Кафедра електронних обчислювальних машин (ЕОМ)
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Публікація Analysing the impact of IaaS infrastructure components to improve system performance(ДП "ПДПРОНДІАВІАПРОМ", 2021) Bondarenko, M. E.Публікація Analysis of information structure modeling methods(ФОП Петров В.В., 2022) Kuchuk, N.; Kotova, O.A mathematical model is often used to analyze the information structure of a network. This model has the form of queuing networks. Queuing network – This is a system that performs the service of incoming requests to it. The main elements of the system are the input flow of applications, service channels, the queue of applications, the output flow of applications. Service requests arrive at discrete (constant or random) time intervals. It is important to know the law of distribution of the incoming flow. The channels needed to serve these applications. Service lasts for a while, constant or occasionalПублікація Analysis of methods of using the Raspberry PI platform in the training of computer engineers(ХНУРЕ, 2021) Bilash, D. A.Raspberry Pi is the name of a series of single-board computers and high-performance microcontrollers. First of them was launched by the Raspberry Pi Foundation in 2012. A UK charity that aims to teach people in computing and provide them with easy knowledge in the Internet of Things, giving a big opportunity to use their products. Also it is cheap and costs less than 35 $ and there is a model that costs only 5$.Публікація Analysis of multimedia data replication methods(ХНУРЭ, 2021) Hvozdetska, K. P.This work is devoted to the analysis of existing methods of data replication when using the scheme of increasing fault tolerance of servers with multimedia content. It analyzes such methods as detachment/attachment method, one-way and two-way replication methods.Публікація Analysis of the influence of selected audio pre-processing stages on accuracy of speaker language recognition(ХНУРЕ, 2023) Barkovska, O. Yu.; Havrashenko, A. O.In the course of the work, the best sequence of stages of pre-processing audio data was selected for use in further training of the neural network for different ways to convert signals into features. Mel-cepstral characteristic coefficients are better suited for solving our problem. Since the neural network strongly depends on its structure, the results may change with the increase in the volume of input data and the number of languages. But at this stage, it was decided to use only mel-cepstral characteristic coefficients with normalization.Публікація Approach to building a global mobile agent way based on q-learning(ХНУРЕ, 2020) Martovytskyi, V.; Ivaniuk, O.Today, the problem of navigation of autonomous mobile systems in a space where disturbances are possible is urgent. The task of finding a route for a mobile robot is a complex and non-trivial task. At the moment, there are many algorithms that allow you to solve such problems in accordance with the specified criteria for building a route. Most of these algorithms are modifications of "basic" path planning methods that are optimized for specific conditions. The subject of research in the article is the process of building a global path for a mobile agent. The purpose of the work is to create an algorithm for planning the route of autonomous mobile systems in space using the Q-learning algorithm. The following tasks are solved in the article: development of an approach to training and support of a reinforcement learning algorithm for building a global path of a mobile agent; testing the agent's ability to find a path in environments that are not in the training set. The following methods are used: graph theory, queuing theory, Markov decision-making process theory and mathematical programming methods. The research is based on scientific articles and other materials from foreign conferences and archives in the field of machine learning, deep learning and deep reinforcement learning. The following results were obtained: an approach was formulated to construct the global path of a mobile agent based on the accumulated data in the process of interaction with the external environment. The environment rewards these actions and the agent continues to carry them out. This approach will allow this method to be applied to a wide range of situations and devices. Conclusions: This approach allows accumulating the knowledge of the outside world for further decision-making when planning a route where the robot can acquire the skill of self-learning, studying and training like a human, and finding the path from the initial state to the target state in an unknown environment. In the modern world, the use of robots and autonomous systems is spreading, designed to replace or facilitate human labor, make it safer and speed it up. Adaptive autonomous path finding algorithms are very important in many robotics applications. Thus, navigation tasks with limited information are relevant today, since this is the main task that the agent solves, and one of the tasks that are part of the robot during operation.Публікація Architecture of overlay network with nested vpn tunneling(2020) Hunko, M.; Tkachov, V.; Bondarenko, M.The development of algorithms and methods for optimizing packet transmission in overlay networks has recently become relevant. The reason for this is the constantly increasing size and number of overlay networks. This is conditioned by the global concept of anonymizing traffic on computer networks, which leads to increased load in transmission channels, complexity of data packet structures, especially in low-speed networks, their stacks.Публікація Audio signal transmission method in network-based audio analytics system(ХНУРЕ, 2023) Poroshenko, A. I.; Kovalenko, A. A.The subject matter of the article is аudio signal transmission method in network-based audio analytics system. The creation of a network-based audio analytics system leads to the emergence of new classes of load sources that transmit packetized sound data. Therefore, without constructing adequate mathematical models, it is impossible to build a well-functioning network-based audio analytics system. A fundamental question in traffic theory is the question of load source models. The development of an method for transmitting audio signals in a network-based audio analytics system becomes necessary. Based on this, the goal of the work is to create methods an method for transmitting audio signals in a network-based audio analytics system to ensure efficiency and accuracy in audio analytics. The following tasks were solved in the article: the formation of a model for the system's load sources, investigation of connection and traffic management, implementation of control and traffic monitoring functions in the network, research of methods to ensure the quality of audio signal transmission and the development of a method of transmitting an audio signal by virtual routes switching. To achieve these goals, the following methods are used: mathematical signal processing, data compression algorithms, optimization of network protocols, and the use of high-speed network connections. The obtained results include modeling of the system's load sources, examination of connection and traffic management, investigation of methods to ensure the quality of audio signal transmission and a method of transmitting an audio signal by virtual routes switching was proposed. In conclusion, the possibilities of using simulation modeling of nodes in the network-based audio analytics system are highly limited. This is explained by the fact that the acceptable level of information loss in data centers is very low. The use of the developed method enables effective control and processing of sound information in real-time. This method can find broad applications in various fields, including security, healthcare, management systems, and other industries where the analysis of audio signals is a crucial element.Публікація Automated Controllers Functioning Criteria in Content Distribution Systems(Scholars Journal of Engineering and Technology (SJET), 2014) Саваневич, В. Е.; Ткачев, В. Н.This paper describes content distribution systems (CDS) used in telecommunication datacenters. First or last, the CDS becomes large, and its detailed engineering can not be performed during reasonable time span. Therefore, its optimization is out of question. In this case, formulating a model for a huge system functioning, not the system optimization, is required. This paper describes the problem of automated controllers functioning in telecommunication up-diffused datacenters. We propose the functional criteria of the practicability CDS behavior agreed with a specification of earlier informational system criterion. It belongs to a class of additive functional-cost criterion. The mentioned problem of CDS functioning can be solved using the Lagrange's method of undetermined coefficients. This allows to develop the system with minimal average costs during the extended period of its operational time under conforming to the possibility of tasks solving. At that the behavior model parameters values are equivalent to the corresponding Lagrange coefficients. The presented approach can be practically implemented in the suballocated service systems or the systems working according to the "observer-subscriber" principle.Публікація Automated nondestroying roughness control on optical ferrule surfaces(2001) Токарев, В. В.; Невлюдов, И. Ш.; Цимбал, А. М.In the developed automated quality control system for end face of optical ferrules, a Linnik interferometer scheme, and a CCD coordinate-sensitive photo-receiver are used. There is need to fulfill the following basic requirement in an optical micro-interferometer scheme: the intensity of light flux from standard mirror is approximately equal to light flux intensity from surface of object, because that condition is necessary for interference traces observation. The MII-4 micro-interferometer is intended for end face roughness with greater coefficient of reflection (e.g. metal surfaces).Публікація City’s digital infrastructure as a factor of sustainability(2021) Leha, Ye. S.; Fesenko, Т. G.; Liashenko, O. S.Публікація CNN-модель прогнозування поширення COVID-19 в Україні(2021) Андрусенко, Ю. О.Прогнозування фінансово-економічних, логістичних та навіть продовольчих показників залежить від поширення COVID-19 в Україні. Для прийняття рішення посилення або пом'якшення карантинних обмежень, необхідно прогнозувати поширення захворюваності по регіонах України в довгостроковій і короткостроковій перспективі з максимальною точністю.Публікація Collection and primary processing of medical and biological data(2021) Yeroshenko, O.; Prasol, I.The collection of data is the accumulation of them sufficiently in order to make an adequate decision or to obtain a statistically significant result. The amount of data is usually set in advance or determined by the analysis of intermediate results.Публікація Comparative analysis of neural network models for the problem of speaker recognition(ХНУРЕ, 2023) Kholiev, V.; Barkovska, O.The subject matter of the article are the neural network models designed or adapted for the problem of voice analysis in the context of the speaker identification and verification tasks. The goal of this work is to perform a comparative analysis of relevant neural network models in order to determine the model(s) that best meet the chosen formulated criteria, – model type, programming language of model’s implementation, parallelizing potential, binary or multiclass, accuracy and computing complexity. Some of these criteria were chosen because of universal importance, regardless of particular application, such as accuracy and computational complexity. Others were chosen due to the architecture and challenges of the scientific communication system mentioned in the work that performs tasks of the speaker identification and verification. The relevance of the paper lies in the prevalence of audio as a communication medium, which results in a wide range of practical applications of audio intelligence in various fields of human activity (business, law, military), as well as in the necessity of enabling and encouraging efficient environment for inward-facing audio-based scientific communication among young scientists in order for them to accelerate their research and to acquire scientific communication skills. To achieve the goal, the following tasks were solved: criteria for models to be judged upon were formulated based on the needs and challenges of the proposed model; the models, designed for the problems of speaker identification and verification, according to formulated criteria were reviewed with the results compiled into a comprehensive table; optimal models were determined in accordance with the formulated criteria. The following neural network based models have been reviewed: SincNet, VGGVox, Jasper, TitaNet, SpeakerNet, ECAPA_TDNN. Conclusions. For the future research and practical solution of the problem of speaker authentication it will be reasonable to use a convolutional neural network implemented in the Python programming language, as it offers a wide variety of development tools and libraries to utilize.Публікація Computer system for retina non-invasive diagnostics of human visual analyzer(2014) Токарев, В. В.; Семенець, В. В.; Наталуха, Ю. В.; Тарануха, О. А.Публікація Conceptualizing of sustainable-oriented construction project management methodology(2022) Fesenko, T.The integration of sustainability into construction project management is considered in correlation with the Sustainable Development Goals (SDGs). Conceptual guidelines for the development of a focused methodology for construction project management are outlined. It is taken into account that construction is a technologically specific activity carried out within the framework of industry norms, rules, and standards. On the other hand, the parameters of "sustainability" in the context of 17 SDGs and integration with economic, environmental, and social aspects are analyzed. A matrix of the integration of SDGs into ISO standards for sustainability in building construction, which allows identifying gaps and points in the development of sustainable-oriented construction project management methodology, is presented.Публікація Data Analysis in the Internet of Things(2021) Tkachov, V. M.; Yerokhin, B. O.Публікація Development of a module for sorting the ip-addresses of user nodes in cloud firewall protection of web resourсes(2019) Hunko, M. A.; Tkachov, V. M.In connection with the expanding field of application of cloud services, there are new tasks that they solve.Публікація Development of information technology of tasks distribution for GRID-systems using the GRASS simulation environment(Eastern-European Journal of Enterprise Technologies, 2016) Филимончук, Т. В.; Волк, М. А.; Рубан, И. В.; Ткачев, В. Н.An information distribution task technology for GRID-systems based on the use of simulation modeling GRASS environment was proposed. GRASS reproduces the process of functioning over time of elementary events that occur in the GRID-system with maintaining their interaction logic. This solution enables conducting of computational experiments that implement different methods of distribution, with a following selecting of the most effective solution on the basis of the collection, analysis and interpretation of simulation results. The proposed task of distribution technology using simulation modeling GRASS environment, enables implementing multiple distribution methods and selecting the best distribution environment that increases the efficiency of GRID-systems by reducing the time of the task performance and reducing the downtime of resources in highly related tasks. GRASS modeling environment has a modular structure, which consists of a core and dynamically loaded modules (plug-ins). Each module performs a highly specialized task, referring if necessary to the other modules of the system. The core provides means of inter-module interaction and provides boot and system configuration.Публікація Efficiency of image convolution(2019) Smelyakov, K.; Shupyliuk, M.; Martovytskyi, V.; Tovchyrechko, D.; Ponomarenko, O.The article discusses the main algorithms used to convolve a digital image, experiment is performed on various reduction factors, and discusses the use of convolution algorithms for an image with a large number of fine details, analyzes the effectiveness of the experimental results and selects the most effective convolution algorithms used for images with a large number small parts.