The research object is the mathematical modeling of human skeletal muscle electrical stimulation characteristics during therapy. The subject of research is mathematical models of electrical stimulation characteristics that relate muscle contraction amplitude to the amplitude, the rate of stimulating effects, and other parameters. The research purpose is to study such models, develop an algorithm for their correction and a method for estimating their adequacy. The methods used: mathematical modeling methods, methods of structural and parametric identification of models, optimization methods, methods for estimating the adequacy of models, and interval methods. The results: an algorithm for muscle electrical stimulation characteristics mathematical models correcting during several sessions in case of their change is proposed; a method for estimating the model adequacy area in the external variables space in order to control its adequacy is proposed; using the interval mathematics methods to construct the adequacy actual area is justified; an interval estimating of the error in modeling a certain output characteristic is introduced, that, in the case of characteristic monotonicity, allows checking the adequacy maintaining by checking some inequalities. The results can be used in the design of electrical stimulators and for determining the electrical stimulation effects of individual parameters during one session or a series of sessions. The scientific originality: the interval mathematics methods for approximating the mathematical model adequacy area in a hyperparallepiped and checking for nesting in the target area in the external parameters space in order to control the adequacy during the model correction in electrical stimulation is proposed and justified.
{"title":"Modeling and estimating the model adequacy in muscle tissue electrical stimulator designing","authors":"I. Prasol, Olha Yeroshenko","doi":"10.32620/reks.2023.2.02","DOIUrl":"https://doi.org/10.32620/reks.2023.2.02","url":null,"abstract":"The research object is the mathematical modeling of human skeletal muscle electrical stimulation characteristics during therapy. The subject of research is mathematical models of electrical stimulation characteristics that relate muscle contraction amplitude to the amplitude, the rate of stimulating effects, and other parameters. The research purpose is to study such models, develop an algorithm for their correction and a method for estimating their adequacy. The methods used: mathematical modeling methods, methods of structural and parametric identification of models, optimization methods, methods for estimating the adequacy of models, and interval methods. The results: an algorithm for muscle electrical stimulation characteristics mathematical models correcting during several sessions in case of their change is proposed; a method for estimating the model adequacy area in the external variables space in order to control its adequacy is proposed; using the interval mathematics methods to construct the adequacy actual area is justified; an interval estimating of the error in modeling a certain output characteristic is introduced, that, in the case of characteristic monotonicity, allows checking the adequacy maintaining by checking some inequalities. The results can be used in the design of electrical stimulators and for determining the electrical stimulation effects of individual parameters during one session or a series of sessions. The scientific originality: the interval mathematics methods for approximating the mathematical model adequacy area in a hyperparallepiped and checking for nesting in the target area in the external parameters space in order to control the adequacy during the model correction in electrical stimulation is proposed and justified.","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":"47524457","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}
E. Fedorov, O. Nechyporenko, Maryna Chychuzhko, Vladyslav Chychuzhko, Ruslan Leshchenko
Nowadays, solving optimizations problems is one of the tasks for intelligent computer systems. Currently, there is a problem of insufficient efficiency of optimizations tasks solving methods (for example, high computing time and/or accuracy). The object of the research is the process of finding the shortest path and establishing associative connections between objects. The subject of the research is the methods of finding the shortest path and establishing associative connections between objects based on neural networks with associative memory and neural network reinforcement training. The objective of this work is to improve the efficiency of finding the shortest path and establishing associative connections between objects through neural networks with associative memory and neural network reinforcement training. To achieve this goal, a neuro-associative method and a neural network reinforcement training method was developed. The advantages of the proposed methods include the following. First, the proposed bi-directional recurrent correlative associative memory, which uses hetero-associative and auto-associative memory and an exponential weighting function, allows for increasing the associative memory capacity while preserving learning accuracy. Second, the Deep Q-Network (DQN) reinforcement learning method with dynamic parameters uses the ε-greedy approach, which in the initial iterations is close to random search, and in the final iterations is close to directed search, which is ensured by using dynamic parameters and allows increasing the learning speed while preserving learning accuracy. Conducted numerical research allowed us to estimate both methods (for the first method, the root mean square error was 0.02, and for the second method it was 0.05). The proposed methods allow expanding the field of application of neural networks with associative memory and neural network reinforcement learning, which is confirmed by their adaptation for the tasks of finding the shortest path and establishing associative connections between objects and contribute to the effectiveness of intelligent computer systems of general and special purpose. Prospects for further research are to investigate the proposed methods for a wide class of artificial intelligence problems.
{"title":"NEURAL NETWORK-BASED METHODS FOR FINDING THE SHORTEST PATH and establishing associative connections between objects","authors":"E. Fedorov, O. Nechyporenko, Maryna Chychuzhko, Vladyslav Chychuzhko, Ruslan Leshchenko","doi":"10.32620/reks.2023.2.05","DOIUrl":"https://doi.org/10.32620/reks.2023.2.05","url":null,"abstract":"Nowadays, solving optimizations problems is one of the tasks for intelligent computer systems. Currently, there is a problem of insufficient efficiency of optimizations tasks solving methods (for example, high computing time and/or accuracy). The object of the research is the process of finding the shortest path and establishing associative connections between objects. The subject of the research is the methods of finding the shortest path and establishing associative connections between objects based on neural networks with associative memory and neural network reinforcement training. The objective of this work is to improve the efficiency of finding the shortest path and establishing associative connections between objects through neural networks with associative memory and neural network reinforcement training. To achieve this goal, a neuro-associative method and a neural network reinforcement training method was developed. The advantages of the proposed methods include the following. First, the proposed bi-directional recurrent correlative associative memory, which uses hetero-associative and auto-associative memory and an exponential weighting function, allows for increasing the associative memory capacity while preserving learning accuracy. Second, the Deep Q-Network (DQN) reinforcement learning method with dynamic parameters uses the ε-greedy approach, which in the initial iterations is close to random search, and in the final iterations is close to directed search, which is ensured by using dynamic parameters and allows increasing the learning speed while preserving learning accuracy. Conducted numerical research allowed us to estimate both methods (for the first method, the root mean square error was 0.02, and for the second method it was 0.05). The proposed methods allow expanding the field of application of neural networks with associative memory and neural network reinforcement learning, which is confirmed by their adaptation for the tasks of finding the shortest path and establishing associative connections between objects and contribute to the effectiveness of intelligent computer systems of general and special purpose. Prospects for further research are to investigate the proposed methods for a wide class of artificial intelligence problems.","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":"48847807","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 Yaloveha, A. Podorozhniak, Heorhii Kuchuk, Nataliia Garashchuk
Multispectral images acquired by satellites have been used in many fields such as agriculture, urban change detection, finding fire-hazardous forest areas, and real-time surface monitoring. The central issue in remote sensing analysis is land use and land cover classification. Land use and land cover classification (LULC) is the process of classification into meaningful classes based on the spectral characteristics of remote sensing data. Land use and land cover classification is a challenging task due to the complex nature of the Earth's surface. The accuracy of solving the issue using deep learning approaches depends on the quality of the remote sensing data, the choice of the classification algorithm. The ability to obtain high-resolution multispectral images periodically could dramatically improve remote sensing solutions. In this study, we propose a solution for the land cover and land classification problem of high-resolution remote sensing data by applying deep learning methods using EuroPlanet geo-referenced high-quality images with four bands and pixel resolution of 204x204 per image, and acquired by Planet platform in 2020-2022 years. The dataset consists of 25911 images with spatial resolution up to 3.125 meters per pixel and 10 different classes. In the past decade, artificial neural networks have shown great performance in solving complex image classification tasks. For the dataset evaluation, we have taken advantage of state-of-art pretrained convolutional neural network models ResNet50v2, EfficientNetV2, Xception, VGG-16, and DenseNet201 with fine tuning. It has been established that DenseNet201 pretrained neural network outperformed other models. The accuracy of the test data was 92.01 % and the F1 metric was 91.63 %. In addition, bands evaluation for the dataset was carried out. Overall classification accuracy of 93.83 % and F1 score of 93.56 % were achieved by DenseNet201 model. The results could be used for area verification, real-time monitoring, and surface change detection. Nowadays, this is very helpful for Ukrainian territory because of the Russian invasion and the country's recovery in the future.
{"title":"Performance comparison of CNNs on high-resolution multispectral dataset applied to land cover classification problem","authors":"Vladyslav Yaloveha, A. Podorozhniak, Heorhii Kuchuk, Nataliia Garashchuk","doi":"10.32620/reks.2023.2.09","DOIUrl":"https://doi.org/10.32620/reks.2023.2.09","url":null,"abstract":"Multispectral images acquired by satellites have been used in many fields such as agriculture, urban change detection, finding fire-hazardous forest areas, and real-time surface monitoring. The central issue in remote sensing analysis is land use and land cover classification. Land use and land cover classification (LULC) is the process of classification into meaningful classes based on the spectral characteristics of remote sensing data. Land use and land cover classification is a challenging task due to the complex nature of the Earth's surface. The accuracy of solving the issue using deep learning approaches depends on the quality of the remote sensing data, the choice of the classification algorithm. The ability to obtain high-resolution multispectral images periodically could dramatically improve remote sensing solutions. In this study, we propose a solution for the land cover and land classification problem of high-resolution remote sensing data by applying deep learning methods using EuroPlanet geo-referenced high-quality images with four bands and pixel resolution of 204x204 per image, and acquired by Planet platform in 2020-2022 years. The dataset consists of 25911 images with spatial resolution up to 3.125 meters per pixel and 10 different classes. In the past decade, artificial neural networks have shown great performance in solving complex image classification tasks. For the dataset evaluation, we have taken advantage of state-of-art pretrained convolutional neural network models ResNet50v2, EfficientNetV2, Xception, VGG-16, and DenseNet201 with fine tuning. It has been established that DenseNet201 pretrained neural network outperformed other models. The accuracy of the test data was 92.01 % and the F1 metric was 91.63 %. In addition, bands evaluation for the dataset was carried out. Overall classification accuracy of 93.83 % and F1 score of 93.56 % were achieved by DenseNet201 model. The results could be used for area verification, real-time monitoring, and surface change detection. Nowadays, this is very helpful for Ukrainian territory because of the Russian invasion and the country's recovery in the future.","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":"47265333","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}
A. Serkov, O. Kasilov, Bogdan Lazurenko, Volodimir Pevnev, Karyna Trubchaninova
The subject of research in this article is the process of building a mobile communication system that operates under electronic countermeasures. The aim is to develop recommendations for building a wireless mobile communication system that operates effectively in a complex interfering electromagnetic environment. The strategy for building a mobile wireless communication system is based on the use of a grouping of low-altitude UAVs with ultra-wideband signal technology circulating in control and communication channels, with the integration of artificial intelligence elements into its structure. The objective of this study is to ensure the stable and secure operation of a wireless mobile communication system despite electronic countermeasures. The methods of analytical, temporal positional pulse coding, and fuzzy logical inference were used to make decisions on the transfer of service in the network. The following results were obtained. A strategy for building a wireless mobile communication system despite electronic countermeasures has been developed. It is shown that in order to obtain high noise immunity of control and communication channels and to protect information from interception, wireless ultra-wideband communication technology should be used. This will provide large volumes and speeds of information transmission. A technical solution for the design of an ultra-wideband transceiver antenna system is proposed. Moreover, it is recommended to use the results of data processing in a fuzzy decision-making system for the transfer of service between mobile network nodes in conditions of interference. Conclusions. The scientific novelty of the obtained results is as follows. The use of ultra-wideband channels makes it possible to increase the number of control and communication channels in a wireless mobile system almost unlimitedly. The preliminary distribution of orthogonal codes between the channels realizes the process of control and communication without the interception of information and mutual interference. The use of the time-position-pulse coding method prevents the occurrence of intercharacter distortions of the encoding ultrashort pulses. This also reduces the level of distortion of information signals caused by multipath propagation, which guarantees the security of information in the system. The use of a fuzzy decision-making system for the transfer of services between mobile network nodes allows dynamically changing the network topology in real time and maintaining high quality of service under electronic countermeasures.
{"title":"Strategy of building a wireless mobile communication system in the conditions of electronic counteraction","authors":"A. Serkov, O. Kasilov, Bogdan Lazurenko, Volodimir Pevnev, Karyna Trubchaninova","doi":"10.32620/reks.2023.2.13","DOIUrl":"https://doi.org/10.32620/reks.2023.2.13","url":null,"abstract":"The subject of research in this article is the process of building a mobile communication system that operates under electronic countermeasures. The aim is to develop recommendations for building a wireless mobile communication system that operates effectively in a complex interfering electromagnetic environment. The strategy for building a mobile wireless communication system is based on the use of a grouping of low-altitude UAVs with ultra-wideband signal technology circulating in control and communication channels, with the integration of artificial intelligence elements into its structure. The objective of this study is to ensure the stable and secure operation of a wireless mobile communication system despite electronic countermeasures. The methods of analytical, temporal positional pulse coding, and fuzzy logical inference were used to make decisions on the transfer of service in the network. The following results were obtained. A strategy for building a wireless mobile communication system despite electronic countermeasures has been developed. It is shown that in order to obtain high noise immunity of control and communication channels and to protect information from interception, wireless ultra-wideband communication technology should be used. This will provide large volumes and speeds of information transmission. A technical solution for the design of an ultra-wideband transceiver antenna system is proposed. Moreover, it is recommended to use the results of data processing in a fuzzy decision-making system for the transfer of service between mobile network nodes in conditions of interference. Conclusions. The scientific novelty of the obtained results is as follows. The use of ultra-wideband channels makes it possible to increase the number of control and communication channels in a wireless mobile system almost unlimitedly. The preliminary distribution of orthogonal codes between the channels realizes the process of control and communication without the interception of information and mutual interference. The use of the time-position-pulse coding method prevents the occurrence of intercharacter distortions of the encoding ultrashort pulses. This also reduces the level of distortion of information signals caused by multipath propagation, which guarantees the security of information in the system. The use of a fuzzy decision-making system for the transfer of services between mobile network nodes allows dynamically changing the network topology in real time and maintaining high quality of service under electronic countermeasures.","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":"48345390","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 study in this article is the voltage ranges, methods, and tools for prototyping independent sources of power supply and artificial lighting for home appliances with reuse of only widespread components. The goal is to improve the efficiency of the creation and use of independent power supply sources for home appliances. Task: to analyze the history of the development of voltage standards for households; analyze existing autonomous power sources and types of batteries; analyze different loads; find rational voltage ranges based on fundamental values; analyze charge control and balancing circuits for lithium-based batteries; propose the technique of prototyping independent sources of power supply based on reused lithium-ion (Li-ion) accumulators; provide an example of the practical application of the results of research. According to the tasks, the following results were obtained. The evolution of voltage standards of electrical supply networks is analyzed. Types of autonomous power supplies, including pure sine versions, are discussed. The analysis of batteries for autonomous power sources of different chemical compositions is performed. It is proposed to use the water analogy of current and area as an analogy of battery capacity for visual representation of electrical processes. Models of constant current consumption and constant power consumption are considered. It is proposed to reduce the internal resistance of the battery assembly by parallel connection of the reused lithium-ion accumulators. Correspondence of voltage ranges of sequential connection of lithium-ion cells to ensure compatibility with existing devices is investigated. Rational parameters of voltage ranges to ensure compatibility of lithium-ion and acid accumulators with the ability to charge directly from solar panels without a charge controller are found. Charge controllers, battery management systems (BMS), and battery balancing circuits are analyzed. A set of steps for reuse of lithium-ion accumulators for the creation of autonomous power sources is proposed. Conclusions. The main contribution of this research is the proposed method of creation of power supply and interior lighting based on the reuse of accumulators without additional components. The discovered and proposed magic numbers of 3, 5, 7, 9, 11 and 13 for series connection of lithium-ion cells allows to obtain the equivalent of standard voltage ranges of 12 V, 19 V, 27 V, 36 V, 42 V and 48 V. The proposed technique of adjusting the voltage of the passive balancer allows adding 4.5 % to the capacity of the battery assembly. The described solutions allow to build the completely scalable autonomous low-voltage electrical supply network with the ability to charge directly from solar panels without expensive charge controllers.
{"title":"Method of creation of power sources for home appliances under constraints of limited resources","authors":"A. Perepelitsyn, A. Tetskyi","doi":"10.32620/reks.2023.2.07","DOIUrl":"https://doi.org/10.32620/reks.2023.2.07","url":null,"abstract":"The subject of study in this article is the voltage ranges, methods, and tools for prototyping independent sources of power supply and artificial lighting for home appliances with reuse of only widespread components. The goal is to improve the efficiency of the creation and use of independent power supply sources for home appliances. Task: to analyze the history of the development of voltage standards for households; analyze existing autonomous power sources and types of batteries; analyze different loads; find rational voltage ranges based on fundamental values; analyze charge control and balancing circuits for lithium-based batteries; propose the technique of prototyping independent sources of power supply based on reused lithium-ion (Li-ion) accumulators; provide an example of the practical application of the results of research. According to the tasks, the following results were obtained. The evolution of voltage standards of electrical supply networks is analyzed. Types of autonomous power supplies, including pure sine versions, are discussed. The analysis of batteries for autonomous power sources of different chemical compositions is performed. It is proposed to use the water analogy of current and area as an analogy of battery capacity for visual representation of electrical processes. Models of constant current consumption and constant power consumption are considered. It is proposed to reduce the internal resistance of the battery assembly by parallel connection of the reused lithium-ion accumulators. Correspondence of voltage ranges of sequential connection of lithium-ion cells to ensure compatibility with existing devices is investigated. Rational parameters of voltage ranges to ensure compatibility of lithium-ion and acid accumulators with the ability to charge directly from solar panels without a charge controller are found. Charge controllers, battery management systems (BMS), and battery balancing circuits are analyzed. A set of steps for reuse of lithium-ion accumulators for the creation of autonomous power sources is proposed. Conclusions. The main contribution of this research is the proposed method of creation of power supply and interior lighting based on the reuse of accumulators without additional components. The discovered and proposed magic numbers of 3, 5, 7, 9, 11 and 13 for series connection of lithium-ion cells allows to obtain the equivalent of standard voltage ranges of 12 V, 19 V, 27 V, 36 V, 42 V and 48 V. The proposed technique of adjusting the voltage of the passive balancer allows adding 4.5 % to the capacity of the battery assembly. The described solutions allow to build the completely scalable autonomous low-voltage electrical supply network with the ability to charge directly from solar panels without expensive charge controllers.","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":"44657486","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}
Images are mainly viewed and analyzed by humans. Because of this, in the characterization of image quality and effectiveness of image processing, it is necessary to take into account the peculiarities of the human vision system and cognition that are very complex. Saliency maps as well as priority and meaning maps introduced recently are the attempts to incorporate specific features of human vision into image analysis and processing fields. Many authors that consider the aforementioned maps consider them from different viewpoints. Thus, the basic subject of this paper is the factors that influence and determine these maps. Among such factors, there are low-level features as well as social and psychological ones such as emotions, age, and life values. The main goal of this paper is to give a brief survey of these factors and to consider how maps are already used in image quality assessment and processing as well as how they can be employed in the future. The tasks of the paper are to provide a definition of saliency, priority, and meaning maps, to analyze the factors that influence these maps, and to evaluate what improvement can be obtained due to taking maps into account in the assessment of image visual quality and such image processing operations as quality assessment, denoising, and lossy compression. The main result is that, by taking saliency maps into account, image quality assessment and processing efficiency can be sufficiently improved, especially for applications oriented on image viewing and analysis by observers or customers. This can be done by the simple weighting of local estimates of a given metric with further aggregation as well as by approaches based on neural networks. Using different quantitative criteria, we show what positive results can be got due to incorporating maps into quality assessment and image processing. As conclusion, we present possible directions of future research that are mainly related to an adaptation of denoising and lossy compression parameters to peculiarities of human attention.
{"title":"Saliency map in image visual quality assessment and processing","authors":"V. Lukin, E. Bataeva, S. Abramov","doi":"10.32620/reks.2023.1.09","DOIUrl":"https://doi.org/10.32620/reks.2023.1.09","url":null,"abstract":"Images are mainly viewed and analyzed by humans. Because of this, in the characterization of image quality and effectiveness of image processing, it is necessary to take into account the peculiarities of the human vision system and cognition that are very complex. Saliency maps as well as priority and meaning maps introduced recently are the attempts to incorporate specific features of human vision into image analysis and processing fields. Many authors that consider the aforementioned maps consider them from different viewpoints. Thus, the basic subject of this paper is the factors that influence and determine these maps. Among such factors, there are low-level features as well as social and psychological ones such as emotions, age, and life values. The main goal of this paper is to give a brief survey of these factors and to consider how maps are already used in image quality assessment and processing as well as how they can be employed in the future. The tasks of the paper are to provide a definition of saliency, priority, and meaning maps, to analyze the factors that influence these maps, and to evaluate what improvement can be obtained due to taking maps into account in the assessment of image visual quality and such image processing operations as quality assessment, denoising, and lossy compression. The main result is that, by taking saliency maps into account, image quality assessment and processing efficiency can be sufficiently improved, especially for applications oriented on image viewing and analysis by observers or customers. This can be done by the simple weighting of local estimates of a given metric with further aggregation as well as by approaches based on neural networks. Using different quantitative criteria, we show what positive results can be got due to incorporating maps into quality assessment and image processing. As conclusion, we present possible directions of future research that are mainly related to an adaptation of denoising and lossy compression parameters to peculiarities of human attention.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41394162","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}
COVID-19 pandemic has significantly impacted the world, with millions of infections and deaths, healthcare systems overwhelmed, economies disrupted, and daily life changed. Simulation has been recognized as a valuable tool in combating the pandemic, helping to model the spread of the virus, evaluate the impact of interventions, and inform decision-making processes. The accuracy and effectiveness of simulations depend on the quality of the underlying data, assumptions, and modeling techniques. Ongoing efforts to improve and refine simulation approaches can enhance their value in addressing future public health emergencies. The Russian full-scale military invasion of Ukraine on February 24, 2022, has created a significant humanitarian and public health crisis, with disrupted healthcare services, shortages of medical supplies, and increased demand for emergency care. The ongoing conflict has displaced millions of people, with Spain ranking 5th in the world for the number of registered refugees from Ukraine. The research aims to estimate the impact of the Russian war in Ukraine on COVID-19 transmission in Spain using means of machine learning. The research is targeted at COVID-19 epidemic process during the war. The research subjects are methods and models of epidemic process simulation based on machine learning. To achieve the study's aim, we used forecasting methods and built a model of COVID-19 epidemic process based on the XGBoost method. As a result of the experiments, the accuracy of forecasting new cases of COVID-19 in Spain for 30 days was 99.79 %, and the death cases of COVID-19 in Spain – were 99.86 %. The model was applied to data on the incidence of COVID-19 in Spain for the first 30 days of the war escalation (24.02.2022 – 25.03.2022). The calculated forecasted values showed that the forced migration of the Ukrainian population to Spain, caused by the full-scale invasion of Russia, is not a decisive factor affecting the dynamics of the epidemic process of COVID-19 in Spain. Conclusions. The paper describes the results of an experimental study assessing the impact of the Russian full-scale war in Ukraine on COVID-19 dynamics in Spain. The developed model showed good performance to use it in public health practice. The analysis of the obtained results of the experimental study showed that the forced migration of the Ukrainian population to Spain, caused by the full-scale invasion of Russia, is not a decisive factor affecting the dynamics of the epidemic process of COVID-19 in Spain.
{"title":"Assessing the impact of the russian war in Ukraine on COVID-19 transmission in Spain: a machine learning-based study","authors":"D. Chumachenko, T. Dudkina, T. Chumachenko","doi":"10.32620/reks.2023.1.01","DOIUrl":"https://doi.org/10.32620/reks.2023.1.01","url":null,"abstract":"COVID-19 pandemic has significantly impacted the world, with millions of infections and deaths, healthcare systems overwhelmed, economies disrupted, and daily life changed. Simulation has been recognized as a valuable tool in combating the pandemic, helping to model the spread of the virus, evaluate the impact of interventions, and inform decision-making processes. The accuracy and effectiveness of simulations depend on the quality of the underlying data, assumptions, and modeling techniques. Ongoing efforts to improve and refine simulation approaches can enhance their value in addressing future public health emergencies. The Russian full-scale military invasion of Ukraine on February 24, 2022, has created a significant humanitarian and public health crisis, with disrupted healthcare services, shortages of medical supplies, and increased demand for emergency care. The ongoing conflict has displaced millions of people, with Spain ranking 5th in the world for the number of registered refugees from Ukraine. The research aims to estimate the impact of the Russian war in Ukraine on COVID-19 transmission in Spain using means of machine learning. The research is targeted at COVID-19 epidemic process during the war. The research subjects are methods and models of epidemic process simulation based on machine learning. To achieve the study's aim, we used forecasting methods and built a model of COVID-19 epidemic process based on the XGBoost method. As a result of the experiments, the accuracy of forecasting new cases of COVID-19 in Spain for 30 days was 99.79 %, and the death cases of COVID-19 in Spain – were 99.86 %. The model was applied to data on the incidence of COVID-19 in Spain for the first 30 days of the war escalation (24.02.2022 – 25.03.2022). The calculated forecasted values showed that the forced migration of the Ukrainian population to Spain, caused by the full-scale invasion of Russia, is not a decisive factor affecting the dynamics of the epidemic process of COVID-19 in Spain. Conclusions. The paper describes the results of an experimental study assessing the impact of the Russian full-scale war in Ukraine on COVID-19 dynamics in Spain. The developed model showed good performance to use it in public health practice. The analysis of the obtained results of the experimental study showed that the forced migration of the Ukrainian population to Spain, caused by the full-scale invasion of Russia, is not a decisive factor affecting the dynamics of the epidemic process of COVID-19 in Spain.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41888529","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}
N. Koshevoy, I. Ilina, V. Tokariev, Anna Malkova, V. Muratov
One of the main ways to improve the efficiency of experimental research is the use of methods for planning experiments. At the same time, experiment planning can significantly reduce the amount of experimental research by reducing the number of experiments, as well as improve the accuracy and reliability of the results obtained. It is characteristic that the experiments in terms of experiment are not equivalent, that is, their implementation requires different material and time costs. In this regard, the problem arises of optimizing the plans of multivariate experiments in terms of cost or time costs. This is especially important when studying valuable and long-term processes. To solve the problems of optimizing plans for multifactorial experiments in terms of cost (time) costs, it is necessary to develop effective methods for finding optimal plans and their software. Existing methods for optimizing experimental plans are characterized by such shortcomings as low speed, a limited number of studied object factors, and the exact solution is not always found. This article explores the method of gravitational search for the optimal cost (time) cost plan for multifactorial experiments. The method uses the analogy of the motion of solid bodies due to their gravitational interaction. In this case, the rows of the experiment planning matrix are considered as such solid bodies, which are placed in it depending on the decrease in the cost of transitions between rows (gravity). An algorithm and software have been developed that implement the proposed method. The program is presented in the algorithmic language Python. On a number of examples for the study of technological processes, the efficiency and effectiveness of the method of gravitational search for optimal cost (time) costs of plans for multifactor experiments has been proved. The object of the research: processes of optimization of plans of multifactorial experiments according to cost (time) costs. The subject of the study: the method of gravitational search for the optimal cost (time) plans of multifactorial experiments and the software implementing it.
{"title":"Implementation of the gravity search method for optimization by cost expenses of plans for multifactorial experiments","authors":"N. Koshevoy, I. Ilina, V. Tokariev, Anna Malkova, V. Muratov","doi":"10.32620/reks.2023.1.02","DOIUrl":"https://doi.org/10.32620/reks.2023.1.02","url":null,"abstract":"One of the main ways to improve the efficiency of experimental research is the use of methods for planning experiments. At the same time, experiment planning can significantly reduce the amount of experimental research by reducing the number of experiments, as well as improve the accuracy and reliability of the results obtained. It is characteristic that the experiments in terms of experiment are not equivalent, that is, their implementation requires different material and time costs. In this regard, the problem arises of optimizing the plans of multivariate experiments in terms of cost or time costs. This is especially important when studying valuable and long-term processes. To solve the problems of optimizing plans for multifactorial experiments in terms of cost (time) costs, it is necessary to develop effective methods for finding optimal plans and their software. Existing methods for optimizing experimental plans are characterized by such shortcomings as low speed, a limited number of studied object factors, and the exact solution is not always found. This article explores the method of gravitational search for the optimal cost (time) cost plan for multifactorial experiments. The method uses the analogy of the motion of solid bodies due to their gravitational interaction. In this case, the rows of the experiment planning matrix are considered as such solid bodies, which are placed in it depending on the decrease in the cost of transitions between rows (gravity). An algorithm and software have been developed that implement the proposed method. The program is presented in the algorithmic language Python. On a number of examples for the study of technological processes, the efficiency and effectiveness of the method of gravitational search for optimal cost (time) costs of plans for multifactor experiments has been proved. The object of the research: processes of optimization of plans of multifactorial experiments according to cost (time) costs. The subject of the study: the method of gravitational search for the optimal cost (time) plans of multifactorial experiments and the software implementing it.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47534568","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}
This article presents the results of the development of silicon coordinate p-i-n photodiodes (PD) with improved parameters. The technological possibilities of reducing the gaps between the responsive areas of multi-element PDs were studied. PDs with reduced gaps were modeled, samples were made according to the models, the parameters of the obtained PDs and the influence of various technological factors on their values were investigated. During research, it was established that the factor that limits the possibility of reducing the gaps is the insulation resistance between the responsive elements. The decrease in the insulation resistance between the PD elements was a consequence of the formation of inversion leakage channels at the Si-SiO2 interface, which is characteristic of high-resistance p-type silicon, the conductivity of which increased with a decrease in the width of the gaps. To increase the resistance of the gaps between the platforms and reduce the influence of inversion layers, it was decided to form regions of the restriction of the leakage channels between the REs – highly doped regions isotypic with the substrate material (p+-type). They will prevent the movement of current carriers that are generated in the inversion layers on the surface of the substrate. Four-element p-i-n photodiodes with 31 μm gaps between the sites were made. The proposed PD is not significantly inferior in parameters to analogues, but it is the sample with the smallest gaps between RE among photodiodes of the same type and size in the world market. The improvement of the insulation resistance between the REs made it possible to reduce the level of dark current of the PD by twice compared to serial products, with a slight decrease in responsivity due to the introduction of additional thermal operations into the technological route. In particular, the dark current density of the RE of experimental PDs was 40-80 nA/cm2, compared to 80-250 nA/cm2 for commercial samples. Impulse current monochromatic sensitivity at a wavelength of 1064 nm for experimental samples was 0.41-0.44 A/W, and for commercial ones - 0.45-0.48 A/W.
{"title":"Silicon four element p-i-n photodiode with improved characteristics","authors":"M. Kukurudziak","doi":"10.32620/reks.2023.1.07","DOIUrl":"https://doi.org/10.32620/reks.2023.1.07","url":null,"abstract":"This article presents the results of the development of silicon coordinate p-i-n photodiodes (PD) with improved parameters. The technological possibilities of reducing the gaps between the responsive areas of multi-element PDs were studied. PDs with reduced gaps were modeled, samples were made according to the models, the parameters of the obtained PDs and the influence of various technological factors on their values were investigated. During research, it was established that the factor that limits the possibility of reducing the gaps is the insulation resistance between the responsive elements. The decrease in the insulation resistance between the PD elements was a consequence of the formation of inversion leakage channels at the Si-SiO2 interface, which is characteristic of high-resistance p-type silicon, the conductivity of which increased with a decrease in the width of the gaps. To increase the resistance of the gaps between the platforms and reduce the influence of inversion layers, it was decided to form regions of the restriction of the leakage channels between the REs – highly doped regions isotypic with the substrate material (p+-type). They will prevent the movement of current carriers that are generated in the inversion layers on the surface of the substrate. Four-element p-i-n photodiodes with 31 μm gaps between the sites were made. The proposed PD is not significantly inferior in parameters to analogues, but it is the sample with the smallest gaps between RE among photodiodes of the same type and size in the world market. The improvement of the insulation resistance between the REs made it possible to reduce the level of dark current of the PD by twice compared to serial products, with a slight decrease in responsivity due to the introduction of additional thermal operations into the technological route. In particular, the dark current density of the RE of experimental PDs was 40-80 nA/cm2, compared to 80-250 nA/cm2 for commercial samples. Impulse current monochromatic sensitivity at a wavelength of 1064 nm for experimental samples was 0.41-0.44 A/W, and for commercial ones - 0.45-0.48 A/W.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43356713","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 the article is the analysis and design of a via free metamaterial antenna based on a composite right/left-handed transmission line (CRLH-TL) structure. The goal is to design a high-gain antenna with dual-band resonance capable of changing its resonance frequency and gain adaptively. The tasks to be solved are creating an antenna with a high gain-bandwidth product along the operated band, achieving adaptive frequency reconfiguration and creating a direct antenna modulation process using active elements. The simulation methods used are: the proposed antenna is designed by integrating a CRLH-TL structure to a 1D array based on two types of unit cells: The first unit cell is realized from a Hilbert curve of the 3rd order, and the second one is based on the 1st order of Minkowski – stepped impedance resonator (SIR). The antenna parts are printed on a Taconic RF-43 substrate with thickness = 1.57 mm. The following results were obtained: The Hilbert/Minkowski–SIR antenna achieved dual-band operation with a maximum gain equal to 14 dBi and 18 dBi at 5 GHz and 5.5 GHz, respectively. Furthermore, by changing the states of the PIN diode, an amplitude shift keying direct antenna modulation process is achieved; for instance, at 5 GHz, the antenna can change its gain directly in the range from (12-14) dBi with good impedance matching. Finally, the proposed antenna shows a low profile and operates at different frequency bands within sub-6 GHz applications. Conclusions. The simulation results indicate that such antenna performance enhancement is the result of eliminating via conduction losses, ground plane capacitance losses and suppressing surface wave reflections due to the Hilbert/Minkowski SIR introduction.
{"title":"Reconfigurable composite right/left-handed transmission line antenna based Hilbert/Minkowski stepped impedance resonator for wireless applications","authors":"Marwa M. Ismail, T. Elwi, A. Salim","doi":"10.32620/reks.2023.1.06","DOIUrl":"https://doi.org/10.32620/reks.2023.1.06","url":null,"abstract":"The subject matter of the article is the analysis and design of a via free metamaterial antenna based on a composite right/left-handed transmission line (CRLH-TL) structure. The goal is to design a high-gain antenna with dual-band resonance capable of changing its resonance frequency and gain adaptively. The tasks to be solved are creating an antenna with a high gain-bandwidth product along the operated band, achieving adaptive frequency reconfiguration and creating a direct antenna modulation process using active elements. The simulation methods used are: the proposed antenna is designed by integrating a CRLH-TL structure to a 1D array based on two types of unit cells: The first unit cell is realized from a Hilbert curve of the 3rd order, and the second one is based on the 1st order of Minkowski – stepped impedance resonator (SIR). The antenna parts are printed on a Taconic RF-43 substrate with thickness = 1.57 mm. The following results were obtained: The Hilbert/Minkowski–SIR antenna achieved dual-band operation with a maximum gain equal to 14 dBi and 18 dBi at 5 GHz and 5.5 GHz, respectively. Furthermore, by changing the states of the PIN diode, an amplitude shift keying direct antenna modulation process is achieved; for instance, at 5 GHz, the antenna can change its gain directly in the range from (12-14) dBi with good impedance matching. Finally, the proposed antenna shows a low profile and operates at different frequency bands within sub-6 GHz applications. Conclusions. The simulation results indicate that such antenna performance enhancement is the result of eliminating via conduction losses, ground plane capacitance losses and suppressing surface wave reflections due to the Hilbert/Minkowski SIR introduction.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42978841","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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