Pub Date : 2017-08-01DOI: 10.1109/IC3.2017.8284348
S. Pandey, Nikita Jain, Aditi Bhardwaj, Gagandeep Kaur, Vimal Kumar
Firstly, women safety is utmost concern in India. The efforts are always being done to look out for solutions in this regard. In the recent years GPS and android enabled mobile phones have become a tool of study for providing ‘women safety’ apps. Secondly, there is growing demand in the industry for entrepreneurship. Therefore, Reach 360-an app for women safety has been developed by girl students of the institute to meet both the objectives.
{"title":"Reach360: A comprehensive safety solution","authors":"S. Pandey, Nikita Jain, Aditi Bhardwaj, Gagandeep Kaur, Vimal Kumar","doi":"10.1109/IC3.2017.8284348","DOIUrl":"https://doi.org/10.1109/IC3.2017.8284348","url":null,"abstract":"Firstly, women safety is utmost concern in India. The efforts are always being done to look out for solutions in this regard. In the recent years GPS and android enabled mobile phones have become a tool of study for providing ‘women safety’ apps. Secondly, there is growing demand in the industry for entrepreneurship. Therefore, Reach 360-an app for women safety has been developed by girl students of the institute to meet both the objectives.","PeriodicalId":147099,"journal":{"name":"2017 Tenth International Conference on Contemporary Computing (IC3)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129802050","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 : 2017-08-01DOI: 10.1109/IC3.2017.8284357
A. Pal, Prateek Parhi, M. Aggarwal
Recommender system comprises of two prime methods which help in providing meaningful recommendations namely, Collaborative Filtering algorithm and Content-Based Filtering. In this paper, we have used a hybrid methodology which takes advantage of both Content and Collaborative filtering algorithm into account. The algorithm discussed in this article is different from the previous work in this field as it includes a novel method to find the similar content between two items. The paper incorporates an analysis that justifies this new methodology and how it can provide practical recommendations. The above approach is tested on existing user and objects data and produced improved results when compared with other two favourite methods, Pure Collaborative Filtering, and Singular Value Decomposition.
{"title":"An improved content based collaborative filtering algorithm for movie recommendations","authors":"A. Pal, Prateek Parhi, M. Aggarwal","doi":"10.1109/IC3.2017.8284357","DOIUrl":"https://doi.org/10.1109/IC3.2017.8284357","url":null,"abstract":"Recommender system comprises of two prime methods which help in providing meaningful recommendations namely, Collaborative Filtering algorithm and Content-Based Filtering. In this paper, we have used a hybrid methodology which takes advantage of both Content and Collaborative filtering algorithm into account. The algorithm discussed in this article is different from the previous work in this field as it includes a novel method to find the similar content between two items. The paper incorporates an analysis that justifies this new methodology and how it can provide practical recommendations. The above approach is tested on existing user and objects data and produced improved results when compared with other two favourite methods, Pure Collaborative Filtering, and Singular Value Decomposition.","PeriodicalId":147099,"journal":{"name":"2017 Tenth International Conference on Contemporary Computing (IC3)","volume":"14 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128909732","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 : 2017-08-01DOI: 10.1109/IC3.2017.8284341
D. Sharma, Anurag Singh, A. Khanna, Anubhav Jain
Genetic Algorithm is a promising optimization technique for solving the problem of Channel Allocation in Cognitive Radio Networks(CRNs). This work involves exploration of various parameters and techniques used in Genetic Algorithm(GA). The selection of parameters and techniques influence the run-time and ability of genetic algorithm to arrive at a globally optimal solution. Therefore, this paper validates various crossover and mutation techniques to be fit/unfit for use and their effect on convergence of genetic algorithm for optimum channel allocation strategy. Extended version of current genetic algorithm for channel allocation using partial mapped crossover(PMX) is proposed. The simulation results show that PMX crossover is a robust method for dealing with the interference problem encountered in the extended version of the genetic algorithm.
{"title":"Evaluation of parameters and techniques for genetic algorithm based channel allocation in Cognitive Radio Networks","authors":"D. Sharma, Anurag Singh, A. Khanna, Anubhav Jain","doi":"10.1109/IC3.2017.8284341","DOIUrl":"https://doi.org/10.1109/IC3.2017.8284341","url":null,"abstract":"Genetic Algorithm is a promising optimization technique for solving the problem of Channel Allocation in Cognitive Radio Networks(CRNs). This work involves exploration of various parameters and techniques used in Genetic Algorithm(GA). The selection of parameters and techniques influence the run-time and ability of genetic algorithm to arrive at a globally optimal solution. Therefore, this paper validates various crossover and mutation techniques to be fit/unfit for use and their effect on convergence of genetic algorithm for optimum channel allocation strategy. Extended version of current genetic algorithm for channel allocation using partial mapped crossover(PMX) is proposed. The simulation results show that PMX crossover is a robust method for dealing with the interference problem encountered in the extended version of the genetic algorithm.","PeriodicalId":147099,"journal":{"name":"2017 Tenth International Conference on Contemporary Computing (IC3)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117320902","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 : 2017-08-01DOI: 10.1109/IC3.2017.8284304
R. Niyogi, M. Misra, Tarun Kulshrestha, Dhaval Patel
Smart environment at holy places integrates various intelligent devices, infrastructures, and services to monitor and control pilgrims' activities with efficiency. Smart pilgrim management requires aggregation of surrounding informatics for sustainable development of pilgrimage tourism. Some conventional sensing techniques, such as sensor networks are used to gather real time data. The management of large congregation is a primary factor in ensuring human's safety. In this paper, we investigate how sensor, mobile, and cloud technologies can be coupled together to address the pilgrim's safety, especially sensing, storing and analyzing the enormous number of pilgrims' whereabouts information in the smart environment. The existing solutions require a tag to track pilgrim. These tags need expensive sensors to detect them which results in high infrastructure cost. We develop a portable sensing system, named Smart Pilgrim, which uses pilgrims' smartphone whenever possible instead of tags. For sensing pilgrims' smartphones, we develop a sensing unit consisting of an Android based smartphone and an external Wi-Fi adapter. An extensive set of experiments is performed to evaluate the proposed system. The system developed is cost efficient, and will be helpful in congregation management.
{"title":"Smart pilgrim: A mobile-sensor-cloud based system to safeguard pilgrims through smart environment","authors":"R. Niyogi, M. Misra, Tarun Kulshrestha, Dhaval Patel","doi":"10.1109/IC3.2017.8284304","DOIUrl":"https://doi.org/10.1109/IC3.2017.8284304","url":null,"abstract":"Smart environment at holy places integrates various intelligent devices, infrastructures, and services to monitor and control pilgrims' activities with efficiency. Smart pilgrim management requires aggregation of surrounding informatics for sustainable development of pilgrimage tourism. Some conventional sensing techniques, such as sensor networks are used to gather real time data. The management of large congregation is a primary factor in ensuring human's safety. In this paper, we investigate how sensor, mobile, and cloud technologies can be coupled together to address the pilgrim's safety, especially sensing, storing and analyzing the enormous number of pilgrims' whereabouts information in the smart environment. The existing solutions require a tag to track pilgrim. These tags need expensive sensors to detect them which results in high infrastructure cost. We develop a portable sensing system, named Smart Pilgrim, which uses pilgrims' smartphone whenever possible instead of tags. For sensing pilgrims' smartphones, we develop a sensing unit consisting of an Android based smartphone and an external Wi-Fi adapter. An extensive set of experiments is performed to evaluate the proposed system. The system developed is cost efficient, and will be helpful in congregation management.","PeriodicalId":147099,"journal":{"name":"2017 Tenth International Conference on Contemporary Computing (IC3)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124604145","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 : 2017-08-01DOI: 10.1109/IC3.2017.8284342
D. Sharma, Aayush, Abhishek Sharma, J. Kumar
Opportunistic Networks (OppNets) are an extension of Mobile Adhoc Networks (MANETs), where no assumption is made regarding the preexistent path between the source and the destination node. Hence, the nodes in OppNets are required to rely upon intermediate nodes for successful message delivery. Therefore, the biggest challenge in OppNets for a carrier node is to make a decision whether the neighbour node will be a good carrier for the message in the future or not. Hence, in this paper a new routing protocol called K-Nearest Neighbour based Routing protocol (KNNR) is proposed which judicially forwards the message through intermediate nodes towards the destination. The proposed protocol initially stores the past behaviour of nodes in a dataset. Whenever a decision has to be made related to an intermediate node, the protocol studies this dataset and finds instances that closely resemble the intermediate node based on their network parameters using K-Nearest Neighhbour (KNN) algorithm. To evaluate the efficiency of the proposed protocol simulation results are compared with the existing routing protocols i.e. Epidemic, HBPR and ProPHET. It was observed that the KNNR protocol efficiently reduces average latency, overhead ratio and average hop count while at the same time increases the message delivery probability.
{"title":"KNNR:K-nearest neighbour classification based routing protocol for opportunistic networks","authors":"D. Sharma, Aayush, Abhishek Sharma, J. Kumar","doi":"10.1109/IC3.2017.8284342","DOIUrl":"https://doi.org/10.1109/IC3.2017.8284342","url":null,"abstract":"Opportunistic Networks (OppNets) are an extension of Mobile Adhoc Networks (MANETs), where no assumption is made regarding the preexistent path between the source and the destination node. Hence, the nodes in OppNets are required to rely upon intermediate nodes for successful message delivery. Therefore, the biggest challenge in OppNets for a carrier node is to make a decision whether the neighbour node will be a good carrier for the message in the future or not. Hence, in this paper a new routing protocol called K-Nearest Neighbour based Routing protocol (KNNR) is proposed which judicially forwards the message through intermediate nodes towards the destination. The proposed protocol initially stores the past behaviour of nodes in a dataset. Whenever a decision has to be made related to an intermediate node, the protocol studies this dataset and finds instances that closely resemble the intermediate node based on their network parameters using K-Nearest Neighhbour (KNN) algorithm. To evaluate the efficiency of the proposed protocol simulation results are compared with the existing routing protocols i.e. Epidemic, HBPR and ProPHET. It was observed that the KNNR protocol efficiently reduces average latency, overhead ratio and average hop count while at the same time increases the message delivery probability.","PeriodicalId":147099,"journal":{"name":"2017 Tenth International Conference on Contemporary Computing (IC3)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117105604","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 : 2017-08-01DOI: 10.1109/IC3.2017.8284292
Fernando A. Pitters-Figueroa, C. Travieso-González, M. Dutta, Anushikha Singh
The present work presents a biometric identifier system using the combination of two different features: hands shape (finger lengths and width) and hand-written signature contour. Signature database contains 300 different signers with 24 signatures and the hand database has 144 owners with 10 images. The study covers three different classifiers: Hidden Markov Models (HMM), Support Vector Machines (SVM) and a combination of both using the Fisher Kernel. Systems are evaluated separately and in conjunction, giving in each case 100% of identification success rate for the combined classifier. The combination of features gives better results when reducing the training set than the independent systems.
{"title":"Biometric identifier based on hand and hand-written signature contour information","authors":"Fernando A. Pitters-Figueroa, C. Travieso-González, M. Dutta, Anushikha Singh","doi":"10.1109/IC3.2017.8284292","DOIUrl":"https://doi.org/10.1109/IC3.2017.8284292","url":null,"abstract":"The present work presents a biometric identifier system using the combination of two different features: hands shape (finger lengths and width) and hand-written signature contour. Signature database contains 300 different signers with 24 signatures and the hand database has 144 owners with 10 images. The study covers three different classifiers: Hidden Markov Models (HMM), Support Vector Machines (SVM) and a combination of both using the Fisher Kernel. Systems are evaluated separately and in conjunction, giving in each case 100% of identification success rate for the combined classifier. The combination of features gives better results when reducing the training set than the independent systems.","PeriodicalId":147099,"journal":{"name":"2017 Tenth International Conference on Contemporary Computing (IC3)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131955405","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 : 2017-08-01DOI: 10.1109/IC3.2017.8284291
Abhisek Paul, Prantik Biswas, P. Bhattacharya, S. Maity
In this paper, we propose a power logarithm based plateau limit histogram equalization algorithm to enhance infrared images. Conventional histogram equalization methods lag significantly while enhancing infrared images whose histogram contains large spikes. To diminish the effects of large spikes log transformation is used which additionally aids in the expansion of the smaller values in the histogram. Power transformation assists in regaining the original shape of the histogram while clipping of histogram in a plateau limit is beneficial to reduce the over enhancement of the image. Plateau limit is set to the mean of modified histogram after the power-log transformation. After that, the modified histogram is equalized independently to achieve the enhanced output. Experimental results demonstrate that the proposed power-log based plateau limit histogram equalization algorithm efficiently enhances the contrast of infrared images while, quantitative measures and visual quality assessment effectively validate the superiority of the proposed algorithm with respect to the other traditional histogram equalization algorithms.
{"title":"Power-log based plateau limit histogram equalization algorithm for infrared image enhancement","authors":"Abhisek Paul, Prantik Biswas, P. Bhattacharya, S. Maity","doi":"10.1109/IC3.2017.8284291","DOIUrl":"https://doi.org/10.1109/IC3.2017.8284291","url":null,"abstract":"In this paper, we propose a power logarithm based plateau limit histogram equalization algorithm to enhance infrared images. Conventional histogram equalization methods lag significantly while enhancing infrared images whose histogram contains large spikes. To diminish the effects of large spikes log transformation is used which additionally aids in the expansion of the smaller values in the histogram. Power transformation assists in regaining the original shape of the histogram while clipping of histogram in a plateau limit is beneficial to reduce the over enhancement of the image. Plateau limit is set to the mean of modified histogram after the power-log transformation. After that, the modified histogram is equalized independently to achieve the enhanced output. Experimental results demonstrate that the proposed power-log based plateau limit histogram equalization algorithm efficiently enhances the contrast of infrared images while, quantitative measures and visual quality assessment effectively validate the superiority of the proposed algorithm with respect to the other traditional histogram equalization algorithms.","PeriodicalId":147099,"journal":{"name":"2017 Tenth International Conference on Contemporary Computing (IC3)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128460429","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 : 2017-08-01DOI: 10.1109/IC3.2017.8284335
Parmjit Singh, R. Chandel, N. Sharma
In modern technologies, read stability and write ability have become major concerns in nano regime for static random access memory (SRAM) cell. This paper provides the stability analysis of 6T-SRAM cell using the N-curve method. Various performance parameters namely SVNM, SINM, WTV, and WTI are evaluated for SRAM. Variation of SVNM, SINM, WTV and WTI with scaled supply voltage has been presented. A comparative analysis of CNTFET and GNRFET with conventional CMOS technology using HSPICE tool has been performed. To ensure a fair comparison of (19,0) CNTFET(DCNT=1.49nm) and (13,0) GNRFET(width=1.49nm) dimensions have been chosen for proper circuit size integration. The simulation results show that the SRAM cells designed using CNT and GNR field effect transistors (FETs) have better stability as compared to CMOS technology.
{"title":"Stability analysis of SRAM cell using CNT and GNR field effect transistors","authors":"Parmjit Singh, R. Chandel, N. Sharma","doi":"10.1109/IC3.2017.8284335","DOIUrl":"https://doi.org/10.1109/IC3.2017.8284335","url":null,"abstract":"In modern technologies, read stability and write ability have become major concerns in nano regime for static random access memory (SRAM) cell. This paper provides the stability analysis of 6T-SRAM cell using the N-curve method. Various performance parameters namely SVNM, SINM, WTV, and WTI are evaluated for SRAM. Variation of SVNM, SINM, WTV and WTI with scaled supply voltage has been presented. A comparative analysis of CNTFET and GNRFET with conventional CMOS technology using HSPICE tool has been performed. To ensure a fair comparison of (19,0) CNTFET(DCNT=1.49nm) and (13,0) GNRFET(width=1.49nm) dimensions have been chosen for proper circuit size integration. The simulation results show that the SRAM cells designed using CNT and GNR field effect transistors (FETs) have better stability as compared to CMOS technology.","PeriodicalId":147099,"journal":{"name":"2017 Tenth International Conference on Contemporary Computing (IC3)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131248054","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 : 2017-08-01DOI: 10.1109/IC3.2017.8284285
A. Pandey, D. Rajpoot, M. Saraswat
Cuckoo Search is a metaheuristic optimization method which uses obligate brood parasitic conduct of cuckoos. Successive moves (steps) of a cuckoo are basically drawn from a process which uses biased random walk and follows power law step-length distribution with a heavy tail. Therefore, quick convergence and precision cannot be assured in most of the cases. To resolve the convergence and accuracy problem this paper proposes a novel cuckoo search method which uses Lévy flight and Gauss distribution in alternate iteration along with variable Pa and a. The experimental outcomes validate that the proposed method outperforms the existing methods.
{"title":"Hybrid step size based cuckoo search","authors":"A. Pandey, D. Rajpoot, M. Saraswat","doi":"10.1109/IC3.2017.8284285","DOIUrl":"https://doi.org/10.1109/IC3.2017.8284285","url":null,"abstract":"Cuckoo Search is a metaheuristic optimization method which uses obligate brood parasitic conduct of cuckoos. Successive moves (steps) of a cuckoo are basically drawn from a process which uses biased random walk and follows power law step-length distribution with a heavy tail. Therefore, quick convergence and precision cannot be assured in most of the cases. To resolve the convergence and accuracy problem this paper proposes a novel cuckoo search method which uses Lévy flight and Gauss distribution in alternate iteration along with variable Pa and a. The experimental outcomes validate that the proposed method outperforms the existing methods.","PeriodicalId":147099,"journal":{"name":"2017 Tenth International Conference on Contemporary Computing (IC3)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114654520","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 : 2017-08-01DOI: 10.1109/IC3.2017.8284333
Avadh Kishor, R. Niyogi
In this paper, we suggest a game-theoretic approach to alleviate the free-rider problem. In this approach, we model the free-rider problem as a constrained single objective optimization problem. We formally prove that in our proposed model, the free-rider problem can be solved completely. Moreover, we validate our proposed model using a meta heuristic algorithm — artificial bee colony (ABC) algorithm. To ensure the constraint is satisfied, we perform the experimental study using ABC algorithm. The experimental results are consistent with those obtained theoretically.
{"title":"A game-theoretic approach to solve the free-rider problem","authors":"Avadh Kishor, R. Niyogi","doi":"10.1109/IC3.2017.8284333","DOIUrl":"https://doi.org/10.1109/IC3.2017.8284333","url":null,"abstract":"In this paper, we suggest a game-theoretic approach to alleviate the free-rider problem. In this approach, we model the free-rider problem as a constrained single objective optimization problem. We formally prove that in our proposed model, the free-rider problem can be solved completely. Moreover, we validate our proposed model using a meta heuristic algorithm — artificial bee colony (ABC) algorithm. To ensure the constraint is satisfied, we perform the experimental study using ABC algorithm. The experimental results are consistent with those obtained theoretically.","PeriodicalId":147099,"journal":{"name":"2017 Tenth International Conference on Contemporary Computing (IC3)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124337401","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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