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Kultygin O.

Ph. D, Associate Professor, Moscow University of Finance and Industry «Synergy»
Moscow, Russia

Integrated information system for mashinists’ route sheets processing

Rail transport is one of the most important sectors of the Russian economy. At present of particular relevance is the creation and introduction into commercial operation on railways distributed information systems that can provide staff of any management level with comprehensive information on the state of the control object. One system of this kind is an integrated information system processing mashinists’ routes developed by the author for the Moscow railway enterprises.

The application of economic and mathematical methods in the management of locomotive brigades on the Moscow metro

Fast and comfortable transportation of passengers, ensuring safety in trains and in the territory occupied by transport infrastructure are the most important factors affecting competitiveness in the market of transportation services of all types of transport, including the Moscow Metro. To solve this problem, it is necessary to plan efficiently the work of the locomotive subway crews on the basis of the application of modern economic and mathematical methods, which ensures the fulfillment of a given scope of work by the minimum possible number of brigades. The Metropolitan as the most important element of the transport infrastructure of the capital in its work needs to apply effective economic and mathematical methods, in particular, in the planning and distribution of work between locomotive brigades. The specified scope of work of the electro depot must be carried out as far as possible by a minimum contingent of locomotive crews. For this distribution, one of the methods of industrial management «Material cutting problem» is most suitable, which allows to reduce the time of planning procedures execution, to reduce the number of team orderers, to ensure the optimal distribution of locomotive brigades by composition, to reduce their list composition.

Development of an information system for testing students’ knowledge using Delphi and MS SQL Server

Testing students is one way to verify their knowledge. Any person, one way or another, meets with the passage of tests related to his professional activities, training or re-certification. Of course, tests are a serious psychological strain on the subjects, especially in conditions of limited testing time and the number of attempts. Therefore, the actual question is: how to properly organize testing to obtain the maximum positive effect. For comparison: in order to pass the professional tests Microsoft or Oracle companies to receive the certificates of experts or professionals in software these companies need to respond to 75% of the questions correctly. Moreover, the delivery of such tests is carried out in specially equipped, isolated rooms, in the complete absence of mobile phones, tablets, iPads and other similar means. Having tried various methods of testing, the author, having considerable professional experience in the field of programming and creating users’ workplaces, decided to develop a testing system on his own. Software development for testing was carried out using the RAD programming environment Embarcadero Delphi, which made it possible to create an interface convenient for the end user. The main business logic of the testing system was implemented as Microsoft SQL Server stored procedures, which ensured high performance, system scalability and reliable information protection from unauthorized access.

Application of artificial intelligence — reality and prospects

Lately, more and more people are talking about the introduction of neural networks, artificial intelligence systems, and machine learning into various spheres of human activity. This involves new projects such as unmanned vehicles, DNA sequence decryption programs, vacuum cleaning robots, spacecraft robots, robots for functioning in harmful environments, human speech recognition systems, and human speech synthesis. But most often manufacturers of smartphones talk about using artificial intelligence in their new products. Currently, many smartphone manufacturers compete with each other in the market for goods and services, fighting for customers, seeking to draw attention to their products; they are conducting advertising campaigns in which they claim that their products have artificial intelligence. A processor with a neuromorphic module emulating artificial intelligence functions allows machine learning to be used and makes the smartphone as responsive as possible to user habits. A neuromorphic module can predict which applications the user will soon need, loading them into memory in advance and optimizing their work. That is, the advertised artificial intelligence is reduced only to setting up the user's habits using neural-like devices — neural networks. Now most of the portable devices that use machine learning, have a lack of capacity to run artificial intelligence programs, so they resort to using cloud servers. But the use of artificial intelligence programs that work autonomously can significantly improve the performance of smartphones, reduce the time delay between the user's request and the device's response to this request.

Expert Analysis Systems of subject area for the design of information system

The relevance of the topic of this article is to solve the problems of designing rationally built databases for enterprises and to teach students of the University of Synergy, direction«Information Systems and Technologies», the correct design. The purpose of the study is to analyze the applied methodologies at the stage of a system analysis of the enterprise subject area, to develop algorithms for the operation of an expert system. A brief statement of the problem consists in analyzing the available expert systems on the market for similar purposes, identifying the main stages of the work of the created expert system for the automatic design of the enterprise database. Development of our own expert system is economically more profitable. The used methods are the methods of analysis and design IDEF0, DFD, IDEF1, IDEF3, methods of functional (structural) design, methods of object-oriented design. The obtained results are an expert system was developed in the RAD Delphi 7 programming environment that generates a database script in SQL according to a given verbal description of the subject area. The script allows you to create an enterprise database in any industrial DBMS, for example, MS SQL Server. When designing information systems for managing the activities of enterprises, firms, corporations, the correct organization of the storage of their data, the creation of an effective database based on relational industrial database management systems (DBMS), such as Microsoft SQL Server, Oracle, IBM DB2, Informix, MySQL, Firebird, etc., are of great importance.

The application of cloud DBMS in the design of information systems

The relevance of the topic of this article is to solve the problems of organizing remote data warehouses for small newly founded enterprises that do not have the financial resources to create their own information infrastructure. The purpose of the study is to analyze the cloud computing technologies offered by the market from various software manufacturers and select from them the ones most suitable for a particular enterprise. A brief statement of the problem consists in analyzing the systems for organizing cloud data storages available on the market, determining their main characteristics, verifying the compliance of their relational data model, comparing them with traditional industrial DBMSs. Identify the advantages and disadvantages of cloud data storage. Designing an enterprise information system is with using cloud data storage. The used methods are systems analysis methods, SADT structural design methods, methods for constructing relational data models. The obtained results are a methodology has been developed for designing the information system of a small business using cloud storage from Microsoft SQL Azure. Cloud computing is currently one of the most popular areas of information technology development. The largest software companies: Microsoft, Amazon and Google pay special attention to cloud computing. Cloud computing usually refers to the ability of the user to obtain the necessary computing power on demand from the Internet, and the details of the implementation of these features are not important for the consumer. Of particular interest is the implementation of cloud computing for organizing corporate data warehouses and database management systems (DBMS).

Application of big data in the design of expert systems

The relevance of the topic considered in the article lies in solving the problems of designing expert systems for industrial enterprises based on big data technology. The purpose of the study is to analyze the applied methodologies at the design stage of an enterprise information system, to develop algorithms for the operation of an expert system with big data. A brief statement of the problem consists in analyzing the technologies available on the market for working with big data and the possibility of using them for expert systems, identifying the main stages of working with big data for industrial enterprises. In the modern world, the problem of using Big Data has become extremely urgent. Companies, firms and corporations that are leaders in the field of information technology and business conduct are busy looking for optimal solutions for managing a huge amount of constantly incoming information and its in-depth analysis. They are looking for ways to profit from the data at their disposal, trying to get new data from the existing ones. Developing your own expert system is more cost effective. Methods used - methods of analysis and design IDEF0, DFD, IDEF1, IDEF3, methods of functional (structural) design, methods of object-oriented design. The results obtained - a method of using big data to create an expert system for an industrial enterprise has been developed. Implementation of such an expert system on your own is much cheaper than purchasing ready- made software systems. Read more...

Business intelligence as a decision support system tool

The relevance of the topic considered in the article is to solve the problems of designing management decision support systems for enterprises based on business analytics technology. The research purpose is to analyze the applied methodologies during the design stage of the enterprise information system, to develop principles for using management decision support systems based on business intelligence. The problem statement is to analyze the technologies available on the market, which deal with business analyst systems, their potential use for decision support systems, and to identify the main stages of business analyst for enterprises. Business intelligence (BI) is information that can be obtained from data contained in the operational systems of a firm, enterprise, corporation, or from external sources. The BI can help the management of a company make the best decision in the chosen sphere of human activity faster, and, consequently, win the competition in the market for goods and services. A decision support system (DSS) which uses business intelligence, is an automated structure designed to assist professionals in making decisions in a complex environment and to objectively analyze a subject area. The decision support system is the result of the integration of management information systems and database management systems (DBMS). The internal development of BI is more cost-effective. The methods used are Structured Analysis and Design Technique and Object-oriented methods. The results of the research: the analysis of the possibilities was conducted and recommendations relating to the use of BI within DSS were given. Competition between BI software in business analysts reduces the cost of products created making them accessible to end-users – producers, traders and corporations. Read more...

Economic efficiency assessment of projects for the information systems creation

The article is concerned with an approach to assess the economic efficiency of IT projects, which results are recommended to be used when choosing the informatization version for organizations of various types. This approach is based on the calculation of such indicators as capital costs for an IT project, the magnitude of the projected change in operating costs to ensure the functioning of the IS (information system), the growth rate in the efficiency of business processes as a result of informatization, as well as the costs to ensure the required level of information security. The analysis results of modern trends in the IS development for informatization of organization business processes are given, which made it possible to identify the main features of the solutions offered on the market. The analysis of direct and indirect costs for an IT project is shown to be rather difficult in a number of cases, which leads to inaccuracies in assessing its economic efficiency. In this case, the estimated payback period of the project (usually unreasonably short) can be exceeded many times in practice. At the same time, as a result of rapid progress in the field of information technology, the IT projects results are subjected to intense obsolescence, so long payback periods can lead to significant losses for the organization implementing the project. The consideration of the influence of the information security threats and the necessary additional funds for its provision on the forecast indicators for the economic efficiency of the proposed IT projects can significantly affect the decisions on choosing not only the configuration of the IS but the platform on which it operates as well. The article proposes an approach to determine the costs for ensuring information security, which should be considered when assessing the IT project economic efficiency. A mathematical model is described to choose an option for the tables rational placement on IS units (database servers) used by employees of various geographically detached divisions of an enterprise, which will allow reducing operating costs for this system operation. Read more...

Algorithm for predicting the parameters of a system for processing waste apatite-nepheline ores

Within the framework of the concept of a circular economy, research in the field of creating technological systems for recycling waste from mining and processing plants occupies one of the key positions. This is connected, on the one hand, with significant volumes of such waste, reaching tens of millions of tons and posing a significant environmental hazard to air and water basins, human health, and, on the other hand, with their rich chemical and mineralogical composition, which makes it possible to call them accumulations of technogenic deposits. In this regard, the task of creating control systems for technological processes of processing such waste and their information support, including support for all stages of the passage of information processes, is urgent. The novelty of the presented research lies in the proposed structure of an intelligent control system for a complex chemical and energy technological system for processing apatite-nepheline ores, as well as in an algorithm for predicting technological parameters, which is part of the information support of the control system under consideration. The algorithm is based on the use of the apparatus of deep recurrent neural networks and Kalman filtering, which is used at the stage of data preprocessing to train the neural network. The paper describes the proposed algorithm for predicting multidimensional time series, adapted to the considered technological process, presents the software executed in the MatLab environment to demonstrate the efficiency of the specified combination of methods for processing technological parameters. In a model experiment, it has been shown that the use of filtering makes it possible to increase the accuracy of the forecast, which is especially noticeable at its large horizons. The practical significance of the research results is the proposed structure of an intelligent control system for the processing of apatite-nepheline ore waste and software for predicting its parameters, which can be used in various decision support systems. Read more...

Neural network model to support decision-making on managing cooperative relations in innovative ecosystems

Currently, the specifics of external conditions and peculiarities of innovation activity main subjects development determine not only the need for close, long-term scientific and technical cooperation with the state for the sustainable development of territories, but also the need to develop and substantiate proposals for managing the development of innovation processes in such a system as a whole. The article proposes a model for the representation of scientific and industrial interaction in the implementation of regional innovation processes in the form of a three-dimensional "slice" of the triple helix as a resource VRIO-profile of cooperative formation, which allows to clearly demonstrate the system of relations, identify in which direction the problem area is, influencing which it will be possible to return the system to an equilibrium state of sustainable development in a strategic perspective. The analysis of modern scientific works shows the relevance, necessity and effectiveness of using methods based on neural networks to predict changes in the state of complex socio-economic systems, such as regional innovation systems. Existing approaches, as a rule, demonstrate a narrow focus and belonging to a separate enterprise or organization, and therefore do not meet all the requirements from both the implementation of the innovation process itself and the modification of the external environment. In this connection, the authors proposed an information and analytical solution for using the described model to support decision-making on the management of cooperative formations. The developed program is based on predicting the future state (position in a three-dimensional coordinate system) of the system using deep neural networks, namely recurrent. The described practical approbation of the model can in the future serve as a basis for decision-making on the choice of forms and directions of interaction of cooperative formations in the strategic perspective. Read more...

Solving the inverse kinematics problem for sequential robot manipulators based on fuzzy numerical methods

Nowadays the introduction of robotic systems is one of the most common forms of the technological operations automation in various spheres of human activity. Among the robotic systems a special place is occupied by sequential multi-link robotic manipulators (SRM). SRM have become widespread due to relatively small dimensions and high maneuverability, which makes their use indispensable to solve various tasks. In practice, the effectiveness of the functioning of the SRM can be influenced by various types of external environment fuzzy factors. Among the external factors there is a group affecting the ability to determine the exact target position. Such factors often affect technical vision systems. This problem is especially relevant for special purpose mobile robots operating in aggressive environmental conditions. A situation similar to the described one also occurs when a medical robot manipulator is used for minimally invasive surgery, when the role of the control and monitoring system is assumed by an operator. In this regard, the organization of effective control taking into account influence of the external fuzzy factors, that prevent the correct recognition of the target position of the SRM instrument, is an urgent problem. The authors consider the solution of the inverse kinematics problem for SRM based on the use of fuzzy numerical methods, taking into account the possible occurrence of singular configurations in the process of solving. Read more...

Building the mathematical model of the decision support system in the field of pricing for e-commerce

This work is devoted to the study of pricing issues for obtaining maximum profit when selling consumer goods at a constant purchase price. The said goods come in from either manufacturers or warehouses where the retail companies buy the goods in order to sell them directly to the consumers. The dependence of the selling rate per unit of time on the level of the added price in relation to the purchase price of the item is established by the means of sales price variation. The object of the research is the specific case of a linear approximation of said dependence, which is usually actualized in the event of either more elastic or less elastic demand for goods, when they are sold through Internet platforms. The proposed approach to determining prices of all the goods which are being sold for maximizing the total profit from the sales of all consumer goods or maximizing the total revenue throughout the whole period of sales time, based on the search of extremum points of the profit and revenue functions for each item of goods remains valid in the case of more complex approximations by quadratic and cubic functions of demand function. The type of the function of maximum value added revenue and the type of the function of maximum profit can be both found per unit of time depending on the variable level of the added price included into the sales price of the item. The type of maximum revenue function can be found per unit of time depending on the sales price of the item. The extremum points of the found functions are being determined. The theorems have been proved, that the extremum points which are being determined appear to be the maximum points of the researched functions for each item of goods, when the maximum profit or the maximum revenues are reached by selling goods to consumers. All common variables of said functions are found by summing up these functions among the multitude of goods on the interval of the whole sales time. The received data is used for the practical implementation of an effective sales strategy that ensures maximum profits for companies specializing in direct sales to consumers of the purchased goods. An applied methodicalэф approach to the sales of goods which ensures maximum profit from the sales in the field of elastic demand approximated by a linear function and under the condition of a constant purchase price for goods is proposed and theoretically substantiated. Read more...