Information, Computing and Intelligent systems

Постійне посилання на фонд

https://ela.kpi.ua/handle/123456789/38945

ISSN: 2708-4930 Рік заснування: 1964
Тематика: Висвітлення результатів досліджень із створення компонентів обчислювальних й інформаційних систем і комплексів, пристроїв автоматики та передавання даних, систем автоматизації програмування, контролю й діагностики, штучного інтелекту тощо.
Попередня назва: Журнал «Information, Computing and Intelligent systems» є правонаступником збірника “Вісник національного технічного університету України «Київський політехнічний інститут». Інформатика, управління та обчислювальна техніка”, який припинив своє існування.
Офіційний сайт: http://itvisnyk.kpi.ua/

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Loop parallelization automation for graphics processing units
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2020) Doroshenko, Anatoliy; Beketov, Olexii; Yatsenko, Olena
A technology that allows extending GPU capabilities to deal with data volumes that outfit internal GPU’s memory capacity is proposed. It involves loop tiling and data serialization and can be applied to utilize clusters consisting of several GPUs. Applicability criterion is specified and a semi-automatic proof-of-concept software tool is implemented. The experiment to demonstrate the feasibility of the proposed technology is described.
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Making an iot development platform from a simple microcontroller demonstration board
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2020) Muraviov, Ihor; Taraniuk, Viktoriia; Klymenko, Iryna
The IOT is now in trend. Because of its huge popularity and business interest to it, IOT is only now coming massively to universities worldwide as a separate study. This article provides an IOT solution based on embedded technologies that were not specifically designed for IOT. The core of this solution - board is developed for studying peripherals of a particular general-purpose MCU. But we successfully adapted it to use in IOT and for study of IOT systems.
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Hash search organization in e-dictionaries using block ciphers
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2020) Markovskyi, Olexander; Humeniuk, Inna; Shevchenko, Olha
The article is devoted to the problem of developing high-speed electronic dictionaries for systems computer translation. The method of organizing a high-speed electronic dictionary based on an ideal hash addressing, where the cryptographic cipher block acts as a hash transformation is proposed. This method was developed taking into account the multilevel memory structure of modern computer systems. It was testified theoretically and experimentally that the proposed organization of electronic dictionaries guarantees at least twice higher search rate compared to known technologies.
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Protected discrete Fourier transform implementation on remote computer systems
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2020) Mirataei, Alireza; Khalil, Hana; Markovskyi, Olexander
Effective method of the discrete Fourier transform acceleration with the use of cloud computing is theoretically substantiated and developed. The reigning feature of the suggested method is homomorphic encryption of the input signals, which provides efficient protection during the remote calculation. It has been shown theoretically and experimentally that the proposed method allows one to 1-2 orders of magnitude to speed up the processing of signals while maintaining their confidentiality. The proposed method can be applied for effective signal stream processing in clouds.
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Road monitoring system based on iot technology for SmartCity
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2020) Кopiika, Anton; Piskun, Roman; Tkachenko, Valentyna; Klymenko, Iryna
This work is devoted to the problem of automatic road quality control, which can be used by both road repair services and common drivers. This paper provides a survey of different known techniques and algorithms of finding potholes on the road and describe our own method, using accelerometer. It will be shown our device for detecting potholes on the road, which can be used, as a part of the IoT system of SmartCity. It uses data from an accelerometer for finding road bumps.
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The method of SDN clustering for controller load balancing
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2020) Dolynnyi, Oleksandr; Nikolskiy, Serhiy; Kulakov, Yurii
The paper proposes the method of SDN clustering using connections density and controller load distribution that solves the problem of controller load balancing. Clustering efficiency criteria have been considered, including fault tolerance, controller-to-switch and intercontroller latency and network limitations. Review of the key clustering methods has been performed, and the base algorithm for modification has been chosen. Density-based controller placement algorithm is modified to solve the problem of multicontroller placement. Metric of the node boundary index is introduced to advance the efficiency of proposed algorithm. A software implementation of the developed algorithm has been created, and its performance has been tested. The algorithm’s modelling results have been compared with those of the other algorithms using the metrics of distribution of service traffic propagation delay and computational speed in relation to network topology size.
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USAK method for the reinforcement learning
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2020) Novotarskyi, Mykhailo; Kuzmich, Valentin
In the field of reinforcement learning, tabular methods have become widespread. There are many important scientific results, which significantly improve their performance in specific applications. However, the application of tabular methods is limited due to the large amount of resources required to store value functions in tabular form under high-dimensional state spaces. A natural solution to the memory problem is to use parameterized function approximations. However, conventional approaches to function approximations, in most cases, have ceased to give the desired result of memory reduction in solving real world problems. This fact became the basis for the application of new approaches, one of which is the use of Sparse Distributed Memory (SDM) based on Kanerva coding. A further development of this direction was the method of Similarity-Aware Kanerva (SAK). In this paper, a modification of the SAK method is proposed, the Uniform Similarity-Aware Kanerva (USAK) method, which is based on the uniform distribution of prototypes in the state space. This approach has reduced the use of RAM required to store prototypes. In addition, reducing the receptive distance of each of the prototypes made it possible to increase the learning speed by reducing the number of calculations in the linear approximator.
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Petri-object simulation: technique and software
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2020) Stetsenko, Inna; Dyfuchyn, Anton
Nowadays information systems tend to be including components for transforming data into information applying modelling and simulation. Combined with real-time data, discrete event simulation could create powerful making decision and control systems. For these purposes, simulation software should be concentrated on creation the model as a code which can be easy integrated with other components of software. In this regard, Petri-object simulation technique, the main concept of which is to compose the code of model of complicated discrete event system in a fast and flexible way, simultaneously providing fast running the simulation, is requisite. The behaviour description of the model based on stochastic multichannel Petri net while the model composition is grounded on object-oriented technology. The Petri-object simulation software provides scalable simulation algorithm, graphical editor, correct transformation graphical images into model, correct simulation results. Graphical editor helps to cope with error-prone process of linking elements with each other. For better understanding the technique, the Petri-object model of web information system has been developed. Investigation of the response time has been conducted. The experiment has revealed system parameters impact on the value of response time. Thus, the model can be useful to avoid long-running request.
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Local feature extraction in images
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2021) Sergiyenko, Anatoliy; Serhiienko, Pavlo; Orlova, Mariia
The methods of the local feature point extraction are analyzed. The analysis shows that the most effective detectors are based on the brightness gradient determination. They usually use the Harris angle detector, which is complex in calculations. The algorithm complexity minimization contradicts both the detector effectiveness and to the high dynamic range of the analyzed image. As a result, the high-speed methods could not recognize the feature points in the heavy luminance conditions. The modification of the high dynamic range (HDR) image compression algorithm based on the Retinex method is proposed. It contains an adaptive filter, which preserves the image edges. The filter is based on a set of feature detectors performing the Harris-Laplace transform which is much simpler than the Harris angle detector. A prototype of the HDR video camera is designed which provides sharp images. Its structure simplifies the design of the artificial intelligence engine, which is implemented in FPGA of medium or large size.
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Architectural review and conceptual development of faculty information system “KPI-Connect”
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2021) Klymenko, Iryna Anatoliivna; Butskyi, Yurii Petrovych; Hryshchenko, Kostiantyn Mykolayovych; Sivachenko, Maryna Hennadiivna; Kryvets, Vadim Volodymyrovych; Kryvoshei, Denys Anatoliiovych; Thin, Nguen Duс
This paper is dedicated to development model of information system to automate educational process based on the Faculty of Informatics and Computer Science at NTUU “Igor Sikorsky Kyiv Polytechnic Institute”. Existing educational systems of different higher education institutions had been studied; main realized functions of similar platforms were defined. As a result of research model, that enables insertion of students, teachers and other university personnel data, storing personal data and information about users’ scientific works, and also is able to be integrated into existing university information space, has been obtained.
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Microcontroller for the logic tasks
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2021) Sergiyenko, Anatoliy; Molchanov, Oleksii; Orlova, Maria
A new SM16 microcontroller architecture is proposed which is intended for the logic-intensive applications in the field-programmable gate array (FPGA). The microcontroller has the stack architecture which provides the implementation of the most of instructions for a single clock cycle. The short but fast programs are derived due to the 16-bit instructions, which code up to three independent operations, and intensive use of the threaded code style. The framework is developed which compiles the program, simulates it, and translates to the ROM. The developed SM16 core with additional three-stack blocks, hash-table, and instructions that accelerate the execution of parsing operations is used for efficient XML-document processing and can be frequently reconfigured to the given document grammar set. The parsing speed equals to one byte per 24 clock cycles.
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Vector space models of kyiv city petitions
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2021) Shaptala, Roman; Kyselov, Gennadiy
In this study, we explore and compare two ways of vector space model creation for Kyiv city petitions. Both models are built on top of word vectors based on the distributional hypothesis, namely Word2Vec and FastText. We train word vectors on the dataset of Kyiv city petitions, preprocess the documents, and apply averaging to create petition vectors. Visualizations of the vector spaces after dimensionality reduction via UMAP are demonstrated in an attempt to show their overall structure. We show that the resulting models can be used to effectively query semantically related petitions as well as search for clusters of related petitions. The advantages and disadvantages of both models are analyzed.
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GIF image hardware compressors
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2021) Mozghovyi, Ivan; Sergiyenko, Anatoliy; Yershov, Roman
Increasing requirements for data transfer and storage is one of the crucial questions now. There are several ways of high-speed data transmission, but they meet limited requirements applied to their narrowly focused specific target. The data compression approach gives the solution to the problems of high-speed transfer and low-volume data storage. This paper is devoted to the compression of GIF images, using a modified LZW algorithm with a tree-based dictionary. It has led to a decrease in lookup time and an increase in the speed of data compression, and in turn, allows developing the method of constructing a hardware compression accelerator during the future research.
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Optimal construction of the pattern matrix for probabilistic neural networks in technical diagnostics based on expert estimations
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2021) Romanuke, Vadim
In the field of technical diagnostics, many tasks are solved by using automated classification. For this, such classifiers like probabilistic neural networks fit best owing to their simplicity. To obtain a probabilistic neural network pattern matrix for technical diagnostics, expert estimations or measurements are commonly involved. The pattern matrix can be deduced straightforwardly by just averaging over those estimations. However, averages are not always the best way to process expert estimations. The goal is to suggest a method of optimally deducing the pattern matrix for technical diagnostics based on expert estimations. The main criterion of the optimality is maximization of the performance, in which the subcriterion of maximization of the operation speed is included. First of all, the maximal width of the pattern matrix is determined. The width does not exceed the number of experts. Then, for every state of an object, the expert estimations are clustered. The clustering can be done by using the k-means method or similar. The centroids of these clusters successively form the pattern matrix. The optimal number of clusters determines the probabilistic neural network optimality by its performance maximization. In general, most results of the error rate percentage of probabilistic neural networks appear to be near-exponentially decreasing as the number of clustered expert estimations is increased. Therefore, if the optimal number of clusters defines a too “wide” pattern matrix whose operation speed is intolerably slow, the performance maximization implies a tradeoff between the error rate percentage minimum and maximally tolerable slowness in the probabilistic neural network operation speed. The optimal number of clusters is found at an asymptotically minimal error rate percentage, or at an acceptable error rate percentage which corresponds to maximally tolerable slowness in operation speed. The optimality is practically referred to the simultaneous acceptability of error rate and operation speed.
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Methodology of network environment testing for IoT devices
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2021) Her, Vladyslav; Taraniuk, Viktoriia; Tkachenko, Valentyna; Nikolskiy, Serhiy; Klymenko, Iryna
The article describes the basics of testing: writing test documentation (an example based on a report defect was proposed) and some testing methods. A performance test was also developed to test the load. Received basic knowledge of testing theory, as well as skills of writing and using bash scripts for performance tests.
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Overview of ocr tools for the task of recognizing tables and graphs in documents
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2022) Yaroshenko, O.
This study describes OCR tools for recognizing tables and graphs. There is a great demand for solutions that can effectively automate the processing of an extensive array of documents. Existing OCR solutions can efficiently recognize text, but recognizing graphical elements, such as charts and tables, is still in the making. Solutions that can increase the accuracy of visual data recognition can be valuable for technical document processing, such as scientific, financial, and analytical documents.
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Design of data buffers in field programmablr gate arrays
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2022) Sergiyenko, Anatoliy; Serhiienko, Pavlo; Mozghovyi, Ivan; Molchanova, Anastasiia
The design of the data buffers for the field programable gate array (FPGA) projects is considered. A new method of buffer design is proposed, which is based on the representation of the synchronous dataflow graph in the three-dimensional space, optimization of them, and description in VHDL. The method gives the optimized buffers which are based either on RAM or on the register pipeline. The derived pipeline buffer can be mapped into the shift register primitive of FPGA. The method is built in the experimental SDFCAD framework intended for the pipelined datapath synthesis.
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Fast secure calculation of the open key cryptography procedures for IoT in clouds
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2022) Mirataei, Alireza; Markovskyi, Oleksandr; Haidukevych, Maria
The article proposes a method for accelerating the implementation of cryptographic data protection mechanisms on embedded IoT terminal microcontrollers, the basic operation of which is the modular exponentiation of high-capacity numbers. The method is based on the use of remote computer systems to speed up calculations and provides protection against the reconstruction of the secret keys of cryptosystems from data transmitted to the cloud. It has been theoretically and experimentally proven that the method allows, on average, 50 times, to speed up the implementation of cryptographic data protection protocols in IoT while providing a level of security sufficient for most practical applications.
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Organization of protected filtering of images in clouds
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2022) Mirataei, Alireza; Rusanova, Olga; Tribynska, Karolina; Markovskyi, Oleksandr
The article proposes an approach to using cloud technologies to accelerate the filtering of image streams while ensuring their protection during processing on remote computer systems. Homomorphic encryption of images during their remote filtering is proposed to be carried out by shuffling rows of pixel matrices. This provides a high level of protection against attempts to illegally restore images on computer systems that filter them. The developed approach makes it possible to speed up the performance of this important image processing operation by 1-2 orders of magnitude.
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Simulation of fluid motion in complex closed surfaces using a lattice Boltzmann model
(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2022) Kuzmych, Valentyn; Novotarskyi, Mykhailo
CFD (computational fluid dynamics) modeling is used to determine the distribution of pressure, velocity, and other movement parameters of liquids or gases. Simulation of a fluid flow in a complex closed surface has become demandable in many scientific, medical, and industrial areas. The lattice Boltzmann model is an efficient numerical scheme for modeling fluid flows. In this paper, we investigate nonstationary hydrodynamic processes in closed surfaces using the Boltzmann lattice model to simulate fluid flow in the human stomach.

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