Actual Problems of System and Software Engineering 2017. Proceedings of the 5th International Conference on Actual Problems of System and Software Engineering Supported by Russian Foundation for Basic Research. Project #17-07-20565 Moscow, Russia, November 14-16, 2017, 408 P.
The volume consists of scientific and research papers of the Fifth International Con- ference “Actual Problems of System and Software Engineering” (APSSE-2017), which took place with the support of the Russian Foundation for Basic Research (RFBR) (Project No17-07-20565). The Conference was held at the National Research University “Higher School of Economics” from November 14 to November 16, 2017 in Moscow, Russia. The conference was devoted to the analysis of the status, contemporary trends, re- search issues and practical results obtained by national and foreign scientists and ex- perts in the system and software engineering area, as well as information and analyti- cal systems development area using Big Data technologies. The target audience of the conference came to be the experts, students and post- graduates working in the area of ordering, designing, development, implementation, operation, and maintenance of information and analytical systems for various applica- tions and their software, also working on custom software development. Plenary papers were delivered by the leading domestic and foreign specialists and were aimed at developing the views on the most important and fundamental aspects of the information technology development. The Conference hosted 13 invited reports. There were submitted 77 articles, 51 from which were selected for publication. All the submitted articles were reviewed by the members of the Program Committee as well as by the independent reviewers.
The article examines in detail the method of design of an own cryptocurrency with a description of its parameters. At the output, a program is obtained, with the help of which it is possible to mining its cryptocurrency and exchange it among users.
The paper examines the functional requirements and the basic architecture of the tools supporting model-oriented techniques for design of safety critical software/hardware systems. The best practices of development such systems are described in international standards like ARP-4754, ARP-4761, and DO-178. The proposed approach is built around architecture models expressed in AADL language and its extensions.
The aim of the work is to create applications for execution of practice works on the stand NI ELVIS II by National Instruments using augmented reality. To form proposals and obtain information about existing objects and the conditions for their interaction with virtual objects. The scheme of the development object is described, its main blocks are indicated.
The information designed for the mobile operating system Android. A user holding a smartphone in their hand (or donning a special helmet) bring the device to the workstation. When the object camera is placed on the laboratory stand, the application starts the algorithm for comparing the captured image with the base markers, after which the analysis result appears on the screen. The user can be tested on the current laboratory work by testing their knowledge.
The methodology, used in this research, allow to identify the structure of non-linear connections in the models of statistical interconnections. The empirical base of research is the reasons for revoking of licenses of Russian banks from 01.2013 to 12.2015 in two groups — due to economic reasons and laundering of money. Models of binary choice for the forecast of revoking licenses were built with the help of the fractional polynomial regression. Models were built for above-mentioned groups. Each model contains financial and social variables. The latter have been got with the help of networks theory from banks relationship analysis.
In this paper, we analyze the use of different neural networks for the text classification task. The accuracy of the studied text classifiers can be changed by a small number of previously classified texts. This is important due to the fact that in many applications of text classification a large number of un- labeled texts are easily accessible, while the receipt of marked texts is quite a difficult task. The paper also shows that the convolution neural network can work better at the level of words, and does not require knowledge of the syntac- tic or semantic structure of the language. On the other hand, a recurrent neural network for the level of data representation in the form of a sequence can effec- tively classify the text. Experimental results obtained for text corpora from two different sources show that using a vector data representation can also improve the accuracy of the classification.
By planning production and marketing strategy it is necessary to find the balance between customer’s preferences and manufacturability. It is very important to understand the manufacturer-vendor chain, i.e. to avoid over/underproduction, oversupply and shortage of goods. In order to solve this problem it is required to collect and process a great volume of different data both from open sources and from the customer. This article shows you the Big Data Technology solution experience.
The extremely important role of information in the modern world has led to the identification of information as an own resource, as important and necessary as energy, financial, raw materials. The needs of society in the collection, storage and processing of information as a commodity have created a new range of services – the information technology market. The volumes of information are growing rapidly, such kind of data volume is called "Big Data», and has been offered for analysis. In order to solve management problems based on the analysis of such data, it is necessary to take into account their heterogeneity, high degree of variation. Therefore, the systematization and grouping of the information obtained makes it possible to improve the quality of the decisions made in the planning and production management tasks. In the process of choosing the grouping methods, the greater dimensionality of the data that affects the processing time of information should be taken into account besides the type of the task in hand. This work presents the results of research of the methods of grouping data for a certain range of practical problems in the processing of large data, as well as the results of solving various practical management problems using various methods
The modification of algorithm of Viterbi convolutional decoding for the fading channels and use of interleaving of symbols is described. The modification represents the use of additional correcting coefficients in the process of calculation of metrics of various parts in the trellis diagram. It gives opportunity to reduce the probability of errors of decoded symbols.
At the beginning of the paper, it is demonstrated that the technology of the most widely used SQL-oriented DBMS is inextricably linked with HDD technology. Features of HDD affect the data structures and algorithms for performing operations, methods of managing the buffer pool of the DBMS, transaction management, query optimization, etc. An alternative to a disk DBMS is an in-memory DBMS, storing databases entirely in the main memory. Despite the fact that in-memory DBMS has a number of advantages over disk DBMS, at present there is practically no competition. This, first of all, is due to natural limitations on the size of databases, inherent in in-memory DBMS. At present, new types of data storage hardware have appeared: SSD – block solid-state drives and SCM – storage-class memory (non-volatile main memory). SSD characteristics made it expedient to develop a DBMS in terms of their exclusive use, but so far such a DBMS has not been created, and SSDs are used simply instead of HDDs in DBMS that do not take into account their features. The availability of SCM allows to radically simplify the architecture of the database and significantly improve their performance. To do this, you need to review many of the ideas used in disk-based databases.
The article is dedicated to application of case-based method in the problem of choosing correct suitable scenarios to resolve emergency situations occurring on main gas pipeline. The result of the work is the algorithm for choosing scenarios with the given level for suitable solutions to resolve emergency situations using base of cases describing emergency situations on main gas pipeline.