Software & Systems

Articles of journal № 1 at 2021 year.

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1. Architecture and programming implementation of research testbed of a corporate Wireless Local Area Network [№1 за 2021 год]
Authors: L.I. Abrosimov , M.A. Orlova, H. Khayou
Visitors: 2463
The paper presents the architecture and implementation of a research testbed for obtaining and analyz-ing the probabilistic time characteristics of a corporate Wireless Local Area Network (WLAN). To de-velop this testbed, the authors obtained mathematical relations for calculating the guaranteed intensity of multimedia traffic. The research testbed architecture includes the two independent blocks. The block "Simulation testbed" contains the corporate WLAN description and the multimedia traffic flows in the discrete-event simulation system ns-3. The block "Analyzing simulation results" contains programs for analyz-ing files of transmitted traffic and simulation results and programs for calculating performance charac-teristics. To write the block "Analyzing simulation results ", the authors used the Python3 language, the analysis of the transmitted traffic files was performed using the pyshark library. The paper also contains the analytical equations of the WLAN model used in the block " Analyzing simulation results ". The above equations allow us to determine the maximum intensity of the delivered packets for a prescribed time of guaranteed packet delivery, for wireless communication channels us-ing a prescribed channel protocol. A software implementation of the research testbed affords the op-portunity to get the dependence of intensity guaranteed multimedia traffic for the specified parameters: structure WLAN, the settings of the wireless communication channel protocols, and channel access control. The developed testbed provides the capability of operation in two modes. In the development mode of a new WLAN, when the known parameters are the equipment passport data, logical characteristics of protocols, and expected traffic characteristics, a full set of functional modules and blocks is used, which allows both traffic matching with transmission and processing resources, and the specified per-formance of the WLAN. In operation mode, when monitoring allows you to get actual characteristics of traffic and protocols, the testbed allows the WLAN administrator to test the performance of the WLAN and the traffic intensity. This mode uses a limited module set, which requires much less time to evalu-ate the performance of the WLAN, provides the ability to adaptively change the settings of the WLAN, and provides the performance characteristics of the WLAN that meet the requirements of QoS.

2. Software environments for studying the basics of neural networks [№1 за 2021 год]
Authors: P.Yu. Bogdanov , E.V. Kraeva , S.A. Verevkin, E.D. Poymanova, Tatarnikova, T.M.
Visitors: 3291
The paper describes the ways and methods of studying and constructing neural networks. It is shown that the study of the functioning guidelines of neural networks, their application for solving certain problems is possible only through practice. There is the analysis of various software environments that can be used in the laboratory and prac-tical classes for the study and application of neural networks in the paper. Highlighted the modern cloud service Google Colaboratory, which is recommended for teaching the basics of neural networks due to the presence of a pre-installation of the Tensorflow library and a library for working in Python, free access to graphics processors, the ability to write and execute program code in a browser, and no need for special configuration of the service. Examples of designing neural networks in the Colaboratory are considered. In particular, solving recognition problems and image classification, predictive modeling. The authors show that a convolu-tional neural network can be used for image recognition and classification, a feature of which is obtain-ing the image features a map with subsequent convolution. There are chunks of code for the connecting phases the necessary libraries, loading data sets, normalizing images, assembling a neural network, and its training, in the paper. The solving of the forecasting problem is considered on the example of a feed-forward neural net-work with an algorithm for backpropagation of errors in the learning process, the essence of which is to obtain the expected value at the output layer when the corresponding data is fed to the input layer. Backpropagation of errors consists of adjusting the weights that give the greatest correlation between the input dataset and its corresponding result.

3. Semantic analysis of scientific texts: Experience in creating a corpus and building language pattern [№1 за 2021 год]
Authors: E.P. Bruches , A.E. Pauls , Batura T.V., V.V. Isachenko, D.R. Shsherbatov
Visitors: 2876
This paper is devoted to the development of methods for named entity recognition (NER) and relation classification (RC) in scientific texts from the information technology domain. Scientific publications provide valuable information about cutting-edge scientific advances, but efficient processing of in-creasing amounts of data is a time-consuming problem. Continuous improvement of automatic methods of such information processing is required. Modern deep learning methods are relatively good at solv-ing these problems with the help of deep computer-aided learning, but in order to achieve outstanding quality on data from specific areas of knowledge, it is necessary to additional training the obtained models on the specially prepared dataset. Such collections of scientific texts are available in English and are actively used by the Russian scientific community, but at present such collections are not pub-licly available in Russian. The paper contains the RuSERRC dataset description, which consists of 1600 unlabeled documents and 80 labeled with entities and semantic relations (6 relation types are considered). Several modifications of the methods for building models for the Russian language are also pro-posed. This is especially important, since most of the existing research is focused on working with data in English and Chinese, and it is not always possible to find high-quality models for the Russian lan-guage in the public domain. The paper includes the results of experiments comparing the vocabulary method, RAKE, and methods based on neural networks. Models and datasets are publicly available, and we hope it can be useful for research purposes and the development of information extraction systems.

4. Mental models in designing the behavior of artificial objects [№1 за 2021 год]
Author: Vinogradov G.P.
Visitors: 3509
The authors relate the immediacy of the problem considered in this paper to the need to design artifi-cial systems to perform a certain mission like a person and when interacting with him. The analysis of approaches to the construction of artificial objects has shown that developers often give artificial objects their own patterns of behavior because of the specifics of the concepts and con-cepts they use. As a result, there are gaps between the formal models of patterns offered by developers and the expectations of users. The aim of the authors is to justify an approach to the development of software for intelligent sys-tems for managing the behavior of artificial entities based on the theory of patterns and to propose an approach that provides the development of digital products based on the patterns of behavior of the subject-leader for artificial entity management systems that automate the implementation of mission problems. The work uses the methods of the theories of reflexive games and information management of sys-tems with willpower and intelligence. There are ten constituent elements based on a formal model of the behavior pattern. The work shows that these elements form what can be called an intelligent digital machine designed to automate the execution of a mission in the interests of the host subject. These components are present when a person performs a mission, including all participants in the project to develop an artificial entity. The authors show that the ideas adjustment about the architecture of an ar-tificial entity through the exchange of information during the discussion allows us to determine the most effective model of the behavior pattern and all its components for implementation in an artificial entity. The authors proposed to conduct matching as a game by conducting experiments using the TOTHE method (a set of input data  impact  result), using spatial and visual logic to interpret the results. The possible logic of interpretation is justified. The authors briefly considered the models of the constituent elements of the behavior pattern for an artificial entity. An example of the approach im-plementation is considered. The authors show that in conditions of severe time scarcity; the choice based on behavior patterns makes it possible to implement effective behavior that does not require sig-nificant computational resources.

5. Algorithms for smart node patterns in a wireless sensor network [№1 за 2021 год]
Authors: Vinogradov G.P., Emtsev А.S., Fedotov I.S.
Visitors: 3777
One of the trends in the development of modern weapons is the "linking" of individual samples with a certain degree of autonomy into a complex using, as a rule, wireless sensor networks. The scope of such complexes is uncertain and poorly formalized environments. It is possible to achieve their desired efficiency mainly by improving the intellectual component of the management system of the complex as a whole and the individual node in particular. However, it should be noted that the vast majority of research in this area remains only at the theoretical level. There is a gap be-tween the primitive models of artificial entities’ behavior, for example, in swarm robotics, models of their interaction, and expectations from the practice. The situation is aggravated by the secrecy re-quirements, miniaturization, and low energy con- sumption. This paper presents an approach to the development of software for intelligent control systems for a separate network node that has a given degree of autonomy when performing problems. To offer rela-tively simple algorithms in the conditions of restrictions on power consumption and speed for giving the network node the properties of intelligent behavior, to provide the ability to study the situation and decide both independently, considering the data received from other network devices, and as part of a group. There are methods of the fuzzy sets theory, the theory of building fuzzy models and networks, and approaches and algorithms for building on-board intelligent control systems in this work. The work shows that the class identification of typical situations and successful action methods in actual conditions contribute to the development of the required algorithms. On this basis, it becomes possible to develop formal behavior models (patterns) for implementation in the node management system. The authors propose a two-level structure of an intelligent network management system. The upper level, implemented by the operator, corresponds to such properties as survival, safety, the fulfillment of mission obligations, accumulation, and adjustment of the knowledge base as effective behavior pat-terns. The object of control for it is the network, considered as a functional system. It calculates the current indicators of specific value based on the results and effectiveness at time t, calculates and im-plements the method of action (behavior) at time t according to a given behavior pattern, and monitors the results of implementing the behavior pattern.

6. Approach to designing software for artificial entity management systems [№1 за 2021 год]
Authors: Vinogradov G.P., Konukhov I.А., Shepelev G.А.
Visitors: 3943
The problems of intelligent control of artificial entities (including robotic complexes (RC)) are closely associated with the problem of decision-making. The formal decision theory was developed by abstracting from subjective fac-tors. This led to the development of a normative theory of decision - making by the "ideal" subject. Analysis of ap-proaches to the construction of RC control systems has shown that they do not have the property of independent de-cision-making. In practice, developers entertain possible behaviors of such systems, and the corresponding algo-rithms are embedded in the RС control system. As a result, such an object doesn’t have a self-sufficient behavior that guarantees the fulfillment of some mission, especially as part of a human-machine system. The demand for be-havior intellectualization forces us to reconsider the logical and mathematical abstractions underlying the construc-tion of their onboard control systems. The work objective is to substantiate the approach to software development of intelligent RC control systems based on the pattern theory. It is necessary to develop an approach that ensures the transfer of effective experience to the RC management system, the compatibility of the theological approach, and the causal approach, which is im-portant when integrating the RC and the personnel of the units. Show that the patterns of the subject's departure from the ideal rational choice to the subjectively rational are associated with the peculiarities of identification and under-standing of the state of the external environment and the properties of their interests. External factors are related to the obligations that the agent assumes. Internal factors reflect the interests of the subject, induced by his needs and the ethical system that he sticks to. The paper uses the methods of the theory of reflexive games and the theory of information management of sys-tems with will and intelligence. It is shown that the choice in conditions of severe time deficit is made based on behavior patterns that reflect ef-fective experience. Patterns form both the information structure of representations and the set of possible variants of representations. Assessments of contentment with the current situation of choice by the subject lead to a change in the structure of interests of the subject, and he can choose it. A formal model of the behavior pattern is developed. An approach to solving the problem of identification and construction of pattern models is proposed. For these pur-poses, four positions of information processing were used, and a method of logical inference on patterns was devel-oped. The results of software solutions for identifying the behavior pattern when using a new generation of training systems are presented.

7. Developing ontology schemas based on spreadsheet transformation [№1 за 2021 год]
Authors: Dorodnykh N.O., Yurin A.Yu., A.V. Vidiya
Visitors: 3484
Using ontologies is a widespread practice in the in creating intelligent systems and knowledge bases, in particular, for the conceptualization and formalization of knowledge. However, most modern ap-proaches and tools provide only manual manipulation of concepts and relationships, which is not al-ways effective. In this regard, using various information sources, including spreadsheets, is relevant for the automated creation of ontologies. This paper describes a method for the automated creation of ontological schemes in the OWL2 DL format based on the analysis and transformation of data extracted from spreadsheets. A feature of the method is the use of the original canonical relational form for the intermediate representation of spreadsheets, which provides the unification of input data. The method is based on the principles of model transformation and comprises four primary stages: converting the original spreadsheets with an arbitrary layout into a canonical (relational) form; obtaining fragments of the ontological scheme; ag-gregation of separate fragments of the ontological scheme; generation of the code of the ontological scheme in the OWL2 DL format. The method is implemented in the form of two software tools integrat-ed by the data: TabbyXL as the console Java application for table conversion and the PKBD.Onto plugin as the extension module for Personal Knowledge Base Designer (software for expert systems prototyping). The transformation of a spreadsheet with information about minerals is considered as an illustrative example, and the transformation result is presented in the form of a fragment of an ontolog-ical scheme. The method and tools are used in the educational process at the Institute of Information Technologies and Data Analysis of the Irkutsk National Research Technical University (INRTU).

8. Parallelization in the analysis of physical data of the LHCb experiment [№1 за 2021 год]
Authors: A.V. Egorychev, I.M. Belyaev, Т.A. Ovsiannikova
Visitors: 2862
The general progress in hardware performance since the 1990s has completely expanded the ability to build information systems from ready-made components and made available freely distributed soft-ware tools for designing programming systems, including those that support the organization of parallel processes, if not at the language level itself, then at the level of library components. The paper presents the application results of parallelization in physical data analysis problems of the LHCb experiment. The current realization is implemented in the OSTAP framework based on the ROOT and python packages. The amount of the data obtained in proper time in experiments at the Large Hadron Collider require a high speed of preprocessing, which means high computing perfor-mance. The high processing speed is also a major requirement for analyzing the data obtained in the subsequent stages. Adaptation of the software to modern multi-core and multiprocessor systems makes it possible to achieve the necessary computing power for efficiently solving the data analysis problems in experiments of elementary particle physics. The OSTAP software package has a user-friendly interface which is implemented by using the Py-thon. The Python has also established itself as a powerful tool for developing distributed systems and network programming. The parallel algorithm can be implemented in parts on many different devices with the subsequent combination of the obtained results and obtaining the target result. Multiparadig-matic languages, such as Python, show excellent results in programming network processes for multi-processor systems and attract many supporters.

9. Software complex for detection and classification of natural objects based on topological analysis [№1 за 2021 год]
Authors: S.V. Eremeev , A.V. Abakumov
Visitors: 2482
The algorithm of natural objects search on satellite images requires a certain balance. Due to natural character, there are no two completely identical objects, so this problem requires some stability from the algorithm. For such purposes, topological data analysis methods can be used. These methods allow us to obtain a unique characteristic of the image as barcodes, which can be used as training by most modern classifiers. Software complex, based on topological analysis methods, has been developed. It allows us to search for a necessary natural object on a raster image for its further classification and processing. The software complex structure includes several subsystems. They are a subsystem of interest areas selec-tion on the image, a subsystem of barcode building, a subsystem of similar objects search, and a sub-system of found objects output. The principles of selecting objects of interest in images, building barcodes, and comparing them are described in detail. Topological characteristics in the form of Betty numbers are calculated for each spatial object selected on the geo-image. These characteristics are the basis for building the barcode. The process of image decomposition into a sequence of binary images to obtain stable topological characteristics is shown. The principle of barcode comparison for determining the similarity of selected areas of interest with reference objects is demonstrated. There are examples of using software complex for the search problem for ice on the raster image in the paper. The results of found objects with different degree of similarity regarding templates depend-ing on the specified parameters are shown. The software complex can be used for a wide range of problems of natural objects analysis on satellite images including data processing for a different time and on different scales.

10. Using the entropy characteristics of network traffic to determine its abnormality [№1 за 2021 год]
Author: Efimov A.Yu.
Visitors: 3531
The number and scale of network computer attacks (intrusions) are constantly growing, which makes the problem of their prompt detection highly relevant. For this, network-level intrusion detection sys-tems are used, based on two approaches – abuse detection and anomaly detection, and the second ap-proach is more promising in the face of the constant appearance of new and modified types of intru-sions. The main objects of application of anomaly detection techniques are mass attacks (DoS- and DDoS attacks, scanning, spreading of worm viruses, etc.), which are difficult to detect by other (for ex-ample, signature-based) methods, since they are often based on regular network interactions. The entropy analysis method for detecting network traffic anomalies, compared to many other methods, is characterized by sufficient simplicity of implementation and speed of operation. The appli-cation of the method is based on the general assumption that abnormal traffic is more ordered or struc-tured than normal traffic in some parameters and more chaotic in others, which manifests itself as a de-crease or increase in the entropy of these parameters. This paper is devoted to determining the nature of the impact of attacks on the entropy of such traf-fic parameters as the source and destination IP addresses, as well as the destination port, considering several types of DoS- and DDoS attacks as objects. The author describes an approach to determining entropy (using Shannon entropy). The paper presents the results of the author's model, which reveal the ambiguity of the impact of attacks on entropy characteristics. The results show a clear dependence of such inpact (decrease or increase) depends on factors such as the source, target, attack power, and dis-tribution of normal traffic. Conclusions are made about the possibility of effective detection of anomalies corresponding to DoS and DDoS attacks by analyzing the entropy of network traffic parameters, but only if this analysis is carried out taking into account the distribution of normal traffic and the volumetric characteristics of normal and total traffic.

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