Ivan Kit
@wunu.edu.ua
Department of Information Computer Systems And Control
West Ukrainian National University
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Science, Artificial Intelligence
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Khrystyna Lipianina-Honcharenko, Carsten Wolff, Anatoliy Sachenko, Ivan Kit, and Diana Zahorodnia
MDPI AG
Anthropogenic disasters pose a challenge to management in the modern world. At the same time, it is important to have accurate and timely information to assess the level of danger and take appropriate measures to eliminate disasters. Therefore, the purpose of the paper is to develop an effective method for assessing the level of anthropogenic disasters based on information from witnesses to the event. For this purpose, a conceptual model for assessing the consequences of anthropogenic disasters is proposed, the main components of which are the following ones: the analysis of collected data, modeling and assessment of their consequences. The main characteristics of the intelligent method for classifying the level of anthropogenic disasters are considered, in particular, exploratory data analysis using the EDA method, classification based on textual data using SMOTE, and data classification by the ensemble method of machine learning using boosting. The experimental results confirmed that for textual data, the best classification is at level V and level I with an error of 0.97 and 0.94, respectively, and the average error estimate is 0.68. For quantitative data, the classification accuracy of Potential Accident Level relative to Industry Sector is 77%, and the f1-score is 0.88, which indicates a fairly high accuracy of the model. The architecture of a mobile application for classifying the level of anthropogenic disasters has been developed, which reduces the time required to assess consequences of danger in the region. In addition, the proposed approach ensures interaction with dynamic and uncertain environments, which makes it an effective tool for classifying.
Khrystyna Lipianina-Honcharenko, Carsten Wolff, Anatoliy Sachenko, Oksana Desyatnyuk, Svitlana Sachenko, and Ivan Kit
MDPI AG
The influence of Internet marketing has grown so much that producers must now reconfigure their businesses from offline operation to online presence simply to meet user expectations. Thus, the development of an intelligent information system for product promotion online is quite relevant. It may lead to automatized selection of competing products and advertising content, a subsequent increase in the effectiveness of advertisements, and a decrease in costs for Internet ad placements. The paper presents the approach for creating an intelligent information system for product promotion in online spaces that makes it possible to reduce advertising costs. A methodology is based on outcomes of own previous studies as well as the flow nature and semantics of data streams. The framework of the proposed intelligent system includes the four key procedures and functions: intelligent formation of keywords for advertising content based on feedback, intelligent formation of product catalogs of online stores, generation of advertising content, and generation of improved advertising content and its targeting generation of text based on keywords. An experimental study confirmed that the effectiveness of posts on social media increased by at least 125%, while the price decreased by 87%.
Oleh Pisnyi, Ivan Kit, Khrystyna Lipianina-Honcharenko, Jürgen Sieck, Anatoliy Sachenko, Maciej Dobrowolski, and Grygoriy Sapozhnyk
IEEE
In a world of rapid technological changes and growing interest in cultural heritage, the development of innovative tools for travelers and history enthusiasts becomes incredibly important. Even in the digital age, interactive ways of exploring historical landmarks remain relevant and attractive. In this research, an AR Intelligent Real-time Method for Cultural Heritage Object Recognition has been developed. The method is implemented through a chatbot, which, when using a smartphone's camera, recognizes objects of cultural heritage and provides descriptions of these objects. The chatbot opens up new possibilities for travelers, allowing them to enjoy history and cultural heritage using intelligent tools and augmented reality.
Sophie Schauer, Jürgen Sieck, Khrystyna Lipianina-Honcharenko, Anatoliy Sachenko, and Ivan Kit
IEEE
This paper explores how digital auralised 3D models of cultural heritage sites can be used for long-term preservation. An overview of current digitalisation and auralisation techniques will be given, focusing on the results of a project where three music venues were digitalised through laser-scanning surveys, auralised and made available to visitors as a virtual reality application. Furthermore, case studies which had been conducted during the project will be evaluated, and the importance of preservation uses highlighted. The paper finishes with a conclusion and a future outlook.
Khrystyna Lipianina-Honcharenko, Ruslan Savchyshyn, Anatoliy Sachenko, Anastasiia Chaban, Ivan Kit, and Taras Lendiuk
Research Institute for Intelligent Computer Systems
In order to save time and money for tourists, as well as taking into account their limited mobility in the conditions of Covid, the concept of an intelligent guide based on augmented reality (AR) is proposed. A UML method diagram and algorithm for communication of the system with the user with AR and voice control support have been developed, as well as an application that allows tourists to immerse themselves in the historical retrospective of recreational places. On the example of the central part (downtown) of Ternopil, Ukraine, AR locations are offered, which gives an opportunity to get acquainted in more detail with the information about the tourist object. At the same time, the shortest tourist route is illuminated of historical monuments.
Ivan Kit, Hrystyna Lipyanina-Goncharenko, Taras Lendyuk, Anatoliy Sachenko, and Myroslav Komar
Springer International Publishing
Viktor Turchenko, Ivan Kit, Oleksandr Osolinskyi, Diana Zahorodnia, Pavlo Bykovyy, and Anatoliy Sachenko
IEEE
nowadays, living space, food and water for the rapidly growing urban population are not used quite sparingly, which makes them extremely vulnerable resources. Therefore, the trend has emerged where people in urban areas choose to have a small garden (for example, a balcony garden), and want to grow healthy and environmentally friendly food. To achieve this, a compact plant growing system "Grow Box" is needed, which gives an optimal use of space and can provide an automated plant growing process. The authors proposed the concept of IoT based smart system using the augmented reality for growing plants in the city. System implementation has a modular structure and can act as an experimental site or a full-fledged tool with some changes for greenhouses.
Hrystyna Lipyanina, Valeriya Maksymovych, Anatoliy Sachenko, Taras Lendyuk, Andrii Fomenko, and Ivan Kit
Springer International Publishing
Diana Zahorodnia, Pavlo Bykovyy, Anatoliy Sachenko, Viktor Krylov, Galina Shcherbakova, Ivan Kit, Andriy Kaniovskyi, and Mykola Dacko
Springer International Publishing
Andrij Sydor, Diana Zahorodnia, Pavlo Bykovyy, Ivan Kit, Vasyl Koval, and Konrad Grzeszczyk
IEEE
Recognition of multidimensional images based on the Hamming distance, as well as development of estimation criteria of certain image classes and new methods for determining the Hemming distance differentiating between identical objects with different number of coding parameters are highly topical problems facing various areas of knowledge and activity. The paper proposes a method of encoding of multidimensional objects for diagnosis with the same and different number of parameters, which represent multidimensional vectors at nodes of a two-dimensional plane as a model of a multichannel object for diagnosis in the Hemming space. The monitoring system scheme of the nodes of the object for diagnosis is developed. Coding methods for priority and prohibitory road signs are proposed. The value of the Hamming distance estimate for these categories is determined. A method and algorithm for the Hamming distance estimate for objects with different number of parameters are proposed. In addition, a method of value of the Hamming distance estimate for some road sign categories with different number of informative parameters is proposed.
Ivan Kit, Andrii Fomenko, Volodymyr Vyshnia, and Iryna Novosad
IEEE
Today Ukraine's railways have significant problems due to cargo thefts during both their transportation and at train stops. Large losses of railways in this case require intensifying the fight against these crimes. The point of the research is that for the first time, in order to combat the encroachment on the cargo, it is proposed to create a network of weigh checkpoints (WCP) on the railroad. Such WCP network automatically controls the actual weight of goods in cars along the train without moving them, and compares it with the accompanying data documents for cargo. Then results of the control are transmitted in the direction of train movement via electronic communication. In the case of a discrepancy between the indications of WCP device and the accompanying information about the load, there is a fixed shortage of cargo in the carriage. The optimization of WCP general demand on the railways in practice enables to use the research carried out by law enforcement officers as means for the effectively combat the railway crime.