Pub Date : 2020-10-07DOI: 10.1109/AICT50176.2020.9368706
Yassine Loukili, Mohamed El Mehdi El Aissi, Sarah Benjelloun, Y. Lakhrissi, Hiba Chougrad, Safae Elhaj Ben Ali, Abdessamad El Boushaki
Over the past decade, big data with a spatial component "GEOSPATIAL BIG DATA" (GSBD) has become a focus of global interest, attracting increasing attention from universities, industry, governments and other organizations. The possibility of managing and processing GSBD to help decision-making therefore appears to be an important scientific and societal issue. This state of the art successively explores the concepts of big data, of spatial component and presents some main existing solutions for the management and processing of GSBD.
近十年来，具有空间成分的大数据“地理空间大数据”(GEOSPATIAL big data, GSBD)已成为全球关注的焦点，越来越受到大学、行业、政府和其他组织的关注。因此，管理和处理GSBD以帮助决策的可能性似乎是一个重要的科学和社会问题。本研究先后探索了大数据、空间分量的概念，并提出了目前GSBD管理和处理的一些主要解决方案。
{"title":"Analysis and exploitation of Geospatial Big Data: State of art","authors":"Yassine Loukili, Mohamed El Mehdi El Aissi, Sarah Benjelloun, Y. Lakhrissi, Hiba Chougrad, Safae Elhaj Ben Ali, Abdessamad El Boushaki","doi":"10.1109/AICT50176.2020.9368706","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368706","url":null,"abstract":"Over the past decade, big data with a spatial component \"GEOSPATIAL BIG DATA\" (GSBD) has become a focus of global interest, attracting increasing attention from universities, industry, governments and other organizations. The possibility of managing and processing GSBD to help decision-making therefore appears to be an important scientific and societal issue. This state of the art successively explores the concepts of big data, of spatial component and presents some main existing solutions for the management and processing of GSBD.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"236 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132191591","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368741
Cheikh Ba, A. Gueye
Large NFAs are automata that cannot fit in a single computer, or the computations would not fit within the computer RAM, or may take a long time. We describe and implement a distributed solution of such NFAs determinization. Our method drastically reduces required iterations, and avoids producing useless states of the determinized automaton, contrary to some previous implementations of well-known powerset construction. A running example is provided with execution details. Finally, complexity analysis is given. This work will help in bringing out relevant programming artifacts for our long term goal that consists of a high level distributed graph language.
{"title":"On The Distributed Determinization Of Large NFAs","authors":"Cheikh Ba, A. Gueye","doi":"10.1109/AICT50176.2020.9368741","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368741","url":null,"abstract":"Large NFAs are automata that cannot fit in a single computer, or the computations would not fit within the computer RAM, or may take a long time. We describe and implement a distributed solution of such NFAs determinization. Our method drastically reduces required iterations, and avoids producing useless states of the determinized automaton, contrary to some previous implementations of well-known powerset construction. A running example is provided with execution details. Finally, complexity analysis is given. This work will help in bringing out relevant programming artifacts for our long term goal that consists of a high level distributed graph language.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128871024","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368598
M. Rakhmatullaev, S. Normatov
Analysis of the state of development of research on the protection of valuable scientific and educational databases, library resources, information centers, publishers show the importance of information security, especially in corporate information networks and systems for data exchange. Corporate library networks include dozens and even hundreds of libraries for active information exchange, and they (libraries) are equipped with information security tools to varying degrees. The purpose of the research is to create effective methods and tools to protect the databases of the scientific and educational resources from unauthorized access in libraries and library networks using fuzzy logic methods. As a model and solution method, a fuzzy model of second-type correspondences is proposed, which makes it possible to comprehensively solve the problem of identifying threats in the event of a situation, as well as provide recommendations on how to eliminate them. For the creation of a knowledge database, experts are involved who determine the functions of belonging to "Situation-Threat-Methods of eliminating threats". The research results are used in the expert system the corporate network of electronic libraries to protect scientific and educational information from unauthorized access.
{"title":"Expert system with Fuzzy logic for protecting Scientific Information Resources","authors":"M. Rakhmatullaev, S. Normatov","doi":"10.1109/AICT50176.2020.9368598","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368598","url":null,"abstract":"Analysis of the state of development of research on the protection of valuable scientific and educational databases, library resources, information centers, publishers show the importance of information security, especially in corporate information networks and systems for data exchange. Corporate library networks include dozens and even hundreds of libraries for active information exchange, and they (libraries) are equipped with information security tools to varying degrees. The purpose of the research is to create effective methods and tools to protect the databases of the scientific and educational resources from unauthorized access in libraries and library networks using fuzzy logic methods. As a model and solution method, a fuzzy model of second-type correspondences is proposed, which makes it possible to comprehensively solve the problem of identifying threats in the event of a situation, as well as provide recommendations on how to eliminate them. For the creation of a knowledge database, experts are involved who determine the functions of belonging to \"Situation-Threat-Methods of eliminating threats\". The research results are used in the expert system the corporate network of electronic libraries to protect scientific and educational information from unauthorized access.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128886860","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368811
S. I. Jabbar, Abathar Qahtan Aladi
Objects recognition of the Magnetic Resonance Imaging (MRI) is a powerful tool in the detection of the geometric parameters such as area and perimeter. When outlining the border of an object, it is hard to calculate the area when it has irrelevant details inside the outline. Therefore, in this work we presented and applied a new technique based on fuzzy inference technique which helps to identify objects across MRI video with more accurate way. Fuzzy video edge detection technique was compared with Canny operator technique based on two assessment metrics (FOM and Pinho). Fuzzy video edge detection technique is superior than Canny operator with 14.5% and 7.5% based on the mean values of quantitative assessments (FOM and Pinho) respectively. The results are promising and it is possible to implement this technique and apply it on other medical imaging videos.
{"title":"MRI video edge detection based on Fuzzy inference technique","authors":"S. I. Jabbar, Abathar Qahtan Aladi","doi":"10.1109/AICT50176.2020.9368811","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368811","url":null,"abstract":"Objects recognition of the Magnetic Resonance Imaging (MRI) is a powerful tool in the detection of the geometric parameters such as area and perimeter. When outlining the border of an object, it is hard to calculate the area when it has irrelevant details inside the outline. Therefore, in this work we presented and applied a new technique based on fuzzy inference technique which helps to identify objects across MRI video with more accurate way. Fuzzy video edge detection technique was compared with Canny operator technique based on two assessment metrics (FOM and Pinho). Fuzzy video edge detection technique is superior than Canny operator with 14.5% and 7.5% based on the mean values of quantitative assessments (FOM and Pinho) respectively. The results are promising and it is possible to implement this technique and apply it on other medical imaging videos.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131422137","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368611
D. Subbotin, I. Babalova, V. Bazanov, N. Ivanov
Wi-Fi technology has a huge distribution around the world. There are a large number of devices that in one way or another work with different versions of the 802.11 protocol. However, this technology has a large number of different vulnerabilities. Many of them can be solved in the production of Wi-Fi modules. But not all manufacturers produce modules with fixed vulnerabilities. Therefore, the objective of this article is to create a product that can automatically check the stability of a wi-fi module to DoS attacks.
{"title":"Automation Check Vulnerabilities Of Access Points Based On 802.11 Protocol","authors":"D. Subbotin, I. Babalova, V. Bazanov, N. Ivanov","doi":"10.1109/AICT50176.2020.9368611","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368611","url":null,"abstract":"Wi-Fi technology has a huge distribution around the world. There are a large number of devices that in one way or another work with different versions of the 802.11 protocol. However, this technology has a large number of different vulnerabilities. Many of them can be solved in the production of Wi-Fi modules. But not all manufacturers produce modules with fixed vulnerabilities. Therefore, the objective of this article is to create a product that can automatically check the stability of a wi-fi module to DoS attacks.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114877742","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368719
M. Musaev, Ilyos Khujayorov, M. Ochilov
In this paper investigates the approach to realization of recognition of Uzbek words on the basis of end-to-end models is considered. Also presented are some theoretical data on the architecture of neural networks used in the integrated model, and the results of preliminary experimental studies conducted on their basis. Deep recurrent neural networks, which combine the multiple levels of representation that have proved so effective in deep networks with the flexible use of long-range context that empowers RNNs. When trained end-to-end with suitable regularization, we find that deep BRNNs achieve a test set error of CER=49.1% on our dataset.
{"title":"Development of integral model of speech recognition system for Uzbek language","authors":"M. Musaev, Ilyos Khujayorov, M. Ochilov","doi":"10.1109/AICT50176.2020.9368719","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368719","url":null,"abstract":"In this paper investigates the approach to realization of recognition of Uzbek words on the basis of end-to-end models is considered. Also presented are some theoretical data on the architecture of neural networks used in the integrated model, and the results of preliminary experimental studies conducted on their basis. Deep recurrent neural networks, which combine the multiple levels of representation that have proved so effective in deep networks with the flexible use of long-range context that empowers RNNs. When trained end-to-end with suitable regularization, we find that deep BRNNs achieve a test set error of CER=49.1% on our dataset.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124423867","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368586
Kseniya V. Tcyguleva, Anna E. Stepanova, D. Silnov
The problem of using computer-assisted learning technologies for organization musical recommendations according to user’s preferences. The main content of work is an analysis of spectrograms of musical compositions of various styles and directions and its further processing using the algorithms of neural network. In this research the problem of making new way of musical classification is solving and proving the idea about the fact that musical preferences can be developed on basics of compiling several packs of digital tags, that were stated to compositions because of the work of neural network.
{"title":"Application of machine learning in the development of databases of recommendation resources and music services","authors":"Kseniya V. Tcyguleva, Anna E. Stepanova, D. Silnov","doi":"10.1109/AICT50176.2020.9368586","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368586","url":null,"abstract":"The problem of using computer-assisted learning technologies for organization musical recommendations according to user’s preferences. The main content of work is an analysis of spectrograms of musical compositions of various styles and directions and its further processing using the algorithms of neural network. In this research the problem of making new way of musical classification is solving and proving the idea about the fact that musical preferences can be developed on basics of compiling several packs of digital tags, that were stated to compositions because of the work of neural network.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124840663","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368603
Nuno Pombo, R. Teixeira
The bug-fixing process challenges development teams and practitioners for best practices that may pave the way not only to efficient human resources management but also to provide information in advance on the required time to investigate and fix a bug. In this study, we proposed a temporal sequence activity model based on Hidden Markov Models to predict bug fixing time. Comprehensive evaluation results of two different scenarios based on bug reports existing in the the Bugzilla repository were provided. Our experiments demonstrate the feasibility of the proposed model in which the most accurate configuration was obtained with the 50 percent of bug records for training and test set.
{"title":"Contribution of Temporal Sequence Activities To Predict Bug Fixing Time","authors":"Nuno Pombo, R. Teixeira","doi":"10.1109/AICT50176.2020.9368603","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368603","url":null,"abstract":"The bug-fixing process challenges development teams and practitioners for best practices that may pave the way not only to efficient human resources management but also to provide information in advance on the required time to investigate and fix a bug. In this study, we proposed a temporal sequence activity model based on Hidden Markov Models to predict bug fixing time. Comprehensive evaluation results of two different scenarios based on bug reports existing in the the Bugzilla repository were provided. Our experiments demonstrate the feasibility of the proposed model in which the most accurate configuration was obtained with the 50 percent of bug records for training and test set.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129785491","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368751
Zh. Ismailov, D. Kononov, M. Furugyan
Problems of planning the execution of a set of jobs arising during the design and operation of backbone networks and transport and logistics centers are considered. This problem is formalized as the problem of finding the best schedule in a multi-agent system. Various options of problems of job planning and correction of deadlines depending on available throughput and processing capabilities are considered (all jobs are non-preemptive; all jobs allow interruptions and switching from one machine to another; part of jobs allows interruptions and switching, and part does not allow; in addition to machines non-renewable resource is also used). The mathematical solution is based on the reduction of incoming and outgoing flows to transport and logistics centers with a minimum cost in the backbone network. The areas of using the obtained results in the design systems of transport and logistics centers are proposed.
{"title":"Efficient Information and Communication Technologies in the Design of Transport and Logistics Centers of the New Silk Road","authors":"Zh. Ismailov, D. Kononov, M. Furugyan","doi":"10.1109/AICT50176.2020.9368751","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368751","url":null,"abstract":"Problems of planning the execution of a set of jobs arising during the design and operation of backbone networks and transport and logistics centers are considered. This problem is formalized as the problem of finding the best schedule in a multi-agent system. Various options of problems of job planning and correction of deadlines depending on available throughput and processing capabilities are considered (all jobs are non-preemptive; all jobs allow interruptions and switching from one machine to another; part of jobs allows interruptions and switching, and part does not allow; in addition to machines non-renewable resource is also used). The mathematical solution is based on the reduction of incoming and outgoing flows to transport and logistics centers with a minimum cost in the backbone network. The areas of using the obtained results in the design systems of transport and logistics centers are proposed.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127982352","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 : 2020-10-07DOI: 10.1109/AICT50176.2020.9368792
M. Artemenko, V. Budanov, N. Korenevskiy
The work is devoted to pilot modeling of the reaction of society to technogenic and biological sudden environmental influences. For the description, the methodology of the socio-technical landscape is used, which reflects the development of certain social practices in the digital and technical environments. At the bifurcation points of the evolution of the socio-technical landscape, the phenomena of the "Black Swan" and "Boomerang Blow" arise - a powerful impulse effect on the landscape. There is an urgent problem of predicting reaction reactions. The aim of the work is the development and pilot study of a self-organizing algorithm of structural-parametric identification of transients. Impacts of a technical and biological nature are considered as objects of research: the development of the use of artificial intelligence and computer technology in medicine and the spread of COVID 19. Models for countries: UK, Russia and Uzbekistan are given. It is shown that the reaction of the sociotechnical landscape is acceptable described by homogeneous differential equations of the second degree with a complex exponentially harmonic function on the right side. The most adequate mathematical models are given. This work was supported by the Russian Science Foundation grant # 19-18-00504.
{"title":"Self-organizing algorithm for pilot modeling the reaction of society to the phenomenon of the Black Swan","authors":"M. Artemenko, V. Budanov, N. Korenevskiy","doi":"10.1109/AICT50176.2020.9368792","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368792","url":null,"abstract":"The work is devoted to pilot modeling of the reaction of society to technogenic and biological sudden environmental influences. For the description, the methodology of the socio-technical landscape is used, which reflects the development of certain social practices in the digital and technical environments. At the bifurcation points of the evolution of the socio-technical landscape, the phenomena of the \"Black Swan\" and \"Boomerang Blow\" arise - a powerful impulse effect on the landscape. There is an urgent problem of predicting reaction reactions. The aim of the work is the development and pilot study of a self-organizing algorithm of structural-parametric identification of transients. Impacts of a technical and biological nature are considered as objects of research: the development of the use of artificial intelligence and computer technology in medicine and the spread of COVID 19. Models for countries: UK, Russia and Uzbekistan are given. It is shown that the reaction of the sociotechnical landscape is acceptable described by homogeneous differential equations of the second degree with a complex exponentially harmonic function on the right side. The most adequate mathematical models are given. This work was supported by the Russian Science Foundation grant # 19-18-00504.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126309327","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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