Software & Systems

Articles of journal № 3 at 2021 year.

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11. Software implementation of the data mining module based on case-based reasoning for distributed intelligent systems [№3 за 2021 год]
Authors: Eremeev, A.P. , Varshavskiy P.R., Polyakov S.A.
Visitors: 3982
The paper discusses the problems of implementing the Case-Based Reasoning (CBR) module that al-lows performing all stages of the case-based learning cycle (CBR-cycle) for distributed intelligent sys-tems. Nowadays, there is a steady trend towards widespread using of methods and tools for data mining (DM) for solving various applied problems. More and more large companies are using intelligent sys-tems and DM tools to improve their business efficiency and reduce costs. Due to developing Internet technologies and the availability of cloud computing, a promising direction in the field of artificial in-telligence (AI) is the creation of distributed intelligent systems (DIS). DIS systems are characterized by the distribution of computing and information resources, which increases adaptability, reliability, as well as the overall performance of the system due to the ability to simultaneously process large data sets. DIS systems consist of autonomous nodes (agents) that can act independently and exchange information with each other asynchronously. Since there are agents capa-ble of implementing certain intelligent functions, this is an indication of the close connection between DIS systems and multi-agent systems (MAS). The work focuses on one of the DM methods based on the use of previously accumulated experi-ence (cases). The indicated case method (CBR-method) allows solving a new problem using (adopting) the solution of a similar and already known problem. To solve data analysis problems based on cases, there is a modular case system (CBR-module) that implements the main stages of the CBR-cycle. The implemented system allows working with cases presented in a parametric and structured (based on on-tologies) form. The CBR-module is a web application implemented in the Python 3.7.5 programming language using the Flask web framework and the Owlready2 library to work with ontologies. The de-veloped CBR-module focuses on integrating into a DIS system to perform data mining based on cases. The implemented CBR-module has been tested on the example of solving the classification task us-ing data sets taken from the open repository of the University of California (UCI Machine Learning Re-pository).

12. Methods for accelerating the preparation and embedding of a digital watermark using mobile devices based on Arnold and wavelet transforms [№3 за 2021 год]
Authors: Zotin A.G., Proskurin A.V.
Visitors: 3811
In recent years, digital watermarking technology has become increasingly important due to the explo-sive growth of data transmitted through unprotected communication channels. Digital watermarks can reduce the amount of transmitted information and be used to protect images (hosts) from illegal use. For a more effective implementation of the latter task, various studies are being carried out in order to improve robustness, imperceptibility and security of the watermark. In most cases, this leads to an in-crease in computational costs, which makes it difficult to use digital watermarking in mobile devices. This work proposes several ways to reduce computational costs and computation time of digital wa-termarking methods based on Arnold and wavelet transforms. The first way consists in linear interpre-tation of digital watermark and a host, so it avoids the use of double cycles. The second way is to use lookup tables (LUT) to replace direct calculations. One of these tables allows performing the Arnold transform in certain time regardless of the number of iterations. Iterations for each block are deter-mined using hash code of the secret key and specially formed tables. The third way of digital water-marks embedding time reduction is multithreaded execution implemented using the OpenMP technolo-gy. In combination with linear interpretation, this results in accelerations of 1.90, 2.56 and 3.01 times for two, three and four threads, respectively.

13. Comparative analysis of video conferencing tools for distance learning [№3 за 2021 год]
Author: Sukhanov M.B.
Visitors: 3731
Suddenly appeared pandemic problem has led to the need to switch to distance learning and to choose video conferencing means for conducting lectures and practical classes remotely. Video conferencing software was chosen as the object of the research. The analysis of publications on the research topic has shown that nowadays it is difficult to find reasonable recommendations in the scientific literature on the choice of modern informatization tools for distance learning, and the prospects for using web and video conferencing platforms by both re-searchers and participants are poorly studied. The video conferencing software of foreign companies is very popular. The paper compares the functionality and features of video conferencing software. It considers the requirements for a computer and mobile devices, their technical characteristics are the most important for ensuring high-quality video conferencing. There is an example of studying the performance dynam-ics of the main computer resources during the Zoom video conference. The performance data is ob-tained using the “Task Manager” program, which is a part of the Windows 10 operating system. It is shown that video conferencing programs consume a lot of computer resources (CPU, RAM). The paper identifies the trends in using video conferencing software in Russian distance education – the transition to using Microsoft corporate solutions, the joint use of Office 365 and Microsoft Teams, and the widespread use of Zoom software. Since video recordings of lessons are intellectual property, import substitution of foreign video conferencing tools in the field of education is advisable. The advantages of such tools should be high reliability, security, assessment of the student satisfaction level, and a cognitive interface.

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