Big sensor data is huge amount of data in both industry and scientific research application in which it generate high quantity of data. Cloud computing provides a special platform to support this challenge as it provides a flexible massive data, storage, and different software services in a scalable manner at low cost. Different technique has been developing in recent years for processing sensor data on cloud, such as sensor-cloud. But, these techniques do not provide efficient support on fast detection and locating of errors in big sensor data. For faster error detection in big sensor data sets, in this system, it develop a novel data error detection approach which gives the full feature of cloud platform and the network feature of Wireless sensor network(WSN). Firstly, it classifies a set of sensor data error types and then defined it. Specifically, in proposed system, the error detection is based on the scale-free network topology and most of detection operations can be conducted in clustered form not a whole big data set.
{"title":"Errors Detection in Big Sensor Data on Cloud using Time Efficient Technique","authors":"J. Pansare, V. Bajad","doi":"10.1145/2909067.2909071","DOIUrl":"https://doi.org/10.1145/2909067.2909071","url":null,"abstract":"Big sensor data is huge amount of data in both industry and scientific research application in which it generate high quantity of data. Cloud computing provides a special platform to support this challenge as it provides a flexible massive data, storage, and different software services in a scalable manner at low cost. Different technique has been developing in recent years for processing sensor data on cloud, such as sensor-cloud. But, these techniques do not provide efficient support on fast detection and locating of errors in big sensor data. For faster error detection in big sensor data sets, in this system, it develop a novel data error detection approach which gives the full feature of cloud platform and the network feature of Wireless sensor network(WSN). Firstly, it classifies a set of sensor data error types and then defined it. Specifically, in proposed system, the error detection is based on the scale-free network topology and most of detection operations can be conducted in clustered form not a whole big data set.","PeriodicalId":371590,"journal":{"name":"Women In Research","volume":"349 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115847523","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}
Visualization is a term used in the wide area of research to visualize the things as per the human vision. Mostly these terms are used to optimize the data, file format, multimedia format to clarify the concept of human understanding and acceptance in easiest manner. To prove the research in this perspective standard term involved to maintain the quality of work is known as scientific. Scientific visualization emphasises that the research on visualization will be performed as deep learning. Image visualization is mostly used in the medical field for visualization of complex images as per human vision. Sometimes images are visualized as enjoyable, memorable, analysis or for understanding the depth behind the images. Deep learning facilitates visualization of images as per the human vision through inceptions of processed vector/pixels involved in a image. The main motive of visualized image through deep learning is to project an image more attractive as per human vision. Different scientific parameters of computations are involved to process the image as per the user interaction. These parameters sometimes create a dangerous form of image, attractive look of image; deform the image quality through counting inceptions. In this article we analyze the deep learning process in an image visualization to find out the actual parameter to achieve the desired quality of image as per human vision and compute the chaining inceptions to form a new image within the images as meta-images.
{"title":"Image Visualization as per the User Appeal through Deep Learning","authors":"Ankit Gandhi, Amarjeet Poonia","doi":"10.1145/2909067.2909081","DOIUrl":"https://doi.org/10.1145/2909067.2909081","url":null,"abstract":"Visualization is a term used in the wide area of research to visualize the things as per the human vision. Mostly these terms are used to optimize the data, file format, multimedia format to clarify the concept of human understanding and acceptance in easiest manner. To prove the research in this perspective standard term involved to maintain the quality of work is known as scientific. Scientific visualization emphasises that the research on visualization will be performed as deep learning. Image visualization is mostly used in the medical field for visualization of complex images as per human vision. Sometimes images are visualized as enjoyable, memorable, analysis or for understanding the depth behind the images. Deep learning facilitates visualization of images as per the human vision through inceptions of processed vector/pixels involved in a image. The main motive of visualized image through deep learning is to project an image more attractive as per human vision. Different scientific parameters of computations are involved to process the image as per the user interaction. These parameters sometimes create a dangerous form of image, attractive look of image; deform the image quality through counting inceptions. In this article we analyze the deep learning process in an image visualization to find out the actual parameter to achieve the desired quality of image as per human vision and compute the chaining inceptions to form a new image within the images as meta-images.","PeriodicalId":371590,"journal":{"name":"Women In Research","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133475203","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}
Vehicular Ad Hoc Network (VANET) is the special branch of the Mobile Ad Hoc Network. MANET has un-controlled moving patterns of a number of nodes where as VANET has restricted node movement by factors like a road course, traffic and traffic regulations because VANET is formed mainly by vehicles. VANET is the collection of information on moving vehicles throughout the period of communication. The Routing Protocols are intended to deliver several different service qualities like packet Delivery Ratio, Throughput, Jitter Rate, End to End Delay and Routing Overhead. In this paper, a study on various topology based routing protocols such as DSDV, AODV, DSR and AOMDV in VANET and we are exploiting routing protocols by varying the No. Of nodes and Constant bit rate and then comparing their performances with respect to throughput, end to end delay.
{"title":"Execution and Analysis of Topology Based Routing Protocols in VANET","authors":"Srishti, S. Yadav","doi":"10.1145/2909067.2909082","DOIUrl":"https://doi.org/10.1145/2909067.2909082","url":null,"abstract":"Vehicular Ad Hoc Network (VANET) is the special branch of the Mobile Ad Hoc Network. MANET has un-controlled moving patterns of a number of nodes where as VANET has restricted node movement by factors like a road course, traffic and traffic regulations because VANET is formed mainly by vehicles. VANET is the collection of information on moving vehicles throughout the period of communication. The Routing Protocols are intended to deliver several different service qualities like packet Delivery Ratio, Throughput, Jitter Rate, End to End Delay and Routing Overhead. In this paper, a study on various topology based routing protocols such as DSDV, AODV, DSR and AOMDV in VANET and we are exploiting routing protocols by varying the No. Of nodes and Constant bit rate and then comparing their performances with respect to throughput, end to end delay.","PeriodicalId":371590,"journal":{"name":"Women In Research","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114438618","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}
Nilakshi Jain, Priyanka Sharma, R. Anchan, Apoorva Bhosale, Pooja Anchan, D. Kalbande
Criminal activities are a manifestation of unseen termites that are slowly but steadily decaying the deep rooted pillars of ethics and values established in our society. The evolving technology can be very well be utilized as arms and ammunitions by the law agencies against this social evil of criminalization. In our paper, we propose a novel and unified approach to examine and investigate digital crimes as well as physical crimes. Our model works on the principle of integrating various computerized forensic tools to analyze the reported digital crime and adopts data mining techniques for detecting crime and predicting the criminal in the case of physical crimes. In the first phase the user registered in the system can file a valid case by entering the details of the crime occurred. Depending on the type of crime the case will be evaluated. For detecting and investigating intruder attacks launched on a user's system, a set of digital tools is used and the generated report is sent to the intended user. In the event of a physical crime, k-means clustering algorithm is used to generate crime clusters. Based on the crime location the clusters are diagrammatically represented on google maps. We have further incorporated the use of Naïve Bayes classification algorithm for predicting the criminals for a particular crime case based on similar crime activities that happened in the past. If no previous record is found then the new crime pattern is added to the existing crime dataset. Our computerized forensic model aids the victim to amicably cooperate with the law agencies and aims to accelerate the process of crime investigation in order to combat rapidly growing criminal activities.
{"title":"Computerized Forensic Approach Using Data Mining Techniques","authors":"Nilakshi Jain, Priyanka Sharma, R. Anchan, Apoorva Bhosale, Pooja Anchan, D. Kalbande","doi":"10.1145/2909067.2909076","DOIUrl":"https://doi.org/10.1145/2909067.2909076","url":null,"abstract":"Criminal activities are a manifestation of unseen termites that are slowly but steadily decaying the deep rooted pillars of ethics and values established in our society. The evolving technology can be very well be utilized as arms and ammunitions by the law agencies against this social evil of criminalization. In our paper, we propose a novel and unified approach to examine and investigate digital crimes as well as physical crimes. Our model works on the principle of integrating various computerized forensic tools to analyze the reported digital crime and adopts data mining techniques for detecting crime and predicting the criminal in the case of physical crimes. In the first phase the user registered in the system can file a valid case by entering the details of the crime occurred. Depending on the type of crime the case will be evaluated. For detecting and investigating intruder attacks launched on a user's system, a set of digital tools is used and the generated report is sent to the intended user. In the event of a physical crime, k-means clustering algorithm is used to generate crime clusters. Based on the crime location the clusters are diagrammatically represented on google maps. We have further incorporated the use of Naïve Bayes classification algorithm for predicting the criminals for a particular crime case based on similar crime activities that happened in the past. If no previous record is found then the new crime pattern is added to the existing crime dataset. Our computerized forensic model aids the victim to amicably cooperate with the law agencies and aims to accelerate the process of crime investigation in order to combat rapidly growing criminal activities.","PeriodicalId":371590,"journal":{"name":"Women In Research","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122388428","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}
Today's applications asking for finding spatial protests nearest to a predefined area in the meantime fulfill limitation of keywords. Best answer for such questions depends on the IR2-tree, which has some inadequacies that truly affect system s efficiency. To defeat those inadequacies another access strategy is produced called the Spatial-inverted Index (SI) that extends the modified file to adapt to multidimensional information, and accompanies calculations that can answer closest neighbor queries with keywords continuously. This new technique SI is produced broadens the capacities of routine modified record makes do with multidimensional information, alongside the arrangement of using so as to move reach queries replied SI results to calculation which tackles the issue continuously.
{"title":"Nearest Neighbor Search Technique Using Keywords and Threshold","authors":"P. Shejawal, J. Pansare","doi":"10.1145/2909067.2909070","DOIUrl":"https://doi.org/10.1145/2909067.2909070","url":null,"abstract":"Today's applications asking for finding spatial protests nearest to a predefined area in the meantime fulfill limitation of keywords. Best answer for such questions depends on the IR2-tree, which has some inadequacies that truly affect system s efficiency. To defeat those inadequacies another access strategy is produced called the Spatial-inverted Index (SI) that extends the modified file to adapt to multidimensional information, and accompanies calculations that can answer closest neighbor queries with keywords continuously. This new technique SI is produced broadens the capacities of routine modified record makes do with multidimensional information, alongside the arrangement of using so as to move reach queries replied SI results to calculation which tackles the issue continuously.","PeriodicalId":371590,"journal":{"name":"Women In Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124386141","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}
In this paper, we have mentioned a method to find the performance of projectwhich detects various web - attacks. The project is capable to identifying and preventing attacks like SQL Injection, Cross -- Site Scripting, URL rewriting, Web server 400 error code etc. The performance of system is detected using the system attributes that are mentioned in this paper. This is also used to determine efficiency of the system.
{"title":"System Attribute Measures of Network Security Analyzer","authors":"S. Pawar, Nilakshi Jain, Swati Deshpande","doi":"10.1145/2909067.2909099","DOIUrl":"https://doi.org/10.1145/2909067.2909099","url":null,"abstract":"In this paper, we have mentioned a method to find the performance of projectwhich detects various web - attacks. The project is capable to identifying and preventing attacks like SQL Injection, Cross -- Site Scripting, URL rewriting, Web server 400 error code etc. The performance of system is detected using the system attributes that are mentioned in this paper. This is also used to determine efficiency of the system.","PeriodicalId":371590,"journal":{"name":"Women In Research","volume":"10 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113964433","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}
With advent of Unicode encoding, Punjabi language content, written using gurmukhi script as well as in shahmukhi script, is increasing day by day on internet. Processing textual information involves passing it to various pre-processing phases. Stop-word elimination is one such sub phase. 256 Gurmukhi stop words had been identified from poetry, stories and online material and passed to Punjabi stemmer. After stemming, 184 stemmed stop words were generated and these stemmed stop words were passed to transliteration phase. This led to generation of stop words in shahmukhi script. For the first time in scientific community dealing with computational linguistics and literature processing using NLP techniques, the list of 184 stop words of Punjabi language is released for public usage and further NLP applications. The presented list consists of stop words of Punjabi language with their Gurmukhi, Shahmukhi as well as Roman scripted forms.
{"title":"Punjabi Stop Words: A Gurmukhi, Shahmukhi and Roman Scripted Chronicle","authors":"Jasleen Kaur, Jatinderkumar R. Saini","doi":"10.1145/2909067.2909073","DOIUrl":"https://doi.org/10.1145/2909067.2909073","url":null,"abstract":"With advent of Unicode encoding, Punjabi language content, written using gurmukhi script as well as in shahmukhi script, is increasing day by day on internet. Processing textual information involves passing it to various pre-processing phases. Stop-word elimination is one such sub phase. 256 Gurmukhi stop words had been identified from poetry, stories and online material and passed to Punjabi stemmer. After stemming, 184 stemmed stop words were generated and these stemmed stop words were passed to transliteration phase. This led to generation of stop words in shahmukhi script. For the first time in scientific community dealing with computational linguistics and literature processing using NLP techniques, the list of 184 stop words of Punjabi language is released for public usage and further NLP applications. The presented list consists of stop words of Punjabi language with their Gurmukhi, Shahmukhi as well as Roman scripted forms.","PeriodicalId":371590,"journal":{"name":"Women In Research","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124133683","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}
Association discovery finds closely correlate sets so the presence of some components in an exceedingly frequent set can imply the presence of the remaining components (in identical set). Closed item sets are a solution to the problems described above. These are obtained by partitioning the lattice of frequent item sets into equivalence classes according to the following property: two distinct item sets belong the same class if and only if they occur in the same set of transactions. Closed item sets are the collection of maximal item sets of these equivalence classes. This paper proposes a comprehensive survey of the closed item set mining. The concept of the frequent closed item set mining is also elaborated in detail. The modern methods of frequent closed item set mining are also discussed in brief.
{"title":"A Survey Paper on a Compact Data Structure Based Technique for Mining Frequent Closed Item Set","authors":"Kamlesh Ahuja, D. Mishra, Sarika Jain","doi":"10.1145/2909067.2909093","DOIUrl":"https://doi.org/10.1145/2909067.2909093","url":null,"abstract":"Association discovery finds closely correlate sets so the presence of some components in an exceedingly frequent set can imply the presence of the remaining components (in identical set). Closed item sets are a solution to the problems described above. These are obtained by partitioning the lattice of frequent item sets into equivalence classes according to the following property: two distinct item sets belong the same class if and only if they occur in the same set of transactions. Closed item sets are the collection of maximal item sets of these equivalence classes. This paper proposes a comprehensive survey of the closed item set mining. The concept of the frequent closed item set mining is also elaborated in detail. The modern methods of frequent closed item set mining are also discussed in brief.","PeriodicalId":371590,"journal":{"name":"Women In Research","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128205954","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}
Computer crime also popularly known as Cybercrime has escalated to such a huge extent that it is now posing a threat to various industries, educational universities and professional organizations as well. The law enforcement agencies, police departments and crime branch units have acknowledged the upsurge in digital crime cases and they have begun to deploy measures to curb this evil phenomenon. In this paper, we inspect about the awareness of digital crime among the general public and illustrate an overview of Cybercrime, with the motive of highlighting the necessity to restrain the impact of cybercrime all over the world. This paper examines the rise in number of cybercrimes in India and takes into consideration the analytical traits of the offenders who commit such crimes. The paper banks on the information obtained from different sects of our country. The experimentation results depict that the top four cyber crimes committed in the past few years such as Internet frauds, data theft, cyber piracy and crime sex were all spread across the internet. The output reveals that cyber crime not only encompasses the internet but it has already expanded across all communities worldwide. The soaring crime rate is a major concern as it is indicative of the huge amount of cyber crime cases enrolled in recent years. The objective of this paper is to provide some guidelines to cybercrime analysts, government organizations, and educational universities.
{"title":"Empirical relationship between Victim's occupation and their knowledge of Digital Forensic","authors":"Nilakshi Jain, D. Kalbande, Priyanka Sharma","doi":"10.1145/2909067.2909077","DOIUrl":"https://doi.org/10.1145/2909067.2909077","url":null,"abstract":"Computer crime also popularly known as Cybercrime has escalated to such a huge extent that it is now posing a threat to various industries, educational universities and professional organizations as well. The law enforcement agencies, police departments and crime branch units have acknowledged the upsurge in digital crime cases and they have begun to deploy measures to curb this evil phenomenon. In this paper, we inspect about the awareness of digital crime among the general public and illustrate an overview of Cybercrime, with the motive of highlighting the necessity to restrain the impact of cybercrime all over the world. This paper examines the rise in number of cybercrimes in India and takes into consideration the analytical traits of the offenders who commit such crimes. The paper banks on the information obtained from different sects of our country. The experimentation results depict that the top four cyber crimes committed in the past few years such as Internet frauds, data theft, cyber piracy and crime sex were all spread across the internet. The output reveals that cyber crime not only encompasses the internet but it has already expanded across all communities worldwide. The soaring crime rate is a major concern as it is indicative of the huge amount of cyber crime cases enrolled in recent years. The objective of this paper is to provide some guidelines to cybercrime analysts, government organizations, and educational universities.","PeriodicalId":371590,"journal":{"name":"Women In Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122053680","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}
Rajdeep Chowdhury, Jenifar Khan, Subham Sengupta, Saswata Dasgupta, S. Datta, Mallika De
Network Security has become imperative in the contemporary scenario and subsequently an assortment of modus operandi is being espoused to evade it. Network administrators need to adhere with latest advancement in both hardware and software field to prevent user data from malicious intrusions. The formulated paper outlines a cryptographic algorithm based on Time Integrated Seed modus operandi Engendering Elements at bay and focusing on Dynamic Referencing Data Warehouse employing the identical concept amid its functionality. An amalgamation would endow with a proficient and prearranged approach of amassing data with stringent security modus operandi, with effective deployment of all obtainable space. The incorporation of the novel cryptographic algorithm with the Dynamic Referencing Data Warehouse would ensure performance enhancement in course of action. The pertinent employment of the formulated work could be ensured in a variety of organizations where accrual of cosseted data is of extreme enormity, which would include educational organizations, corporate houses, medical establishments, private establishments and so on and so forth.
{"title":"Dynamic Referencing Data Warehouse Employing Proposed Time Integrated Seed Based Element Engendered Cryptographic Algorithm","authors":"Rajdeep Chowdhury, Jenifar Khan, Subham Sengupta, Saswata Dasgupta, S. Datta, Mallika De","doi":"10.1145/2909067.2909094","DOIUrl":"https://doi.org/10.1145/2909067.2909094","url":null,"abstract":"Network Security has become imperative in the contemporary scenario and subsequently an assortment of modus operandi is being espoused to evade it. Network administrators need to adhere with latest advancement in both hardware and software field to prevent user data from malicious intrusions. The formulated paper outlines a cryptographic algorithm based on Time Integrated Seed modus operandi Engendering Elements at bay and focusing on Dynamic Referencing Data Warehouse employing the identical concept amid its functionality. An amalgamation would endow with a proficient and prearranged approach of amassing data with stringent security modus operandi, with effective deployment of all obtainable space. The incorporation of the novel cryptographic algorithm with the Dynamic Referencing Data Warehouse would ensure performance enhancement in course of action. The pertinent employment of the formulated work could be ensured in a variety of organizations where accrual of cosseted data is of extreme enormity, which would include educational organizations, corporate houses, medical establishments, private establishments and so on and so forth.","PeriodicalId":371590,"journal":{"name":"Women In Research","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122019217","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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