Institute Of Computer Science Research Articles

Wkład ośrodków statystycznych w Krakowie i we Wrocławiu w rozwój metod klasyfikacji i analizy danych

The year 2022 marked the 10th anniversary of the passing of Prof. Kazimierz Zając, the long-standing head of the Department of Statistics and later the director of the Institute of Statistics, Econometrics and Computer Science at Krakow University of Economics, while 2023 marked the 10th year of the passing of Prof. Zdzisław Hellwig, the long-standing head of the Department of Statistics and director of the Institute of Economic Cybernetics at Wroclaw University of Economics. Both professors were the scientific leaders of statistical centres at the above-mentioned universities. The aim of the article is to present the contribution of Polish statisticians to the development of the theoretical foundations and empirical research in the field of numerical taxonomy and methods of data classification and analysis. Particular emphasis is placed on the achievements of Professor Zając and Professor Hellwig and their students and associates. According to the authors of this work, recalling the achievements of these scholars is especially important as most commonly cited sources on data classification and analysis are mainly English-language.

К истории математического моделирования в Южном федеральном университете

The article is devoted to the history of mathematical modeling at Rostov State University (RSU), now Southern Federal University (SFU). The authors have been describing it since 1950. As elsewhere in the world, its begin-nings are associated with problems of mechanics. At the Rostov State University, its founders are considered to be I.I. Vorovich and N.N. Moiseev, future academicians of the Russian Academy of Sciences. The flourishing of work on mathematical modeling is associated with the opening of a computer center at the Rostov State University (1958), and then a research institute of mechanics and applied mathematics (1971), where a simulation model of the Sea of Azov was created, for which its developers were awarded the USSR State Prize. The article examines not only the history of mathematical modeling as a scientific direction, but also the history of its formation as an academic subject at the Faculty of Mechanics and Mathematics (now the I.I. Vorovich Institute of Mathematics, Mechanics and Computer Science of the SFedU).

A Modified Total Energy Control Scheme for Unmanned Aircraft

The paper focuses on safety and simplicity of unmanned aircraft longitudinal control and proposes a new combination of total energy control (TECS) and conventional control. The introduced new modified total energy control (TECSMOD) method applies IAS priority all the time. IAS is controlled through the elevator while the total energy of the system and so the altitude is maintained with throttle. Neither engine fault or stall detection nor switching logic is required while stall is prevented keeping the solution simple and safe. To prove the viability of the new concept it is compared to a conventional multiple zone PI controller and the TECS solution in simulation and real flight tests. First, the six degrees of freedom simulation model of the Sindy test UAV (developed and built in Institute for Computer Science and Control, HUN-REN, Hungary) is verified comparing its inputs and outputs to flight results. Then a simulation campaign is done for all three controllers with special test cases which can be critical according to the literature. Finally, real flight test comparison is done considering IAS and altitude tracking and engine fault handling. The new method was the best in IAS tracking with acceptable results in altitude tracking and successful stall prevention upon engine fault (without any fault detection or switching). Future improvements can be fine tuning for improved altitude tracking with the price of decreased IAS tracking performance and the introduction of a glideslope tracking mode for landing scenarios.

Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing Publishing.• Type of peer review: Double Anonymous• Conference submission management system: First round by email, Final round by Morressier• Number of submissions received: 31• Number of submissions sent for review: 31• Number of submissions accepted: 31• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 100• Average number of reviews per paper: 2• Total number of reviewers involved: 18• Contact person for queries: Name: Ahmed Haron Email: Info.vfc2022@gmail.com Affiliation: Cairo Higher Institute for Engineering, Computer Science and Management

Investigation of Cerebral Autoregulation Using Time-Frequency Transformations.

The authors carried out the study of the state of systemic and cerebral hemodynamics in normal conditions and in various neurosurgical pathologies using modern signal processing methods. The results characterize the condition for the mechanisms of cerebral circulation Institute of Computer Science and Control, Higher School of Cyber-Physical Systems and Control regulation, which allows for finding a solution to fundamental and specific clinical problems for the effective treatment of patients with various pathologies. The proposed method is based on the continuous wavelet transform of systemic arterial pressure and blood flow velocity signals in the middle cerebral artery recorded by non-invasive methods of photoplethysmography and transcranial doppler ultrasonography. The study of these signals in real-time in the frequency range of Mayer waves makes it possible to determine the cerebral autoregulation state in certain diseases before and after surgical interventions. The proposed method uses a cross-wavelet spectrum, which helps obtain wavelet coherence and a phase shift between the wavelet coefficients of systemic arterial pressure signals and blood flow velocity in the Mayer wave range. The obtained results enable comparing the proposed method with that based on the short-time Fourier transform. The comparison showed that the proposed method has higher sensitivity to changes in cerebral autoregulation and better localization of changes in time and frequency.

Use of Uncertain External Information in Statistical Estimation

Use of Uncertain External Information in Statistical Estimation by Sergey Tarima 1,* , Zhanna Zenkova 2 1 Medical College of Wisconsin, Division of Biostatistics, Institute for Health and Equity, Wauwatosa, Wisconsin, 53226, USA2 National Research Tomsk State University, Institute of Applied Mathematics and Computer Science, Tomsk, 634002, Russia * Author to whom correspondence should be

Fundamental Approach to University Education and Training of IT Professionals

The paper is devoted to education and training of professionals in the IT field in classical universities in the context of the implementation of the Federal Project “Human Resources for the Digital Economy” of the National Program “Digital Economy of the Russian Federation”. The general approach, goals and content of fundamental education and specialized training of Bachelors, Masters and PhD-holders to complex, innovative and research activities have been determined. The structure of Bachelor, Master and PhD programs of the Institute of Applied Mathematics and Computer Science of Tomsk State University modernized on the basis of the above approach, is presented. The paper pays special attention to the training of T-Shaped specialists in IT in classical universities, dwells on the fundamental education of IT specialists. The results of the coordination of programs with employers and students are given.

Support of individual educational trajectories based on the concept of explainable artificial intelligence

Introduction. Professional education in the context of individual educational trajectories (IET) meets the needs of both students themselves and the labour market due to the relevance of the content, flexibility of the educational process and learning technologies. However, in the context of digitalisation, IET support, including their planning and subsequent management of learning, entails the emergence of new requirements for information, analytical and methodological support of information systems designed to manage the educational process of the university. The problem of this study is determined by the contradiction between the intensive growth (natural for digitalisation) in the volume and variety of types of collected data, which can and should be used to support IET. In addition, there is also a lack of adequate analytical tools in educational information management systems.Aim. The present research aimed to study and test the digitalisation methodology for IET support, based on the application of the concept of explainable artificial intelligence for analysing student digital footprint data, the content of documents regulating the educational process, as well as labour market demands.Research methodology and methods. As a theoretical basis for the study, the authors relied on the principles of explainable artificial intelligence and their application to the interpretation of data from the educational process and the prediction of educational outcomes. The methods of intellectual analysis of texts in natural language were employed for preliminary processing of source documents. To predict educational outcomes, the authors used clustering, classification and regression models created through applying machine learning methods.Results. The authors developed and studied predictive models with the subsequent formation of recommendations for the tasks of choosing an educational programme by applicants, choosing an elective discipline, forming a team for a group project and employment in accordance with professional competencies. The developed computer program automatically generates objective and explainable recommendations based on expert knowledge and predicting results. The algorithm for constructing recommendations is divided into stages and provides for variability in decision making.Scientific novelty. The authors proposed a methodology for digital support of IET, corresponding to the principles of explainable artificial intelligence, i.e. machine learning models predict educational outcomes, and a special algorithm automatically generates personalised recommendations based on the results of the analysis of data on the educational process. The developed approach confirmed its effectiveness in testing on the example of bachelor’s and master’s degree programmes in the field of computer science, information technology and information security.Practical significance. A preliminary analysis of significant volumes of initial data made it possible to obtain objective information about the data quality, including the content and structure of documents presented in various university information systems. Based on the the oretical results of the research, the authors developed a recommendation system. It included special services for students, teaching staff, tutors, and administrators, providing visual and user-oriented predictive results and recommendations. Testing of services at the Institute of Mathematics and Computer Science of University of Tyumen confirmed the feasibility of developing the functionality of the university information systems in the direction of collecting and analysing data from a student’s digital footprint and the relevance of this analysis results both by subjects of the educational process and by the labour market.

The Development and Innovation of the First Supercomputer YH-1 in China: From the Perspective of Technology History

China’s first supercomputer capable of 100 million calculations per second was the YH-1, which was independently developed by the Institute of Computer Science at the National University of Defense Technology (NUDT) between 1978 and 1983. YH-1 played an important role in China’s national defense construction and national economic development. It made China one of the few countries in the world to successfully develop a supercomputer. Based on original archive documents, interviews with relevant personnel, and an analysis of the technological parameters of the supercomputers YH-1 in China and Cray-1 in the United States, this paper reviews in detail the historic process of the development of YH-1, analyzing its innovation and summarizing the experience and lessons learned from it. This analysis is significant for current military-civilian integration, and the commercialization of university research findings in China.

ФОРМИРОВАНИЕ У БУДУЩИХ УЧИТЕЛЕЙ МАТЕМАТИКИ ПРОФЕССИОНАЛЬНЫХ УМЕНИЙ РАБОТЫ В СИСТЕМЕ ДОПОЛНИТЕЛЬНОГО МАТЕМАТИЧЕСКОГО ОБРАЗОВАНИЯ

The article is devoted to the peculiarities and prospects of practical training of future mathematics teachers to carry out cultural and educational activities in mathematics in educational institutions, including in the system of additional mathematical education. The experience of organizing educational and industrial practices of students of the directions 44.03.01 Pedagogical education, profile «Mathematics» and 44.03.05 Pedagogical education, profile «Mathematics and Computer Science», studying at the Institute of Mathematics, Mechanics and Computer Science named after I.I. is given. Vorovich of the Southern Federal University of Rostov-on-Don.
 The article describes the main activities of students during academic and industrial practices: the study of the specific content of additional mathematical education, methods and means of organizing training; the development of didactic materials for the implementation of classes in the field of additional mathematical education; the implementation of career guidance in schools of Rostov-on-Don; conducting extracurricular activities in mathematics in educational institutions.

CATS: Customizable Abstractive Topic-based Summarization

Neural sequence-to-sequence models are the state-of-the-art approach used in abstractive summarization of textual documents, useful for producing condensed versions of source text narratives without being restricted to using only words from the original text. Despite the advances in abstractive summarization, custom generation of summaries (e.g., towards a user’s preference) remains unexplored. In this article, we present CATS, an abstractive neural summarization model that summarizes content in a sequence-to-sequence fashion while also introducing a new mechanism to control the underlying latent topic distribution of the produced summaries. We empirically illustrate the efficacy of our model in producing customized summaries and present findings that facilitate the design of such systems. We use the well-known CNN/DailyMail dataset to evaluate our model. Furthermore, we present a transfer-learning method and demonstrate the effectiveness of our approach in a low resource setting, i.e., abstractive summarization of meetings minutes, where combining the main available meetings’ transcripts datasets, AMI and International Computer Science Institute(ICSI) , results in merely a few hundred training documents.

Making the Right Move to Senior Researcher

I have been working on research in data management for the last 40 years. I like my job and my research institution (Inria, the French national research institute for computer science), which have offered me great opportunities to learn a lot, do good work, get to know smart and nice people and overall feel useful. However, since the early days of my mid-career, the research environment, including academia and industry, has certainly become more complex, making the move from junior (or pre-tenure) researcher to senior researcher quite challenging. Based on my experience, I review some of the main questions and challenges and give some hints on how to deal with them. I'll sometimes use stories and anecdotes to illustrate the point.

CAPITALISATION ERRORS IN WRITTEN WORKS OF LEARNERS OF LATVIAN AS A FOREIGN LANGUAGE

Capitalisation in writing is usually determined by tradition. Different written languages can have their own grammatical, conceptual or stylistic capitalisation rules. Orthographies exist which do not have the division into capital and small letters. The aim of the article is to find out what problems with capitalisation foreign students in Latvian higher education institutions have during the acquisition of writing skills in Latvian as a foreign language. The research source are the essays written by learners of the Latvian language (foreign students studying in Latvian higher education institutions): the data of the Latvian language learner text corpus being created in the Institute of Mathematics and Computer Science of the University of Latvia were used. The requirements for the acquisition of capitalisation in the context of language learner competences are analysed in the study; the most typical capitalisation errors and possible reasons for them are analysed; and the author’s practical experience teaching the Latvian language to foreign students is revealed.

Selected Works From International Workshop on Biometrics and Forensics 2020

The 8TH edition of the International Workshop on Biometrics and Forensics (IWBF 2020) was held online, and organized remotely from Porto, Portugal, on 29 and 30 April 2020. The event, organized by the Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Porto (Portugal), the Norwegian University of Science and Technology (NTNU, Norway), and the European Association of Biometrics (EAB), received technical co-sponsorship from IEEE-Biometrics Council and IAPR—Technical Committee on Biometrics (TC4).

Individual psychological peculiarities of the inconsistency between cognitive and socio-psychological development of students

The subject of this article is the search for individual psychological peculiarities of the inconsistency between cognitive and socio-psychological development of students. The relevance of this topic is substantiated by the theoretical diversity of research on the inconsistency in psychology and the need for the development of socio-cultural and cognitive skills in the educational process. A hypothesis is advanced that the inconsistency between the processes of cognitive and socio-personal development would be variable, determining the individual psychological methods of its resolution. The goal of this research lies in conjoint analysis of cognitive and personal characteristics for assessing the inconsistency of students’ development. The author applies the correlational research design, which is defined by the goal of research and specificity of the sampling. The survey involved 34 students (18 boys and 16 girls) of the Institute of Mathematics and Computer Science of the Ural Federal University aged 18-22 (M=18.3 3 SD=0.79). The article employs the psychodiagnostic questionnaires: Aizenka EPI test; short version of the “Dark Triad of Personality” scale adapted by M. S. Egorova and others; characterological questionnaire by G. Schmishek, “Rational-experiential” questionnaire by S. Epstein adapted by T. V. Kornilova, A. Y. Razvalyaeva; Mann-Whitney U-test, Spearman's rank correlation coefficient. The following gender differences are revealed: for the female students, cognitive and personal characteristics are generally more interrelated, while the pronounced affective personality traits testify to the possible tension in social communication; male students demonstrated greater proneness to rational processing of information and formation of engineering skills, while weakness of integration of the inner and outer Self, which may increase narcissistic traits, reduce self-criticism, and cause difficulties in establishment and maintenance of social contacts. The acquired results empirically  prove the importance of socio-psychological competence, and allow differentiating the technologies of its formation in the educational process.

First Results of a Survey on Manufacturing of the Future

Today’s production methods are challenged by changing paradigms from a static constraint mass production and mass customization to continuing personalization and regionalization of product, production and markets. It is yet unclear what future production systems will be the most appropriate, how they will look like and how the current, uncertain trends in manufacturing can be tackled most effectively. In this paper, first results from a comprehensive questionnaire on »The Intelligent Production of the Future«, performed by a consortium of researchers from the Institute for Computer Science and Control (SZTAKI) and the Fraunhofer-Institute for Manufacturing Engineering and Automation IPA are outlined. During this survey, stakeholders and peers from more than 70 companies and research institutions in Germany, Austria and Hungary have been asked to share their impressions, describe their opinions and rate central statements on future production systems, methodologies and trends. The paper outlines the most important topics of future production systems and lessons learned during the evaluation of the survey.

Problems and Results of Forced Transition to Distance Learning of Students and Teachers (Institute of Mathematics and Computer Science, Moscow Pedagogical State University)

Problems and Results of Forced Transition to Distance Learning of Students and Teachers (Institute of Mathematics and Computer Science, Moscow Pedagogical State University)

Experimental Verification of the Neural Network Predicting Procedure Applied for UTC(PL)

The article presents and summarizes the research results of the UTC-UTC(PL) differences predicting procedure for the Polish Time Scale UTC(PL) developed at the Institute of Metrology, Electronics and Computer Science of the University of Zielona Gora. The research has been conducted in close cooperation with the Time and Frequency Laboratory of Central Office of Measures, responsible for the realization of the UTC(PL). The planned experiment covered a 50-month period, in which the UTC(PL) timescale has been carried out using, as a master clock, atomic clocks with different properties: commercial cesium atomic clock 5071A Opt. 001 (first case) and VCH-1003M hydrogen maser (second and third cases). In case of the developed predicting procedure by means of group method of data handling (GMDH)-type neural network (NN), the transitional period (second case) in which the master clock had been replaced by the new clock, is also very important. For GMDH-type NN, input data as a TS1 and TS2 time series have been prepared, based on the already-known differences of UTC(PL) from UTC and UTC rapid timescales and on determined differences between UTC(PL) and the master clock steering the UTC(PL). The method of preparing TS1 and TS2 time series is an important part of the developed procedure for predicting UTC(PL) differences from UTC, before they will be calculated and published by fr. Bureau International des Poids et Mesures (BIPM). The obtained research results confirmed that the developed predicting procedure by means of GMDH-type NN ensures a proper quality of maintaining the national timescale. The best quality of UTC(PL) predicting has been achieved for the third case, both for data prepared according to the TS1 and TS2 time series. This is confirmed by the calculated values of the prediction quality measures and the Modified Allan deviation. On the other hand, the second case confirmed the possibility of using the proprietary development of the TS2 time series to predict UTC-UTC(k) differences. This time series is a very good alternative for the TS1 time series, when the amount of data in this series is insufficient due to replacement of the clock or its failure.

Diagnostics of professional competence of IT students based on digital footprint data

The article goal is to demonstrate the possibilities of the approach to diagnosing the level of IT graduates’ professional competence, based on the analysis of the student’s digital footprint and the content of the corresponding educational program. We describe methods for extracting student professional level indicators from digital footprint text data — courses’ descriptions and graduation qualification works. We show methods of comparing these indicators with the formalized requirements of employers, reflected in the texts of vacancies in the field of information technology. The proposed approach was applied at the Institute of Mathematics and Computer Science of the University of Tyumen. We performed diagnostics using a data set that included texts of courses’ descriptions for IT areas of undergraduate studies, 542 graduation qualification works in these areas, 879 descriptions of job requirements and information on graduate employment. The presented approach allows us to evaluate the relevance of the educational program as a whole and the level of professional competence of each student based on objective data. The results were used to update the content of some major courses and to include new elective courses in the curriculum.

Peer review declaration

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.□ Type of peer review: Single-blind / Double-blind / Triple-blind / Open / Other (please describe) Double-blindThe conference Program Committee chose 4 reviewers. The papers were distributed so that each was reviewed by two reviewers.List of reviewers:✓ Fedchenko L.M. – Grand PhD in geographical sciences, professor, research advisor, High-Mountain Geophysical Institute;✓ Senov H. M. – Grand PhD in physico-mathematical sciences, professor, Institute of Computer Science, Electronics and Robotics;✓ Kalov H.M. - Grand PhD in physico-mathematical sciences, professor, research advisor, High-Mountain Geophysical Institute;✓ Barekova M. V. – PhD in physico-mathematical sciences, scientific secretary, High-Mountain Geophysical Institute. Conference submission management system: Conference site:http://vgistikhiya.ru/index.php/konferentsiiConference secretary mail: sozaeva.lezhinka@yandex.ru□ Number of submissions received: 18 □ Number of submissions sent for review: 18 □ Number of submissions accepted:16 □ Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 88,88 □ Average number of reviews per paper: 2 □ Total number of reviewers involved:4 □ Any additional info on review process: □ Contact person for queries: Sozaeva Lezhinka Tanashevna, +7(928) 723 20 08, sozaeva.lezhinka@yandex.ru