With daily increasing use of cloud services, saving energy and using needed resources regardless of time and place, for both providers and users, have great importance. Resource provisioning in Cloud providers is a challenge because of the high variability of load over time. Most cloud providers conduct requests with a limited amount of resources that may be cause to reject the request of customers at the peak of workloads. Federated cloud is a mechanism for sharing resources thereby increasing scalability. Allocating resources in cloud is a complex procedure. Today with development of cloud-based data centers and increasing demand for cloud services, the main problems are high energy consumption and the profit of the services. In this paper, we propose an approach to reduce power consumption in data centers and increase profits for the satisfaction of service providers offering cloud services. The proposed approach is offered based on a real model for cloud federation. Experimental results show that the proposed approach, compared to the other similar approaches, causes to increase utilization and turns off idle servers to decrease consumed power which followed by an increase in providers' profit.
{"title":"Improving resource management of IaaS providers in cloud federation","authors":"Behnam Bagheri Ghavam Abadi, Mostafa Ghobaei Arani","doi":"10.1109/KBEI.2015.7436137","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436137","url":null,"abstract":"With daily increasing use of cloud services, saving energy and using needed resources regardless of time and place, for both providers and users, have great importance. Resource provisioning in Cloud providers is a challenge because of the high variability of load over time. Most cloud providers conduct requests with a limited amount of resources that may be cause to reject the request of customers at the peak of workloads. Federated cloud is a mechanism for sharing resources thereby increasing scalability. Allocating resources in cloud is a complex procedure. Today with development of cloud-based data centers and increasing demand for cloud services, the main problems are high energy consumption and the profit of the services. In this paper, we propose an approach to reduce power consumption in data centers and increase profits for the satisfaction of service providers offering cloud services. The proposed approach is offered based on a real model for cloud federation. Experimental results show that the proposed approach, compared to the other similar approaches, causes to increase utilization and turns off idle servers to decrease consumed power which followed by an increase in providers' profit.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116630528","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 : 2015-11-01DOI: 10.1109/KBEI.2015.7436211
Sedigheh Abbasghorbani, Reza Tavoli
Because of the important applications in today's world such as, users behavior in buying, mining web page traversal sequences or disease treatments, many algorithms have been produced in the area of sequential pattern mining over the last decade, most of which have also been modified to support short representations like closed, maximal, incremental or hierarchical sequences. This article reviews a number of algorithms in each category and puts them in taxonomy of sequential pattern mining techniques as an application. This article checks these algorithms by taxonomy for classifying sequential pattern mining algorithms based on their theoretical features and say advantage/disadvantage of them. This classification help to enhancing understanding of sequential pattern mining problems, current status of provided solutions, and direction of research in this area.
{"title":"Survey on sequential pattern mining algorithms","authors":"Sedigheh Abbasghorbani, Reza Tavoli","doi":"10.1109/KBEI.2015.7436211","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436211","url":null,"abstract":"Because of the important applications in today's world such as, users behavior in buying, mining web page traversal sequences or disease treatments, many algorithms have been produced in the area of sequential pattern mining over the last decade, most of which have also been modified to support short representations like closed, maximal, incremental or hierarchical sequences. This article reviews a number of algorithms in each category and puts them in taxonomy of sequential pattern mining techniques as an application. This article checks these algorithms by taxonomy for classifying sequential pattern mining algorithms based on their theoretical features and say advantage/disadvantage of them. This classification help to enhancing understanding of sequential pattern mining problems, current status of provided solutions, and direction of research in this area.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130076855","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 : 2015-11-01DOI: 10.1109/KBEI.2015.7436053
Navid Rajabi, Omid Rajabi
IRAN is located in a region of high seismic potential. This paper presents a real-time method of predicting earthquake before its arrival. Our proposed method is based on cross-correlation calculation of data sensed by Wireless Sensor Network (WSN) as well as, Transfer Function (TF) calculation for the seismic wave propagation path between a location close to the hypo-center and the location where vibration is going to be predicted. The information which was obtained during a long period of continuous monitoring, have been used and deployed for mathematical calculations. This information was relayed to the main server to collect data and store it for future evaluations. We show that there is some consistency between discrepant faults in such a way that releasing energy in one area can lead to another vibration and quake. Our proposed working procedure consists of two algorithms first is named learning algorithm which concentrates on long-term waveform collection, Signal to Noise Ratio (SNR) enhancement, cross-correlation calculations, and finally transfer function calculation during foreshock time, and second is named Prediction Algorithm which calculates the seismic output waveform based on earthquake around hypo-center as input for already determined transfer function. By this approach, we have introduced a novel solution as Earthquake Early-Warning System (EEWS) gives golden time which can preserve human's life and mitigate economical loss by mentioned elaborated process.
{"title":"Real time earthquake prediction using cross-correlation analysis & transfer function model","authors":"Navid Rajabi, Omid Rajabi","doi":"10.1109/KBEI.2015.7436053","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436053","url":null,"abstract":"IRAN is located in a region of high seismic potential. This paper presents a real-time method of predicting earthquake before its arrival. Our proposed method is based on cross-correlation calculation of data sensed by Wireless Sensor Network (WSN) as well as, Transfer Function (TF) calculation for the seismic wave propagation path between a location close to the hypo-center and the location where vibration is going to be predicted. The information which was obtained during a long period of continuous monitoring, have been used and deployed for mathematical calculations. This information was relayed to the main server to collect data and store it for future evaluations. We show that there is some consistency between discrepant faults in such a way that releasing energy in one area can lead to another vibration and quake. Our proposed working procedure consists of two algorithms first is named learning algorithm which concentrates on long-term waveform collection, Signal to Noise Ratio (SNR) enhancement, cross-correlation calculations, and finally transfer function calculation during foreshock time, and second is named Prediction Algorithm which calculates the seismic output waveform based on earthquake around hypo-center as input for already determined transfer function. By this approach, we have introduced a novel solution as Earthquake Early-Warning System (EEWS) gives golden time which can preserve human's life and mitigate economical loss by mentioned elaborated process.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130299243","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 : 2015-11-01DOI: 10.1109/KBEI.2015.7436192
Ahmad Pouramini, H. Varaee
A major goal of many manufactures is minimizing unscheduled downtime caused by equipment breakdown. To achieve this goal, an automatic defect detection system for the equipment can be employed. This paper presents a machine vision application for detecting defects in a traveling grate conveyor in pelletizing industry and similar industries. For this purpose, a video stream of the conveyor is captured by a camera and sent to a computer. In the computer, the image of each grate is extracted from the stream and then by processing its image over a sliding window, the damaged parts are detected. The detection rate of the proposed method is more than 98%.
{"title":"A machine vision system for defect detection of a traveling grate conveyor","authors":"Ahmad Pouramini, H. Varaee","doi":"10.1109/KBEI.2015.7436192","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436192","url":null,"abstract":"A major goal of many manufactures is minimizing unscheduled downtime caused by equipment breakdown. To achieve this goal, an automatic defect detection system for the equipment can be employed. This paper presents a machine vision application for detecting defects in a traveling grate conveyor in pelletizing industry and similar industries. For this purpose, a video stream of the conveyor is captured by a camera and sent to a computer. In the computer, the image of each grate is extracted from the stream and then by processing its image over a sliding window, the damaged parts are detected. The detection rate of the proposed method is more than 98%.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128048596","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 : 2015-11-01DOI: 10.1109/KBEI.2015.7436202
K. Kiani, Elmira Mohsenzadeh Korayem
In recent years Spiking Neural Networks (SNNs) have gained in popularity due to their low complexity. They have been used in many processes like learning and classification of data such as images. In this paper we have used the SNN Model, in order to have robust learning and classification of handwritten digits, i.e., to have a learning process which is persistent against changes and high noise levels. Due to the similarities among handwritten digits, the classifications have been erratic but the Deep Belief Network we have used in this paper solves this problem to a great extent. Our model consists of three layers. The first layer, composed of 225 neurons (15*15 pixels for each image), works as the receptor of input images. The middle layer is used for processes, encoding and network learning, while the last layer, which is composed of 10 neurons (as we have 10 distinct classes), does the job of prediction and classification of images. The model was implemented using MATLAB and we have used Hoda Persian handwritten digits dataset as our input images. The obtained results show that the implemented model can carry out, with good accuracy (95%), the learning and classification of images of handwritten digits with high levels of noise.
{"title":"Classification of Persian handwritten digits using spiking neural networks","authors":"K. Kiani, Elmira Mohsenzadeh Korayem","doi":"10.1109/KBEI.2015.7436202","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436202","url":null,"abstract":"In recent years Spiking Neural Networks (SNNs) have gained in popularity due to their low complexity. They have been used in many processes like learning and classification of data such as images. In this paper we have used the SNN Model, in order to have robust learning and classification of handwritten digits, i.e., to have a learning process which is persistent against changes and high noise levels. Due to the similarities among handwritten digits, the classifications have been erratic but the Deep Belief Network we have used in this paper solves this problem to a great extent. Our model consists of three layers. The first layer, composed of 225 neurons (15*15 pixels for each image), works as the receptor of input images. The middle layer is used for processes, encoding and network learning, while the last layer, which is composed of 10 neurons (as we have 10 distinct classes), does the job of prediction and classification of images. The model was implemented using MATLAB and we have used Hoda Persian handwritten digits dataset as our input images. The obtained results show that the implemented model can carry out, with good accuracy (95%), the learning and classification of images of handwritten digits with high levels of noise.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127913707","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 : 2015-11-01DOI: 10.1109/KBEI.2015.7436099
Amin Aref, Sonia Naderi, O. R. Ma'rouzi
Cooperative diversity has been proposed as a promising technology to achieve spatial diversity in wireless systems. In this paper, we analyze the outage probability and achievable spectral efficiency of SNR-based hybrid decode-amplify-forward (HDAF) relaying system with Adaptive discrete M-ary Quadrature Amplitude Modulation (M-QAM) over Rayleigh Fading channels. We consider a simple cooperative wireless system with three terminals while maximum ratio combining (MRC) technique, is used at destination.
{"title":"On the performance evaluation of hybrid decode-amplify-forward relaying protocol with adaptive M-QAM modulation over Rayleigh fading channels","authors":"Amin Aref, Sonia Naderi, O. R. Ma'rouzi","doi":"10.1109/KBEI.2015.7436099","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436099","url":null,"abstract":"Cooperative diversity has been proposed as a promising technology to achieve spatial diversity in wireless systems. In this paper, we analyze the outage probability and achievable spectral efficiency of SNR-based hybrid decode-amplify-forward (HDAF) relaying system with Adaptive discrete M-ary Quadrature Amplitude Modulation (M-QAM) over Rayleigh Fading channels. We consider a simple cooperative wireless system with three terminals while maximum ratio combining (MRC) technique, is used at destination.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117282133","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 : 2015-11-01DOI: 10.1109/KBEI.2015.7436159
A. R. Noei, H. Kholerdi
Three-phase induction motor has a high order and complex dynamics which makes the control of its parameters difficult in the presence of disturbance. Synergetic controller has been recently introduced and can be defined in such a way to guarantee the robustness of control system. In this paper, the synergetic control is used to control the speed of a fifth-order induction motor in the presence of load. Five manifolds are defined on five state space variables of induction motor. The goal is for the variables to converge to the desired values. The result shows that the synergetic control is able to control the speed when the load is suddenly applied to the motor. Adjusting the control parameters of the controller reduces the speed of convergence while decreasing the overshoot.
{"title":"Robust speed control of induction machine using synergetic controller","authors":"A. R. Noei, H. Kholerdi","doi":"10.1109/KBEI.2015.7436159","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436159","url":null,"abstract":"Three-phase induction motor has a high order and complex dynamics which makes the control of its parameters difficult in the presence of disturbance. Synergetic controller has been recently introduced and can be defined in such a way to guarantee the robustness of control system. In this paper, the synergetic control is used to control the speed of a fifth-order induction motor in the presence of load. Five manifolds are defined on five state space variables of induction motor. The goal is for the variables to converge to the desired values. The result shows that the synergetic control is able to control the speed when the load is suddenly applied to the motor. Adjusting the control parameters of the controller reduces the speed of convergence while decreasing the overshoot.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121535182","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 : 2015-11-01DOI: 10.1109/KBEI.2015.7436091
S. Haghpanah, Fatemeh Haghpanah
Human posture control is a complex issue in biomechanics. Human body is unstable without any controller. The stabilization of the body is achieved by the activation of the muscles and creating the joint torques. In this paper, human body in upright standing position has been modeled using an inverted double pendulum. Since the body parameters are different among the individuals, it is assumed that these parameters are not known exactly and are uncertain. An adaptive controller based on the inverse dynamics in addition to parameter adaptation law has been designed. The simulation of the system using this controller shows the effectiveness of the proposed method in controlling the human posture.
{"title":"Adaptive control of human posture in a specific movement","authors":"S. Haghpanah, Fatemeh Haghpanah","doi":"10.1109/KBEI.2015.7436091","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436091","url":null,"abstract":"Human posture control is a complex issue in biomechanics. Human body is unstable without any controller. The stabilization of the body is achieved by the activation of the muscles and creating the joint torques. In this paper, human body in upright standing position has been modeled using an inverted double pendulum. Since the body parameters are different among the individuals, it is assumed that these parameters are not known exactly and are uncertain. An adaptive controller based on the inverse dynamics in addition to parameter adaptation law has been designed. The simulation of the system using this controller shows the effectiveness of the proposed method in controlling the human posture.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122852277","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}
Ant Colony Optimization (ACO) is a nature inspired meta-heuristic algorithms, which can be applied to a wide range of optimization problems. In this paper we present a modified method for edge detection based on the Ant Colony Optimization. Because of disadvantages of traditional edge detection methods, ACO as a relatively new meta-heuristic approach has been used to solve the edge detection problem. The performance of proposed method is compared with traditional ant colony methods, also we have large number of experiments to find out the suitable threshold for proposed method. The experimental results clearly indicate how the ACO can extracts edges in efficient way, also we speed up the proposed method by modifying the effective parameters in speed of the problem and replacing them by optimized values. The results show that this method is faster and more efficient than other former Ant Colony-based edge detection methods.
{"title":"A modified ant colony based approach to digital image edge detection","authors":"Aydin Ayanzadeh, Hossein Pourghaemi, Yousef Seyfari","doi":"10.1109/KBEI.2015.7436096","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436096","url":null,"abstract":"Ant Colony Optimization (ACO) is a nature inspired meta-heuristic algorithms, which can be applied to a wide range of optimization problems. In this paper we present a modified method for edge detection based on the Ant Colony Optimization. Because of disadvantages of traditional edge detection methods, ACO as a relatively new meta-heuristic approach has been used to solve the edge detection problem. The performance of proposed method is compared with traditional ant colony methods, also we have large number of experiments to find out the suitable threshold for proposed method. The experimental results clearly indicate how the ACO can extracts edges in efficient way, also we speed up the proposed method by modifying the effective parameters in speed of the problem and replacing them by optimized values. The results show that this method is faster and more efficient than other former Ant Colony-based edge detection methods.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117339687","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 : 2015-11-01DOI: 10.1109/KBEI.2015.7436101
S. Mahmoudi, M. Menhaj
Microarray technology in the last decade has been widely applied to detect correlated biomarkers in biological processes. Due to the need for analyzing massive amounts of generated data in this technology, computational intelligence approaches are used increasingly in this field. Biclustering algorithms are one of the most important of these techniques in microarray analysis. Two aspects of search mechanisms and biologists' desired patterns are the most essential issues in the design and evaluation of these algorithms. Different patterns can be achieved by considering different metrics. In this paper, Transposed Virtual Error (VET) is used as main metric. Also a hybrid evolutionary algorithm is proposed based on Evo-Bexpa algorithm which is introduced with VET. The proposed method is developed based on Genetic Algorithm (GA) used in Evo-Bexpa and Asexual Reproduction Optimization (ARO). The results indicate that underlying algorithm against Evo-Bexpa is more efficient in finding biclusters.
{"title":"A new hybrid evolutionary biclustring algorithm based on transposed virtual error","authors":"S. Mahmoudi, M. Menhaj","doi":"10.1109/KBEI.2015.7436101","DOIUrl":"https://doi.org/10.1109/KBEI.2015.7436101","url":null,"abstract":"Microarray technology in the last decade has been widely applied to detect correlated biomarkers in biological processes. Due to the need for analyzing massive amounts of generated data in this technology, computational intelligence approaches are used increasingly in this field. Biclustering algorithms are one of the most important of these techniques in microarray analysis. Two aspects of search mechanisms and biologists' desired patterns are the most essential issues in the design and evaluation of these algorithms. Different patterns can be achieved by considering different metrics. In this paper, Transposed Virtual Error (VET) is used as main metric. Also a hybrid evolutionary algorithm is proposed based on Evo-Bexpa algorithm which is introduced with VET. The proposed method is developed based on Genetic Algorithm (GA) used in Evo-Bexpa and Asexual Reproduction Optimization (ARO). The results indicate that underlying algorithm against Evo-Bexpa is more efficient in finding biclusters.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132331787","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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