ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 11. Vol. 22. 2016

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V. I. Levin, Dr of Tech Sci, Professor, e-mail: vilevin@mail.ru; Penza State Technological Academy

Continuous-Logical Model for Solution of Combinatorial Problems

The class of combinatorial problems equivalent to the problem of determination of mutual dislocation of interval sequences is formulated. It is shown, that an adequate mathematical model of solution of delivered problem is the finite dynamic automaton without memory, and adequate mathematical means — continuous logic. The algorithms of a solution are constructed. The example is indicated.
Keywords: continuous logic, combinatorial problems, automata model, interval value

P. 803 – 811

A. A. Dvornikov, Teaching Assistant MIEM NRU HSE, Post-Graduate Student, e-mail: advornikov@hse.ru, L. S. Voskov, Professor MIEM NRU HSE, PhD, e-mail: lvoskov@hse.ru, E. A. Saksonov, Professor MSUTM named after K. G. Razumovskiy, PhD, e-mail: saksmiem@mail.ru, S. G. Efremov, Senior Lecturer NRU HSE, PhD, e-mail: sefremov@hse.ru

A Method for Organization of an Optimal Overlay Channel in Wireless Sensor Networks

A new method of optimal route search for an overlay channel built on top of a wireless sensor network is proposed. It allows to increase utilization of unused telecommunication and energy resources in wireless sensor networks without loss of their primary functions.
Keywords: telecommunication networks, wireless sensor networks, route search, unused telecommunication resources, unused energy resources, underloaded network, shortest path with a maximum weight problem, load balancing, overlay networks, overlay channels.

P. 812 – 818

A. A. Yakovlev, D. Sc., Professor, yaa_777@mail.ru, V. A. Kamaev, D. Sc., Professor, vkamaev40@mail.ru, V. S. Sorokin, Graduate Student, s.o.r.o.k.i.n@mail.ru, S. N. Mishustina, Senior Lecturer, svt4656@mail.ru,
Volgograd state technical university, 400005, Volgograd

Search Engine Design Systems Cooling Based Engineering and Physical Approach

The technique of search engine design that allows by constructing a model of the physical principle of action to get a lot of cartsible technical solutions cooling systems and identify the most promising options for constructive realization. Obtained data domain techniques and refined model of the physical principle of action for the cooling systems. The algorithms and the basic data structures for information support search design.
Keywords: tags, search engine design, the physical principle of action, the technical solution, the cooling system, the working fluid

P. 819 – 826

E. V. Bimakov, Leading Engineer, LLC "Voxel equipment", Graduate Student, Izhevsk State Technical University, robint@mail.ru

The Method of Virtual Probing of Scene Based on the Voxel Technology of Scene Processing
The high-speed method of virtual probing of a scene based on voxel technology of scene processing is explained. The method is intended for the solution of tasks of navigation of the autonomous ground mobile robot (obstacle avoidance and object recognition in real time). The general concept of this method, the choice of the type of digital device, the choice of probe model and scene model for the high-speed virtual scene probing are described. High speed of the automatic analysis of scene is reached thanks to deep multisequencing of operations and procedures which are most often used when scene is probing.
Keywords: scene and image processing, navigation, autonomous ground robot, obstacle avoidance, object recognition, voxel geometrical model, v๎xel computers

P. 827 – 835

S. L. Belyakov, DSc., Professor, e-mail: beliacov@yandex.ru; M. L. Belyakova, Ph. D., Associate Professor, e-mail: mamitabha@yandex.ru; A. A. Glushkov, Postgraduate Student, e-mail: andrey@glushkov.net; Federal State-Owned Autonomy Educational Establishment of Higher Vocational Education "Southern Federal University", Taganrog

Images Meta-Transformation when Searching for Reliable Solutions in Intelligent Geographic Information Systems

The article devoted a problem of decision-making at lack of information. Taking decisions implemented with the support geoinformation system. The reliability is a criterion of quality of decisions that forms a geographic information system. We propose a method of construction of solutions based on an experience. An experience presented by cartographic imagery. Each image consists of a center and transformation. The center describes a specific situation. The transformation set possible changes in the center, which do not alter the meaning of precedent in general. In this paper proposed to use meta-transformation images. The essence of meta-transformation is to create a new situations according to a known precedents and describe them on the map. Meta-trans-formation is a vector. The elements of the vector are the transformations of the image a precedent. A measure of the reliability of the cartographic representation of a situation has been introduced. It is a number of a changes of a center of a image. A metric is a norm of a vector of a meta-transformation. Using of meta-transformation allows a special way to evaluate a semantic proximity of situations and to adapt earlier decisions. The factors which determine the accuracy of the generated solutions has been analyzed. The results of the article can be used for a supply chain management, in developing a various logistics projects. The authors reviewed the example, showing the formation of reliable solutions.
Keywords: decision making, knowledge, case based resoninng, intelligent systems, cartographic visualization, geographic information systems

P. 836 – 842

I. V. Mashkina, DSc, Professor, mashkina.vtzi@gmail.com, A. Yu. Sentsova, Postgraduate Student, sentsova.alina@yandex.ru Ufa State Aviation Technical University (UGATU), Ufa, Russia

Information Security of Cloud Computing System

The development model of threats and private information security policy cloud computing systems are discussed The threat model on the based of fuzzy cognitive map is developed, which allows modeling the propagation of threats to the information system, built using cloud computing technologies, through the exploited vulnerability of the components of its infrastructure. The formation of the private security policy based on the use of the model RBAC.
Keywords: cloud computing, community cloud, the cloud computing system, cloud provider, cloud service consumer, the threat model, fuzzy cognitive map, private security policy, a role hierarchy.

P. 843 – 853

K. A. Shcheglov, Graduate Student, A. Yu. Shcheglov, Professor, e-mail.ru: info@npp-itb.spb.ru;
St. Petersburg university of ITMO, Russia

Correctness and Versatility Problems of Modeling Attack Threats Reliability Parameters and Characteristics Approach

We did research correctness and universalism problems of suggested attack threat modeling approach which allows to determine reliability parameters and characteristics of attack threat security. This approach is based on building attack threat Markov model (a model with discrete states and continuous time) with its following transformation to input streams probability rarefaction model. Input streams probability rarefaction model based research allowed to do the conclusion that discrete states and continues time Markov model must be counting (not finite) and that such model use is correct for solving attack threats modeling problem. We suggest an approach to elaborate assumptions for counting Markov model transformation into finite model with the usage of Poisson law. We researched universalism problem of suggested attack threat modeling approach basing on states unification possibility in input streams rarefaction probability model.
Keywords: attack threat, vulnerability threat, reservation, leveling, mathematical modeling, security parameters and characteristics, informational security reliability, attack threat actuality quantitative measure, Markov model, input streams rarefaction

P. 854 – 861

R. M. Aliguliyev, Head of Departament, r.aliguliyev@gmail.com, I. Ja. Alakperova, Head of Sector, airada.09@gmail.com Institute of Information Technology of Azerbaijan National Academy of Sciences, Baku

Big DATA Problem in Oil and Gas Industry: Current State and Prospects

Topic big data in oil and gas industry is multifaceted. The biggest oil and gas companies of the world have long had to deal with big data for decision-making. To increase production and resist the competitors, oil and gas companies implement effective big data analytics. The article reveals the problems associated with big data, the classification of the data sources in the oil and gas industry. Also have been explored approaches used by biggest oil and gas companies to solve the problems associated with the storage and processing of big data.
It was confirmed that the volume and variety of data play a key role in increasing business opportunities giant oil and gas companies. Proposals for effective analysis of big data to predict the market prices in the investigation, drilling and materilano logistics and other tasks. Howled found that, taking into account the high level of performance, which should be provided in the oil and gas industry, as a priority are reducing costs and security of workers and the environment. The future prospects of using complete, accurate and fast processing of large data collected in the oil and gas companies have been identified that have become part of the architecture of information.
Keywords: oil & gas companies, big data, information technology, data analysis, analytics, complex analytical queries

P. 862 – 869

V. V. Pekunov, Engineer, e-mail: pekunov@mail.ru, "Informatika"

The Compact Description of Variative Fields of Physical Variables in the Repetitive Tasks of Simulation of Atmospheric Pollution's Transfer

This work deals with the problem of compactization of the data fields resulting from mathematical simulation of the atmospheric flows. In the first stage such fields are clusterized (using k-means) by the similar values. In the second stage each such metacluster is clusterized by space variables. In the third stage each resulting cluster is described by a sequence of neural networks (this is a proposed compression). A special algorithm of the selection of an optimal set of networks is proposed. This algorithm uses a prediction-correction technique. The prediction is realized by an extrapolation using a specially builded (interpolating) function. The correction is realized using a probe network results. The proposed scheme can gives a compression of the data fields into 45—70 times. The task has a big calculating cost and is solved in parallel on the multicore machine.
Keywords: lossy data compression, clustering, artificial neural networks, numerical simulation, adaptive algorithm, parallelization

P. 871 – 875

S. D. Kurgalin, DSc, Professor, kurgalin@bk.ru, Ya. A. Turovsky, PhD, Associate Professor, yaroslav_turovsk@mail.ru, S. V. Borzunov, PhD, Associate Professor, borzunov@cs.vsu.ru Voronezh State University, Voronezh, A. A. Adamenko, Postgraduate Student, adamenko.artem@gmail.com Voronezh State University of Engineering Technologies, Voronezh

Theoretical Aspects of Optimization of Evolutionary Learning of Neurochips Using "Isolates"

The evolutionary learning algorithm neurochips, used to restore the damaged nervous tissue, proposed and developed an optimization algorithm based on the method of biological isolation. Proposed and justified the use of theoretical statements "isolates" based on the model of linear city. "Isolated" can be applied to most artificial neural network learning algorithm (INS) without a teacher, based on the evolution of the INS, by crossing the weighting coefficients. Developed approach can be used to construct neurochip used to restore the damaged nervous tissue. The proposed approach makes it possible in most cases to define the proper direction of weight change coefficient to reduce classification errors and achieve the best results neurochip training, compared with using an evolutionary algorithm without "isolates" and, consequently, improve the recovery of damaged nervous ptissue.
Keywords: neurochip, nervous tissue, artificial neural networks, evolutionary algorithms, simulation training

P. 875 – 880

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