Skip to main content
main-content

Über dieses Buch

This book features high-quality, peer-reviewed research papers presented at the First International Conference on Computer Science, Engineering and Education Applications (ICCSEEA2018), held in Kiev, Ukraine on 18–20 January 2018, and organized jointly by the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” and the International Research Association of Modern Education and Computer Science. The state-of-the-art papers discuss topics in computer science, such as neural networks, pattern recognition, engineering techniques, genetic coding systems, deep learning with its medical applications, as well as knowledge representation and its applications in education. It is an excellent reference resource for researchers, graduate students, engineers, management practitioners, and undergraduate students interested in computer science and their applications in engineering and education.

Inhaltsverzeichnis

Frontmatter

Computer Science for Manage of Natural and Engineering Processes

Frontmatter

Physical and Mathematical Modeling of Permeable Breakwaters

This article presents the experimental result and mathematical analysis influences of the permeable breakwaters to dynamics of the coast on various conditions by the action of waves. Deposition of sediment behind breakwaters leads to the formation tombolo of a certain size and intensity depending on the parameters of breakwater and the presence of a weak along-shore sediment flow. The results of the experiments determined empirical dependences, which are necessary for scientific study design of permeable breakwaters. Mathematical modeling of experimental data was also carried out. Experimental data are compared with already known results of research for permeable breakwaters with frontal and oblique approaches of waves. The experiment was held in Kyiv, Ukraine at the Institute of Hydromechanics National Academy of Sciences of Ukraine.

Lidiia Tereshchenko, Vitalii Khomicky, Ludmyla Abramova, Ihor Kudybyn, Ivan Nikitin, Igor Tereshchenko

Risk Modeling of Accidents in the Power System of Ukraine with Using Bayesian Network

Current studies of impact of climatic factors on overhead power lines are limited to calculations of load of climatic factors on the overhead transmission lines, so the problem of conducting a comprehensive study of accidents probability under the influence of climatic factors is important.The paper addresses the research of approaches to spatial risk modeling of overhead power lines accidents in the power systems of Ukraine under the influence of climatic factors. The article presents the construction of a model of accidents under the influence of climatic impacts and prediction of emergencies on based geospatial data sets. Pattern recognition techniques, namely the Bayesian network, were used to simulate accidents and verification of the results. This method is based on calculation of a posteriori probabilities of model variables. As a result, a model of accidents under the influence of climatic factors was built, which constitutes a Bayesian network with given conditional probabilities and independent variables of the model.

Viktor Putrenko, Nataliia Pashynska

Influence of the Deep Spherical Dimple on the Pressure Field Under the Turbulent Boundary Layer

The influence of a local dimple in the form of a deep spherical cavity on the pressure field inside the dimple and its vicinity for the turbulent flow regime is experimentally determined. Specific features of the vortex formation inside the dimple are established and the influences of vortex structures that are ejected outward from the spherical dimple on the structure of the turbulent boundary layer are shown. The antiphase oscillations of the wall pressure fluctuation field occur in the halves of the dimple separated by a longitudinal axial plane when the vortex flow “switches” from one side of the dimple to another. The spectral components of the wall pressure fluctuations on the streamlined surface of the spherical dimple have discrete components corresponding to the frequencies of the “switching” of the vortex formation inside the dimple (St ≈ 0.003), the frequencies of the vortex ejections from the dimple (St ≈ 0.05) and the frequencies of the self-oscillations of the shear layer (St ≈ 0.4).

V. A. Voskoboinick, V. N. Turick, O. A. Voskoboinyk, A. V. Voskoboinick, I. A. Tereshchenko

Structural Model of Robot-Manipulator for the Capture of Non-cooperative Client Spacecraft

Reorientation, service operation of client spacecrafts etc. are very actual tasks nowadays. Most of such spacecrafts are non-cooperative. Although service operations of these satellites were held before, they are not fully automated. However, docking in manual mode needs huge amount of time and human aboard. That makes impossible to carry out the required number of service operations. In current work it is represented conceptual model of the robot - manipulator for capture and maintenance of non-cooperative client spacecraft. Mechanism of collet effector was proposed for this purpose. Payload Adapter interface PAS 1666 S, PAS 1194 C, PAS 1666 MVS, PAS 1184 VS was chosen as a docking point, because of this interface’s convenience and prevalence. Proposed mechanism allows to work in conditions of client spacecraft’s linear and angular dynamic position errors in a range of ±5° per minute and ±0.1 meters per minute respectively. This is achieved by design of the robot-manipulator. Problem of jogless docking and methods of shock prevention are examined. In addition, the berthing and girth operations need axes coincidence of non-cooperative client spacecraft and service spacecraft. Having this in mind, phases of berthing and girth are described and main functions of service spacecraft’s control system for solving this problem are considered.

D. Humennyi, I. Parkhomey, M. Tkach

The Designing and Research of Generators of Poisson Pulse Sequences on Base of Fibonacci Modified Additive Generator

The article presents principles of optimizing the parameters of structural elements of Poisson pulses sequence generator that is based on modified additive Fibonacci generator. The results of their simulation modeling show, that statistical characteristics of output pulse sequence correspond to Poisson law of distribution. In addition, in this article have been defined the limits of control code for concrete parameters of structural scheme.

Volodymyr Maksymovych, Oleh Harasymchuk, Ivan Opirskyy

Methods of the Statistical Simulation of the Self-similar Traffic

The problem of evaluating the quality of the service is one of the important tasks of analyzing the traffic of telecommunication networks. Characteristics of traffic of modern telecommunication networks vary widely and depend on a large number of parameters and network settings, characteristics of protocols and user’s work. Recent studies argue that network traffic of modern networks has the properties of self-similarity. And this requires finding adequate methods for traffic simulating and loading processes in modern telecommunication networks.The article deals with the methods of statistical simulation of fractional Brownian motion based on the spectral image. The developed methods are used for modeling of self-similar traffic and loading process of telecommunication networks. Estimates of the probability of repositioning are found.

Anatolii Pashko, Violeta Tretynyk

Multidimensional Wavelet Neuron for Pattern Recognition Tasks in the Internet of Things Applications

Data mining and processing of Big Data is key problem in developing intelligent Internet of Things (IoT) applications. In this article, the multidimensional wavelet neuron for pattern recognition tasks is proposed. Also, the learning algorithm based on the quadratic error criterion is synthesized. This approach combines the benefits of the neural networks, the neuro-fuzzy system, and the wavelet functions approximation. The proposed multidimensional wavelet neuron can be used to solve a very large class of information processing problems for the Internet of Things applications when signals are fed in online mode from many sensors. The proposed approach is uncomplicated for computational realization and can be implemented in hardware for IoT systems. The proposed learning algorithm is characterized by a high rate of convergence and high approximation properties.

Olena Vynokurova, Dmytro Peleshko, Semen Oskerko, Vitalii Lutsan, Marta Peleshko

Simulation of Shear Motion of Angular Grains Massif via the Discrete Element Method

Dynamics of granular materials is a challenge for predictability of their response under dynamic load due to the complex behavior of granular systems. In this report, we consider the granular system composed of the polyhedral particles, namely cubes, and study system’s dynamics via the discrete element method which allows us to describe the interactions between cubes in detail. On the base of modeling the shear motion of granular medium, the statistical laws of multiparticle system dynamics are observed. These studies are extremely important for the geophysics, material science, etc.

Sergiy Mykulyak, Vasyl Kulich, Sergii Skurativskyi

Model of Reconfigured Sensor Network for the Determination of Moving Objects Location

In recent years, the implementation of distributed sensor networks has been allowing to create more and more sophisticated systems especially for environment monitoring. Among those applications are detecting, locating and tracking static or moving objects of interest. The advances of sensor technologies open up new possibilities of solving those sorts of tasks. One of the approaches is the Time Difference of Arrival algorithm, which is designed for locating an acoustic source. Moreover, sensor based systems usually produce a great deal of information streams those are subjected to further analysis: clustering, classification, regression etc. Hence, it is important to develop effective methods of determinations of moving object location based on a special model of reconfigured sensor network. The aim of the research is to propose a new model of reconfigured sensor network for the determination of the moving objects location using Time Difference of Arrival algorithm. The simulation study is presented.

Andrii Petrashenko, Denis Zamiatin, Oleksii Donchak

Research and Development of a Stereo Encoder of a FM-Transmitter Based on FPGA

This paper describes the research and development of the digital stereo encoder FM transmitter including its implementation on Field Programmable Gate Array (FPGA). The development of structural schemes of the digital part of the FM transmitter exciter, the stereo encoder and the digital synthesizer of the sine wave on the FPGA is also described. Paper includes a description of development of a digital synthesizer of a sinusoidal signal on a FPGA, which uses a tabular method to generate the sinusoidal wave, fourth part of its period is written to memory and the rest of the period is calculated using the first part. To generate five sinusoids of different frequencies in a stereo encoder, only one table in memory used. The simulation of the stereocoder on the FPGA in carried out in the specialized Computer-Aided Design (CAD). The graphs of the left and right balance signals, the sum and difference of these signals, the signal of difference of the two sine waves which have their amplitude modulated and with a carrier signal of 19 kHz and the complex stereo signal are constructed. After receiving a complex stereo signal its frequency modulation is carried out with a carrier signal of 100 MHz, the FPGA chip outputs the frequency code of modulated signal.

Volokyta Artem, Shymkovych Volodymyr, Volokyta Ivan, Vasyliev Vladyslav

Video Shots Retrieval with Use of Pivot Points

Intelligent analysis of video data is inextricably linked to methods aimed at reducing the amount of initial data necessary for processing in various ways. In this paper, we propose an approach that allows us to reduce the amount of processed video data by excluding it from consideration that is inappropriate for the query. This is achieved by the pivot points analysis of the original data clusters. If the pivot point to be compared is far from the query, then the entire cluster is also far from the query, respectively. Thus, it is possible to significantly reduce the number of operations of query comparison with data and, accordingly, speed up the process.

Dmytro Kinoshenko, Sergii Mashtalir, Vladyslav Shlyakhov, Mykhailo Stolbovyi

Imbalance Data Classification via Neural-Like Structures of Geometric Transformations Model: Local and Global Approaches

The classification task is one of the most widespread among the tasks of Data Mining - spam detection, medical diagnosis, ad targeting, risk assessment and image classification. However, all these tasks have a common feature - training dataset can be unbalanced, the number of instances of the target class can be less than one percent of all data. In this article, we compare the results of solving one of these problems using the most common classification methods (Random Forest Leaner, Logistic Regression, SVM). The article describes a new classification method based on neural-like structures of Geometric Transformations Model (local and global approaches) and compares their result with the obtained results.

Roman Tkachenko, Anastasiya Doroshenko, Ivan Izonin, Yurii Tsymbal, Bohdana Havrysh

Information Technology of the System Control of Water Use Within River Basins

One of the key problems of system control of water use is the flushing of river beds with the water from reservoirs. To control the process of flushing, an information technology has been developed. Under the conditions of sustainable development, it provides the optimization of water use and contributes to the ecological rehabilitation within the river basin. The combined operational control of the distribution of water masses and pollution transformation along the river bed is implemented by the balance method. The balance difference equations describe the dynamics of water in the upper and lower layers, its movement and enable to visualize the pollution process. Optimization of the options for operational control is based on a scenario analysis. Multicriteria optimization methods are used based on economic and environmental criteria. Water quality assessment was improved by using the neural network in the monitoring system. The neural network provides a feedback coupling within the control system.The information technology is adapted to the conditions of water supply for irrigation providing the ecological rehabilitation of the Ingulets River. A scenario analysis of some options for flushing operational control was made. The scenarios are estimated by the economic criterion for saving water resources and the ecological criterion for river rehabilitation. The decision making is based on the Pareto principle. The recommended optimal scenario provides a water supply for the period of 7 days applying small portions of water to prevent pollution sedimentation within the flood plain. The displacement of the mineralized water lens is carried out with less water consumption. It enables to provide a regulatory water supply for irrigation.

Pavlo Kovalchuk, Hanna Balykhina, Roman Kovalenko, Olena Demchuk, Viacheslav Rozhon

Data Mining for a Model of Irrigation Control Using Weather Web-Services

The article deals with obtaining forecast weather data, its processing and use in mathematical models for irrigation management in the application of Decision Support System. The data obtained from the weather service databases on temperature and humidity are summarized on the basis of potential evapotranspiration calculations. Forecast data on precipitation is handled under uncertainty. On the basis of the weather forecast data, moisture transfer is modeled, soil moisture is predicted, that is, new knowledge is obtained about the state of soil moisture, on the basis of which Decision Support System generates a certain management solution. Due to the Internet and the use of the online regime, the decision maker does not directly process large arrays of weather information, but receives Decision Support System solutions as quickly and easily as possible.

Volodymyr Kovalchuk, Olena Demchuk, Dmytro Demchuk, Oleksandr Voitovich

Hardware and Software Complex for Automatic Level Estimation and Removal of Gaussian Noise in Images

The hardware and software complex for an automatic level estimation and the removal of Gaussian noise in digital images has been developed. The complex consists of video cameras, computers and the software developed in MATLAB.The calculation of Gaussian noise level is performed by the developed method, which is based on image filtering and iterative selection of region of interest. As the noise level, its standard deviation is considered. The developed software is designed for the video camera adjustment and is aimed at obtaining a series of images of one object, taken with video camera under the same lighting conditions, but at different values of the brightness parameter. For each image from the series, calculation of noise level and signal-to-noise ratio enable one to determine the optimal value of the brightness parameter.The mathematical model, the method and the software for automatic removal of Gaussian noise in digital images with the use quasi-optimal Gaussian filter have been developed. A signal is described by the sum of the sinusoids, the amplitudes and periods of which are calculated on the basis of the energy spectrum of the original image. The quasi-optimal value of the standard deviation of the Gaussian filter kernel is obtained as the value at which the standard deviation between the filtered image brightness and the signal brightness is minimized. The accuracy of the developed filtration method has been verified by removing Gaussian noise in a set of 100 test images.

Serhiy V. Balovsyak, Khrystyna S. Odaiska

Building a Generalized Peres Gate with Multiple Control Signals

We consider a physical realization of the generalized quantum Peres and Toffoli gates with n-control signals, implemented in a one-dimensional chain of nuclear spins (one half) in a strong magnetic field coupled by an Ising interaction. Quantum algorithms in such system can be performed by transverse electromagnetic radio-frequency field using a number of resonant π-pulses on the initial states. The maximum number of π-pulses needed for the implementation of the Peres gate with n-control signals is discussed. It is found, that required number of π-pulses linearly scales with the number n of the control signals of the generalized quantum Peres gate. Comparison of our studies with the known values of the quantum cost of the generalized Peres gate allows us to suggest that proposed physical implementation of the gate is more efficient. The fidelity parameter is used to study the performance of the generalized Peres gate as a function of the relative error of the resonance frequency. The limits of an imbalance of the generator settings remaining the gate well defined are determined.

O. I. Rozhdov, I. M. Yuriychuk, V. G. Deibuk

Mathematical Model of Queue Management with Flows Aggregation and Bandwidth Allocation

The flow-based mathematical model of queue management on routers of telecommunication networks on the basis of optimal aggregation of flows and bandwidth allocation in queues has been further developed. The novelty of the model is that when flows are queued, they are aggregated based on the comparison of the classes of flows and queues in the course of analyzing the set of classification characteristics. Moreover, the result of calculating the percentage of unused queues in the course of optimal aggregation of flows provided assuming the hypothesis of a uniform or normal distribution of flow service classes within the framework of the model under consideration is presented. Applying the uniform distribution law, it was possible to reduce the number of unused queues by 20%, and by 30% for the normal distribution. Research results confirmed the efficiency of the proposed model.

Oleksandr Lemeshko, Tetiana Lebedenko, Oleksandra Yeremenko, Oleksandr Simonenko

Planning Automation in Discrete Systems with a Given Structure of Technological Processes

In this paper, we consider mathematical models and algorithms for efficient planning process automation in discrete systems of a wide class (innovative software development, small-scale production). An effective solution of the proposed models is based on earlier results of M.Z. Zgurovsky, A.A. Pavlov, E.B. Misura, and E.A. Khalus in the field of intractable single stage single machine scheduling problems.

Alexander Anatolievich Pavlov, Elena Andreevna Khalus, Iryna Vitalievna Borysenko

Fault-Tolerant Multiprocessor Systems Reliability Estimation Using Statistical Experiments with GL-Models

The article is focused on the reliability estimation of fault-tolerant multiprocessor systems with huge number of processors and complex behavior of the systems on its processors failures. A universal method for the reliability estimation of such fault-tolerant multi-processor systems for a given time period is proposed. The method is based on conducting statistical experiments (Monte-Carlo) with models that adequately reflect the behavior of the fault-tolerant multiprocessor systems in the flow of failures. For that purpose, it is suggested using GL-model, which is a graph with special way formed Boolean functions assigned to its edges. The questions of synthesis, minimization and transformation of such models are considered. The article addresses the statistical estimation error (Monte-Carlo Error). The upper bound for calculating the error before conducting statistical experiments is suggested. It is shown that the error could be estimated more precisely using the results of conducted statistical experiments. Correspondent statistical estimator is proposed.

Alexei Romankevich, Andrii Feseniuk, Ivan Maidaniuk, Vitaliy Romankevich

Optimal Control of Point Sources in Richards-Klute Equation

This article represents an approach to humidity control in porous media, which combines linearization with numerical methods. The main problems and several ideas to solve them are mentioned. The main interest for our research is humidity regulation, described by Richards-Klute equation. The optimization problem is to minimize the difference between a reached state and a desired state.Modelling moisture transport in porous media requires taking into account the processes of heat transfer, chemical and physical processes, as they have a considerable influence on characteristics of the medium.First of all, a mathematical model is developed with a number of simplifications: moisture incompressibility, constant external pressure, limitations on transfer or isothermal requirements. Then, it is often preferable to make a transition to linear problem, as this case is explored and it allows us to use more theoretical background for the research. After that, numerical models and time and space discretization are constructed according to the related problem. When the process is represented in a suitable way, control and optimization problems arise and should be solved.

A. Tymoshenko, D. Klyushin, S. Lyashko

Method of Calculation of Averaged Digital Image Profiles by Envelopes as the Conic Sections

The method of calculation of averaged digital image profiles has been developed. The image profile is dependence of the value of the pixel brightness on the image coordinate along the specified line segment. The corresponding software was developed in the MATLAB system. Profile analysis is widely used in the processing of experimental and simulated digital images, especially if the images contain band-shaped objects. The presence of bands is characteristic of electron diffraction images, X-ray moire images, images of scanning probe microscopy, optical medical images, and others. Cross-section profiles contain important information about the explored object, since they describe the one-dimensional distribution of object brightness.A single band profile may contain an appreciable noise component. Therefore, in order to increase the signal-to-noise ratio, a series of band profiles were obtained, on the basis of which the averaged profile was calculated. The calculation of the average profile is relatively easy to implement in cases when all the band profiles have the same scale, and line consisting of their starting points is parallel to line consisting of their ending points. However, the most of the experimental images undergo the geometric distortions, and the lines consisting of starting or ending points of the profiles correspond to conic-shaped curves. Therefore, in this paper we proposed firstly to approximate the curves consisting of starting/ending points by two envelopes, and then to calculate a series of profiles on the basis of these envelopes. Circles, ellipses, parabolas and hyperbolas were used as envelope functions.The mathematical model, algorithm and software for calculating enveloping profiles in images are developed. The envelopes are calculated on the basis of the coordinates of the base points, which are determined by the user or calculated through the contours of the band. The high accuracy of the developed method for calculating averaged profiles has been confirmed in the processing of images of electron and X-ray diffraction, atomic force microscope, optical and medical images etc.

Serhiy V. Balovsyak, Oleksandr V. Derevyanchuk, Igor M. Fodchuk

On Formalization of Semantics of Real-Time and Cyber-Physical Systems

In the article we describe theoretical foundations of a framework for formalizing semantics of real-time and cyber-physical systems in interactive theorem proving environments. The framework is based on viewing a system as a predicate on system’s executions which are modeled as functions from the continuous time domain to a set of states. We consider how it can be applied to the safety verification problems. The proposed framework may be useful in verification of software for real-time and cyber-physical systems and of the corresponding development tools.

Ievgen Ivanov, Taras Panchenko, Mykola Nikitchenko, Fabunmi Sunmade

Optimization of Operation Regimes of Irrigation Canals Using Genetic Algorithms

The paper focuses on the problem of irrigation canals operation regimes optimization which is important for minimizing operating expenses and ensuring stable water supply for agriculture. Regarding the complexity of the optimization problem we propose to solve it using genetic algorithm that searches for per-hour pumping station units’ operation regimes, their pumping rates and the heights of controllable weirs and gate structures that should guarantee water levels and flow velocities needed by farmers. As an underlying direct problem we use an initial-boundary value problem for one-dimensional Saint-Venant equations system discretized by finite difference scheme. The algorithms of direct and optimization problems solution was applied to model water flow and determine optimal water supply rates for North Crimean canal.

V. O. Bohaienko, V. M. Popov

Monitoring of Laser Welding Process Using Its Acoustic Emission Signal

Processing and identification of signals informatively characterizing any technological process, especially the signals of acoustic and electromagnetic emission, is a complex multi-level task. Many studies are devoted to solving it. However, no comprehensive system for analyzing these signals has been represented yet. This study found out that there is a relationship between the parameters of laser welding technological process and registered acoustic emission signals, and that relationship is independent on investigation methods. The signals of acoustic and electromagnetic emission have been chosen as feedback signals of laser welding technological process, because their transmission and analysis require minimal time and computational resources. The paper describes the peculiarities of channels shielding for transmitting the technological data, in particular, the circuits of applying the shields for electromagnetic protection are given and their efficiency is shown.

Volodymyr Shelyagin, Ievgen Zaitsev, Artemii Bernatskyi, Vladyslav Khaskin, Ivan Shuba, Volodymyr Sydorets, Oleksandr Siora

QoS Ensuring over Probability of Timely Delivery in Multipath Routing

This article proposes a solution aimed at improving such an important Quality of Service indicator as the probability of timely delivery of packets based on optimization of multipath routing processes in infocommunication networks. The novelty of the proposed solution consists in using a dynamic model of the operation of the network routers interfaces, which allowed to take into account the nonstationary nature of the change in their state and to track the nonlinear dynamics of the average delay both on individual network interfaces and along the used set of routes in the network. This allowed formulating in an analytical form an expression for calculating the probability of timely delivery of packets, the maximum of which was the criterion of optimality in solving the problem of multipath routing in the infocommunication network. The results of the research have shown that the application of the proposed routing solution significantly improves the probability of timely delivery of packets in comparison with the results obtained during the implementation of the Traffic Engineering technology.

Oleksandra Yeremenko, Oleksandr Lemeshko

Icing Thickness Prediction of Overhead Power Transmission Lines Using Parallel Coordinates and Convolutional Neural Networks

In this paper, a model used for predicting icing thickness of power transmission lines is proposed. An algorithm derived from parallel coordinates is applied to convert the high-dimensional source data, which includes relevant factors about the icing thickness of power transmission lines, to two dimensional images. Then the images are used for training convolutional neural networks (CNNs). Finally, the icing thickness is predicted by the trained CNNs. In this way, our system combines the advantages of information visualization and CNNs. It provides an universal method to process multi-dimensional numerical data with CNNs algorithmically and in a real sense.

Baiming Xie, Chi Zhang, Qing-wu Gong, Koyamada Koji, Hua-rong Zeng, Li-jin Zhao, Hu Qiao, Liang Huang

Prediction of Dissolved Gas Concentration in Oil Based on Fuzzy Time Series

The prediction of dissolved gas content in transformer oil is helpful for early detection of latent faults in transformer, and it has important guiding significance for better condition based maintenance. In view of the abundant data of transformer DGA, and that the trend of the change of dissolved gas content in oil under normal running condition is not obvious, a prediction method based on fuzzy time series model is proposed. Consider that the change in dissolved gas content in oil is interaction and influenced, in this paper, the classical fuzzy time series model is improved from the view of domain division, and propose a multi factor fuzzy time series model based on spatial FCM domain partition. The example analysis shows that the method can well fit the changing trend of DGA data, and compared with the classic fuzzy time series model and the one-dimensional FCM fuzzy time series model, the superiority of the improved model in prediction is verified.

Jun Liu, Lijin Zhao, Liang Huang, Huarong Zeng, Xun Zhang, Hui Peng

Perfection of Computer Algorithms and Methods

Frontmatter

A Comprehensive Analysis of the Bat Algorithm

Optimization is one of the most challenging problems that has received considerable attention over the last decade. The bio-inspired evolutionary optimization algorithms due to their robustness, simplicity and efficiency are widely used to solve complex optimization problems. The Bat algorithm is one of the most recent one from this category. Given that the original Bat algorithm is vulnerable to local optimum and unsatisfactory calculation accuracy, the paper presents detailed analysis of its main stages and a measure of their influence on the algorithm performance. In particular, the global best solution acceptance condition, the way a new solution is generated by random flight and the local search procedure implementation have been studied. The ways to overcome the original algorithm’s flaws have been suggested. Their effectiveness has been proved by numerous computational experiments.

Yury Zorin

Complex Steganalytic Method for Digital Videos

In work the analysis of steganalytic algorithms realizing methods which are earlier developed by the author aimed to detect the additional information attachments in digital videos is carried out. Comparison of efficiency of steganalytic algorithms allowed to develop practical recommendations for use of the proposed methods which formed the basis of a complex steganalytic method of detecting attachments of additional information in digital videos. The complex method proposed in work is capable to detect hidden information embedded into digital videos under different conditions, including small values of hidden capacity, irrespective of a format and color representation of an original container.

A. V. Akhmametieva

Video Data Compression Methods in the Decision Support Systems

The paper presents the developed methods of video data compression and decompression providing the maximum degree of intersecting information flows of critical video information at the given quality levels of digital video images. Due to the developed methods, mathematical models and techniques, the technology of video data compression has been improved on the basis of reducing the structural redundancy under limited loss of visualization quality. The proposed technology provides an increased level of effective functioning of communication channels and critical video information processing, as well as presents an opportunity for information support and improved quality of decision-making in crisis situations.

V. Barannik, O. Yudin, Y. Boiko, R. Ziubina, N. Vyshnevska

Method of Searching Birationally Equivalent Edwards Curves Over Binary Fields

This paper is devoted to increasing of performance of digital signature algorithms based on elliptic curves over binary fields. Group operations complexity on Edwards curves are less than on Weierstrass curves and have immunity to some side channel attacks. Hence, it is interesting to search birationally equivalent curves in Edwards form for curves in Weierstrass form presented in NIST recommended curves list. It allows using operations over points on Edwards curve in intermediate computations in scalar multiplications over curves in Weierstrass form. This approach improves the performance and security of digital signature.

Zhengbing Hu, Sergiy Gnatyuk, Maria Kovtun, Nurgul Seilova

Criteria for Evaluating the Effectiveness of the Decision Support System

The task of increasing effectiveness for decision-making support in the condition of information protection is considered. The main criteria for assessing the processes effectiveness of forming an information security system in conditions of limitations and uncertainties are described. The integral criteria of effectiveness consists of sub-criteria: efficiency, quality, continuity, reliability, uniqueness, risk. In this article, the author suggests using risk criteria for implementing threats to assess effectiveness.

V. Tolubko, S. Kozelkov, S. Zybin, V. Kozlovskyi, Y. Boiko

Prospects for the Application of Many-Valued Logic Functions in Cryptography

The paper considers development of cryptographic methods based on the principles of many-valued logic. The results concerning the construction of block and stream cryptographic algorithms based on functions of many-valued logic are presented. The synergy of the principles of many-valued logic and the variable fragmentation of the block made it possible to construct an effective block symmetric cryptographic algorithm. The results of computational experiments confirm its high cryptographic quality and easily scalable number of protection levels. As shown by experiments, the principles of many-valued logic are an excellent basis for the construction of gamma generators (the basis of stream ciphers), which are based on the use of triple sets of ternary bent-sequences. The paper outlines the scope of the tasks, the solution of which is necessary for the further development in this direction of cryptography.

Artem Sokolov, Oleg Zhdanov

Suspicious Object Search in Airborne Camera Video Stream

In some areas of drone application an object search task arises. Also there are cases where usage of standard approaches, e.g. object detection methods or fully manual video view, could be complicated or problematic. However it is possible to find local image (video frame) areas where suspicious object potentially can be present in such cases. We propose (i) an algorithm for suspicious object search in real time and (ii) an automated system (drone and ground control station) based on it, show brief results of its testing, make conclusions about further research direction.

Artem Chyrkov, Pylyp Prystavka

Stochastic Optimization Method in Computer Decision Support System

The questions of parameter optimization are considered in the article. These parameters describe technological processes at ore-dressing plants. There are many problems in creating of automated control systems for such technological processes. Among them are a large number of industrial parameters, the nondeterministic nature of physical and mechanical properties of the raw materials, and many disturbing influences. Thus, to solve these problems authors propose to use an intelligent computer decision support system. It allows calculating a regression equation of some optimization criterion. The complete Kolmogorov-Gabor polynomial is used as a regression model. In addition, the possibility of applying the differential evolution method is analysed. The stochastic optimization method has been compared with the full enumeration method, gradient descent method and Monte Carlo. A simple function with an extremum has been used as an example for demonstrating of search efficiency.

Andrey Kupin, Ivan Muzyka, Dennis Kuznetsov, Yurii Kumchenko

Optimal Control of Retrial Queues with Finite Population and State-Dependent Service Rate

The research of wide class of retrial queuing systems faces the problem of calculating characteristics of the system in stationary regime. Markov chain that describes service process in such system is multidimensional and its transaction matrix usually does not have special properties that would streamline the explicit solution of Kolmogorov set of equations. In addition, the probabilities of transition between states of the controlled system depend on its current state that complicates their obtaining even more. Therefore, only the simplest models are explicitly researched on this moment.In this paper we consider a finitesource retrial queue with c servers and controlled parameters. The primary calls arrive from n customers. Each customer after some random period of time which is exponential distributed random variable tries to get service and is served immediately if there is any free server. Service times are also exponentially distributed. The customer who finds all servers busy leaves the system and returns after an exponential time. Two- and three-dimensional Markov models that describe threshold and hysteresis control policies are taken into account. Explicit vector-matrix representations of stationary distributions are main results in both cases. Also we state and give an algorithm for solving a multi-criteria problem of maximization of total income from the system.

Vadym Ponomarov, Eugene Lebedev

Deobfuscation of Computer Virus Malware Code with Value State Dependence Graph

This paper deals with improvement of malware protection efficiency. The analysis of applied scientific research on malware protection development has shown that improvement of the methods for deobfuscation of program code being analyzed is one of the main means of increasing efficiency of malware recognition. This paper demonstrates that the main drawback of the modern-day deobfuscation methods is that they are insufficiently adapted to the formalized presentation of the functional semantics of programs being tested. Based on the research results, we suggest that theoretical solutions which have been tried out in program code optimization procedures may be used for code deobfuscation. In the course of the study, we have developed a program code deobfuscation procedure utilizing a value state dependence graph. Utilization of the developed procedure was found to enable presentation of the functional semantics of the programs being tested in a graph form. As the result, identification of malware based on its execution semantics became possible. The paper shows that further research should focus on the development of a method for comparison of the value state dependence graph of the program being tested with corresponding graphs of security software and malware.

Ivan Dychka, Ihor Tereikovskyi, Liudmyla Tereikovska, Volodymyr Pogorelov, Shynar Mussiraliyeva

Optimization of Processor Devices Based on the Maximum Indicators of Self-correction

It is proposed to characterize the state of digital processing devices’ outputs with a system of probabilities, where for any binary processing results the probability of getting the same real result is set, if it is theoretically possible. Since the outputs of some devices in their compositions are the inputs of other devices, than such a probability system is universal, that allows taking into account faults of hardware means. For the original inputs the models of probabilistic information converters (data distortion on the initial inputs system) are used, on the outputs of which the indicated probabilities system exists, allowing for distortion of the input data only. Heuristic algorithm for optimal encoding (as per the maximal possible self-correction) of digital machines (as the models of processing devices) is proposed for their structural synthesis. The obtained results enable reaching optimize results on the design stage, that are directed to increase veracity of computer systems processor devices’ functioning.

Y. Klyatchenko, G. Tarasenko, O. Tarasenko-Klyatchenko, V. Tarasenko, O. Teslenko

Simulation of Multithreaded Algorithms Using Petri-Object Models

Multithreaded programming used for the development of faster algorithms is a very effective method. However, the designing, testing and debugging of nontrivial programs are not easy and need to be improved. Stochastic behavior of threads entails their conflicts and in some cases the unpredictable result of the program. Stochastic Petri nets are widely used for the investigation of concurrent processes in many areas: manufacturing, computer systems, workflow management. In this research stochastic multichannel Petri net is considered as a tool for multithreaded programs modeling. The correspondence between main instructions of multithreaded program and fragments of stochastic Petri net is discovered. Petri-object model’s formalization and software are used for complicated models’ constructions. This approach allows duplicating objects with the same dynamics and aggregating them in model. Models that present the concurrent functioning of multithreaded Java programs are considered. Model’s verification indicates its accuracy. The results of experimental research of these models show a strong impact the values of time delay.

Inna V. Stetsenko, Oleksandra Dyfuchyna

On-line Robust Fuzzy Clustering for Anomalies Detection

Widly-used fuzzy c-means algorithm (FCM) has been utilized, with much success, in a variety of applications. The algorithm is known as an objective function based fuzzy clustering technique that extends the use of classical k-means method to fuzzy partitions. However, one of the most important drawbacks of this method is its sensitivity to noise and outliers in data since the objective function is the sum of squared distance. New robust fuzzy clustering algorithm (RFC) for exploring of signals of different nature taking into account the presence of noise with unknown density distributions and anomalous outliers in the data being analyzed is presented in this paper. By rejection of the Euclidean distance in the objective function the insensibility to the noise and outliers in the data was archived. Our approach introduces a robust probabilistic clustering procedure and is based on a modified objective function.

Yevgeniy Bodyanskiy, Oleksii Didyk

Data Stream Clustering in Conditions of an Unknown Amount of Classes

An on-line modified X-means method is proposed for solving data stream clustering tasks in conditions when an amount of clusters is apriori unknown. This approach is based on an ensemble of clustering neural networks that contains the self-organizing maps by T. Kohonen. Each clustering neural network consists of a different number of neurons where an amount of clusters is connected to a quality of the clustering process. All ensemble’s members process information which is fed sequentially to the system in a parallel mode. The effectiveness of the clustering process is determined using the Caliński-Harabasz index. The self-learning algorithm uses a similarity measure of a special type. A main feature of the proposed method is an absence of the competition step, i.e. neuron-winner is not determined. A number of experiments has been held in order to investigate the proposed system’s properties. Experimental results have confirmed the fact that the system under consideration could be used for solving a wide range of Data Mining tasks when data sets are processed in an on-line mode. The proposed ensemble system provides computational simplicity, and data sets are processed faster due to the possibility of parallel tuning.

Polina Zhernova, Anastasiya Deyneko, Zhanna Deyneko, Irina Pliss, Volodymyr Ahafonov

Stegoalgorithm Resistant to Compression

In this paper, we propose a choice of parameters for constructing an efficient stegoalgorithm that is resistant to compression. In order to preserve the reliability of perception of formed stegoimage, we analyze changes of second singular value number for different compression coefficients Q = {70, 80, 90, 100}. Experimental results show that we can choose second singular value number as one of the parameters. In the paper, authors proposed the efficient stegoalgorithm resistant to compression with different quality of compression. It was added a condition that allows to decode the information if the block is close to the maximum border of the range of brightness values 255. It was done the rate of reliability of perception and normalized cross-correlation coefficient.

M. A. Kozina, A. B. Kozin, O. B. Papkovskaya

NP-Hard Scheduling Problems in Planning Process Automation in Discrete Systems of Certain Classes

In this paper, we consider an intractable problem of total tardiness of tasks minimization on single machine. The problem has a broad applications solutions during planning process automation in systems in various spheres of human activity. We investigate the solutions obtained by the exact algorithm for this problem earlier developed by M.Z. Zgurovsky and A.A. Pavlov. We propose an efficient approximation algorithm with $$ O\left( {n^{2} } \right) $$On2 complexity with estimate of the maximum possible deviation from optimum. We calculate the estimate separately for each problem instance. Based on this estimate, we construct an efficient estimate of the deviation from the optimum for solutions obtained by any heuristic algorithms. Our statistical studies have revealed the conditions under which our approximation algorithm statistically significantly yields a solution within 1–2% deviation from the optimum, presumably for any problem size. This makes possible obtaining efficient approximate solutions for real practical size problems that cannot be solved with known exact methods.

Alexander Anatolievich Pavlov, Elena Borisovna Misura, Oleg Valentinovich Melnikov, Iryna Pavlovna Mukha

Statistic Properties and Cryptographic Resistance of Pseudorandom Bit Sequence Generators

Generators of pseudorandom sequences are widely used in practice. Generators of pseudorandom bit sequences occupy a special place among them; they are necessary for solving a number of important tasks, for example, for strong cryptography. The impossibility of predicting the following values of pseudorandom sequences is one of the basic requirements for such generators. Otherwise, these generators cannot be used to protect of information. It is generally accepted that if the stochastic sequence is stationary, then the prediction of such sequence is impossible. Our research shows that there are invariants for specific pseudorandom sequences that can be used to this prediction.The article is devoted to the method of prediction of pseudorandom bit sequences. The values of the autocorrelation coefficients for some lags are used. Good results are obtained for software-implemented stationary stochastic sequences.

V. Maksymovych, E. Nyemkova, M. Shevchuk

Organization of Network Data Centers Based on Software-Defined Networking

In this paper, we propose and substantiate organization of modern data center networks (DCN) with Fat Tree topology based on software-configurable network technology (SDN). In order to increase efficiency of traffic engineering in DCN with Fat Tree topology, we propose to construct a set of disjoint paths. We also propose an improved deep search algorithm that enables us to reduce time needed for constructing such a set due to taking into consideration self-similarity of DCN topology. Main difference of this algorithm, compared to known analogies, lies in possibility to construct a maximal set of optimal disjoint paths. Applying SDN technology enabled us to increase efficiency of functioning of large-scale DCNs. Central SDN controller possesses full information about paths and trees that generated them. This enables us to optimize the paths according to specified metrics in the process of their construction. We show the application of the proposed method with an example of constructing a set of disjoint paths in DCN.

Yurii Kulakov, Sergii Kopychko, Victoria Gromova

Management of Services of a Hyperconverged Infrastructure Using the Coordinator

Modern data centers’ providers are gradually moving away from traditional and multi-vendor IT infrastructures to open, standardized and interchangeable solutions that are based on a software defined approach to managing data center resources. The authors analyze the architectural features, requirements, limitations, hardware and software of hyperconverged infrastructures and their advantages in comparison with traditional and converged architectures deployed in data centers. The authors propose to employ two-level coordination schema to manage compute, storage, network and virtualization subsystems of hyperconverged infrastructure along with the self-management algorithms inside these subsystems.

Oleksandr Rolik, Sergii Telenyk, Eduard Zharikov

Detection of MAC Spoofing Attacks in IEEE 802.11 Networks Using Signal Strength from Attackers’ Devices

The main goal of this project is to improve intrusion detection process in IEEE 802.11 based networks in order to provide conditions for further interaction between attackers and honeypot. In order to gather metadata from clients’ devices, part of Wi-Fi Honeypot as a Service model was applied in the experiment, and for the first time ever. MAC addresses of access points and clients’ devices, probe requests, beacons and power of signal were used as basic data for further processing. Gathered metadata was used to detect malicious activities against network which is under defense and its clients. Several modifications of MAC spoofing attack were provided by authors in order to find attacks’ fingerprints in Wi-Fi ether. Besides base MAC spoofing attack authors suggested a method which allows to identify modification of MAC spoofing where attacker uses power antenna. Also, the new synchronization method for external elements of honeypot was proposed. It is based on centralized random message generation and allows to avoid detection from attackers’ side.

R. Banakh, A. Piskozub, I. Opirskyy

Steganographic Method of Bitwise Information Hiding in Point-Defined Curves of Vector Images

In this paper the authors propose steganographic method of bitwise information hiding, which allows embedding information in vector images by splitting point-defined curves into segments. Due to the invariance property of the curves of this type (B-splines, NURB curves, Bezier curves, Hermite curves), the proposed method will provide resistance to active attacks based on affine transformations. On the basis of the proposed method and the properties of the Bezier curves, StegoBIT algorithm was realized. This algorithm allows to embed information in the Bezier curves of the third degree and provides resistance to active attacks based on affine transformations. An experimental study of the stability of proposed algorithm for affine transformations was carried out. 30 arbitrary SVG images were selected for the experiment. Their structural configuration contained parameters for constructing Bezier curves. The information of different sizes was hidden in the curves, by way of its gradual division into visually identical sets of segments. The affine transformations such as transfer, rotation, almost rotation, biasing for the abscissa and ordinate axis and proportional and disproportional scaling was gradually carried out with the obtained steganocontainer. The obtained results of the experiment demonstrate the effectiveness and stability of the proposed StegoBIT algorithm to various transformations that are based on affine transformations.

Oleksiy Kinzeryavyy, Iryna Kinzeriava, Alexander Olenyuk, Krzysztof Sulkowsky

Self-learning Procedures for a Kernel Fuzzy Clustering System

The paper exemplifies several self-learning methods through the prism of diverse objective functions used for training a kernel fuzzy clustering system. A self-learning process for synaptic weights is implemented in terms of the competitive learning concept and the probabilistic fuzzy clustering approach. The main feature of the introduced fuzzy clustering system is its capability to cluster data in an online way under conditions when clusters are rather likely to be of an arbitrary shape (which cannot usually be separated in a linear manner) and to be mutually intersecting. Generally speaking, the offered system’s topology is mainly based on both the fuzzy clustering neural network by Kohonen and the general regression neural network. When it comes to training this hybrid system, it is grounded on both the lazy and optimization-based learning concepts.

Zhengbing Hu, Yevgeniy Bodyanskiy, Oleksii K. Tyshchenko

Information Technology of Data Protection on the Basis of Combined Access Methods

The main task of the article is to develop information technology (IT) for data protection based on combined access methods. The need to create a reliable IT for data protection is conditioned by an active increase in confidential information and unauthorized access. The article presents the existing static and dynamic biometric access methods, the evaluation of biometric technologies is reviewed: market segmentation, access errors and a general table of characteristics. A combined access method based on Acuity Market Intelligence and International Biometric Group data is proposed, which includes a combination of voice and face - a multimodal method. The article contains the calculation of the work accuracy by using the characteristic curves: DET (Detection error trade-off), which establish the relationship between FRR errors (False Rejection Rate) and FAR (False Acceptance Rate) and identify the advantages of a multimodal biometric personnel identification system comparing the unimodal one. Also, the mathematical model of IT for data protection has been developed. The proposed scheme of information links is developed for the IT for data protection based on combined access methods.

Andrey Kupin, Yurii Kumchenko, Ivan Muzyka, Dennis Kuznetsov

Neural Network Algorithm for Accuracy Control in Modelling of Structures with Changing Characteristics

The paper is devoted to the creation of neural network algorithm for control of the accuracy of durability calculation in problems of modelling the behavior of structures with changing characteristics, in particular, corroding trusses. In contrast to known methods, the approach suggested in this paper takes into account the change of forces in elements of the truss over time. First, the analysis of corrosive wear models is given to choose the most suitable one for further research. Then, the mathematical statement of durability determination problem is given. The paper describes the approach to the approximation of the numerical solution error for the durability problem. To build an approximating function, artificial neural networks are used. The architecture of these networks and the procedure of their training are described further in the paper. At the end, the results of numerical experiments, which prove the correctness of the chosen approach, are given. The developed algorithm can be especially effective in solving optimization problems with constraints on the durability of a structure. The same approach can also be generalized to other classes of structures.

Dmitriy Zelentsov, Olga Denysiuk

The Study of Visual Self-adaptive Controlled MeanShift Algorithm

This paper proposed a self-adaptive visual control system which is controlled by human eyes, the visual image tracking algorithm utilized by this system is also introduced in this paper. Through eye-gaze detection and electrical device control corresponding, it will automatically respond to the provided interface. This paper mainly introduces helmets and remote vision-based eye-gaze tracking algorithms; the algorithm has good performance in aspects of usability and adaptability.

P. H. Wu, G. Q. Hu, D. Wang

Computer Science for Medicine and Biology

Frontmatter

Method for Research of the Human Static Equilibrium Function

The paper deals with problems of determination of the informative indices, which characterize the function of the human balance (human static equilibrium). The kefalographic method for research of the human static equilibrium is suggested. The kefalographic plant for this method implementation was modified. The informative indices, which characterize the space dynamic range and features of the human body oscillations relative to the axis z, were determined. Such indices represent the coefficients, which characterize changes of the sampling mathematical expectation $$ K_{{\tilde{m}_{r} }} $$Km~r, variance $$ K_{{\tilde{D}_{r} }} $$KD~r, skewness $$ K_{{\tilde{a}_{r} }} $$Ka~r and kurtosis $$ K_{{\tilde{e}_{r} }} $$Ke~r for the vector projection of central position the human body.

Yurii Onykiienko

Levitating Orbitron: Grid Computing

Mathematical model of interaction for magnetic symmetric top (i.e. a rigid body and magnetic dipole simultaneously) in external magnetic field under uniform gravitational field is presented. Numerical modeling of the top dynamics, i.e. spinning and rotating around the axis of symmetry in axially-symmetric magnetic field is proposed. Investigation of the dynamics in some neighborhood of a given relative equilibrium for physically reasonable parameters of the system was required to generate a set of random trajectories (Monte-Carlo simulation) with small variations of parameters or initial conditions. More than 1000 of trajectories with 100 turns for each have been tested using grid computing on Grid-clusters of Ukrainian Academic Grid. The motion was limited in certain region for the trajectories with disturbed initial conditions and parameters within 1%. Executed analysis shows the possibility of stable motions and levitation in some neighborhood of a given relative equilibrium. It corresponds to the long trajectories observed in a physical experiment.

Stanislav S. Zub, N. I. Lyashko, S. I. Lyashko, Andrii Yu. Cherniavskyi

A Fuzzy Model for Gene Expression Profiles Reducing Based on the Complex Use of Statistical Criteria and Shannon Entropy

The paper presents the technology of gene expression profiles reducing based on the complex use of fuzzy logic methods, statistical criteria and Shannon entropy. Simulation of the reducing process has been performed with the use of gene expression profiles of lung cancer patients. The variance and the average absolute value were changed within the defined range from the minimum to the maximum value, and Shannon entropy from the maximum to the minimum value during the simulation process. 311 gene expression profiles from 7129 were removed as non-informativity during simulation process. The structural block diagram of the step-by-step data processing in order to remove non-informativity gene expression profiles has been proposed as the simulation results.

Sergii Babichev, Volodymyr Lytvynenko, Aleksandr Gozhyj, Maksym Korobchynskyi, Mariia Voronenko

Quality of Symptom-Based Diagnosis of Rotavirus Infection Based on Mathematical Modeling

Rotavirus is the leading cause of severe childhood gastroenteritis worldwide. The laboratory diagnosis requires testing of fecal specimens with commercial assays that often are not available in low resource settings. Therefore, estimation of rotavirus presence based on clinical symptoms is expected to improve the disease management without laboratory verification.We aimed to develop and compare different mathematical approaches to model-based evaluation of expected rotavirus presence in patients with similar clinical symptoms. Two clinical datasets were used to develop clinical evaluation models of rotavirus presence or absence based on Bayesian network (BN), linear and nonlinear regression.The developed models produced different levels of reliability. BN compared with regression models showed better rotavirus detection results according to optimal cut-off points. Such approach is viable to help physicians refer patient to the group with suspected rotavirus infection to avoid unnecessary antibiotic treatment and to prevent rotavirus infection spread in a hospital ward.

Serhii O. Soloviov, Mohamad S. Hakim, Hera Nirwati, Abu T. Aman, Yati Soenarto, Qiuwei Pan, Iryna V. Dzyublyk, Tatiana I. Andreeva

Optimization of Convolutional Neural Network Structure for Biometric Authentication by Face Geometry

The article presents development of the methodology of using a convolutional neural network for biometric authentication based on the analysis of the user face geometry. The need to create a method of the structural parameters of convolutional neural network adaptation to the expected conditions of its use in a biometric authentication system is postulated. It is proposed to adapt the convolutional neural network structural parameters based on the maximum similarity to the process of recognizing a human face image by an average user considering peculiar properties of computer input and display. A group of principles for optimization methods is formulated by combining this assumption with the generally accepted concept of a convolutional neural network constructing. The number of convolution layers should be equal to the number of the person image recognition levels by an average user. The number of feature maps in the n-th convolutional layer should be equal to the number of features at the n-th recognition level. The feature map in the n-th layer, corresponding to the j-th recognition feature, is associated only with those feature maps of the previous layer that are used to build the specified figure. The size of the convolution kernel for the n-th convolutional layer should be equal to the size of the recognizable feature on the n-th hierarchical level. Based on these principles, a method of the structural parameters optimization of a convolutional neural network has been developed. Advisability of these principles use has been proved experimentally.

Zhengbing Hu, Igor Tereykovskiy, Yury Zorin, Lyudmila Tereykovska, Alibiyeva Zhibek

Model and Principles for the Implementation of Neural-Like Structures Based on Geometric Data Transformations

In this paper, the concept of information modeling based on a new model of geometric transformations is considered. This concept ensures the solutions of the following tasks like pattern recognition, predicting, classification, the principal independent components selection, optimization, recovering of lost data or their consolidation and implementing the information protection and privacy methods. Neural-like structures based on the Geometric Transformations Model as universal approximator implement principles of training and self-training and base on an algorithmic or hardware performing variants using the space and time parallelization principles. Geometric Transformations Model uses a single methodological framework for various tasks and fast non-iterative study with pre-defined number of computation steps, provides repeatability of the training outcomes and the possibility to obtain satisfactory solutions for large and small training samples.

Roman Tkachenko, Ivan Izonin

New Symmetries and Fractal-Like Structures in the Genetic Coding System

The achievements of molecular genetics and bioinformatics lead to significant changes in technological, medical and many other areas of our lives. This article is devoted to new results of study of structural organization of genetic information in living organisms. A new class of symmetries and fractal-like patterns in long DNA-texts is represented in addition to two Chargaff’s parity rules, which played an important role in development of genetics and bioinformatics. Our results provide new approaches for modeling genetic informatics from viewpoints of quantum informatics and theory of dynamic chaos.

Sergey Petoukhov, Elena Petukhova, Vitaliy Svirin

Triply Stochastic Cubes Associated with Genetic Code Numerical Mappings

Knowledge about genetic coding systems are useful for computer science, engineering and education. In this paper we derive triply stochastic cubes associated with the triplet genetic code numerical mappings. We also demonstrate the symmetrical patterns between the entries of the cubes and DNA molar concentration accumulation via an arithmetic sequence. The stochastic cubes based on genetic code were derived by using three kinds of chemically determined equivalences. We have shown that at each stage (Nth step) of matrix evolution, hydrogen bonds expansion is triply stochastic and its accumulation is governed by an arithmetic sequence with a common difference of total number of hydrogen bonds of 5N; the pyrimidines/purines ring expansion is triply stochastic and its accumulation is governed by an arithmetic sequence with a common difference of total number of rings of 3N; and the amino-mutating absence/present expansion is also triply stochastic and its accumulation is governed by an arithmetic sequence with a common difference of total number of amino-mutating of 1N. Data about the genetic stochastic matrices/cubes associated with the genetic codes can lead to new understanding of genetic code systems, to new effective algorithms of information processing which has a perspective to be applied for modeling mutual communication among different parts of the genetic ensemble.

Matthew He, Zhengbing Hu, Sergey Petoukhov

Mathematical Modeling of Blood Vessel Stenosis and Their Impact on the Blood Vessel Wall Behavior

This article presents experimental result and mathematical analysis of the blood vessel stenosis influences on blood vessel wall behavior by the action of blood circulation. Stenosis leads to less vessel wall segment stretching depending on size and stiffness of vessel segment with stenosis. During the research, the MRI data processing approaches were performed to get blood vessel through-time behavior information and simplified model of blood vessel behavior was determined for obtained information processing to detect stenosis automatically. The results determined empirical dependences, which are necessary for the scientific study of blood vessel behavior. Mathematical analysis of research data was also carried out. Research results are compared with expert’s opinion about stenosis segment of blood vessel’s projection.

Igor Tereshchenko, Ivan Zhuk

Simulation of Electrical Restitution in Cardiomyocytes

The efforts of many scientists are directed to study of heart electrical instability by experimental methods and mathematical modeling of cardiomyocytes’ functional properties. The development of arrhythmias can be caused by cardiac beat-to-beat alternations in action potential duration (APD), concentration of intracellular Ca2+ and contraction force. One of the methods for investigation of dangerous arrhythmias genesis is based on the restitution hypothesis.Motivated by theoretical foundations and experimental research of the arrhythmias, the new approach to stimulation of action potential (AP) alternans in cardiomyocytes due to the heart rate variability was proposed. The main attention was paid to study of electrical restitution dynamics of cardiomyocytes using several pacing protocols. Computational simulation of the action potential and currents for potassium, sodium, calcium ions in cardiomyocytes was carried out using parallel conductance model. Numerical experiments, performed in Matlab environment, allowed us to study electrical properties of cardiomyocytes. The occurrence of APD alternans in areas of electrical restitution curve with a maximum slope is presented.

N. Ivanushkina, K. Ivanko, Y. Prokopenko, A. Redaelli, V. Timofeyev, R. Visone

Deep Learning with Lung Segmentation and Bone Shadow Exclusion Techniques for Chest X-Ray Analysis of Lung Cancer

The recent progress of computing, machine learning, and especially deep learning, for image recognition brings a meaningful effect for automatic detection of various diseases from chest X-ray images (CXRs). Here efficiency of lung segmentation and bone shadow exclusion techniques is demonstrated for analysis of 2D CXRs by deep learning approach to help radiologists identify suspicious lesions and nodules in lung cancer patients. Training and validation was performed on the original JSRT dataset (dataset #01), BSE-JSRT dataset, i.e. the same JSRT dataset, but without clavicle and rib shadows (dataset #02), original JSRT dataset after segmentation (dataset #03), and BSE-JSRT dataset after segmentation (dataset #04). The results demonstrate the high efficiency and usefulness of the considered pre-processing techniques in the simplified configuration even. The pre-processed dataset without bones (dataset #02) demonstrates the much better accuracy and loss results in comparison to the other pre-processed datasets after lung segmentation (datasets #02 and #03).

Yu. Gordienko, Peng Gang, Jiang Hui, Wei Zeng, Yu. Kochura, O. Alienin, O. Rokovyi, S. Stirenko

RNA Quasi-Orthogonal Block Code

This paper presents a single strand ribonucleic acid (RNA) Kronecker product of double stochastic matrix to a deoxyribose nucleic acid (DNA) double helix based on the block circulant Jacket matrix (BCJM) characteristics which is used to develop a bioinformatics for the molecular communications. The RNA matrix decomposition is the form of the Kronecker product of Hadamard matrices with its pair complementarity. The variants of kernel of the Kronecker families are produced by permutations of the four letters C, A, U, G on positions in the matrix. This decomposition of DNA to RNA leads very clearly to the Kronecker product of the symmetrical genetic matrices. We also analyze DNA quasi-orthogonal matrix.

Han Hai, Moon Ho Lee

Computer Science and Education

Frontmatter

Information Technologies for Maintaining of Management Activity of Universities

A specified method and model for analyzing the organizational management of information flows of a large educational institution is suggested. The described solutions allow to reveal information resources, for systems of support of management decision making and control of development plans. As a data source, information obtained from software complexes is used, in particular, from information complexes and electronic document circulation of educational institutions. The configuration and characteristics of information exchange in the information systems supporting the management decisions of the European University are studied. During the research, approaches to the creation and modernization of effective information systems of large educational institutions have been improved.It is shown that the suggested models which are implemented in software tools supporting management activities of universities, allow to increase the flexibility and adaptability of existing information and electronic document management systems.

V. A. Lakhno, V. V. Tretynyk

Adaptive Expert Systems Development for Cyber Attacks Recognition in Information Educational Systems on the Basis of Signs’ Clustering

The article proposes a new approach to solving the issue of efficiency in systems of cyberattacks intelligent recognition, anomalies and threats for the educational and informational environment of universities and colleges. The solution is based on models and methodology of creating an adaptive expert system capable of self-learning. Unlike the existing ones, the model proposed in the article, takes into account the known statistical and remote parameters of cyberattacks signs’ clustering, as well as third-type errors during the machine learning process. It is proposed to evaluate the quality of signs’ space partitioning recognition of objects in an adaptive expert system with the use of a modified information performance condition as an evaluation indicator. It is proved that model and application of the method of clustering of signs based on the entropy and information-distance Kullback–Leibler criterion, allows getting the input fuzzy classified educational matrix which is used as an object of study.

V. Lakhno, S. Zaitsev, Y. Tkach, T. Petrenko

Research on the Use of OLAP Technologies in Management Tasks

The article is dedicated to research of application of OLAP technologies when management. Much attention in the article is paid to creation of the decision-making support system. Such system is set aside for increase of effectiveness of governing, owing to analysis of data collected for a few years. The author demonstrates structure of data warehouse, on which basis analysis of university’s processes is kept. The article is important because the study uses the latest information technologies like MS Excel, Power BI, Business Intelligence Development Studio. Their use will allow management getting a system that will enhance the position in competitive environment.

Daria Yu. Yashchuk, Bella L. Golub

Impact of the Textbooks’ Graphic Design on the Augmented Reality Applications Tracking Ability

Augmented reality (AR) is very effective in school education. Thus, a number of these applications are growing permanently. In most cases, these applications use school textbooks as target images for the AR technology. In developing a textbook design accompanied by the AR application, it is important to use such elements will ensure a stable tracking property when a gadget is held by a kid. There are also various graphic design elements as addition to texts and illustrations in modern textbooks. It is necessary to study how these elements ensure the tracking stability when conditions of textbook viewing are changing. The use of corner detectors to assess the tracking ability of different graphic elements in a textbook is considered. A comparative analysis of the tracking stability for textbook pages is carried out by means of the Harris-Stephens method, BRISK, FAST, Shi & Tomasi methods (also known as the minimum eigenvalue algorithm) which detect features and form their descriptors for the image. Results for these methods are collated with the tracking ability of targets used for a rating estimation on the basis of the Augmented Reality Platform Qualcomm Vuforia.

N. Kulishova, N. Suchkova

Information Technologies of Modeling Processes for Preparation of Professionals in Smart Cities

It is proposed the training process of qualified specialists in accordance with the needs of a person and the requirements of the labor market in the smart city to be presented in the form of five consecutive functional stages: determination of professional inclinations and abilities; monitoring of the urban labor market; a choice of the future profession; a choice of educational institution; formation of an individual learning trajectory. The model of the data analysis process of career orientation testing with obvious uncertainty and hidden redundancy is presented. For storing and analyzing big data, it is suggested to use data warehouses and the model of data warehouse of the complex assessment of educational institution activities is provided. The diffusion-liked model of the multicomponent knowledge potential dissemination is described and variants of the problem solution of identifying the component parameters of the knowledge potential are described, with the aim of their further usage for the formation of individual learning trajectories. The architecture of the software and algorithmic complex of information and technological support of the processes for specialist training in the smart city is developed.

Andrii Bomba, Nataliia Kunanets, Mariia Nazaruk, Volodymyr Pasichnyk, Nataliia Veretennikova

The Procedures for the Selection of Knowledge Representation Methods in the “Virtual University” Distance Learning System

The advantages of usage and the main functions of the “Virtual University” distance learning system are analyzed, which provides opportunities for planning the processes for course developing, creating and accounting of arbitrary hierarchy of learning objects, accounting of learning outcomes as well as providing interactive communication (forums, graphical chats, virtual classes, trainings, video broadcasts, webinars, etc.). The basic models of the “Virtual University” system prototype as the educational web-based environment of distance learning are presented. The functional structure of the system and the architecture of software and algorithmic complex, which is implemented on the basis of the GPL-license of the developer tools, are disclosed. The most common ways of knowledge presentation are analyzed as well as its parametrization and expert evaluation of the basic characteristics are carried out. A hierarchy analysis method is used to select the method of presenting knowledge in the system of distance education. Our calculations showed that it is suitable to use the ontological representation of knowledge in the “Virtual University” distance learning system.

Vasyl Kut, Nataliia Kunanets, Volodymyr Pasichnik, Valentyn Tomashevskyi

Perceptual Computer for Grading Mathematics Tests within Bilingual Education Program

In this paper, we propose an outline of a perceptual computer for grading mathematical tests written by students studying within the bilingual education program. A generic approach to implementing such a computer is proposed. Concrete implementation is described for the case of teaching mathematics in French. The perceptual computer constructed for this case is tested with real tests written by students of one of Kyiv bilingual schools. Results show that the grades obtained using words are compatible with the grades assigned using conventional numbers, which validates the use of the perceptual computer to reduce subjectivity and uncertainty for a teacher.

Dan Tavrov, Liudmyla Kovalchuk-Khymiuk, Olena Temnikova, Nazar-Mykola Kaminskyi

Modelling Nonlinear Nonstationary Processes in Macroeconomy and Finances

Modern decision support systems need the methods of predictive modelling, which would allow create models of systems with given parameters, such that they are capable of being promptly subjected to changes and additions. It could be used to deal with uncertainties of different types, to maximize the automation of the process of constructing predictive models and improve the quality of forecasts estimated. This article is devoted to the study and solving the problem of modeling and forecasting nonlinear nonstationary processes in economy and finances using the methodology proposed based on systemic approach to model structure and parameter estimation. We present preliminary data processing techniques necessary for eliminating possible uncertainties, application of data correlation analysis for model structure estimation, and a set of model parameter estimation methods providing a possibility for computing unbiased estimates of parameters. Proposed methodology can be applied in decision support systems used in finance and economy spheres under conditions of various uncertainties and risks that usually take place in modeling and forecasting using statistical data. In the present paper we will describe in short the usage of the methodology of adaptive modelling and give a couple of examples presenting new results of its application for forecasting behavior of several economic and financial processes.

P. Bidyuk, T. Prosyankina-Zharova, O. Terentiev

Information and Technology Support of Inclusive Education in Ukraine

In modern understanding of education of people with special needs, the inclusive education considers being the beneficial way of socialization. With the growing number of children, who are suggested to be educated inclusively, the use of information technologies will enable a new level of support for all participants of such education – the children, their parents, as well as a wide range of specialists who work with people with special needs.In this paper, we propose the model of information and technological support of inclusive education, built according to the specialty of such process in Ukraine. We present a model of data warehouse, designed to process data of complex psychophysical assessment of persons with special needs. The paper presents the key aspects and main formal criteria of evaluation of effects, caused by the implementation of complex information technology of inclusive educational support. These criteria reflect the impact on social, scientific and technological effects from implementation of information technologies of every stage of inclusive education support.

Tetiana Shestakevych, Volodymyr Pasichnyk, Nataliia Kunanets

Knowledge Representation and Formal Reasoning in Ontologies with Coq

The paper describes a modern type-theoretical approach to the knowledge representation and formal reasoning in ontologies. The current state and limitations of the adopted technology for reasoning in ontologies as well as the advantages of the proposed approach are highlighted. Curry-Howard correspondence and its role in the establishment of computational reasoning are emphasized. The main part is dedicated towards the representation of ontology elements in Coq proof assistant and the execution of a semi-automated reasoning over them.

Vasyl Lenko, Volodymyr Pasichnyk, Natalia Kunanets, Yuriy Shcherbyna

Backmatter

Weitere Informationen

Premium Partner

BranchenIndex Online

Die B2B-Firmensuche für Industrie und Wirtschaft: Kostenfrei in Firmenprofilen nach Lieferanten, Herstellern, Dienstleistern und Händlern recherchieren.

Whitepaper

- ANZEIGE -

Best Practices für die Mitarbeiter-Partizipation in der Produktentwicklung

Unternehmen haben das Innovationspotenzial der eigenen Mitarbeiter auch außerhalb der F&E-Abteilung erkannt. Viele Initiativen zur Partizipation scheitern in der Praxis jedoch häufig. Lesen Sie hier  - basierend auf einer qualitativ-explorativen Expertenstudie - mehr über die wesentlichen Problemfelder der mitarbeiterzentrierten Produktentwicklung und profitieren Sie von konkreten Handlungsempfehlungen aus der Praxis.
Jetzt gratis downloaden!

Bildnachweise