Кафедра мережних технологій
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Item Cross-language text classification with convolutional neural networks from scratch(2017) Enweiji, Musbah; Lehinevych, Taras; Glybovets, AndriiCross language classification is an important task in multilingual learning, where documents in different languages often share the same set of categories. The main goal is to reduce the labeling cost of training classification model for each individual language. The novel approach by using Convolutional Neural Networks for multilingual language classification is proposed in this article. It learns representation of knowledge gained from languages. Moreover, current method works for new individual language, which was not used in training. The results of empirical study on large dataset of 21 languages demonstrate robustness and competitiveness of the presented approach.Item E-government developed systemprototype about USA and Jordan(МНУ імені В. О. Сухомлинського, 2017) Glybovets, Andriy; AlHawawsha, MohammadThe use of the Information technology, in the improvement of the e-government is considered as another territory related with the use if the ICT for conveying the legislative administrations to the citizens of the country. The e-government framework contains different advancements including the web and wide area networks, mobile computing for providing constant government services for the natives. Demonstrated that the United Nations portrayed e-government as the application and use of the "Data and Communication Technology" for provisioning general society administrations and data to people in general. The following report consists of discussion about the features and challenges in implementing e government. In addition to that, this paper also proposes a new architecture for the e governments that may improve the functionalities of e government whereas reducing the overhead of maintain it.Item MathPartner Computer Algebra(2017) Malaschonok, GennadiIn this paper, we describe general characteristics of the MathPartner computer algebra system (CAS) and Mathpar programming language thereof. MathPartner can be used for scientific and engineering calculations, as well as in high schools and universities. It allows one to carry out both simple calculations (acting as a scientific calculator) and complex calculations with large-scale mathematical objects. Mathpar is a procedural language; it supports a large number of elementary and special functions, as well as matrix and polynomial operators. This service allows one to build function images and animate them. MathPartner also makes it possible to solve some symbolic computation problems on supercomputers with distributed memory. We highlight main differences of MathPartner from other CASs and describe the Mathpar language along with the user service provided.Item Recognizing gestures of the Ukrainian dactylic alphabet(2023) Hlybovets, Andrii; Bikchentayev, MykolaSign language is a visual way of communicating used by people who are deaf or hard of hearing. It involves handshapes, facial expressions, and body movements to con-vey meaning. Sign language helps the deaf community interact with each other and the hearing world, allowing them to participate fully in society. According to the WHO (World Health Organization) over 5 % of the world’s population – or 430 mil-lion people — experience problems with hearing. More than 44,000 people with hearing impairments are registered with the Ukrainian Society of the Deaf, an all-Ukrainian public organization for the disabled. Therefore, it is extremely important to develop new software, available to the public, that would allow quickly and effec-tively learn and understand sign language. This work aims to review gesture recogni-tion techniques and develop a system for detecting and classifying gestures of the Ukrainian dactylic alphabet. Two main approaches to gesture recognition, glove-based and computer vision-based (CV), are explained, with the latter being preferred due to its flexibility and widespread usage. The text elaborates on deep learning-based approaches, particularly LSTM networks, and the advantages they offer in au-tomatically learning features from raw image data. The process of creating a dataset for training the gesture classification model is described, which involves recording videos of hand gestures and extracting keypoints using Google MediaPipe. The mo-del training phase is detailed, covering the architecture of the LSTM-based classifier, optimization algorithms, and loss functions. The resulting model achieves an accura-cy of 98.4% on the test dataset. A program for real-time gesture recognition is deve-loped using Python and relevant libraries. The program utilizes a webcam feed to de-tect and classify hand gestures, displaying the top three predicted letters of the Ukrainian dactylic alphabet. The scientific novelty of the obtained results: the paper presents a method that utilizes hand keypoints for recognizing hand gestures of the Ukrainian dactyl alphabet. Also, as part of the development of the gesture recognition system, a data set was collected, where each gesture corresponds to 50 videos of 65 frames. The practical significance of the results obtained: the model obtained as a result of the study can be used to interpret the gestures of the Ukrainian dactylic al-phabet. The dataset collected for training this model can be used in other works to train or validate similar models. The paper might be of use to the ones who are inte-rested in developing similar systems for gesture recognition.Item Software architecture of the question-answering subsystem with elements of self-learning(2021) Hlybovets, Andrii; Tsaruk, A.Within the framework of this paper, the analysis of software systems of question-answering type and their basic architectures has been carried out. With the development of machine learning technologies, creation of natural language processing (NLP) engines, as well as the rising popularity of virtual personal assistant programs that use the capabilities of speech synthesis (text-to-speech), there is a growing need in developing question-answering systems which can provide personalized answers to users' questions. All modern cloud providers proposed frameworks for organization of question answering systems but still we have a problem with personalized dialogs. Personalization is very important, it can put forward additional demands to a question-answering system’s capabilities to take this information into account while processing users’ questions. Traditionally, a question-answering system (QAS) is developed in the form of an application that contains a knowledge base and a user interface, which provides a user with answers to questions, and a means of interaction with an expert. In this article we analyze modern approaches to architecture development and try to build system from the building blocks that already exist on the market. Main criteria for the NLP modules were: support of the Ukrainian language, natural language understanding, functions of automatic definition of entities (attributes), ability to construct a dialogue flow, quality and completeness of documentation, API capabilities and integration with external systems, possibilities of external knowledge bases integration After provided analyses article propose the detailed architecture of the question-answering subsystem with elements of self-learning in the Ukrainian language. In the work you can find detailed description of main semantic components of the system (architecture components).Item Software security overview(2019) Rashidinia, Anoushirvan; Gavrilenko, S.; Pochebut, Maksym; Sytnikova, O.The article analyzes the main threats and problems of software protection. Methods for protecting information, their advantages and disadvantages are considered, and the possibility of using existing tools to protect software is studied. The possibility of improving and using a number of software protection methods against active fraud attacks was brought. Type of attacks exists and why protection is necessary was specified. Furthermore, we discussed several states of the art protection techniques which can be used in software to protect against analysis and tampering attacks. Analyzed such methods: Client-Server Solutions, Code Encryption, Code Diversity, Code Obfuscation, White-Box Cryptography, Tamper Resistant Software, Software Guards, Oblivious Hashing. Although we considered all these possible techniques separately, it is possible to combine these techniques into one solution.Item Аналіз програмних систем підтримки розумного будинку(2019) Глибовець, Андрій; Моголівський, ВіталійПроведено аналіз досліджень у сфері "розумного будинку". Визначено ключові проблеми галузі. Розглянуто наявні Saas системи, здійснено порівняння між ними та знайдено сильні та слабкі сторони кожної із систем. Визначено ключові характеристики системи підтримки "розумного будинку".