Actual Problems of System and Software Engineering. Proceedings of the 6th International Conference Actual Problems of System and Software Engineering. Moscow, Russia, 12-14 November, 2019
The volume consists of scientifi c and research papers of the Sixth International Conference “Actual Problems of System and Software Engineering” (APSSE-2019). The Conference was held at the National Research University “Higher School of Economics” from November 12 to November 14, 2019 in Moscow, Russia. The conference was devoted to the analysis of the status, contemporary trends, research issues and practical results obtained by national and foreign scientists and experts in the system and software engineering area, as well as information and analytical systems development area using Big Data technologies. The target audience of the conference came to be the experts, students and postgraduates working in the area of ordering, designing, development, implementation, operation, and maintenance of information and analytical systems for various applications 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. Submitted articles 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 using of a project-based learning approach to teaching students still causes a lot of disputes and disagreements. This learning approach allows to minimize the set of the necessary theory and increases the number of practical activities. We applied project-based approach for teaching 150 software engineering students simultaneously. The article shows how to apply project-based training on large group of students and gives examples of typical mistakes in such teaching approach.
Visually impaired and blind people frequently have no knowledge of outdoor obstacles. and need guidance in order to avoid colliding risks. The aim of this research is to develop a mobile-based navigation system for helping visually impaired people in outdoor navigation. The proposed system will be able to reduce the obstacle collision risks by enabling users to walk outside smoothly with voice awareness. The current used systems for navigating visually impaired have several drawbacks such as cost, dependency, and usability. The suggested solution includes a mobile-based camera vision system to build an independent application for outdoor navigation. Moreover, the system has high usability to navigate visually impaired people in unfamiliar environments such as a park, roads and so on. In the presented work, the deep learning algorithms are employed for recognizing and detecting different objects and it is implemented as a mobile navigation application. The suggested smartphone-based system is not restricted to the defined outdoor environments and does not depend on any other positioning system. Therefore, the proposed solution is not limited to any specific environment and provides the voice aids about surrounding obstacles for users.
Abstract: The article describes an approach to solving the problem of structuring the supply and demand of goods and services. The proposed approach, based on the use of Data Science methods, will allow implementing modern tool for monitoring the development of industry in Moscow. Such tool helps to analyze a large number of structured, unstructured and poorly structured data from any open source. This allows to timely and accurately assess the appearance of positive and negative trends in the performance of industrial enterprises in Moscow.
This paper discusses ways of structuring networks using clusterization. In the work, the probabilities of reaching fixed network nodes are calculated for various characteristics of a data transmission system. It will be shown here the clustarization in the network allows us to specify digraph, the numbering of vertices in which makes it possible to calculate the stages of transmission using multiplication table of substitution.
Abstract. Background: Digital content is a key part of a Digital University, which is becoming more relevant to meet the requirements of the digital world. Traditional universities should in fact “reinvent themselves”: they need to switch quickly from the usual focus on managing the learning process (program portfolio) to managing the educatinal experience of the target audience, whose expectations of the personalized, adaptive and 24/7 format of interaction with the learning system become more natural. Design/Methodology: Transformation affects organiza-tion, processes, people, including educational content and the ways to present it. The paper reviews the key aspects of a digital university with the main focus on digital educational content and explores different perspectives of the digital content. Objective: This paper outlines the generalized model of the digital education and suggests the application of a digital platform for the innovative educational purposes by the example of the idea of the digital “SuperBook” press. Results: The authors of the paper propose the concept of an innovative SuperBook web-service, which can be used on the basis of a digital university and can provide great opportunities to students to use digital content. Conclusion: The research gives a better insight in transformation process of the educational content. This research can be used as a basis for further transformation to a digital university. An analysis of the current trends of the digital university and the research of the interested parties showed that the SuperBook technology platform will be in demand in the academic field.
This paper addresses analyzing the data flows that appear when distributed database works. An algorithm for optimizing database replication is proposed. As a protocol data replication two-phase commit protocol (2PC) with two levels of lock records (shared lock (Shared), and an exclusive lock (Exclusive)) is considered.
Review of intelligent methods for intrusion detection in local area networks is presented. Publically available datasets of intrusions are shortly described. A problem of imbalanced classes appointed and approach for batch training of a neural network intrusion classifier with imbalanced classes is presented. In computer simulation, it is shown that such approach helps to train on classes with small amount of examples by the cost of larger classes.