Кафедра мережних технологій

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About Big Matrix Inversion
(2021) Malaschonok, Gennadi; Tchaikovsky, Igor
Матеріал доповіді учасників 4-ої Міжнародної конференції "Комп'ютерна алгебра", 28–29 червня 2021 р., Москва.
Algebraic and algorithmic classification of matrix algorithms [electronic resourse]
(2021) Malaschonok, Gennadi
Due to the growing size of the matrices used in applications, it is useful to carefully distinguish between some groups of matrix algorithms. We propose to use algebraic classi cation as the main way to group matrix algorithms. From an algorithmic point of view, we propose to highlight the class of block-recursive algorithms. These algorithms make it possible to ensure a uniform load of a computing cluster, to solve the problem of protecting against failure of its individual nodes, and, in addition, they have the complexity of matrix multiplication.
An approach to modeling elections in bipartisan democracies on the base of the "state-probability of action" model
(2024) Dosyn, Dmytro; Oletsky, Oleksiy
An approach to constructing the two-level behavioral "state-probability of action" model and to getting appropriate matrices "state-probability of choice" for the case of two competing alternatives has been suggested. The top level is directly connected to probabilities of choice between alternatives. States of the model are connected to grades of pairwise comparisons. For getting rows of the matrix on this basis transitive scales are offered to be applied, but not only. It appears important to distinguish values of preferences themselves and probabilities of choice related to them. For this reason, another parameter standing for decisiveness of agents has been introduced. The bottom level is related to separate criteria influencing a choice. A way to applying such a model for modeling voting in a bipartisan democracy has been suggested. Within this context, a problem of equilibrium between two alternatives, when no alternative has advantages over the other, is of great importance. Some sufficient conditions for equilibrium between two alternatives have been postulated in the paper, they significantly rely upon properties of symmetry. The illustrating example of modeling elections in an imaginary country has been provided. Voters in this example are to make a choice between two candidates on the base of comparing them by some given criteria. In the initial example the equilibrium between alternatives holds. Then an issue how agents of influence could change the situation in a desirable direction is discussed.
Attempts at Computing Gröbner Bases without S-polynomials whenever Possible
(2017) Akritas, Alkiviadis G.; Malaschonok, Gennadi
In this note we lay down some thoughts on computing Grobner bases using subresultant polynomial remainder sequences (prs’s) to eliminate variables. In this way we try to minimise 5-polynomial computations and, if possible, to completely avoid them. A personal note to us by Bruno Buchberger - at the Polynomial Computer Algebra conference (PCA-2015) in St. Petersburg, Russia - served as the motivation for our effort.
Calculations on a Cluster with Distributed Memory: Matrix Decomposition and Inversion in the Commutative Domain
(2017) Malaschonok, G.; Ilchenko, E.
Матеріал виступу на XIV Мiжнародній науково-практичній конференцiї "Теоретичнi та прикладнi аспекти побудови програмних систем (TAAPSD'2017)", Київ, 4-8 грудня 2017 року.
Control of matrix computations on distributed memory
(2019) Malaschonok, Gennadi; Sidko, Alla
Dedicated to research in the field of parallel computer algebra, in particular the parallelization of matrix recursive algorithms on a cluster with distributed memory. A new dynamic control scheme for matrix recursive algorithms is proposed. We considered in detail new software objects that ensure the effective operations of the dynamic control scheme.
Cross-language text classification with convolutional neural networks
(2017) Musbah, Zaid; Lehinevych, Taras; Glybovets, Аndrii
Text classification or text categorization problem is currently one of the most observed in the field of information and computer sciences. The task is to assign a text to one or more classes or categories and it becomes more difficult if we have to deal with different languages. This problem is called cross-language text classification problem. In our paper [1] was shown that cross-language multi-label text classification can be handled by a deep learning system without artificially embedding knowledge about words, phrases, sentences or any other syntactic or semantic structures associated with a language.
Cross-language text classification with convolutional neural networks from scratch
(2017) Enweiji, Musbah; Lehinevych, Taras; Glybovets, Andrii
Cross 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.
Developing the open science infrastructure: a supercomputing platform for large matrix computing
(2022) Sidko, Alla; Malaschonok, Gennadi
It is proposed to use a new DAP supercomputer runtime for the creation of a component of the Open Science infrastructure in the form of access to a supercomputer with a special library of matrix algorithms. This will allow solving problems with large matrices in many application areas.
Development the software applications for mobile medical systems based on OS Android
(2016) Dorosh, Natalya; Kuchmiy, H.; Boyko, O. V.; Dorosh, Oleg; Stepanjuk, O.; Maritz, N.
In this paper the methods and tools to develop specialized software for mobile medicine (m-health navigator) on the base OS Android are given. The results of test studies using the developed software are shown.
E-government developed systemprototype about USA and Jordan
(МНУ імені В. О. Сухомлинського, 2017) Glybovets, Andriy; AlHawawsha, Mohammad
The 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.
E-Government versus Smart government: The United States Versus Jordan
(МНУ імені В.О. Сухомлинського, 2017) Glybovets, Andriy; AlHawawsha, Mohammad
This paper discusses the concepts of e-government and Smart Government as they relate to the use of digital and ICT technologies to enhance the way governments provide services to their citizens.
Efficient Calculation Managing on a Cluster with Distributed Memory: [preprint]
(2017) Ilchenko, E.; Malaschonok, Gennadi
Managing of cluster parallel computations for tree-like recursive algebraic algorithms for the case of cluster with distributed memory is one of the diffcult problems of computer algebra. The block-recursive algorithms of matrix and polynomial multiplication, Strassen's and Karatsuba's algorithms, matrix inversion and computation of the kernel of a matrix operator, LDU and Bruhat factorization are examples of such algorithms. We suggest a scheme with multidispatching for management of such parallel computing processes and demonstrate the results of experiments at the JSC RAS cluster MVS-10P.
MathPartner Computer Algebra
(2017) Malaschonok, Gennadi
In 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.
Matrix algorithms in commutative domains: the history of development in recent decades
(2017) Malaschonok, Gennadi
We discuss the history of development of matrix algorithms in commutative domains, starting from the 1983 year.
Neo4j як ядро рекомендаційної системи
(2017) Глибовець, Андрій; Haenssgen, Klaus
Матерiал виступу на XIV Мiжнародній науково-практичній конференцiї "Теоретичнi та прикладнi аспекти побудови програмних систем (TAAPSD'2017)", Київ, 4-8 грудня 2017 року.
Open science in Ukraine: open cloud mathematics
(2022) Malaschonok, Gennadi
One of the very important services that are essential for the scientific community is cloud math. We propose to use our open cloud mathematical platform MathPartner. It is a ready-made universal mathematical tool that can be connected as a service to the EU Open Science Platform.
Quick Recursive QR Decomposition
(2021) Malaschonok, Gennadi; Ivashkevich, Andriy
Матеріал доповіді учасників VI Міжнародної конференції з математичних основ інформатики MFOI-2020, 12-16 січня 2021 р., Київ.
Quick triangular orthogonal decomposition of matrices
(2019) Malaschonok, Gennadi; Gevondov, Gurgen
A new algorithm for calculating the triangular orthogonal decomposition of matrices is proposed. It differs from previously known algorithms by the smallest asymphotic complexity.
Recognizing gestures of the Ukrainian dactylic alphabet
(2023) Hlybovets, Andrii; Bikchentayev, Mykola
Sign 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.

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