29 research outputs found

    An Approach to Model Checking of Multi-agent Data Analysis

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    The paper presents an approach to verification of a multi-agent data analysis algorithm. We base correct simulation of the multi-agent system by a finite integer model. For verification we use model checking tool SPIN. Protocols of agents are written in Promela language and properties of the multi-agent data analysis system are expressed in logic LTL. We run several experiments with SPIN and the model.Comment: In Proceedings MOD* 2014, arXiv:1411.345

    Autotuning Parallel Programs by Model Checking

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    The paper presents a new approach to autotuning data-parallel programs. Autotuning is a search for optimal program settings which maximize its performance. The novelty of the approach lies in the use of the model checking method to find the optimal tuning parameters by the method of counterexamples. In our work, we abstract from specific programs and specific processors by defining their representative abstract patterns. Our method of counterexamples implements the following four steps. At the first step, an execution model of an abstract program on an abstract processor is described in the language of a model checking tool. At the second step, in the language of the model checking tool, we formulate the optimality property that depends on the constructed model. At the third step, we find the optimal values of the tuning parameters by using a counterexample constructed during the verification of the optimality property. In the fourth step, we extract the information about the tuning parameters from the counter-example for the optimal parameters. We apply this approach to autotuning parallel programs written in OpenCL, a popular modern language that extends the C language for programming both standard multi-core processors (CPUs) and massively parallel graphics processing units (GPUs). As a verification tool, we use the SPIN verifier and its model representation language Promela, whose formal semantics is good for modelling the execution of parallel programs on processors with different architectures

    Алгоритмы для BDI-Π°Π³Π΅Π½Ρ‚ΠΎΠ², основанныС Π½Π° знаниях

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    Multiagent algorithm is a knowledge-based distributed algorithm that solves some problems by means of cooperative work of agents. From an individual agent's perspective, a multiagent algorithm is a reactive and proactive knowledge/believe-based rational algorithm aimed to achieve an agent's own desires. In the paper we study a couple of knowledge-based multiagent algorithms. One particular algorithm is for a system consisting of agents that arrive one by one (in a non-deterministic order) to a resource center to rent (for a while) one of available desired resources. Available resources are passive, they form a cloud; each of the available resources is lent on demand if there is no race for this resource and returns to the cloud after use. Agents also form a cloud but leave the cloud immediately when they rent a desired resource. The problem is to design a knowledge-based multiagent algorithm, which allows each arriving agent eventually to rent some of desired resources (without race for these resources).ΠœΡƒΠ»ΡŒΡ‚ΠΈΠ°Π³Π΅Π½Ρ‚Π½Ρ‹ΠΉ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌ β€” это распрСдСлённый Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌ, основанный Π½Π° знаниях, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹ΠΉ Ρ€Π΅ΡˆΠ°Π΅Ρ‚ Π½Π΅ΠΊΠΎΡ‚ΠΎΡ€ΡƒΡŽ ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌΡƒ посрСдством совмСстной Ρ€Π°Π±ΠΎΡ‚Ρ‹ Π°Π³Π΅Π½Ρ‚ΠΎΠ². BDI-Π°Π³Π΅Π½Ρ‚ β€” это Π°Π³Π΅Π½Ρ‚, ΠΎΠ±Π»Π°Π΄Π°ΡŽΡ‰ΠΈΠΉ убСТдСниями (Belief), ТСланиями (Desire) ΠΈ намСрСниями (Intention). Π‘ Ρ‚ΠΎΡ‡ΠΊΠΈ зрСния Ρ‚Π°ΠΊΠΎΠ³ΠΎ Π°Π³Π΅Π½Ρ‚Π°, ΠΌΡƒΠ»ΡŒΡ‚ΠΈΠ°Π³Π΅Π½Ρ‚Π½Ρ‹ΠΉ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌ β€” это Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌ, основанный Π½Π° Π΅Π³ΠΎ знаниях ΠΈ убСТдСниях, с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠ³ΠΎ достигаСтся Π²Ρ‹ΠΏΠΎΠ»Π½Π΅Π½ΠΈΠ΅ Π΅Π³ΠΎ ΠΆΠ΅Π»Π°Π½ΠΈΠΉ посрСдством ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ осущСствлСния Π½Π°ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ. ΠœΡ‹ считаСм Ρ‚Π°ΠΊΠΆΠ΅, Ρ‡Ρ‚ΠΎ Π°Π³Π΅Π½Ρ‚Ρ‹ Ρ€Π΅Π°ΠΊΡ‚ΠΈΠ²Π½Ρ‹, ΠΏΡ€ΠΎΠ°ΠΊΡ‚ΠΈΠ²Π½Ρ‹ ΠΈ Ρ€Π°Ρ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹. Π’ этой ΡΡ‚Π°Ρ‚ΡŒΠ΅ ΠΌΡ‹ ΠΏΡ€Π΅Π΄Π»Π°Π³Π°Π΅ΠΌ ΠΈ ΠΈΠ·ΡƒΡ‡Π°Π΅ΠΌ Π΄Π²Π° ΠΌΡƒΠ»ΡŒΡ‚ΠΈΠ°Π³Π΅Π½Ρ‚Π½Ρ‹Ρ… Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ°, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ основаны Π½Π° знаниях. Π’ частности, ΠΌΡ‹ ΠΏΡ€Π΅Π΄Π»Π°Π³Π°Π΅ΠΌ ΠΌΡƒΠ»ΡŒΡ‚ΠΈΠ°Π³Π΅Π½Ρ‚Π½Ρ‹ΠΉ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌ для ΡΠ»Π΅Π΄ΡƒΡŽΡ‰Π΅ΠΉ Π·Π°Π΄Π°Ρ‡ΠΈ Π°Ρ€Π΅Π½Π΄Ρ‹ рСсурсов. БистСма состоит ΠΈΠ· Π°Π³Π΅Π½Ρ‚ΠΎΠ², ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΏΡ€ΠΈΠ±Ρ‹Π²Π°ΡŽΡ‚ ΠΎΠ΄ΠΈΠ½ Π·Π° Π΄Ρ€ΡƒΠ³ΠΈΠΌ Π² ΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ»ΡŒΠ½ΠΎΠΌ порядкС Π² рСсурсный Ρ†Π΅Π½Ρ‚Ρ€, Ρ‡Ρ‚ΠΎΠ±Ρ‹ Π°Ρ€Π΅Π½Π΄ΠΎΠ²Π°Ρ‚ΡŒ ΠΎΠ΄ΠΈΠ½ ΠΈΠ· прСдоставляСмыхрСсурсов. ΠŸΡ€Π΅Π΄ΠΎΡΡ‚Π°Π²Π»ΡΠ΅ΠΌΡ‹Π΅ рСсурсы пассивны, ΠΎΠ½ΠΈ ΠΎΠ±Ρ€Π°Π·ΡƒΡŽΡ‚ ΠΎΠ±Π»Π°ΠΊΠΎ. Если Π·Π° рСсурс Π½Π΅Ρ‚ ΠΊΠΎΠ½ΠΊΡƒΡ€Π΅Π½Ρ†ΠΈΠΈ, Ρ‚ΠΎ ΠΎΠ½ прСдоставляСтся ΠΏΠΎ запросу, ΠΈ возвращаСтся Π² ΠΎΠ±Π»Π°ΠΊΠΎ послС использования. АгСнты Ρ‚Π°ΠΊΠΆΠ΅ ΠΎΠ±Ρ€Π°Π·ΡƒΡŽΡ‚ ΠΎΠ±Π»Π°ΠΊΠΎ, Π½ΠΎ ΠΊΠΎΠ³Π΄Π° Π°Ρ€Π΅Π½Π΄ΡƒΡŽΡ‚ Π½ΡƒΠΆΠ½Ρ‹ΠΉ рСсурс, Ρ‚ΠΎ сразу ΠΆΠ΅ ΠΏΠΎΠΊΠΈΠ΄Π°ΡŽΡ‚ рСсурсный Ρ†Π΅Π½Ρ‚Ρ€. Π—Π°Π΄Π°Ρ‡Π° состоит Π² Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠ΅ ΠΌΡƒΠ»ΡŒΡ‚ΠΈΠ°Π³Π΅Π½Ρ‚Π½ΠΎΠ³ΠΎ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌΠ°, основанного Π½Π° знаниях, ΠΎΠ±Π»Π°Π΄Π°ΡŽΡ‰Π΅Π³ΠΎ ΡΠ»Π΅Π΄ΡƒΡŽΡ‰ΠΈΠΌ свойством коррСктности: ΠΊΠ°ΠΆΠ΄Ρ‹ΠΉ ΠΏΡ€ΠΈΠ±Ρ‹Π²Π°ΡŽΡ‰ΠΈΠΉ Π² рСсурсный Ρ†Π΅Π½Ρ‚Ρ€ Π°Π³Π΅Π½Ρ‚ Ρ€Π°Π½ΠΎ ΠΈΠ»ΠΈ ΠΏΠΎΠ·Π΄Π½ΠΎ Π°Ρ€Π΅Π½Π΄ΡƒΠ΅Ρ‚ ΠΊΠ°ΠΊΠΎΠΉ-Π»ΠΈΠ±ΠΎ ΠΈΠ· Π·Π°ΠΏΡ€Π°ΡˆΠΈΠ²Π°Π΅ΠΌΡ‹Ρ… рСсурсов Π±Π΅Π· ΠΊΠΎΠ½ΠΊΡƒΡ€Π΅Π½Ρ†ΠΈΠΈ Π·Π° этот рСсурс Π² Π΄Π°Π½Π½Ρ‹ΠΉ ΠΌΠΎΠΌΠ΅Π½Ρ‚

    ΠŸΠΎΠ΄Ρ…ΠΎΠ΄ ΠΊ автонастройкС ΠΏΠ°Ρ€Π°Π»Π»Π΅Π»ΡŒΠ½Ρ‹Ρ… ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΊΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ

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    The paper presents a new approach to autotuning data-parallel programs. Autotuning is a search for optimal program settings which maximize its performance. The novelty of the approach lies in the use of the model checking method to find the optimal tuning parameters by the method of counterexamples. In our work, we abstract from specific programs and specific processors by defining their representative abstract patterns. Our method of counterexamples implements the following four steps. At the first step, an execution model of an abstract program on an abstract processor is described in the language of a model checking tool. At the second step, in the language of the model checking tool, we formulate the optimality property that depends on the constructed model. At the third step, we find the optimal values of the tuning parameters by using a counterexample constructed during the verification of the optimality property. In the fourth step, we extract the information about the tuning parameters from the counter-example for the optimal parameters. We apply this approach to autotuning parallel programs written in OpenCL, a popular modern language that extends the C language for programming both standard multi-core processors (CPUs) and massively parallel graphics processing units (GPUs). As a verification tool, we use the SPIN verifier and its model representation language Promela, whose formal semantics is good for modelling the execution of parallel programs on processors with different architectures.Π’ этой ΡΡ‚Π°Ρ‚ΡŒΠ΅ прСдставлСн Π½ΠΎΠ²Ρ‹ΠΉ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄ ΠΊ автонастройкС ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌ, ΠΏΠ°Ρ€Π°Π»Π»Π΅Π»ΡŒΠ½Ρ‹Ρ… ΠΏΠΎ Π΄Π°Π½Π½Ρ‹ΠΌ. Автонастройка -- это поиск ΠΎΠΏΡ‚ΠΈΠΌΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€ΠΎΠ² настройки ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡ‹, ΠΏΡ€ΠΈ ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… Π΅Ρ‘ ΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΡŒ оказываСтся максимальной. Новизна ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Π° состоит Π² использовании ΠΌΠ΅Ρ‚ΠΎΠ΄Π° ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΊΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ для поиска ΠΎΠΏΡ‚ΠΈΠΌΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€ΠΎΠ² настройки ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ ΠΊΠΎΠ½Ρ‚Ρ€ΠΏΡ€ΠΈΠΌΠ΅Ρ€ΠΎΠ². Π’ нашСй Ρ€Π°Π±ΠΎΡ‚Π΅ ΠΌΡ‹ абстрагируСмся ΠΎΡ‚ ΠΊΠΎΠ½ΠΊΡ€Π΅Ρ‚Π½Ρ‹Ρ… ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌ ΠΈ ΠΊΠΎΠ½ΠΊΡ€Π΅Ρ‚Π½Ρ‹Ρ… процСссоров, задавая ΠΈΡ… ΠΏΡ€Π΅Π΄ΡΡ‚Π°Π²ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Π΅ абстрактныС ΡˆΠ°Π±Π»ΠΎΠ½Ρ‹. Наш ΠΌΠ΅Ρ‚ΠΎΠ΄ ΠΊΠΎΠ½Ρ‚Ρ€ΠΏΡ€ΠΈΠΌΠ΅Ρ€ΠΎΠ² состоит Π² Ρ€Π΅Π°Π»ΠΈΠ·Π°Ρ†ΠΈΠΈ ΡΠ»Π΅Π΄ΡƒΡŽΡ‰ΠΈΡ… Ρ‡Π΅Ρ‚Ρ‹Ρ€Ρ‘Ρ… шагов. На ΠΏΠ΅Ρ€Π²ΠΎΠΌ шагС Π½Π° языкС инструмСнта ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΊΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ задаётся модСль исполнСния абстрактной ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡ‹ Π½Π° абстрактном процСссорС. На Π²Ρ‚ΠΎΡ€ΠΎΠΌ шагС Π½Π° языкС инструмСнта ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΊΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Ρ„ΠΎΡ€ΠΌΡƒΠ»ΠΈΡ€ΡƒΠ΅ΠΌ свойство ΠΎΠΏΡ‚ΠΈΠΌΠ°Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ, зависящСС ΠΎΡ‚ построСнной ΠΌΠΎΠ΄Π΅Π»ΠΈ. На Ρ‚Ρ€Π΅Ρ‚ΡŒΠ΅ΠΌ шагС ΠΏΠΎΠ΄Π±ΠΈΡ€Π°Π΅ΠΌ ΠΎΠΏΡ‚ΠΈΠΌΠ°Π»ΡŒΠ½Ρ‹Π΅ значСния ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€ΠΎΠ² настройки посрСдством использования ΠΊΠΎΠ½Ρ‚Ρ€ΠΏΡ€ΠΈΠΌΠ΅Ρ€ΠΎΠ², построСнных Π² Ρ…ΠΎΠ΄Π΅ Π²Π΅Ρ€ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ свойства ΠΎΠΏΡ‚ΠΈΠΌΠ°Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ. На Ρ‡Π΅Ρ‚Π²Ρ‘Ρ€Ρ‚ΠΎΠΌ шагС ΠΈΠ·Π²Π»Π΅ΠΊΠ°Π΅ΠΌ ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΡŽ ΠΎ ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€Π°Ρ… настройки ΠΈΠ· ΠΊΠΎΠ½Ρ‚Ρ€ΠΏΡ€ΠΈΠΌΠ΅Ρ€Π° для ΠΎΠΏΡ‚ΠΈΠΌΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΏΠ°Ρ€Π°ΠΌΠ΅Ρ‚Ρ€ΠΎΠ². ΠœΡ‹ примСняСм этот ΠΏΠΎΠ΄Ρ…ΠΎΠ΄ ΠΊ автонастройкС ΠΏΠ°Ρ€Π°Π»Π»Π΅Π»ΡŒΠ½Ρ‹Ρ… ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌ, написанных Π½Π° языкС OpenCL -- соврСмСнном популярном языкС, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹ΠΉ Ρ€Π°ΡΡˆΠΈΡ€ΡΠ΅Ρ‚ язык C для программирования ΠΊΠ°ΠΊ ΠΎΠ±Ρ‹Ρ‡Π½Ρ‹Ρ… многоядСрных процСссоров (CPU), Ρ‚Π°ΠΊ ΠΈ массивно-ΠΏΠ°Ρ€Π°Π»Π»Π΅Π»ΡŒΠ½Ρ‹Ρ… графичСских процСссоров (GPU). Π’ качСствС инструмСнта Π²Π΅Ρ€ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ ΠΌΡ‹ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΠ΅ΠΌ Π²Π΅Ρ€ΠΈΡ„ΠΈΠΊΠ°Ρ‚ΠΎΡ€ SPIN ΠΈ Π΅Π³ΠΎ язык прСдставлСния ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Promela, Ρ„ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½Π°Ρ сСмантика ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠ³ΠΎ позволяСт ΠΌΠΎΠ΄Π΅Π»ΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒ исполнСниС ΠΏΠ°Ρ€Π°Π»Π»Π΅Π»ΡŒΠ½Ρ‹Ρ… ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌ Π½Π° процСссорах с Ρ€Π°Π·Π»ΠΈΡ‡Π½ΠΎΠΉ Π°Ρ€Ρ…ΠΈΡ‚Π΅ΠΊΡ‚ΡƒΡ€ΠΎΠΉ

    New hybrid materials on the basis of magnetite and magnetite-gold nanoparticles for biomedical application

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    During last decades magnetite nanoparticles (NPs) attract a deep interest of scientists due to their potential application in therapy and diagnostics. However, magnetite nanoparticles are toxic and non-stable in physiological conditions. To solve these problems, we decided to create two types of hybrid systems based on magnetite and gold which is inert and biocompatible: gold as a shell material (first type) and gold as separate NPs interfacially bond to magnetite NPs (second type). An additional advantage of gold is the possibility of its functionalization with a variety of sulphur-containing ligands; that is very important for drug delivery and creating of tissue-specific MRI contrast agents. The synthesis of the first type hybrid nanoparticles was carried out as follows: magnetite nanoparticles with an average diameter of 9Β±2 nm were obtained by co-precipitation of iron (II, III) chlorides then they were covered with gold shell by iterative reduction of hydrogen tetrachloroaurate with hydroxylamine hydrochloride. According to the TEM, ICP MS and EDX data, final nanoparticles had an average diameter of 31Β±4 nm and contained iron even after hydrochloric acid treatment. However, iron signals (K-line, 7,1 keV) were not localized so we can’t speak about one single magnetic core. Described nanoparticles covered with mercapto-PEG acid were non-toxic for human prostate cancer PC-3/ LNCaP cell lines (more than 90% survived cells as compared to control) and had high R2-relaxivity rates (\u3e190 mМ-1s-1) that exceed the transverse relaxation rate of commercial MRI-contrasting agents. These nanoparticles were also used for chymotrypsin enzyme immobilization. The effect of alternating magnetic field on catalytic properties of chymotrypsin immobilized on magnetite nanoparticles, notably the slowdown of catalyzed reaction at the level of 35-40 % was found. The most probable reason for the observed effect is the change of active centers topology on the enzyme surface as a result of its deformation under applied forces. The synthesis of the second type hybrid nanoparticles also involved two steps. Firstly, spherical gold nanoparticles with an average diameter of 9Β±2 nm were synthesized by the reduction of hydrogen tetrachloroaurate with oleylamine; secondly, they were used as seeds during magnetite synthesis by thermal decomposition of iron pentacarbonyl in octadecene. As a result, so-called dumbbell-like structures were obtained where magnetite (cubes with 25Β±6 nm diagonal) and gold nanoparticles were connected together pairwise. By HRTEM method (first time for this type of structure) an epitaxial growth of magnetite nanoparticles on gold surface with co-orientation of (111) planes was discovered. These nanoparticles were transferred into water by means of block-copolymer Pluronic F127 then loaded with anti-cancer drug doxorubicin and also PSMA-vector specific for LNCaP cell line. Obtained nanoparticles were found to have moderate toxicity for human prostate cancer cells and got into the intracellular space after 45 minutes of incubation (according to fluorescence microscopy data). These materials are also perspective from MRI point of view (R2-relaxivity rates \u3e70 mМ-1s-1). Thereby, in this work magnetite-gold hybrid nanoparticles, which have a strong potential for biomedical application, particularly in targeted drug delivery and magnetic resonance imaging, were synthesized and characterized. That paves the way to the development of new medicine types – theranostics. The authors knowledge financial support from Ministry of Education and Science of the Russian Federation (14.607.21.0132, RFMEFI60715X0132). This work was also supported by Grant of Ministry of Education and Science of the Russian Federation К1-2014-022, Grant of Russian Scientific Foundation 14-13-00731 and MSU development program 5.13

    Mathematical Modelling of the Parameters of Braided Textile Tapes

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    Braided textile materials are widely used in many industries and agriculture. Braided tapes are used for domestic purposes, in the food industry, in construction, in medicine, in aircraft manufacturing, in electrical engineering, etc. Every braided product must correspond to a unique group of parameters and properties, depending on the initial manufacturing parameters. The production of braided tapes is still insufficiently explored. In the process of designing and manufacturing products with specified parameters, it is necessary to substantiate the formation of braided products. The manufacture of products with specific parameters and properties, and the creation of rational technological modes for that production represent urgent scientific issues to be addressed. One way to solve this problem is to conduct factorial experiments. This article thus presents the results of a factorial experiment, during which the following input parameters were determined based on preliminary studies: type of raw material, the linear density of raw materials and speed of removal of the product from the formation zone. The following were chosen as output parameters: breaking load, breaking elongation, the linear density of tapes, product width and the number of strands per 10 mm. The limits of factor variation were determined for four types of raw materials. Based on the results of the processing of the obtained experimental data, linear mathematical models were developed. The results of the verification of mathematical models indicated that they adequately describe the process of braiding tapes within the intervals determined by the conditions of the experiment. We thus established a connection between the factors of the braiding process and the properties of braided tapes

    poST

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    Publisher Copyright: AuthorThis paper presents the core concepts for the poST language - a process-oriented extension of the IEC 61131-3 Structured Text (ST) language which intends to provide a conceptual consistency of the PLC source code with technological description of the plant operating procedure. The poST can be seamlessly used as a textual programming language for complex PLC software in the context of IEC 61131-3 (3rd Edition). The language combines the advantages of FSM-based programming with the conventional syntax of the ST language which would facilitate its adoption. The poST language assumes that a poST-program is a set of weakly connected concurrent processes, structurally and functionally corresponding to the technological description of the plant. Each process is specified by a sequential set of states. The states are specified by a set of the ST constructs, extended by TIMEOUT operation, SET STATE operation, and START / STOP / check state operations to communicate with other processes. The paper describes the basic syntax of the poST language, demonstrates the usage of the poST language by developing control software for an elevator, and compares the development in poST with pure Structured Text.Peer reviewe

    ΠžΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΡ процСссов, ориСнтированная Π½Π° Π²Π΅Ρ€ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΡŽ

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    This paper presents the ontology of the concurrent processes close to Hoare communicating sequential processes. It is the part of the intellectual system for supporting verification of behavioural properties of these processes. Our ontological representation of the processes is oriented both to the application of formal verification methods and to the extraction of information from technical documentation (by our previously developed system of information extraction from a natural language text). We describe the ontology classes and domains that define communicating concurrent processes. These processes are characterized by sets of local and shared variables, a list of actions on these variables which change their values, a list of channels for the process communication (which, in turn, are characterized by the type of reading messages, capacity, ways of writing and reading, and reliability), and also a list of communication actions for sending messages. In addition to the formal mathematical definition of classes and domains of the ontology, examples of descriptions of some ontological classes as well as typical properties and axioms for them are specified in the editor Prot ́eg ́e in the OWL language with the use of the inference rules in the SWRL language. The formal operational semantics of communicating processes is determined on their ontological representation and is given as a labelled transition system. It is reduced to the local operational semantics of separate process instances in the interleaving model. We specialize several types of processes from the subject domain of automatic control systems that model the typical functional elements of the automatic control system (sensors, comparators and regulators) as well as their combinations. The concepts of the specialized ontology are illustrated by the example of a control part for a bottle-filling system.Π’ ΡΡ‚Π°Ρ‚ΡŒΠ΅ прСдставлСна онтология процСссов, Π±Π»ΠΈΠ·ΠΊΠΈΡ… Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΠΌ ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΠ½Ρ‹ΠΌ процСссам Π₯ΠΎΠ°Ρ€Π°. Она являСтся Ρ‡Π°ΡΡ‚ΡŒΡŽ ΠΈΠ½Ρ‚Π΅Π»Π»Π΅ΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½ΠΎΠΉ систСмы ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΠΈ Π²Π΅Ρ€ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ свойств повСдСния Ρ‚Π°ΠΊΠΈΡ… процСссов. НашС онтологичСскоС прСдставлСниС процСссов ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½ΠΎ ΠΊΠ°ΠΊ Π½Π° ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ Ρ„ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² Π²Π΅Ρ€ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ, Ρ‚Π°ΠΊ ΠΈ Π½Π° ΠΈΠ·Π²Π»Π΅Ρ‡Π΅Π½ΠΈΠ΅ ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ ΠΈΠ· тСхничСской Π΄ΠΎΠΊΡƒΠΌΠ΅Π½Ρ‚Π°Ρ†ΠΈΠΈ (с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ нашСй Ρ€Π°Π½Π΅Π΅ Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½Π½ΠΎΠΉ систСмы извлСчСния ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ ΠΈΠ· тСкстов Π½Π° СстСствСнном языкС). ΠœΡ‹ описываСм классы ΠΈ Π΄ΠΎΠΌΠ΅Π½Ρ‹ ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΡΡŽΡ‚ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΠ΅ процСссы. Π­Ρ‚ΠΈ процСссы Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ·ΡƒΡŽΡ‚ΡΡ мноТСствами Π»ΠΎΠΊΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΈ раздСляСмых ΠΏΠ΅Ρ€Π΅ΠΌΠ΅Π½Π½Ρ‹Ρ…, списком дСйствий Π½Π°Π΄ этими ΠΏΠ΅Ρ€Π΅ΠΌΠ΅Π½Π½Ρ‹ΠΌΠΈ, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΈΠ·ΠΌΠ΅Π½ΡΡŽΡ‚ ΠΈΡ… значСния, списком ΠΊΠ°Π½Π°Π»ΠΎΠ² взаимодСйствия процСссов (ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅, Π² свою ΠΎΡ‡Π΅Ρ€Π΅Π΄ΡŒ, Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ·ΡƒΡŽΡ‚ΡΡ Ρ‚ΠΈΠΏΠΎΠΌ чтСния сообщСний, Π΅ΠΌΠΊΠΎΡΡ‚ΡŒΡŽ, способами записи ΠΈ считывания, Π° Ρ‚Π°ΠΊΠΆΠ΅ Π½Π°Π΄Π΅ΠΆΠ½ΠΎΡΡ‚ΡŒΡŽ), списком ΠΊΠΎΠΌΠΌΡƒΠ½ΠΈΠΊΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… дСйствий для ΠΎΡ‚ΠΏΡ€Π°Π²ΠΊΠΈ сообщСний. Помимо Ρ„ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½ΠΎΠ³ΠΎ матСматичСского опрСдСлСния классов ΠΈ Π΄ΠΎΠΌΠ΅Π½ΠΎΠ² ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΠΏΡ€ΠΈΠ²Π΅Π΄Π΅Π½Ρ‹ ΠΏΡ€ΠΈΠΌΠ΅Ρ€Ρ‹ описаний Π½Π΅ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… онтологичСских классов, Π° Ρ‚Π°ΠΊΠΆΠ΅ Ρ‚ΠΈΠΏΠΎΠ²Ρ‹Ρ… свойств ΠΈ аксиом для Π½ΠΈΡ… Π² Ρ€Π΅Π΄Π°ΠΊΡ‚ΠΎΡ€Π΅ Prot ́eg ́e Π½Π° языкС OWL с использованиСм ΠΏΡ€Π°Π²ΠΈΠ» Π²Ρ‹Π²ΠΎΠ΄Π° Π½Π° языкС SWRL. Для онтологичСского прСдставлСния Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡ‚Π²ΡƒΡŽΡ‰ΠΈΡ… процСссов опрСдСляСтся ΠΈΡ… Ρ„ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½Π°Ρ опСрационная сСмантика, которая задаСтся с использованиСм ΠΏΠΎΠΌΠ΅Ρ‡Π΅Π½Π½ΠΎΠΉ систСмы ΠΏΠ΅Ρ€Π΅Ρ…ΠΎΠ΄ΠΎΠ². Π’ ΠΈΠ½Ρ‚Π΅Ρ€Π»ΠΈΠ²ΠΈΠ½Π³ΠΎΠ²ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΎΠ½Π° сводится ΠΊ локальной ΠΎΠΏΠ΅Ρ€Π°Ρ†ΠΈΠΎΠ½Π½ΠΎΠΉ сСмантикС ΠΎΡ‚Π΄Π΅Π»ΡŒΠ½Ρ‹Ρ… экзСмпляров процСссов. ΠŸΡ€Π΅Π΄ΡΡ‚Π°Π²Π»Π΅Π½Π° спСциализация ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ для Π½Π΅ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… Ρ‚ΠΈΠΏΠΎΠ² процСссов ΠΈΠ· ΠΏΡ€Π΅Π΄ΠΌΠ΅Ρ‚Π½ΠΎΠΉ области систСм автоматичСского управлСния, ΠΌΠΎΠ΄Π΅Π»ΠΈΡ€ΡƒΡŽΡ‰ΠΈΡ… Ρ‚ΠΈΠΏΠΎΠ²Ρ‹Π΅ Ρ„ΡƒΠ½ΠΊΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Π΅ элСмСнты систСмы автоматичСского управлСния (Π΄Π°Ρ‚Ρ‡ΠΈΠΊΠΈ, ΡΡ€Π°Π²Π½ΠΈΠ²Π°ΡŽΡ‰ΠΈΠ΅ устройства ΠΈ Ρ€Π΅Π³ΡƒΠ»ΠΈΡ€ΡƒΡŽΡ‰ΠΈΠ΅ устройства), Π° Ρ‚Π°ΠΊΠΆΠ΅ ΠΈΡ… ΠΊΠΎΠΌΠ±ΠΈΠ½Π°Ρ†ΠΈΠΈ. ΠŸΠΎΠ½ΡΡ‚ΠΈΡ спСциализированной ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈΠ»Π»ΡŽΡΡ‚Ρ€ΠΈΡ€ΡƒΡŽΡ‚ΡΡ Π½Π° ΠΏΡ€ΠΈΠΌΠ΅Ρ€Π΅ ΡƒΠΏΡ€Π°Π²Π»ΡΡŽΡ‰Π΅ΠΉ части систСмы Ρ€ΠΎΠ·Π»ΠΈΠ²Π° Π±ΡƒΡ‚Ρ‹Π»ΠΎΠΊ

    Temporal Logic for Programmable Logic Controllers

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    We address the formal verification of the control software of critical systems, i.e., ensuring the absence of design errors in a system with respect to requirements. Control systems are usually based on industrial controllers, also known as Programmable Logic Controllers (PLCs). A specific feature of a PLC is a scan cycle: 1) the inputs are read, 2) the PLC states change, and 3) the outputs are written. Therefore, in order to formally verify PLC, e.g., by model checking, it is necessary to describe the transition system taking into account this specificity and reason both in terms of state transitions within a cycle and in terms of larger state transitions according to the scan-cyclic semantics. We propose a formal PLC model as a hyperprocess transition system and temporal cycle-LTL logic based on LTL logic for formulating PLC property. A feature of the cycle-LTL logic is the possibility of viewing the scan cycle in two ways: as the effect of the environment (in particular, the control object) on the control system and as the effect of the control system on the environment. For both cases we introduce modified LTL temporal operators. We also define special modified LTL temporal operators to specify inside properties of scan cycles. We describe the translation of formulas of cycle-LTL into formulas of LTL, and prove its correctness. This implies the possibility ofmodel checking requirements expressed in logic cycle-LTL, by using well-known model checking tools with LTL as specification logic, e.g., Spin. We give the illustrative examples of requirements expressed in the cycle-LTL logic

    ΠœΠ΅Ρ‚ΠΎΠ΄Ρ‹ спСциализации ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ процСссов, ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠΉ Π½Π° Π²Π΅Ρ€ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΡŽ

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    User-friendly formal specifications and verification of parallel and distributed systems from various subject fields, such as automatic control, telecommunications, business processes, are active research topics due to its practical significance. In this paper, we present methods for the development of verification-oriented domain-specific process ontologies which are used to describe parallel and distributed systems of subject fields. One of the advantages of such ontologies is their formal semantics which make possible formal verification of the described systems. Our method is based on the abstract verification-oriented process ontology. We use two methods of specialization of the abstract process ontology. The declarative method uses the specialization of the classes of the original ontology, introduction of new declarative classes, as well as use of new axioms system, which restrict the classes and relations of the abstract ontology. The constructive method uses semantic markup and pattern matching techniques to link sublect fields with classes of the abstract process ontology. We provide detailed ontological specifications for these techniques. Our methods preserve the formal semantics of the original process ontology and, therefore, the possibility of applying formal verification methods to the specializedΒ process ontologies. We show that the constructive method is a refinement of the declarative method. The construction of ontology of the typical elements of automatic control systems illustrates our methods: we develop a declarative description of the classes and restrictions for the specialized ontology in the ProtΒ΄egΒ΄e system in the OWL language using the deriving rules written in the SWRL language and we construct the system of semantic markup templates which implements typical elements of automatic control systems.Удобная для ΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚Π΅Π»Ρ Ρ„ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½Π°Ρ спСцификация ΠΈ вСрификация ΠΏΠ°Ρ€Π°Π»Π»Π΅Π»ΡŒΠ½Ρ‹Ρ… ΠΈ распрСдСлённых систСм, ΠΏΡ€ΠΈΠ½Π°Π΄Π»Π΅ΠΆΠ°Ρ‰ΠΈΡ… Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹ΠΌ ΠΏΡ€Π΅Π΄ΠΌΠ΅Ρ‚Π½Ρ‹ΠΌ областям, Ρ‚Π°ΠΊΠΈΠΌ ΠΊΠ°ΠΊ систСмы автоматичСского управлСния, Ρ‚Π΅Π»Π΅ΠΊΠΎΠΌΠΌΡƒΠ½ΠΈΠΊΠ°Ρ†ΠΈΠΈ, бизнСс-процСссы, ΡΠ²Π»ΡΡŽΡ‚ΡΡ Π°ΠΊΡ‚ΠΈΠ²Π½Ρ‹ΠΌΠΈ Ρ‚Π΅ΠΌΠ°ΠΌΠΈ исслСдований Π² силу ΠΈΡ… практичСской значимости. Π’ этой ΡΡ‚Π°Ρ‚ΡŒΠ΅ ΠΌΡ‹ прСдставляСм ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ спСциализированных ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹Ρ… Π½Π° Π²Π΅Ρ€ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΡŽ ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΉ процСссов, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡŽΡ‚ΡΡ для описания ΠΏΠ°Ρ€Π°Π»Π»Π΅Π»ΡŒΠ½Ρ‹Ρ… ΠΈ распрСдСлСнных систСм ΠΏΡ€Π΅Π΄ΠΌΠ΅Ρ‚Π½Ρ‹Ρ… областСй. Одним ΠΈΠ· прСимущСств Ρ‚Π°ΠΊΠΈΡ… ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΉ являСтся ΠΈΡ… Ρ„ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½Π°Ρ сСмантика, которая Π΄Π΅Π»Π°Π΅Ρ‚ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΠΉ Ρ„ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½ΡƒΡŽ Π²Π΅Ρ€ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΡŽ описанных систСм. Наш ΠΌΠ΅Ρ‚ΠΎΠ΄ основан Π½Π° абстрактной ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ процСссов, ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠΉ Π½Π° Π²Π΅Ρ€ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΡŽ. ΠœΡ‹ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΠ΅ΠΌ Π΄Π²Π° ΠΌΠ΅Ρ‚ΠΎΠ΄Π° спСциализации абстрактной ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ процСссов. Π”Π΅ΠΊΠ»Π°Ρ€Π°Ρ‚ΠΈΠ²Π½Ρ‹ΠΉ ΠΌΠ΅Ρ‚ΠΎΠ΄ с ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ спСциализации классов исходной ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ, ввСдСния Π½ΠΎΠ²Ρ‹Ρ… Π΄Π΅ΠΊΠ»Π°Ρ€Π°Ρ‚ΠΈΠ²Π½Ρ‹Ρ… классов, Π° Ρ‚Π°ΠΊΠΆΠ΅ систСмы аксиом Π·Π°Π΄Π°Ρ‘Ρ‚ ограничСния для классов ΠΈ ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΠΉ абстрактной ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ. ΠšΠΎΠ½ΡΡ‚Ρ€ΡƒΠΊΡ‚ΠΈΠ²Π½Ρ‹ΠΉ ΠΌΠ΅Ρ‚ΠΎΠ΄ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΠ΅Ρ‚ Ρ‚Π΅Ρ…Π½ΠΈΠΊΠΈ сСмантичСской Ρ€Π°Π·ΠΌΠ΅Ρ‚ΠΊΠΈ ΠΈ сопоставлСния с ΠΎΠ±Ρ€Π°Π·Ρ†ΠΎΠΌ, Ρ‡Ρ‚ΠΎΠ±Ρ‹ ΡΠ²ΡΠ·Π°Ρ‚ΡŒ понятия ΠΏΡ€Π΅Π΄ΠΌΠ΅Ρ‚Π½ΠΎΠΉ области с классами абстрактной ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ процСссов. ΠœΡ‹ Π΄Π°Ρ‘ΠΌ ΠΏΠΎΠ΄Ρ€ΠΎΠ±Π½Ρ‹Π΅ онтологичСскиС спСцификации этих Ρ‚Π΅Ρ…Π½ΠΈΠΊ. Наши ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ ΡΠΎΡ…Ρ€Π°Π½ΡΡŽΡ‚ Ρ„ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½ΡƒΡŽ сСмантику исходной ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ процСссов ΠΈ, ΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎ, Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡ‚ΡŒ примСнСния Ρ„ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² Π²Π΅Ρ€ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ ΠΊ спСциализированным онтологиям процСссов. ΠœΡ‹ ΠΏΠΎΠΊΠ°Π·Ρ‹Π²Π°Π΅ΠΌ, Ρ‡Ρ‚ΠΎ конструктивный ΠΌΠ΅Ρ‚ΠΎΠ΄ являСтся ΡƒΡ‚ΠΎΡ‡Π½Π΅Π½ΠΈΠ΅ΠΌ Π΄Π΅ΠΊΠ»Π°Ρ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ ΠΌΠ΅Ρ‚ΠΎΠ΄Π°. ΠŸΠΎΡΡ‚Ρ€ΠΎΠ΅Π½ΠΈΠ΅ ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ Ρ‚ΠΈΠΏΠΎΠ²Ρ‹Ρ… элСмСнтов систСм автоматичСского управлСния ΠΈΠ»Π»ΡŽΡΡ‚Ρ€ΠΈΡ€ΡƒΠ΅Ρ‚ наши ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹: Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½ΠΎ Π΄Π΅ΠΊΠ»Π°Ρ€Π°Ρ‚ΠΈΠ²Π½ΠΎΠ΅ описаниС классов ΠΈ ΠΎΠ³Ρ€Π°Π½ΠΈΡ‡Π΅Π½ΠΈΠΉ спСциализированной ΠΎΠ½Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ Π² систСмС Protege Π½Π° языкС OWL с использованиСм ΠΏΡ€Π°Π²ΠΈΠ» Π²Ρ‹Π²ΠΎΠ΄Π° Π½Π° языкС SWRL ΠΈ построСна систСма шаблонов сСмантичСской Ρ€Π°Π·ΠΌΠ΅Ρ‚ΠΊΠΈ, которая Ρ€Π΅Π°Π»ΠΈΠ·ΡƒΠ΅Ρ‚ Ρ‚ΠΈΠΏΠΎΠ²Ρ‹Π΅ элСмСнты систСм автоматичСского управлСния
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