Pub Date : 2020-12-04DOI: 10.1109/IBSSC51096.2020.9332170
M. Khanapurkar, Sonali Joshi, K. Akant, V. Gadre, S. Untawale, Anita S. Diwakar
COVID-19 is considered as threat to mankind, the educational technologists and academicians are considering it as an opportunity to develop and carve out new horizons as far as online teaching - learning is concerned. Thus developed technologies and methodologies during this pandemic situation will continue to be in existence and impact the world even though the so called pandemic situation remains in existence or not. An inter-institute faculty student peer collaboration has been initiated and is ongoing between an premium institute Indian Institute of Technology Bombay and another premier self-financing autonomous institute G. H. Raisoni College of Engineering Nagpur with involvement of NPTEL for the development of MOOC of Digital Signal Processing course. Philosophy of this novel initiative for noble cause is to make best teaching standards in the country accessible to a large number of student and other stakeholders and to provide them with an experience of learning at par with live interaction as student peers from IIT Bombay have. The implementation methodology, results, current status and future scope of ongoing endeavor is presented in this paper. The paper is having six sections. The outcomes in the form of takeaways for partnering institutes are presented with the current status of the ongoing inter-institute student - faculty peer collaboration. The future plans are presented in the last section with proposed involvement of another institute PVG's College of Engineering, Pune in the collaboration to expand its reach, scope and horizon leading toward exploring the other avenues of joining hands to serve the society in the best possible way.
{"title":"Developing Learner Generated MOOC Content through Inter-Institute Faculty- Student Peer Collaboration: Case Study","authors":"M. Khanapurkar, Sonali Joshi, K. Akant, V. Gadre, S. Untawale, Anita S. Diwakar","doi":"10.1109/IBSSC51096.2020.9332170","DOIUrl":"https://doi.org/10.1109/IBSSC51096.2020.9332170","url":null,"abstract":"COVID-19 is considered as threat to mankind, the educational technologists and academicians are considering it as an opportunity to develop and carve out new horizons as far as online teaching - learning is concerned. Thus developed technologies and methodologies during this pandemic situation will continue to be in existence and impact the world even though the so called pandemic situation remains in existence or not. An inter-institute faculty student peer collaboration has been initiated and is ongoing between an premium institute Indian Institute of Technology Bombay and another premier self-financing autonomous institute G. H. Raisoni College of Engineering Nagpur with involvement of NPTEL for the development of MOOC of Digital Signal Processing course. Philosophy of this novel initiative for noble cause is to make best teaching standards in the country accessible to a large number of student and other stakeholders and to provide them with an experience of learning at par with live interaction as student peers from IIT Bombay have. The implementation methodology, results, current status and future scope of ongoing endeavor is presented in this paper. The paper is having six sections. The outcomes in the form of takeaways for partnering institutes are presented with the current status of the ongoing inter-institute student - faculty peer collaboration. The future plans are presented in the last section with proposed involvement of another institute PVG's College of Engineering, Pune in the collaboration to expand its reach, scope and horizon leading toward exploring the other avenues of joining hands to serve the society in the best possible way.","PeriodicalId":432093,"journal":{"name":"2020 IEEE Bombay Section Signature Conference (IBSSC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115694216","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 : 2020-12-04DOI: 10.1109/IBSSC51096.2020.9332159
Siddhant Meshram
Life Expectancy is an important metric to assess the health of a nation. This paper presents a comparative analysis of life expectancy between developed and developing countries with the help of a Supervised Machine Learning model. The prediction model is trained using three regression models, namely Linear Regression, Decision Tree Regressor and Random Forest Regressor. The selection of model is done on the basis of R2 score, Mean Squared Error & Mean Absolute Error. Random Forest Regressor is selected for the development of the prediction model for life expectancy, as it had R2 score as 0.99 and 0.95 on training & testing data respectively, along with 4.43 and 1.58 as the Mean Squared Error & Mean Absolute Error. The comparative analysis is done on the basis of HIV/AIDS, Adult Mortality and Expenditure on Healthcare, as they are the important features suggested by the model. The study undertaken suggests that, developed countries have high life expectancy as compared to developing countries. India has high adult mortality as compared to considered developed countries because of the low expenditure on healthcare. The insights from this analysis can be used by Government and Healthcare sectors for the betterment of society.
{"title":"Comparative Analysis of Life Expectancy between Developed and Developing Countries using Machine Learning","authors":"Siddhant Meshram","doi":"10.1109/IBSSC51096.2020.9332159","DOIUrl":"https://doi.org/10.1109/IBSSC51096.2020.9332159","url":null,"abstract":"Life Expectancy is an important metric to assess the health of a nation. This paper presents a comparative analysis of life expectancy between developed and developing countries with the help of a Supervised Machine Learning model. The prediction model is trained using three regression models, namely Linear Regression, Decision Tree Regressor and Random Forest Regressor. The selection of model is done on the basis of R2 score, Mean Squared Error & Mean Absolute Error. Random Forest Regressor is selected for the development of the prediction model for life expectancy, as it had R2 score as 0.99 and 0.95 on training & testing data respectively, along with 4.43 and 1.58 as the Mean Squared Error & Mean Absolute Error. The comparative analysis is done on the basis of HIV/AIDS, Adult Mortality and Expenditure on Healthcare, as they are the important features suggested by the model. The study undertaken suggests that, developed countries have high life expectancy as compared to developing countries. India has high adult mortality as compared to considered developed countries because of the low expenditure on healthcare. The insights from this analysis can be used by Government and Healthcare sectors for the betterment of society.","PeriodicalId":432093,"journal":{"name":"2020 IEEE Bombay Section Signature Conference (IBSSC)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126306758","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 : 2020-12-04DOI: 10.1109/IBSSC51096.2020.9332156
S. Goutam, S. Unnikrishnan, Neel Kudu
In this research paper, we have implemented the decision for Vertical Handover using k-Means Clustering. We have analyzed the accuracy of the algorithm. The input parameters considered are Received Signal Strength (RSS), Quality of Service (QoS), Bandwidth and Network Coverage. We have derived the Quality of Service for a network using network parameters like packet loss, latency and jitter.
{"title":"Decision for Vertical Handover using k-Means Clustering Algorithm","authors":"S. Goutam, S. Unnikrishnan, Neel Kudu","doi":"10.1109/IBSSC51096.2020.9332156","DOIUrl":"https://doi.org/10.1109/IBSSC51096.2020.9332156","url":null,"abstract":"In this research paper, we have implemented the decision for Vertical Handover using k-Means Clustering. We have analyzed the accuracy of the algorithm. The input parameters considered are Received Signal Strength (RSS), Quality of Service (QoS), Bandwidth and Network Coverage. We have derived the Quality of Service for a network using network parameters like packet loss, latency and jitter.","PeriodicalId":432093,"journal":{"name":"2020 IEEE Bombay Section Signature Conference (IBSSC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126423804","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 : 2020-12-04DOI: 10.1109/IBSSC51096.2020.9332209
S. Goutam, S. Unnikrishnan, Pradeep Singh, A. Karandikar
The main aim of this research paper is to design and implement decision for Vertical Handover (VHO) using Fuzzy Logic. The main parameters considered in the design of Vertical Handover Decision Algorithm (VHDA) are Received Signal Strength, Bandwidth, Cost and Velocity of the user. The statistical analysis of handover with respect to velocity of the user is also presented in the paper.
{"title":"Algorithm for handover decision using Fuzzy Logic","authors":"S. Goutam, S. Unnikrishnan, Pradeep Singh, A. Karandikar","doi":"10.1109/IBSSC51096.2020.9332209","DOIUrl":"https://doi.org/10.1109/IBSSC51096.2020.9332209","url":null,"abstract":"The main aim of this research paper is to design and implement decision for Vertical Handover (VHO) using Fuzzy Logic. The main parameters considered in the design of Vertical Handover Decision Algorithm (VHDA) are Received Signal Strength, Bandwidth, Cost and Velocity of the user. The statistical analysis of handover with respect to velocity of the user is also presented in the paper.","PeriodicalId":432093,"journal":{"name":"2020 IEEE Bombay Section Signature Conference (IBSSC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130452575","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 : 2020-12-04DOI: 10.1109/IBSSC51096.2020.9332214
Atharva Karnik, Diksha Adke, Pushkar Sathe
The system explained in this paper provides a compact smart surveillance system. Recent years have seen the Internet of Things (IoT) dominating in various fields of applications. With devices getting smarter and insurgence of 5G technology, the connectivity of people with devices is increasing. Smarter surveillance systems are more reliable and accessible. A gyroscope is a MEM sensor which detects angular disturbances. The principle is to detect opening or knockdown of the door physically or by a gas cutter. The system is connected to the user via Wi-Fi using ESP8266. Being a system with a low form factor, this system can be implemented on doors, shops, cars, etc. An alarm system is included in the system to alert the neighbors as well as to send a notification to the user via Blynk mobile application. The proposed system is a portable smart home solution for theft detection. The code for this system is available here: https://github.com/atharvakarnik/TheftDetectionMPU.git
{"title":"Low-Cost Compact Theft-Detection System using MPU-6050 and Blynk IoT Platform","authors":"Atharva Karnik, Diksha Adke, Pushkar Sathe","doi":"10.1109/IBSSC51096.2020.9332214","DOIUrl":"https://doi.org/10.1109/IBSSC51096.2020.9332214","url":null,"abstract":"The system explained in this paper provides a compact smart surveillance system. Recent years have seen the Internet of Things (IoT) dominating in various fields of applications. With devices getting smarter and insurgence of 5G technology, the connectivity of people with devices is increasing. Smarter surveillance systems are more reliable and accessible. A gyroscope is a MEM sensor which detects angular disturbances. The principle is to detect opening or knockdown of the door physically or by a gas cutter. The system is connected to the user via Wi-Fi using ESP8266. Being a system with a low form factor, this system can be implemented on doors, shops, cars, etc. An alarm system is included in the system to alert the neighbors as well as to send a notification to the user via Blynk mobile application. The proposed system is a portable smart home solution for theft detection. The code for this system is available here: https://github.com/atharvakarnik/TheftDetectionMPU.git","PeriodicalId":432093,"journal":{"name":"2020 IEEE Bombay Section Signature Conference (IBSSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132997366","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 : 2020-12-04DOI: 10.1109/IBSSC51096.2020.9332166
Mandar P. Joshi, Umesh Gite, J. G. Joshi
This paper presents circularly polarized microstrip antenna for Indian Regional Navigation Satellite System (IRNSS). The proposed antenna is resonating at 1190 MHz with bandwidth of 112 MHz. An elliptical cross shaped defected ground structure (DGS) is etched on ground plane to realized circular polarization. The proposed antenna design offers axial ratio bandwidth of 27 MHz with gain of 7.9 dBi. The antenna radiates in broadside direction with right hand circular polarization. The antenna is fabricated and tested. The measured results are presented in this paper.
{"title":"Circularly Polarized Microstrip Antenna using DGS for IRNSS Services","authors":"Mandar P. Joshi, Umesh Gite, J. G. Joshi","doi":"10.1109/IBSSC51096.2020.9332166","DOIUrl":"https://doi.org/10.1109/IBSSC51096.2020.9332166","url":null,"abstract":"This paper presents circularly polarized microstrip antenna for Indian Regional Navigation Satellite System (IRNSS). The proposed antenna is resonating at 1190 MHz with bandwidth of 112 MHz. An elliptical cross shaped defected ground structure (DGS) is etched on ground plane to realized circular polarization. The proposed antenna design offers axial ratio bandwidth of 27 MHz with gain of 7.9 dBi. The antenna radiates in broadside direction with right hand circular polarization. The antenna is fabricated and tested. The measured results are presented in this paper.","PeriodicalId":432093,"journal":{"name":"2020 IEEE Bombay Section Signature Conference (IBSSC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116082305","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 : 2020-12-04DOI: 10.1109/IBSSC51096.2020.9332189
Devansh P. Shah, Nikhil M. Jagtap, Shloka S. Shah, Anant V. Nimkar
Spaced Repetition has proven to be an effective way in learning and memorizing complex topics. An algorithm ‘Spaced Repetition for Slow Learners’ (SRSL) is described to schedule repetitions which eventually adapts to the capacity of the learner. SRSL computes the score of learners for a particular assessment based on factors such as response time, difficulty and dependency of questions. The exponential forgetting curve model is the memory model assumed by SRSL. Based on this algorithm, a model has been proposed with experimental analysis of the same. Further, comparison of SRSL and the Leitner System demonstrates the adaptability of the algorithm to the learning curve of the learner.
{"title":"Spaced Repetition for Slow Learners","authors":"Devansh P. Shah, Nikhil M. Jagtap, Shloka S. Shah, Anant V. Nimkar","doi":"10.1109/IBSSC51096.2020.9332189","DOIUrl":"https://doi.org/10.1109/IBSSC51096.2020.9332189","url":null,"abstract":"Spaced Repetition has proven to be an effective way in learning and memorizing complex topics. An algorithm ‘Spaced Repetition for Slow Learners’ (SRSL) is described to schedule repetitions which eventually adapts to the capacity of the learner. SRSL computes the score of learners for a particular assessment based on factors such as response time, difficulty and dependency of questions. The exponential forgetting curve model is the memory model assumed by SRSL. Based on this algorithm, a model has been proposed with experimental analysis of the same. Further, comparison of SRSL and the Leitner System demonstrates the adaptability of the algorithm to the learning curve of the learner.","PeriodicalId":432093,"journal":{"name":"2020 IEEE Bombay Section Signature Conference (IBSSC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126448060","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}
Snake Species Identification is a challenge as erroneous snake identification from the perceptible traits is a prime reason of death because of snake bites. The main objective of the proposed system is to be able to identify snake species from their visual traits in order to provide suitable treatment, thus preventing subsequent deaths. The proposed system involves techniques based on Image Processing, Convolution Neural Networks and Deep Learning to achieve the mentioned purpose. CNN has been highly used in automatic image classification system. In most cases, extracting features and utilizing them for classification. Deep learning successfully achieves recognition of objects in images as it is implemented using artificial neural networks. Image classification tasks have seen a rise with the introduction of deep learning techniques. So far, no automated method for classification has been suggested to categorize snakes. The system that would be developed will be useful to recognize snake species correctly and thus take necessary action.
{"title":"Snake Species Identification and Recognition","authors":"Mrugendra Vasmatkar, Ishwari Zare, Prachi Kumbla, Shantanu Pimpalkar, Aditya Sharma","doi":"10.1109/IBSSC51096.2020.9332218","DOIUrl":"https://doi.org/10.1109/IBSSC51096.2020.9332218","url":null,"abstract":"Snake Species Identification is a challenge as erroneous snake identification from the perceptible traits is a prime reason of death because of snake bites. The main objective of the proposed system is to be able to identify snake species from their visual traits in order to provide suitable treatment, thus preventing subsequent deaths. The proposed system involves techniques based on Image Processing, Convolution Neural Networks and Deep Learning to achieve the mentioned purpose. CNN has been highly used in automatic image classification system. In most cases, extracting features and utilizing them for classification. Deep learning successfully achieves recognition of objects in images as it is implemented using artificial neural networks. Image classification tasks have seen a rise with the introduction of deep learning techniques. So far, no automated method for classification has been suggested to categorize snakes. The system that would be developed will be useful to recognize snake species correctly and thus take necessary action.","PeriodicalId":432093,"journal":{"name":"2020 IEEE Bombay Section Signature Conference (IBSSC)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124238447","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 : 2020-12-04DOI: 10.1109/IBSSC51096.2020.9332173
Divya Khetan, Prafful Javare, Anita S. Diwakar, M. Naik, Shivani Umredkar, Sakib Shaikh
The world is going through a very tough time due to the pandemic, and people are only leaving their houses if it’s unavoidable. As the lockdown restrictions begin to ease slowly, wearing masks, sanitization and social distancing has become a priority. Safety workers are putting their lives on the line to ensure the safety of the citizens. This paper presents a product in the form of an automated kiosk that aims to reduce the load on the safety workers, while efficiently screening people entering any premises. The kiosk was deployed in a real commercial environment, and thousands of people have used it. The goal of the research paper is to answer this research question - What can be the best solution in this situation in order to safeguard the premises?
{"title":"Innovative product for premise safety from Covid 19: NeelKavach Kiosk","authors":"Divya Khetan, Prafful Javare, Anita S. Diwakar, M. Naik, Shivani Umredkar, Sakib Shaikh","doi":"10.1109/IBSSC51096.2020.9332173","DOIUrl":"https://doi.org/10.1109/IBSSC51096.2020.9332173","url":null,"abstract":"The world is going through a very tough time due to the pandemic, and people are only leaving their houses if it’s unavoidable. As the lockdown restrictions begin to ease slowly, wearing masks, sanitization and social distancing has become a priority. Safety workers are putting their lives on the line to ensure the safety of the citizens. This paper presents a product in the form of an automated kiosk that aims to reduce the load on the safety workers, while efficiently screening people entering any premises. The kiosk was deployed in a real commercial environment, and thousands of people have used it. The goal of the research paper is to answer this research question - What can be the best solution in this situation in order to safeguard the premises?","PeriodicalId":432093,"journal":{"name":"2020 IEEE Bombay Section Signature Conference (IBSSC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126619040","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 : 2020-12-04DOI: 10.1109/IBSSC51096.2020.9332161
Lakshmana Rao Arla, Sridevi Bonthu, Abhinav Dayal
Spoken Language Identification (SLID) aims at assigning language labels to speech in an audio file. This paper proposes an approach based on Convolution Neural Networks (CNN) for the automatic identification of four Indian languages, Bengali, Gujarati, Tamil and Telugu. The classifier is trained on audio data of 5 hours duration, from each of the four languages. The CNN operates on MFCC spectrogram images generated from short splits of two to four second duration from the raw audio input with varying audio quality and noise print. The paper also analyzes the SLID system performance as a function of different train and test audio sample durations. The proposed CNN model achieves 88.82% accuracy, which can be considered as best when compared with machine learning models.
{"title":"Multiclass Spoken Language Identification for Indian Languages using Deep Learning","authors":"Lakshmana Rao Arla, Sridevi Bonthu, Abhinav Dayal","doi":"10.1109/IBSSC51096.2020.9332161","DOIUrl":"https://doi.org/10.1109/IBSSC51096.2020.9332161","url":null,"abstract":"Spoken Language Identification (SLID) aims at assigning language labels to speech in an audio file. This paper proposes an approach based on Convolution Neural Networks (CNN) for the automatic identification of four Indian languages, Bengali, Gujarati, Tamil and Telugu. The classifier is trained on audio data of 5 hours duration, from each of the four languages. The CNN operates on MFCC spectrogram images generated from short splits of two to four second duration from the raw audio input with varying audio quality and noise print. The paper also analyzes the SLID system performance as a function of different train and test audio sample durations. The proposed CNN model achieves 88.82% accuracy, which can be considered as best when compared with machine learning models.","PeriodicalId":432093,"journal":{"name":"2020 IEEE Bombay Section Signature Conference (IBSSC)","volume":"6 23","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113979429","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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