashem, I. Yaqoob, N. B. Anuar, S. Mokhtar, A. Gani, and S. Ullah Khan, “The rise of ‘big data’ on cloud computing: Review and open research issues,” Inf. Syst., vol. 47, pp. 98–115, 2015. [13] D. A. Heger, “Hadoop Design , Architecture & MapReduce Performance,” (DHTechnologies www.dhtusa.com, pp. 1–18, 2011. [14] Dr.Siddaraju, C. L. Sowmya, K. Rashmi, and M. Rahul, “Efficient Analysis of Big Data Using Map Reduce Framework,” Int. J. Recent Dev. Eng. Technol., vol. 2, no. 6, pp. 64–68, 2014. [15] S. Suryawanshi and P. V. S. Wadne, “Big Data Mining using Map Reduce : A Survey Paper,” www.iosrjournals.org, vol. 16, no. 6, pp. 37–40, 2014. [16] J. Dean and S. Ghemawat, “MapReduce: Simplified Data Processing on Large Clusters,” Commun. ACM, vol. 51, no. 1, p. 107, 2008. [17] D. Florescu and D. Kossmann, “Rethinking cost and performance of database systems,” ACM SIGMOD Rec., vol. 38, no. 1, p. 43, 2009. [18] A. Pavlo, E. Paulson, A. Rasin, D. J. Abadi, D. J. DeWitt, S. Madden, and M. Stonebraker, “A comparison of approaches to large-scale data analysis,” Proc. 35th SIGMOD Int. Conf. Manag. data, pp. 165–178, 2009. [19] M. Stonebraker, D. Abadi, D. J. DeWitt, S. Madden, E. Paulson, A. Pavlo, and A. Rasin, “MapReduce and parallel DBMSs,” Commun. ACM, vol. 53, no. 1, p. 64, 2010. [20] S. Loebman, D. Nunley, Y. C. Kwon, B. Howe, M. Balazinska, and J. P. Gardner, “Analyzing massive astrophysical datasets: Can Pig/Hadoop or a relational DBMS help?,” Proc. - IEEE Int. Conf. Clust. Comput. ICCC, 2009. [21] http://www.thegeekstuff.com/2012/01/hadoop-hdfsmapreduce-intro . [22] http://sci2s.ugr.es/BigData .
7. Discussion And Challenges MapReduce is becoming ubiquitous, even though its efficiency and performance are controversial. There is nothing new about principles used in MapReduce. However, MapReduce shows that many problems can be solved in the model at scale unprecedented before. Due to frequent checkpoints and runtime scheduling with speculative execution, MapReduce reveals low efficiency. However, such methods would be necessary to achieve high scalability and fault tolerance in massive data processing. Thus, how to increase efficiency guaranteeing the same level of scalability and fault tolerance is a major challenge. The efficiency problem is expected to be overcome in two ways: improving MapReduce itself and leveraging new hardware. How to utilize the features of modern hardware has not been answered in many areas. However, modern computing devices such as chip-level multiprocessors and Solid State Disk can help reduce computations and I/Os in MapReduce significantly. The size of MR clusters is continuously increasing. A 4,000-node cluster is not surprising any more. How to efficiently manage resources in the clusters of that size in multi-user environment and achieving high utilizations of MR clusters is also challenging [5].
8. Conclusion We are living in the big data era where enormous amounts of heterogeneous, semi structured and unstructured data are continually generated at unprecedented scale, and processing large volumes of data has never been greater. Through better Big Data analysis tools like Map Reduce over Hadoop and HDFS, guarantees faster advances in many scientific disciplines and improving the profitability and success of many enterprises. MapReduce has received a lot of attentions in many fields, including data mining, information retrieval, image retrieval, machine learning, and pattern recognition. However, as the amount of data that need to be processed grows, many data processing methods have become not suitable or limited. In this paper we discussed about the MapReduce framework for efficient analysis of big data and for solving challenging data processing problems on large scale datasets in different domains. MapReduce provides a simple way to scale your application. It
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THE METHOD OF SPIRAL DESIGN MODEL FOR THE AUTOMATED DESIGN OF ANALOG IP-CORES IN COMPUTING МЕТОД СПИРАЛЕВИДНОЙ МОДЕЛИ ПРОЕКТИРОВАНИЯ ДЛЯ АВТОМАТИЗАЦИИ РАЗРАБОТКИ АНАЛОГОВЫХ IP-БЛОКОВ В ВЫЧИСЛИТЕЛЬНЫХ СИСТЕМАХ Student Gavrilova N.M.1, Prof. Dr. Tech. Sci. Molodyakov S.A.2 Peter the Great St. Petersburg Polytechnic University1, 2 – Saint-Petersburg, Russia
[email protected] [email protected] Abstract: The systematic approach of complex technical devices design allows not only to design new devices and objects, but also to automate the design process. This article discusses the seven-layer spiral design model, which can be used to simplify the design process of complex devices in areas of mechanical engineering and computer engineering. The spiral model in this work is used for automation of analog IP-cores design; in particular, the windows application that implements the automated design system of analog low-pass filters was developed. The application allows user to design the filter scheme in automated mode after inputting the parameters. The proposed method has certain benefits compared to the known automated design methods for the specific object classes. Keywords: AUTOMATED DESIGN, SEVEN-LAYER SPIRAL DESIGN MODEL, IP-CORES, LOW-PASS FILTERS
software development. Design stages are clearly described in these models. However, methodologies based on them are mainly used for development of software and not for technical objects.
1. Introduction In modern mechanical engineering, as in other industrial branches, the period of production update is getting shorter and more and more complex technical objects have been designed. One of the most important stages in manufacturing of such objects is design stage. At this very stage of development of the object its general configuration is determined and many mistakes in the object development could be prevented. Therefore sustained interest in methodology and methods of design is observed.
Specific design flows exist for several types of objects. Various models are used depending on the object. They differ in set of stages and objective of design. Statement of objectives allows choosing criteria connected with them. There are several design models for electronic analog components [5], digital elements [6], video systems [7, 8], software packages [9]. One of the most full (detailed) design models is spiral model [10]. It can be used in design of various devices, including objects of mechanical engineering.
2. Methods of technical objects design. Systematic approach
3. Seven-layer spiral model methodology
There are several approaches for technical objects design. One of design methodologies is the system design. It assumes sequential stage by stage design of a device. Dividing the design process into stages and aspects allows: firstly, using concurrent design methods, and secondly, organizing existing data and forming new knowledge. Concurrent design makes it possible for a large development team to elaborate a new device. Main principles of systematic approach are practical usefulness, unity of the components and variability in time.
Contracting spiral model of design is most fully described by Lypar Ju. I. [10] (see Fig.1). It uses objective approach where design of object is leaded through spiral-like route from objectives towards the final structure of object and its parameters.
Modern design processes of technical objects in most cases are computer-aided. Very seldom it is possible to make these processes fully automatic. Structuring of design process by applying systematic approach allows creation of computer-aided design (CAD) systems, which simplify and accelerate development of new devices and moreover allow receiving products of optimal quality at the output. CAD facilities (such as Matlab Simulink, Actel, Altera, Cadence and many others) usually follow some design flows [1]. In most of such systems modelling and design of end product are automated but the stage of structuring is given to a developer. At this stage the developer is supposed to build up the model of designed object from component blocks suggested by the system. The developer chooses one or another decision using his own ideas of optimality and later checks how it fits the demanded characteristics. The design flows for objects in such CAD systems are quite difficult and in most cases include textual or graphical setting of object structure and subsequent modelling, synthesis and debugging of this object at various levels [2]. There are also several methodologies based on design models used for software development. They include iterative [3], waterfall [4] and other models of development. Each of these models has its advantages and drawbacks, and is used or was used till recently in
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Fig.1. Spiral model of objects design. Titles of seven stages are given in the upper middle part of the picture, four aspects are shown in the corners
table 1. Table 1: Comparison of spiral model with other design models and design flows
The model includes seven levels (or stages) of design for every aspect of design: technological, functional, structural and constructional. At each stage a subset of the most effective decisions is selected from a number of suggested decisions with the help of a choice function, which determines the optimal configuration of the object. Spiral model in a compact way describes a huge diversity of structure variants of designed object and variants of its functionality. This scheme gives no practical limitations to application field and component composition of technical object. Therefore this design methodology can be considered rather general and can be used in development of many technical objects and devices, either simple or complex.
Characteristics
The stages of spiral design model go in the following order: stage of setting of requirements that designed object should meet (STET); stage of synthesis of construction principles (SPr); stage of approximation of desired configuration and characteristics of the object (SApp); stage of synthesis of construction ways (SRes); stage of structure synthesis (SApp); stage of structure elements parameters calculation (SPar); stage of tolerances (STol). Each stage has a feedback, movement towards and backwards along design stages is also possible. Consequently the model is sustainable to any changes at any design stage and if it becomes necessary to include such changes there is no need to start design process from the beginning.
Generality
Applicability
Specific design flows
+
−
+
Design flows of CAD systems (Altera, Simulink)
−
+
+
Software design models (e.g., iterative, waterfall models)
+
−
±
Spiral design model
+
+
+
Methodology based on spiral design model has clarity, generality and applicability. In design of technical objects this features can give advantage over other existing methodologies.
4. Practical use of the spiral model methodology in filter design
Result of design in one or another aspect is a composition of functions of choice at all stages (1). The resulting set should include effective solution describing the designed technical object realized in the most optimal way. Π=STol°SPar°SApp°SRes°SA°SPr°STET
Clarity
Based on spiral model methodology, an application for a design system of analog IP-cores, named Design IP [11], was developed. IP-cores are the reusable units of logic, cell or chip layout design, which are the intellectual property of the designer, so IP in IP-cores stands for “Intellectual Property”. IP-cores have made a huge impact on system-on-chip design, that is why analog IP-cores are an essential part of modern portable computing systems, but the automation of the analog IP-cores is so far less developed than the digital IP-cores automation. This is why the goal of developing an application for digital IP-cores automated design was set in the present work.
(1)
At each turn of the spiral the following tasks are solved. Work on functional aspect (F) of designed object means analysis of technical, technological, exploitation, economical and ecological requirements to devices and subsystems (briefly TET). In most cases at the first stage there is lack of data for solving all the tasks. Therefore at each new stage system analysis of results of previous stages is done and additional requirements are formulated for new stages. The complex of those requirements forms a choice function for the next stage.
The goal was to develop an automated design system which allows user to design one of the simplest IP-cores - low-pass analog filter circuitries - in automated mode. Now the first stage of the work is done. It includes development of an application for design system for passive filters of low orders. The Filter Wiz Pro [12] system was taken as a prototype of developed system.
Structural aspect (S) includes synthesis of structures relevant to stages. Solutions at this stage can be not numerical most of the time, they can partly be put on inventive level. Therefore the problem of searching for subsets of optimal solutions from the set of existing solutions has to be solved. In other words, the key of this aspect is not to list all of possible structural decisions, but to isolate and structure subsets of solutions that meet choice functions of every design stage according to principles of systematic approach.
Design process in the developed application goes step-by-step; each step corresponds to one of the stages of spiral design model. The user controls design process by inputting object parameters and observing the solutions that program suggests for each stage, choosing the most suitable solution for the specific object according to optimality criteria provided by the program. At each stage the user can go back at any number of the stages and change his choice or the input parameters. Changes will be set and applied, and the result of the next design stage will be different, considering the changes.
Work on constructional aspect (C) includes allocation of subsystems, components and elements and connection layout. It should be done in such a way that minimizes parasitic influence of corresponding objects on each other. In this aspect methods of optimization are widely used and CAD systems have programs for this purpose. In the frames of work on technological aspect (T) elements of the components, subsystems and the whole system are designed at physical level. As a rule CAD system of this aspect is the first to be developed for it sets parameters of all used elements, but their allocation and other peculiarities are given during work on the previous aspects.
Design IP system was developed using C# programming language in Visual Studio environment. It was made as a Windows Form application. In the main form (window) of the application the object of design is chosen, its parameters are input and the scheme of design progress is shown step-by-step. Each tab corresponds to one of the spiral model design stages applied to analog filter design. The user progresses from the left to the right, moving forwards and backwards between the tabs when necessary.
Spiral model scheme gives clear demonstration of all stages of the technical object design process according to systematic design approach and its principles. Such detailed and at the same time clear and easy understandable scheme can help simplifying the automation of design process at least at the structural aspect of design. Comparison of the described spiral model methodology with some other design methods mentioned earlier is done in
Let’s observe the working process of the application. The circuity and its parameters can be saved in the end, and the recently saved circuitries for the specific filter of certain order can be shown to user when the user restarts the program. The appropriate window
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is opened by pressing the button “Existing solutions”. On Fig.2 the main window of the application is presented.
On the next stage, “Circuitry parameters calculation”, calculation of such parameters as capacitances, inductances, resistances, is done. Calculation is fulfilled using knowledge of filter zeros and poles, which were determined earlier in the program at the “Approximation” stage, and using the formulas from the program database for calculations of parameters for different units. Current version of the program only implements calculation of Butterworth filters. Fig. 4 shows the stage of parameters calculation for Butterworth filter with order equal to five.
Fig.2. Main window of Design IP system. Titles of tabs (translated from Russian) are given in the bubble below
At the “Designed element choice” stage the user decides which type of filter to make. By default, only the choice of the low-pass filter is implemented. However, types of filters that can be done based on it are mentioned too, such as high-pass filter, band-pass filter, band-stop filter. At the “Element parameters” stage the input of filter parameters is made. For filter design the parameters that measure filter bandwidth and transmittance are needed, such as passband frequency, stopband frequency, passband attenuation and stopband attenuation. A picture is provided for the user to show clearly how these parameters are graphically described. Also, the value of load resistance is being input at this stage, which will be later needed for the filter circuitry parameters calculation. Fig. 3 demonstrates the tab of this stage.
Fig.4. “Circuitry parameters calculation” stage of Design IP system. Explanation of parameters for the first, second and third unit of the filter is given below
On the final “Tolerances” stage user chooses the row of standard values of capacitances, inductances and resistances, according to which the nominal values for the circuitry elements parameters are calculated. Several rows are provided; each of them has a different number of values so that the user would choose optimal tolerance value, which characterizes the difference between nominal value and the calculated value. As a result of the program use, the nominal values of parameters are successfully received according to user’s choice. Also on this stage user can see the plot amplitude-frequency response of the filter, by which he can esteem the transmittance qualities of the deigned filter.
Fig.3. “Element parameters” stage of Design IP system. Parameters are input in the textboxes by user
At the “Approximation” stage the user observes the result of calculation of filter amplitude-frequency response and filter order is calculated according to a chosen approximation method (Chebyshev [13], Butterworth [14] or elliptic [15]). Also the window contains the example of amplitude-frequency response of filter for the particular approximation for comparison. Fig. 2 shows the result of Butterworth filter approximation, where the calculated filter order is equal to five. Also on this stage the transfer function of the filter is determined by calculating its zeros and poles according to the chosen approximation method.
The developed application allows user to develop analog lowpass filters in automated mode, progressing step-by-step through separate stages of design, and receive the filter circuitry with nominal values of its parameters as the output.
5. Conclusions This paper observes the design methodology based on spiral design model. The advantages of this methodology, such as generality and clarity, allow using it for the automated design of technical objects and devices.
At the “Choosing construction methods” stage the choice of the construction method for circuitry is done. By default, only chain connection of passive units is implemented. This stage also provides the choice of the low-order units, which are combined into a filter of higher order. Units are chosen form the menu on the right side of the application window.
As an example of practical use of this method, a windows form application was developed. It implements step-by-step design of analog IP-cores. The design process is based on stages of spiral model. The use of the application was demonstrated: based on the input filter parameters, the circuitry of the filter with the parameters of its elements was developed in automated mode. This application may serve as an illustration of the systematic approach to design in general and also be an example of usage of the spiral model based methodology for design automation in particular. Further
At “Structure” stage the picture of filter circuitry is combined, using the units that user had chosen. It is shown to the user and the user is able to save it as an image file.
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development of this application can include widening of types of designed objects by applying new schemes and new methods for design of separate parts of the object, for example, methods of directed graphs for unit synthesis [16].
References 1. Amosov, V. Circuit design tools for digital devices. SaintPetersburg, BHV Petersburg, 2007, 560 p. (in Russian) 2. FPGA, SoC and CPLD from Altera. URL: www.altera.com 3. Larman, C., Basili, V. R. Iterative and Incremental Development: A Brief History – Computer, vol. 36 (6), 2003, p. 47– 56. 4. Royce, W. W. Managing the Development of Large Software Systems: Concepts and Techniques. in: Proceedings of the 9th international conference on Software Engineering, 1987, p. 328338. 5. Golovitsyna, M. Informational technologies of radioelectronic means design, Moscow, Binom, 2008, 432 p. (in Russian) 6. Ugrumov, E.P. Digital circuit technique. Saint-Petersburg, BHV-Petersburg, 2010, 798 p. (in Russian) 7. Molodyakov, S.A. System design of optoelectronic signal processors. Saint-Petersburg: Polytechnic University Publishers, 2011, 226 p. (in Russian) 8. Lypar, Ju. I., Molodyakov, S. A. System design methodology for analog digital optoelectronic signal processors – St. Petersburg State Polytechnical University Journal. Computer Science. Telecommunication and Control Systems, Vol. 6 (138), part1, 2011, p. 181-190. (in Russian) 9. Lipaev, N.V. System design of complex software for information systems. Moscow: SINTEG, 2002, 268 p. (in Russian) 10. Lypar, Ju. I. System design. Functional and structural aspects. – in: Cybernetics and Informatics (collected works). Polytechnica Publishing, 2006, p. 217-238. (in Russian) 11. Gavrilova, N. M., Molodyakov, S. A. Application of spiral model for design of analog filters. in: Proceedings of students conference “Informatics and cybernetics” (ComCon-2016), SaintPetersburg, 2016, p.3-5. (in Russian) 12. Schematica. Filter Wiz Pro active filter designer version 5. URL: http://www.schematica.com/active_filters/fwpro.html 13. Hagen, J.B. Radio-Frequency Electronics: Circuits and applications, Cambrige University press, 2009, 434 p. 14. Paarmann, L. D. Design and Analysis of Analog Filters: A Signal Processing Perspective. Springer Science & Business Media, 2006, 440 p. 15. Orfanidis, S. J. Lecture notes on elliptic filter design. URL: http://www.ece.rutgers.edu/~orfanidi/ece521/notes.pdf 16. Zakharov, V. K., Lypar, Ju. I. Electronic devices of automatics and telemechanics. Leningrad: Energoatomisdat, 1984, 432 p. (in Russian)
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ADVANCED CREATING OF 3D DENTAL MODELS IN BLENDER SOFTWARE Phd Tihomir Dovramadjiev Mechanical Engineering Faculty, Industrial Design Department - Technical University of Varna, Bulgaria.
[email protected]
Abstract: The development of virtual 3D dental models evolves with great pace. This is a stage of construction, which is of great importance in future developments of real manipulation, prosthetics and other activities set for execution. Concept of modeling of 3D dental models is determined on the basis of concrete requirements, factors and opportunities. A good basis for creating virtual dental models provide Blender software combined with specialized applications which improve the process of modeling. Keywords: Blender, 3D, dental, tooth, implants, open source
parametric building of virtual dental models is through specialized applications addons. These are applications that are specifically designed for the needs of 3D modeling of teeth, jaws, tissue and dental implants, abutments and dental crowns. At this stage the applications running on the latest version 2.76 Blender's are: Human teeth addon и Open Dental CAD addon [14, 15]. Human teeth addon enables direct modeling of high-quality 3D models of teeth. The virtual models are accurately modeled and tailored to the geometric characteristics of such real samples. Computer-generated full set of teeth is shown on fig. 2. The green box has covered the location that occupies Human teeth addon in the composition of Blender software.
1. Problem discussion The modeling of 3D virtual models of dental models is particularly relevant. This is done in regardless of, and by means of computer-generated environment to examine the dental specimens for purposes of science. The developed 3D models are used by designers, engineers, medical specialists, etc. Designing 3D virtual dental models is carried out through the use of methodologies for the relevant software systems. The following types of design are possible: by individual design using design tools and/or by generating parametric virtual models. The aim of this study is to determine the correct approach to develop 3D virtual dental models which have the necessary qualities, using the resources of modern open source program Blender [1, 2].
2. Objective and research methodologies A standard method for developing 3D virtual dental models of teeth, jaw tissues, dental implants, abutments and dental crowns in Blender software is to use set of tools for modeling, editing, modification and sculpturing (fig. 1) [3 - 13]. .
Fig. 2. Interface of Blender software with enabled application Human teeth addon. There is a computer-generated full set of teeth on the desktop
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(c)
The possibilities for parametric modeling are: individual computer generating of tooth (by number) or multiple computer modeling using "sup" for upper dentition and "inf" for lower dentition. The individual numbering of teeth is shown on fig. 3.
(b)
(d) (a)
Fig.1. A standard method for developing 3D virtual dental via toolbox of Blender software (a) object mode; (b) edit mode; (c) modifier; (d) sculpt mode
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Fig. 3. Individual numbering of teeth (a) upper dentition (b) a lower dentition
If necessary the set of tools in Blender software can be used combined with parametric built virtual dental models. The
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The teeth are modeled with high quality they have complied with all features. Fig. 4 shows part of the models of teeth in schematic options and 3D prepared [14].
operation panel of the Open Dental CAD addon in Blender's environment.
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Fig.6. Model of tooth number 17 (a) scheme of tooth No.17; (b) 3D model of tooth 17 by default; (c) 3D model of tooth 17 sculpt modified
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The application Open Dental CAD addon can be provided by download from the webpage https://github.com/patmo141/odc_public/wiki.
3. Conclusion
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Very well constructed variations of dental and implant 3D computer models not only from a visual standpoint, but also as a foundation on which to build, modify and alter depending on the job that needs to be realized is an opportunity that is successfully implemented in development of projects related to high-quality dental visualizations. Fully-functional applications Human teeth addon and Open Dental CAD addon are freely available for providing and integration into practice. Dental applications integrated into Blender software provide very good perspective in the workflow.
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Fig.4. Dental models (a) scheme of tooth number 11; (b) 3D model of tooth 11; (c) diagram of tooth number 14 (d) model tooth 14 Once the computer-generated model of the respective tooth is done the designer can make individual remodeling (fig.5).
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References [1]. Tihomir Dovramadjiev. Modern accessible application of the system blender in 3d design practice. International scientific on-line journal "SCIENCE & TECHNOLOGIES" Publisher "Union of Scientists - Stara Zagora". ISSN 1314-4111 140. Bulgaria, 2015. 10 - 13p. [2]. Felician Alecu, Blender Institute – the Institute for Open 3D Projects, Open Source Science Journal Vol. 2, No. 1, Economic Informatics Department, ASE Bucharest, Romania, 2010, 36 – 45p. [3]. Ami Chopine, 3D Art Essentials The Fundamentals of 3D Modeling, Texturing, and Animation, Elsevier, ISBN: 978-0-240-81471-1, USA, 2011, 249 – 252p. [4]. John M. Blain. Computer Modeling and Animation. The Complete Guide to Blender Graphics. Taylor & Francis Group, LLC. ISBN:13: 9781-4665-1704-2. UK, 2012. [5]. А.А.Прахов, Blender: ЗD-моделирование и анимация. СПб.: БХ В, ISBN 978-5-9775-0393-8, Русия, 2009, 272 с: ил. [6]. А.А.Прахов, Blender 2.6, Самоучитель — Спб «БХВПетербург» ISBN 978-5-9775-0823-0, Русия, 2013, 384 с. ил. [7]. A.A.Portniyagin, Innovative technologies used in the classroom for computer modeling, SSPI, UDK 004.42, Russia, 2014. [8]. Ami Chopine, 3D Art Essentials The Fundamentals of 3D Modeling, Texturing, and Animation, Elsevier, ISBN: 978-0-240-81471-1, USA, 2011, 249 – 252. [9]. Felician Alecu, Blender Institute – the Institute for Open 3D Projects, Open Source Science Journal Vol. 2, No. 1, Economic Informatics Department, ASE Bucharest, Romania, 2010, 36 – 45. [10]. James Chronister, Blender 3D Basics 3rd Edition, Creative commons attributionNonCommercial-share alike 3.0 Unported License, 2009,146 p. [11]. Lance Flavell, Beginning Blender - Open Source 3D Modeling, Animation, and Game Design, Apress, ISBN-13 (pbk): 978-1-4302-3126-4, USA, 2010. [12]. Regina Erak, Get started in 3D tutorials, tips and techniques to get you started in 3D art,future publishing limited, UK, 2014, 175p. [13]. Roger D. Wickes, Foundation Blender Compositing, ISBN-13 (pbk): 978-1-4302-1976-7,USA, 2009. [14]. Human teeth addon. Official website. http://byaapplication3d.blogspot.bg/p/ents-3d.html. Direct download link: http://dl.dropbox.com/u/4691790/Teeth_human.py [15]. Open Dental CAD addon. Actual webpage:
(b)
(c) Fig.5. Model of tooth number 17 (a) scheme of tooth No.17; (b) 3D model of tooth 17 by default; (c) 3D model of tooth 17 sculpt modified Human teeth addon application can be provided by download from the website http://byaapplication3d.blogspot.bg/p/ents3d.html. When used the Human teeth addon in combination with Open Dental CAD addon the opportunities to build 3D computer models dental are significantly increasing [15]. Fig. 6 shows the
https://github.com/patmo141/odc_public/wiki. link: https://github.com/patmo141/odc_public.
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Direct
download
MOLECULAR MODELING AND CREATING 3D MODELS OF CHEMICAL COMPOUNDS IN BLENDER SOFTWARE USING THE RESOURCES OF CHEMSPIDER AND OPEN BABEL Phd Tihomir Dovramadjiev Mechanical Engineering Faculty, Industrial Design Department - Technical University of Varna, Bulgaria.
[email protected]
Abstract: Creating 3D models of molecules and chemical compounds is a necessity in scientific work, which examines different states, structures, processes and interaction of molecules. This is done through the use of comprehensive 3D graphics programs as well as specialized applications containing and maintaining a database of ready-made models. The ability to work with good 3D graphics platform such as Blender combined with available resources of ChemSpider and Open Babel, builds a powerful system allowing the creation of highquality and realistic virtual models of molecules and chemical compounds. Keywords: Chemical, molecules, compounds, ChemSpider, Open Babel, Blender
1. Problem discussion The use of modern technological tools for designing molecules and compounds is an advantage that ensures reliability and speed in the workflow. Very good compatibility to the final modeling in Blender's software [1 - 10] have the utilities ChemSpider [11 - 13] providing molecular resources and Open Babel, as a tool for converting the required file formats [14 - 16]. This study aims to explore possibilities for providing the necessary virtual 3D molecules and chemical compounds used in modern practice and science.
Fig. 2. 2D view of Hydroxyapatite. Molecular Formula HCa5O13P3. Average mass 502.311 Da Monoisotopic mass 501.675964 Da ChemSpider ID 14098
2. Objective and research methodologies For the purposes of the study a 3D virtual model of Hydroxyapatite (chemical formula HCa5O13P3) will be provided. This important model is used for creation of computer simulations and animations in Blender environment with support of ChemSpider and Open Babel. ChemSpider is a freely available database based on chemical structures, that provides information on over 26 million deduplicated compounds derived from over 400 sources. These sources include a wide variety of government databases, chemical supplier catalogs, academic and commercial websites. Each of the listed sources has a brief popup description, with the full record providing a web link to the source. ChemSpider augments the default information from these sources with additional of property data (official website: http://www.chemspider.com). Possibilities of the ChemSpider free chemical database are shown on Fig. 1.
.
Fig. 3. 3D (JSmol) View of Hydroxyapatite (HCa5O13P3). (http://www.chemspider.com/ChemicalStructure.14098.html?rid=376769cf-b675-44b6-b4edc475ae68ccce). The file from the basis of ChemSpider is downloaded in * .mol format with number 14 098 (as listed in the database). To prepare HCa5O13P3 model for work first it must be synchronized with the Open Babel (fig. 4) (source Open Babel: An open chemical toolbox). Fig. 1. ChemSpider - the free chemical database. ChemSpider search engine results: Systematic Name, Synonym, Trade Name, Registry Number, SMILES, InChI or CSID In a real environment HCa5O13P3 occupies an important place in medicine and implantology in particular, where is applied as a coating and has bioactive function [17 - 19]. Fig. 2 shows 2D view of HCa5O13P3 and it's parameters. Fig. 3 shows 3D image (JSmol) of HCa5O13P3.
Fig. 4. Open Babel - open source chemical toolbox [14]
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Open Babel is a chemical toolbox designed platform which can: search, convert, analyze, or store data from molecular modeling, chemistry, solid-state materials, biochemistry, or related areas. Open Babel is a project to facilitate the interconversion of chemical data from one format to another – including file formats of various types. This is important for the following reasons: multiple programs are often required in realistic workflows; many programs have individual data formats, and/or support only a small subset of other file types; chemical representations often vary considerably (some programs are 2D; some are 3D; some use fractional k-space coordinates; some programs use bonds and atoms of discrete types.; others use only atoms and electrons; some programs use symmetric representations - others do not; some programs specify all atoms others use “residues” or omit hydrogen atoms). Open Babel Documentation Release 2.3.1. Providing (download) a fully functional open source program Open Babel can be done on the official website http://openbabel.org/, following the footsteps. Synchronization of 3D model HCa5O13P3 obtained from Chem Spider in Open Babel is provided as it is defined in the field "Input format", using format: "mol-- MDL MOL format". The working file is opening with the following data for the model shown in Fig. 4. Processing of HCa5O13P3 virtual model in PDB is possible by building a 3D coordinate system and determine the location of molecules. In the "Output format", is determined using format: "pdb - Protein Data Bank format". In panel settings are enabled: "Add hydrogens" and "Generate 3D coordinates". Following the conversion data a result is obtained with values shown in Fig. 5.
(a)
Using the same methodology other molecules and compounds can be used, to be added to the existing ones, to be modified and examined.
3. Conclusion Finding and using available open source reservoirs which have data for the needs of modern science, and especially biology, medicine, biomedicine, chemistry and others is particularly relevant at the moment. This is possible due to the rapidly increasing volume of information, delivery to accessible repositories of information and easy access. A very good example is ChemSpider, where incoming information data is scientifically confirmed. On the other side the data is easily converted to Open Babel and becomes fit for further research in Blender software, which allows to carry out many successful actions and developments on assignment.
References [1]. Tihomir Dovramadjiev. Modern accessible application of the system blender in 3d design practice. International scientific on-line journal "SCIENCE & TECHNOLOGIES" Publisher "Union of Scientists - Stara Zagora". ISSN 1314-4111 140. Bulgaria, 2015. 10 - 13p. [2]. Felician Alecu, Blender Institute – the Institute for Open 3D Projects, Open Source Science Journal Vol. 2, No. 1, Economic Informatics Department, ASE Bucharest, Romania, 2010, 36 – 45p. [3]. Ami Chopine, 3D Art Essentials The Fundamentals of 3D Modeling, Texturing, and Animation, Elsevier, ISBN: 978-0-240-81471-1, USA, 2011, 249 – 252p. [4]. John M. Blain. Computer Modeling and Animation. The Complete Guide to Blender Graphics. Taylor & Francis Group, LLC. ISBN:13: 9781-4665-1704-2. UK, 2012. [5]. А.А.Прахов, Blender: ЗD-моделирование и анимация. СПб.: БХ В, ISBN 978-5-9775-0393-8, Русия, 2009, 272 с: ил. [6]. Ami Chopine, 3D Art Essentials The Fundamentals of 3D Modeling, Texturing, and Animation, Elsevier, ISBN: 978-0-240-81471-1, USA, 2011, 249 – 252. [7]. Felician Alecu, Blender Institute – the Institute for Open 3D Projects, Open Source Science Journal Vol. 2, No. 1, Economic Informatics Department, ASE Bucharest, Romania, 2010, 36 – 45. [8]. James Chronister, Blender 3D Basics 3rd Edition, Creative commons attribution NonCommercial-share alike 3.0 Unported License, 2009,146 p. [9]. Lance Flavell, Beginning Blender - Open Source 3D Modeling, Animation, and Game Design, Apress, ISBN-13 (pbk): 978-1-4302-3126-4, USA, 2010. [10]. Roger D. Wickes, Foundation Blender Compositing, ISBN-13 (pbk): 978-1-4302-1976-7,USA, 2009. [11]. Pence, H. E. & Williams, A. (2010). ChemSpider: An Online Chemical Information Resource, Journal of Chemical Education 87 : 11231124. [12]. Crystallography Open Database (COD). Vilnius University Press. 2014. 12-13p. [13]. M. Rabie and C. M. Franck. Predicting the electric strength of proposed sf6 replacement gases by means of density functional theory. 18th Int. Simp. of high voltage engineering. South Korea, 2013. 1381 - 1386p. [14]. Noel M. O’Boyle. Open Babel. Access and interconvert chemical information. Open Babel development team and NextMove Software. Cambridge, UK, 2013. 39p. [15]. Enade Perdana Istyastono. Construction and optimization of structure-based virtual screening protocols to identify cyclooxygenase-1 inhibitors using Open Babel, spores and plants. Indo. J. Chem., Indonesia 2012, 12 (2), 141 - 145p. [16]. Geoffrey R Hutchison Chris Morley Craig James Chris Swain Hans De Winter Tim Vandermeersch Noel M O’Boyle (Ed.). Open Babel Documentation. Release 2.3.1. 2012. 145p. [17]. Abdulaziz Binahmed, Andrew Stoykewych, Ali Hussain, Brock Love, Vijay Pruthi. Long-Term Follow-up of Hydroxyapatite-Coated Dental Implants—A Clinical Trial. The International Journal of Oral & Maxillofacial Implants. Quintessence Publishing Co. 2007, 963 - 968 p. [18]. A. Jemat, M. J. Ghazali, M. Razali and Y. Otsuka. Surface Modifications and Their Effects on Titanium Dental Implants. Hindawi Publishing. Egypt, 2015. 11p. [19]. A Simunek, D Kopecka, M Cierny, I Krulichova. A Six-Year Study of Hydroxyapatite-Coated Root-Form Dental Implants. West Indian Med J 2005; 54 (6): 393 - 397p.
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Fig. 5. Open Bible data conversation (a) Input format: mol-MDL MOL format of HCa5O13P3 (b) . Output format: pdb -Protein Data Bank format of HCa5O13P3. The resulting data is saved in a file with the extension * .PDB. (HA.PDB). The file is imported into Blender software, through activation of Atomic Blender - PDB Addon (File → User Preferences → Import-Export Atomic Blender - PDB. The file containing the data for HCa5O13P3 is used for simulations, animations and visualizations for assignment. Fig.6(a) shows the configuration of the defined HCa5O13P3 and Fig.6(b) shows visualization of 3D models in Blender's environment.
(a)
(b)
Fig. 6. 3D model of HCa5O13P3 in Blender's environment (a) configuration (b) visualization
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МУЛТИМОДАЛНО ПРЕДСТАВЯНЕ НА РЕЗУЛТАТИ ОТ ИНЖЕНЕРНИ (CAE) АНАЛИЗИ В СРЕДА НА ВИРТУАЛНА РЕЛНОСТ MULTIMODAL PRESENTATION OF ENGINEERING (CAE) ANALYSIS RESULTS IN VIRTUAL REALITY ENVIRONMENT гл. ас. Бъчваров, А. Г., проф. д-р Малешков, С. Б., гл. ас. д-р Чотров, Д. И. Лаборатория по Виртуална реалност, Технически университет - София, България
[email protected] Abstract: In this article we present our concept for utilization of multimodal presentation of implicit object properties (like radiation, roughness, stress, temperature, etc.) for faster and better interpretation of engineering analysis results. The paper describes methods for binding different sensorial stimuli to represent objects’ implicit properties and their exploration in virtual environment. It also discusses the results from the conducted usability study confirming the applicability of the proposed methods. Keywords: MULTIMODAL PRESENTATION, ENGINEERING ANALYSIS RESULTS, CAE, VIRTUAL REALITY виртуалните обекти, изграждащи тази среда. Тук под мултимодално се разбира използването на няколко канала за възприятие (зрение, слух, осезание).
1. Увод Съвременните системи за компютърен инженерен анализ (CAE), използвани за симулиране, валидиране и оптимизиране на изделия са важен инструмент, който помага на конструкторите при изпълнение на техните рутинни дейности. Голям брой различни софтуерни пакети за CAE се използват широко във всички клонове на промишлеността. Модулите за числено решение в CAE пакетите генерират големи обеми от данни, които изискват специална допълнителна обработка (пост-процесинг), за да могат да бъдат разбрани и използвани от потребителите. Обикновено, представянето на тези данни става чрез визуализиране. Най-често използваният в практиката метод за визуално представяне на свойствата на симулирания обект е чрез промяна на цвета и осветяването на неговите елементи. Това става с цветни кодове (фиг. 1), които представляват скали от цветове, в които всеки нюанс или наситеност на цвета се свързва със съответна стойност на представяната величина. Това позволява на потребителя бързо и лесно да се ориентира за присъствието или разпределението на изследваното свойство в тримерното пространство.
Първичният източник на представа за характера и свойствата на виртуалните обекти е комбинация на няколко презентационни елемента, съответстващи пряко на отделните модалности, използвани в системата за виртуална реалност (фиг. 2).
Фиг. 2 Представяне на обекти във виртуална среда чрез разделянето им на презентационни елементи с различна модалност.
Това гарантира естествено възприемане от потребителя, т.е. взаимодействието с виртуалните обекти се извършва от него по познат начин, аналогичен на този, с който го прави в реалния свят. Отделните канали на перцепция се характеризират със свои специфични функции и характеристики, които ги правят уникални и ограничават възможността за тяхната смяна. Информацията от отделните сетивни канали се преработва по различен начин, а отделните презентационни елементи се комбинират и припокриват (комплементарност и редундантност), което означава, че използването на мултимодалност води и до значително разширяване и интензифициране на предаваното в рамките на взаимодействието между потребителя и обекта информационно съдържание [Morris-2006]. Допълнително предимство при използването на мултимодалното представяне е възможността за двустранно взаимодействие с потребителя. Представената информация вече не е пасивна, а може да също да оказва влияние върху потребителя.
Фиг. 1 Използване на конвенционален цветен код за представяне на температурно разпределение.
Този начин на представяне на данни е удобен и технически лесен за реализация и се използва традиционно в софтуерните пакети, но когато анализираните модели са с висока степен на комплексност или когато се налага едновременното разглеждане на няколко свойства обичайното визуално представяне на данните не е достатъчно за получаване на необходимата информация и взимане на правилното инженерно решение. Виртуалната реалност (ВР) и свързаните с нея технологии могат да предложат решение на така формулирания проблем.
2. ВР и мултимодално представяне на CAE данни
Създаването на мултимодално представяне на обектите във виртуалната среда се разделя условно на две фази: (i) фаза на създаване и (ii) фаза на реализация. В първата фаза се прави избор на начина, по-който виртуални обекти ще изглеждат, звучат и ще се усещат от
Една от характеристиките на ВР е способността ѝ да „потапя“ потребителите в изкуствено създадена виртуална среда. Това се случва чрез мултимодално представяне на
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наблюдателя. Във втората фаза, избраният начин на представяне на обектите се реализира чрез хардуерна и софтуерна система за възпроизвеждане на виртуална реалност. Фазите са свързани тясно помежду си, а качеството на получения резултат съществено зависи от специфичните технически характеристики на използваните хардуерни устройства и софтуер.
инженерни анализи във виртуалната реалност обикновено 3 от тях (зрение, слух, осезание) приемат изкуствено синтезирани от компютърната система стимули, които заместват стимулите от физическата реалност. Според [Sherm-05] по-големият брой на използваните сетивни канали води до подобрение на усещането за „потапяне“ и усещането за присъствие. Таблица 1 обобщава информацията в [SprJe-93], [Sherm-05], [Kim-05], [Sutcli-02] и представя опит за обща таксономия на ефектите във виртуалната среда, които могат да бъдат използвани за представяне на свойствата на обектите, получени от данни от инженерни анализи за трите споменати основни сетивни възприятия (визуално, слухово и осезателно). Свойствата са подредени по азбучен ред и са допълнени с информация за типа на свойствата според класификацията на [Wexel-91]. Представеният списък е непълен и подлежи на разширение и редактиране.
Изборът на подходяща форма на представяне зависи в голяма степен от целта на приложението и характера на свойствата на представените в средата виртуални обекти. В определени случаи трябва да бъде осигурена възможност за точно възприемане на количествена информация от данни, което налага потребителя да може да извлича числови стойности на базата на възприеманото от него сетивното изображение. Това може да стане пряко (чрез числови таблици) или косвено (чрез разнообразни методи за изобразяване на данни през отделните сетивни канали). В други случаи представяната информация има качествен характер или се налага комбиниране на представянето на количествени и качествени данни.
Таблица 1: Примерна таксономия на параметрите (свойствата) на виртуалната среда и на включените в нея виртуални обекти.
Визуално възприятие
На основата на комбиниране на препоръките в [Sherm-05], [Keim-02] и [Kim-05] беше развит общ практически подход за представяне на данните от инженерни анализи във виртуална среда, включващ 4 етапа: 1. Избор на свойствата за представяне; 2. Избор на презентационния елемент (ефект) на виртуалната среда, който ще предава информация за това свойство; 3. Съпоставяне на изобразяваното свойството с избрания ефект във виртуалната среда („mapping“); 4. Представяне. Броят на свойствата на симулираните обекти информация, за които се съдържа в данните от инженерния анализ, може да бъде голям и зависи от специфичните нужди на извършвания анализ. Едновременното представяне на твърде много свойства може да доведе до трудности при възприемането и когнитивно претоварване.
Параметри на обектите
(свойства)
Слухово възприятие Параметри на обектите
(свойства)
Тактилно възприятие Параметри на обектите
Ефектите за представяне на свойствата във виртуалната среда са постоянни. Тяхното съществуване се предопределя от хардуера и софтуера на използваното решение за виртуална реалност. Съответно, свойствата на виртуалната среда ограничават свойствата на съществуващите в нея виртуални обекти. Това ограничение може да бъде преодоляно чрез използването на така нареченото „сетивно заместване“ („sensory substitution“). Чрез него даден ефект, използван за представяне на определено свойство на виртуалния обект, се замества с друг, но от друга модалност. Този подход се използва и когато дадено свойство на виртуалния обект не може да бъде представено във виртуалната среда при приемливо ниво на разходите или безопасността [Sherm-05].
(свойства)
Ефект Наситеност Прозрачност Размер Разположение Текстура Форма Цветен тон Яркост Ефект Височина на тона Продължителност Разположение Сила на звука Темпо Хармония Чистота Ефект Вибрация Размер Разположение Твърдост Тегло Текстура Температура Форма
3. Методика и програмна реализация Приложени са два различни подхода за представяне на CAE данни в среда на виртуална реалност: (i) създаване на специализиран софтуерен модул като част от системата за виртуална реалност; (ii) разширяване на функционалността на стандартните софтуерни пакети за виртуална реалност. Първият подход включва добавянето на няколко допълнителни компонента към пакета за разработка на софтуерни приложения SceniX Scene Graph на NVIDIA. Вторият подход използва предимствата на функционалността на предлаганите на пазара програмни пакети за реализация на виртуална реалност и вградените им инструменти.
Дефинирането на съответствието между свойството и избрания за неговото представяне параметър на виртуалната среда е важно за постигане на добри резултати за конкретното приложение. При него се прилагат няколко принципа: представящият ефект трябва да бъде възможно най-близък до типа на свойството, което ще представя [Wexel-91]; трябва да се осигури съответствие между необходимостта от разграничаване на свойството и разграничителната способност на избрания за неговото представяне ефект. Свойството, което трябва да бъде представено, се класифицира по отношение на интервала от стойности, които може да приема и критичното (значимо) изменение на тези стойности [SprJe-93].
За да бъдат представяни данните от инженерния анализ в среда на виртуална реалност трябва да бъдат изпълнени няколко стъпки, показани в диаграмата на действията (фиг. 3). CAD моделът използван в CAE приложението трябва да бъде експортиран в подходящ файлов формат, поддържан от системата за виртуална реалност (например 3DS, VRML, COLLADA, OBJ, и т.н.). Следва задаването на свойствата към модела, които трябва да бъдат представени. За тази цел е разработен конфигуратор, който позволява на потребителя да импортира модела и да зададе свойствата към него. Всъщност, този процес представлява „налагане“ (установяване на съответствие) на стойностите на съответното свойство, информация за които се съдържа в CAE приложението, към отделните точки на виртуалния обект („мапинг“). Следва задаването на презентационните елементи (ефектите) към отделните свойства на обекта в дървото на сцената. Като
Самата технология на представяне на свойствата на обектите от данните от инженерни анализи във виртуалната среда е ключов елемент за начина и качеството, с което потребителят възприема виртуалната средата. Сетивната система на човека разполага с пет канала, които осигуряват информация на мозъка. За целите на представяне на данни от
37
резултат от горната процедура потребителят получава мултимодална обратна връзка в реално време за избраните свойства на изследвания CAD модел в среда на виртуална реалност. Конфигураторът генерира специален дескрипторен файл, който съдържа информация за зададените свойства на обектите. За да бъде разгледана и/или променена създадената в среда на виртуална реалност сцена, изградена от пространствено и темпорално организирани обекти, се стартира приложението за виртуална реалност. Направени са имплементации за два основни типа хардуерни конфигурации: • за десктоп компютър или мобилно устройство и • за компютърен клъстер за имерсивна прожекционна система.
субективна промяна за потребителя на информационното съдържание на обектите при представяне на данните за техните свойства от CAE данни, [Marc-2006]. Беше изготвен тестов сценарий за извършване на изследването, който използва термо-структурен изчислителен модел на бойлер, показан на фиг. 1. За създаване на изходния CAD модел е използван Creo Parametric, а самата симулация е направена с ANSYS. Тестовият сценарий включва 7 задачи, които оценяващото лице – респондент трябваше да изпълни последователно на две специално оборудвани работни места. Едното работно място е мобилна десктоп система за стереоскопична визуализация, включваща лаптоп, 3D телевизор, таблет и безжични слушалки (фиг. 4-вляво), а второто е система за имерсивна прожекция в мащаб 1:1 (фиг. 5-вдясно).
Създаване на модел/сцена в DCC/CAD приложение
Експортиране на виртуалния модел/сцена
Зареждане на сцена в конфигуратора
Избор на виртуален обект от сцената
Фиг. 4 Използвани в експериментите мобилна (вляво) и имерсивна (вдясно) системи за виртуална реалност
Избор на имлицитно свойство, характеризиращо избрания обект
Избор на сетивен стимул (ефект) за представянето на имлицитното свойство
Задаване на стойности на имплицитното свойство
Добавяне на избрания ефект към списъка с ефекти на избрания обект
[всички ефекти са зададени]
Запаметяване на ефектите
Фиг. 3 Обобщен алгоритъм за задаване и промяна на неявни свойства на виртуални обекти.
4. Резултати и дискусия
Самият експеримент за проверка на използваемостта е изпълнен по следния начин: лицето – респондент се запознава с целта на експеримента, получава копие от задачите и започва самостоятелна работа. След прочитане на условието на задачата, лицето я изпълнява и веднага след това попълва специален въпросник, в който отговаря на контролни въпроси, регистриращи неговите субективни усещания от използването на обекти, разширени с допълнителни имплицитни свойства във виртуална среда. За отговорите се използва 5 степенна неутрална скала или се избира между Да/ Не/ Не мога да преценя. След завършване на изпълнението на задачите, респондентът отговаря и на допълнителни въпроси, които регистрират цялостните му впечатления и опит по време на работа. Също така посочва в отворена форма, какво според него трябва да бъде променено и какво му е създало проблем. Времето, с което разполага за изпълнение на теста е неограничено.
В експеримента за проверка на използваемостта на обекти, допълнени с имплицитни свойства във виртуална среда чрез евристична оценка участваха 12 лица със средна възраст 25,4 години. Подборът е случаен в съответствие с принципите на така наречения и широко използван при проверката па използваемостта метод на коридора (Hallway method), при който се използват не професионални, случайно избрани („взети от коридора“) оценители. За целите на анализа, групата от 12 оценяващи лица се разделя на 2 подгрупи: (i) обикновени потребители и (ii) експерти съставени от съответно 7 и 5 лица.
[Burdea-2003] разглежда виртуалната реалност като високо усъвършенстван потребителски интерфейс. На базата на това определение и поради липса на литературни сведения за специфични методи за верификация на начините на взаимодействие на потребителя с обектите от виртуалната среда за целите на изследването беше прието използване на модифициран вариант на обичайната за потребителските интерфейси Проверка на използваемостта (Usability Testing). Избран е методът Евристична оценка (Heuristic evaluation), предложен в с широко приложение в практиката [Cockton et al.-2003]. Той служи за определяне на проблемите при използване на потребителски интерфейси в ранна фаза на процеса на проектирането им. Евристичната оценка включва участието на малка група респонденти, които оценяват съответствието на интерфейса с определени набори от принципи (известни като евристики), описани подробно в [Nielsen-2005]. Разработеният модифициран вариант за проверка на използваемостта се фокусира върху изследването на пет основни аспекта, обединяващи различни групи евристики (по приетата за използване целите на изследването класификация, предложена в [Weinschenk-2000]): (i) възприемане и (ii) чувствителност на потребителя, (iii) влияние на представянето върху възможността за използване на работната (виртуална) средата, (iv) взаимното влияние между отделните свойства и начините на тяхното представяне и (v)
Резултатите от проведения експеримент показват, че за 75% от оценителите комбинираното използване на цветно и звуково кодиране за представяне на свойствата на обектите е удобно. По отношение на използването на тактилен стимул (вибрация) като модалност за представяне на допълнително имплицитно свойство, 58 % от оценителите намират, че той дава допълнителна информация. Само за 1 респондент това не е така, останалите се колебаят. По-голямата част от колебаещите се са от извадката на експертите. След допълнителен разговор с тях беше установено, че тяхната несигурност се дължи основно на рутинния начин на работа с CAD системи, с който те са свикнали и ограниченото време, през което са имали възможност да използват новия механизъм на взаимодействие. 75% от оценители са на мнение, че представяне на обекта в имерсивна система за виртуална реалност подобрява
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възприемането му от потребителя като в извадката на експертите оценката е категорична (100 %) за полезността на този начин на работа. На фиг. 5-вляво е показано средната оценка на групата респонденти, на базата на субективните им впечатления по отношение на информацията за свойствата, която получават при разглеждане на обекта в среда на виртуална реалност, в която се използва комбинация на различни модалности за представяне на имплицитните му свойства. Легенда:
1. Стереоскопичната визуализация 2. Добавяне на звуково кодиране 3. Добавяне на тактилни стимули (вибрация) 4. Комбиниране на няколко начина на кодиране 5. Визуализиране в мащаб 1:1 Фиг. 6 Елементи, подобряващи възприемането на свойствата на обекта във виртуална среда, средна оценка на цялата група.
Фиг. 5 Средната оценка на оценителите при разглеждане на обекта в среда на виртуална реалност (вляво) и сравнение на резултатите от експертна група и обикновени потребители (вдясно).
5. Заключение
Цифровите означения в диаграмите, показани на Фиг. 5 имат посочения в Таблица 2 смисъл. Там са дадени и усреднените оценки на оценителите за качеството на получаваната информация, заедно със съответните стандартни отклонения.
На базата на получените в рамките на изследването на използваемостта резултати може да се направи следното заключение: представянето на данни от CAE анализи чрез различни модалности в среда на виртуална реалност води до увеличаване на обема и подобряване на възприемането на информацията от потребителя. Потребителите оценяват тази информация като ясна, логична, представена по интуитивен начин, непротиворечива и важна. Възприемането на представените в среда на виртуална реалност данни е свързано с известни първоначални затруднения, които увеличават времето за постигане на поставената цел поради непознаване на конвенциите на използваната скала на стимулите на кодирането за различните ефекти. По тази причина потребителите не смятат в определени случаи допълнително получената информация за еднозначна. Това налага период за запознаване и обучение за използване на новите възможности или конфигуриране на стимулите за отделните модалности според личните предпочитания и специфичните когнитивни ограничения на потребителите. Неприятните усещания, които се срещат при някои от потребителите при продължителен престой във виртуална среда налагат използване на специализирани интерфейсни устройства с подобрени характеристики. Представеното изследване е извършено по изследователски проект, финансиран от ФНИ по дог. ДУНК01/3.
Таблица 2: Усреднена оценка на получената информацията за свойствата на обектите, която възприемат оценителите Стандартно Показател Оценка отклонение 1. Информацията е ясна 4.25 0.59 2. Информацията е логична
4.00
1.15
3. Информацията е еднозначна
3.66
0.84
4. Информацията се възприема по интуитивен начин
4.08
0.86
5. Информацията е непротиворечива
3.75
0.92
6. Информацията е допълваща
4.08
1.18
7. Информацията е важна
4.16
0.79
Ясно се вижда тенденцията респондентите да определят получената информация като ясна, логична, еднозначна, възприемана по интуитивен начин, непротиворечива, допълваща и съществена. Оценките са около 4 с ниско стандартно отклонение. Най-ниска е стойността за показателя еднозначност - 3.66. При допълнителен разговор с участниците в експеримента беше установено, че това се дължи на първоначалното объркване при изпълнение на задачата за комбиниране на цветно и звуково кодиране, без наличие на подробни указания за начина на използване на звуковия код.
6. Литература [Burdea2003] [Cockton et al.-2003]
Фиг. 5 (дясно) показва сравнение на средната оценката между двете извадки от цялата група оценители. Разлика между експертите и обикновените потребители от 0.5 има само по отношение на еднозначността и важността на получената допълнителна информация за свойствата на обекта в среда на виртуална реалност. Експертите оценяват по-високо важността ѝ и са по резервирани по отношение на еднозначността ѝ по посочените по-горе причини. Мнението на оценителите (цялата група) за това, какво подобрява значително представата за свойствата, които носи разглеждания в средата на виртуална реалност обект е обобщено на фиг. 6. От графиката се вижда, че двата елемента, които имат най-висок принос за по-доброто възприятие на свойствата са комбинирането на няколко начина на кодиране (т.е. използването на няколко различни модалности за представяне на свойствата на обекта) и използване на визуализация в реален мащаб (т.е. използване на системата за имерсивна визуализация на виртуална реалност). Освен това и стереоскопичната визуализация и добавянето само на звукови или само на тактилни стимули към конвенционалния начин на представяне имат ползотворен ефект според оценителите.
[Keim-02] [Kim-05] [Marc-2006] [Morris2006] [Nielsen2005] [Sherm-05]
[Sutcli-02] [Weinschenk2000] [Wexel-91
39
Burdea, Grigore C. and Coiffet, P. (2003): Virtual Reality Technology, Wiley-IEEE Press; 2 edition Cockton, G., Lavery, D., and Woolrych, A., (2003). Inspection-based methods. In J.A. Jacko and A. Sears (Eds.), The Human-Computer Interaction Handbook. Mahwah, NJ: Lawrence Erlbaum Associates. Keim, Daniel (2002): Information Visualization and Visual Data Mining. IEEE Transactions On Visualization And Computer Graphics, Vol. 7, No. 1, January-March 2002 Kim, Gerard (2005): Designing Virtual Reality Systems: The Structured Approach. Springer, London Marc, J., Belkacem, N., Marsot, J., Virtual reality: a design tool for enhanced consideration of usability "Validation elements", 9th International symposium of ISSA research comity, Nice, France, 2006 Richard Morris, Lionel Tarassenko, Michael Kenward (2006): Cognitive Systems: Information Processing Meets Brain Science. Academic Press. Nielsen, J., (2005). Ten Usability Heuristics. Jakob Nielsen’s Alertbox. http://www.useit.com/papers/heuristic/heuristic_list.html. William R. Sherman and Alan B. Craig. Understanding Virtual Reality: Interface, Application, and Design. Morgan Kaufmann San Francisco, 2005 Alistair Sutcliffe (2002), Multimedia and Virtual Reality: Designing Usable Multisensory User Interfaces L. Erlbaum Associates Inc. Hillsdale, NJ, USA. Weinschenk, S and Barker, (2000) Designing Effective Speech Interfaces. Wiley. Wexelblat, A., (1991): Giving Meaning to Place: Semantic Spaces. In Michael Benedict(ed.)
THE PROBLEM OF OVERLAPPING PROJECT ACTIVITIES WITH INTERDEPENDENCY Prof. Gurevich G., Prof. Keren B., Prof. Laslo Z. Department of Industrial Engineering and Management – SCE-Shamoon College of Engineering, Beer Sheva, Israel
[email protected],
[email protected],
[email protected]
Abstract: This paper analyzes a simple project with two activities. The activities can be executed in a serial mode (separately), in a parallel mode (overlapping), or in a mixed mode (partly in a serial mode and partly in a parallel mode). There is interdependence between the activities and the duration-budget tradeoffs functions of the activities are defined differently for each execution strategy. The paper presents a deterministic duration-budget tradeoff model that takes into account the interdependence between the activities in order to determine the optimal execution-mode and the budget distributions among the project activities. A stochastic extension of the proposed model is also considered. The presented analysis can help project managers and practitioners in choosing the optimal overlapping strategy for different objective functions and constraints. Keywords: DURATION-BUDGET TRADEOFF, OVERLAPPING, INTERDEPEBDENCE, TIME CONSTRAINT.
If the two activities are executed separately, then the durationbudget tradeoff functions for the first and second activities are defined by the following equation
1. Introduction There are three main techniques for project time compression: activity crashing, substitution and overlapping (Hazini et al. [1]). Crashing is a schedule compression technique in which cost and schedule tradeoffs are analyzed to determine how to optimize the best schedule compression for the least cost (Laslo and Gurevich [2]-[5], Laslo et al. [6]). Activity substitution involves the replacement of one activity or a sequence of activities in a series by other activities. Overlapping is a schedule compression technique in which activities that normally executed in sequence, are executed in parallel. Terwiesch and Loch [7] claimed that overlapping research and development activities are widely used to reduce project completion times. Dehghan et al. [8] restated that for a typical construction project, a number of overlapping strategies exist which can result a timesaving. The cost of these strategies varies significantly depending on the total rework and complexity they generate. Therefore, the best overlapping strategy that generates the required timesaving at a minimum cost should be found. This paper analyzes a simple project with two activities. The activities can be executed separately, with overlapping (in a parallel mode), or in a mixed mode (partly separately and partly in a parallel mode). There is interdependence between the activities and the duration-budget tradeoff functions of the activities are defined differently if the activities are executed separately, in a parallel mode or in a mixed mode. The presented deterministic durationbudget tradeoff model takes into account the interdependence between the activities and helps to determine the optimal strategy for different objective functions and constraints. In particular, the model allows to determine: 1) the optimal execution-mode that minimizes the total project duration given that the budget of each activity is already allocated; 2) the optimal execution-mode and the budget distribution that minimize the total project duration, given a fixed total budget that should be optimally distributed among the activities; 3) the optimal execution-mode, the budget size and the budget distribution among the activities that minimize the total expenses, given the penalties/bonuses for a delay/early completion time; 4) the optimal execution-mode and the budget distribution that minimize the total budget for the project, given a constraint on the completion time of the project. A stochastic extension of the proposed model is also being considered. In the stochastic context, the activities durations are random variables where the expected values of the durations are results of the budget size that is invested in each activity
t1 = f1 ( b1 ) ,
(1)
t2 = f 2 ( b2 ) , where, ti is the in series,
bi
i ’s activity duration if both activities are executed
is the budget allocated to activity
i , biN ≤ bi ≤ biC ,
biN is the known normal (minimal) budget that can be allocated to activity i , biC is the known crash (maximal) budget that can be
allocated to the activity, fi ( bi ) is the estimated (known) durationbudget tradeoff, a decreasing function that characterizes the duration of the i ’s activity when both activities are executed in series. The end points of the function
fi ( bi ) are the normal
(maximal) duration fi ( biN ) corresponding to the known normal (minimal) budget
biN ,
and the crash (minimal) duration,
fi ( biC ) corresponding to the known crash (maximal) budget
biC , fi ( biC ) ≤ fi ( bi ) ≤ fi ( biN ) , i = 1, 2 .
If the two activities are executed in parallel, then the durationbudget tradeoff functions for the first and second activities are defined by the following equation
t1* = f1* ( b1 ) , t*2
=
where,
(2)
f 2* ( b2 ) ,
t*i is
the
i ’s
activity duration if the two activities are
executed in parallel, fi* ( bi ) is the estimated (known) durationbudget tradeoff, a decreasing function that characterizes the duration of the i ’s activity if both activities are executed jointly. The end points of the duration-budget tradeoff function fi* ( bi ) are the normal (maximal) duration fi* biN corresponding to the known normal (minimal) budget biN , and the crash (minimal)
(
2. Model description The duration-budget tradeoff functions for activities i = 1, 2 are defined differently for situations where the activities executed separately or jointly.
)
duration, fi* ( biC ) corresponding to the known crash (maximal) budget biC , fi* ( biC ) ≤ fi* ( bi ) ≤ fi* ( biN ) ,
40
i = 1, 2 .
f b If f * ( b ) 1 − 2 ( 2 ) − f ( b ) < 0 then equation (5) has the 1 1 1 1 f 2* ( b2 ) unique solution
The model assumes that the rate of execution of both activities is constant. Let x and y be decision variables that defined the portions of the first and the second activity, respectively, that are executed
jointly,
= 0 ≤ x x ( b1 ,b2 ) ≤ 1 ,
1 if f 2* ( b2 ) ≥ f1* ( b1 ) , f 2* ( b2 ) * * if f 2 ( b2 ) < f1 ( b1 ) * f1 ( b1 ) f (b ) then each f1* ( b1 ) 1 − 2 2 − f1 ( b1 ) = 0 * f b ( ) 2 2
= 0 ≤ y y ( b1 ,b2 ) ≤ 1 . Then, by (1)-(2), the total durations of the two activities are:
xt1* + (1 − = x ) t1 xf1* ( b1 ) + (1 − x ) f1 ( b1 ) ,
f * ( b ) 2 2 = = x* min 1, * f1 ( b1 ) (3) If
yt*2 + (1 − = y ) t2 yf 2* ( b2 ) + (1 − y ) f 2 ( b2 ) , respectively. Moreover, since
x ∈ 0 ,min 1,
xf1* ( b1 ) = yf 2* ( b2 ) , then by
*
equation (3) the total duration of the project is
xf1* ( b1 ) + (1 − x ) f1 ( b1 )
= t
+ 1 − x
f1* ( b1 ) f 2 ( b2 ) . f 2* ( b2 )
Let b be an additional available budget that can be added to the normal (minimal) budget of the project's activities, b1N + b2 N ,
0 ≤ b ≤ ( b1C + b2C ) − ( b1N + b2 N ) , and bai
0 ≤ bai ≤ biC − biN , i = 1, 2 .
project activity
i ’s
That is, the
budgets that can be allocated to the first and second project activities are = b1 b1N + ba1 , = b2 b2 N + ba 2 , respectively,
3.1. The optimal strategy that minimizes the total project duration given a fixed budget allocated to each activity
ba 2= b − ba1 . The considered problem is to minimize the project duration, t , given the amount b of the additional
where
total budget. In other words, the problem is to determine values
The considered problem is to minimize the total duration of the
t , given the values of b1 and b2 , b1N ≤ b1 ≤ b1C , b2 N ≤ b2 ≤ b2C . It means that the problem is to determine the
project,
* ba1 = b*a1 and x = x of equation (4) such that
x = x* that minimizes the total duration of the project. Since 0 ≤ x ≤ 1 , 0 ≤ y ≤ 1 , then the optimal portion of overlapping x * can be expressed by equation (4) as follows
(b*a1,x* )
value
xf * ( b + b ) + (1 − x ) f ( b + b ) 1 1N a1 1 1N a1 * , = arg min f (b + b ) ( ba1 ,x )∈A + 1 − x 1 1N a1 f 2 ( b2 N + b − ba1 ) f 2* ( b2 N + b − ba1 )
x* = xf * ( b ) + (1 − x ) f ( b ) 1 1 1 1 * arg min . f1 ( b1 ) f 2 ( b2 ) f * ( b ) + 1 − x * f 2 ( b2 ) 0 ≤ x ≤ min 1, 2 2 *
be an additional
budget that can be added to the normal (minimal) budget of the
This section analyses the optimal working strategies and budget distributions among the project activities in the context of four different objective functions.
(5)
(6)
( ba1 ,x ) : 0 ≤ ba1 ≤ min {b,b1C − b1N } , f * ( b ) A= . 2 2 0 ≤ x ≤ min 1, * f1 ( b1 )
f1 ( b1 )
*
The following Proposition 1 presents the solutions x of equation (5). Proposition 1. Given values of b1 and b2 ( b1N ≤ b1 ≤ b1C ,
Equation (6) is a standard mathematical programing problem of minimization of a function with two decision variables, ba1 and
* b2 N ≤ b2 ≤ b2C ), the solutions x of equation (5) are defined as
x.
follows.
3.3. The optimal strategy and the budget distribution that minimize the total project expenses given the penalties for a delay and the bonuses for earlier completion time
f 2 ( b2 ) − f1 ( b1 ) > 0 then equation (5) has f 2* ( b2 )
the unique solution
f 2* ( b2 ) is a solution of equation (5). f1* ( b1 )
3.2. The optimal strategy and budget distribution that minimize the total project duration given a fixed total budget for the project
(4)
3 Analysis of working strategies and budget distributions among the project activities
If f1* ( b1 ) 1 −
Let t0 be a given agreed completion time of the project. The
*
x = 0,
known function
g ( t − t0 ) defines penalties/bonuses for a delayed/
earlier completion time. That is,
g ( t − t0 ) ≤ 0 41
if
g ( t − t0 ) ≥ 0 if t ≥ t0 , and
t ≤ t0 . The total project expenses are defined as
c = b1 + b2 + g ( t − t0 ) , where
If the two activities are executed jointly, then the durationbudget tradeoff functions for the first and the second activities are defined by the following equation
(7)
biN ≤ bi ≤ biC , i = 1, 2 , t = t ( b1 ,b2 ,x ) are defined by
*
t1 equation (4). The considered problem is to minimize the total = project expenses c as defined by equation (7). Thus, the problem is
to determine the values bi = bi* ,
* * * (b= 1 ,b2 ,x )
= t*2
i = 1, 2 , and x = x* such that
arg min {b1 + b2 + g ( t − t0 )} ,
( b1 ,b2 ,x )∈B
(8)
{
(
≤ bi ≤ biC ,
{
i = 1, 2 ,
}
t ≤ t0 , where t
E (t )
arg min
{b1 + b2 }
)
(
E xt* xt* ≤ yt* ,t* + 1 − x E t ( ) ( 1 ) 1 1 2 2 1 = E + 1 − E xt1* xt1* ≤ yt*2 ,t*2 E ( t2 ) * t2 × P xt1* ≤ yt*2 t*2
(
(12)
)
(
is
defined by equation (4). Thus, the problem is to determine the values bi = bi* , i = 1, 2 , and x = x* such that
( b1 ,b2 ,x )∈B
}
project, t , are random variables. Straightforwardly, by the law of total expectation, it can be shown that the expected value of the total duration of the project is
considered problem is to minimize the total budget, b1 + b2 , subject to a given time constraint on the total duration,
)
0 ≤ y y b1 ,b2 ≤ 1 are decision = 0 ≤ x x ( b1 ,b2 ) ≤ 1 and = variables. The rest of the activities should be executed in a serial mode. The rate of execution of both of activities is assumed to be constant. In this framework, the duration where both activities are executed in parallel, min xt1* , yt*2 , and the total duration of the
Assume a situation where there is a time constraint on the total duration of the project, t ≤ t0 , where t0 is a known value. The
)
)
The strategy for project execution in the stochastic case can be defined as follows. The two activities should be executed in parallel until a portion x of the first activity or a portion y of the second activity will be completed, where the variables
3.4. The optimal strategy and budget distribution that minimize the total needed budget given a time constraint on the total duration
(
) (
(
0 ≤ x ≤ min 1, f 2* ( b2 ) / f1* ( b1 ) ).
= b1* ,b*2 , x*
f 2* ( b2 ) + ε *2 ( b2 ) .
E= ε1* ( b1 ) E= ε *2 ( b2 ) 0 .
Equation (8) is a standard mathematical programing problem of minimization of a function with three decision variables: b1 , b1 and ( biN
(11)
where, fi* ( bi ) is defined as in equation (2), i = 1, 2 , ε1* ( b1 ) and ε *2 ( b2 ) are independent random variables with zero expectations,
( b1 ,b2 ,x ) : b1N ≤ b1 ≤ b1C ,b2 N ≤ b2 ≤ b2C , f * ( b ) B= . 2 2 0 ≤ x ≤ min 1, * f1 ( b1 )
x
f1* ( b1 ) + ε1* ( b1 ) ,
)
yt* + (1 − y ) E ( t ) 2 2 1 * * * + 1 − yt* E 2 * xt1 > yt2 ,t2 E ( t1 ) +E t 1 * * * × P xt1 > yt2 t2
(9)
s.t. t ≤ t0 ,
(
where B is defined in equation (8). This is also a standard mathematical programming problem.
)
4. A stochastic extension of the model In this section, the durations of the activities i = 1, 2 are assumed to be random variables. Similarly to the model presented in section 3, the duration-budget tradeoff functions for activities i = 1, 2 are defined differently when the activities are executed in a serial mode or in a parallel mode. If the two activities are executed separately, then the durationbudget tradeoff functions for the first and the second activities are defined by the following equation
= t1
f1 ( b1 ) + ε1 ( b1 ) ,
= t2
f 2 ( b2 ) + ε 2 ( b2 ) .
In a stochastic framework, equation (12) will be used instead of equation (1). Thus, the optimal strategies and the budget distribution among the project activities for the stochastic case can be analyzed in a similar way as was presented in section 3 for different objective functions.
5. Conclusions In a real life projects have interdependency among their activities, and a parallel execution-mode may increase or decrease the activity duration and the total completion time of a project. We believe that the proposed analysis will help practitioners to select the optimal execution-mode, which is not trivial in the general case and can be a mixed one. Future research is needed to solve the stochastic problems for different distribution functions of project activities durations and to generalize the presented analysis for large projects with many activities.
(10)
( )
where, bi , fi ( bi ) are defined as in equation (1), i = 1, 2 , ε1 b1 and ε 2 ( b2 ) are independent random variables with zero expectations,
= E ( ε1 ( b1 ) ) E= (ε 2 ( b2 ) ) 0 .
42
6. References 1. Hazini, K., Dehghan, R. and Ruwanpura, J.Y. (2013). A heuristic method to determine optimum degree of activity accelerating and overlapping in schedule compression. Canadian Journal of Civil Engineering, 40(4), pp: 382-391. 2. Laslo, Z. and Gurevich, G. (2015). Planning and controlling projects under uncertainty. American Journal of Operational Research, 5(3), pp: 47-56. 3. Laslo, Z. and Gurevich, G. (2014). Enhancing project on time within budget performance by implementing proper control routines. Management, 72, pp: 53-69. 4. Laslo, Z. and Gurevich, G. (2013). PERT-type projects: timecost tradeoffs under uncertainty. Simulation: Transactions of the Society for Modeling and Simulation International, 89(3), pp: 278-293. 5. Laslo, Z. and Gurevich, G. (2007). Minimal budget for activities chain with chance constrained lead-time. International Journal of Production Economics, 107(1), pp: 164-172. 6. Laslo, Z., Gurevich, G. and Keren, B. (2009). Economic distribution of budget among producers for fulfilling orders under delivery chance constraints. International Journal of Production Economics, 122(2), pp: 656-662. 7. Terwiesch, C. and Loch, C.H. (1999). Measuring the effectiveness of overlapping development activities. Management science, 45(4), pp: 455-465. 8. Dehghan, R., Hazini, K. and Ruwanpura, J. (2015). Optimization of overlapping activities in the design phase of construction projects. Automation in Construction, 59, pp: 8195.
43
IMPROVING PROCEDURES OF TRAINANG EMPLOYEES BY IMPLEMENTING GUIDANCE CARDS SAFE METHODS AND TECHNIQUES OF WORK СОВЕРШЕНСТВОВАНИЕ ПРОЦЕДУРЫ ОБУЧЕНИЯ ПЕРСОНАЛА ПУТЕМ ВНЕДРЕНИЯ ИНСТРУКТИВНЫХ КАРТ ПО БЕЗОПАСНЫМ МЕТОДАМ И ПРИЕМАМ ТРУДА Associate Professor of the Department of industrial safety and environmental protection, Ph.D. Afanasyeva I.V. 1, Graduate student of the Department of industrial safety and environmental protection Fatkhutdinov R. I. 2, The department of industrial safety and environmental protection 1, 2 - Ukhta State Technical University, Russian Federation
[email protected] 1,
[email protected] 2 Abstract: Training and examination of working professions employees (further – workers) of the organisations, that are controled by Federal department of ecological, technological and nuclear supervision in Russian Federation (further – Rostechnadzor) of occupational Safety and Health and in the field of safety – it is one of the key factors in creating conditions for trouble-free operation of hazardous production facilities (further – HPF) and reduce industrial injuries at these facilities. This article provides an overview of the existing system of training and examination of workers on occupational health and safety and industrial safety, revealed its main gaps. The development and implementation of guidance cards safe methods and techniques of work are revealed, as a form of industrial instructions. KEYWORDS: GUIDANCE CARDS, INDUSTRIAL INSTRUCTION, TRAINING, EXAMINATION, INDUSTRIAL SAFETY, OCCUPATIONAL HEALTH AND SAFETY, INDUSTRIAL INJURIES, EXTRACT, TRANSPORTATION, OIL
1. Introduction Training and examination on occupational Safety and Health and in the field of safety of workers employed in the HPF takes an important role in the preparation of skilled and highly-qualified workers; it is a guarantee of trouble-free operation of the HPF and the absence of industrial injuries at these facilities. Therefore, training of workers begins from the moment of hiring and continues consistently during the employment.
2. Preconditions and means for resolving the problem Analysis of Rostechnadzor’s statistical data on accidents and industrial injuries at the facilities of oil and gas industry of the Russian Federation from 2004 to 2015 shows that every third event occurred through the fault of human error associated with the violation of the requirements of the organisation and production of hazardous works. For example, in 2015, 17 accidents occurred only in oil and gas production facilities, of which 4 accidents were caused by human error. In turn, the human error associated with the violation of the requirements of the organisation and production of the work, due to the following factors: - Dismissive attitude to the demands of workers in the field of industrial safety and occupational Safety and Health; - The absence or lack of knowledge and skills among workers in the field of industrial safety and occupational Safety and Health. The number of occupational accidents with a fatal outcome on Russian oil and gas industry facilities in 2015 was 19 cases , 10 cases ( 53 % ) more compared to the same period in 2014 (see Figure 1). In 2015, there was 7 groups of accidents that was 1 case more than in 2014. Thus, the analysis of statistical data shows that the issue of training and examination of workers is urgent.
Fig. 1 - The data on accidents and injuries at the facilities of the oil and gas industry of Russia for 2015
3. The solution of the problem In the Russian Federation the duty to provide training and examination of workers assigned to the employer according to the law [6, 7]. Organizational issues and requirements for the training and education of workers on occupational Safety and Health and industrial safety are specified in the Order training [3], GOST 12.0.004-90 [1] and RD 03-20-2007 [4]. Figure 2 shows the current system of training and examination of occupational health and safety of workers at hazardous production facilities. As seen in Figure 2, the training of workers in safe methods and techniques of work carried out with the use of instructions on occupational Safety and Health and industrial instructions [5]. If now the development of instructions on occupational Safety and Health based on the Methodical recommendation [2], the development of industrial instructions , according to RD 03-202007 [4] , carried out on the basis of accepted standards in the oil and gas company. It should be noted that there is no methodical recommendation for the development of industrial instructions neither in RD 03-20-2007 [4] nor in other normative-legal acts of the federal level. Thus, the content of the industrial instructions and their correctness depends on the knowledge, experience, competencies of employees who develop these instructions. In this connection, it is proposed to use the instructional cards for training workers in safe and working methods. The main support and the basic elements of guidance cards are structured and visual means of presenting information.
44
Fig. 2 - The current system of training and examination of occupational health and safety and industrial safety of workers at hazardous production facilities This section also identifies the necessary and used special work clothes, safety shoes, personal protective equipment, respiratory protective equipment, tools, materials, etc. in the performance of work.
4. Results and discussion As a result of the research and practice of drawing up guidance cards, the template was formed. Purpose of the guidance cards: prevention of accidents, incidents, industrial injuries at hazardous production facilities, including objects of oil and gas extraction and transportation. Guidance card includes the information provided below. Title: Guidance card safe methods and techniques of work with (specify the name of the type of work). Part 1. Characteristics of the equipment (see Figure 3) It consists of a description of the characteristics of the used equipment, technical devices. This section should briefly provide information on the equipment used with graphic materials.
Fig. 4 - Example of Part 2 of guidance card
Fig. 3 - Example of Part 1 of guidance card Part 2: Safety requirements for the performance of work (Figure 4, 5) In the second part of the guidance card details the harmful and dangerous production factors are designed which can lead to an accident, incident or industrial injuries. It is important to specify the methods for safe, trouble-free operation and techniques reduce or eliminate the impact of these factors on the workers. For clarity, it is desirable to accompany the text part with drawings.
Fig. 5 - Example of Part 2 of guidance card
45
Part 3: Procedure for the performance of work (Figure 6, 7) The main part of the guidance card, where a detailed operations algorithm is performed for the workers compliance with safe practices and methods of work. This part of the guidance card is advisable to split into 3 sections: I – the beginning of work, organisational activities. Specifies the procedure for admitting workers to perform work, the availability and the filling of the necessary documents, the requirements for protective clothing, personal protective equipment, respiratory protective equipment, tools and materials. While learning the section I of guidance card worker must learn how the admission to the works is carried out and which the necessary tools and materials he has to prepare prior to performing the works themselves. II – execution of works. Main part. It specifies the order of the main part of the work. III – completion of work. It determines the order of completion, to restore order in the workplace, filling in the necessary documents to complete the work . All forums at the guidance card are issued in the form of a table with the following information: a) The first column « Number of the operation». Numbers are listed in chronological order of operations. b) The second column: «The content and sequence of elements of the operations (the amount of the employees). Particular attention during the operation». The column is the primary table and is divided into columns by the number of employees participating in the execution of works. The columns indicate the position (profession) of the employee. This section describes the operations performed by the employees in chronological order. The section should be performed in the most concise, clear and intuitive way to the employees. Description of performed elements of operations must be uniformly understood and should not be interpreted by each worker in different ways. At the same time it is also important to specify the place occupied by the employee during the operation. In each cell the picture, describing these actions is attached with a description of the operation element. Subject to the conditions, restrictions, warnings, to which the employee must pay special attention during the operation. These the conditions are described by the word «CAUTION» (It is drawn in red to indicate a particular importance of the operation and attract the attention of the worker to the item). We give photos or graphics for clarity and better understanding of working memory and information. Conditions labeled «CAUTION» must be indicated before or after the description of operation, depending on the time period in which the employees must pay attention to them, i. e., in chronological order.
Fig. 7 - Example of Part 3 of guidance card
5. Conclusion Thus, guidance cards as a form of industrial instructions of safety have the following advantages: - A clear idea and a detailed description of the performing each operation by employees; - Emphasising employees’ attention to important points in the works, affecting their safety and the safety of the facility; - The formation of the visual memory of the employee while learning guidance cards; - The exclusion of inaccurate definitions and operations that increase the chance of errors; - Reduction of work time without reducing the level of safety of the facility and the employee. Apart from the obvious advantages, guidance cards have disadvantages. The main disadvantages are: - The impossibility of the maximum inclusion of all local regulatory documents of the Company in the Guidance card; - The inability to specify and complete details of some types of work; - Duplication of local regulatory documents of the Company; - Labor-intensive; - The need to involve experts in various fields; - The impossibility of taking pictures of certain types of work.
6. References 1. GOST 12.0.004-90. Meghgosudarstvenniy standart. Sistema standartov bezopasnosti truda. Organizatsiya obucheniya bezopasnosti truda.Obchie pologeniya. Utv. i vveden v deisstvie Postanovleniem Gosstandarta SSSR ot 05.11.1990 N 2797. 2. Metodicheskie rekomendatsie po razrabotke instruktciy po ohrane truda. Utv.Mintrudom RF ot 13.05.2004 g. 3. Poryadok obucheniya ohrane truda i proverki znaniy, trebovaniy ohrani truda rabotnikov organizatciy. Utv. Postanovleniem Ministerstva truda I sotcialnogo razvitiya RF ot 13.01.2003 g. N 1/29 и postanovleniem Minobrazovaniya RF ot 13.01.2003 g. N 1/29. 4. RD 03-20-2007 Pologhenie ob organizatsii obucheniya i proverki znanii rabochih organizatsiyi, podnadzornih Federalnoi slughbe po ecologicheskomu, tehnologicheskomu i atomnomu nadzoru. 5. Solodovnikov A.V. Razrabotka instruktcii po ohrane truda. Izd. 5-ye, – Ufa: UGNTU, 2015. – 71 s. 6. Trudovoi kodeks Rossiyskoi Federatcii ot 30.12.2001 N 197-FZ (red. ot 30.12.2015) (s ism. i dop., vstup. v silu s 01.07.2016). 7. Federalniy Zakon ot 21.07.97 № 116-FZ «O promishlennoy bezopasnosti opasnih proizvodstvennih obyektov» (s izmeneniyami na 13.07.2015 g.). 8. Eghegodniyi otcheti o deyatelnosti Federalnoi slughbe po ecologicheskomu, tehnologicheskomu i atomnomu nadzoru. URL: http://www.gosnadzor.ru/public/annual_reports/ (data obracheniya: 02.07.2016). 9. Kashin V.I. Samoe dorogoyo – eto zhizn. URL: https://kprf.ru/activity/ecology/153964.html/ (data obracheniya: 02.07.2016).
Fig. 6 - Example of Part 3 of guidance card
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SUMMARY OF INNOVATION MODELS ON A COMPANY LEVEL – CREATING A FRAMEWORK FOR AN INNOVATION MODEL THAT WILL INCREASE A COMPANY’S INNOVATION ACTIVITY M.Sc. Stefanovska Ceravolo LJ.1, Prof. PhD. Polenakovikj R.2, Prof. PhD Dzidrov M.1 Faculty of Mechanical Engineering – University “Goce Delcev” in Stip, Republic of Macedonia1 Faculty of Mechanical Engineering – University “Ss.Cyril and Methodius” in Skopje, Republic of Macedonia 2
[email protected]
Abstract: There are six known and generally accepted generations of innovation models. Innovation models transform from simple, linear models, to integrated and networking models that are dynamic and interactive. Each generation of innovation models is presented in this paper with their characteristics as well as drawbacks. The main goal of this paper is to show the transformation path of innovation models and create a framework for a new innovation model on a company level, that could be used by companies to increase their innovative activity and performance. Innovation models define the innovation process and its phases. The framework for the new innovation model includes feedback that was lacking in the first and the second generation of innovation models, but is included in the other generations. It also includes integrated and networking activities which are a characteristic of the third and fourth generation of innovation models. Another component of the model is the usage of information and communications technology (ICT) to facilitate the process of innovation, which is one of the characteristic of the fifth generation of innovation models. It uses a process approach and is based on the open innovation model, which is the signature model from the sixth generation of innovation models and best represents the complex system and characteristic of innovation. The model is supposed to help companies generate innovative ideas and select them through a predetermined process with four main components that act as control points. The purpose of this model is to create a continuous culture for innovation and to set up official procedures. These will help companies to accomplish their innovative ideas and activities. Keywords: INNOVATION, INNOVATION MODELS, OPEN INNOVATION, TECHNOLOGICAL INNOVATION, INNOVATION PROCESS.
technological models that apply to the overall economy, plus they give a theoretical background of the generations of the innovation models, as well as their positive and negative sides [6]. Table 1 shows the generations of innovation models by Rothwell [7] and Marinova & Phillimore [8].
1. Introduction Innovation models are being used so that companies can manage their innovation processes which have evolved tremendously in the last few decades of the XX century. Companies can adopt an existing model, or they can create their own [1]. By having an innovation model, it is easier to manage the order in which innovation activities happen. It also helps with determining the resources and responsibilities for every stage of the process as well as deciding which methods and tools companies will use. Innovation as a process has a very dynamic character, and the models of innovation have transformed throughout the years. Innovation models can be on a company level or a national level (such as National Innovation Systems – NIS) and can also be adopted and used by a region, an economy etc. In this paper we will focus on the company level innovation models. Based on the main characteristics of the different generations of innovation models, we are suggesting a framework for an innovation model that can be highly applicable to all company sizes, whose main goal is to increase the innovation activity and increase a company’s innovation performance.
Table 1. Generations of innovation models, author’s adaptation of Rothwell (1992) and Marinova & Phillimore (2003) GeneMarinova & Period Rothwell ration Phillimore 1950’s – Technology push The black box model 1 mid model 1960’s Mid Linear models 1960’s – 2 Market pull model (technology push – early need pull) 1970’s Early Interactive models 1970’s – Interactive or (coupling and 3 mid Coupling model integrated models) 1980’s Early Integrated Models of innovation 1980’s – innovation process systems (networks 4 early (parallel and national 1990’s development) innovations system) SIN (Systems 5 1990’s integration and Evolutionary models Networking Model) 6 Innovation milieu
2. Innovation models and their characteristics Currently there are six known generations of innovation models, although a seventh generation of innovation models is mentioned by Kotsemir et al., that has “emerged”, but is “not formed yet” [2]. Rothwell’s five generations of innovation models give a historical perspective of innovations management that shows how innovation models have transformed from linear to complex interactive models [3]. The approach to innovation management Rothwell gives in his classification relates to the evolution of organizations, the strategies of innovations management under various socio-economic and political circumstances and doesn’t include the substantive development of the innovation models themselves [4]. Rothwell’s typology is based on models of innovation on a company level. Another typology of innovation models is presented by Marinova and Phillimore where they present six generations of innovation models [5] and for their classification they use
The model of Innovation milieu is considered to be a networking model that applies on a national level. On a company level though, the model of Open Innovation is the sixth generation model of innovation [9]. The father of the open innovation model is Henry W. Chesbrough, who has introduced this concept stating that innovation has become an increasingly open process thanks to a growing division of labor [10]. Therefore, we will present the six generations of models and their main phases and characteristics, as well as their drawbacks. We will start with the first generation of innovation models and the famous linear model of innovation (technology push). The main phases of this type of models are: 1) basic science/fundamental
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research; 2) design and engineering; 3) manufacturing; 4) marketing and 5) sales [11,12]. This is a period where a lot of resources were put towards the R&D in companies, because it was believed that the more R&D is done, then more new products will be out. This pushed innovations forward, but did not give enough attention to the transformation process of existing products [13] or the needs of the market place and the consumers [14]. The second generation of innovation models is not much different from the first one. Both lack feedback loops, but the second one recognizes the fact that including the market/consumer needs will help drive performance and will be a source of ideas for new and better products/services [15]. Therefore, the second generation linear model of innovation is called the linear model of innovation (market pull/demand pull). Both models are shown in Figure 1 and these are the technology push and need pull models suggested by Rothwell.
marketing research and the other elements in the linear process [20], but could not differentiate the need from the demand. The Coupling model of Mayers & Marqis (as shown in Figure 3 [21]) is a third generation innovation model, where the innovation activities are divided in subcategories under each phase, and all of them are interacting [22]. The fourth generation of innovation models corresponds to the Japanese perception of the innovation process and it was the answer to the need of replacing the linear model with a different model that can reflect the complex innovation process [23]. The models from this generation consist of the basic stages of the linear models of innovations, enriched by many feedback loops and interaction between the stages, as well as a validation of the knowledge gained in the innovation process [24].
Fig. 1. Rothwell’s Diagram (source: Godin, 2013)
The first and second generation of innovation models have predetermined phases with a consecutive nature (as shown on Figure 1) and are both still being used today, with minor modifications such as adding control elements between each phase to approve the transitioning from one phase to another, and also to better the decision process just like the stage-gate model. This model was predominantly used by NASA in the 1960’s while trying to find creative innovative ideas to send a man on the Moon. This model, further simplified and suggested by Cooper [16] consists of five relevant phases or stages (as shown on Figure 2), and the added controlling elements here are the gates positioned after each phase. Their function is to follow the fulfillment of strict and predetermined criteria before we move onto the next stage [17]. Many other companies have adopted and used, or are still using, this model [18].
Fig. 3. The Myers and Marquis Coupling Model from 1969 (source Godin, 2013)
These models are also functionally integrated innovation models and they achieved integrating the suppliers, customers and partners in the development process [25]. On Figure 4 is the ChainLinked Model, developed by Rosenberg and Kline (1986).
Fig. 2. Cooper’s Stage Gate Model (Source: Cooper, 1994)
Fig. 4. The Chain-Linked Model of Innovation (Rosenberg and Kline, 1986) Source: www.uis.unesco.org.
The third generation of innovation models differ from the first and second significantly. These models are given the name Interactive models as a result of recognizing the interaction between elements in the innovation process which is a key for innovation’s success. The technology push and market pull models are “coupled” in this generation which implies suppliers and customers to be closely “coupled” in product development teams [19]. The models include interaction and feedback between phases such as the
After seeing a trend of cutting down on R&D costs companies had to network and find different ways to proceed with their innovative activities [26]. Information systems became the next big thing and started being incorporated into the companies work, especially in process automation and in expediting the communications inside a company’s network [27]. Therefore, the different activities within the innovation process became even more integrated and could occur simultaneously, with feedback loops. We
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also notice a trend of overlapping functions. This is when the fifth generation of innovation models appeared. Rothwell’s SIN (Systems Integration and Networking) model as a fifth generation innovation model incorporates the higher integration inside companies as well as with the outside entities such as suppliers, consumers, universities and authorities [28].
first time in the second generation of innovation models, where market pull became the main source of ideas. Planning a reliable and safe funneling of ideas and their distribution will encourage innovative minds to take part of the process and share their ideas and knowledge. The selection process of innovative ideas should be done by strict criteria and very carefully, and the model should be able to know whether it is the right time for introducing a certain innovation on the market or not. This should be enabled by using marketing, legal, economical and development component as a part of the process, where the marketing component can determine whether an idea can be marketable or not, the legal component will deal with the patenting potential of the innovative idea that can be an additional source of income and potential success, the economic component will be able to say how economically feasible the new idea is and whether we can use outside R&D facilities or other entities to help in the process; and the development component the actual R&D of the idea before bringing it to market and getting to the realization and diffusion stages.
Introduced by Chesbrough, The Open Innovation Model (Figure 5) underlines idea management not just within the organizations, but also with other organizations. R&D is being done by outside partners, if it is not possible to be handled by the company itself, and ideas can occur while developing a new product/service which can change the course of the process. This model promotes using outside knowledge, such as suppliers, competition, entrepreneurs, scientists etc. [29]. The open innovation process can be 1) the outside in process; 2) the inside out process; and 3) the coupling process [30] and innovative ideas are introduced by outside sources such as universities, research centers, suppliers, competition, government bodies and consumers [31]. There are four main phases of this innovation model: 1) research; 2) development; 3) manufacturing; and 4) marketing, coupled with other processes and entities with an interactive nature [36]. R&D in this model is taken over by publicly funded research centers or universities where ideas are chosen through a highly competitive selection process which promotes transparency of innovation activities.
4. Conclusion The transformation process of the innovation models show that innovation is of a changing nature and very complexed. In order to suggest a new model that can help companies innovate more in regions with a low innovation activity trend, we need to take in consideration that no innovation can happen if the company culture doesn’t enable this itself. For companies to become more innovative, they need to be ready for change and to have set up mechanisms that will support the process. We can state that in order to have an innovation model that could be widely applicable to different types and sizes of companies, the model itself should be of a simple and maybe with a certain linear character, but with enough details that are going to clearly describe the innovation process. The main phases of the innovation model should be marketing, legal, economic, development, realization and diffusion phase, integrated with feedback loops, and potentially modified with other predetermined phases. It should include measures and tools for evaluation of feedback. The model should also be knowledge based, easy to adapt to a networking environment, handle interaction, know the competition and easily identify new sources of ideas that will be funneled through a predetermined channel. Achieving a continuous learning culture should be an integrated part of the model. As a beginning of the innovation process we can say that generation of ideas is the most important part, as well as planning a reliable and safe funneling and distribution of the same ideas.
Fig. 5. The Open Innovation Model (Chesbrough, 2014)
Such models have been implemented in large companies, but there are also findings that open innovation models have been used in SME’s as well, primarily for market related motives, such as meeting customer demands and keeping up with competitors where the biggest challenges lie in organizational and cultural issues as a consequence from dealing with increased external contacts [32].
5. References [1] Jovanoski, D., Innovations management, Skopje, University “Ss. Cyril and Methoduis”, Faculty of Mechanical engineering, 2012 (Jovanoski, D.) [2] Kotsemir, M.N., D. Meissner, Conceptualizing the innovation process–trends and outlook. Higher School of Economics Research Paper No. WP BPR, 10, 2013 (Kotsemir, M.N., D. Meissner) [3] Rothwell, R., Zegveld, W., Innovation and the small and medium sized firm, University of Illinois at Urbana-Champaign's Academy for Entrepreneurial Leadership Historical Research Reference in Entrepreneurship, 1982 (Rothwell, R., Zegveld, W.) [4] Kotsemir, M. N., A. Abroskin, D. Meissner: Innovation concepts and typology–an evolutionary discussion. Higher School of Economics Research Paper No. WP BRP. 2013, Feb 20;5. (Kotsemir, M.N., A. Abroskin, D. Meissner) [5,6] Marinova, D., Phillimore, J. Models of innovation, The international handbook on innovation, Elsevier, 2003, pp. 44-53 (Marinova, D., Phillimore D.)
3. Discussion What we have learned from the six generations of innovation models is that a good innovation model has to have predetermined phases, feedback loops, large capability for interaction and integration, but also to be knowledge based, able to use outside knowledge, endorse knowledge gain and maintain the knowledge level in the company through achieving a continuous learning culture. Because the feedback loops were lacking in the first and second generation of innovation models, and customer’s feedback is an essential element of innovation, we consider them as a part of every stage of the innovation process. Another element for a successful innovation process is networking, which will help companies of all sizes, not just the large ones that can afford their own R&D, to be able to innovate and enter new markets. This will also help in the effort of knowing the competition and keep in tune with the technological advances. Identifying new sources of ideas is crucial for generating innovative ideas, that has been used for the
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[7] Rothwell, R., Towards the Fifth‐generation Innovation Process-International Marketing Review, Vol. 11 Iss: 1, 1994, pp.7 – 31 (Rothwell, R.) [8] same as [5,6] [9] same as [5.6] [10] Chesbrough, H. W., Why companies should have open business models - MIT Sloan management review, 48(2), 22, 2007 (Chesbrough, H. W.) [11] Godin, B., The Linear model of innovation the historical construction of an analytical framework - Science, Technology & Human Values, 31(6), 2006, pp.639-667. (Godin, B.) [12] Le Corre, A., Mischke, G., The innovation game: a new approach to innovation management and R&D, Springer, 2002 (Le Corre, A., Mischke, G.) [13] Carter, C. F., Williams, B. R., Industry and technical progress, 1957 (Carter, C. F., Williams, B. R.) [14] Rothwell, R., H. Wissema, Technology, culture and public policy - Technovation, 4(2), 1986, pp. 91-115 (Rothwell, R., H. Wissema) [15] Hughes, D. G., D. C. Chafin, Turning new product development into a continuous learning process - Journal of Product Innovation Management, 13(2), 1996, pp. 89-104 (Highes, D.G., D.C.Chafin) [16] same as [11] [17] Cooper, R. G., E. J. Kleinschmidt, Stage-gate process for new product success - Innovation Management U 3 (2001): 2001 (Cooper, R.G., E. J. Kleinschmidt) [18] Cooper, R. G., S. J. Edgett, E. J. Kleinschmidt, Optimizing the stage-gate process: what best-practice companies do — I Research-Technology Management, 45(5), 2002, pp.21-27. (Cooper, R. G., S. J. Edgett, E. J. Kleinschmidt) [19] Nicolov, M., Badulescu, A. D., Different types of innovation modeling – Annals of DAAAM of 2012 and Proceedings of 23rd DAAAM International Symposium, Volume 23, No.1, Vienna, Austria, 2012, pp. 1071-1074 (Nicolov, M., Badulescu, A. D.) [20] Hobday, M, Firm-level innovation models: perspectives on research in developed and developing countries - Technology Analysis & Strategic Management, 17(2), 2005, pp. 121-146 (Hobday, M.) [21] Godin, B., J. P. Lane, Pushes and Pulls Hi (S) tory of the Demand Pull Model of Innovation - Science, Technology & Human Values, 38(5), 2013, pp.621-654. (Godin, B. J., J. P. Lane) [22] same as [5,6] [23] Mahdjoubi, D., The Linear Model Of Technological Innovation: Background and Taxonomy, UTexas working paper, 1997 (Mahdjoubi, D.) [24] Ryan, C. D., P. W. Phillips, Knowledge management in advanced technology industries: an examination of international agricultural biotechnology clusters - Environment and Planning C, Government and Policy, 22(2), 2004, pp. 217-232 (Ryan, C. D., P. W. Phillips) [25] same as [19] [26] same as [20] [27] Gabison, G., Pesole, A., An Overview of Models of Distributed Innovation. Open Innovation, User Innovation, and Social Innovation. No. JRC93533, Institute for Prospective and Technological Studies, Joint Research Centre, 2014 (Ganbison, G., Pesole, A.) [28] same as [20] [29] same as [27] [30] Enkel, E. O. Gassmann, H. Chesbrough: Open R&D and open innovation: exploring the phenomenon - R&D Management, 39.4, 2009, pp. 311–316. (Enkel, E., O. Gassmann, H., Chesbrough) [31] same as [27] [32] Van de Vrande, V., J. P. De Jong, W. Vanhaverbeke, M. De Rochemont, Open innovation in SMEs: Trends, motives and management challenges – Technovation, 29(6), 2009, pp. 423-437. (Van de Vrande, V., J. P. De Jong, W. Vanhaverbeke, M. De Rochemont)
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MATHEMATICS INDUSDTRY ECONOMY – MICRO-FOUNDRY Bushev St. PhD. assoc. prof. eng. Institute of Metal Science, Equipment and Technologies with Center for Hydro and Aerodynamics “Acad. Angel Balevski” – BAS, Sofia, Bulgaria
[email protected] Abstract: This article presents fundamental results in mathematics and mathematical physics on the example of a theoretical model of structure formation in casting. Basic scientific results are innovations for all micro-foundries. Keywords: FUNDAMENTAL RESULTS, MATHEMATICS & MATEMATCAL PHYSICS, INOVATIONS, MICRO-FOUNDRY
reasoned decision with minimal risk. On Fig.1 is shown the schema of OTT
1. Introduction – Mathematics and economy 1.1 Mathematics Definition of mathematics is by historical approach [1]: 1. Early definitions – Aristotle; 2. Greater abstraction and competing philosophical schools; 3. Definition in general reference works. Our opinion: mathematics is the science that takes care of its internal logic and never abandons not solved problems. Not resolved tasks often resolved after centuries. In this work we present mathematics with it in our papers. The mathematical based of the casting is theory of heat conductivity – Stefan-Schwarz problem. This theory today is developing by modern mathematics and mathematical physics for investigate by computational physics to design new structure at phase transition. Paper [2] presented the fundamental role of mathematics in thermodynamics. Other bright example for interaction between mathematics and physics is [3]. Today computational physics is a great part of investigations [7]. Multyscales modeling is introduced in [4 and 5]. At work with multiscale modeling must be render an account Gödel's theorems for precision of interaction between different mathematical methods.
Fig.1 Schema of Offices transfer of technology and knowledge [6].
2. Micro-foundry – application of science and technology in casting practice
For description of structure is use mathematical description in solidification zone introduce not only numerically of phase transition like area, but and descript and polycrystalline structure formation with maximum details. The first is mathematical theory of scattering for introduction driving force of crystallization [9]. Second is description polycrystalline structure formation by quantum mechanics: the equations of the molecular mechanics
i ri = f i m
f i = ∂U ∂ri ,
− 2 ∇ 2 ψ ( r ) 2 m + V ( r ) = Eψ ( r )
Fig. 2 presents the subject of foundry work: Fig. 2 a mold with cavity cast and Fig. 2 b machine for gas casting pressure
(MM) (Schrödinger equation, 1, 2)
i ∂ψ (r , t ) ∂t = − 2 / 2m ∂ψ (r , r ) ∂r 2
where m, r and fi – mass, coordinates and acting on atomic force derived from potential energy U(rN), where rN = (r1, r2,…,rN) introduced full set of 3N coordinates of atoms; Planck's constant – ħ; ψ - wave function, m – mass of the electron. The potential energy can introduce: interaction between not connection or connected atoms; the atoms and electrons building the crystal lattice and behavior of electrons are describes with Schrödinger’s equation equation. For this equations is used methods which introduced of microfoundry applied in their practice by investment of mathematical results – software. In work [6] present term open innovation which introduced Henry Kembarou in 2003 paradigm that requires companies to use external ideas as well as internal to find advanced technology. For companies this is an open market approach science technological transfer "maximum speed" to market a new product.
Fig.2 Casting technology.
On Fig. 1 is show schema of office for technological transfer (OTT) which subject is to develop a system for services of branch machine building particularly – micro-foundry. That system mast helps full innovation process. Micro-foundries have not many and innovation capacitance. The generation of an idea mast lead to a
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3. Offices for science and technological transfer of branch machine building – micro-foundry
Fig. 1 Phase Transition: a) Fundamental states of the matter and different phase transition processes; b) Phase diagram a single component system [13]; c) thermodynamic diving force and crystallization of liquid [13]; d) Phase diagram of a second order quantum phase transition; Solidification process – zone of phase transition.
Thermodynamics system:
3. Conclusion
Mathematical
Micro-foundry.
The nature
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4. References 1. https://en.wikipedia.org/wiki/Definitions_of_mathematics 2. R. Clausius, Mechanical theory of heat, with its application to the steam-engine and to the physical properties of bodies, Jon Van Voorst, 1 Paternoster Row. MDCCCLXVII, London. http://books.google.com 3. I. Todorov, Einstein and Hilbert: The creation of general relativity, The world of physics, 1, 2014, 1-14. (In Bulgarien) 4. M. Tompa, Lectures, Dep. of Computer Science and Eng. FR-35, Univ. Washington, Seattle, Washington, U.S.A. 98195, 1991. 5. Weinan E, Principles of Multiscales Modeling, Cambridge University Press, UK, 2011, ISBN 978-1-107-09654-7 6. R. Georgiev, Open innovation – based of sustainable operational the offices for technological transfer, NTSM, 2012, Sofia, not publishing (In Bulgarian). 7. Uzi Landman, Materials by numbers: Computations as tools of discovery, PNAS, May 10, 2005, vol. 102, no. 19, 6671–6678.
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ЭЛЕКТРОННАЯ КОММЕРЧЕСКАЯ ДЕЯТЕЛЬНОСТЬ КАК СРЕДСТВО УДЛИНЕНИЯ ЦЕПОЧКИ ДОБАВЛЕННОЙ СТОИМОСТИ
E-BUSINESS AS A MEANS OF LENGTHENING OF THE VALUE CHAIN Post Gr Student, Shepitko G., Post Gr Studet Beloborodjko V. Institute of Mathematics, Economics, Mechanics, Odessa National Mechnikov’s University, Odessa. Ukraine.
[email protected], University KROK, Kiev , Ukraine.
[email protected]
Abstract: The main issues are considered in this topic: development of tax system under conditions of electronic commerce and investigation new properties of electronic commerce as instrument of creation of value added cost, economic security of state KEYWORDS: ELECTRONIC COMMERCE, VALUE ADDED CHAIN. VALUE ADDED COST, TAX SYSTEM, SHADOW ECONOMY, ECONOMIC SECURITY.
1. Введение
выразителей атрибутики системы как целого на узловой линии мер» [2]. . Оптимизация разнообразия в развивающейся системе бизнеса является обязательной предпосылкой ее устойчивого функционирования, т.е. электронная коммерческая деятельность с общесистемных позиций может рассматриваться именно как тенденция к оптимизации разнообразия и повышения устойчивости, способности к самоорганизации системы бизнеса в целом.
Цель удлинения цепочки добавленной стоимости – обеспечение более высокого экономического результата и повышение уровня экономической безопасности бизнеса. Всякая безопасность полагается на единство; единство состоит из противоположностей, образующих бинарную оппозицию; противоположности порождают или динамический хаос или согласованность и соразмерность действий, т.е. удлинение цепочки добавленной стоимости должно соответствовать закону Меры. [1].
3. Решение рассматриваемой проблемы Цель развития электронной коммерции как инструмента удлинения цепочки добавленной стоимости исходит их возможности измеримости, с целью определения необходимых пропорций в структуре бизнеса в целом. При наличии статистических данных, характеризующих бизнес как системное образование, уровень структурного разнообразия входящих в него составляющих может быть измерен. Для этого существует рекуррентный ряд инвариантов – обобщенных золотых сечений: p: 0,500; 0,618…; 0,682… Это так называемые обобщенные золотые сечения, узловые значения меры, инварианты процессов самоорганизации и эволюции систем, аттракторы их нормированных интегральных показателей. Также, существуют и k (3/2, 5/2, 7/2…): 0,570; 0,654…; 0,705… - антиузлы меры, репеллеры (дистракторы), в пространстве ее значений. Структурная дисгармония, хаос – таковы состояния систем, им отвечающие. [2].
Эволюция экономики вследствие возникновения и развития различных форм электронной коммерческой деятельности в сети создаёт новые возможности для проектирования цепочек добавленной стоимости и их удлинения, адаптации к новым условиям бизнеса.
2. Предпосылки проблемы
и
средства
для
решения
Всякая система стремится к состоянию, в котором испытывает минимум сопротивления со стороны среды (принцип Ле Шателье). Чаще всего такое положение предполагает соответствие аттрактору, изменяющему развитие системы и формирующему у нее структуру в соответствии с тяготением к данному аттрактору. «Оптимальная организация внутреннего пространства всякой самоорганизующуюся, эволюционирующей, неравновесно-устойчивой сложной системы есть важнейший фактор ее жизнеобеспечения, жизненности, жизнеспособности, силы. Лишь при наличии оптимальных параметров собственного пространства и собственного времени возможен выбор состояния, адекватного структурной гармонии системы и ее функциональному потенциалу., благодаря которому совершается ее самоактуализация и осуществляется ее жизненный цикл. Внутреннее (собственное) пространство системы должно обладать определенными степенями свободы, размерностями, регламентированной уровнем структурного разнообразия и определенными значениями интегральных
4. Результаты и дискуссия Регулирование электронной составляющей бизнеса и формирование оптимальной его структуры должно придерживаться следующего требования , «узловая линия меры, представляющая собою канонические количественные отношения, представлена в границах единичного интервала нелинейно сжимающейся к флангам одномерной решеткой иррациональных чисел. Их последовательность известна в качестве обобщенных золотых сечений (ОЗС): …0,1883…; 0,2035…; 0,2219…; 0,2451…; 0,2755…; 0,3177…; 0,3820…;
54
6. Литература
0,5000…; 0,6180…; 0,6823…;0,7245…;0,7549…; 0,7781…;0,7965…; 0,8117… Стократ увеличенная, она превращается в последовательность узловых процентных отношений: …18,83%; 20,35; 22,19; 24,51; 27,55; 31,77; 38,2; 50,0; 61,8; 68,23; 72,45; 75,49; 77,81; 79,65; 81,17%… Распределение предстает в степенной форме и симметрично относительно центра 0,5. Так, 0,382 = (0,618)2, 0,3177 = (0,6823)3 и т.д., удовлетворяя гегелевской формулировке закона развития меры как закона степеней» . [2]. . В качестве интегрального показателя может быть предложена информационная энтропия по Шеннону. Формула информационной энтропии, имеет следующий вид:
1 n Hˆ = − ∑ pi log pi log n i =1
1. . Егорова-Гудкова T. И. Мировоззренческометодологические аспекты проектирования устойчивых экономических систем: Закон Золотого сечения // Сб. науч. трудов Восточно-украинского национального университета им. Владимира Даля. Серия: Менеджмент. – Луганск, 2014. – Вып. 26 (1) . - С. 183-184. 2. Сороко Э.М. Золотые сечения, процессы самоорганизации и эволюции систем: Введение в общую теорию гармонии систем. Изд 4-е. — М.: Книжный дом «ЛИБРОКОМ», 2012. – 264 с 3. Сороко Э.М. Структурная гармония систем. — Мн.; Наука и
где pi – удельные веса классов.
техника, 1984. – 287 с.
Относительная информационная энтропия имеет область приложений там, важны относительные доли, частоты, вероятности, вариации которых и определяют состояния названных систем, в том числе и система бизнеса при проектировании цепочки добавленной стоимости.
4. Егорова-Гудкова Т.И. Проектирование устойчивой экономической системы государства на основе модели золотого сечения / Т.И. Егорова-Гудкова; в кн.: Гармоничное развитие систем – третий путь человечества [монография]; под ред. Э. М. Сороко, Т. И. Егоровой-Гудковой. — Одесса: изд-во Института креативных технологий, 2011. — С. 333 - 336.
5. Заключение Для того, чтобы бизнес со сложной структурой обладал системными качествами необходимо, при проектировании цепочки добавленной стоимости так формировать доли его составляющих (физический бизнес, физическая торговля, электронная составляющая и т.п.) чтобы в результате цепочка добавленной стоимости в интегральном выражении целого при распределении долей составляющих этого целого, имела показатель относительной информационной энтропии, стремящийся к узлу Меры и соответствовала значению из реуррентного ряда золотых сечений - 0,618… (или 0,682…; 0,725… – в зависимости от степени состояния и развитости системы [3,4].
55
ВЛИЯНИЕ ИЗМЕНЕНИЯ ДОЛИ ГОСУДАРСТВЕННОЙ СОБСТВЕННОСТИ НА ЭКОНОМИЧЕСКУЮ БЕЗОПАСНОСТЬ ГОСУДАРСТВА IMPACT OF CHANGES IN SHARE OF STATE OWNERSHIP ON ECONOMIC SECURITY OF STATE As. Prof., dr. Yegorova-Gudkova Т Institute of Mathematics, Economics, Mechanics, Odessa National Mechnikov’s University, Odessa. Ukraine.
[email protected] Abstract: The main issues are considered in this topic: share of state ownership is the base of economic security. The basis of proportion of economy should be corresponded to the law Measures: the number of Phidias and its derivatives as components of law Measures: recurrent series of the Golden sections, the tri-metallic proportions and vurfs. KEYWORDS: ANTICRISIS STRATEGY, SHARE OF STATE OWNERSHIP, RATE OF INTERESTS, ECONOMIC GROWTH, GOLDEN SECTION ATTRACTOR, ECONOMIC SECURITY.
1. Введение Зависит ли устойчивость экономического развития от того, какая доля собственности принадлежит государству в том или ином размере? Ответ очевиден. Ещё с времён древних греков велась дискуссия о «числе государственного управления», под которым понималось распределение долей между государственной и частной собственностью. Также безспорно, что снижение доли государственной собственности в экономике сопряжено в стратегическом периоде с проблемой возникновения недостатка средств на государственные расходы, и в итоге приведёт к необходимости внешних заимствований и росту государственного долга. То есть, снижая долю государственной собственности посредством приватизации государственных предприятий, решая тактические задачи, государство стратегически формирует условия самовоспроизводящегося кризиса, роста государственного долга со всеми вытекающими последствиями.
Рис. 1 Доля различных форм собственности в России[4].. В Украине, по данным 2014 года, при расчётах по балансовой стоимости, то доля ГС составляет 29,5%. Если по объемам реализации то всего лишь 3,5%.. [2].. В 2015 году - доля государства в экономике Украины составила более 16,3%. [3].. Подтверждением влияния доли ГС на государственные расходы может служить следующая диаграмма:
2. Предпосылки и средства для решения проблемы Рассмотрим, в разрезе некоторых стран, какова доля государственной собственности. В Китае доля госсобственности составляет 66% (и страна, кстати, показывает самые высокие темпы экономического роста в мире уже в течение 20 лет).Швеция — 62%, Финляндия и Франция — 52%., Италия —51%, Германия — 48%, Канада — 43%., Англия — 40%, Япония — 35%, США — 32%. В России – оценивается пределах от 10 до 29 процентов. [1]..
Рис. 2 Доля государственных расходов в ВВП [5].. Вспомним параболическую модель Лаффера, согласно которой зона устойчивости начинается с 38% и продолжается
56
5. Заключение
до 62-х%, что соответствует аттрактору закона Меры – золотому сечению.
В неконтролируемого на институциональном уровне снижения доли государственной собственности и недостаточности собственных бюджетных средств на государственные расходы имеет место постоянный рост внешних заимствований, который может привести к потере как экономической безопасности, так и независимости государства. Контроль государства доли государственной собственности в соответствии с параметрами параболической модели Лаффера, законодательное закрепление норматива государственной собственности и стратегия на новую индустриализацию в приоритете воссоздания государственной собственности будут формировать условия для возрождения государственности и национальной независимости.
Т.е. снижение доли государственной собственности продуцирует риски и угрозы экономической и иной безопасности государства, риск потери независимости.
3. Решение рассматриваемой проблемы Прежде всего следует обратить внимание на тот факт, что "Один рыночный механизм не может выполнять всех экономических функций. Государственная политика необходима для управления, корректировки и дополнения определенных его аспектов. Этот факт важно понять, поскольку он означает, что соответствующий размер государственного сектора в значительной мере есть вопрос технического, а не идеологического порядка",( Р. Масгрейв).
6. Литература
Идеализация частной собственности и курс на увеличение её доли становятся тормозом экономического развития страны и угрозой её национальной безопасности.
1. Сулакшин С.С. В сторону нуля. Электрогнный ресурс: режим доступа: http://sulakshin.ru/v-storonu-nulya/ 2. Электрогнный ресурс: режим доступа: Marketolog.Info
4. Результаты и дискуссия
3. Доля госсектора в экономике Украины в І квартале составила 16,3%, - Минэкономразвития Электрогный ресурс: режим доступа http://ubr.ua/finances/macroeconomics-u ... -16362426 4. С. Демура. Доля госсобственности в России. Электрогный ресурс: режим доступа http://voprosik.net/rossiya-budet-rekon ... ekonomiku/ 5. http://www.worldbank.org/depweb/beyond/ ... beg_11.pdf
Пропорции между соотношением частной и государственной собственности должны определяться по секторам экономики на основе ценологического подхода. Методика анализа закономерности для различных бизнес-форм применительно к экономическим ценозам была разработана проф. В.В. Фуфаевым и содержит следующие этапы: 1. Составляется перечень всех видов деятельности по выборке организаций выделенного экономического ценоза. 2. По списку производится пересчет организаций, у которых одинаковый основной вид деятельности. 3. Виды деятельности, представленные в данной выборке одинаковым количеством организаций, объединяются в касты. 4. Касты располагаются в порядке уменьшения в них числа видов деятельности, в результате чего и получается распределение видов деятельности по повторяемости. Для диагностики состояния экономических ценозов (а также других видов формирований) на предмет «нормапатология» используются Н-распределения Б.И. Кудрина [6]..
6. Кудрин Б.И. Самодостаточность общей и прикладной ценологии / Техногенная самоорганизация и математический аппарат ценологических исследований. Вып. 28. «Ценологические исследования». - М., 2005. – С.179-180.
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ПРОДОВОЛЬСТВЕННАЯ БЕЗОПАСНОСТЬ ГОСУДАРСТВА И СМЕНА СОБСТВЕННОСТИ НА ЗЕМЕЛЬНЫЕ РЕСУРСЫ FOOD SECURITY OF STATE AND CHANGE OF OWNERSHIP OF LAND RESOURCES Post Gr Student, Zverkov 0. Institute of Mathematics, Economics, Mechanics, Odessa National Mechnikov’s University, Odessa. Ukraine.
[email protected] Abstract: The main issues are considered in this topic: projecting the value chains, increasing the multiplication of added value in agriculture sector of economy; using the cenology approach and demographically conditioned needs in the preparation of food balance/ KEYWORDS: VALUE CHAINS, AGRO-INDUSTRIAL DEINDUSTRIALIZATION, CENOLOGY APPROACH.
COMPLEX,
FOOD
SECURITY,
позиция собственников пользователей
1. Введение
земли
ECONOMIC
и слабая земли
SECURITY,
защита
прав [2].
Рассматривая проблему продовольственной безопасности в аспекте собственности на земельные ресурсы следует увязывать её с возможностями проектирования цепочек добавленной стоимости. Собственник земельных ресурсов определяет вид бизнеса, сектор АПК, экспортную политику. В проектировании цепочек, в первую очередь заинтересованы национальные собственники. Иностранные собственники в большей своей части, ориентированы на вывоз сырья. Проектирование цепочек добавленной стоимости (ЦДС) оказывает непосредственное влияние на состояние и развитие бизнеса в аграрной сфере. Длина цепочки добавленной стоимости влияет на уровень продовольственной безопасности уже постольку, поскольку определяет, что экспортируется сырье, полуфабрикаты или готовая продукция. [1].
2. Предпосылки и средства для решения проблемы По мнению проф. Ефимова В.А., - АПК – это не только отрасль народного хозяйства, обеспечивающая продовольственную безопасность, но и инструмент содержания и обустройства территории страны, гарант целостности государства. Система продовольственной безопасности является составляющей системы экономической безопасности и также подчиняется вышеперечисленным свойствам. В условиях моратория на продажу земли сельскохозяйственного назначения формально не существует механизма продажи, однако, фактически, существуют различные схемы и механизмы, позволяющие иностранному бизнесу распоряжаться земельными ресурсами как собственникам. Это формирует стратегическую угрозу продовольственной безопасности государства, а в условиях неконтролируемого распространения ГМО – угрозы демографической безопасности и экономической безопасности, в целом.
4. Результаты и дискуссия Сегодняшняя стоимость аренды земель сельскохозяйственного назначения в Украине ниже, чем могла быть, если бы не мораторий и раздробленная собственность земли, а также плохой доступ к капиталу. Стоимость аренды достигала бы $455 за гектар, но пока она составляет лишь $37, что в 11 раз ниже потенциальной стоимости - достаточно небольшое число хозяйств, которые обрабатываются собственниками, поскольку владельцам не хватает доступа к капиталу, способности обрабатывать землю (около 50% владельцев — пожилого
3. Решение рассматриваемой проблемы В Украине, около 60% сельскохозяйственной земли в пользовании обрабатывается арендаторами, которые снимают землю в индивидуальных владельцев. Владельцы земли получают лишь 37 долл./га в качестве арендного платежа. Причинами этого является сравнительно слабая переговорная
возраста) или они работают в других секторах экономики. [2]. Такая ситуация открывает дорогу иностранным арендаторам земель сельскохозяйственного назначения. С 6 октября 2015 года, открыли информацию о владельцах и пользователях
58
земельных участков по всей территории страны. В Государственной службе Украины по вопросам геодезии, картографии и кадастра отмечают, что открытие реестра значительно усилит контроль гражданского общества за использованием и оборотом земель в стране.
фондовой бирже 29 января 2014 года "впредь до особого уведомления" после того, как в отношении компании была открыта процедура банкротства. В 2013 году ее веб-сайт (также недействующий в настоящее время) сообщил, что 36,3 процента капитала компании составляют акции, находящиеся в свободном обращении.
Компании и акционеры, стоящие за приобретением земельных участков на Украине, находятся в самых разных странах мира. Так, например, 52 тысячи гектар принадлежат датской компании "Trigon Agri". Эта компания была создана в 2006 году на основе стартового капитала финской группы "High net worth individuals". Ее акции торгуются в Стокгольме (NASDAQ), а список крупнейших акционеров включает JPM Chase (Великобритания, 9,5 процентов), Swedbank (Швеция, 9,4 процента), UB Securities (Финляндия, 7,9 процента), Euroclear Bank (Бельгия, 6,6 процента), а также JP Morgan Clearing Corp (США, 6,2 процента).
Через механизм банкротства этих корпораций возможен переход земли иностранным собственникам., Аналогичный опыт имел место в Румынии, где контроль над землями со стороны иностранных компаний стал открытым. Пробелы в национальном законодательстве создали условия для установления иностранного контроля над землей путем процедуры банкротства.
5. Заключение
Компания "United Farmers Holding Company", принадлежащая группе инвесторов из Саудовской Аравии, контролирует 33 тысячи гектар украинских сельскохозяйственных земель через посредничество компании "Continental Farmers Group PLC". "AgroGeneration", обладатель 120 тысяч гектар земли на Украине, является частью французской корпорации, причем 62 процента акций находится в управлении инвестиционной компании из Техаса "SigmaBleyzer".
Концентрация земель в руках нескольких олигархов и иностранных корпораций не соответствует интересам страны, и формирует стратегические угрозы продовольственной безопасности государства.
6. Литература 1. Єгорова-Гудкова Т. І. Управління складними системами за допомогою ценологічного підходу (на прикладі системи економічної безпеки держави) / Т. І. Єгорова-Гудкова, М.В. Бойко., О.Є.Звірков // Науковий вісник Полтавського університету економіки і торгівлі. 2015. № 1 (69), ч. 1. С.41 – 49
Американскому пенсионному фонду NCH Capital принадлежат 450 тысяч гектар. Компания начала свою деятельность в 1993 году и стала одним из первых западных инвесторов на Украине после распада Советского Союза. За последнее десятилетие, она систематически арендовала небольшие участки сельскохозяйственных угодий (от двух до шести гектар) по всей Украине, объединяя их в крупные фермы. Согласно заявлению генерального партнера NCH Capital Джорджа Рора, эти договоры аренды дают компании право выкупа арендуемых в настоящее время участков после отмены правительством Украины моратория на продажу земли.
2. КТО ВЛАДЕЕТ УКРАИНОЙ: ПОЧЕМУ ЦЕНА ЗЕМЛИ В 11 РАЗ НИЖЕ РЕАЛЬНОЙ. ЭЛЕКТРОННЫЙ РЕСУРС. :РЕЖИМ ДОСТУПА: HTTP://FINANCE.OBOZREVATEL.COM/BUSINESS-ANDFINANCE/96058-KTO-VLADEET-UKRAINOJ-POCHEMUTSENA-ZEMLI-V-11-RAZ-NIZHE-REALNOJ.HTM 3. КОМУ ПРИНАДЛЕЖАТ ЗЕМЛИ УКРАИНЫ. ЭЛЕКТРОННЫЙ РЕСУРС. :РЕЖИМ ДОСТУПА HTTP://WWW.DAL.BY/NEWS/119/14-05-15-7/
Еще одна группа компаний, руководство которыми осуществляют граждане Украины, создана на базе комбинации отечественных и иностранных инвестиций.. Например, "UkrLandFarming" контролирует крупнейший в стране земельный банк общим объемом в 645 тысяч гектар. 95 процентов акций "UkrLandFarming" принадлежат мультимиллионеру Олегу Бахматюку, а оставшиеся пять процентов недавно были проданы компании "Cargill". Другой олигарх, занимающий пятую позицию в списке богатейших людей Украины, Юрий Козюк, является президентом компании "MHP", одной из крупнейших сельскохозяйственных компаний, Совместное украинско-кипрское предприятие "Mriya Agro Holding", контролирующее земли площадью около 300 тысяч гектар. В 2014 году на своем веб-сайте (который уже прекратил существование) компания указывала, что 80 процентов акций принадлежат семье Гута (Украина), занимающей лидирующие позиции. Оставшиеся 20 процентов торговались на Франкфуртской фондовой бирже. Остальные компании, принадлежащие украинцам и инкорпорированные в налоговых гаванях, также испытывают трудности. "Sintal Agriculture Public Ltd" (зарегистрированная на Кипре и контролирующая 150 тысяч гектар земли), прекратила торговлю своими акциями на франкфуртской
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ИССЛЕДОВАНИЕ ЭМЕРДЖЕНТНЫХ СВОЙСТВ ТЕНЕВОЙ ЭКОНОМИКИ STUDY OF EMERGENT PROPERTIES OF THE SHADOW ECONOMY Post Gr Student, Bojko M. University KROK, Kiev , Ukraine.
[email protected] Abstract: The main issues are considered in this topic: Study of the shadow economy as a sustainable economic system, the nature of occurrence of emergent properties of the shadow economy, compliance with the law of the shadow economy of structural harmony of systems. Mathematical background of it is non-Gaussian nature of functional or shadow economy. KEYWORDS: SHADOW ECONOMY, NON-GAUSSIAN DISTRIBUTION, TRANSACTION COSTS, SELF-ORGANIZATION, ECONOMIC SECURITY, EMERGENT PROPETIES, SELF-GARMONIZATION
1. Введение
возникают от их соединения. Этот эффект называется эмерджентностью» [2]. Устойчивость системы теневой экономики обеспечивается её структурой. Структура системы может быть представлена при помощи инвариант и вариаций : Различают инварианты структурные, функциональные, генетические (эволюционные), метрические, которые в совокупности наиболее адекватны интегральному отражению и освоению действительности, природе вещей, локальных универсумов и служат опорными точками процессов самоорганизации и развития в природе и обществе». Вариации– изменяющиеся элементы системы [4]. Способность к самоорганизации теневой экономики обуславливается именно её структурными параметрами и задачей снижения уровня теневой экономики должны быть не только институциональные изменения, способствующие детенизации, но и исследование её структурных пропорций, выявление инвариантов или аттракторов. Знание аттракторов системы теневой экономики даст возможность разработки методов противодействия. Это становится возможным при обосновании математической интерпретации как инвариантов, так и вариаций теневой экономики, разработки математической модели самоорганизующейся системы теневой экономики и прогнозирования её изменений.
Понятие СВЕРХСВОЙСТВ ИЛИ ЭМЕРДЖЕНТНЫХ СВОЙСТВ СИСТЕМЫ связано с явлением синергетического эффекта, наличием состояния самоорганизации и самогармонизации систем. Теневая экономика - это сложная открытая самоорганизующаяся система, быстрота реакции в которой непосредственно связана с возникновением диссипативных или пространственно –временных структур. Высокий уровень адаптации системы теневой экономики к быстро изменяющимся внешним условиям сопряжен именно с возникновением диссипативных структур. Стимулирует к их появлению изменения в законодательном окружении, попытки законодательного воздействия на теневую экономику. В условиях более низких трансакционных издержек теневой экономики и её высокого уровня самоорганизации эмнрджентные свойства теневой экономики позволяют быстро адаптироваться к изменениям окружающей среды бизнеса.
2. Предпосылки и средства для решения проблемы Тенизация экономики - это закономерная реакция части общества на бюрократическую заорганизованность и дороговизны входа на легальный рынок. Источниками теневой экономики является несовершенство законодательного окружения, неразвитость институциональной окружения, недостатки в налоговой системе, бизнес на государственных ресурсах, коррупция и т.д.. В условиях реформирования отношений собственности и появления частного сектора сфера хозяйственной деятельности большого количества предприятий перестала быть объектом обязательного государственного финансового контроля, что способствовало распространению явлений тенизации и негативного влияния на состояние экономической безопасности страны и ее регионов. Теневая экономика представляет собой устойчивую систему, с множеством связей, эта система является открытой, неравновесной, нелинейной, сложной, эмерджентной и быстро адаптирующейся к происходящим изменениям внешней и внутренней среды. Очевидно, что высокий уровень самоорганизации теневой экономики обусловлен наличием у неё сверхсвойств или эмерджентных свойств. «Главные свойства системы, определяющие ее идентичность и целостность, не присущи никакой из ее составляющих, не выводятся из свойств частей, а
3. Решение рассматриваемой проблемы Исследование эмерджентных свойств теневой экономики необходимо, поскольку создаёт предпосылки нахождения её слабых мест, влияя на которые как со стороны законодательного окружения, так и с точки зрения макроэкономического системного управляющего воздействия можно будет, на определённый период ограничивать возможности её роста. Целью исследования сверхсвойств теневой экономики является разработка методологии дезорганизующего влияния на теневую экономику, которая должна быть положена в основу государственной политики детенизации экономики.
4
Результаты и дискуссия
Минимизация уровня теневой экономики с точки зрения системного подхода возможна только при разработке комплекса мер по выявлению её слабых мест и привнесения в систему теневой экономики дезорганизующего воздействия. Сущность дезорганизующего влияния может быть определена
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6. Литература
как возникновение нежелательных свойств системы и появление дисфункций. Дезорганизуюшее влияние на систему приводит к росту энтропии, т.е. необходимым инструментом может быть энтропийное тестирование систем и расчёт относительной информационной энтропии системы. Сложность такого расчёта определяется выбором параметров системы. Тема параметров системы – предмет отдельного исследования, от состава параметров системы, возможности их измерения будут формироваться условия прогнозирования влияния на теневую экономику.Также, в качестве направления разработки механизма дезорганизующего воздействия на систему теневой экономики может быть использована концепция байесовского ансамбля нейросетей. [1]. При введении определённых критериев фильтрации и разработки алгоритма распределения шумов и определении возможности управления этими критериями можно предположить, что станет возможным решить задачу возбуждения дисфункций системы. Экономическм – дезорганизующее воздействие будет выражаться в росте трансакционных издержек в теневой экономике.
1. Бирюков А.Н. - О выборе числовых мер оценки погрешности данных и ошибок приближения восстанавливаемых функций в алгоритмах регуляризации нейросетевы моделей налогового контроля // Российский научный журнал «Экономика и управление», С-Петербург, 2010 г. №6., 83-88с 2. Хиценко В.Е. Несколько шагов к новой системной методологии.- [электронный ресурс.] - режим доступа: http://www.certicom.kiev.ua/hitzenko.html
3. Егорова-Гудкова T. И. Мировоззренческо-методологические аспекты проектирования устойчивых экономических систем: Закон Золотого сечения // Сб. науч. трудов Восточноукраинского национального университета им. Владимира Даля. Серия: Менеджмент. – Луганск, 2014. – Вып. 26 (1) . - С. 183184. 4. Сороко Э.М. Золотые сечения, процессы самоорганизации и эволюции систем: Введение в общую теорию гармонии систем. Изд 4-е. — М.: Книжный дом «ЛИБРОКОМ», 2012. – 264 с.
5. Заключение Сверхсвойства системы теневой экономики обуславливаются тем, что существует соответствие характеристик контура операциональной замкнутости системы теневой экономики закону структурной гармонии систем, что является важнейшим признаком устойчивых экономических систем [2]. Таким образом мы можем высказать следующую гипотезу, что в соответствии законом структурной гармонии систем и методологией проектирования устойчивых экономических систем управляющее воздействие с целью дезорганизации теневой экономики должно осуществляться в направлении дестабилизации узлов меры и стимулирования антиузлов [3, 4]. Это непременно приведёт к росту трансакционных издержек и сделает условия бизнеса «в тени» менее конкурентными. Узлами Меры является реккурентный ряд золотых сечений, т.е. целью дезорганизующего воздействия на теневую экономику должно быть изменение её структуры и максимальный «отход» от узлов Меры.
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ИЗМЕНЕНИЯ В ГЛОБАЛЬНОЙ ЭКОНОМИКЕ В УСЛОВИЯХ СТАНОВЛЕНИЯ ЮАНЯ МИРОВОЙ РЕЗЕРВНОЙ ВАЛЮТОЙ CHANGES IN GLOBAL ECONOMY UNDER CONDITIONS OF FORMATION OF RENMINBI AS WORLD'S RESERVE CURRENCY As. Prof., dr. Yegorova-Gudkova Т, Student Panj Li Institute of Mathematics, Economics, Mechanics, Odessa National Mechnikov’s University, Odessa. Ukraine.
[email protected] Abstract: The main issues are considered in this topic:. participation of China in the formation of a new system of world reserve currencies creates new conditions of global financial security KEYWORDS: ANTICRISIS STRATEGY, , ECONOMIC GROWTH, , FORMATION OF RENMINBI AS WORLD'S RESERVE CURRENCY, ECONOMIC SECURITY.
1. Введение
Китая с их контрагентами в соседних Гонконге и Макао и в странах АСЕАН. На сегодняшний день сфера обращения юаня за границей постепенно расширяется по мере повышения экономической силы Китая и углубления взаимодействия с другими странами. Спрос других стран на юань становится больше и больше, валюта страны имеет предварительные условия быть интернациональной. Одним из важных элементов проекта интернационализации юаня стала система соглашений о валютных свопах, которые начал заключать Народный банк Китая с зарубежными регуляторами.
Несовершенная система мировых валют с одной или двумя резервными валютами может привести к серьёзным финансовым кризисам. Участие Китая в формировании новой системы мировых резервных валют создаёт новые условия мировой финансовой безопасности [1]. Китай как страна, занимающая второе место по объемам ВВП в мире и сохраняющая постоянные темпы роста экономики, существенно отличается от других развитых стран, очевидно, что экономике Китая необходимо поддержать свою самостоятельность своеобычность в мировом сотрудничестве и международной торговли. Следовательно, интернационализации юаня становится обязательной стратегией и общей политикой в соответствии с его экономической силой.
По мере реализации проекта интернационализации китайского юаня значительно вырос и общий объем международных торговых расчетов в юанях. Если по состоянию на конец 2011 г. общий объем расчетов в юанях по трансграничной торговле со времени начала указанного проекта достиг 2,58 трлн юаней, то только в 2013 г. объем международных торговых расчетов в юанях составил 5,16 трлн. юаней (прирост на 61% по сравнению с 2012 г.)[2].
Существуют также возможность и необходимость осуществления такой политики: 1, Минимизация влияния валютного кризиса на инвестиционную политику и торговлю с другими странами, балансирование валютных резервов;
3. Решение рассматриваемой проблемы
2, Трансформирование структуры экономики, и смягчение международной конкуренции.
«Увеличение запасов золота повысит уверенность инвесторов в период, когда Китай старается добиться интернационализации юаня», — добавил Ван, управляющий директор китайского подразделения Всемирного золотого совета (World Gold Council, WGC). [3].
3, Необходимость сосредоточения внимания на государственной стратегии долгосрочного развития, снижение степени зависимости от других стран и повышение влияния страны в мире.
После распада Бреттон-Вудской валютной системы мир вошел в эпоху кредитных денег. В отличие от товарных или бумажных денег кредитные деньги имеют особые характеры. С одной стороны, их нельзя обменять на другие конкретные товары, включающие драгоценные монеты. Например, в период золотого стандарта бумажные деньги и банкноты смогли обменять на золото, но кроме кредитных денег. Иными словами, у них нет свободной конвертируемости, и те деньги сами не обладают никакой стоимостью, выражают определенные стоимости в товарообмене посредством кредитов и доверий тех, которые их эмитировали. С другой стороны, у данного вида денег высокая количественная гибкость, количество их эмиссии зависит от спроса. Сторонники посткейнсианства думают, что в отличие от золота кредитные деньги являются задолженностями
2. Предпосылки и средства для решения проблемы Интернационализация любой валюты является непрерывным процессом прогрессивного развития. Только если страны заложили прочную основу в начале периода, они смогут подвигаться вперёд к успехам постоянно и устойчиво. Глобальный проект Китая по превращению своей национальной валюты в одну из мировых валют начался в декабре 2008 г., когда было объявлено об использовании юаней в международных торговых расчетах между компаниями и предприятиями некоторых провинций Южного
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скупить какой-нибудь огромный размер золота на международном рынке, так как действие этой скупки может вызывать резкий рост цены на золото и дальше оказывать отрицательное влияние на систему мирового валютного курса, а также вредить интересам отечественного предприятия обработки золота. В-третьих, «золото хранится у народа», то есть государство поощряет население больше покупать золота в виде товаров. В этой модели народ как хранитель золота, имеет огромный размер запасов. При необходимости правительство сможет скупать определенное его количество золота за валюту, векселями или ценными бумагами. В наши дни, для Китая, третий путь является более выгодным и актуальным. Факторы, влияющие на модель «золото хранится у народа»:
эмиссионных лиц и отношениями между кредиторами и задолжниками. В настоящее время внешняя ситуация перед интернационализацией юаня такая, что в мире долго существовали и функционировали валюты такие, как доллар США, Евро, Фунт стернитов, и другие, их механизм обращения достаточно совершенный и зрелый. Валюта юаня станет такой же мировой резервной только тогда, когда она получит высокую конкурентоспособность и высокий уровень доверия к ней. Уровень доверия к валюте зависит от множества факторов, один из важных это количество и качество активов центрального банка данной страны. К качеству активов ЦБ относится финансовая стабильность, чем выше качество активов, тем стабильнее курс валют и финансовая система.
1. Быстро увеличивается ВВП на душу населения и доход населения Китая; 2. Огромный размер депозитов населения в банках и мало методов инвестирования; 3. Поддержка политики государства; 4. Традиция потребления золота населением;
Увеличение запасов золота способствует усилению стабильности системы активов центрального банка, повышению уровня доверия к юаню. Таблица 1. Структура активов Центробанков Структура активов ЦБ
США
Евросоюз
Китай
Япония
Золотые запасы
8,6%
14,81%
0,79%
0,2%
Валютные резервы
0,6%
9,57%
82,81%
2,37%
Государственные долги и ценные бумаги
55,11%
1,01%
4,8;
80,9%
Другие
35,69%
74,61%
11,6%
16,53%
Постоянное повышение объема добычи и производства золота, и соответственно сокращение импорта золота
5.
Заключение Де-факто юань в определённой мере уже стал для некоторых стран резервной валютой. Однако де-юре он еще далек от этого. Последней инстанцией, определяющей статус валют, остается на сегодняшний день Международный валютный фонд. В группу резервных валют МВФ помещены всего четыре валюты – доллар США, евро, британский фунт стерлингов, японская иена. Именно они составляют корзину валют, с помощью которой определяется курс специальных прав заимствования.
Структура активов ЦБ 2013 г., источник официальные сайты ЦБ данных стран, и официальный сайт МВФ
Перспектива золотого юаня в качестве мировых денег вероятна, но путь существует долгий путь со множеством препятствий. Сначала юань может стать региональной валютой, может стать резервной валютой и для развивающихся стран, затем фактически станет именно «мировым». Несомненно одно – становление юаня мировой резервной валютой изменит глобальные условия не только в экономическом, но и во всех возможных аспектах мирового порядка.
Эти данные показывают, что большинство активов ЦБ США, Евросоюза и Японии – золото, государственные долги и ценные бумаги, представляющие собой постоянной доходностью, и сравнительно низкой вероятностью воздействия кризиса. Наоборот, у ЦБ Китая большинство активов является иностранными валютными резервами, в том числе около 65% - в долларах, и на стоимость данного вида активов сильно влияет изменение курса валют. Можем говорить, что структура активов центрального банка Китая не стабильная, и когда возникнет кризис то может иметь место значительный ущерб всей экономической системе государства.
Литература 1. Осипова О.А., Пухов С.Г. Экономический кризис 1997-99 гг. в Таиланде, Корее и Индонезии, 1999. //Колосюк Н. А. Причины азиатского финансового кризиса. / Известия Восточного института № 7. 2003
4. Результаты и дискуссия
2. Aizenman J., Lee J. (2006). Financial versus monetary mercantilism: Long-run view of large international reserves hoarding. IMF Working Paper, No. WP/06/280.
Теоретически существуют 3 основных пути или модели к увеличению размера запасов, во-первых, государственная покупка на внутреннем рынке, модель которая несет сильный характер плановой экономики, не полезно для развития рынка золота; Во-вторых, покупка золота заграницей, то есть на внешнем рынке. Недостатком этой модели является то, что каждый год количество добычи золота в мире определено, правительство нельзя сразу
3. Аруна Гаитонде. Китаю следует увеличить золотые запасы.//Rough&Polished. 03 2015.
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СИСТЕМА ФИНАНСОВОГО КОНТРОЛЯ ГОСУДАРСТВА КАК ИНСТРУМЕНТ ДЕТЕНИЗАЦИИ ЭКОНОМИКИ SYSTEM OF FINANCIAL CONTROL OF STATE AS INSTRUMENT OF LEGALIZATION OF THE ECONOMY Honored Economist of Ukraine, Karabanov A., Post Gr Student, Krygin A., Director Tetlezkij J. Institute of Mathematics, Economics, Mechanics, Odessa National Mechnikov’s University, Odessa. Ukraine. Abstract: The main issues are considered in this topic: problem of financial sector of the economy on the example of the finance control, the emergence of institutional traps and shadowing of economic processes in using of state’s finance due to the imperfections of the market mechanism and legislative environment KEYWORDS: TRANSACTION COSTS, ECONOMIC SECURITY OF STATE, SHADOWING OF ECONOMIC PROCESSES, INSTITUTIONAL TRAPS, FINANCE CONTROL, TRANSFERTED PRICES
1. Введение
контроль в той или иной форме присутствует на всех стадиях управленческого цикла, но в первую очередь он необходим, как ранее отмечалось, при выборе долгосрочной стратегии развития, во время стратегического планирования развития государства, - и, если обобщить: требует использования системного подхода.. Эффективно организованный контроль использования государственных финансов должен обеспечивать прозрачную деятельность субъектов ведения хозяйства и положительно влиять на экономическую безопасность страны.
В странах с транзитивной экономикой довольно часто возникает бизнес на государственных финансах. Он является как источником теневой экономики, так и стимулятором коррупции. В итоге, бюджетные средства подвергаются как нецелевому, так и не рациональному использованию. Для преодоления подобных явлений в Украине существует специализированная институция - Государственная финансовая инспекция. Деятельность этой инспекции значительно эффективность расходования бюджетных средств..
повышает
3. Решение рассматриваемой проблемы Система государственных финансов должна быть структурирована и спроектирована на принципах самоорганизации – только так можно проектировать условия взаимодействия любой системы с внешней средой, в т.ч и системы государственных финансов и ее регионов. Как государство, так и ее регионы являются открытыми неравновесными системами, изменения в которых становятся заметными, когда достигают точки перехода или бифуркации. Система государственных финансов по отношению к системе экономической безопасности, с одной стороны является ее инвариантом, с другой стороны - является подсистемой. Если система государственных финансов спроектирована корректно, то на основании сбора и анализа совокупности индикаторов мы можем рассчитать относительную информационную энтропию и спрогнозировать события достижения точки бифуркации.
.
2. Предпосылки и средства для решения проблемы Государственный финансовый контроль может существовать только как система, основными составляющими частями которой являются: нормативно - правовая база, органы, осуществляющие государственный финансовый контроль, формы и методы финансового контроля. Отсутствие системного решения теории, методологии, методики и практики организации процесса финансового контроля как подсистемы открытой нелинейной сложной и системы экономической безопасности. не способствует полной реализации ее функций и выполнению задач обеспечения эффективного использования государственных финансов и именно – поддержания условий экономической безопасности государства.
По мнению. Проф. Э. Сороко «Метод компаративного анализа и энтропийной индикации систем
ˆ с ее узловым (антиузловым) путем сопоставления меры H значением одинаково приемлем во всех случаях, где есть связанное в структурах разнообразие. А значит, он есть средство кодификации состояния функционального статуса соответствующих систем и подсистем: геологических, биологических, экологических, демографических, экономических, финансовых, информационных, технических, геополитических, лингвистических и других специфик.».
Эффективно организованный контроль использования государственных финансов должна обеспечивать прозрачную деятельность субъектов хозяйствования и положительно влиять на экономическую безопасность страны. Рыночная экономика не исключает, а, наоборот, предполагает развитую систему органов внутреннего и внешнего финансового контроля. Государственный финансовый
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5. Заключение
Данное положение полностью соответствует ранее рассмотренной нами возможностью применения ценологического подхода (по Кудрину) при формировании процессов финансового контроля применительно к объектам, использующим средства государственного бюджета. .
Прогнозирование «контура эффективности» аудита эффективности, т.е. модели и индикаторов, выход за которые будет свидетельствовать как о позитивном, так и негативном положении дел даст возможность разработать уникальные критерии для углублённого изучения эффективности расходования средств на изучение результатов конкретного государственного проекта или программы.
4. Результаты и дискуссия В Украине создаётся новая форма государственного финансового контроля – аудит эффективности, в соответствии с принятым новым законом Украины «Об аудиторской деятельности». Предполагается, что она будет более эффективна в условиях дефицита бюджетных средств в государстве. Аудит эффективности, по сути, отличается от финансового аудита. Отличие заключается прежде всего в том, что целью финансового аудита является оценка достоверности бухгалтерского учета и финансовой отчетности, а целью аудита эффективности – оценка уровня эффективности проектов и программ, финансируемых из госбюджета, а также оценка деятельности структур, которые используют государственные ресурсы.
В качестве типовой модели можно использовать модель Лаффера, в качестве рабочего подхода – ценологический подход и расчёт относительной информационной энтропии. Литература 1. Аудит адміністративної діяльності: Теорія та практика/ Пер. з англ.. В.Шульги. -К.: Основи, 2000. –С.242. 2. Дзюба С. Направления преобразований в аудиторской деятельности // Экономика Украины, 2003, No1 с.36-42. 3. Кудрин Б.И. Самодостаточность общей и прикладной ценологии / Техногенная самоорганизация и математический аппарат ценологических исследований. Вып. 28. «Ценологические исследования». - М., 2005. – С.179-180.
Процедура аудита эффективности использования ГФ менее регламентирована и заорганизована, что даёт возможность предложения авторских методик аудита (например, основанных на применении ценологического подхода, расчета относительной информационной энтропии и прогнозирования на этой основе «контуров эффективности».
4. Єгорова-Гудкова Т. І. , М.В. Бойко., О.Є.Звірков . Управління складними системами за допомогою ценологічного підходу (на прикладі системи економічної безпеки держави) / Т. І. Єгорова-Гудкова, М.В. Бойко., О.Є.Звірков // Науковий вісник Полтавського університету економіки і торгівлі. 2015. № 1 (69), ч. 1. С.41 – 49
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