Кафедра математики

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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 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.
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.
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.
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.
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.
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.
Development of the online course for training master students majoring in mathematics
(2021) Vlasenko, Catherine; Lovianova, Iryna; Rovenska, Olga; Armash, Tatiana; Achkan, Vitaly
This article considers the issue of implementing a model of blended learning to prepare master students majoring in Mathematics (speciality code in Ukrainian educational system "014 Secondary Education. Mathematics"). The research analyses the existing developments of the issue about the use of blended learning while training would-be mathematics teachers. The researchers determined and explained the stages of work on developing the online course "Methods for Teaching Mathematics to Students at Technical Universities", that is used when students learn methodological subjects of the curriculum. The research describes the development of the theoretical online course model and methodological recommendations on the learning materials and preparing papers for the course. The article offers recommendations related to the course structure. The course developers de ned the usability criteria of the educational platforms, determined the stages of course users' activity, their content, and organization. The research describes the areas of online course activity management, the course tutors' and moderators' teamwork is de ned as the main condition of its development and support. In order to prove the e ciency of implementing blended learning of the methodological subjects, an experiment was carried out during the assistant practice in technical universities that master students of the specialization \Mathematics" had. The results allowed con rming the e ciency of students' practical training during blended learning of the methodological subjects that in its turn encouraged the improvement of the assistant practice results.
DEvS: Data Distillation Algorithm Based on Evolution Strategy
(2022) Shvai, Nadiya; Llanza, Arcadi; Hasnat, Abul; Nakib, Amir
The development of machine learning solutions often relies on training using large labeled datasets. This raises challenges in terms of data storage, data privacy protection, and longer model training time. One of the possible solutions to overcome these problems is called dataset distillation – a process of creating a smaller dataset while maximizing the preservation of its task-related information. In this paper, a new dataset distillation algorithm is proposed, called DEvS, which uses an evolutionary strategy approach to condense the training samples initially available for an image classification task, while minimizing the loss of classification accuracy. Experiments on CIFAR-10 demonstrate the competitiveness of the proposed approach. Also, contrary to recent trends, DEvS is derivative-free image generation, and therefore has greater scalability on larger input image sizes.
Diffusion model in Image Transforms Inversion tasks
(2022) Kravchuk, Oleg; Kriukova, Galyna
Матеріали доповіді учасників міжнародної наукової конференції, присвяченої 60-річчю кафедри прикладної математики та інформаційних технологій "Прикладна математика та інформаційні технології", 22-24 вересня 2022 р.
A discrete regularization method for hidden Markov models embedded into reproducing kernel Hilbert space
(2018) Kriukova, Galyna
Hidden Markov models are a well-known probabilistic graphical model for time series of discrete, partially observable stochastic processes. We consider the method to extend the application of hidden Markov models to non-Gaussian continuous distributions by embedding a priori probability distribution of the state space into reproducing kernel Hilbert space. Corresponding regularization techniques are proposed to reduce the tendency to overfitting and computational complexity of the algorithm, i.e. Nystr¨om subsampling and the general regularization family for inversion of feature and kernel matrices. This method may be applied to various statistical inference and learning problems, including classification, prediction, identification, segmentation, and as an online algorithm it may be used for dynamic data mining and data stream mining. We investigate, both theoretically and empirically, the regularization and approximation bounds of the discrete regularization method. Furthermore, we discuss applications of the method to real-world problems, comparing the approach to several state-of-the-art algorithms.
Distributed System for Sampling and Analysis of Electroencephalograms
(2017) Sudakov, Oleksandr; Kriukova, Galyna; Natarov, Roman; Gaidar, Viktoriia; Maximyuk, Oleksandr; Radchenko, Sergiy; Isaev, Dmytro
Distributed system for sampling and analysis of electroencephalograms is proposed and implemented in alpha state. The system is based on the previously developed database for archiving of the electroencephalograms in Ukrainian National Grid infrastructure. The new components of the system include EEG sensors for laboratory animals, simulations software and data procession algorithms. The first application of the system for data sampling, analysis and simulations of epileptic seizures is performed.
Eccentric digraphs of unique point eccentric graphs
(2021) Hak, Artem; Haponenko, V.; Kozerenko, Sergiy
Тези виступу на X Всеукраїнській науковій конференції молодих математиків, Київ, 16-17 квітня 2021.
Edge Imbalance Sequences and Their Graphicness: [preprint]
(2019) Kozerenko, Sergiy
The main focus of combinatorial dynamics is put on the structure of periodic points (and the corresponding orbits) of topological dynamical systems. The first result in this area is the famous Sharkovsky’s theorem which completely describes the coexistence of periods of periodic points for a continuous map from the closed unit interval to itself. One feature of this theorem is that it can be proved using digraphs of a special type (the so-called periodic graphs). In this paper we use Markov graphs (which are the natural generalization of periodic graphs in case of dynamical systems on trees) as a tool to study several classes of maps on trees. The emphasis is put on linear and metric maps.
Embedding Hidden Markov Models into Reproducing Kernel Hilbert Spaces
(2018) Kriukova, Galyna
Abstract of the speech at 4th AMMODIT Conference, 19-23 March 2018, Malekhiv (Lviv region), Ukraine.

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