003. Факультет інформатики

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9th Workshop on Cloud Technologies in Education: Report
(2022) Kiv, Arnold; Semerikov, Serhiy; Shyshkina, Mariya; Striuk, Andrii; Striuk, Mykola; Yechkalo, Yuliia; Mintii, Iryna; Nechypurenko, Pavlo; Kalinichenko, Olga; Kolgatina, Larisa; Vlasenko, Kateryna; Amelina, Svitlana; Semenikhina, Olena
This is an introductory text to a collection of selected papers from the 9th Workshop on Cloud Technologies in Education (CTE 2021) which held in Kryvyi Rih, Ukraine, on the December 17, 2021. It consists of short introduction, papers’ review and some observations about the event and its future.
A competency-based approach to the systematization of mathematical problems in a specialized school
(2021) Vlasenko, Catherine; Lovianova, Iryna; Armash, Tatiana; Sitak, Iryna; Kovalenko, Daria
The issue of searching for new methodological approaches to the systematization that will encourage the increase of students motivation to learn mathematics under the competency-based approach is considered in this article. The research analyzes the existing works on the increase in students motivation to learn Mathematics, in particular, the use of cross-curricular connections while forming students competency. Competency-based problems, systematized according to the topic of the 10th grade Functions, their features and graphics, were determined as the tools to measure students competency and a method to form their motivation to learn mathematics. The use of such methods as the initial research and information gathering, systematization and structural analysis of the problems, data processing allowed the authors of the article to systematize the problems for school subjects of the 10th grade that demonstrate cross-curricular connections of Mathematics with other learning subjects and allow showing the advantages of the mathematical modeling in researching real processes. The research shows the realization of cross-curricular connections in time and such connections as parallel learning, perspective connections, use of the mathematical modeling method are shown. An experiment was held in order to prove the e ciency of implementing a system of the problems to demonstrate the use of the function in di erent tasks of natural subjects. The results proved that the implemented system of problems considerably in uences the increase in students motivation to learn mathematics.
A Comprehensive Program of activities to develop sustainable core skills in novice scientists
(2021) Vlasenko, Catherine; Rovenska, Olga; Chumak, Olena; Lovianova, Iryna; Achkan, Vitaly
This paper is aimed at studying scientific communication as an integral part of a scientists activity. The authors of this article analysed the development of informational technologies, which gave rise to a new paradigm of scientific communication Research 2.0. In the present study the analysis of research papers, describing models of scientific communication is done. The findings allow to define the structure and content of a comprehensive program of activities, connected to scientific communication in compliance with the Scientific Communication Life Cycle Model. In order to implement the program, aimed at developing core skills through scientific communication of scientists, a target audience, comprising postgraduate students and young researchers in Mathematics and TeachingMethods was engaged. A five-stage program of activities, which was developed, prompted scientific activity of young researchers and gave them an opportunity to learn about means of presenting research results, elements of management, mechanisms for applying the findings. A constructive description of each module of the program is done, actions and a strategy are described, communication between participants and tutors through the platform Higher School Mathematics Teacher is arranged in this research. In order to assess the efficiency of implementing the program, Researcher Development Framework (RDF) is used. The study also presents the results of the activity of young researchers, who were engaged in the program. Following the change in the phase of the development of researchers characteristic features and in compliance with RDF, a conclusion is made about a positive impact of the program on the development of career skills of young scientists, their interaction skills, awareness of professional behavior procedure.
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.
About one problem for equation of fractal diffusion with argument deviation
(2017) Drin, Iryna; Drin, Svitlana; Drin, Yaroslav
Матеріал VI-ї Міжнародної науково-практичної конференції "Проблеми інформатики та комп'ютерної техніки (ПІКТ-2017)", 5-8 жовтня 2017 року.
Accurate classification for Automatic Vehicle Type Recognition based on ensemble classifiers
(2019) Shvai, Nadiya; Hasnat, Abul; Meicler, Antoine; Nakib, Amir
In this work, a real world problem of the vehicle type classification for Automatic Toll Collection (ATC) is considered. This problem is very challenging because any loss of accuracy even of the order of 1% quickly turns into a significant economic loss. To deal with such problem, many companies currently use Optical Sensors (OS) and human observers to correct the classification errors. Herein, a novel vehicle classification method is proposed. It consists in regularizing the problem using one camera to obtain vehicle class probabilities using a set of Convolutional Neural Networks (CNN), then, uses the Gradient Boosting based classifier to fuse the continuous class probabilities with the discrete class labels obtained from OS. The method is evaluated on a real world dataset collected from the toll collection points of the VINCI Autoroutes French network. Results show that it performs significantly better than the existing ATC system and, hence will vastly reduce the workload of human operators.
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.
The algorithm for knowledge assessment based on the Rusch model
(2022) Kostikov, Alexander; Vlasenko, Kateryna; Lovianova, Iryna; Volkov, Sergii; Avramov, Evgeny
In this paper the algorithm for adaptive testing of students’ knowledge in distance learning and an assessment of its effectiveness in the educational process has been proposed. The paper provides an overview of the results of the application of modern test theory, a description and block diagram of the proposed algorithm and the results of its application in the real educational process. The effectiveness of using this algorithm for the objective assessment of students’ knowledge has been experimentally shown.
Analysis of the Shape of Wave Packets in the "Half Space–Layer–Layer with Rigid Lid" Three-Layer Hydrodynamic System
(2022) Avramenko, Olga; Lunyova, Мariia
We study the process of propagation of weakly nonlinear wave packets on the contact surfaces of a "half space–layer–layer with rigid lid" hydrodynamic system by the method of multiscale expansions. The solutions of the weakly nonlinear problem are obtained in the second approximation. The condition of solvability of this problem is established. For each frequency of the wave packet, we construct the domains of sign constancy for the coefficient for the second harmonic on the bottom and top contact surfaces. The regularities of wave formation are determined depending on the geometric and physical parameters of the hydrodynamic system. We also analyze the plots of the shapes of deviations of the bottom and top contact surfaces typical of the constructed domains of sign-constancy of the coefficient. We discover the domains where the waves become ∪ - and ∩ -shaped and reveal a significant influence of wavelength on the shapes of deviations of the contact surfaces of the analyzed hydrodynamic system.
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.
The boundary problem by variable t for equation of fractal diffusion with argument deviation
(2017) Drin, I.; Drin, Svitlana; Drin, Y.
For a quasilinear pseudodifferential equation with fractional derivative by time variable t with order a e (0,1), the second derivative by space variable x and the argument deviation with the help of the step method we prove the solvability of the boundary problem with two unknown functions by variable t.
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.
CNN Classifier's Robustness Enhancement when Preserving Privacy
(2021) Hasnat, Abul; Shvai, Nadiya; Nakib, Amir
Laws on privacy preservation challenges supervised learning algorithms in industrial applications and could be an obstacle for the artificial intelligence solutions. In the literature, this issue is never discussed for the algorithm’s design. Indeed, algorithms do not behave the same when the input is modified to protect privacy. Particularly, the unmodified data samples predicts with low confidences show high vulnerability to decision changes. To overcome this challenge, we propose a novel solution that enhances classifier’s robustness by particularly addressing the vulnerable samples. It consists of a novel formulation of the learning objective by hybridizing similarity learning, decision margin and intra-class distance. Experimental results and evaluation on a challenging vehicle image dataset exhibit the high effectiveness and potentials of our method for the privacy preserving classification problems.
Commuting sets for topological set operators
(2021) Antoshyna, Kateryna; Kozerenko, Sergiy
Proceedings of the "Algebraic and Geometric Methods of Analysis", May 25-28, 2021 Odesa, Ukraine.
Complexity of the problem of verifying the coordination mechanism in a system of software support of network collaboration
(Springer New York, 2008) Glybovets, Mykola; Hlomozda, Dmytro
The problem of verifying the coordination mechanism in a system of software support of network collaboration is considered. This problem is demonstrated to be similar to the agent verification problem. It is proved that the problem of verifying the coordination mechanism is co-complete.
Conjugacy in finite state wreath powers of finite permutation groups
(2019) Oliynyk, Andriy; Russyev, Andriy
It is proved that conjugated periodic elements of the infinite wreath power of a finite permutation group are conjugated in the finite state wreath power of this group. Counter-examples for non-periodic elements are given.
Construction of a mathematical model of multiobjective optimization on permutations
(2020) Koliechkina, Liudmyla; Dvirna, Olena; Nahirna, Alla
The article is devoted to the problem of constructing and solving mathematical models of applied problems as multiobjective problems on combinatorial configurations. This question is actual branch because any task of optimal design of complex economic and technical systems, technological devices, planning and management etc. requires that the desired solution be found consider many criteria. It is used transfer to Euclidian combinatorial configurations and using of discrete optimizations methods. Method for solving such problems is considered and it includes the analyzing of structural graph of Euclidean combinatorial configurations sets. These methods can be modified by combining with other multiobjective optimization approaches depending on the initial conditions of the problem. Models for defining real estate contribution plans and production planning as multiobjective discrete problems are proposed. These models can be supplemented as needed by the required functions and, depending on the initial conditions, are presented as tasks on different sets of combinatorial configurations.
The construction of riskless portdolio for Student-like FAT models
(2016) Musienko, J.; Shchestyuk, Nataliia
In this paper we set up a riskless portfolio for alternative to Black-Scholes GBM model that incorporates the Student-like distribution of the returns.
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.

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