International Workshop Advances & Challenges in Computing (A2C)
Past workshops
Date: 28 June 2023 (Wednesday)
Date: 20 December 2023 (Wednesday)
Place: online (a link will be put in invitation)
Time: 18:00-20:00 (East European time, Kyiv)
AGENDA:
1. Speaker: Yuliia Tarasich
((Ph.D., Information Technology) Doctoral Student, V.M.Glushkov Institute of Cybernetics of the NAS of Ukraine)
E-mail: yutarasich@gmail.com
Topic: Neuro-symbolic approach in the cell-virus interactions modelling
Presentation in Ukrainian
2. Speaker: Dmytro Chumachenko
(PhD, Associate Professor, Associate Professor of Mathematical Modeling and Artificial Intelligence department of National Aerospace University “Kharkiv Aviation Institute”, Affiliated Researcher of Ubiquitous Health Technologies Lab of University of Waterloo)
E-mail: d.chumachenko@khai.edu
Topic: Hybrid approach for epidemic process simulation Presentation in Ukrainian
3. Information about research projects and conferences: Anatoliy Sachenko
Doctor of Technical Sciences, Professor, scientific advisor of Research Institute for Intelligent Computer Systems.
E-mail: as@wunu.edu.ua
Date: 28 June 2023 (Wednesday)
Place: online (a link will be put in invitation)
Time: 18:00-20:00 (East European time, Kyiv)
AGENDA:
- Speaker: Khrystyna Lipianina-Honcharenko
(Associate professor, Ph.D. in information technologies
Department for Information Computer Systems and Control,
West Ukrainian National University)
E-mail: kh.lipianina@wunu.edu.ua
Topic: Intelligent Methods for Data Analysis in the Infrastructure of a Smart City
Presentation in Ukrainian
Abstract: “Intelligent Approaches for Enhancing Social Life in a City” explores various aspects of using intelligent approaches to improve social life in a city. It encompasses research and development in the fields of machine learning, virtual companies, advertising strategies, and more. The main topics covered include assessing the quality of life in Ukrainian cities during wartime, intelligent advertising strategies for products in the online market of a smart city, intelligent management of virtual companies in a smart city, evaluating investment risks in a virtual IT company using machine learning, business process management in a virtual enterprise using augmented reality, using machine learning for real estate value prediction in a smart city, and utilizing virtual reality to enhance social life in a smart city.
Resume: Khrystyna Lipianina-Honcharenko is a researcher and scientist with over ten years of experience in the field of data analysis, machine learning, simulation, and forecasting of socio-economic processes. She was born in 1990 in Ternopil, Ukraine, and has always shown a passion for research and technology throughout her career. With 13 years of overall research experience, Khrystyna has developed a diverse skill set and deep understanding of information technology. She holds a PhD degree in Technical Sciences, specializing in Information Technology, and has been awarded the academic title of Associate Professor. Her research interests primarily revolve around data analysis, machine learning, and forecasting socio-economic phenomena. In terms of her professional experience, Khrystyna has held various teaching positions in prestigious institutions such as Ternopil National Economic University and West Ukrainian National University. She has taught a wide range of subjects, including machine learning, cloud technologies, data mining, and modern information technologies. Her passion for education and research is evident in her current role as an Associate Professor at West Ukrainian National University. Khrystyna’s academic journey also includes postdoctoral research in the field of computer science, with a focus on intelligent information technologies for data analysis in “smart cities” during crisis situations. She is scheduled to defend her dissertation in the summer of 2024.
- Speaker: Valerii Zavgorodnii
(Prof., Dr. Sc.,
Head of the Department of Information Technologies,
State University of Infrastructure and Technologies, Kyiv)
E-mail: zavgorodniivalerii@gmail.com
Topic: Distance learning system organization on the basis of formation of a uniform information space
Presentation in Ukrainian
Abstract: Models and methods of identification of input objects based on the formation of a single information space in order to increase the effectiveness of the distance learning system are proposed. The investigated problem is that heterogeneous data sources are used to obtain informational features of objects, which are characterized by different degrees of accuracy and different formats of data presentation. At the same time, the organization of a distance learning system based on the formation of a single information space requires the unification of data obtained from heterogeneous sources and the implementation of a mechanism for converting such formats. There is a contradiction between the heterogeneous nature of features of objects and the requirement of a unified presentation of data. At the same time, the same object, the parameters of which are obtained from different sensors, must be uniquely identified.
Resume: In 2004, Valerii Zavgorodnii graduated with honour from Dniprovsky State Technical University. In 2013, he defended the Candidate Dissertation. In 2015, he was awarded the academic title of Assosiate Professor. In 2021, he defended the Doctoral Thesis. In 2022, he was awarded the academic title of Professor. His major fields of research are information technologies, databases, decision support systems, introduction of information and communication technology in the educational process.
In 2007-2016, he worked at Dniprovsky State Technical University in positions assistant, senior lecturer, associate professor of the Department of Systems Software. Since 2016, he has been working at State University of Infrastructure and Technologies. In 2016-2020, he was a Deputy Head of the Department of Information Technologies. Since 2020, he has been a Head of the Department of Information Technologies.
He has more than 150 scientific publications, including 60 scientific publications in specialized publications of Ukraine and more than 20 publications in foreign scientific publications. International activities:
- Participant of the academic cooperation program «International Research Network for study and development of new tools and methods for advanced pedagogical science in the field of ICT instruments, e-learning and intercultural competences». Project financed by the European Commission under the 7th Framework Programme, within the Marie Curie Actions International Research Staff Exchange Scheme (№PIRSES-GA-2013-612536).
- Participant of the international project “Academic counteraction to hybrid threats” (WARN) 610133-EPP-1-2019-1-FI-EPPKA2-CBHE-JP
3. Information about research projects and conferences: Anatoliy Sachenko
Doctor of Technical Sciences, Professor, scientific advisor of Research Institute for Intelligent Computer Systems.
E-mail: as@wunu.edu.ua
A regular meeting
Date: 26 April 2023 (Wednesday)
Place: online (a link will be put in invitation)
Time: 18:00-20:00 (East European time, Kyiv)
AGENDA:
- Speaker: Sergiy Gnatyuk
Prof., DSc.
Dean of the Faculty of Computer Science and Technology,
National Aviation University;
Lead Researcher of the State Scientific and Research Institute of Cybersecurity Technologies and Information Protection;
President of Scientific Cybersecurity Association of Ukraine.
E-mail: s.gnatyuk@nau.edu.ua
Topic: QKD-based security: advanced technologies and applications
Abstract: The report presents alternative directions for the cryptographic protection methods development that will be secure in the post-quantum period. In particular, the main attention is paid to the quantum cryptography technologies – quantum key distribution (QKD) and quantum direct secure communication. A generalized classification of quantum methods and information security protocols is given. Cases where the implementation of quantum algorithms can be a real threat to traditional cryptographic systems are considered. The results of the analysis of modern commercial quantum cryptographic systems used for key distribution, secure communication, random number generation, network security, virtual encryption, etc. are displayed. An overview of the latest projects related to the development and implementation of QKD and other quantum technologies in cellular communication systems, data centers, telecommunication systems and networks, satellite technologies, etc. is presented. In addition, the main scientific results of the speaker and his research group in the field of quantum cryptography and quantum communication are presented.
Resume: Sergiy Gnatyuk holds PhD (in 2011) and DSc (in 2017) in Cybersecurity, he is Professor in Computer Science (from 2021). Sergiy is Dean of the Faculty of Computer Science and Technology at National Aviation University, Professor of Computer Information Technology Academic Department as well as Scientific Advisor of the NAU Cybersecurity R&D Lab
Also, Sergiy is a cybersecurity expert and consultant for state and private Ukrainian and international organizations as well as he is the President of Scientific Cybersecurity Association of Ukraine Prof. Gnatyuk is a speaker and organizer of many international cybersecurity events, coordinator of state and international projects as well as the author (co-author) of many books, patents and papers. He is IEEE Member (from 2010), Scientific Adviser of Engineering Academy of Ukraine (from 2013), Member of Dissertation Council D 26.062.01 in NAU (Information technology) from 2019 (Vice-Chair from 2022), Member of PhD Dissertation Council in Satbayev University and Al-Farabi Kazakh National University (from 2019), Chairman in Young Scientist Association of National Aviation University (2015-2018) and others.
His research interests include cybersecurity, AI/ML-based security, cryptography, QKD, 5G / 6G security, incident response, critical information infrastructure protection and others.
Author profiles:
- Scopus https://www.scopus.com/authid/detail.uri?authorId=36184129600
- Google Scholar
https://scholar.google.com/citations?user=H8oHKbYAAAAJ&hl=en
Academic awards
- Rector of National Aviation University Acknowledgement, 2011 and 2021
- ECAC Executive Secretary Acknowledgement, 2011
- Letter of Recognition from Rector of National Aviation University, 2012
- Entry on Honors Board of National Aviation University, 2013
- Scholarship of Cabinet of Ministers of Ukraine for Young Scientists, 2016-2018
- Winner of State Research Grant for Young Scientists, 2017, 2019 and 2021
- Winner of State Research Grant, 2021
- Scholarship of Verkhovna Rada (Parliament) of Ukraine for the Most Talented Young Scientists, 2019 and 2020
- Winner of Research Grant for Young Scientists of National Academy of Sciences of Ukraine State, 2020
- Letter of Recognition from the Head of the State Service of Special Communications and Information Protection of Ukraine, 2021
- Winner of Young Scientist of the year in Ukraine (Section IT & Cybersecurity), 2022
- Minister of Education & Science Acknowledgement, 2023
- Information about research projects and conferences: Anatoliy Sachenko
Doctor of Technical Sciences, Professor, scientific advisor of Research Institute for Intelligent Computer Systems.
E-mail: as@wunu.edu.ua
A regular meeting
Date: 28 December 2022 (Wednesday)
Place: online (a link will be put in invitation)
Time: 18:00-20:00 (East European time, Kyiv)
AGENDA:
- Speaker: Roman Odarchenko
(Prof., Dr. Sc.)
Head of the department of telecommunication and radio electronic systems,
National aviation university, Kyiv, Ukraine
Senior researcher in Bundleslab KFT, Budapest, Hungary
Chief executive officer in Scientific cyber security association of Ukraine
E-mail: odarchenko.r.s@ukr.net
Topic: Evaluation and improvement of QoE and QoS parameters in commercial 5G networks: 5G-TOURS approach
Abstract: The 5G-TOURS project aimed at deploying full end-to-end 5G trials involving real end-users and vertical operational services in three different European cities (Turin, Rennes, and Athens). In the 5G-TOURS “ecosystem” realised in the three cities, 13 use cases related with the themes of the touristic city (5 use cases), the safe city (4 use cases) and the mobility-efficient city (4 use cases) have been deployed. The ultimate goal of this approach was to trial the use cases in real environments to continuously collecting network, service and vertical KPIs and then to evaluate them against a set of predefined verticaloriented criteria.
The results from the application of such QoS/QoE estimation methodology on the use cases are presented. By following the 5G-TOURS QoS/QoE methodology, the level of satisfaction of end-users and verticals’ players in the use cases were measured and evaluated. This evaluation included users’ QoE as well as the feedback from the vertical players on how the technology provided can improve their business operations. The final 5G-TOURS evaluation methodology was followed in the trial execution of all use cases. Initially, during the actual trial execution, both the QoS metrics, automatically obtained from the infrastructure, and the QoE metrics (and vertical satisfaction), were collected using appropriate questionnaires. Then, all the collected metrics were analysed and the KPIs calculated and validated against the predefined targets. In addition, insights were provided in the case of successful validation results, while a justification in case of not fulfilled KPIs. Besides, in selected use cases, models for QoS/QoE correlation were created by using correlation-regression analysis.
Resume: In 2010, Roman Odarchenko graduated with honor from National aviation university. In 2013, he defended the Candidate Thesis and in 2019 he defended the Doctoral Thesis. In 2021, he was awarded the academic title of Professor.
Since 2010, he has been working at National aviation university. Now, Roman Odarchenko works as the head of the department of telecommunication and radio electronic systems of the National Aviation University (http://tks.nau.edu.ua/vikladatskij-sklad/odarchenko-r-s/).
He has more than 250 scientific publications, including 14 inventions and 1 monograph. Research interests include: cellular networks, IoT networks, cybersecurity.
For the last 5 years Roman Odarchenko was the scientific supervisor (co-supervisor) of the following international and domestic research projects related to the subject of this project:
- project of young scientists of the Ministry of Education and Science “Quantum-cryptographic methods to ensure the confidentiality of the critical information infrastructure of the state” (2017-2019);
- project of young scientists of the Ministry of Education and Science “Methods of building secure networks of mobile government radio communication based on 5G networks in Ukraine” (2020-2021);
- scientific projects of the State Special Communications, the code “Dolphin” (2019-2020) and the code “Platform” (2016);
- scientific project of the National Scientific Fund of the Republic of Georgia named after Shota Rustaveli “Development of a platform for cybersecurity of 5G cellular networks”, 2021: (https://rustaveli.org.ge/res/docs/76fbfd85e10d418476f404353490066298836263.pdf).
Also Roman Odarchenko participated in three research projects under the Horizon 2020 program (5G-Xcast (https://5g-xcast.eu/), 5G-TOURS (http://5gtours.eu/), 5GASP(https://5gasp.eu/)).
- Information about research projects and conferences: Anatoliy Sachenko
Doctor of Technical Sciences, Professor, scientific advisor of Research Institute for Intelligent Computer Systems.
E-mail: as@wunu.edu.ua
A regular meeting
Date: 28 September 2022 (Wednesday)
Place: online (a link will be put in invitation)
Time: 18:00-20:00 (East European time, Kyiv)
AGENDA:
Speaker: Vasyl Sheketa
(Prof., Dr. Sc. (Doctor of Sciences in Technical Sciences)
Head of the Department of Software Engineering
Ivano-Frankivsk National Technical University of Oil and Gas
E-mail: vasylsheketa@gmail.com
Topic: Intelligent Decision Support System when Controlling Drilling
(Presentation in Ukrainian)
Abstract: The development of the oil and gas industry has always relied on industrial data to conduct production activities. This branch of industry is one of the few that first introduced the use of low-level data transmitters. Oil and gas companies have long been collecting data from their oil and gas wells to monitor the progress of relevant technological operations and to model the life cycle of relevant industrial facilities. Today, oil and gas companies collect various types of data at a fast pace and in huge volumes. This includes drilling and production data, GPS and spatial data, seismic data, general industrial data, weather information (especially for offshore drilling), and event logging data (field development histories). Much of this data is unstructured or loosely structured, which raises relevant questions about the storage, integration and access to such data using traditional and emerging technologies of databases, data banks, data warehouses, knowledge bases and knowledge oriented technologies in general.
Resume: Vasyl Stefanyk Precarpathian National University, Faculty of Physics and Mathematics, 1995, specialty “Mathematics”.
Assistant of the department of applied mathematics, NUNG, 1995–1999.
- Degree: phD. Specialty: Technical sciences. 05.13.06 – Information technologies City: Kherson. Institution: Kherson State Technical University
Associate Professor of the Department of Applied Mathematics, NUNG, 1999–2004.
Associate Professor of the department of software of automated systems of NUNG since 2004.
- Degree: Doctor. Specialty: Technical sciences. 05.13.06 – Information technologies City: Kyiv. Institution: Institute of Problems of Mathematical Machines and Systems (Kyiv)
Head of the Department of Software Engineering since 2018.
- Speaker: Oksana Kyrychenko
Assistant Professor,
Department of Mathematical Problems of Control and Cybernetics,
Yuriy Fedkovych Chernivtsi National University
E-mail: o.kyrychenko@chnu.edu.ua
Topic: Statistical-clustering analysis of information in complex networks.
Presentation in Ukrainian.
Abstract: The research of statistical characteristics of complex networks e.g. WWW is proposed. We have developed application which was used for gathering statistical information of web pages. Several zones within the Ukrainian, Israeli and Polish Domains were researched. Comparison of statistical characteristics of researched domains shows that they are fully developed structures and meet the modern trends of the Internet. It is shown that the properties of an undirected graph depend on the subnets of input and output connections. The research of the cluster structure of several zones of the web space on the basis of the previously collected statistical data is performed. The efficiency and visibility of the РІС clustering algorithm (Рower iteration clustering) is demonstrated. The results of finding the optimal number of clusters are performed by two methods: the Elbow Method and the k-Core decomposition method. A new method of finding the optimal number of clusters and cluster centers is also proposed. New algorithm is based on the distribution of eigenvalues of the stochastic matrix, which describes the process of Markov transitions in the system. The result of all conducted research is information technology, with the help of which statistical and cluster analysis of information in complex networks is done.
Resume: In 1996, Oksana Kyrychenko graduated from Yuriy Fedkovych Chernivtsi State University (Qualification: Mathematician. Teacher). In 2001 – 2016, she worked as the Laboratory Chief Manager of the Department of Mathematical Problems of Management and Cybernetics. Since 2016, she has been working as an Assistant Professor. In 2017 – 2022, she studied at a graduate school in the specialty 121 – Software Engineering. Her major fields of research are complex networks, statistical characteristics of complex networks, clustering data. She has 20 scientific publications.
- Information about research projects and conferences: Anatoliy Sachenko
Doctor of Technical Sciences, Professor, scientific advisor of Research Institute for Intelligent Computer Systems.
E-mail: as@wunu.edu.ua
A regular meeting
Date: 28 December 2021 (Tuesday)
Place: online (a link will be put in invitation)
Time: 18:00-20:00 (East European time, Kyiv)
AGENDA:
- Speaker: Kyrylo Malakhov
Master’s degree in IT,
Scientific associate of the Microprocessors technology Department,
V.M. Glushkov Institute of Cybernetics,
The National Academy of Sciences of Ukraine
E-mail: malakhovks@nas.gov.ua
https://orcid.org/0000-0003-3223-9844
Topic: Deep learning and inductive inference technologies composition for the development of ontology-related systems.
Abstract: The workshop called “Deep learning and inductive inference technologies composition for the development of ontology-related systems” is dedicated to a new technique of semantic language modeling for ontology-related systems development. Our method relies on the composition of deep learning technologies (using the revised technique for the distributional semantic modeling – word embeddings applying the ontology-related approach) and inductive inference (using the growing pyramidal networks). Also, the semantic maps of relations between words can be represented as a graph using Vec2graph – a Python library for visualizing word embeddings (term embeddings in our case) as dynamic and interactive graphs. The Vec2graph library coupled with term embeddings will not only improve accuracy in solving standard NLP tasks but also update the conventional concept of automated ontology development.
Resume:
In 2010, Kyrylo Malakhov graduated Master’s degree from Luhansk Taras Shevchenko National University Specialty “Computer science”, qualified as the software engineer, teacher of computer science.
Since 2013, he has been working at V.M.Glushkov Institute of Cybernetic of National Academy of Sciences of Ukraine (InCyb). In 2013-2020, he was а Junior researcher; since 2020 he has been Researcher at at InCyb. He has more than 49 scientific publications.
Research interests include Data Mining and Knowledge Discovery, Knowledge Representation and Management, Logical Inference, Semantic Web, Computational linguistics (Natural language processing, Natural language understanding, Natural language generation),
2. Speaker: Vitalii Velychko
Doctor of engineering science, associated professor,
Senior researcher of the Microprocessors technology Department,
V.M. Glushkov Institute of Cybernetics,
The National Academy of Sciences of Ukraine
E-mail: aduisukr@gmail.com
https://orcid.org/0000-0002-7155-9202
Topic: Deep learning and inductive inference technologies composition for the development of ontology-related systems.
Abstract: The workshop called “Deep learning and inductive inference technologies composition for the development of ontology-related systems” is dedicated to a new technique of semantic language modeling for ontology-related systems development. Our method relies on the composition of deep learning technologies (using the revised technique for the distributional semantic modeling – word embeddings applying the ontology-related approach) and inductive inference (using the growing pyramidal networks). Also, the semantic maps of relations between words can be represented as a graph using Vec2graph – a Python library for visualizing word embeddings (term embeddings in our case) as dynamic and interactive graphs. The Vec2graph library coupled with term embeddings will not only improve accuracy in solving standard NLP tasks but also update the conventional concept of automated ontology development.
Resume:
In 1985, Vitalii Velychko graduated with honour from Kyiv institute of civil aviation engineers. In 2004 he defended the PhD Thesis in Automated control system and advanced information technology, in 2021 he defended the Doctoral Thesis. In 2007 he was awarded the academic title of associate professor. Since 1995, he has been working at Higher educational institution “KROK” University, Kyiv, Ukraine. n 1995 – 2007, he was an assistant professor; in 2007-2012, he was a visiting associate professor. Since 2007, he has been working at V.M.Glushkov Institute of Cybernetic of National Academy of Sciences of Ukraine as Senior Researcher. He has more than 100 scientific publications, including 7 monographs. Main scientific interests include Data Mining and Knowledge Discovery, Natural Language Text Processing, Knowledge Representation and Management, Ontology Engineering, E-learning, Healthcare informatics, medical cybernetics, Logical Inference, Neural and Growing Networks. He is a member of the Association of Developers and Users of Intelligent Systems (Ukraine); ITHEA International Scientific Society (Bulgaria); а member of 2 editorial boards.
- Speaker: Vladik Kreinovich
Professor, Doctor
Department of Computer Science
University of Texas at El Paso
E-mail: vladik@utep.edu
Topic: Fourier Transform and Other Quadratic Problems under Interval Uncertainty
Presentation in English
Abstract: Computers are used to estimate the current values of physical quantities and to predict their future values – e.g., to predict tomorrow’s temperature. The inputs x1,…, xn for such data processing come from measurements (or from expert estimates). Both measurements and expert estimates are not absolutely accurate: measurement results Xi are, in general, somewhat different from the actual (unknown) values xi of the corresponding quantities. Because of these differences Xi — xi (called “measurement errors”), the result Y = f(X1,…,Xn) of data processing is also somewhat different from the actual value of the desired quantity y – at least from the value y = f(x1,…,xn) that we would have obtained if we knew the exact values xi of the inputs.
In many practical situations, the only information that we have about measurement uncertainty is the upper bound Di on the absolute value of each measurement error. In such situations, if the measurement result is Xi, then all we know about the actual value xi of the corresponding quantity is that this value is in the interval [Xi – Di, Xi + Di]. Under such interval uncertainty, it is desirable to know the range of possible value of y.
In general, computing such a range is NP-hard already for quadratic functions f(x1,…,xn). Recently, a feasible algorithm was proposed for a practically important quadratic problem – of estimating the absolute value (modulus) of Fourier coefficients. In this talk, we show that this feasible algorithm can be extended to a reasonable general class of quadratic problems.
Resume: Vladik Kreinovich is Professor of Computer Science at the University of Texas at El Paso. His main interests are representation and processing of uncertainty, especially interval computations and intelligent control. He has published nine books, 34 edited books, and more than 1,700 papers.
Vladik is Vice President of the International Fuzzy Systems Association (IFSA), Vice President of the European Society for Fuzzy Logic and Technology (EUSFLAT), Fellow of International Fuzzy Systems Association (IFSA), Fellow of Mexican Society for Artificial Intelligence (SMIA), Fellow of the Russian Association for Fuzzy Systems and Soft Computing. He is Treasurer of IEEE Systems, Man, and Cybernetics Society.
- Information about research projects and conferences: Anatoliy Sachenko
Doctor of Technical Sciences, Professor, scientific advisor of Research Institute for Intelligent Computer Systems.
E-mail: as@wunu.edu.ua
A regular meeting
Date: 20 October 2021 (Wednesday)
Place: online (a link will be put in invitation)
Time: 17:00-19:00 (East European time, Kyiv)
AGENDA:
- Speaker: Yelyzaveta Hnatchuk
PhD, Associate Professor
Computer Engineering & Information Systems Department
Khmelnytskyi National University
E-mail: liza_veta@ukr.net
Topic: Intelligent Information Technology for Supporting the Medical Decision-Making Considering the Legal Basis
Abstract: The decision support system (DSS) and information technology (IT) in the field of medical law are designed to provide the possibility of free and automated verification of all significant conditions of the contract and provide recommendations for the conclusion of the contract or not. Modern decisions for support the adoption of medical decisions on legal basis have shown that none of the known decisions does meet all the necessary criteria in the complex. Therefore, an urgent problem for Ukraine is the development and implementation of intelligent information technology to support medical decision-making, taking into account the legal basis, which is the purpose of this study. The proposed intelligent information technology to support medical decision-making based on legal basis provides support for decision-making on the possibility of using reproductive technologies (the possibility of surrogacy and/or in vitro fertilization), the possibility of donation and transplantation, the possibility of concluding contracts for therapeutic services, contracts for dental services and general contracts for medical services. In addition, intelligent information technology to support medical decision-making based on the legal basis automates the semantic parsing of contracts and draws conclusions about the possibility or impossibility of concluding a contract, as well as provides a request stating the reasons for impossibility to conclude a contract (for example, indicating missing essential conditions), if it was concluded that such a contract cannot be concluded.
Resume: In 2003, Yelyzaveta Hnatchuk graduated with honour from Khmelnitskyi National University. In 2008, she defended the PhD Thesis. Since 2003, she has been working at Khmelnitskyi National University. She has more than 50 scientific publications. Research interests include hybrid systems of computational intelligence: adaptive, neuro-, fuzzy-, real-time systems, including problems connected with control, identification, and forecasting, diagnostics, fault detection in technical and medical objects. She is the IntelITSIS workshops organizing committee member, member of 1 editorial board.
- Speaker: Eduard Manziuk
(PhD, Khmelnytskyi National University, Ukraine)
ORCID ID: https://orcid.org/0000-0002-7310-2126
E-mail: eduard.em.km@gmail.com
Topic: Theoretical and applied grounds of human-oriented information technologies on the principles of ethics and trustworthy artificial intelligence
Presentation in Ukrainian
Abstract: The widespread dissemination and application of artificial intelligence (AI) systems requires the development of formalized approaches and the construction of basic principles of functioning of the subject areas of the use of AI. This need is realized in the development of recommendations, regulations, and standards to maximize the benefits from the use of AI and minimize the possible risks. The regulatory framework is built on a human-centric basis. According to the developed standards should form the basis for further activities aimed at the application of AI and be applicable at all stages of the creation of practical solutions. Therefore, an important step is to formalize the requirements, principles and provisions of legal and ethical norms in the form of practical templates of practical application. With this method, the study developed models and ontologies of the standardized concept of trustworthiness for AI. This allowed to determine the basic concepts, which allow forming a position of trust, are a substantial part of the concept of AI trustworthiness, determine the necessity of its existence and pose a threat to it. On the basis of the subject domain ontology the models were developed and further decomposition of structural meaningful concepts was performed. Further defined the characteristics of the concept of trust formation. Machine learning methods have been proposed that allow dividing into interpreted and non-interpreted decisions within the framework of the concept of trust. Among the non-interpreted decision a method for improving the values of the target quality function using the grouping of an ensemble of models by the correlation of the decisions made is proposed. Also proposed a method for data features regularization in order to identify atypical features and feature outliers in the non-interpreted decisions based on the grouping of decisions in a single-class classification. Thus developed the model of confidence in AI allowed to determine the basic requirements in accordance with which were developed methods of obtaining decisions based on ensembles with maximization of the target function and the method of analysis of transient data features.
- Information about research projects and conferences: Anatoliy Sachenko
Doctor of Technical Sciences, Professor, scientific advisor of Research Institute for Intelligent Computer Systems.
E-mail: as@wunu.edu.ua
A regular meeting
Date: 16 June 2021 (Wednesday)
Place: online (a link will be put in invitation)
Time: 17:00-19:00 (East European time, Kyiv)
AGENDA:
- Speaker: Oleksandr Drozd
Prof., Dr. Sc.,
Professor of Computer Intelligent Systems and Networks Department,
Odessа Polytechnic State University
E-mail: drozd@ukr.net
Topic: Models, Methods and Means of Resilient Computing
Presentation in Russian
Abstract: The resource-based approach is proposed, which analyzes the integration of models, methods and means of the computer world into the natural one. The current state of the computer world resources (models, methods and means) is assessed. The vector of development of resources and the levels of this development are determined: replication, diversification and self-sufficiency as the goal of development. Dominance of replication, which is the lowest level of development, is noted. The main challenges in the development of computer resources are considered, and it is also shown how to resiliently develop models and methods. Real examples are given, the absence of which would make all the above arguments untenable.
Resume: In 1976, Alexander Drozd graduated with honors from the Odessa Polytechnic Institute. In 1982, he defended the doctoral Thesis. In 1990, he was awarded the academic title of Associate Professor. In 2003, he was awarded the title of Doctor of habil.sc. ing. Degree. In 2004, he was awarded the academic title of professor. His main areas of research are on-line testing of computer systems and their components, which has been developed for approximate data processing and in relation to safety-related systems. Since 1976, he has been working at the Odessa Polytechnic Institute. He has more than 540 scientific publications, including 240 inventions, 23 of which have been introduced into serial production. Research interests: on-line testing of digital circuits, FPGA-designing, green technologies, checkability analysis and checkable design of digital circuits for functional safety of critical systems. He took part in 4 international projects TEMPUS and Erasmus +.
2. Speaker: Volodymyr Romanov
Professor, PhD, Doctor of Science
Head of Data Acquisition Systems Department Glushkov Institute of Cybernetics of Ukrainian National Academy of Sciences (www.dasd.com.ua)
Head and Editor Electronic Components and Systems Journal (www.ekis.kiev.ua)
E-mail: VRomanov@i.ua
Topic: Wireless Sensor Networks with Elements of Artificial Intelligence for Medicine
Presentation in Russian
Abstract: The integrated digitalization of medicine, the use of the AIIoT(Artificial Intelligence IoT), and the networks of medical wireless sensors offers new opportunities to remotely support the quality of life of chronically ill patients, the elderly, and athletes and professionals with heavy physical or mental workloads. Wireless sensor networks and computer remote means of maintaining quality of life includes smart wearable medical sensors, and analog interface. The sensors are intended to monitor heart rate, respiration and blood pressure, determine skin moisture, patient’s position and other medical parameters in real time. Miniature interfaces are intended for data acquisition, analog-to-digital conversion, data preprocessing of medical parameters received from wearable medical sensors and data communication to remote diagnostic center. The current state and prospects for the development of these tools are discussed in the report.
- Information about research projects and conferences:
Anatoliy Sachenko
(Doctor of Technical Sciences, Professor, scientific advisor of Research Institute for Intelligent Computer Systems).
E-mail: as@wunu.edu.ua
A regular meeting
Date: 21 April 2021 (Wednesday)
Place: online (a link will be put in invitation)
Time: 17:00-19:00 (East European time, Kyiv)
AGENDA:
- Speaker: Yevgeniy Bodyanskiy
(Prof., Dr. Sc. (Dr.-Ing. habil.)
Scientific Head of Control Systems Research Laboratory,
Professor of Artificial Intelligence Department,
Kharkiv National University of Radio Electronics)
E-mail: yevgeniy.bodyanskiy@nure.ua
Topic: Fast Pattern Recognition using Combined Learning of Neural Networks
Presentation in Ukrainian
Abstract: The adaptive probabilistic neural network and neuro-fuzzy system for classification task in situation of overlapping classes are proposed. These systems are designed to solve data classification task when data are fed sequentially in the online mode, and forming classes are mutually overlapped – the fuzzy case. The distinct feature of the systems is that the learning process of the pattern layer uses the sliding window and combined tuning. This allows us to keep the constant number of neurons in layer. Another point of the learning process is the tuning ability of activation functions’ widespread parameters in online mode. The described advantage allows us to raise the classification quality. Last but not least is the ability to compute both the probability and membership levels of each observation to each of forming classes. The proposed adaptive probabilistic systems with fuzzy interference are simple in numerical implementation and have high learning speed. The results of experiments confirmed the correctness of approach under consideration.
Resume: In 1971, Yevgeniy Bodyanskiy graduated with honour from Kharkiv National University of Radio Electronics. In 1980, he defended the Doctoral Thesis. In 1984, he was awarded the academic title of Senior Researcher. In 1990, he was awarded Dr. habil.sc. ing. Degree. In 1994, he was awarded the academic title of Professor. His major fields of research are evolving hybrid systems of computational intelligence, data stream mining, data science, and big data. Since 1974, he has been working at Kharkiv National University of Radio Electronics. In 1974-1976, he was a Researcher; in 1977-1983, he was a Senior Researcher; in 1986–1991, he was a Scientific Head of Control Systems Research Laboratory; in 1991–1992, he was a Research Fellow. Since 1992, he has been a Professor of Artificial Intelligence Department at KhNURE, Scientific Head of Control Systems Research Laboratory at KhNURE. He has more than 660 scientific publications, including 42 inventions and 16 monographs. Research interests include hybrid systems of computational intelligence: adaptive, neuro-, wavelet-, neo-fuzzy-, real-time systems, including problems connected with control, identification, and forecasting, clustering, diagnostics, fault detection in technical, economic, medical and ecological objects. He is the IEEE senior member, member of 4 scientific and 7 editorial boards.
- Speaker: Tetiana Hovorushchenko
(Doctor of Technical Sciences, Professor, Khmelnytskyi National University, Ukraine)
E-mail: tat_yana@ukr.net
Topic: Intelligent Information-Analytical Technologies for Improving the Software Quality by Assessing the Sufficiency of Information at Initial Stages of the Life Cycle.
Presentation in Ukrainian
Abstract: The field of software engineering needs special attention in the direction of development and implementation of effective information technologies, in particular, to solve the problem of software quality assurance. Developing high-quality software is a key factor in its effective use and one of the main needs of customers. The need for quality assurance is based on the fact that software errors and failures lead to disasters that lead to human casualties, environmental cataclysms, significant time losses and financial losses.
The critical impact on software projects and the success of their implementation are issues related to the analysis and evaluation of the initial stages of the life cycle. Today, when the number of high-budget software projects is growing rapidly, analysis of the specification of software requirements is actual. The possibility of automated assessment of the initial stages of the software life cycle, in particular, identifying and eliminating shortcomings of the initial stages of the software life cycle and the facts of the insufficiency of information, which is relevant to them, is actual too (moreover special attention needs to be paid to information about the non-functional characteristics of the software).
The need to ensure the quality of software, the presence of information losses in the formation and formulation of software requirements, the need to identify and eliminate insufficiency of information at the initial stages of the software life cycle creates an urgent scientific and applied problem, one way to solve which is to develop intelligent information technology for improving the quality of software by assessing the sufficiency of information in the early stages of the life cycle, which will provide the ability to identify lack of quality information in the specifications of the requirements in the early stages of the software life cycle and the ability to generate requests to supplement requirements by such information, which together will allow to assess the current situation and provide the appropriate level of quality at later stages of the software life cycle.
The presentation is devoted to solving the current scientific and applied problem of improving the quality of software in the early stages of the life cycle by assessing the sufficiency of information on quality in the specifications of software requirements. Developed intelligent information-analytical technologies for improving the quality of software by assessing the sufficiency of information in the early stages of the life cycle: will increase the level of sufficiency of information of requirements for determining the quality of software, thereby reducing the gap in knowledge about software projects; will provide a conclusion on the sufficiency of information on quality in the specification of requirements; will determine the priority of supplementing the specification with the necessary information (in case of insufficient information); will provide a quantitative assessment of the level of sufficiency of the quality information, which is available in the specification; will provide the opportunity to process quality information in the software requirements specifications by intelligent agents, without the participation of specialists, which will eliminate the subjective influence of specialists and the safety of this information in the software company in case of dismissal of specialists. The developed information-analytical technologies will automatically process the existing knowledge (quality requirements from the specification) and will form new knowledge (conclusions about the sufficiency of information, about the level of information sufficiency, recommendations for improving the sufficiency of information in the specification requirements). Developed intelligent information-analytical technologies will increase the sufficiency of information on quality in the specifications of software requirements to 100% – if it’s necessary (for critical application systems) or at the request of the customer.
Resume: Tetiana Hovorushchenko received the Master Degree in Computer Engineering in 2002 from Technological University of Podillya (Khmelnytskiy), her PhD Degree in information technologies in 2007 from National University “Lvivska Politekhnyka”, her Degree of Doctor of Engineering Sciences in information technologies in 2018 from Ukrainian Academy of Printing (Lviv). Tetiana Hovorushchenko received the Degree of Senior Researcher in Information Technologies in 2010, her Degree of Docent of System Programming Department (Associate Professor) in 2011, her Degree of Professor of Computer Engineering & System Programming Department in 2019. Now she is a Head of Computer Engineering and System Programming Department of Khmelnytskyi National University, and Editor-in-chief of the scientific journal “Computer Systems and Information technologies”. Tetiana Hovorushchenko is the founder and general chair of the International Workshop on Intelligent Information Technologies and Systems of Information Security (IntelITSIS).
- Information about research projects and conferences:
Anatoliy Sachenko
(Doctor of Technical Sciences, Professor, scientific advisor of Research Institute for Intelligent Computer Systems).
E-mail: as@wunu.edu.ua
A regular meeting
Date: 24 February 2021 (Wednesday)
Place: online (a link will be put in invitation)
Time: 17:00-19:00 (East European time, Kyiv)
AGENDA:
- Speaker: Nataliya Shakhovska
(Doctor of Technical Sciences, Professor, Lviv Polytechnic National University)
ORCID ID: https://orcid.org/0000-0002-6875-8534
E-mail: natalya233@gmail.com
Topic: The hierarchical classifier for COVID-19 resistance evaluation.
Presentation in Ukrainian
Abstract: Finding dependencies in the data requires the analysis of relations between dozens of parameters of the studied process and hundreds of possible sources of influence on this process. Dependencies are nondeterministic and therefore modeling requires the use of statistical methods for analyzing random processes. Part of the information is often hidden from observation or not monitored. That is why many difficulties have arisen in the process of analyzing the collected information. The paper aims to find frequent patterns and parameters affected by COVID-19. The novelty of the paper is hierarchical architecture comprises supervised and unsupervised methods. It allows the development of an ensemble of the methods based on k-means clustering and classification. The best classifiers from the ensemble are Random Forest with 500 trees and XGBoost. Classification for separated clusters gives us higher accuracy on 4% in comparison with while dataset analysis. The proposed approach can be used also for personalized medicine decision support in other domains. The features selection gives us to analyze the following features with the highest impact on COVID-19.
2. Speaker: Sergii Babichev
(Doctor of Technical Sciences, Professor, Jan Evangelista Purkyne University in Usti nad Labem, Czech Republic/ Kherson State University, Ukraine)
URL: https://ki.ujep.cz/cs/personalni-slozeni/sergii-babichev/
ORCID: https://orcid.org/0000-0001-6797-1467
E-mail: sergii.babichev@ujep.cz
Topic: Techniques of gene expression profiles processing for purpose of gene regulatory networks reconstruction.
Presentation in Ukrainian
Abstract: The main direction of our research is focused to gene expression profiles processing for purpose of both gene regulatory network reconstruction and validation of the reconstructed models. This problem is one of the main directions of current bioinformatics.
The experimental foundation for our research are arrays of gene expressions obtained as a result of both DNA microarray experiments or RNA molecules sequencing technique. Gene expression in this case means a level of gene activity. This value is proportional to the number of genes that correspond to the appropriate type of protein in the biological organism.
Gene expressions profile is a vector of gene expressions determined for differed samples or different conditions of the experiment performing. Reconstruction of gene regulatory networks and further simulation of the reconstructed models form the basis for investigation and analysis of both the character of molecular systems elements interconnections and influences of these interconnections to functional possibilities of the investigated objects. The complexity of gene network reconstruction is determined by the following: the experimental data which are used for the reconstruction process usually does not allow defining the network structure and pattern of genes interconnection in the network. Moreover, a large quantity of genes complicates the interpretation of the network elements interconnections. In this case, it is necessary to conduct research concerning: experimental data pre-processing to determine the optimal ways of gene expression array formation; gene expression profiles reducing for purpose of informative genes allocation in terms of quantitative quality criteria; evaluation of both the network topology and the pattern of genes interconnection in the network with the use of experimental data obtained by the use of both DNA microchip experiment or RNA-molecules sequencing method. A qualitatively reconstructed gene regulatory network allows investigating the pattern of the biological organism development at the genetic level. It creates the conditions for both making new effective medicines and the development of methods of early diagnostics and effective treatment of complex diseases. This fact indicates the actuality of the research in this subject area.
Within the framework of this presentation, I would like to describe briefly a stepwise procedure of the gene expression data formation, pre-processing, and informative genes extraction for the purpose of both the gene regulatory network reconstruction or diseases diagnostic system creation.
3. Information about research projects and conferences:
Anatoliy Sachenko
(Doctor of Technical Sciences, Professor, scientific advisor of Research Institute for Intelligent Computer Systems).
E-mail: as@wunu.edu.ua
A regular meeting
Date: 23 December 2020 (Wednesday)
Place: online
Time: 17:00-19:00 (East European time)
AGENDA:
- Speaker: Sergiy Lysenko
(Doctor of Technical Sciences, Khmelnytskyy National University)
URL: http://ki.khnu.km.ua/team/sergii-lysenko/
E-mail: sprlysenko@gmail.com
Topic: Information Technologies for Proactive Cyberattacks Detection in Computer Systems.
Presentation in Ukrainian with slides in English
- Speaker: Inna Skarga-Bandurova
(Doctor of Technical Sciences, professor, researcher of the laboratory of visual artificial intelligence, Oxford Brookes University; researcher of the department of mathematical and econometric modeling, Pukhov Institute of Modeling Problems in Energy, Ukrainian National Academy of Sciences)
E-mail: iskarga-bandurova@brookes.ac.uk
Topic: Challenges of Decision Making in Medical Robotics: Towards the Autonomous Surgical Robotic Systems.
- Information about research projects, conferences and workshops:
Speaker: Anatoliy Sachenko
(doctor of technical sciences, scientific advisor of Research Institute of Intelligent Computer Systems).
URL: https://www.wunu.edu.ua/en/6998-sachenko-anatolii-oleksiiovych.html
E-mail: as@wunu.edu.ua
A regular meeting
Date: 10 June 2020 (Wednesday)
Place: online
Time: 17:00-19:00 (East European time)
AGENDA:
- Speaker: Volodymyr Pasicnyk
(doctor of technical sciences, professor of Department for Information Systems and Networks, Institute of Computer Sciences and Information Technologies, National University «Lviv Polytechnics»)
URL: http://wiki.lp.edu.ua/wiki/Пасічник_Володимир_Володимирович
E-mail: vpasichnyk@gmail.com
Topic: Information technology-smart weapons and locomotive of victory in the war with coronavirus: the concept of public IT arsenal.
2. Speaker: Igor Kotsiuba
(PhD, Pukhov Institute of Modeling Problems in Energy, National Academy of Sciences of Ukraine)
URL: http://www.nas.gov.ua/UA/PersonalSite/Statuses/Pages/default.aspx?PersonID=0000024464
E-mail: i.kotsiuba@gmail.com
Topic: Digital Forensic Readiness in Critical and Smart Infrastructures.
- Information about research projects, conferences and workshops:
Speaker: Anatoliy Sachenko
(doctor of technical sciences, scientific advisor of Research Institute of Intelligent Computer Systems).
URL: https://www.tneu.edu.ua/en/6998-sachenko-anatolii-oleksiiovych.html
E-mail: as@tneu.edu.ua