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Oral Presentation. 2021 IEEE 11th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications. Cracow University of Technology. Cracow, Poland September 22���25, 2021. The title of my presentation is An AI-based approach for decision-making in Hybrid E-rehabilitation. This research is done by the team of Glushkov Institute of Cybernetics of the National academy of sciences of Ukraine. Our team includes: Oleksandr Palagin, Vitalii Velychko, Kyrylo Malakhov This research takes place as a part of the project of the National research foundation of Ukraine. The project title is - "Transdisciplinary intelligent information and analytical system for the rehabilitation processes support in a pandemic (TISP)". The current epidemiological situation in the world caused by COVID-19 disease requires the intensive use of modern information and communication technologies for remote interaction, in particular, in the field of rehabilitation medicine and physical therapy. The new term in rehabilitation medicine and physical therapy has raised - hybrid e-rehabilitation. This new term includes the following essential parts: Telecommunication technologies (that means the delivery of rehabilitation services over telecommunication networks and the internet. Also, this allows patients to interact with providers remotely and can be used both to assess patients and to deliver therapy); Rich Internet Applications (first of all this is the hospital information systems. HIS - is a comprehensive, integrated information system designed to manage all the aspects of a hospital's operation, such as medical, administrative, financial, and legal issues and the corresponding processing of services. Another feature of such systems is the provision of communication between the patient and the doctors from the multidisciplinary rehabilitation team); Telemetry (this is a set of technologies that allow remote measurement, collection and transmission of information about performance indicators (physiological parameters) of the patient's body); Wearable devices (Wearables may be for general use, in which case they are just a particularly small example of mobile computing. Alternatively they may be for the special purposes such as fitness trackers or medical devices. They may incorporate special sensors such as accelerometers, heart rate monitors, or on the more advanced side, electrocardiogram (ECG) and blood oxygen saturation (SpO2) monitors); Biofeedback (Biofeedback is the process of gaining greater awareness of many physiological functions of one's own body. Biofeedback may be used to improve health, performance, and the physiological changes that often occur in conjunction with changes to thoughts, emotions, and behavior. Recently, technologies have provided assistance with intentional biofeedback.); Virtual assistants is a software agent that can perform tasks or services for individual based on commands or questions; Artificial Intelligence methods and applications for extracting knowledge from data and solving analytical tasks., This paper and the research behind it would not have been possible without the financial support of the National research foundation of Ukraine under the contract No 159/01/0245 from 07.05.2021, project title: "Transdisciplinary intelligent information and analytical system for the rehabilitation processes support in a pandemic (TISP)".

Our main goal in this paper is to propose a new approach for storing dictionaries and thesauruses using only the names but not pointers and this way to simplify and to speed up the corresponded computer programs. It is called “Natural Language Addressing” (NLA). This approach is a possibility to access information using natural language words or phrases as direct addresses of the information in the computer memory. For this purpose the internal encoding of the letters is used to generate corresponded address co-ordinates. This paper outlines the main idea of NLA approach. An extended example based on the WordNet thesaurus is given.

This paper introduces an approach to storing graphs based on the Natural Language Addressing in multidimensional numbered information spaces. A sample graph is analyzed to find its proper NL-representation. Taking in account the interrelations between nodes and edges, a “multi-layer” representation is possible and identifiers of nodes and edges can be avoided. The advantages and disadvantages of NL-addressing for the multi-layer representation of graphs are discussed.

Natural Language Addressing (NLA) is a possibility to access information using natural language words or phrases as direct addresses of the information in the computer memory. For this purpose the internal encoding of the letters is used to generate corresponded address co-ordinates. This paper outlines the main idea of NLA.

В настоящей работе представлена идея естественно-языковой адресации. Это дополнительная возможность для представления онтологической информации в интеллектуальных системах. Естественно-языковая адресация имеет ряд преимуществ. На первом месте – это линейная алгоритмическая сложность, которая зависит от максимальной длины слов (max_L), а не от их количества. Во-вторых, это уменьшение объема занимаемой памяти – дополнительные индексы не используются. В-третьих, уменьшение времени обработки из-за полного отсутствия поиска – информация извлекается прямо по адресу. Необходимо отметить, что это универсальное представление информации одновременно доступной как для человека, так и для автоматизированных систем. Такой способ организации информации применим для ее хранения и использования в библиотеках онтологий, терминов, понятий, текстовых документов This book maintains articles on actual problems of research and application of information technologies, especially the new approaches, models, algorithms and methods for information modeling of knowledge in: Intelligent NL Processing; Management of computing and information system; Knowledge Engineering; Mathematical Foundation of Artificial Intelligence; Computing; Decision Making; Economics Decision Support Systems; Modern (e-) Learning; Philosophy and Methodology of Informatics.

NL-addressing is a possibility to access information using natural language words as addresses of the information stored in the multi-dimensional numbered information spaces. For this purpose the internal encoding of the letters is used to generate corresponded co-ordinates. The tool for working in such style is named OntoArM. Its main principles, functions and using for storing RDF graphs are outlined in this paper

In the article it is considered preconditions and main principles of creation of virtual laboratories for computer-aided design, as tools for interdisciplinary researches. Virtual laboratory, what are offered, is worth to be used on the stage of the requirements specification or EFT-stage, because it gives the possibility of fast estimating of the project realization, certain characteristics and, as a result, expected benefit of its applications. Using of these technologies already increase automation level of design stages of new devices for different purposes. Proposed computer technology gives possibility to specialists from such scientific fields, as chemistry, biology, biochemistry, physics etc, to check possibility of device creating on the basis of developed sensors. It lets to reduce terms and costs of designing of computer devices and systems on the early stages of designing, for example on the stage of requirements specification or EFT-stage. An important feature of this project is using the advanced multi-dimensional access method for organizing the information base of the Virtual laboratory.

The principal feature of ontology, which is developed for a text processing, is wider knowledge representation of an external world due to introduction of three-level hierarchy. It allows to improve semantic interpretation of natural language texts.

The problems of constructing the selfsrtucturized systems of memory of intelligence information processing tools, allowing formation of associative links in the memory, hierarchical organization and classification, generating concepts in the process of the information input, are discussed. The principles and methods for realization of selfstructurized systems on basis of hierarchic network structures of some special class – growing pyramidal network are studied. The algorithms for building, learning and recognition on basis of such type network structures are proposed. The examples of practical application are demonstrated.

The formal model of natural language processing in knowledge-based information systems is considered. The components realizing functions of offered formal model are described.