Pub Date : 2019-03-15DOI: 10.1109/ICACCS.2019.8728355
B. Priya, R. Sri, Amulya Nimmagadda, Krishnai Garudkar
Cloud computing has been a significant breakthrough technology in large scale data storage and computation over a decade. However, due to advancement in mobile devices along with other technologies such as Internet of Things (IOT), Augmented Reality (AR), there is a need for real-time responses and reduce delays generated over WAN. Thus concepts of Edge computing such as Fog computing and Mobile Edge computing has evolved in order to bridge a gap between cloud and the consumer devices. This paper gives an overview of MEC in 5G, a brief comparison with Fog Computing and about various aspects and deployment scenarios.
{"title":"Mobile Edge Communication An overview of MEC in 5G","authors":"B. Priya, R. Sri, Amulya Nimmagadda, Krishnai Garudkar","doi":"10.1109/ICACCS.2019.8728355","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728355","url":null,"abstract":"Cloud computing has been a significant breakthrough technology in large scale data storage and computation over a decade. However, due to advancement in mobile devices along with other technologies such as Internet of Things (IOT), Augmented Reality (AR), there is a need for real-time responses and reduce delays generated over WAN. Thus concepts of Edge computing such as Fog computing and Mobile Edge computing has evolved in order to bridge a gap between cloud and the consumer devices. This paper gives an overview of MEC in 5G, a brief comparison with Fog Computing and about various aspects and deployment scenarios.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"223 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115182871","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 : 2019-03-15DOI: 10.1109/ICACCS.2019.8728356
Srushti Patil, Sudhir Dhage
Phishing is a security attack to acquire personal information like passwords, credit card details or other account details of a user by means of websites or emails. Phishing websites look similar to the legitimate ones which make it difficult for a layman to differentiate between them. As per the reports of Anti Phishing Working Group (APWG) published in December 2018, phishing against banking services and payment processor was high. Almost all the phishy URLs use HTTPS and use redirects to avoid getting detected. This paper presents a focused literature survey of methods available to detect phishing websites. A comparative study of the in-use anti-phishing tools was accomplished and their limitations were acknowledged. We analyzed the URL-based features used in the past to improve their definitions as per the current scenario which is our major contribution. Also, a step wise procedure of designing an anti-phishing model is discussed to construct an efficient framework which adds to our contribution. Observations made out of this study are stated along with recommendations on existing systems.
{"title":"A Methodical Overview on Phishing Detection along with an Organized Way to Construct an Anti-Phishing Framework","authors":"Srushti Patil, Sudhir Dhage","doi":"10.1109/ICACCS.2019.8728356","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728356","url":null,"abstract":"Phishing is a security attack to acquire personal information like passwords, credit card details or other account details of a user by means of websites or emails. Phishing websites look similar to the legitimate ones which make it difficult for a layman to differentiate between them. As per the reports of Anti Phishing Working Group (APWG) published in December 2018, phishing against banking services and payment processor was high. Almost all the phishy URLs use HTTPS and use redirects to avoid getting detected. This paper presents a focused literature survey of methods available to detect phishing websites. A comparative study of the in-use anti-phishing tools was accomplished and their limitations were acknowledged. We analyzed the URL-based features used in the past to improve their definitions as per the current scenario which is our major contribution. Also, a step wise procedure of designing an anti-phishing model is discussed to construct an efficient framework which adds to our contribution. Observations made out of this study are stated along with recommendations on existing systems.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115010057","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 : 2019-03-15DOI: 10.1109/ICACCS.2019.8728364
H. J. Patel, V. Dabhi, H. Prajapati
River water is one of the essential components for the ecological environment, which plays a main role in human survival and socioeconomic development. The quality of river water is essential because river water is generally used for multiple purposes such as for drinking, agriculture, hydroelectric power plants, etc. Therefore, it is necessary to identify the water pollution regions of river. Researchers have attempted an analysis of river water using high-resolution satellite images and machine learning concepts. This paper presents a survey of solutions that use various image processing tasks and machine learning concepts to detect pollution in river water. In this survey, we carried out a useful analysis of various satellite sensors, image processing techniques, and classifiers used for classification of river water.
{"title":"River Water Pollution Analysis using High Resolution Satellite Images : A Survey","authors":"H. J. Patel, V. Dabhi, H. Prajapati","doi":"10.1109/ICACCS.2019.8728364","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728364","url":null,"abstract":"River water is one of the essential components for the ecological environment, which plays a main role in human survival and socioeconomic development. The quality of river water is essential because river water is generally used for multiple purposes such as for drinking, agriculture, hydroelectric power plants, etc. Therefore, it is necessary to identify the water pollution regions of river. Researchers have attempted an analysis of river water using high-resolution satellite images and machine learning concepts. This paper presents a survey of solutions that use various image processing tasks and machine learning concepts to detect pollution in river water. In this survey, we carried out a useful analysis of various satellite sensors, image processing techniques, and classifiers used for classification of river water.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124728994","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 : 2019-03-15DOI: 10.1109/ICACCS.2019.8728518
Nitesh Funde, Parnika N. Paranjape, K. Ram, Punit Magde, Meera M. Dhabu
Object detection and tracking are the most challenging part of any computer vision applications. In computer vision, video surveillance is a popular research area in a dynamic environment, particularly for security reasons. The video surveillance technology plays a crucial role to prevent crime, terrorism etc. The video outputs are filtered and processed by human operators and in case of a forensic, the high volume of data made it difficult to track any object. This work has been done with an aim to reduce the effort of human operators with an increase in the response time to forensic events. It involves designing of an efficient object tracking system for simple environments where the camera is static, background is simple and no similar object to the one being tracked is present. The system is provided with network configuration of the cameras and roads of the surveillance area, videodumps and an image of the object to be tracked. It tracks the objects through the videos and dumps the tracked portions of the videos where the object was present.
{"title":"Object Detection and Tracking Approaches for Video Surveillance Over Camera Network","authors":"Nitesh Funde, Parnika N. Paranjape, K. Ram, Punit Magde, Meera M. Dhabu","doi":"10.1109/ICACCS.2019.8728518","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728518","url":null,"abstract":"Object detection and tracking are the most challenging part of any computer vision applications. In computer vision, video surveillance is a popular research area in a dynamic environment, particularly for security reasons. The video surveillance technology plays a crucial role to prevent crime, terrorism etc. The video outputs are filtered and processed by human operators and in case of a forensic, the high volume of data made it difficult to track any object. This work has been done with an aim to reduce the effort of human operators with an increase in the response time to forensic events. It involves designing of an efficient object tracking system for simple environments where the camera is static, background is simple and no similar object to the one being tracked is present. The system is provided with network configuration of the cameras and roads of the surveillance area, videodumps and an image of the object to be tracked. It tracks the objects through the videos and dumps the tracked portions of the videos where the object was present.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"61 5part2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113978652","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 : 2019-03-15DOI: 10.1109/ICACCS.2019.8728544
S. Akarsh, S. Sriram, P. Poornachandran, V. Menon, K. Soman
Real-time prediction of domain names that are generated using the Domain Generation Algorithms (DGAs) is a challenging cyber security task. Scope to collect the vast amount of data for training favored data-driven techniques and deep learning architectures have the potential to address this challenge. This paper proposes a deep learning framework using long short-term memory (LSTM) architecture for prediction of the domain names that are generated using the DGAs. Binary classification had benign and DGA domain names and multiclass classification was performed using 20 different DGAs. For the binary classification, LSTM model gave accuracy of 98.7% and 71.3% on two different test data sets and for the multi-class classification, it gave accuracy of 68.3% and 67.0% respectively. Two diversified data sets were used to analyze the robustness of the LSTM architecture.
{"title":"Deep Learning Framework for Domain Generation Algorithms Prediction Using Long Short-term Memory","authors":"S. Akarsh, S. Sriram, P. Poornachandran, V. Menon, K. Soman","doi":"10.1109/ICACCS.2019.8728544","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728544","url":null,"abstract":"Real-time prediction of domain names that are generated using the Domain Generation Algorithms (DGAs) is a challenging cyber security task. Scope to collect the vast amount of data for training favored data-driven techniques and deep learning architectures have the potential to address this challenge. This paper proposes a deep learning framework using long short-term memory (LSTM) architecture for prediction of the domain names that are generated using the DGAs. Binary classification had benign and DGA domain names and multiclass classification was performed using 20 different DGAs. For the binary classification, LSTM model gave accuracy of 98.7% and 71.3% on two different test data sets and for the multi-class classification, it gave accuracy of 68.3% and 67.0% respectively. Two diversified data sets were used to analyze the robustness of the LSTM architecture.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130190689","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 : 2019-03-15DOI: 10.1109/ICACCS.2019.8728482
Pavithran P G, A. K, N. P. Guhan Seshadri, Bikesh Kumar Singh, V. Mahesh, B. Geethanjali
Dyslexia is a neurodevelopmental disorder that is characterized by deficits in both phonological and in visual spatial processing. In this study, a visual selective attention task was employed to ten dyslexic’s participants and the brain activation was measured using electroencephalograph (EEG). The mean relative power of the alpha and theta band was computed to calculate theta/alpha ratio. The theta / alpha was significantly higher (p<0.05) during task at temporal lobe and occipital lobe electrode locations than during rest. Parameters including target detection rate as a performance measure was calculated and found to be 59.4±32.4% which is a testimony of their poor performance in orienting and sustaining the visual attention. These cumulatively corroborated the positive correlation between increased theta/alpha ratio in dyslexics during task and their associated deficits in successfully orienting their attention towards the spatially presented target stimuli.
{"title":"Index of Theta/Alpha ratio to quantify visual - spatial attention in dyslexics using Electroencephalogram","authors":"Pavithran P G, A. K, N. P. Guhan Seshadri, Bikesh Kumar Singh, V. Mahesh, B. Geethanjali","doi":"10.1109/ICACCS.2019.8728482","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728482","url":null,"abstract":"Dyslexia is a neurodevelopmental disorder that is characterized by deficits in both phonological and in visual spatial processing. In this study, a visual selective attention task was employed to ten dyslexic’s participants and the brain activation was measured using electroencephalograph (EEG). The mean relative power of the alpha and theta band was computed to calculate theta/alpha ratio. The theta / alpha was significantly higher (p<0.05) during task at temporal lobe and occipital lobe electrode locations than during rest. Parameters including target detection rate as a performance measure was calculated and found to be 59.4±32.4% which is a testimony of their poor performance in orienting and sustaining the visual attention. These cumulatively corroborated the positive correlation between increased theta/alpha ratio in dyslexics during task and their associated deficits in successfully orienting their attention towards the spatially presented target stimuli.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130217906","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 : 2019-03-15DOI: 10.1109/ICACCS.2019.8728440
R. Narmadha, P. Perumal
The classification of the aspect and its category from the product and service reviews has become a primary concern for the consumer in decision making. Nowadays reviews becoming more valuable in making wise decisions. Many advanced approaches based on supervised method and unsupervised method models has helped to provide this objective in terms of summarization. The key challenges were propagating on sentence summarization and orientation. Due to unsatisfactory results, there exists an exploration for unsupervised learning model through utilization of the sentiment analysis for developing and idea in an effective way. In this paper, the detailed analysis is carried out on existing literature to identify aspects and aspect categories using unsupervised model. The aspect categories play a major role in providing useful information about the particular assumption of a certain idea. It essentially attains a useful representation of the reviews automatically and it identify the typical sentiment assigning of sentences. The aspect category is determined on basis of context co-occurrence frequency. In addition, lexical representation is carried out for each category. For analysis of each technique, the breakdowns and obtained performance are included.
{"title":"An Extensive Study On Automated Aspect And Aspect Category Summarization Technique To Influence On Sentimental Analysis Of Co-Occurrence Data","authors":"R. Narmadha, P. Perumal","doi":"10.1109/ICACCS.2019.8728440","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728440","url":null,"abstract":"The classification of the aspect and its category from the product and service reviews has become a primary concern for the consumer in decision making. Nowadays reviews becoming more valuable in making wise decisions. Many advanced approaches based on supervised method and unsupervised method models has helped to provide this objective in terms of summarization. The key challenges were propagating on sentence summarization and orientation. Due to unsatisfactory results, there exists an exploration for unsupervised learning model through utilization of the sentiment analysis for developing and idea in an effective way. In this paper, the detailed analysis is carried out on existing literature to identify aspects and aspect categories using unsupervised model. The aspect categories play a major role in providing useful information about the particular assumption of a certain idea. It essentially attains a useful representation of the reviews automatically and it identify the typical sentiment assigning of sentences. The aspect category is determined on basis of context co-occurrence frequency. In addition, lexical representation is carried out for each category. For analysis of each technique, the breakdowns and obtained performance are included.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124059134","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 : 2019-03-15DOI: 10.1109/ICACCS.2019.8728325
S. S, B. Raghavendra
Agriculture is a key source of livelihood. Agriculture provides employment opportunities for village people on large scale in developing country like India. India's agriculture is composed of many crops and according to survey nearly 70% population is depends on agriculture. Most of Indian farmers are adopting manual cultivation due to lagging of technical knowledge. Farmers are unaware of what kind of crops that grows well on their land. When plants are affected by heterogeneous diseases through their leaves that will effects on production of agriculture and profitable loss. Also reduction in both quality and amount of agricultural production. Leaves are important for fast growing of plant and to increase production of crops. Identifying diseases in plants leave is challenging for farmers also for researchers. Currently farmers are spraying pesticides to the plants but it effects human directly or indirectly by health or also economically. To detect these plant diseases many fast techniques need to be adopt. In this paper, we have done survey on different plants disease and various advance techniques to detect these diseases.
{"title":"Diseases Detection of Various Plant Leaf Using Image Processing Techniques: A Review","authors":"S. S, B. Raghavendra","doi":"10.1109/ICACCS.2019.8728325","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728325","url":null,"abstract":"Agriculture is a key source of livelihood. Agriculture provides employment opportunities for village people on large scale in developing country like India. India's agriculture is composed of many crops and according to survey nearly 70% population is depends on agriculture. Most of Indian farmers are adopting manual cultivation due to lagging of technical knowledge. Farmers are unaware of what kind of crops that grows well on their land. When plants are affected by heterogeneous diseases through their leaves that will effects on production of agriculture and profitable loss. Also reduction in both quality and amount of agricultural production. Leaves are important for fast growing of plant and to increase production of crops. Identifying diseases in plants leave is challenging for farmers also for researchers. Currently farmers are spraying pesticides to the plants but it effects human directly or indirectly by health or also economically. To detect these plant diseases many fast techniques need to be adopt. In this paper, we have done survey on different plants disease and various advance techniques to detect these diseases.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129011232","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 : 2019-03-15DOI: 10.1109/ICACCS.2019.8728514
K. Prasanti, Kalpana Seelam, C. Jayalakshmi, C. Savalam
Past decades onwards the forest property (sandalwood and teak trees) is victimizes within the kind of exporting. The objective of this paper is to prevent the exporting of forest property unauthorized and protect the nature. For the implementation pf this system PIR sensor, FSR sensor and Flex sensors network is required. These sensors are used to detect the signal where the unauthorized cuttings are takes place and this detected signal information carries through wireless communication to the concerned forest authorities to take preventive action.
{"title":"Preventive system for forests property using wireless communication","authors":"K. Prasanti, Kalpana Seelam, C. Jayalakshmi, C. Savalam","doi":"10.1109/ICACCS.2019.8728514","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728514","url":null,"abstract":"Past decades onwards the forest property (sandalwood and teak trees) is victimizes within the kind of exporting. The objective of this paper is to prevent the exporting of forest property unauthorized and protect the nature. For the implementation pf this system PIR sensor, FSR sensor and Flex sensors network is required. These sensors are used to detect the signal where the unauthorized cuttings are takes place and this detected signal information carries through wireless communication to the concerned forest authorities to take preventive action.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125938703","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 : 2019-03-15DOI: 10.1109/ICACCS.2019.8728344
P. Udupa, S. Nithyanandam
Software Testing is the process of rectifying and validating the system with the intent of finding and excluding the errors and it requires validating an attribute to see that whether it generates expected and demanded outputs. proposed technique used apfd, test case reduction, prioritization and test case rank to prolong performance and an algorithm is developed to optimize the overall testing efficiency and to lessen the execution time by decreasing number of test cases, and then performing prioritization and fault detection, and further prioritized parallelization is used to maximize performance.
{"title":"An Efficient Method for Testing Source Code by Using Test Case Reduction, Prioritization and Prioritized Parallelization","authors":"P. Udupa, S. Nithyanandam","doi":"10.1109/ICACCS.2019.8728344","DOIUrl":"https://doi.org/10.1109/ICACCS.2019.8728344","url":null,"abstract":"Software Testing is the process of rectifying and validating the system with the intent of finding and excluding the errors and it requires validating an attribute to see that whether it generates expected and demanded outputs. proposed technique used apfd, test case reduction, prioritization and test case rank to prolong performance and an algorithm is developed to optimize the overall testing efficiency and to lessen the execution time by decreasing number of test cases, and then performing prioritization and fault detection, and further prioritized parallelization is used to maximize performance.","PeriodicalId":249139,"journal":{"name":"2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS)","volume":"346 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124311948","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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