Pub Date : 2024-06-04DOI: 10.20998/2522-9052.2024.2.04
Volodymyr Bezkorovainyi, L. Kolesnyk, V. Gopejenko, Viktor Kosenko
The subject of research in the article is the process of ranking options in support systems for project decision-making under conditions of incomplete certainty. The goal of the work is to increase the efficiency of technologies for automated design of complex systems due to the development of a combined method of ranking effective options for building objects in conditions of incomplete certainty of input data. The following tasks are solved in the article: analysis of the current state of the problem of ranking options in support systems for project decision-making; decomposition of problems of system optimization of complex design objects and support of project decision-making; development of a variant ranking method that combines the procedures of lexicographic optimization and cardinal ordering in conditions of incomplete certainty of input data. The following methods are used: systems theory, utility theory, optimization, operations research, interval and fuzzy mathematics. Results. According to the results of the analysis of the problem of supporting project decision-making, the existence of the problem of correctly reducing subsets of effective options for ranking, taking into account factors that are difficult to formalize and the experience of the decision-maker (DM), was established. Decomposition of the problems of system optimization of complex design objects and support for project decision-making was carried out. For the case of ordinalistic presentation of preferences between local criteria, an estimate of the size of the rational reduction of subsets of optimal and suboptimal options for each of the indicators is proposed. Its use allows for one approach to obtain a subset of effective variants of a given capacity for analysis and final selection of the DM. A method of transforming the ordinalistic presentation of preferences between local criteria to their quantitative presentation in the form of weighting coefficients is proposed. Conclusions. The developed methods expand the methodological foundations of the automation of processes supporting the adoption of multi-criteria project decisions. They make it possible to correctly reduce the set of effective alternatives in conditions of incomplete certainty of the input data for the final choice, taking into account factors that are difficult to formalize, knowledge and experience of ODA. The practical use of the obtained results will allow to reduce the time and capacity complexity of the procedures for supporting project decision-making, and due to the use of the technology of selection of subsets of effective options with intervally specified characteristics - to guarantee the quality of project decisions and to provide a more complete assessment of them.
{"title":"THE METHOD OF RANKING EFFECTIVE PROJECT SOLUTIONS IN CONDITIONS OF INCOMPLETE CERTAINTY","authors":"Volodymyr Bezkorovainyi, L. Kolesnyk, V. Gopejenko, Viktor Kosenko","doi":"10.20998/2522-9052.2024.2.04","DOIUrl":"https://doi.org/10.20998/2522-9052.2024.2.04","url":null,"abstract":"The subject of research in the article is the process of ranking options in support systems for project decision-making under conditions of incomplete certainty. The goal of the work is to increase the efficiency of technologies for automated design of complex systems due to the development of a combined method of ranking effective options for building objects in conditions of incomplete certainty of input data. The following tasks are solved in the article: analysis of the current state of the problem of ranking options in support systems for project decision-making; decomposition of problems of system optimization of complex design objects and support of project decision-making; development of a variant ranking method that combines the procedures of lexicographic optimization and cardinal ordering in conditions of incomplete certainty of input data. The following methods are used: systems theory, utility theory, optimization, operations research, interval and fuzzy mathematics. Results. According to the results of the analysis of the problem of supporting project decision-making, the existence of the problem of correctly reducing subsets of effective options for ranking, taking into account factors that are difficult to formalize and the experience of the decision-maker (DM), was established. Decomposition of the problems of system optimization of complex design objects and support for project decision-making was carried out. For the case of ordinalistic presentation of preferences between local criteria, an estimate of the size of the rational reduction of subsets of optimal and suboptimal options for each of the indicators is proposed. Its use allows for one approach to obtain a subset of effective variants of a given capacity for analysis and final selection of the DM. A method of transforming the ordinalistic presentation of preferences between local criteria to their quantitative presentation in the form of weighting coefficients is proposed. Conclusions. The developed methods expand the methodological foundations of the automation of processes supporting the adoption of multi-criteria project decisions. They make it possible to correctly reduce the set of effective alternatives in conditions of incomplete certainty of the input data for the final choice, taking into account factors that are difficult to formalize, knowledge and experience of ODA. The practical use of the obtained results will allow to reduce the time and capacity complexity of the procedures for supporting project decision-making, and due to the use of the technology of selection of subsets of effective options with intervally specified characteristics - to guarantee the quality of project decisions and to provide a more complete assessment of them.","PeriodicalId":275587,"journal":{"name":"Advanced Information Systems","volume":"258 2‐4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141386842","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}
Pub Date : 2024-06-04DOI: 10.20998/2522-9052.2024.2.08
Heorhii Kuchuk, Eduard Malokhvii
Purpose of review. The paper provides an in-depth exploration of the integration of Internet of Things (IoT) technologies with cloud, fog, and edge computing paradigms, examining the transformative impact on computational architectures. Approach to review. Beginning with an overview of IoT's evolution and its surge in global adoption, the paper emphasizes the increasing importance of integrating cloud, fog, and edge computing to meet the escalating demands for real-time data processing, low-latency communication, and scalable infrastructure in the IoT ecosystem. The survey meticulously dissects each computing paradigm, highlighting the unique characteristics, advantages, and challenges associated with IoT, cloud computing, edge computing, and fog computing. The discussion delves into the individual strengths and limitations of these technologies, addressing issues such as latency, bandwidth consumption, security, and data privacy. Further, the paper explores the synergies between IoT and cloud computing, recognizing cloud computing as a backend solution for processing vast data streams generated by IoT devices. Review results. Challenges related to unreliable data handling and privacy concerns are acknowledged, emphasizing the need for robust security measures and regulatory frameworks. The integration of edge computing with IoT is investigated, showcasing the symbiotic relationship where edge nodes leverage the residual computing capabilities of IoT devices to provide additional services. The challenges associated with the heterogeneity of edge computing systems are highlighted, and the paper presents research on computational offloading as a strategy to minimize latency in mobile edge computing. Fog computing's intermediary role in enhancing bandwidth, reducing latency, and providing scalability for IoT applications is thoroughly examined. Challenges related to security, authentication, and distributed denial of service in fog computing are acknowledged. The paper also explores innovative algorithms addressing resource management challenges in fog-IoT environments. Conclusions. The survey concludes with insights into the collaborative integration of cloud, fog, and edge computing to form a cohesive computational architecture for IoT. The future perspectives section anticipates the role of 6G technology in unlocking the full potential of IoT, emphasizing applications such as telemedicine, smart cities, and enhanced distance learning. Cybersecurity concerns, energy consumption, and standardization challenges are identified as key areas for future research.
{"title":"INTEGRATION OF IOT WITH CLOUD, FOG, AND EDGE COMPUTING: A REVIEW","authors":"Heorhii Kuchuk, Eduard Malokhvii","doi":"10.20998/2522-9052.2024.2.08","DOIUrl":"https://doi.org/10.20998/2522-9052.2024.2.08","url":null,"abstract":"Purpose of review. The paper provides an in-depth exploration of the integration of Internet of Things (IoT) technologies with cloud, fog, and edge computing paradigms, examining the transformative impact on computational architectures. Approach to review. Beginning with an overview of IoT's evolution and its surge in global adoption, the paper emphasizes the increasing importance of integrating cloud, fog, and edge computing to meet the escalating demands for real-time data processing, low-latency communication, and scalable infrastructure in the IoT ecosystem. The survey meticulously dissects each computing paradigm, highlighting the unique characteristics, advantages, and challenges associated with IoT, cloud computing, edge computing, and fog computing. The discussion delves into the individual strengths and limitations of these technologies, addressing issues such as latency, bandwidth consumption, security, and data privacy. Further, the paper explores the synergies between IoT and cloud computing, recognizing cloud computing as a backend solution for processing vast data streams generated by IoT devices. Review results. Challenges related to unreliable data handling and privacy concerns are acknowledged, emphasizing the need for robust security measures and regulatory frameworks. The integration of edge computing with IoT is investigated, showcasing the symbiotic relationship where edge nodes leverage the residual computing capabilities of IoT devices to provide additional services. The challenges associated with the heterogeneity of edge computing systems are highlighted, and the paper presents research on computational offloading as a strategy to minimize latency in mobile edge computing. Fog computing's intermediary role in enhancing bandwidth, reducing latency, and providing scalability for IoT applications is thoroughly examined. Challenges related to security, authentication, and distributed denial of service in fog computing are acknowledged. The paper also explores innovative algorithms addressing resource management challenges in fog-IoT environments. Conclusions. The survey concludes with insights into the collaborative integration of cloud, fog, and edge computing to form a cohesive computational architecture for IoT. The future perspectives section anticipates the role of 6G technology in unlocking the full potential of IoT, emphasizing applications such as telemedicine, smart cities, and enhanced distance learning. Cybersecurity concerns, energy consumption, and standardization challenges are identified as key areas for future research.","PeriodicalId":275587,"journal":{"name":"Advanced Information Systems","volume":"57 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141387466","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}
Pub Date : 2024-02-26DOI: 10.20998/2522-9052.2024.1.05
Serhii Krivtsov, Yurii Parfeniuk, K. Bazilevych, I. Meniailov, D. Chumachenko
Topicality. The rapid growth of data in various domains has necessitated the development of efficient tools and libraries for data processing and analysis. Python, a popular programming language for data analysis, offers several libraries, such as NumPy and Numba, for numerical computations. However, there is a lack of comprehensive studies comparing the performance of these libraries across different tasks and data sizes. The aim of the study. This study aims to fill this gap by comparing the performance of Python, NumPy, Numba, and Numba.Cuda across different tasks and data sizes. Additionally, it evaluates the impact of multithreading and GPU utilization on computation speed. Research results. The results indicate that Numba and Numba.Cuda significantly optimizes the performance of Python applications, especially for functions involving loops and array operations. Moreover, GPU and multithreading in Python further enhance computation speed, although with certain limitations and considerations. Conclusion. This study contributes to the field by providing valuable insights into the performance of different Python libraries and the effectiveness of GPU and multithreading in Python, thereby aiding researchers and practitioners in selecting the most suitable tools for their computational needs.
{"title":"PERFORMANCE EVALUATION OF PYTHON LIBRARIES FOR MULTITHREADING DATA PROCESSING","authors":"Serhii Krivtsov, Yurii Parfeniuk, K. Bazilevych, I. Meniailov, D. Chumachenko","doi":"10.20998/2522-9052.2024.1.05","DOIUrl":"https://doi.org/10.20998/2522-9052.2024.1.05","url":null,"abstract":"Topicality. The rapid growth of data in various domains has necessitated the development of efficient tools and libraries for data processing and analysis. Python, a popular programming language for data analysis, offers several libraries, such as NumPy and Numba, for numerical computations. However, there is a lack of comprehensive studies comparing the performance of these libraries across different tasks and data sizes. The aim of the study. This study aims to fill this gap by comparing the performance of Python, NumPy, Numba, and Numba.Cuda across different tasks and data sizes. Additionally, it evaluates the impact of multithreading and GPU utilization on computation speed. Research results. The results indicate that Numba and Numba.Cuda significantly optimizes the performance of Python applications, especially for functions involving loops and array operations. Moreover, GPU and multithreading in Python further enhance computation speed, although with certain limitations and considerations. Conclusion. This study contributes to the field by providing valuable insights into the performance of different Python libraries and the effectiveness of GPU and multithreading in Python, thereby aiding researchers and practitioners in selecting the most suitable tools for their computational needs.","PeriodicalId":275587,"journal":{"name":"Advanced Information Systems","volume":"47 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140431368","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}
Pub Date : 2024-02-26DOI: 10.20998/2522-9052.2024.1.09
Heorhii Kuchuk, Andrii Kuliahin
Topicality. Recent studies confirm the growing trend to implement emotional feedback and sentiment analysis to improve the performance of recommender systems. In this way, a deeper personalization and current emotional relevance of the user experience is ensured. The subject of study in the article is a hybrid recommender system with a component of video sentiment analysis. The purpose of the article is to investigate the possibilities of improving the effectiveness of the results of the hybrid recommender system of virtual art compositions by implementing a component of video sentiment analysis. Used methods: matrix factorization methods, collaborative filtering method, content-based method, knowledge-based method, video sentiment analysis method. The following results were obtained. A new model has been created that combines a hybrid recommender system and a video sentiment analysis component. The average absolute error of the system has been significantly reduced. Added system reaction to emotional feedback in the context of user interaction with virtual art compositions. Conclusion. Thus, the system can not only select the most suitable virtual art compositions, but also create adaptive and dynamic content, which will increase user satisfaction and improve the immersive aspects of the system. A promising direction of further research may be the addition of a subsystem with a generative neural network, which will create new virtual art compositions based on the conclusions of the developed recommendation system.
{"title":"HYBRID RECOMMENDER FOR VIRTUAL ART COMPOSITIONS WITH VIDEO SENTIMENTS ANALYSIS","authors":"Heorhii Kuchuk, Andrii Kuliahin","doi":"10.20998/2522-9052.2024.1.09","DOIUrl":"https://doi.org/10.20998/2522-9052.2024.1.09","url":null,"abstract":"Topicality. Recent studies confirm the growing trend to implement emotional feedback and sentiment analysis to improve the performance of recommender systems. In this way, a deeper personalization and current emotional relevance of the user experience is ensured. The subject of study in the article is a hybrid recommender system with a component of video sentiment analysis. The purpose of the article is to investigate the possibilities of improving the effectiveness of the results of the hybrid recommender system of virtual art compositions by implementing a component of video sentiment analysis. Used methods: matrix factorization methods, collaborative filtering method, content-based method, knowledge-based method, video sentiment analysis method. The following results were obtained. A new model has been created that combines a hybrid recommender system and a video sentiment analysis component. The average absolute error of the system has been significantly reduced. Added system reaction to emotional feedback in the context of user interaction with virtual art compositions. Conclusion. Thus, the system can not only select the most suitable virtual art compositions, but also create adaptive and dynamic content, which will increase user satisfaction and improve the immersive aspects of the system. A promising direction of further research may be the addition of a subsystem with a generative neural network, which will create new virtual art compositions based on the conclusions of the developed recommendation system.","PeriodicalId":275587,"journal":{"name":"Advanced Information Systems","volume":"38 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140431833","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}
Pub Date : 2024-02-26DOI: 10.20998/2522-9052.2024.1.08
Jeffry Vincent Louis, N. Noerlina, D. H. Syahchari
The purpose of this study is to determine whether artificial intelligence used in E-Commerce influences product recommendations for users. This study explains how much influence artificial intelligence on product recommendations supplied by E-commerce in terms of consumer behavior in making purchasing decisions. Research methods. This research used bibliometric analysis to find the mapping of this topic with articles period 2017 to 2023 from Scopus database. Of the 103 articles were showed by keyword and analyzing the articles according to the relate of the content about 29 articles were finally obtained. The research result is Artificial Intelligence has influence for E-commerce, recommendation system, decision support system, customer behaviour’s, and customer trust. Product recommendations have an impact on E-Commerce. Conclusion. However, from the literature review, founded that there are still a few journals discussing related to considerations to the implementation regarding the use of AI in e-commerce "Consumer behaviour", "Customer Trust", "Purchasing decisions". This study is also useful to generate additional AI-related research in e-commerce and unquestionably for a fresh subject will be covered especially in context of product recommendations on E-commerce.
{"title":"DIGITAL BUSINESS TRANSFORMATION: ANALYSIS OF THE EFFECT ARTIFICIAL INTELLIGENCE IN E-COMMERCE’S PRODUCT RECOMMENDATION","authors":"Jeffry Vincent Louis, N. Noerlina, D. H. Syahchari","doi":"10.20998/2522-9052.2024.1.08","DOIUrl":"https://doi.org/10.20998/2522-9052.2024.1.08","url":null,"abstract":"The purpose of this study is to determine whether artificial intelligence used in E-Commerce influences product recommendations for users. This study explains how much influence artificial intelligence on product recommendations supplied by E-commerce in terms of consumer behavior in making purchasing decisions. Research methods. This research used bibliometric analysis to find the mapping of this topic with articles period 2017 to 2023 from Scopus database. Of the 103 articles were showed by keyword and analyzing the articles according to the relate of the content about 29 articles were finally obtained. The research result is Artificial Intelligence has influence for E-commerce, recommendation system, decision support system, customer behaviour’s, and customer trust. Product recommendations have an impact on E-Commerce. Conclusion. However, from the literature review, founded that there are still a few journals discussing related to considerations to the implementation regarding the use of AI in e-commerce \"Consumer behaviour\", \"Customer Trust\", \"Purchasing decisions\". This study is also useful to generate additional AI-related research in e-commerce and unquestionably for a fresh subject will be covered especially in context of product recommendations on E-commerce.","PeriodicalId":275587,"journal":{"name":"Advanced Information Systems","volume":"31 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140429503","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}
Pub Date : 2024-02-26DOI: 10.20998/2522-9052.2024.1.06
O. Kuznietsov, Oleksii Kolomiitsev, Ivan Nos, O. Biesova, Heorhii Krykhovetskyi
Sea-based radar stations (RS) are widely used for solving the tasks of radar surveillance of surface objects (SO) and air objects (AO). The subject of the article is the mechanisms of radio wave propagation in the boundary layer of the atmosphere. The aim is to investigate the possibilities of improving the accuracy of measuring the range and radial velocity of SO and AO observed beyond the line-of-sight of coastal-based RS. Objective: to analyse the spatial and temporal parameters and properties of waveguide layers above the water surface. Methods used: maximum likelihood and frequency. The following results were obtained. The results of experimental studies of seasonal and daily changes in the parameters of the lower troposphere layer in the Black Sea coastal zone and the parameters of tropospheric radio waveguides are presented. The procedure for calculating the energy transmission losses during radio wave propagation in the boundary layer of the atmosphere is presented, and the conditions for detecting SO and AO beyond the radar line-of-sight are determined. Recommendations for increasing the range of detection of SO and AO are given, which are associated with the possibility of predicting the existence of tropospheric radio waveguides by using data on the current conditions of radio wave propagation over the sea based on the signals of the automatic ship identification system AIS. Conclusions. Proposals have been developed to improve the accuracy of measuring the range and radial velocity of SO and AO at waveguide propagation of radio waves over the sea surface. A promising area for further research may be to identify ways to optimise the measurement of angular coordinates in modern RS during waveguide propagation of radio waves over the sea surface.
海基雷达站（RS）被广泛用于解决雷达监视水面物体（SO）和空中物体（AO）的任务。文章的主题是无线电波在大气边界层中的传播机制。目的是研究提高测量沿岸 RS 视线外观测到的 SO 和 AO 的距离和径向速度精度的可能性。目标：分析水面以上波导层的时空参数和特性。采用的方法：最大似然法和频率法。结果如下介绍了对黑海沿岸地区对流层下层参数和对流层无线电波导参数的季节变化和日变化的实验研究结果。介绍了无线电波在大气边界层传播期间能量传输损失的计算程序，并确定了在雷达视线之外探测 SO 和 AO 的条件。提出了扩大 SO 和 AO 探测范围的建议，这些建议与利用基于船舶自动识别系统 AIS 信号的海上无线电波传播现状数据预测对流层无线电波导存在的可能性有关。结论。已经提出了一些建议，以提高在海面无线电波传播波导处测量 SO 和 AO 的距离和径向速度的精度。进一步研究的一个有前途的领域可能是确定在无线电波在海面上的波导传播过程中优化现代 RS 角坐标测量的方法。
{"title":"PROPOSALS TO IMPROVE THE INFORMATION CAPABILITIES OF COASTAL-BASED RADAR STATIONS FOR SURVEILLANCE OF SURFACE AND AIR OBJECTS","authors":"O. Kuznietsov, Oleksii Kolomiitsev, Ivan Nos, O. Biesova, Heorhii Krykhovetskyi","doi":"10.20998/2522-9052.2024.1.06","DOIUrl":"https://doi.org/10.20998/2522-9052.2024.1.06","url":null,"abstract":"Sea-based radar stations (RS) are widely used for solving the tasks of radar surveillance of surface objects (SO) and air objects (AO). The subject of the article is the mechanisms of radio wave propagation in the boundary layer of the atmosphere. The aim is to investigate the possibilities of improving the accuracy of measuring the range and radial velocity of SO and AO observed beyond the line-of-sight of coastal-based RS. Objective: to analyse the spatial and temporal parameters and properties of waveguide layers above the water surface. Methods used: maximum likelihood and frequency. The following results were obtained. The results of experimental studies of seasonal and daily changes in the parameters of the lower troposphere layer in the Black Sea coastal zone and the parameters of tropospheric radio waveguides are presented. The procedure for calculating the energy transmission losses during radio wave propagation in the boundary layer of the atmosphere is presented, and the conditions for detecting SO and AO beyond the radar line-of-sight are determined. Recommendations for increasing the range of detection of SO and AO are given, which are associated with the possibility of predicting the existence of tropospheric radio waveguides by using data on the current conditions of radio wave propagation over the sea based on the signals of the automatic ship identification system AIS. Conclusions. Proposals have been developed to improve the accuracy of measuring the range and radial velocity of SO and AO at waveguide propagation of radio waves over the sea surface. A promising area for further research may be to identify ways to optimise the measurement of angular coordinates in modern RS during waveguide propagation of radio waves over the sea surface.","PeriodicalId":275587,"journal":{"name":"Advanced Information Systems","volume":"48 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140429375","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}
Pub Date : 2024-02-26DOI: 10.20998/2522-9052.2024.1.13
Samira Hasanova
Topicality. In this article discusses the identification of soils according to the international soil classification World Reference Base for Soil Resources system (WRB). The World Reference Base for Soil Resources was developed to identify soils and use the obtained data in different areas of everyday life: agriculture, forestry, animal husbandry, etc. The purpose of the work Note that the WRB, developed by a group of soil scientists, is not meant to replace national classification systems. Besides this classification system, there are also different soil classifications designed by national soil science schools. The difference in the structures of these classifications necessitated the development of a diagnostic algorithm to correlate them with each other. Results Three options for determining whether a soil belongs to reference soil groups are considered, depending either on soil parameters only, or on a combination of diagnostic horizons and soil parameters, or only on diagnostic horizons. A group of scientists headed by M. Babayev also developed a national soil classification system for Azerbaijan. In order to compare these two systems, this study proposes a soil data structure, as well as an algorithm for soil identification according to the WRB classification on the basis of the proposed structure. Conclusion A soil diagnostic algorithm is developed, which will allow identifying any soil type with the corresponding WRB Reference Soil Group. Three variants of allocating soils to WRB Reference Soil Groups based only on soil parameters, or on the combination of diagnostic horizons and soil parameters, or only on diagnostic horizons are considered.
{"title":"CONSTRUCTION OF A DIAGNOSTIC ALGORITHM FOR SOIL IDENTIFICATION ACCORDING TO THE INTERNATIONAL SOIL CLASSIFICATION SYSTEM WRB","authors":"Samira Hasanova","doi":"10.20998/2522-9052.2024.1.13","DOIUrl":"https://doi.org/10.20998/2522-9052.2024.1.13","url":null,"abstract":"Topicality. In this article discusses the identification of soils according to the international soil classification World Reference Base for Soil Resources system (WRB). The World Reference Base for Soil Resources was developed to identify soils and use the obtained data in different areas of everyday life: agriculture, forestry, animal husbandry, etc. The purpose of the work Note that the WRB, developed by a group of soil scientists, is not meant to replace national classification systems. Besides this classification system, there are also different soil classifications designed by national soil science schools. The difference in the structures of these classifications necessitated the development of a diagnostic algorithm to correlate them with each other. Results Three options for determining whether a soil belongs to reference soil groups are considered, depending either on soil parameters only, or on a combination of diagnostic horizons and soil parameters, or only on diagnostic horizons. A group of scientists headed by M. Babayev also developed a national soil classification system for Azerbaijan. In order to compare these two systems, this study proposes a soil data structure, as well as an algorithm for soil identification according to the WRB classification on the basis of the proposed structure. Conclusion A soil diagnostic algorithm is developed, which will allow identifying any soil type with the corresponding WRB Reference Soil Group. Three variants of allocating soils to WRB Reference Soil Groups based only on soil parameters, or on the combination of diagnostic horizons and soil parameters, or only on diagnostic horizons are considered.","PeriodicalId":275587,"journal":{"name":"Advanced Information Systems","volume":"70 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140430359","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}
Objective. The aim is to enhance the efficiency of diagnostics for determining the level of air attack safety through the practical integration principles of artificial intelligence. Methodology. Models and technologies for safety diagnostics of the region (territorial community) have been explored. The process of building an artificial intelligence model requires differentiation of objects at a level to accumulate assessments-characteristics of aerial vehicles. The practical integration principles of artificial intelligence into the forecasting technology are based on the Region Safety Index, used for constructing machine learning models. The optimal machine learning model of the proposed approach is selected from a list of several models. Results. A technology for predicting the level of regional safety based on the Safety Index has been developed. The recommended optimal model is the Random Forest model ([('max_depth', 13), ('max_features', 'sqrt'), ('min_samples_leaf', 1), ('min_samples_split', 2), ('n_estimators', 79)]), demonstrating the most effective quality indicators of MAE; MAX; RMSE 0.005; 0.083; 0.0139, respectively. Scientific Novelty. The proposed approach is based on a linear model of the Region Safety Index, which, unlike existing ones, takes into account the interaction of factors. This allows for advantages of the proposed method over existing approaches in terms of the root mean square error of 0.496; 0.625, respectively. In turn, this influences the quality of machine learning models. Practical Significance. The proposed solutions are valuable for diagnosing the level of safety in the region of Ukraine, particularly in the context of air attacks.
{"title":"PRACTICAL PRINCIPLES OF INTEGRATING ARTIFICIAL INTELLIGENCE INTO THE TECHNOLOGY OF REGIONAL SECURITY PREDICTING","authors":"Oleksandr Shefer, Oleksandr Laktionov, Volodymyr Pents, Alina Hlushko, Nina Kuchuk","doi":"10.20998/2522-9052.2024.1.11","DOIUrl":"https://doi.org/10.20998/2522-9052.2024.1.11","url":null,"abstract":"Objective. The aim is to enhance the efficiency of diagnostics for determining the level of air attack safety through the practical integration principles of artificial intelligence. Methodology. Models and technologies for safety diagnostics of the region (territorial community) have been explored. The process of building an artificial intelligence model requires differentiation of objects at a level to accumulate assessments-characteristics of aerial vehicles. The practical integration principles of artificial intelligence into the forecasting technology are based on the Region Safety Index, used for constructing machine learning models. The optimal machine learning model of the proposed approach is selected from a list of several models. Results. A technology for predicting the level of regional safety based on the Safety Index has been developed. The recommended optimal model is the Random Forest model ([('max_depth', 13), ('max_features', 'sqrt'), ('min_samples_leaf', 1), ('min_samples_split', 2), ('n_estimators', 79)]), demonstrating the most effective quality indicators of MAE; MAX; RMSE 0.005; 0.083; 0.0139, respectively. Scientific Novelty. The proposed approach is based on a linear model of the Region Safety Index, which, unlike existing ones, takes into account the interaction of factors. This allows for advantages of the proposed method over existing approaches in terms of the root mean square error of 0.496; 0.625, respectively. In turn, this influences the quality of machine learning models. Practical Significance. The proposed solutions are valuable for diagnosing the level of safety in the region of Ukraine, particularly in the context of air attacks.","PeriodicalId":275587,"journal":{"name":"Advanced Information Systems","volume":"3 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140430675","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 object of the study is the process of identifying the state of a computer network. The subject of the study are the methods of identifying the state of computer networks. The purpose of the paper is to improve the efficacy of intrusion detection in computer networks by developing a method based on transformer models. The results obtained. The work analyzes traditional machine learning algorithms, deep learning methods and considers the advantages of using transformer models. A method for detecting intrusions in computer networks is proposed. This method differs from known approaches by utilizing the Vision Transformer for Small-size Datasets (ViTSD) deep learning algorithm. The method incorporates procedures to reduce the correlation of input data and transform data into a specific format required for model operations. The developed methods are implemented using Python and the GOOGLE COLAB cloud service with Jupyter Notebook. Conclusions. Experiments confirmed the efficiency of the proposed method. The use of the developed method based on the ViTSD algorithm and the data preprocessing procedure increases the model's accuracy to 98.7%. This makes it possible to recommend it for practical use, in order to improve the accuracy of identifying the state of a computer system.
{"title":"INTRUSION DETECTION MODEL BASED ON IMPROVED TRANSFORMER","authors":"Svitlana Gavrylenko, Vadym Poltoratskyi, Alina Nechyporenko","doi":"10.20998/2522-9052.2024.1.12","DOIUrl":"https://doi.org/10.20998/2522-9052.2024.1.12","url":null,"abstract":"The object of the study is the process of identifying the state of a computer network. The subject of the study are the methods of identifying the state of computer networks. The purpose of the paper is to improve the efficacy of intrusion detection in computer networks by developing a method based on transformer models. The results obtained. The work analyzes traditional machine learning algorithms, deep learning methods and considers the advantages of using transformer models. A method for detecting intrusions in computer networks is proposed. This method differs from known approaches by utilizing the Vision Transformer for Small-size Datasets (ViTSD) deep learning algorithm. The method incorporates procedures to reduce the correlation of input data and transform data into a specific format required for model operations. The developed methods are implemented using Python and the GOOGLE COLAB cloud service with Jupyter Notebook. Conclusions. Experiments confirmed the efficiency of the proposed method. The use of the developed method based on the ViTSD algorithm and the data preprocessing procedure increases the model's accuracy to 98.7%. This makes it possible to recommend it for practical use, in order to improve the accuracy of identifying the state of a computer system.","PeriodicalId":275587,"journal":{"name":"Advanced Information Systems","volume":"54 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140430793","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}
Pub Date : 2024-02-26DOI: 10.20998/2522-9052.2024.1.07
Fangfang Li, Sergey Abramov, Ihor Dohtiev, Vladimir Lukin
The object of the study is the process of lossy image compression. The subject of the study is the two-step approach to providing desired parameters (quality and compression ratio) for different coders. The goals of the study are to review advantages of the two-step approach to lossy compression, to analyze the reasons of drawbacks, and to put forward possible ways to get around these shortcomings. Methods used: linear approximation, numerical simulation, statistical analysis. Results obtained: 1) the considered approach main advantage is that, in most applications, it provides substantial improvement of accuracy of providing a desired value of a controlled compression parameter after the second step compared to the first step; 2) the approach is quite universal and can be applied for different coders and different parameters of lossy compression to be provided; 3) the main problems and limitations happen due to the use of linear approximation and essential difference in behavior of rate/distortion curves for images of different complexity; 4) there are ways to avoid the approach drawbacks that employ adaptation to image complexity and/or use certain restrictions at the second step. Conclusions: based on the results of the study, it is worth 1) considering more complex approximations of rate-distortion curves; 2) paying more attention to adequate and fast algorithms of characterizing image complexity before compression; 3) using quality metrics that have quasi-linear rate/distortion curves for a given coder.
{"title":"ADVANTAGES AND DRAWBACKS OF TWO-STEP APPROACH TO PROVIDING DESIRED PARAMETERS IN LOSSY IMAGE COMPRESSION","authors":"Fangfang Li, Sergey Abramov, Ihor Dohtiev, Vladimir Lukin","doi":"10.20998/2522-9052.2024.1.07","DOIUrl":"https://doi.org/10.20998/2522-9052.2024.1.07","url":null,"abstract":"The object of the study is the process of lossy image compression. The subject of the study is the two-step approach to providing desired parameters (quality and compression ratio) for different coders. The goals of the study are to review advantages of the two-step approach to lossy compression, to analyze the reasons of drawbacks, and to put forward possible ways to get around these shortcomings. Methods used: linear approximation, numerical simulation, statistical analysis. Results obtained: 1) the considered approach main advantage is that, in most applications, it provides substantial improvement of accuracy of providing a desired value of a controlled compression parameter after the second step compared to the first step; 2) the approach is quite universal and can be applied for different coders and different parameters of lossy compression to be provided; 3) the main problems and limitations happen due to the use of linear approximation and essential difference in behavior of rate/distortion curves for images of different complexity; 4) there are ways to avoid the approach drawbacks that employ adaptation to image complexity and/or use certain restrictions at the second step. Conclusions: based on the results of the study, it is worth 1) considering more complex approximations of rate-distortion curves; 2) paying more attention to adequate and fast algorithms of characterizing image complexity before compression; 3) using quality metrics that have quasi-linear rate/distortion curves for a given coder. ","PeriodicalId":275587,"journal":{"name":"Advanced Information Systems","volume":"44 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140431597","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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