Pub Date : 2020-10-07DOI: 10.1109/AICT50176.2020.9368873
H. Erol, Recep Erol
Reliability and chaotic risk modeling for a real time data driven smart system is an important problem of systems engineering. A real time data driven smart system is a multicomponent chaotic mechatronic system, such as driveless car with thousands of components. It uses physically sensors for its components and real time data for functioning of components. Its components having increasing, constant or decreasing risk functions. Reliability and chaotic risk modeling in a multicomponent chaotic system uses the reliability block diagrams. Mixture distribution models with weight functions are proposed for modeling reliability and chaotic risk of reliability block diagrams for real time data driven smart systems. Non-linear reliability and hazard functions for real time data driven smart systems are transformed to mixture reliability and hazard functions respectively. Mixture reliability and hazard functions are expressed as linear functions of component functions with non-linear weight functions. Mixture reliability and hazard functions for real time data driven smart systems are obtained as finite sum of products of component’s non-linear weight functions with component pure reliability and hazard functions respectively. It is shown that the number of terms in mixture reliability and hazard functions for real time data driven smart systems are equal to the number of components in multicomponent chaotic systems. The effect of the structure of reliability block diyagram of a multicomponent chaotic system is reflected to the component’s non-linear weight functions. Mixture distribution models with non-linear weight functions and pure component functions are used both for prediction of reliability or life times and risk of multicomponent chaotic system and its components concurrently. The working principle and computational steps of the proposed mixture model reliability and chaotic risk analysis of reliability block diagram of a multicomponent chaotic system were explained on an application for complex event processing.
{"title":"Reliability And Chaotic Risk Modeling For Real Time Data Driven Smart Systems","authors":"H. Erol, Recep Erol","doi":"10.1109/AICT50176.2020.9368873","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368873","url":null,"abstract":"Reliability and chaotic risk modeling for a real time data driven smart system is an important problem of systems engineering. A real time data driven smart system is a multicomponent chaotic mechatronic system, such as driveless car with thousands of components. It uses physically sensors for its components and real time data for functioning of components. Its components having increasing, constant or decreasing risk functions. Reliability and chaotic risk modeling in a multicomponent chaotic system uses the reliability block diagrams. Mixture distribution models with weight functions are proposed for modeling reliability and chaotic risk of reliability block diagrams for real time data driven smart systems. Non-linear reliability and hazard functions for real time data driven smart systems are transformed to mixture reliability and hazard functions respectively. Mixture reliability and hazard functions are expressed as linear functions of component functions with non-linear weight functions. Mixture reliability and hazard functions for real time data driven smart systems are obtained as finite sum of products of component’s non-linear weight functions with component pure reliability and hazard functions respectively. It is shown that the number of terms in mixture reliability and hazard functions for real time data driven smart systems are equal to the number of components in multicomponent chaotic systems. The effect of the structure of reliability block diyagram of a multicomponent chaotic system is reflected to the component’s non-linear weight functions. Mixture distribution models with non-linear weight functions and pure component functions are used both for prediction of reliability or life times and risk of multicomponent chaotic system and its components concurrently. The working principle and computational steps of the proposed mixture model reliability and chaotic risk analysis of reliability block diagram of a multicomponent chaotic system were explained on an application for complex event processing.","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":"128931004","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/aict50176.2020.9368643
{"title":"[Copyright notice]","authors":"","doi":"10.1109/aict50176.2020.9368643","DOIUrl":"https://doi.org/10.1109/aict50176.2020.9368643","url":null,"abstract":"","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"25 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":"127354785","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/AICT50176.2020.9368822
I. Rabbimov, S. Kobilov, I. Mporas
The rapid growth of online news belonging to different categories is causing users to spend a lot of time and effort searching for relevant and important news. Text categorization has a great significance in information retrieval and natural language processing where unstructured text can be organized into predefined categories. In this paper we investigate Uzbek news categorization using a convolution neural network and four word embedding models. We obtain two new word embeddings for Uzbek and present them in the Uzbek news categorization task.
{"title":"Uzbek News Categorization using Word Embeddings and Convolutional Neural Networks","authors":"I. Rabbimov, S. Kobilov, I. Mporas","doi":"10.1109/AICT50176.2020.9368822","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368822","url":null,"abstract":"The rapid growth of online news belonging to different categories is causing users to spend a lot of time and effort searching for relevant and important news. Text categorization has a great significance in information retrieval and natural language processing where unstructured text can be organized into predefined categories. In this paper we investigate Uzbek news categorization using a convolution neural network and four word embedding models. We obtain two new word embeddings for Uzbek and present them in the Uzbek news categorization task.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"31 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":"121222070","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/AICT50176.2020.9368793
Kh.E Khujamatov, E. Reypnazarov, D. Khasanov, Nurshod Akhmedov
Article discusses the issue of building the Internet of things and cyber-physical systems networks, as well as data processing in these systems. Initially, a comparative analysis of the concept of the Internet of things and cyber-physical systems were conducted. Then various network construction technologies are provided, including wired and wireless short-range technologies, solutions based on M2M, LPWAN, NB-IoT and 5G, as well as scientific and analytical data on cloud, fog, edge computing methods of data processing in these systems.
{"title":"Networking and Computing in Internet of Things and Cyber-Physical Systems","authors":"Kh.E Khujamatov, E. Reypnazarov, D. Khasanov, Nurshod Akhmedov","doi":"10.1109/AICT50176.2020.9368793","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368793","url":null,"abstract":"Article discusses the issue of building the Internet of things and cyber-physical systems networks, as well as data processing in these systems. Initially, a comparative analysis of the concept of the Internet of things and cyber-physical systems were conducted. Then various network construction technologies are provided, including wired and wireless short-range technologies, solutions based on M2M, LPWAN, NB-IoT and 5G, as well as scientific and analytical data on cloud, fog, edge computing methods of data processing in these systems.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"8 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":"129406007","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/AICT50176.2020.9368571
D. Kuryazov, Dilshod Jabborov, Bekmurod Khujamuratov
Continuously changing the existing software systems results in large and monolith software solutions making them difficult to maintain. As maintenance and development of monolithic software systems is a difficult task, there is a need for decomposing these monolithic systems into smaller subsystems, components and services, i.e., microservices. Service-oriented architectures yield more maintenance and less complexity in developing large-scale software applications. Thus, this paper focuses on decomposing monolithic software systems into microservices in order to maintain them with less development effort. Moreover, it addresses to the problem of architectural refactoring and improvement of software systems during architectural migration.
{"title":"Towards Decomposing Monolithic Applications into Microservices","authors":"D. Kuryazov, Dilshod Jabborov, Bekmurod Khujamuratov","doi":"10.1109/AICT50176.2020.9368571","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368571","url":null,"abstract":"Continuously changing the existing software systems results in large and monolith software solutions making them difficult to maintain. As maintenance and development of monolithic software systems is a difficult task, there is a need for decomposing these monolithic systems into smaller subsystems, components and services, i.e., microservices. Service-oriented architectures yield more maintenance and less complexity in developing large-scale software applications. Thus, this paper focuses on decomposing monolithic software systems into microservices in order to maintain them with less development effort. Moreover, it addresses to the problem of architectural refactoring and improvement of software systems during architectural migration.","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":"129098036","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/AICT50176.2020.9368680
Hakimjon Zaynidinov, O. Mallayev, Javohir Nurmurodov
The article explores the possibility of computing parallel data compression using cubic spline. For example, ways to parallel the process of digital processing of seismic signals have been considered. The main performance indicators of parallel algorithms have been compared with consecutive algorithms. Spline methods are a versatile signal processing tool. It is more accurate than other mathematical methods, information equality is faster, and maintenance costs are much lower. On the other hand, the equipment used in such systems must also meet high performance requirements. To achieve high speeds, parallel algorithms were developed using OpenMP and MPI technologies and implemented in the architecture of multi-core processors. A mathematical method for the parallel calculation of the coefficients of a cubic spline has been developed and a parallel signal processing algorithm has been developed on its basis. As an example, parallelization is a computation during seismic signal processing. The main indicators of efficiency and acceleration of the parallel algorithm were compared with the sequential algorithm. Explained the relevance of the use of parallel numerical systems, described the main approaches to the distribution of processes and methods of data processing, described the principles of parallel programming technology, studied the basic parameters of parallel algorithms for the initial calculation of the numerical value of cubic spline. The parallel algorithm considered for constructing the cubic spline of defect 1 as p - > n leads to the construction of a local cubic spline on each grid interval ω.
{"title":"Parallel Algorithm For Constructing a Cubic Spline on Multi-Core Processors in a Cluster","authors":"Hakimjon Zaynidinov, O. Mallayev, Javohir Nurmurodov","doi":"10.1109/AICT50176.2020.9368680","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368680","url":null,"abstract":"The article explores the possibility of computing parallel data compression using cubic spline. For example, ways to parallel the process of digital processing of seismic signals have been considered. The main performance indicators of parallel algorithms have been compared with consecutive algorithms. Spline methods are a versatile signal processing tool. It is more accurate than other mathematical methods, information equality is faster, and maintenance costs are much lower. On the other hand, the equipment used in such systems must also meet high performance requirements. To achieve high speeds, parallel algorithms were developed using OpenMP and MPI technologies and implemented in the architecture of multi-core processors. A mathematical method for the parallel calculation of the coefficients of a cubic spline has been developed and a parallel signal processing algorithm has been developed on its basis. As an example, parallelization is a computation during seismic signal processing. The main indicators of efficiency and acceleration of the parallel algorithm were compared with the sequential algorithm. Explained the relevance of the use of parallel numerical systems, described the main approaches to the distribution of processes and methods of data processing, described the principles of parallel programming technology, studied the basic parameters of parallel algorithms for the initial calculation of the numerical value of cubic spline. The parallel algorithm considered for constructing the cubic spline of defect 1 as p - > n leads to the construction of a local cubic spline on each grid interval ω.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"93 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":"124632751","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/aict50176.2020.9368725
{"title":"AICT 2020 Conference Opening Speech","authors":"","doi":"10.1109/aict50176.2020.9368725","DOIUrl":"https://doi.org/10.1109/aict50176.2020.9368725","url":null,"abstract":"","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"54 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":"129661597","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/AICT50176.2020.9368724
Amirsaidov U.B., Qodirov A.A.
An analytical model for establishing a connection in a random access channel is developed. he probabilistic-temporal characteristics are analyzed, such as the probability of a successful and unsuccessful connection establishment, the average delay of a successful connection establishment. The dependence of the listed characteristics on the probability of collision possible with the transmission of the preamble is investigated. a method for selecting a preamble based on a reinforcement learning mechanism is proposed, the probability of choosing the same preambles is determined, a probabilistic-temporal characteristics of the connection establishment procedure are compared with the equally probable and proposed preamble selection methods.
{"title":"Implementation of the Reinforcement Learning Mechanism in the Random Access Channel Procedure","authors":"Amirsaidov U.B., Qodirov A.A.","doi":"10.1109/AICT50176.2020.9368724","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368724","url":null,"abstract":"An analytical model for establishing a connection in a random access channel is developed. he probabilistic-temporal characteristics are analyzed, such as the probability of a successful and unsuccessful connection establishment, the average delay of a successful connection establishment. The dependence of the listed characteristics on the probability of collision possible with the transmission of the preamble is investigated. a method for selecting a preamble based on a reinforcement learning mechanism is proposed, the probability of choosing the same preambles is determined, a probabilistic-temporal characteristics of the connection establishment procedure are compared with the equally probable and proposed preamble selection methods.","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":"130090155","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/AICT50176.2020.9368820
Thaer Thaher, Rashid Jayousi
The academic performance of students is of great interest to tutors and decision-makers in educational institutions. The extensive use of information technology systems in education generates an enormous amount of data, which is challenging to analyze and extract valuable information. Therefore, Educational Data Mining (EDM) concept emerges to adapt Data Mining (DM) techniques to extract the hidden and valuable educational knowledge that improves the learning process. The primary purpose of this paper is to introduce an efficient student’s performance prediction model. For this purpose, a feed-forward Multi-Layer Perceptron approach boosted with stochastic training algorithms is proposed. The proposed model is benchmarked and assessed using three public educational datasets gathered from UCI and Kaggle repositories. Synthetic Minority Oversampling Technique (SMOTE) is utilized to handle the imbalanced data problem. The performance of the proposed model is evaluated by a set of classifiers, namely, Support Vector Machine, Decision Trees, K-Nearest Neighbors, Logistic Regression, Linear Discriminant Analysis, and Random Forest. The comparative study revealed that the MLP achieved promising prediction quality on the majority of datasets compared to other traditional classifiers, as well as those in previous works.
{"title":"Prediction of Student’s Academic Performance using Feedforward Neural Network Augmented with Stochastic Trainers","authors":"Thaer Thaher, Rashid Jayousi","doi":"10.1109/AICT50176.2020.9368820","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368820","url":null,"abstract":"The academic performance of students is of great interest to tutors and decision-makers in educational institutions. The extensive use of information technology systems in education generates an enormous amount of data, which is challenging to analyze and extract valuable information. Therefore, Educational Data Mining (EDM) concept emerges to adapt Data Mining (DM) techniques to extract the hidden and valuable educational knowledge that improves the learning process. The primary purpose of this paper is to introduce an efficient student’s performance prediction model. For this purpose, a feed-forward Multi-Layer Perceptron approach boosted with stochastic training algorithms is proposed. The proposed model is benchmarked and assessed using three public educational datasets gathered from UCI and Kaggle repositories. Synthetic Minority Oversampling Technique (SMOTE) is utilized to handle the imbalanced data problem. The performance of the proposed model is evaluated by a set of classifiers, namely, Support Vector Machine, Decision Trees, K-Nearest Neighbors, Logistic Regression, Linear Discriminant Analysis, and Random Forest. The comparative study revealed that the MLP achieved promising prediction quality on the majority of datasets compared to other traditional classifiers, as well as those in previous works.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"76 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":"121903613","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/AICT50176.2020.9368572
Adel Hassan, Rashid Jayousi
Credit scoring procedures used by most financial services organizations, especially the banking sector to classify their customers-based granting risk methodology. Loans types discussed in this paper can vary from bank to bank and such as housing loans, cars loans, or personal loans. Moreover, this article discussed a different kind of scoring approaches and categorized loans-based scoring level to be good loans or bad loans. Various data mining techniques will be used to analyses and evaluate these loans to enable the bank to grant the loans with minimum risk to the customer that can pay for the loan based on a predefined and approved agreement between the bank and its customers. Data mining techniques and their issues with credit scoring systems will be covered through experiments using data mining techniques and credit scoring techniques using both statistical and advanced techniques by chosen bank credits loans data set for training and testing set.
{"title":"Financial Services Credit Scoring System Using Data Mining","authors":"Adel Hassan, Rashid Jayousi","doi":"10.1109/AICT50176.2020.9368572","DOIUrl":"https://doi.org/10.1109/AICT50176.2020.9368572","url":null,"abstract":"Credit scoring procedures used by most financial services organizations, especially the banking sector to classify their customers-based granting risk methodology. Loans types discussed in this paper can vary from bank to bank and such as housing loans, cars loans, or personal loans. Moreover, this article discussed a different kind of scoring approaches and categorized loans-based scoring level to be good loans or bad loans. Various data mining techniques will be used to analyses and evaluate these loans to enable the bank to grant the loans with minimum risk to the customer that can pay for the loan based on a predefined and approved agreement between the bank and its customers. Data mining techniques and their issues with credit scoring systems will be covered through experiments using data mining techniques and credit scoring techniques using both statistical and advanced techniques by chosen bank credits loans data set for training and testing set.","PeriodicalId":136491,"journal":{"name":"2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT)","volume":"19 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":"127427767","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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