University of KashanSoft Computing Journal2322-37079220210219Approaches of user activity detection and a new fuzzy logic-based method to determine the risk amount of user unusual activity in the smart homeApproaches of user activity detection and a new fuzzy logic-based method to determine the risk amount of user unusual activity in the smart home21311157210.22052/scj.2021.242812.0FAHanieAbbasiFaculty of Electrical and Computer Engineering, Department of Computer Engineering, Qom University of Technology, Qom, Iran.MahboobehShamsiFaculty of Electrical and Computer Engineering, Department of Computer Engineering, Qom University of Technology, Qom, Iran.AbdolrezaRasuli KenariFaculty of Electrical and Computer Engineering, Department of Computer Engineering, Qom University of Technology, Qom, Iran.Journal Article20200824In recent years, the number of sick and elderly people that are living alone in their homes and need care has grown. This is why the smart home is needed for the awareness of their condition. Identification of the patient's activity using environment sensors is the first step in implementing a smart home. In such a home, the patient's relatives can leave the patient alone with less concern. In this research, various methods of recognizing user’s activity in the smart home are presented, and then a new method is introduced to diagnose the risk amount of Alzheimer's patients in which fuzzy-logic is used in cases such as start-up time of the activity. This system uses fuzzy logic in three phases. Since this method is considered for specific patients, the wearing sensors are not used because they have difficulties for the elderly and even an Alzheimer's patient may forget to wear them. However, the implementation of this layer also achieved good results, i.e., 84% accuracy.In recent years, the number of sick and elderly people that are living alone in their homes and need care has grown. This is why the smart home is needed for the awareness of their condition. Identification of the patient's activity using environment sensors is the first step in implementing a smart home. In such a home, the patient's relatives can leave the patient alone with less concern. In this research, various methods of recognizing user’s activity in the smart home are presented, and then a new method is introduced to diagnose the risk amount of Alzheimer's patients in which fuzzy-logic is used in cases such as start-up time of the activity. This system uses fuzzy logic in three phases. Since this method is considered for specific patients, the wearing sensors are not used because they have difficulties for the elderly and even an Alzheimer's patient may forget to wear them. However, the implementation of this layer also achieved good results, i.e., 84% accuracy.https://scj.kashanu.ac.ir/article_111572_0a7320571810d1281cce6246f8f09fb9.pdfUniversity of KashanSoft Computing Journal2322-37079220210219A systematic literature review of blockchain-based E-VotingA systematic literature review of blockchain-based E-Voting143311157310.22052/scj.2021.242836.0FAPayamRanjbariDepartment of Computer Engineering, Islamic Azad University, Sanandaj Branch, Sanandaj, Iran.Seyed AmirSheikhahmadiDepartment of Computer Engineering, Islamic Azad University, Sanandaj Branch, Sanandaj, Iran.Journal Article20210127This paper aims to identify, analyze, and organize the literature on the applications of blockchain technology in electronic/online voting, as well as provide insights for future research. This study tries to show the most important applications of blockchain in e-voting and identify the most important e-voting challenges that blockchain offers a solution to them. This study follows the method of Systematic Literature Review (SLR) to analyze the existing literature on blockchain integration with e-voting. In this study, 30 articles from conferences and journals between 2017 and May 2021 were reviewed. It seems that the integration of blockchain with e-voting is in the early stages of its operation and researchers and experts are not fully aware of the potential of blockchain for e-voting. The most important results of merging or using blockchain for e-voting are voter privacy protection, anonymity, security increase, and voting system reliability. But on the other hand, there are serious discrepancies among researchers in terms of the cost-efficiency and scalability of blockchain-based voting systems. The limitations of this study are mainly due to the scarcity of studies on the applications of blockchain for e-voting (large-scale) in journals and conferences, as well as information on private-university projects that are implementing their idea is not available.This paper aims to identify, analyze, and organize the literature on the applications of blockchain technology in electronic/online voting, as well as provide insights for future research. This study tries to show the most important applications of blockchain in e-voting and identify the most important e-voting challenges that blockchain offers a solution to them. This study follows the method of Systematic Literature Review (SLR) to analyze the existing literature on blockchain integration with e-voting. In this study, 30 articles from conferences and journals between 2017 and May 2021 were reviewed. It seems that the integration of blockchain with e-voting is in the early stages of its operation and researchers and experts are not fully aware of the potential of blockchain for e-voting. The most important results of merging or using blockchain for e-voting are voter privacy protection, anonymity, security increase, and voting system reliability. But on the other hand, there are serious discrepancies among researchers in terms of the cost-efficiency and scalability of blockchain-based voting systems. The limitations of this study are mainly due to the scarcity of studies on the applications of blockchain for e-voting (large-scale) in journals and conferences, as well as information on private-university projects that are implementing their idea is not available.https://scj.kashanu.ac.ir/article_111573_a27e5988630246d18af3ded56fde8191.pdfUniversity of KashanSoft Computing Journal2322-37079220210219Load frequency control by using fuzzy-PID controller with optimized membership functionsLoad frequency control by using fuzzy-PID controller with optimized membership functions344311157410.22052/scj.2021.242834.0FASaberFalahati AliabadiFaculty of Electrical and Computer Engineering, Department of Electrical Engineering, Kashan University, Kashan, IranIsfahan Regional Electricity Company, Isfahan, IranSeyed AbbasTaherFaculty of Electrical and Computer Engineering, Department of Electrical Engineering, Kashan University, Kashan, Iran.Journal Article20210124Load Frequency Control (LFC) is one the most important topics in power systems. To this end, Proportional-integral (PI) controllers is usually employed in industry. In this paper, a Fuzzy-PID controller with optimized membership functions has been designed for LFC in a two-area power system. Optimization has been employed in order to define the location of input membership functions and gains of Fuzzy-PID controllers. Imperialist Competitive Algorithm (ICA) has been used for optimization in this study. Simulations have been carried out in MATLAM/SIMULINK in presence of wind power and variable loads. In order to conduct comparisons, the simulations have been carried out using the fractional order PID (FOPID) controller optimized by ICA. Moreover, to verify robustness degree of the proposed controller against system uncertainties, simulations have been done by changing the parameters of two-area system. Results of simulations illustrate good performance of the proposed controller.Load Frequency Control (LFC) is one the most important topics in power systems. To this end, Proportional-integral (PI) controllers is usually employed in industry. In this paper, a Fuzzy-PID controller with optimized membership functions has been designed for LFC in a two-area power system. Optimization has been employed in order to define the location of input membership functions and gains of Fuzzy-PID controllers. Imperialist Competitive Algorithm (ICA) has been used for optimization in this study. Simulations have been carried out in MATLAM/SIMULINK in presence of wind power and variable loads. In order to conduct comparisons, the simulations have been carried out using the fractional order PID (FOPID) controller optimized by ICA. Moreover, to verify robustness degree of the proposed controller against system uncertainties, simulations have been done by changing the parameters of two-area system. Results of simulations illustrate good performance of the proposed controller.https://scj.kashanu.ac.ir/article_111574_9b860fc1c8f31ced2b2bff4289708edc.pdfUniversity of KashanSoft Computing Journal2322-37079220210219A method to simplify patterns in web services compositions and select optimal probabilistic compositionA method to simplify patterns in web services compositions and select optimal probabilistic composition447111155410.22052/scj.2021.243188.1003FANargesZahiriFaculty of Electrical and Computer Engineering, Department of Computer Engineering, University of Kashan, Kashan, IranSeyed MortezaBabamirFaculty of Electrical and Computer Engineering, Department of Computer Engineering, University of Kashan, Kashan, IranJournal Article20210602One of the most challenging issues in web services is their composition, which is presented as a graph to show the interaction between services. Each node in such a graph is called an abstract web service with a specific function and undetermined quality attributes. For each abstract service, there is a set of candidate services with the same function but different quality attributes. Selecting a candidate web service for each abstract service leading to an optimal combination is an NP-hard problem; hence, heuristic algorithms should be used to resolve it. Several methods have been proposed to select optimal web service composition, but most of them don't support the probability structure. Among others, one method supports a probability structure that is not scalable for large graphs, is constraint based, and analyzes each path of the graph separately. This paper presents an integrated scalable multi-objective approach for analyzing graph where not only two new patterns of nested loops and parallel loops are dealt with but also performance is improved by representing a method for simplifying web-service compositions. In this method, to select optimal web services and to respect scalability, evolutionary algorithms NSGAII and SPEAII are used. In the proposed method, first in conditional graphs, each path is traversed according to its probability and then NSGAII is used to determine the best path in the graph and find better solutions. The proposed method was compared with the best known method; results showed the proposed method enjoys 30% improvement in reliability and 121 milliseconds in response time.One of the most challenging issues in web services is their composition, which is presented as a graph to show the interaction between services. Each node in such a graph is called an abstract web service with a specific function and undetermined quality attributes. For each abstract service, there is a set of candidate services with the same function but different quality attributes. Selecting a candidate web service for each abstract service leading to an optimal combination is an NP-hard problem; hence, heuristic algorithms should be used to resolve it. Several methods have been proposed to select optimal web service composition, but most of them don't support the probability structure. Among others, one method supports a probability structure that is not scalable for large graphs, is constraint based, and analyzes each path of the graph separately. This paper presents an integrated scalable multi-objective approach for analyzing graph where not only two new patterns of nested loops and parallel loops are dealt with but also performance is improved by representing a method for simplifying web-service compositions. In this method, to select optimal web services and to respect scalability, evolutionary algorithms NSGAII and SPEAII are used. In the proposed method, first in conditional graphs, each path is traversed according to its probability and then NSGAII is used to determine the best path in the graph and find better solutions. The proposed method was compared with the best known method; results showed the proposed method enjoys 30% improvement in reliability and 121 milliseconds in response time.https://scj.kashanu.ac.ir/article_111554_4f783773cf97d6566014e37d5795ced4.pdfUniversity of KashanSoft Computing Journal2322-37079220210219An adaptive steganography method for compressed videos with HEVC standardAn adaptive steganography method for compressed videos with HEVC standard728311157510.22052/scj.2021.242817.0FAZahraBahrami-AslDepartment of Computer Engineering, Qom Branch, Islamic Azad University, Qom, IranMohammadrezaRamezanpourDepartment of Computer Engineering, Mobarakeh Branch, Islamic Azad University, Mobarakeh, Isfahan, Iran.ReihanehKhorsandDepartment of Computer Engineering, Dolatabad Branch, Islamic Azad University, Isfahan, Iran.Journal Article20200927Among others, steganography of video data is an important research topic in data encryption technologies, which is considered as an essential tool; this is because not only the security required for the transmission of hidden messages is becoming increasingly difficult, but also such security in video files has a high important. This research is based on the HEVC standard, which is the latest video compression standard to date. This paper presents a new method for steganography of compressed videos with the HEVC standard. In the proposed method, the motion vectors of the prediction blocks inside the frame are used as carriers of hidden information. A set of randomly selected coding block motion vectors is used and embedding of information is done by increasing or decreasing one unit of the motion vector component. The experimental results showed that after embedding the hidden information, the video quality decreased low but the average of the embedding capacity increased.Among others, steganography of video data is an important research topic in data encryption technologies, which is considered as an essential tool; this is because not only the security required for the transmission of hidden messages is becoming increasingly difficult, but also such security in video files has a high important. This research is based on the HEVC standard, which is the latest video compression standard to date. This paper presents a new method for steganography of compressed videos with the HEVC standard. In the proposed method, the motion vectors of the prediction blocks inside the frame are used as carriers of hidden information. A set of randomly selected coding block motion vectors is used and embedding of information is done by increasing or decreasing one unit of the motion vector component. The experimental results showed that after embedding the hidden information, the video quality decreased low but the average of the embedding capacity increased.https://scj.kashanu.ac.ir/article_111575_8917315f008868ef1c32165e4c462ac5.pdfUniversity of KashanSoft Computing Journal2322-37079220210219A hybrid algorithm based on Gossip architecture using SVM for task scheduling in cloud computingA hybrid algorithm based on Gossip architecture using SVM for task scheduling in cloud computing849311157610.22052/scj.2021.242822.0FAShivaRazzaghzadehDepartment of Computer Engineering, Islamic Azad University, Ardabil Branch, Ardabil, Iran.ParisaNorouzi KiviYoung and Elite Researchers Club, Islamic Azad University, Ardabil Branch, Ardabil, Iran.BabakPanahiDepartment of Computer Engineering, Islamic Azad University, Ardabil Branch, Ardabil, Iran.Journal Article20201020Nowadays, Cloud computing is very important due to its widespread use. The considerable extensiveness and flexibility of cloud computing as well as other advantages led to new challenges such as reliability. Such challenges have more importance among researchers because of existing high number of cloud users. To solve the challenge of reliability, a variety of fault tolerance algorithms were provided in recent years to deal with and fix faults in cloud computing. Despite many efforts, there still exist some problems. This paper aims to present an efficient and new hybrid algorithm where SVM features, and Gossip protocol are used. SVM is used to analyze and categorize virtual machine data based on behavioral patterns. Moreover, Gossip is used to gather data monitoring categories. In the proposed model, processing time, load amount, and reliability are evaluated for better service quality. The simulation results through the CloudSim tools show that proposed method is able to increase the processing speed around 0.65 and decrease makespan to 7.22 seconds.Nowadays, Cloud computing is very important due to its widespread use. The considerable extensiveness and flexibility of cloud computing as well as other advantages led to new challenges such as reliability. Such challenges have more importance among researchers because of existing high number of cloud users. To solve the challenge of reliability, a variety of fault tolerance algorithms were provided in recent years to deal with and fix faults in cloud computing. Despite many efforts, there still exist some problems. This paper aims to present an efficient and new hybrid algorithm where SVM features, and Gossip protocol are used. SVM is used to analyze and categorize virtual machine data based on behavioral patterns. Moreover, Gossip is used to gather data monitoring categories. In the proposed model, processing time, load amount, and reliability are evaluated for better service quality. The simulation results through the CloudSim tools show that proposed method is able to increase the processing speed around 0.65 and decrease makespan to 7.22 seconds.https://scj.kashanu.ac.ir/article_111576_a02d5f54f588d92c90042fd889db6610.pdfUniversity of KashanSoft Computing Journal2322-37079220210219Predicting the academic status of admitted applicants based on educational and admission data using data mining techniquesPredicting the academic status of admitted applicants based on educational and admission data using data mining techniques9411311157710.22052/scj.2021.242837.0FAArashKhosraviDepartment of Computer Engineering, Faculty of Engineering, Mahallat Institute of Higher Education, Mahallat, Iran.HadiAbdulmalekiDepartment of Computer Engineering, Faculty of Electrical, Computer and Medical Engineering, Shahab Danesh Institute of Higher Education, Qom, Iran.MehriFayaziDepartment of Computer Engineering, Faculty of Engineering, Qom University, Qom, Iran.Journal Article20210208Educational data mining has become an increasingly popular field of research in recent years due to the vast amount of student data held by educational institutions. This data can be utilized as a tool to improve the quality of education by extracting knowledge that can assist institutions in enhancing their teaching methods, learning processes, and decision-making. The purpose of this paper is to predict the educational status of students who are intending to continue their studies from an associate degree to a bachelor's degree. As the Ministry of Science plans to eliminate the entrance exam, universities are faced with the challenge of selecting students based on what criteria. To address this issue, data mining techniques such as decision tree, Naïve Bayes, neural network, support vector machine, random forest, Bagging, and Boosting were employed to analyze the educational information of new students. Then, by comparing this information with that of graduate, dropout, and expelled students at the bachelor's level, a more effective method for selecting students was proposed. The results indicate that random forest has the highest accuracy at 92.28%, while Naïve Bayes has the lowest accuracy at 61.09% in predicting educational status. Educational data mining has become an increasingly popular field of research in recent years due to the vast amount of student data held by educational institutions. This data can be utilized as a tool to improve the quality of education by extracting knowledge that can assist institutions in enhancing their teaching methods, learning processes, and decision-making. The purpose of this paper is to predict the educational status of students who are intending to continue their studies from an associate degree to a bachelor's degree. As the Ministry of Science plans to eliminate the entrance exam, universities are faced with the challenge of selecting students based on what criteria. To address this issue, data mining techniques such as decision tree, Naïve Bayes, neural network, support vector machine, random forest, Bagging, and Boosting were employed to analyze the educational information of new students. Then, by comparing this information with that of graduate, dropout, and expelled students at the bachelor's level, a more effective method for selecting students was proposed. The results indicate that random forest has the highest accuracy at 92.28%, while Naïve Bayes has the lowest accuracy at 61.09% in predicting educational status. https://scj.kashanu.ac.ir/article_111577_19f15e526a828df055970a61c557bb65.pdfUniversity of KashanSoft Computing Journal2322-37079220210219Cost-based workflow scheduling using algebraic structuresCost-based workflow scheduling using algebraic structures11412911157810.22052/scj.2021.242814.0FAMohammad JavadNadjafi-AraniDepartment of Computer Science, Faculty of Science, Mahallat Institute of Higher Education, Mahallat, Iran.SaeedDoostaliDepartment of Computer Engineering, Faculty of Electrical and Computer Engineering, Kashan University, Kashan, Iran.0000-0002-6217-5813Journal Article20200902Workflow is a common model for describing a wide range of applications in distributed systems. Due to the computing power of cloud computing, it has been widely applied to solve large workflows. Cloud workflow scheduling aims to find the most suitable resources for each task of a workflow so that optimizing certain performance metrics such as execution time and cost are met. Since scheduling is a well-known NP-complete problem, many heuristic approaches have been proposed to solve it in homogeneous and heterogeneous distributed systems. The longest path of a workflow is called the critical path on which the workflow completion time depends. In fact, delays in the execution of critical path tasks can delay the workflow completion time and violate the execution deadline of the workflow. Hence, in this paper, we present a parallel heuristic algorithm for quality-based workflow scheduling. The objective function proposed in the algorithm leads to minimizing the execution time of a workflow as well as respecting the deadline. By assigning a pseudo-lattice to each sub-workflow, the start and end time of each task and the appropriate resources for them are determined. The simulation results on the Montage and LIGO workflows show that the proposed approach reduces the cost by 5.5% compared to IC-PCP and by 11% compared to IC-PCPD2. Workflow is a common model for describing a wide range of applications in distributed systems. Due to the computing power of cloud computing, it has been widely applied to solve large workflows. Cloud workflow scheduling aims to find the most suitable resources for each task of a workflow so that optimizing certain performance metrics such as execution time and cost are met. Since scheduling is a well-known NP-complete problem, many heuristic approaches have been proposed to solve it in homogeneous and heterogeneous distributed systems. The longest path of a workflow is called the critical path on which the workflow completion time depends. In fact, delays in the execution of critical path tasks can delay the workflow completion time and violate the execution deadline of the workflow. Hence, in this paper, we present a parallel heuristic algorithm for quality-based workflow scheduling. The objective function proposed in the algorithm leads to minimizing the execution time of a workflow as well as respecting the deadline. By assigning a pseudo-lattice to each sub-workflow, the start and end time of each task and the appropriate resources for them are determined. The simulation results on the Montage and LIGO workflows show that the proposed approach reduces the cost by 5.5% compared to IC-PCP and by 11% compared to IC-PCPD2. https://scj.kashanu.ac.ir/article_111578_ea47357fe631efb22bcc98ef8389a974.pdf