Air quality has recently been of great concern, as it directly affects people's lives. Continuous monitoring of atmospheric air quality and forecasting the dynamics of its changes are essential steps in assessing its current state and determining the concentration of pollutants. Therefore, the development of an effective system for assessing and forecasting the quality of atmospheric air has become one of the most important tasks. The subject matter of this article is geostatistical methods for air quality analysis. The goal is to analyze pollutants in the air over Ukraine's territory from 1990 to 2021. The dataset on air pollutants was provided by the State Statistics Service of Ukraine in the form of aggregated tables, which were initially processed for subsequent modelling. Cartographic modelling of pollutants was performed using geostatistical methods. As a result, this study presents 13 cartographic models showing the spatial distribution of air pollutants for different regions of Ukraine. However, because of the lack of official information on the presence of military actions, the results of geostatistical methods cannot be interpreted in the context of the military situation in the eastern part of the country. Information about military actions can be gathered from various sources, but this would require a considerable time and effort to structure and systematize the dataset. Conclusions. The method considered in this study cannot simultaneously consider multiple parameters, such as the value of pollutant indicators and the presence of military actions. Additional methods, such as graph theory and regression analysis, are employed to obtain quantitative assessments of the modelling results considering all factors influencing the environmental condition. The chosen method is a straightforward tool for solving environmental problems. Thanks to available GIS systems like ArcGIS Pro, visualization of the applied geostatistical and mathematical methods is possible. The cartographic models presented in this study cover the entire territory of Ukraine and have administrative boundaries depending on the location of the pollutant collection station.
{"title":"Analysis of pollutants in air within the territory of Ukraine using geostatistical methods","authors":"Olga Butenko, Anna Topchiy","doi":"10.32620/reks.2023.3.18","DOIUrl":"https://doi.org/10.32620/reks.2023.3.18","url":null,"abstract":"Air quality has recently been of great concern, as it directly affects people's lives. Continuous monitoring of atmospheric air quality and forecasting the dynamics of its changes are essential steps in assessing its current state and determining the concentration of pollutants. Therefore, the development of an effective system for assessing and forecasting the quality of atmospheric air has become one of the most important tasks. The subject matter of this article is geostatistical methods for air quality analysis. The goal is to analyze pollutants in the air over Ukraine's territory from 1990 to 2021. The dataset on air pollutants was provided by the State Statistics Service of Ukraine in the form of aggregated tables, which were initially processed for subsequent modelling. Cartographic modelling of pollutants was performed using geostatistical methods. As a result, this study presents 13 cartographic models showing the spatial distribution of air pollutants for different regions of Ukraine. However, because of the lack of official information on the presence of military actions, the results of geostatistical methods cannot be interpreted in the context of the military situation in the eastern part of the country. Information about military actions can be gathered from various sources, but this would require a considerable time and effort to structure and systematize the dataset. Conclusions. The method considered in this study cannot simultaneously consider multiple parameters, such as the value of pollutant indicators and the presence of military actions. Additional methods, such as graph theory and regression analysis, are employed to obtain quantitative assessments of the modelling results considering all factors influencing the environmental condition. The chosen method is a straightforward tool for solving environmental problems. Thanks to available GIS systems like ArcGIS Pro, visualization of the applied geostatistical and mathematical methods is possible. The cartographic models presented in this study cover the entire territory of Ukraine and have administrative boundaries depending on the location of the pollutant collection station.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135296774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nikolay Ruzhentsev, Oleg Gribsky, Sergey Maltsev, Sergey Shevchuk, Vladimir Pavlikov, Gleb Cherepnin, Simeon Zhyla, Eduard Tserne
The subject of this manuscript is broadband noise signals and systems. The aim of this research is to show the results of a modern active-passive 3-mm waveband system consisting of a noise-pulsed radar and a radiometer. Noise radar systems (NRS) based on broadband signals are characterized by high resolution, accuracy, and information content when performing unambiguous measurements of the range and speed of targets, as well as increased electromagnetic compatibility and noise immunity. These distinctive features of NRS determine the relevance of their construction for practical tasks of short- and medium-range radar. Additional opportunities for ensuring secrecy, reliability of detection of objects, and their tracking are provided by the combination of active and passive location modes in conjunction with advancement to the short-wave part of the millimeter (MM) wave band (WB). The most important characteristic of any pulsed radar, which largely determines its potential for practical application, is the operating frequency, as well as the shape and width of the probing signal spectrum. The main idea of this work is to describe the construction scheme and the results of preliminary tests of the developed active-passive system in the 94 GHz band with a noisy 20–100 ns illumination pulse in the 5 GHz band. The obtained values of the energy potential of the system in the active location mode (-105 dB) and the achieved radiometer sensitivities in the passive mode (0.007K and 0.03K) make it possible to observe ground and air objects at a distance of several kilometres. Noted that the measured parameters of the radar, in the case of processing the received signal by pulse compression methods, make it possible to count on ensuring the resolution of targets in range at the level of 10-15 cm. A multiple (more than an order of magnitude) decrease in the interference fluctuations of the received signal, which is due to the facet nature of the backscattering of targets, has experimentally demonstrated using a noise probing pulse compared to a single-frequency pulse. The methods for further work on the development and practical application of the constructed measuring system are outlined.
{"title":"Активно-пасивний імпульсно-шумовий радар діапазону 3мм та результати його попередніх випробувань","authors":"Nikolay Ruzhentsev, Oleg Gribsky, Sergey Maltsev, Sergey Shevchuk, Vladimir Pavlikov, Gleb Cherepnin, Simeon Zhyla, Eduard Tserne","doi":"10.32620/reks.2023.3.04","DOIUrl":"https://doi.org/10.32620/reks.2023.3.04","url":null,"abstract":"The subject of this manuscript is broadband noise signals and systems. The aim of this research is to show the results of a modern active-passive 3-mm waveband system consisting of a noise-pulsed radar and a radiometer. Noise radar systems (NRS) based on broadband signals are characterized by high resolution, accuracy, and information content when performing unambiguous measurements of the range and speed of targets, as well as increased electromagnetic compatibility and noise immunity. These distinctive features of NRS determine the relevance of their construction for practical tasks of short- and medium-range radar. Additional opportunities for ensuring secrecy, reliability of detection of objects, and their tracking are provided by the combination of active and passive location modes in conjunction with advancement to the short-wave part of the millimeter (MM) wave band (WB). The most important characteristic of any pulsed radar, which largely determines its potential for practical application, is the operating frequency, as well as the shape and width of the probing signal spectrum. The main idea of this work is to describe the construction scheme and the results of preliminary tests of the developed active-passive system in the 94 GHz band with a noisy 20–100 ns illumination pulse in the 5 GHz band. The obtained values of the energy potential of the system in the active location mode (-105 dB) and the achieved radiometer sensitivities in the passive mode (0.007K and 0.03K) make it possible to observe ground and air objects at a distance of several kilometres. Noted that the measured parameters of the radar, in the case of processing the received signal by pulse compression methods, make it possible to count on ensuring the resolution of targets in range at the level of 10-15 cm. A multiple (more than an order of magnitude) decrease in the interference fluctuations of the received signal, which is due to the facet nature of the backscattering of targets, has experimentally demonstrated using a noise probing pulse compared to a single-frequency pulse. The methods for further work on the development and practical application of the constructed measuring system are outlined.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135296898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The subject of this study is the process of developing block symmetric ciphers with improved cryptographic stability indicators for solving the problems of information protection in information and communication systems. The goal of this study is to develop a mathematical model of the optimal s-box design (non-linear substitution block) for modern block symmetric ciphers. Task: to show that the stability of block symmetric ciphers does not significantly depend on the indicators of the s-boxes included in these ciphers; to justify their use without reducing the stability of random substitutions as s-box constructions of modern block symmetric ciphers; and to prove the futility of searching for s-boxes with special properties. The methods used are: methods of probability theory; mathematical statistics; combinatorics and system analysis; methods of statistical tests; and methods of Boolean algebra. The following results were obtained. In modern ciphers, nonlinear substitution transformations are used as S-boxes (in most ciphers, byte substitutions are used). S-boxes perform the main function of encryption transformation - mixing of text bits. Dynamic indicators of the arrival of the cipher in the state of random substitution depend on their effectiveness. The presented results confirm that the indicators of cipher stability do not significantly depend on the indicators of the S-boxes included in the ciphers. It is not the individual properties of substitutions, but the results of their sequential interactions decisive for achieving stability indicators. It is shown that the fee for encryption is chosen to be three to four times greater than the depth of the avalanche effect - the minimum number of cycles of the cipher’s arrival to the state of random substitution) is hardly noticeable. Conclusions. The scientific novelty of the obtained results is as follows. This work represents a generalization of the transition to the use of random permutations as S-boxes is an increase of only one cycle in the number of cycles of the arrival of the cipher to the state of random permutations, and this is hardly noticeable against the background of the stability margin used in modern ciphers. The result of this generalization is a scientific statement that can be described as follows: random S-boxes can be used in all known modern ciphers without reducing stability. That is, the task of finding S-boxes with special properties loses any meaning, which means that the scientific direction related to the search for S-boxes with special properties becomes redundant.
{"title":"The influence of S-boxes on the arrival of the cipher to the state of random substitution","authors":"Iryna Lysytska, Kostiantyn Lysytskyi, Oleksii Nariezhnii, Tetiana Hrinenko","doi":"10.32620/reks.2023.3.12","DOIUrl":"https://doi.org/10.32620/reks.2023.3.12","url":null,"abstract":"The subject of this study is the process of developing block symmetric ciphers with improved cryptographic stability indicators for solving the problems of information protection in information and communication systems. The goal of this study is to develop a mathematical model of the optimal s-box design (non-linear substitution block) for modern block symmetric ciphers. Task: to show that the stability of block symmetric ciphers does not significantly depend on the indicators of the s-boxes included in these ciphers; to justify their use without reducing the stability of random substitutions as s-box constructions of modern block symmetric ciphers; and to prove the futility of searching for s-boxes with special properties. The methods used are: methods of probability theory; mathematical statistics; combinatorics and system analysis; methods of statistical tests; and methods of Boolean algebra. The following results were obtained. In modern ciphers, nonlinear substitution transformations are used as S-boxes (in most ciphers, byte substitutions are used). S-boxes perform the main function of encryption transformation - mixing of text bits. Dynamic indicators of the arrival of the cipher in the state of random substitution depend on their effectiveness. The presented results confirm that the indicators of cipher stability do not significantly depend on the indicators of the S-boxes included in the ciphers. It is not the individual properties of substitutions, but the results of their sequential interactions decisive for achieving stability indicators. It is shown that the fee for encryption is chosen to be three to four times greater than the depth of the avalanche effect - the minimum number of cycles of the cipher’s arrival to the state of random substitution) is hardly noticeable. Conclusions. The scientific novelty of the obtained results is as follows. This work represents a generalization of the transition to the use of random permutations as S-boxes is an increase of only one cycle in the number of cycles of the arrival of the cipher to the state of random permutations, and this is hardly noticeable against the background of the stability margin used in modern ciphers. The result of this generalization is a scientific statement that can be described as follows: random S-boxes can be used in all known modern ciphers without reducing stability. That is, the task of finding S-boxes with special properties loses any meaning, which means that the scientific direction related to the search for S-boxes with special properties becomes redundant.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":"500 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135296899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The subject matter of this study is algorithms for measuring the components of an aircraft speed vector and altitude. The goal of this study is to improve algorithms for processing wideband stochastic pulse signals in helicopter low-altitude and flight-speed radio systems by introducing secondary signal processing based on artificial intelligence elements. The tasks to be solved are as follows: to develop an optimal algorithm for determining the speed and altitude of flight for a helicopter radio complex; to supplement the signal processing algorithm with an artificial intelligence-based processor to determine the "safety" of the current trajectory; provide the pilot with relevant information about possible options for further actions based on an analysis of the current position of the helicopter and flight parameters; and to analyse the efficiency of the proposed complex when using various artificial intelligence-based algorithms. The methods used are as follows: methods of mathematical statistics and optimal solutions for solving problems of statistical synthesis of active radio complex structure; methods of machine learning; and methods of computer simulation. The following results were obtained. The algorithms for signal processing in a helicopter radio complex are obtained by the method of maximum likelihood, and the use of three radio channels to calculate the full vector of speed and altitude is argued. The structure of a secondary information processing system, using algorithms based on artificial intelligence is proposed. The effectiveness of determining the safety of the current landing trajectory using various algorithms based on artificial intelligence (LinearSVC, GaussianNB, DecisionTreeClassifier, RandomForestClassifier, KNeighborsClassifier, MLPClassifier and RidgeClassifier) was analysed. Conclusions. The simulation results show that in the presence of accurate (noise-free) information on the current location of the helicopter, its axial velocities, and a map of the terrain with defined areas dangerous for landing, the DecisionTreeClassifier and RandomForestClassifier algorithms can provide a high probability of correctly determining the safety of the current landing trajectory. At the same time, in the presence of instability in the measurements of helicopter movement parameters, only the RandomForestClassifier algorithm maintains high accuracy.
{"title":"Helicopter radio system for low altitudes and flight speed measuring with pulsed ultra-wideband stochastic sounding signals and artificial intelligence elements","authors":"Dmytro Vlasenko, Olha Inkarbaieva, Maksym Peretiatko, Danyil Kovalchuk, Oleksandr Sereda","doi":"10.32620/reks.2023.3.05","DOIUrl":"https://doi.org/10.32620/reks.2023.3.05","url":null,"abstract":"The subject matter of this study is algorithms for measuring the components of an aircraft speed vector and altitude. The goal of this study is to improve algorithms for processing wideband stochastic pulse signals in helicopter low-altitude and flight-speed radio systems by introducing secondary signal processing based on artificial intelligence elements. The tasks to be solved are as follows: to develop an optimal algorithm for determining the speed and altitude of flight for a helicopter radio complex; to supplement the signal processing algorithm with an artificial intelligence-based processor to determine the \"safety\" of the current trajectory; provide the pilot with relevant information about possible options for further actions based on an analysis of the current position of the helicopter and flight parameters; and to analyse the efficiency of the proposed complex when using various artificial intelligence-based algorithms. The methods used are as follows: methods of mathematical statistics and optimal solutions for solving problems of statistical synthesis of active radio complex structure; methods of machine learning; and methods of computer simulation. The following results were obtained. The algorithms for signal processing in a helicopter radio complex are obtained by the method of maximum likelihood, and the use of three radio channels to calculate the full vector of speed and altitude is argued. The structure of a secondary information processing system, using algorithms based on artificial intelligence is proposed. The effectiveness of determining the safety of the current landing trajectory using various algorithms based on artificial intelligence (LinearSVC, GaussianNB, DecisionTreeClassifier, RandomForestClassifier, KNeighborsClassifier, MLPClassifier and RidgeClassifier) was analysed. Conclusions. The simulation results show that in the presence of accurate (noise-free) information on the current location of the helicopter, its axial velocities, and a map of the terrain with defined areas dangerous for landing, the DecisionTreeClassifier and RandomForestClassifier algorithms can provide a high probability of correctly determining the safety of the current landing trajectory. At the same time, in the presence of instability in the measurements of helicopter movement parameters, only the RandomForestClassifier algorithm maintains high accuracy.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135296775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vladyslav Bilozerskyi, Konstantin Dergachov, Leonid Krasnov, Anatolii Zymovin, Anatoliy Popov
Subject of study. In this study, for the first time, an original method for estimating the change in the brightness of video data under the influence of changes in the lighting conditions of the scene and external noise is proposed. Algorithms for stabilizing the brightness of the video data are also proposed. An objective assessment of the quality of video data because of pre-processing is given. The purpose of this study is to create a methodology for analyzing the variability of video data parameters under the influence of negative factors and to develop effective algorithms for stabilizing the parameters of the received video stream. A thorough verification of the reliability of the method on real video recordings made under various conditions is given. Objectives: To determine the most universal, resistant to external influences, and informative indicator necessary for an objective assessment of the quality of video data under various shooting conditions and scene lighting features; develop and programmatically implement algorithms for stabilizing video parameters based on modern programming tools. Research methods. Statistical analysis and pre-processing of video stream parameters as a random spatio-temporal process, algorithms for processing video data by digital filtering, and adaptive stabilization of video stream parameters. Research results. It has been proposed and experimentally proven that the optimal indicator of video stream quality is the average frame brightness (AFB). An algorithm for spatiotemporal processing of video data is proposed that generates a sequence of AFB values from the original video stream. This paper also proposes digital algorithms for filtering and stabilizing the brightness of a video stream and investigates the effectiveness of their application. Conclusions. The scientific novelty of the results obtained lies in a new method for analyzing and evaluating the parameters of video surveillance data and algorithms for filtering and stabilizing the brightness of the video stream. The performance of the proposed algorithms was tested on real data. The algorithms were implemented in the Python software environment using the functions of the OpenCV library.
{"title":"A new method for video stream brightness stabilization: algorithms and assessment of effectiveness","authors":"Vladyslav Bilozerskyi, Konstantin Dergachov, Leonid Krasnov, Anatolii Zymovin, Anatoliy Popov","doi":"10.32620/reks.2023.3.10","DOIUrl":"https://doi.org/10.32620/reks.2023.3.10","url":null,"abstract":"Subject of study. In this study, for the first time, an original method for estimating the change in the brightness of video data under the influence of changes in the lighting conditions of the scene and external noise is proposed. Algorithms for stabilizing the brightness of the video data are also proposed. An objective assessment of the quality of video data because of pre-processing is given. The purpose of this study is to create a methodology for analyzing the variability of video data parameters under the influence of negative factors and to develop effective algorithms for stabilizing the parameters of the received video stream. A thorough verification of the reliability of the method on real video recordings made under various conditions is given. Objectives: To determine the most universal, resistant to external influences, and informative indicator necessary for an objective assessment of the quality of video data under various shooting conditions and scene lighting features; develop and programmatically implement algorithms for stabilizing video parameters based on modern programming tools. Research methods. Statistical analysis and pre-processing of video stream parameters as a random spatio-temporal process, algorithms for processing video data by digital filtering, and adaptive stabilization of video stream parameters. Research results. It has been proposed and experimentally proven that the optimal indicator of video stream quality is the average frame brightness (AFB). An algorithm for spatiotemporal processing of video data is proposed that generates a sequence of AFB values from the original video stream. This paper also proposes digital algorithms for filtering and stabilizing the brightness of a video stream and investigates the effectiveness of their application. Conclusions. The scientific novelty of the results obtained lies in a new method for analyzing and evaluating the parameters of video surveillance data and algorithms for filtering and stabilizing the brightness of the video stream. The performance of the proposed algorithms was tested on real data. The algorithms were implemented in the Python software environment using the functions of the OpenCV library.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135296897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gennady Chuiko, Yevhen Darnapuk, Olga Dvornik, Yaroslav Krainyk
The article’s subject matter is the processing of abdominal EMG recordings and finding breathing patterns. The goal is to automatically classify respiratory patterns into two classes, or clusters, by two breathing patterns, regular and irregular, using machine learning (ML) methods. The object of the study was to obtain a dataset of 40 randomly picked abdominal EMG recordings (sampling rate equal to 200 Hz) borrowed from the complete dataset published by the Computational Clinical Neurophysiology Laboratory and the Clinical Data Animation Laboratory of Massachusetts General Hospital. The tasks to be solved are as follows: finding ETS (errors-trend-seasonality) model for the EMG series using the exponential smoothing method; obtaining denoised and detrended signals; obtaining the Hurst exponents for EMGs using the power-law decaying of correlograms for the denoised and detrended signals; describing the variabilities, SNR, the outlier fractions, and Hurst exponents by robust statistics, performing correlation analysis, and Principal Components Analysis (PCA); analyzing the structure of the distant matrix by a graph-based technique; obtaining the periodograms in the frequency domain using the known Wiener-Khinchin theorem; and finding the best models and methods of classification and clusterization and evaluating them within modern Machine Learning methods. The methods used are exponential smoothing, the Wiener-Khinchin theorem, the graph theory method, principal component analysis, programing within MAPLE 2020, and data processing by Weka. The authors obtained the following results: 1) wide data variability has been rated with the median absolute deviations, which is the most robust statistic in this case; 2) most of the signals (38 of 40) showed frequent outliers: from a few percent up to 24.6 % of emissions; 3) these four variables: outliers' percentage, variability, SNR, and persistency factors – form the attributes of input vectors of the subjects for further Machine Learning with Weka software; 4) Manhattan distances matrix among subjects' vectors in 4D attributes space allows imaging the data set as a weighted graph, the vertices of which are subjects; 5) the weights of the graph's edges reflect distances between any pair of them. "Closeness centralities" of vertices allowed us to cluster the data set on two clusters with 11 and 29 subjects, and Weka clustering algorithms confirmed this result. 6) The learning curve shows that a sufficiently small data set (from 25 subjects) might be suitable for classification purposes. Conclusions. The scientific novelty of the results obtained is as follows: 1) the Error-Trend-Seasonality model was the same for all data sets. Abdominal EMG of sleeping patients had additive errors and undamped trends without any seasonality; 2) the correlograms' decaying according to power law had been set, and Hurst exponents were in the range (of 0.776–0.887). This testifies to "long memory" (high persistence) of abdomina
{"title":"Abdominal electromyograms mining: breathing patterns of asleep adults","authors":"Gennady Chuiko, Yevhen Darnapuk, Olga Dvornik, Yaroslav Krainyk","doi":"10.32620/reks.2023.3.06","DOIUrl":"https://doi.org/10.32620/reks.2023.3.06","url":null,"abstract":"The article’s subject matter is the processing of abdominal EMG recordings and finding breathing patterns. The goal is to automatically classify respiratory patterns into two classes, or clusters, by two breathing patterns, regular and irregular, using machine learning (ML) methods. The object of the study was to obtain a dataset of 40 randomly picked abdominal EMG recordings (sampling rate equal to 200 Hz) borrowed from the complete dataset published by the Computational Clinical Neurophysiology Laboratory and the Clinical Data Animation Laboratory of Massachusetts General Hospital. The tasks to be solved are as follows: finding ETS (errors-trend-seasonality) model for the EMG series using the exponential smoothing method; obtaining denoised and detrended signals; obtaining the Hurst exponents for EMGs using the power-law decaying of correlograms for the denoised and detrended signals; describing the variabilities, SNR, the outlier fractions, and Hurst exponents by robust statistics, performing correlation analysis, and Principal Components Analysis (PCA); analyzing the structure of the distant matrix by a graph-based technique; obtaining the periodograms in the frequency domain using the known Wiener-Khinchin theorem; and finding the best models and methods of classification and clusterization and evaluating them within modern Machine Learning methods. The methods used are exponential smoothing, the Wiener-Khinchin theorem, the graph theory method, principal component analysis, programing within MAPLE 2020, and data processing by Weka. The authors obtained the following results: 1) wide data variability has been rated with the median absolute deviations, which is the most robust statistic in this case; 2) most of the signals (38 of 40) showed frequent outliers: from a few percent up to 24.6 % of emissions; 3) these four variables: outliers' percentage, variability, SNR, and persistency factors – form the attributes of input vectors of the subjects for further Machine Learning with Weka software; 4) Manhattan distances matrix among subjects' vectors in 4D attributes space allows imaging the data set as a weighted graph, the vertices of which are subjects; 5) the weights of the graph's edges reflect distances between any pair of them. \"Closeness centralities\" of vertices allowed us to cluster the data set on two clusters with 11 and 29 subjects, and Weka clustering algorithms confirmed this result. 6) The learning curve shows that a sufficiently small data set (from 25 subjects) might be suitable for classification purposes. Conclusions. The scientific novelty of the results obtained is as follows: 1) the Error-Trend-Seasonality model was the same for all data sets. Abdominal EMG of sleeping patients had additive errors and undamped trends without any seasonality; 2) the correlograms' decaying according to power law had been set, and Hurst exponents were in the range (of 0.776–0.887). This testifies to \"long memory\" (high persistence) of abdomina","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135296907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The evaluation of risk and uncertainty in the context of software project management is the subject of this paper. This paper discusses the difficulties faced by project managers in handling uncertainty brought on by the complex nature of software projects and the ever evolving requirements of technology. A review of the literature, data production, visualization, statistical analysis, and mathematical modeling are included in this study. The goal of this study is to create a methodical approach to assist project managers in making decisions by considering the inherent uncertainty in software development and to find approaches and procedures that may successfully reduce risks, improve decision-making, and eventually result in the implementation of successful projects. The following tasks were carried out: to evaluate risk and uncertainty by examining the state-of-the-art in decision theory and its applications in software project management; to develop an integrated strategy that blends Monte Carlo Simulation with Decision Trees to assess risk and uncertainty in software project management; to generate data, visualize it, and perform statistical analysis to comprehend how project outcomes, costs, and time are affected; to identify important variables affecting project results and decision-making using decision trees; to use Monte Carlo simulation to create project scenarios and weigh the likelihood of each; and to supply project managers with knowledge and suggestions to help them make informed decisions and successfully manage risks. Methods. To evaluate risk and uncertainty in software project management, this paper analyzes the decision theory approaches currently used as well as Decision Trees and Monte Carlo Simulation techniques. Results. This study offers thorough insights into how project results, costs, and duration vary among various techniques. The critical factors that have a substantial influence on project success are shown through decision trees. According to the study’s findings, combining decision theory and statistical analysis equips project managers to make wise decisions despite uncertainty. Conclusions. Project managers may improve decision making, risk reduction, and overall project success by applying these cutting-edge approaches. To adapt these techniques to unique software project management contexts and real-world situations, further study and implementation in practice are necessary. With the use of such techniques, the software development sector would be better able to manage the complexity of projects and provide good results within set financial and time parameters.
{"title":"Risk and uncertainty assessment in software project management: integrating decision trees and Monte Carlo modeling","authors":"Anastasiia Strielkina, Artem Tetskyi, Vladyslava Krasilshchykova","doi":"10.32620/reks.2023.3.17","DOIUrl":"https://doi.org/10.32620/reks.2023.3.17","url":null,"abstract":"The evaluation of risk and uncertainty in the context of software project management is the subject of this paper. This paper discusses the difficulties faced by project managers in handling uncertainty brought on by the complex nature of software projects and the ever evolving requirements of technology. A review of the literature, data production, visualization, statistical analysis, and mathematical modeling are included in this study. The goal of this study is to create a methodical approach to assist project managers in making decisions by considering the inherent uncertainty in software development and to find approaches and procedures that may successfully reduce risks, improve decision-making, and eventually result in the implementation of successful projects. The following tasks were carried out: to evaluate risk and uncertainty by examining the state-of-the-art in decision theory and its applications in software project management; to develop an integrated strategy that blends Monte Carlo Simulation with Decision Trees to assess risk and uncertainty in software project management; to generate data, visualize it, and perform statistical analysis to comprehend how project outcomes, costs, and time are affected; to identify important variables affecting project results and decision-making using decision trees; to use Monte Carlo simulation to create project scenarios and weigh the likelihood of each; and to supply project managers with knowledge and suggestions to help them make informed decisions and successfully manage risks. Methods. To evaluate risk and uncertainty in software project management, this paper analyzes the decision theory approaches currently used as well as Decision Trees and Monte Carlo Simulation techniques. Results. This study offers thorough insights into how project results, costs, and duration vary among various techniques. The critical factors that have a substantial influence on project success are shown through decision trees. According to the study’s findings, combining decision theory and statistical analysis equips project managers to make wise decisions despite uncertainty. Conclusions. Project managers may improve decision making, risk reduction, and overall project success by applying these cutting-edge approaches. To adapt these techniques to unique software project management contexts and real-world situations, further study and implementation in practice are necessary. With the use of such techniques, the software development sector would be better able to manage the complexity of projects and provide good results within set financial and time parameters.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135296650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The subject matter is lossy compression using the BPG encoder for medical images with varying levels of visual complexity, which are corrupted by Poisson noise. The goal of this study is to determine the optimal parameters for image compression and select the most suitable metric for identifying the optimal operational point. The tasks addressed include: selecting test images sized 512x512 in grayscale with varying degrees of visual complexity, encompassing visually intricate images rich in edges and textures, moderately complex images with edges and textures adjacent to homogeneous regions, and visually simple images primarily composed of homogeneous regions; establishing image quality evaluation metrics and assessing their performance across different encoder compression parameters; choosing one or multiple metrics that distinctly identify the position of the optimal operational point; and providing recommendations based on the attained results regarding the compression of medical images corrupted by Poisson noise using a BPG encoder, with the aim of maximizing the restored image’s quality resemblance to the original. The employed methods encompass image quality assessment techniques employing MSE, PSNR, MSSIM, and PSNR-HVS-M metrics, as well as software modeling in Python without using the built-in Poisson noise generator. The ensuing results indicate that optimal operational points (OOP) can be discerned for all these metrics when the compressed image quality surpasses that of the corresponding original image, accompanied by a sufficiently high compression ratio. Moreover, striking a suitable balance between the compression ratio and image quality leads to partial noise reduction without introducing notable distortions in the compressed image. This study underscores the significance of employing appropriate metrics for evaluating the quality of compressed medical images and provides insights into determining the compression parameter Q to attain the BPG encoder’s optimal operational point for specific images. Conclusions. The scientific novelty of the findings encompasses the following: 1) the capability of all metrics to determine the OOP for images of moderate visual complexity or those dominated by homogeneous areas; MSE and PSNR metrics demonstrating superior results for images rich in textures and edges; 2) the research highlights the dependency of Q in the OOP on the average image intensity, which can be reasonably established for a given image earmarked for compression based on our outcomes. The compression ratios for images compressed at the OOP are sufficiently high, further substantiating the rationale for compressing images in close proximity to the OOP.
{"title":"BPG-based compression analysis of Poisson-noisy medical images","authors":"Victoriia Naumenko, Bogdan Kovalenko, Volodymyr Lukin","doi":"10.32620/reks.2023.3.08","DOIUrl":"https://doi.org/10.32620/reks.2023.3.08","url":null,"abstract":"The subject matter is lossy compression using the BPG encoder for medical images with varying levels of visual complexity, which are corrupted by Poisson noise. The goal of this study is to determine the optimal parameters for image compression and select the most suitable metric for identifying the optimal operational point. The tasks addressed include: selecting test images sized 512x512 in grayscale with varying degrees of visual complexity, encompassing visually intricate images rich in edges and textures, moderately complex images with edges and textures adjacent to homogeneous regions, and visually simple images primarily composed of homogeneous regions; establishing image quality evaluation metrics and assessing their performance across different encoder compression parameters; choosing one or multiple metrics that distinctly identify the position of the optimal operational point; and providing recommendations based on the attained results regarding the compression of medical images corrupted by Poisson noise using a BPG encoder, with the aim of maximizing the restored image’s quality resemblance to the original. The employed methods encompass image quality assessment techniques employing MSE, PSNR, MSSIM, and PSNR-HVS-M metrics, as well as software modeling in Python without using the built-in Poisson noise generator. The ensuing results indicate that optimal operational points (OOP) can be discerned for all these metrics when the compressed image quality surpasses that of the corresponding original image, accompanied by a sufficiently high compression ratio. Moreover, striking a suitable balance between the compression ratio and image quality leads to partial noise reduction without introducing notable distortions in the compressed image. This study underscores the significance of employing appropriate metrics for evaluating the quality of compressed medical images and provides insights into determining the compression parameter Q to attain the BPG encoder’s optimal operational point for specific images. Conclusions. The scientific novelty of the findings encompasses the following: 1) the capability of all metrics to determine the OOP for images of moderate visual complexity or those dominated by homogeneous areas; MSE and PSNR metrics demonstrating superior results for images rich in textures and edges; 2) the research highlights the dependency of Q in the OOP on the average image intensity, which can be reasonably established for a given image earmarked for compression based on our outcomes. The compression ratios for images compressed at the OOP are sufficiently high, further substantiating the rationale for compressing images in close proximity to the OOP.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135296903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The subject matter of this article is a control system for unmanned aerial vehicles (UAVs) whose mathematical model is a finite state machine (FSM). The goal is to develop FSM structural models that enable (1) detection of multiple faults of FSM elements caused by an electromagnetic pulse or laser beam, and (2) prevent negative impacts on the controlled object. The tasks to be solved are as follows: to develop FSM structural models to detect invalid input vector X for the whole FSM and in each state, to detect invalid output vector Y for the whole FSM, at each transition and in each state, invalid code of the present (current) state, invalid code of the next state, and invalid transition between states; to determine the possible causes of the faults, which can be the failure in the logic Φ of forming the code of the next state, the invalid input vector X, the failure in the feedback circuit, the failure in the logic Ψ of forming the output vector, the failure in the state register R, the failure in the wire between the FSM input and the input of the logic Ψ; development of a combined structural model for the detection of all listed faults with a minimum number of additional combinational circuits, as well as a structural model that combines all additional combinational circuits. The methods used are: the theory of finite state machines, structural models of FSMs, state encoding methods of FSMs, representation methods of FSMs, and Verilog hardware description language. The following results were obtained: (1) the Mealy FSM structural models were developed to detect all the above mentioned faults, (2) the combined FSM structural models were developed, and (3) the possible causes of faults detected by each FSM structural model were identified. Experimental studies have shown that for the presented FSM structural models, the area overhead averages 3-23%, for one-hot encoding of FSM states, and 2-8%, for binary encoding of FSM states. Conclusions. The scientific novelty of the obtained results consists in the following for the first time FSM faults that are not caused by radiation and cosmic rays but by an electromagnetic pulse affecting the control device are considered; the number of faults is not limited for the state codes as well as for the input and output vectors; the faults can be detected not only in the state register R but also in the input vector X, in the logic Φ of generating the next state code, in the logic Ψ of generating the output signals, and in the feedback circuit; the invalid transitions of FSMs and the transitions to invalid states are also detected; the proposed structural models not only detect FSM failures but also prevent their negative impact on the controlled object; combined structural models allow simultaneous detection of faults in all elements of the FSM. Future research will focus on developing structural models for correcting FSM failures.
{"title":"Structural models of Mealy finite state machines detecting faults in control systems","authors":"Valery Salauyou","doi":"10.32620/reks.2023.3.14","DOIUrl":"https://doi.org/10.32620/reks.2023.3.14","url":null,"abstract":"The subject matter of this article is a control system for unmanned aerial vehicles (UAVs) whose mathematical model is a finite state machine (FSM). The goal is to develop FSM structural models that enable (1) detection of multiple faults of FSM elements caused by an electromagnetic pulse or laser beam, and (2) prevent negative impacts on the controlled object. The tasks to be solved are as follows: to develop FSM structural models to detect invalid input vector X for the whole FSM and in each state, to detect invalid output vector Y for the whole FSM, at each transition and in each state, invalid code of the present (current) state, invalid code of the next state, and invalid transition between states; to determine the possible causes of the faults, which can be the failure in the logic Φ of forming the code of the next state, the invalid input vector X, the failure in the feedback circuit, the failure in the logic Ψ of forming the output vector, the failure in the state register R, the failure in the wire between the FSM input and the input of the logic Ψ; development of a combined structural model for the detection of all listed faults with a minimum number of additional combinational circuits, as well as a structural model that combines all additional combinational circuits. The methods used are: the theory of finite state machines, structural models of FSMs, state encoding methods of FSMs, representation methods of FSMs, and Verilog hardware description language. The following results were obtained: (1) the Mealy FSM structural models were developed to detect all the above mentioned faults, (2) the combined FSM structural models were developed, and (3) the possible causes of faults detected by each FSM structural model were identified. Experimental studies have shown that for the presented FSM structural models, the area overhead averages 3-23%, for one-hot encoding of FSM states, and 2-8%, for binary encoding of FSM states. Conclusions. The scientific novelty of the obtained results consists in the following for the first time FSM faults that are not caused by radiation and cosmic rays but by an electromagnetic pulse affecting the control device are considered; the number of faults is not limited for the state codes as well as for the input and output vectors; the faults can be detected not only in the state register R but also in the input vector X, in the logic Φ of generating the next state code, in the logic Ψ of generating the output signals, and in the feedback circuit; the invalid transitions of FSMs and the transitions to invalid states are also detected; the proposed structural models not only detect FSM failures but also prevent their negative impact on the controlled object; combined structural models allow simultaneous detection of faults in all elements of the FSM. Future research will focus on developing structural models for correcting FSM failures.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":"223 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135296772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The subject matter of this article is business analysis and requirement engineering (BA/RE) in software projects. The goal is to identify the challenges faced by Ukrainian business analysts and requirement engineers in software development projects and investigate the possible reasons and negative consequences of these issues. The tasks to be solved are: create and conduct a survey on the practices of BA/RE in IT projects, define the most critical problems in BA/RE, their causes and implications, and define how project context influences problems in business analysis and requirement engineering. The methods used are: a survey (N = 324) was performed among business analysts and requirement engineers in Ukraine regarding problems in BA/RE and the context of IT projects in which they manifest. The Chi-Square test of independence and Cramer's V effect size measure were applied to define statistically significant dependencies between project context and BA/RE problems. The following results were obtained: the most critical problems in BA/RE, their causes, and their implications were defined and compared with other comprehensive studies. Twelve statistically significant associations for pairs "project context – BA/RE problem" were found (based on the p-value and Cramer's V effect size measure). Conclusion: 1) A comparison of the results of this study with similar studies conducted in other contexts has shown that the issues identified by Ukrainian BA/RE professionals are similar to those found by other researchers in other countries; 2) it is concluded that project context influences particular BA/RE problems, and these dependencies allow us to develop recommendations for risk management for particular problems depending on the project context.
{"title":"Towards identifying challenges in business analysis on IT projects – a practical study","authors":"Denys Gobov, Olha Titlova","doi":"10.32620/reks.2023.2.16","DOIUrl":"https://doi.org/10.32620/reks.2023.2.16","url":null,"abstract":"The subject matter of this article is business analysis and requirement engineering (BA/RE) in software projects. The goal is to identify the challenges faced by Ukrainian business analysts and requirement engineers in software development projects and investigate the possible reasons and negative consequences of these issues. The tasks to be solved are: create and conduct a survey on the practices of BA/RE in IT projects, define the most critical problems in BA/RE, their causes and implications, and define how project context influences problems in business analysis and requirement engineering. The methods used are: a survey (N = 324) was performed among business analysts and requirement engineers in Ukraine regarding problems in BA/RE and the context of IT projects in which they manifest. The Chi-Square test of independence and Cramer's V effect size measure were applied to define statistically significant dependencies between project context and BA/RE problems. The following results were obtained: the most critical problems in BA/RE, their causes, and their implications were defined and compared with other comprehensive studies. Twelve statistically significant associations for pairs \"project context – BA/RE problem\" were found (based on the p-value and Cramer's V effect size measure). Conclusion: 1) A comparison of the results of this study with similar studies conducted in other contexts has shown that the issues identified by Ukrainian BA/RE professionals are similar to those found by other researchers in other countries; 2) it is concluded that project context influences particular BA/RE problems, and these dependencies allow us to develop recommendations for risk management for particular problems depending on the project context.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43202488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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