Pub Date : 2019-03-01DOI: 10.1109/ICCMC.2019.8819829
M. Haripriya, S. Saravanan, Rejul M
The Industrial Internet of Things capitalize application of sensors in getting real time data through computers, cloud servers for transformational business outcomes for Industrial applications. Some of the key benefits of Industrial Internet of Things are to reduce human errors, manual labor work, costs, time & money. We also cannot forget the possible underpinnings of IIoT in quality control and maintenance. The heat treatment industry is at turning point, in which digital technology has the capacity to unlock new ways of managing process variables and enhance productivity in vacuum heat treatment operations. Vacuum heat treatment (VHT) plays an important role in capacitor production. During the heat treatment process the zinc element has to undergo certain process within VHT chamber for strengthening the element. The temperature should be maintained and controlled in a proper proportion during capacitor production. By monitoring the live temperature, errors like temperature increase and decrease can be identified and predictive maintenance can be done. In this work, we developed a system to monitor the temperature levels in VHT especially the coolant pipe which is directed to VHT. The developed system uses pt100 sensors to monitor the live temperature of the coolant pipe through a gateway using the PLC. This overall process is done in real time at Schneider Electric, Bangalore. The time taken to complete one process takes 72 hours. The temperature values collected during the process is stored in database created using MySql and then transferred to cloud for analysis to do predictive maintenances.
{"title":"Iot Enabling of Vacuum Heat Treatment Chambers for Data Acquisition and Analytics","authors":"M. Haripriya, S. Saravanan, Rejul M","doi":"10.1109/ICCMC.2019.8819829","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819829","url":null,"abstract":"The Industrial Internet of Things capitalize application of sensors in getting real time data through computers, cloud servers for transformational business outcomes for Industrial applications. Some of the key benefits of Industrial Internet of Things are to reduce human errors, manual labor work, costs, time & money. We also cannot forget the possible underpinnings of IIoT in quality control and maintenance. The heat treatment industry is at turning point, in which digital technology has the capacity to unlock new ways of managing process variables and enhance productivity in vacuum heat treatment operations. Vacuum heat treatment (VHT) plays an important role in capacitor production. During the heat treatment process the zinc element has to undergo certain process within VHT chamber for strengthening the element. The temperature should be maintained and controlled in a proper proportion during capacitor production. By monitoring the live temperature, errors like temperature increase and decrease can be identified and predictive maintenance can be done. In this work, we developed a system to monitor the temperature levels in VHT especially the coolant pipe which is directed to VHT. The developed system uses pt100 sensors to monitor the live temperature of the coolant pipe through a gateway using the PLC. This overall process is done in real time at Schneider Electric, Bangalore. The time taken to complete one process takes 72 hours. The temperature values collected during the process is stored in database created using MySql and then transferred to cloud for analysis to do predictive maintenances.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131671449","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 : 2019-03-01DOI: 10.1109/ICCMC.2019.8819693
Himani Pangasa, Shipra Aggarwal
At mega malls, for grocery shopping and purchase of daily needs artefacts, customers have to wait in extended queues for the billing leading to wastage of their precious time. In order to solve this problem, Different researchers have proposed automation in billing system. When patron picks up an artefact and drops it into the cart, the scanner scans the artefact’s distinctive code and its value, which is flaunted on the display screen of the trolley. After customer has consummate with the purchase, patron goes to the billing counter and pay the total bill which was shown on the display screen incorporated on the cart. In this paper, an attempt has been made to analyse the related works carried out by various researchers in this field based on the main components of smart cart like microcontroller, transmission medium and scanning system.
{"title":"An Analysis of Li-Fi based Prevalent Automated Billing Systems in Shopping Malls","authors":"Himani Pangasa, Shipra Aggarwal","doi":"10.1109/ICCMC.2019.8819693","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819693","url":null,"abstract":"At mega malls, for grocery shopping and purchase of daily needs artefacts, customers have to wait in extended queues for the billing leading to wastage of their precious time. In order to solve this problem, Different researchers have proposed automation in billing system. When patron picks up an artefact and drops it into the cart, the scanner scans the artefact’s distinctive code and its value, which is flaunted on the display screen of the trolley. After customer has consummate with the purchase, patron goes to the billing counter and pay the total bill which was shown on the display screen incorporated on the cart. In this paper, an attempt has been made to analyse the related works carried out by various researchers in this field based on the main components of smart cart like microcontroller, transmission medium and scanning system.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121112760","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 : 2019-03-01DOI: 10.1109/ICCMC.2019.8819810
Sadaf Anjum, S. Shrivastava
Sensor nodes transmit data packets from source to destination in wireless sensor network for that they utilize multi-hop routing. While sending data more energy is consumed. Hence for gathering data in interesting area mobile elements are instigate. Delay to transmit long data is major problem in numerous proposed data collection algorithm. Hence to resolve this problem proposed a data collection algorithm with mobile elements. Here for collecting event packets rely on moving window mechanism mobile elements are dispatched. Hence experimental result shows our proposed system can lower data delay.
{"title":"Implementation of Data Collection Algorithm based on TDA in WSN Mobile Elements","authors":"Sadaf Anjum, S. Shrivastava","doi":"10.1109/ICCMC.2019.8819810","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819810","url":null,"abstract":"Sensor nodes transmit data packets from source to destination in wireless sensor network for that they utilize multi-hop routing. While sending data more energy is consumed. Hence for gathering data in interesting area mobile elements are instigate. Delay to transmit long data is major problem in numerous proposed data collection algorithm. Hence to resolve this problem proposed a data collection algorithm with mobile elements. Here for collecting event packets rely on moving window mechanism mobile elements are dispatched. Hence experimental result shows our proposed system can lower data delay.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121113587","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 : 2019-03-01DOI: 10.1109/ICCMC.2019.8819860
Kanika Suneja, Shelza Dua, M. Dua
In the current scenario of data transmissions, digital images constitute a major part of multimedia communication. Hence, their security is a great area of concern. In this paper, various chaotic maps, which are used in image encryption, are reviewed and their merits and demerits are discussed. The properties of chaotic maps like stochastic, ergodicity and highly sensitive to initial situations make them reliable for image encryption. Many of the earlier proposed image encryption techniques used low dimensional chaotic maps, which exhibit lowest level of security and have very less ability to handle brute force and statistical attacks. To solve this problem, researchers have established various high dimensional chaotic maps. In this review paper, an effort has been made to highlight the features and techniques of different chaotic maps used for image encryption.
{"title":"A Review of Chaos based Image Encryption","authors":"Kanika Suneja, Shelza Dua, M. Dua","doi":"10.1109/ICCMC.2019.8819860","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819860","url":null,"abstract":"In the current scenario of data transmissions, digital images constitute a major part of multimedia communication. Hence, their security is a great area of concern. In this paper, various chaotic maps, which are used in image encryption, are reviewed and their merits and demerits are discussed. The properties of chaotic maps like stochastic, ergodicity and highly sensitive to initial situations make them reliable for image encryption. Many of the earlier proposed image encryption techniques used low dimensional chaotic maps, which exhibit lowest level of security and have very less ability to handle brute force and statistical attacks. To solve this problem, researchers have established various high dimensional chaotic maps. In this review paper, an effort has been made to highlight the features and techniques of different chaotic maps used for image encryption.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123378355","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 : 2019-03-01DOI: 10.1109/ICCMC.2019.8819765
Sarthak Haldar
Surely there has been no time in history where the lived lives of people have changed more dramatically due to the emergence of Artificial Intelligence. Various research and development has taken place over the years on computer vision which is a branch of AI. AI disciplines like a vision system is applied in various fields like self driving cars, face detection by social media apps and law enforcement softwares, google lens and so on. This paper deals with design and implementation of an efficient way of training a GPU using python libraries to process and classify an image. The design is profoundly described along with its performance efficiency. The image processing techniques presented in this paper includes the concept of neural networks and deep learning.
{"title":"Design and Implementation of an Image Classifier using CNN","authors":"Sarthak Haldar","doi":"10.1109/ICCMC.2019.8819765","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819765","url":null,"abstract":"Surely there has been no time in history where the lived lives of people have changed more dramatically due to the emergence of Artificial Intelligence. Various research and development has taken place over the years on computer vision which is a branch of AI. AI disciplines like a vision system is applied in various fields like self driving cars, face detection by social media apps and law enforcement softwares, google lens and so on. This paper deals with design and implementation of an efficient way of training a GPU using python libraries to process and classify an image. The design is profoundly described along with its performance efficiency. The image processing techniques presented in this paper includes the concept of neural networks and deep learning.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116459229","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 : 2019-03-01DOI: 10.1109/ICCMC.2019.8819681
Juned Ahmed Mazumder, K. Hemachandra
In the advancement of information technology the role of security of information is very significant. Many organization including research and educational institute, IT companies exploring the area of quantum computation due to which the field is advancing very quickly. The mechanism of quantum computer provides greater security for quantum data. So in this research we present a new high security steganography system using hybridization of quantum computation and wavelet transformation. The proposed algorithm provides dual security for the embedded data as we transform the normal signal of the high frequency information of wavelet transformation into quantum signal before embedding the secret information. The message extraction process depends on the corresponding coefficient value of low frequency information which acts as a pseudo random key. To assess the accomplishment of our proposed algorithm we have used three parameters MSE, PSNR and RS for different image formats. All these metrics showed that there is very less distortion of the original image.
{"title":"Image Steganography Using the Fusion of Quantum Computation and Wavelet Transformation","authors":"Juned Ahmed Mazumder, K. Hemachandra","doi":"10.1109/ICCMC.2019.8819681","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819681","url":null,"abstract":"In the advancement of information technology the role of security of information is very significant. Many organization including research and educational institute, IT companies exploring the area of quantum computation due to which the field is advancing very quickly. The mechanism of quantum computer provides greater security for quantum data. So in this research we present a new high security steganography system using hybridization of quantum computation and wavelet transformation. The proposed algorithm provides dual security for the embedded data as we transform the normal signal of the high frequency information of wavelet transformation into quantum signal before embedding the secret information. The message extraction process depends on the corresponding coefficient value of low frequency information which acts as a pseudo random key. To assess the accomplishment of our proposed algorithm we have used three parameters MSE, PSNR and RS for different image formats. All these metrics showed that there is very less distortion of the original image.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133995284","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 : 2019-03-01DOI: 10.1109/ICCMC.2019.8819825
Meghana R K, Yojan Chitkara, A. Mohana
Background Modelling and Foreground detection in sports has been achieved by cleverly developing a model of a background from a video by deducing knowledge from frames and comparing this model to every subsequent frame and subtracting the background region from it, hence leaving the foreground detected. This output from GMM background subtraction is fed into the feature extraction algorithm, which segregates the players based on teams. By extracting information of primary colors from each frame, the design of the algorithm based on the color of preference is done. Tracking algorithms Kalman and extended Kalman Filters help to predict and correct the location of players and in correctly estimating their trajectory on the field. Challenges such as shadowing, occlusions and illumination changes are addressed. The designed algorithms are tested against a set of performance parameters for the following datasets (Norway and FIFA) using MATLAB (2017b) and the inferences are respectively made. Object detection, motion detection and Kalman filter algorithms are implemented and the observed results are 100%, 84% and 100% accuracy respectively. With the results quantification and performance analysis, it is observed that with the decrease in contrast between player jerseys a decrease in detection accuracy occurs and with players crowded regions on the field and occluded players a decrease in tracking accuracy was observed.
{"title":"Background-modelling techniques for foreground detection and Tracking using Gaussian Mixture Model","authors":"Meghana R K, Yojan Chitkara, A. Mohana","doi":"10.1109/ICCMC.2019.8819825","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819825","url":null,"abstract":"Background Modelling and Foreground detection in sports has been achieved by cleverly developing a model of a background from a video by deducing knowledge from frames and comparing this model to every subsequent frame and subtracting the background region from it, hence leaving the foreground detected. This output from GMM background subtraction is fed into the feature extraction algorithm, which segregates the players based on teams. By extracting information of primary colors from each frame, the design of the algorithm based on the color of preference is done. Tracking algorithms Kalman and extended Kalman Filters help to predict and correct the location of players and in correctly estimating their trajectory on the field. Challenges such as shadowing, occlusions and illumination changes are addressed. The designed algorithms are tested against a set of performance parameters for the following datasets (Norway and FIFA) using MATLAB (2017b) and the inferences are respectively made. Object detection, motion detection and Kalman filter algorithms are implemented and the observed results are 100%, 84% and 100% accuracy respectively. With the results quantification and performance analysis, it is observed that with the decrease in contrast between player jerseys a decrease in detection accuracy occurs and with players crowded regions on the field and occluded players a decrease in tracking accuracy was observed.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132217151","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 : 2019-03-01DOI: 10.1109/ICCMC.2019.8819792
Piyush Anil Bodhankar, Rajesh K. Nasare, G. Yenurkar
As the trend of e-commerce and online shopping is increasing day by day, we need a method which can be helpful to decide whether to buy the product or not. Here the opinions of the other customers and rating for that product can be used as a considerably good parameter for designing such a system. With the development of new technologies we have a possible solution in the form of recommendation system. Recommendation system gives an important help in providing the necessary information to user based on personalized and practical services. The most vital technique in this field is which plays a crucial role is Collaborative filtering. In this paper we present a recommendations system for tourism and hotel based on enhanced Collaborative filtering approach.
{"title":"Designing a Sales Prediction Model in Tourism Industry and Hotel Recommendation Based on Hybrid Recommendation","authors":"Piyush Anil Bodhankar, Rajesh K. Nasare, G. Yenurkar","doi":"10.1109/ICCMC.2019.8819792","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819792","url":null,"abstract":"As the trend of e-commerce and online shopping is increasing day by day, we need a method which can be helpful to decide whether to buy the product or not. Here the opinions of the other customers and rating for that product can be used as a considerably good parameter for designing such a system. With the development of new technologies we have a possible solution in the form of recommendation system. Recommendation system gives an important help in providing the necessary information to user based on personalized and practical services. The most vital technique in this field is which plays a crucial role is Collaborative filtering. In this paper we present a recommendations system for tourism and hotel based on enhanced Collaborative filtering approach.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133591677","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 : 2019-03-01DOI: 10.1109/ICCMC.2019.8819719
Sagar B.S, N. S, Nithin Kashyap, Sachin D.N
Artificial intelligence is really a kind of computerized version of human intelligence. The way artificial intelligence works is like learning iteratively again and again, just like humans. In this generation, the threat of landscape is unquestionably evolving. The cyber attackers are entirely focused on financial rewards. But the department has found a new way to prevent attacks before they occur, as the old traditional way can no longer be relied upon. This paper introduces the need for the development of cybersecurity skills and how artificial intelligence can be implied to improve skills through the use of artificial neural networks and machine learning algorithms.
{"title":"Providing Cyber Security using Artificial Intelligence – A survey","authors":"Sagar B.S, N. S, Nithin Kashyap, Sachin D.N","doi":"10.1109/ICCMC.2019.8819719","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819719","url":null,"abstract":"Artificial intelligence is really a kind of computerized version of human intelligence. The way artificial intelligence works is like learning iteratively again and again, just like humans. In this generation, the threat of landscape is unquestionably evolving. The cyber attackers are entirely focused on financial rewards. But the department has found a new way to prevent attacks before they occur, as the old traditional way can no longer be relied upon. This paper introduces the need for the development of cybersecurity skills and how artificial intelligence can be implied to improve skills through the use of artificial neural networks and machine learning algorithms.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"728 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133596840","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 : 2019-03-01DOI: 10.1109/ICCMC.2019.8819845
Joseph Herve Balanke, H. V
Lexicon algorithm is used to determine the sentiment expressed by a textual content. This sentiment might be negative, neutral or positive. It is possible to be sarcastic using only positive or neutral sentiment textual contents. Hence, lexicon algorithm can be useful but yet insufficient for sarcasm detection. It is necessary to extend the lexicon algorithm in order to come out with systems that would be proven efficient for sarcasm detection on neutral and positive sentiment textual contents. In this paper, two sarcasm analysis systems both obtained from the extension of the lexicon algorithm have been proposed for that sake. The first system consists of the combination of a lexicon algorithm and a pure sarcasm analysis algorithm. The second system consists of the combination of a lexicon algorithm and a sentiment prediction algorithm.
{"title":"Extension of the Lexicon Algorithm for Sarcasm Detection","authors":"Joseph Herve Balanke, H. V","doi":"10.1109/ICCMC.2019.8819845","DOIUrl":"https://doi.org/10.1109/ICCMC.2019.8819845","url":null,"abstract":"Lexicon algorithm is used to determine the sentiment expressed by a textual content. This sentiment might be negative, neutral or positive. It is possible to be sarcastic using only positive or neutral sentiment textual contents. Hence, lexicon algorithm can be useful but yet insufficient for sarcasm detection. It is necessary to extend the lexicon algorithm in order to come out with systems that would be proven efficient for sarcasm detection on neutral and positive sentiment textual contents. In this paper, two sarcasm analysis systems both obtained from the extension of the lexicon algorithm have been proposed for that sake. The first system consists of the combination of a lexicon algorithm and a pure sarcasm analysis algorithm. The second system consists of the combination of a lexicon algorithm and a sentiment prediction algorithm.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"55 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114119740","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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