Software & Systems

Articles of journal № 3 at 2019 year.

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11. Implementation of a fuzzy model of interaction between objects in complex technical systems based on graphs [№3 за 2019 год]
Author: Muntyan, Е.R.
Visitors: 5817
The paper describes the process of developing a fuzzy model based on graphs, which allows investigat-ing the joint action of objects in complex technical systems using the example of a part of an extended perimeter security system. The objects of such system are stationary and mobile objects of a protected perimeter, uninhabited intelligent interacting mobile robotic platforms, a decision maker who controls their movement (here it is a computer), and potential intruders entering a protected perimeter territory. To represent objects of complex technical systems, the model uses the concept of “actor” according to the Actor-network theory of B. Latour. The results of simulating an extended perimeter protection system are analyzed on the example of three models that take into account various types of communi-cation in a graph: model 1 with the same type of connections, model 2 with the same and different types of connections, model 3 with the same type, different types of edges and multiple connections in a vector form. To simulate and study joint actions of objects in complex technical systems, the author proposes a fuzzy model of interaction of actors, which makes it possible to take into account the complex of vari-ous types of communication between graph nodes according to the specifics of the subject domain. These models are implemented in the software module developed by the author. Experimental research have shown the advantage of the model 3 proposed in the article (a multiple link graph).

12. A performance evaluation methodology for energy efficient control system alternatives for MIMO systems [№3 за 2019 год]
Authors: D.Yu. Muromtsev, A.N. Gribkov, V.N. Shamkin, I.V. Tyurin
Visitors: 5705
The paper presents the methodology for selecting the most optimal alternative of an energy-efficient control system for a complex process system. The proposed methodology is may help to solve structur-al synthesis problems. Designing a control system is a set of interrelated operations aimed at achieving a specific outcome. The implementation of such project might involve uncertainties and risks, high costs, many stages and considerable time consumption, the need to have a well-coordinated team of executors, as well as no guarantee that there wiil be the expected outcome. The choice of a project management methodology and a strategy depends on the type of the process system and the project implementation objectives, the nature of uncertainties and risks, the possibility of using information technology and parallel design. Both project risks and design costs depend on the number of alternatives considered during design stages. Therefore, for project management it is necessary to use design process models that take into account the number of alternatives and their effectiveness at each stage of design work. In general, a design process can be described by a functional model in IDEF0 format supplemented by decision-making nodes. The method of evaluating the effectiveness of alternatives is based on the method of dynamic varia-tion, which assumes that each design stage has a formed group of various alternatives that begin to be developed in parallel. After each stage, there is an expert evaluation session with the following deci-sion on the significance of different alternatives in a group. As an example, the paper describes using the dynamic variation method for developing a control system for a six-section precision furnace for heat treatment of thermistor workpieces in the air. From a control point of view, it is a typical MIMO system with complex relations between inlets and zones.

13. Rating assessment of academic staff in a university based on an automated information system [№3 за 2019 год]
Authors: E.N. Natochaya, Zubkova, T.M.
Visitors: 4667
The paper describes an automated information system (AIS) for assessing the efficiency of professional activities of academic staff in educational organizations of higher education. The proposed system is necessary to form a report on performance indicators of academic staff ac-tivities, based on which a head can quickly make management decisions. When applying AIS, the head of department, faculty or educational organization has an opportunity of selecting a suitable candidate for vacant positions; he is also able to form a so-called top of academic staff whose activities coincide with higher education development trends as much as possible. The authors present a formalized representation of the assessment process of an academic staff rat-ing as IDEF0 model and a decomposition scheme. During a decomposition of a software purpose model the authors allocate the following functions: maintaining data on the academic staff, rating calculation, forming report forms. Academic staff performance indicators are united into groups: educational, or-ganizational and methodical, research, scientific and organizational, educational and social work, repu-tation and image activity. The results of total rating assessment might be considered at competitive selection for a vacant po-sition and a subsequent conclusion of an effective contract, at funding acquisition of the equipment for scientific research, conference trips, training, etc., when determining the size of commercial incentive to salary. The used mathematical model of rating calculation is a method of qualimetric assessment of academic staff activity quality. The calculation includes basic, current and private ratings, as well as production and creative activity rating. The paper presents the developed algorithm to solve the problem, a data structure; shows AIS work and the obtained results.

14. Developing a self-learning method for a spiking neural network to protect against DDoS attacks [№3 за 2019 год]
Authors: E.V. Palchevsky, O.I. Khristodulo
Visitors: 8403
The paper is devoted to the development of a specialized training method for a spiking neural network, which allows speeding up the detection and elimination of attacks by external unauthorized traffic. The paper considers the problem of protecting information availability and teaching neural net-works. It also justifies the need for mathematical analysis to develop new methods of self-learning of neural networks. The paper introduces the developed self-learning spiking neural network that is nec-essary to protect against DDoS attacks. A new self-learning method for a spiking neural network is based on the uniform distribution of neurons across all cores of each processor in a cluster. This allows a neural network to learn from scratch in a short time (530 minutes). As a result, it quickly and effec-tively eliminates DDoS attacks. The authors tested the developed spiking neural network in two modes: combat and normal. The tests gave load values for physical resources of each physical server in a cluster. Long-term testing of a spiking neural network shows fairly low load on a central processor, RAM and solid-state drive during DDoS attacks. Naturally, optimal load increases the availability of each physical server, and makes it possible to simultaneously run resource-intensive computational processes without any disruption of the working environment. Testing was conducted on computing cluster servers in one of Moscow data centers. The spiking neural network has shown stable operation and effective protection against DDoS attacks.

15. Predicting an object state based on applying the Kalman filter and deep neural networks [№3 за 2019 год]
Authors: A.Yu. Puchkov , Dli M.I., E.I. Lobaneva , M.A. Vasilkova
Visitors: 6718
The paper presents an algorithm for predicting an object state based on data from different sources (for example, video cameras) coming in the form of images aimed at critical technological zones. The pro-posed algorithm is based on the consistent use of a deep artificial neural network and the Kalman filter. A neural network is designed to reduce the input data dimension (images) performing the function of an encoder, which gives of an observation vector of the object state on the output. Based on these ob-servations, the object state is evaluated by a recurrent filter. Using the filter directly for images would lead to a large dimension of the problem; it would be impossible to perform it practically due to com-putational difficulties. The program that implements the proposed algorithm was developed in Python 3.6 using the Spyder integrated environment from the Anaconda assembly for the Linux operating environment. The choice of a programming language is due to the availability of powerful libraries for machine learning Tensor-Flow from Google, as well as the convenient Keras framework for creating and working with deep neu-ral networks. The paper describes the results of a model experiment on using the proposed algorithm for predict-ing an object state, which consisted in attributing the obtained observations to a particular class. The experiment also involved generating sets of images belonging to different classes, differing in their tex-ture. A line-by-line horizontal pixel shift simulated the noise in the images. The comparative analysis of the predicted results with and without using the Kalman filter has shown that filtering reduces the number of false classifications. The developed algorithm might be used in decision support systems and automated process control systems.

16. On the approach of modeling linear objects as sources of emergency situations of technogenic nature [№3 за 2019 год]
Authors: A.V. Rybakov , E.V. Ivanov , I.A. Vidrashku , T.B. Khatukhov
Visitors: 5057
Recently the problem of effective and rapid response to emergency situations, as well as the optimal calculation of the necessary manpower and resources for emergency response has become particularly acute due to the insufficiently effective level of disaster response planning. This paper provides a possible solution for the problem of forecasting emergency zones and the dy-namics of their changes over time. This solution is introduced as an interactive emergency modeling system using terrain maps. The paper presents a new approach to the creation of client-server application of an interactive de-cision support system for preventing and eliminating emergencies. The paper demonstrates the mechanism for processing a linear object and modeling an emergency situation related to the violation of its integrity using a gas pipeline. It also provides a list of the source data necessary for the calculation of areas at risk. The result of the calculation is a set of data that is a base for assessing the forces and means necessary to eliminate emergency consequences. There is a brief description of the implementation of a system of modeling various emergency situa-tions, which allows visualizing the affected area, on a cartographic basis. The paper presents an algo-rithm of system operation divided into stages of the client side, and server side stages in the order of their execution. It also describes the interactive system structure with a description of the tools and an example of the options for their application.

17. The automation of scientific studies on the concept of gas well survivability during water flooding [№3 за 2019 год]
Authors: N.A. Solovyov, Valeev, A.F.
Visitors: 4158
Development of gas condensate fields during falling production is characterized by various adverse ef-fects that are not regulated by the design conditions of normal operation. One of the main adverse ef-fects is the well flooding, which worsens the permeability of a bottom-hole zone leading to a sharp de-crease in performance. At the same time, the amount of residual drained gas reserves may be sufficient to maintain industrial production levels. The authors propose to use the survivability property to study a production system under these conditions. The concept of survivability is known in technology, how-ever there is still no a developed theory that would contain (as a theory of reliability) general technical results that allow investigating this property, evaluating it quantitatively and developing practical rec-ommendations to ensure complex system survivability. The paper presents the concept of scientific studies on gas production system survivability. It is based on the system of predictive modeling of gas condensate field production technological process-es, which takes into account new technologies of reservoir fluid extraction and their implementation period. The concept of gas production system survivability is introduced and the signs of this property are defined. The existing application software for hydrodynamic modeling does not allow investigating the sur-vivability of a gas production system. Therefore, the task of developing information and software for research on the survivability of the gas production system under the conditions of gas well waterflood-ing becomes urgent. The paper proposes a conceptual model of scientific studies automation of the wa-tering gas well survivability. It is the development of an integrated geological and technological model of a gas condensate field. There is software implementation of the predictive model of product recov-ery from a flooded well based on the technology of field fluid extraction using a centrifugal pump.

18. Development of operation algorithms of a mathematical model of an airship anti-stealth radar [№3 за 2019 год]
Author: S.V. Susha
Visitors: 8357
The paper describes a complex mathematical model of an airship anti-stealth radar system. The pur-pose of the study was to justify the technical appearance, application features, to assess the effective-ness of the operation and combat (information) capabilities of the complex. The development result in-cludes a number of simulation models (a target environment model, an Earth model, an on-board sys-tems model including a radar station model, an on-board control system model and a navigation system functioning model, a ground control center model including a model for displaying information about detected and tracked targets, a model board control), as well as functionally complete blocks (systems for processing and analyzing results). When modeling, all simulation models in the complex mathematical model are constructed accord-ing to a single principle. The functioning dynamics of the simulated complex is simulated by succes-sive changing of their states at some time intervals. The paper provides a block diagram of a general algorithm of a complex mathematical model in a simulation mode. The modeling process assumes stepwise changing of the model time by a step size. There are algorithms for the main units and their relationship as part of a general algorithm for the op-eration of a complex mathematical model of an airship radar system in a simulation mode. The operation algorithms of the target environment model include both the aerospace target and ra-dio-electronic environments. The spatial position and orientation of targets with respect to a stationary point of the airship radar system and the radiation of all on-board electronic target means is determined by targets parameters, as well as the direction of their arrival and radiation intensity. The operation algorithms of the navigation system model include source data of a carrier position – its location error vectors. The data values of these vectors are determined by the navigation system characteristics. A radar station model is based on calculating the detection parameter using the radar equation and calculating a signal propagation process. This model includes algorithms for primary and secondary processing of radar information. The implementation of the presented algorithms in a complex mathematical model allows reasona-ble describing of operation processes of an airship radar system when detecting, tracking, and recog-nizing subtle air targets. It will provide an assessment of the effectiveness of the options for building the complex and its information capabilities.

19. Methodical support of designing a dynamic object geographic information systems infrastructure [№3 за 2019 год]
Authors: Tatarnikova, T.M., N.V. Yagotinceva
Visitors: 5725
The paper considers the problem of applying geographic information systems (GIS) in managing dy-namic objects. It proposes a structural-functional model of a ship GIS. Functional modules that form a ship local area network represent the GIS hardware layer. It is shown that in order to control a dynamic object, functional modules of GIS hardware must meet the delivery time limits recommended by spatial data distribution standards. The authors form the research task as the task of developing methodological support for ship GIS design for specified sailing goals and taking into account the restrictions on the required GIS perfor-mance indicators when working with spatial data. The choice of a GIS infrastructure is an integral prob-lem of conditional multiparameter optimization with cost and GIS project performance limits. The paper proposes a method of forming a GIS infrastructure with a given set of properties. The method includes the steps of forming initial data, estimating temporal characteristics of spatial data de-livery to a decision maker, determining a GIS infrastructure that meets cost and performance require-ments, and determining the bottleneck in a GIS structure. The initial data of ship GIS design are a ship application and a sea navigation area. The ship application makes it possible to determine the minimum number of workstations, and the sea navigation area determines the minimum composition of the equipment on a ship, which is determined by the Global Maritime Distress and Safety System the Russian Federation.

20. Magnetic resonance imaging data processing methods for cognitive visualization and tracking of zones of interest [№3 за 2019 год]
Authors: V.P. Fralenko, M.V. Shustova , M.V. Khachumov
Visitors: 6293
The main goal of this research is the development of methods for intelligent automatic analysis of mag-netic resonance imaging (MRI) data to support physicians engaged into the study of areas of ischemic lesion and the movement characteristics of mesenchymal stem cells transplanted in the brain of labora-tory animals. The relevance of this research is determined by existence of a number of unsolved prob-lems in the field of study of MRI data automatic analysis. They are: a lack of tools for automated high-precision search of target objects and areas of interests in MRI data (in the interactive mode); problems of fast analysis of a large amount of dynamically changing parameters of the objects under study; a lack of significant improvement of researchers’ equipment through creating a new instrumental base and methods of processing MRI data. The paper presents methods and algorithms to solve the problem of automating the processes of MRI data intellectual processing. The developed methods allow automatic detection and visualization of areas of interest in the brain: ischemic lesions and transplanted stem cells. 2D and 3D visualizations make it possible to model the process of the genesis and changing of zones of interest in time. The methods and algorithms are based on processing DICOM files obtained by scanning a recipient's brain (laboratory rats) in T2 mode (to detect ischemic lesion zone) and SWI mode (to detect mesenchymal stem cells clusters). The developed algorithms form the basis of a software package for processing and analyzing bio-medical data for expert decision-making support for researchers. This software package allows auto-matic detecting of areas of interest in MRI data. The introduction of tracking functions into the devel-oped software package allowed in-depth study of the migration and homing processes of stem cells during a transplantation into a brain affected by various diseases.

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