Software & Systems

Articles of journal № 1 at 2017 year.

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11. On an approach to construct asset master data management system [№1 за 2017 год]
Authors: A.A. Sukhobokov, V.I. Strogonova
Visitors: 9847
The paper describes capabilities of current MDM (Master Data Management) solutions and prospects of multidomain and multivector MDM solutions. The paper presents the reasons for which MDM of asset data solutions for single data domain are not used successfully in contrast to the existing MDM solutions for other data domains such as customers, suppliers, products, employees, etc. There are challenges of combining several different representations of the same assets in MDM of asset data solution. The conclusion shows that as long as relevant single-domain MDM of asset data solutions are not developed and not implemented successfully, it is too early to move this subject area to multidomain systems. To solve the problems described above, the authors propose a model of assets master data, which enable to combine different representations. This model includes multiple independent hierarchies for different representations of the same assets, non-hierarchical links specific for each subject area, grids of links allowing to go between different representations of the same asset, a set of asset classifiers whose classes define sets of attributes for describing assets, classifiers of links between assets, as well as structural and functional models for individual asset types. In order to implement the proposed model of master data on assets, the authors have developed a special architecture of MDM of asset data solution, as well as an algorithm for checking the integrity of links between different representations across the whole data model. Key requirements are defined to the tools for developing a prototype of MDM of asset data solution. It must provide the functionality of a graph DBMS and at the same time a graph engine to perform complex algorithm on the graph as a whole.

12. System models construction based on LTL formula equational characteristics [№1 за 2017 год]
Authors: Korablin Yu.P., Shipov A.A.
Visitors: 7614
Verification of software and technical systems has always been and still remains one of the most significant tasks since appearance of first computing devices. Today there are quite a lot of approaches to solve this problem. However, development of such formal verification method as Model Checking helped to solve the problem of verifying systems representation and to unify verification process for software and technical systems. Its main idea is to transform an original system into a unified form. It means that a verification process requires only a model that would most precisely describe system’s behavior. The article considers the possibility of system model construction using RLTL-notations (Recursive Linear Temporal Logic), which are a recursive representation of formulas of linear temporal logic. However, its usage is not limited to this aspect. The advantage of using RLTL for these purposes is that models based on it might be verified in respect to requirements which are also RLTL-based without casting to any another data structure. It will certainly help to simplify and improve the performance of a verification process. Furthermore, the article describes the formal tools, which allow simplifying RLTL-based models in many cases reducing the number of their states and transitions.

13. Forecasting in dynamic system control [№1 за 2017 год]
Author: Tikhanychev, O.V.
Visitors: 9701
The condition of complex systems management adequacy is a stock of information on their current state and operation conditions. Typically, such data is obtained from environment monitoring systems. But usual monitoring of dynamic systems does not always provide effective management. In some cases it is appropriate to introduce a feedback to a control loop. But this approach does not always work, especially when managing large distributed systems with high inertia. In order to ensure management efficiency it is necessary to use feedback. It means not only monitor the status of a system and the environment, but also to obtain information on their possible changes in advance, that is to use forecasting methods. Now it is common practice to divide all forecasting methods on active (which evaluate possible consequences of the decisions made) and passive (which provide a forecast of changing a state under current conditions). It is proposed to use passive forecasting for active type feedback formation. It allows a user to form control actions in advance taking into account the forecast of a situation development.

14. Program for heat conditions identification in flat products [№1 за 2017 год]
Author: Margolis B.I.
Visitors: 10527
The article considers the problem statement on identification of heat transfer conditions for flat products with asymmetrical shapes convective-radiative heat transfer surfaces to the environment and enclosing surfaces (heating elements) of the process equipment. The paper formulates a possible solution of the problem in Matlab. The program, which has been developed based on the standard fmincon function in MatLab, allows identifying the part of radiation heat transfer energy, which gets from a furnace surface to the product in each zone. For this purpose it uses predetermined thermo-physical characteristics of the material (thermal conductivity, thermal diffusivity), the parameters of convective-radiative heat transfer (coefficients of convective heat transfer and an emissivity factor) and the temperature and time parameters on an annealing furnace. The paper presents an example of radiative heat transfer parameter identification in an annealing furnace for rolled glass sheet on the basis of the temperature field simulation program in Matlab. The authors consider the features of program development related to the need to take into account changing initial and boundary conditions at each stage of the temperature-time mode of an annealing product using pdebeg and pdebound of the standard functions pdepe in MatLab. There are software codes of functions and main program, as well as the results of calculating band surface temperatures and emissivity factors of a furnace surface. There is the analysis of the results of the program. The paper demonstrates good agreement between the obtained emissivity factors and their physically reasonable values for radiative heat transfer in glass annealing furnaces. The paper shows the prospects of using standard Matlab functions to solve product heat treatment mode optimization problems in various technological processes.

15. A software agent to determine student’s psychological state in e-learning systems [№1 за 2017 год]
Authors: E.L. Khryanin, A.N. Shvetsov
Visitors: 7976
The article considers the problem of using software agents to assess students’ psychological state in an e-learning system. The hypothesis of the study is the following: the more psychologically acceptable material for a student, the faster and better it is learned. It is required to develop an automatic algorithm for selection of material. The article describes the developed e-learning system, which has been developed over 5 years and tested in one of the state universities. There is a brief description of e-learning system implementation that includes the agent interaction scheme, main database tables, backend and frontend implementation. The paper also describes a method and an algorithm to determine student’s perceptual modality during psychological testing. It uses statistical methods to predict the probability of logging-in (based on statistics). The authors propose weight coefficients of frequency of using e-learning system by students for the agent, which determines their psychological state, to make decisions. The paper describes the created algorithm of an automatic decision on the need in testing. The study involved 3 groups: a control group, a group with recommendation of material and a group with material chosen by an agent. The study involved more than 90 people. The study has formed formulas for perceptual modality calculation for several consecutive measurements. There is an example of calculation clarification for contradictory data. The experiment has shown positive results when using a recommendation mode. More than 61 % of students have passed the control test, and more than a half of the group has solved a difficult task (about 42 % and 12 % in the control group respectively). There is a conclusion on expediency of using the psychological state definition agent in e-learning systems.

16. Software interface design using elements of artificial intelligence [№1 за 2017 год]
Authors: Zubkova, T.M., E.N. Natochaya
Visitors: 11841
In order to develop high-quality software it is necessary to reflect all customer requirements in the specification, thus, to have a global view on the future software for customers and performers. One of the options to achieve mutual understanding is to develop a prototype of a user interface. The article describes the methods of selecting an alternative version of the interface template using such artificial intelligence methods as expert evaluation and the fuzzy-set theory. Users might be are divided into five groups on the basis of individual characteristics (a newbie, usual, experienced, skilled, an administrator). The article defines the basic parameters of individual characteristics which may help to classify users when designing interfaces (computer literacy, systematic experience, experience of working with similar programs, typing, thinking, memory, motor skills, blindness, concentration, emotional stability). The paper describes mathematical support and software for solving the problems of intelligent user interface design. Task implementation is performed in three stages. The first stage is “Forming and assessing expert group competence”. It defines the characteristics of experts. A quantitative description of experts’ characteristics is based on the calculation of relative ratios of competence according to the results of experts’ statements on the Advisory group. The second stage is “Group expert assessment of the object with direct assessment”. It determines recurrent relations for iterations. The third phase is “Building a fuzzy model on fuzzy binary relations”. It operates by two fuzzy sets: a set of user groups and a variety of interface templates that are maximally effective for users with these characteristics. Fuzzy model input data are selected fuzzy sets, the output data are the degrees of matching interface patterns to users. The user interface design process is automated on the basis of the proposed methodology in order to improve objectivity and optimize decisions taken by software developers.

17. Professional training of ships’ personnel in the system of military product life cycle [№1 за 2017 год]
Authors: Losev E.F., Kuznetsov I.V., A.A. Bavula , I.A. Burik
Visitors: 6006
The article discusses personnel training in a military life-cycle management system based on the so-called “end-to-end life cycle contracts”. The authors propose a conceptual model of a military life-cycle management system with integration professional training of surface ships’ personnel of communication departments into a common information space. The paper presents a critical aspect of the integrated simulator of ship's communicators “Tribe-S”. The authors analyze foreign and historical experience of military professional training. They assess the quality of personnel training based on virtual environment simulation learning of navy crews during transition to end-to-end life cycle contracts. The authors suggest that the virtual environment simulation will allow trainees to acquire unique skills in a variety of emergency situations, which sometimes is not possible to gain in a traditional learning process. The authors also consider that the contracts based on military production life-cycle management will increase the military pre-paredness of a ship in general and will improve the quality of service staff professional education. The exploitation of a communica-tion system supplied to the Navy will decrease the number of facilitators significantly. The transition to these contracts will allow more efficient use of huge funds allocated to defending our country.

18. Development and implementation of a forecasting model for a chromatic error of galvanized strip polymeric coating [№1 за 2017 год]
Authors: V.M. Oskolkov, I.A. Varfolomeev, L.N. Vinogradova, E.V. Ershov
Visitors: 7559
The article presents the results of the study on quality improvement method for galvanized strip polymeric coating using modelling methods for chromatic deviation reduction. A predictive model of the chromatic deviation consisting of 3 sub-models is proposed; each sub-model predicts one CIELab color space model coordinate. Each sub-model is based on Random Forest machine learning algorithm. Full chromatic deviation output value is calculated from predictive coordinates.. Each sub-model is based on Random Forest machine learning algorithm. The paper considers a decision tree algorithm. It also describes the main parameters affecting chromatic deviation. Those parameters are received from 3 sources: paint certificate values, characteristics of an incoming strip coil for further painting, process parameters. The authors have developed an approach for prompt and efficient integration of the mentioned forecasting model into existing IT infrastructure by model translation into a database. The developed script allows translating the model into programming languages used for industrial control systems (SQL, .NET). The paper describes the following stages of forecasting model translation from R language into SQL language: code generation, filling the tables. Forecasting in a database takes 0,3 seconds which is enough for real time mode production. Application of the developed model allows forecasting chromatic deviation of a polymeric coating with a mean error of 6,1 %.

19. Neural network ensembles storage development [№1 за 2017 год]
Authors: Puchkov E.V., S. Terekhov
Visitors: 10080
An important tool in the work of a data analysis and machine learning expert is software for an experiment organization. This is primarily related to a large number of stages in data processing and the characteristic aspects of their im-plementation. In the course of this work the authors have designed and developed a prototype of neural network ensemble storage for data structured storing on various stages of time series forecasting. The article considers a data model, data storage architecture and mechanisms of data acquiring and redistribution in the storage. There is also a description of the developed class model for software-based interaction with the storage. In order to store data on objects and relationships between these objects there has been used MySQL. For storing time series we used non-relational database InfluxDB. There is also user interface with data visualization and easy interaction with the neural network ensembles storage. The system has been tested using solar activity data in the period from January 1700 to February 2015. The experiment (using LSTM recurrent network) showed that an error of a neural network ensemble was lower than an error of each individual neural network model. LSTM was built using the library Keras, the Blending approach was used to form an ensemble. The results of this work indicate the prospects of the developed software solution and provide a high degree of integration into scalable Python software. The development of a fully functional system will allow not only organizing the data analysis process, but also improving the performance of resulting models due to ensemble formation process automation.

20. Implementation of reinforcement learning methods based on temporal differences and a multi-agent approach for real-time intelligent systems [№1 за 2017 год]
Authors: Eremeev, A.P. , A.A. Kozhukhov
Visitors: 12209
The paper describes implementation of reinforcement learning methods based on time (temporal) differences and a multi-agent technology. The authors examine the possibilities of combining learning methods with statistical and expert methods of forecasting for further integration into an instrumental software environment to use in modern and advanced real-time intelligent systems (RT IS), a type of real-time intelligent decision support systems (RT IDSS). There is an analysis of reinforcement learning (RL-learning) methods in terms of using them in RT IS, main components, benefits and tasks. The paper focuses on the methods of RL-learning based on time (temporal) differences (TD-methods) and presents the developed corresponding algorithms. The authors consider the possibility of including RL-learning methods into a multi-agent environment and combining them with statistical and expert forecasting methods in terms of integration into the environment, which was developed for RT IDSS for complex technical object control and diagnosis. The paper proposes the architecture of the forecasting subsystem prototype consisting of an emulator, which simulates the state of environment, forecasting module, analysis and decision-making module and a multi-agent RL-learning module. There is software implementation of the forecasting subsystem prototype using a multi-agent approach in order to solve the problem of the complex technological object expert diagnosis. According to the results of testing and validation of the developed system, the paper considers the conclusions about the efficiency and expediency of including into the RT IDSS.

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