2017. No. 1 (39)

Andrey A. Shcherbovich - Lecturer, Department of the Constitutional and Administrative Law, National Research University Higher School of Economics
Address: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation
E-mail: ashcherbovich@hse.ru

      The decision-making system in international organizations is still very conservative. The composition of international forums that can generate significant international instruments has not changed for centuries. Only diplomats and representatives of international organizations whose credentials have been confirmed in a certain way are admitted to international decision-making. The Internet Governance Forum (IGF), under the auspices of the UN, UNESCO and the International Telecommunication Union, was established in 2006 on the basis of the World Summit on the Information Society, which is today the world’s most authoritative international discussion forum on Internet governance, though its potential to achieve the best regulation of international Internet governance processes is not fully used. The basis for this regulation is the multistakeholder approach, which consists in a multiplicity of categories of the decision-making mechanism, including, in addition to the traditional representatives of states and international organizations, civil society, business, the academic and technical community, the media, and other interested stakeholders.
      This research is expected to provide guidance for improving the global Internet governance arrangements, taking into account the interests of all categories of participants, as well as to establish procedural rules for decision-making based on the multistakeholder approach in Internet governance to give the Internet Governance Forum the opportunity to adopt international “soft law” instruments. An example of this is the Draft Charter of Rights and Principles on the Internet, developed by the Dynamic Coalition on Human Rights and the principles of the Internet Governance Forum – something comparable to the Universal Declaration of Human Rights with regard to the Internet. The need to bring human rights instruments to the Internet determines the direction of the development of programs and policies in global Internet governance and the role of the Internet Governance Forum in these processes.

Larisa A. Ismagilova - Professor, Head of Department of Business Economics, Ufa State Aviation Technical University
Address: 12, Karl Marx Street, Ufa, 450000, Russian Federation
E-mail: Ismagilova_ugatu@mail.ru

Marina V. Frants - Associate Professor, Department of Business Economics, Ufa State Aviation Technical University
Address: 12, Karl Marx Street, Ufa, 450000, Russian Federation
E-mail: tan-Marina@mail.ru

Murat B. Kulmukhametov - Doctoral Student, Institute of Social and Economic Research, Ufa Scientific Center of Russian Academy of Sciences
Address: 71, October Prospect, Ufa, 450000, Russian Federation
E-mail: murat.kulmuhametov@gmail.com

      The article deals with the problem of an enterprise’s human resource management. An enterprise’s human resources are described as a dynamic object of management with a great number of parameters specifying various aspects of its condition.  The traditional techniques of human resources analysis are based, firstly, on retrospective analysis of data, and secondly, they take different aspects isolated from each other. The proposed managerial decisions are assessed from the point of view of their impact on separate parameters, but their synergetic effect is not assessed. These drawbacks may be eliminated through application of dynamic modelling including cognitive and flow modeling.
      Cognitive modeling identifies mechanisms responsible for system reaction on managerial and disturbing influences. A cognitive map of the problem of human resources management was made which includes lots of feedback loops, both reinforcing and balancing. This means, the control object is characterized by nonlinear dynamics and counterintuitive behavior. These features make it difficult to predict object reaction on managerial and disturbing influences.
      Within the overall issue of human resources management, this work reviews its particular aspect – the analysis of company’s nonproduction losses due to temporary disability of employees. The temporary disability of an employee is understood as his/her temporary inability to perform job duties because of health condition of either himself/herself or his/her family members. The temporary disability is considered to be partially controlled by the enterprise. A flow model is elaborated for assessing a company’s nonproduction losses caused by temporary disability of its employees, which can be used to optimize human resources management costs of an enterprise from the perspective of the cost-benefit ratio.

Nerses K. Khachatryan - Senior researcher, Laboratory of Dynamic Models of Economy and Optimization, Central Economics and Mathematics Institute, Russian Academy of Sciences; Associate Professor, Department of Business Analytics, National Research University Higher School of Economics
Address: 47, Nakhimovsky Prospect, Moscow, 117418, Russian Federation  
E-mail: nerses@cemi.rssi.ru; nkhachatryan@hse.ru

Andranik S. Akopov - Professor, Department of Business Analytics, National Research University Higher School of Economics
Address: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation
E-mail: aakopov@hse.ru 

      A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traffic is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the final node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties.
      This model is described by a finite-dimensional system of differential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of differential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.

[1]This work was supported by the Russian Foundation for Basic Research (project No. 16-01-00110).

Liliya R. Chernyakhovskaya - Professor, Department of Technical Cybernetics, Ufa State Aviation Technical University
Address: 12, Karl Marx Street, Ufa, Republic of Bashkortostan, 450008, Russian Federation
E-mail: lrchern@yandex.ru

Albina F. Galiullina - Doctoral Student, Department of Technical Cybernetics, Ufa State Aviation Technical University
Address: 12, Karl Marx Street, Ufa, Republic of Bashkortostan, 450008, Russian Federation
E-mail: GAF1205@yandex.ru

      This article describes the requirements for a decision support system which is designed to assess the quality of public services. Requirements for a decision support system are used as a starting point at its design stage and determine the functions of the developed system without showing the mechanism of its implementation. At the same time, the requirements serve as constraints in the process of system development. The set of the developed requirements for the decision support system includes basic, functional, non-functional and economic requirements.
      We propose to use the ontological approach in the development of requirements for the system. This allows us to solve a number of problems arising from the description of the requirements in natural language: the lack of exposition clarity, misrepresentation of the requirements and so on. The ontological model allows developers to interpret the requirements in the same way, to structure the specification of requirements for the system and to eliminate blurring in their definitions. Ontological representation of knowledge about requirements for the developed system and about the system providing public services in general is used for the semantic integration of existing information resources, appropriate interpretation of the content of text documents and search queries presented in a natural language. The developed ontology improves the quality of user (stakeholder) interaction during the system operation. In addition, it includes rules for term combination to provide reliable assertions on the state of the decision support system.

Mikhail S. Dvoretckii - MSc Program Student, Lomonosov Moscow State University; Programmer, IQ Systems LLC
Address: 1, Leninskie Gory, Moscow, 119991, Russian Federation
E-mail: mike.dvorecky@gmail.com

      An important way of ensuring data quality is controlling data input. One of the methods of doing that is checking the input data against the corresponding reference data where applicable. This may be done via autocomplete. Since reference data is usually stored in a centralized fashion, autocomplete algorithms usually run in client-server architectures and face strict time requirements.
      In this article, a new autocomplete task decomposition is formulated using an existing method based on range minimum queries (RMQ). The Top-k RMQ problem is formulated and used in the autocomplete problem decomposition. A segment tree based algorithm is proposed for the Top-k RMQ problem. While the conventional segment tree based RMQ algorithm when used in autocomplete (in the Top-k RMQ sub-problem) repeatedly processes the same nodes on the tree, the proposed algorithm is adapted directly to the Top-k RMQ problem and does not require any node of the segment tree to be processed more than twice. A complexity analysis is made for both the new Top-k RMQ algorithm and the conventional segment tree-based RMQ approach. This analysis considers different implementations of priority queues used in these algorithms, specifically binary heaps and ordered arrays. The new algorithm has time complexity that is not lower than that of the conventional algorithms with any priority queue implementation.
      To prove the practical value of the new algorithm, a series of experiments was conducted using the data from the All-Russian Classifier of Addresses – a practical source of reference data for Russian address inputs. The new algorithm demonstrates better time efficiency than the conventional one in all experiments with all priority queue implementations.

Yuriy P. Yekhlakov - Professor, Head of Department of Data Processing Automation, Tomsk State University of Control Systems and Radioelectronics (TUSUR)
Address: 40, Prospect Lenina, Tomsk, 634050, Russian Federation
E-mail: upe@tusur.ru

Dmitriy N. Baraksanov - Senior Lecturer, Department of Data Processing Automation, Tomsk State University of Control Systems and Radioelectronics (TUSUR)
Address: 40, Prospect Lenina, Tomsk, 634050, Russian Federation
E-mail: bdn@tusur.ru

      This paper discusses the problem of selecting a set of online marketing tools, advertising space, places and duration of display of advertising communications(AC) restricted by a tight advertising budget. The tool offered to evaluate the efficiency of AC display is the conversion rate. The paper reviews the methods for calculating the conversion rate. The formalized problem statement is represented as an integer valued linear programming model and reduced to maximization of the total conversion from advertising communications displayed under a tight advertising budget and with a limited selection of online marketing tools and duration of AC display.
      The paper describes a solution algorithm based on the method of wave planning. It allows the decision maker to run an iterative decision making process in each interval of the planning period based on the AC conversion rate obtained at the previous stage. The authors propose methods for calculating input parameters for the model: AC display conversion rate, cost of AC placement in the advertising space over the shortest possible period, average number of AC displays over the shortest possible period.
      The paper describes the results of experimental study of the model and the algorithm using the example of AC planning for Electronic Timetable software marketing to colleges and universities of the Kemerovo region. The results have practical value for executives and marketing managers of small innovation-based companies running advertising campaigns and planning communications with potential consumers using the tools of online marketing. 

Ilya A. Hodashinsky - Professor, Department of Complex Information Security of Computer Systems, Tomsk State University of Control Systems and Radioelectronics (TUSUR)  
Address: 40, Prospect Lenina, Tomsk, 634050, Russian Federation
E-mail: hodashn@rambler.ru

Sergey S. Samsonov - Student, Department of Complex Information Security of Computer Systems, Tomsk State University of Control Systems and Radioelectronics (TUSUR)  
Address: 40, Prospect Lenina, Tomsk, 634050, Russian Federation
E-mail: samsonicx@mail.ru

      This article presents an approach for building fuzzy rule based classifiers. A fuzzy rule-based classifier consists of IF-THEN rules with fuzzy antecedents (IF-part) and the class marks in consequents (THEN-part). Antecedent parts of the rules break down the input feature space into a set of fuzzy areas, and consequents define the classifier exit, marking these areas with a class mark. Two main phases of building the classifier are selected: generating the fuzzy rule base and optimizing the rule antecedent parameters. The classifier structure was formed by an algorithm for generating the rule base by extreme features found in the training sample. The peculiarity of this algorithm is that it is generated according to one classification rule for each class. The rule base formed by this algorithm has as low as practicable size in classification of a given data set. The optimization of parameters of antecedents of the fuzzy rules is implemented using the monkey algorithm adapted for these purposes, which is based on observations of monkey migration in the highlands. In the process of the algorithm work, three operations are performed: climb process, watch jump process and somersault process. One of the algorithm’s advantages in solution of high-dimension optimization problems is calculation of the pseudo-gradient of the objective function. Irrespective of the dimension at each iteration of the algorithm execution only two values of the objective function are to be calculated.
      The effectiveness of fuzzy rule-based classifiers built with the use of the proposed algorithms was checked on actual data from the KEEL-dataset repository. A comparative analysis was conducted using the known analog algorithms “D-MOFARC” and “FARC-HD”. The number of rules used by the classifiers built with the use of the algorithms so developed is much lower than the number of rules in analog classifiers with a comparable classification accuracy, that points to the highest interpretability of the classifiers built with the use of the proposed approach.

[1] This work was supported by the Ministry of Education and Science of the Russian Federation, agreement no. 8.9628.2017/BP 

Sergey A. Glushenko - Senior Lecturer, Department of Information Systems and Applied Computer Science, Rostov State University of Economics
Address: 69, Bolshaya Sadovaya Street, Rostov-on-Don, 344002, Russian Federation
E-mail: gs-gears@yandex.ru

      This article explains the importance of applying risk assessment in the implementation of information security systems. It is considered the most common risk assessment procedure and entails application of fuzzy logic theory for this purpose. The paper describes the proposed fuzzy production model (FPM), which defines seven input linguistic variables describing risk factors, four output linguistic variables that characterize different areas of information security risks, as well as four base rules.
      It is noted that the FPM is the first approach to the subject area and requires optimization to minimize the model’s output errors. The most common methods of optimization of fuzzy models parameters are examined, and the advantages of applying methods based on neuro-fuzzy networks (NFN) are justified.
      The article describes the process of converting fuzzy model elements, such as unit fuzzification, rule base unit and unit defuzzification, into fragments of the neural network. The result of this process is a neuro-fuzzy network corresponding to the fuzzy model.
      Formation of the developed NFN is based on an adaptive neuro-fuzzy inference system (ANFIS), using the specialized Neuro-Fuzzy Designer package of MATLAB software. The model was trained by a hybrid method which represents a combination of the methods of least squares and backpropagation. The result of this process is optimization (setting) the parameters of membership functions of input linguistic variables.
      Application of neuro-fuzzy modeling made it possible to obtain a more appropriate fuzzy production model which is able to conduct linguistic analysis of the risks of an organization’s information security. The information obtained with its help allows IT managers to determine risk priorities and to develop effective action plans to reduce the impact of the most dangerous threats.

[1] This research has been carried out with financial support of RFBR within the framework of scientific project No. 16-31-00285 “Fuzzy logic methods and models in risk management decision support systems”