Pub Date : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9754134
S. Vadivel, R. Jayakarthik
Corona virus acute disease, a life-threatening condition, emerged in 2019. In December 2019, the virus was discovered for the first time in Wuhan, China, and has since spread throughout the world. This paper proposes using Residual Neural Networks (ResNets) to predict COVID-19, where the input is collected from Internet of Things (IoT) network. Using a system designed to combat a newly emerging infection in its early stages, this paper tackles the problem. In addition to tracking confirmed and reported cases, the system also keeps tabs on cures and deaths daily. This was done so that all parties involved could see the devastation that the lethal virus would cause as soon as possible. Using RNN and GRU in an ensemble, the RMSE value has been computed for various cases such as infected, cured, and dead. The results of simulation shows that the proposed ResNets for classification is effective in predicting the covid-19 cases than the other existing deep learning models.
{"title":"Predictive Analytics on Covid-19 Prediction using ResNets","authors":"S. Vadivel, R. Jayakarthik","doi":"10.1109/ICCMC53470.2022.9754134","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9754134","url":null,"abstract":"Corona virus acute disease, a life-threatening condition, emerged in 2019. In December 2019, the virus was discovered for the first time in Wuhan, China, and has since spread throughout the world. This paper proposes using Residual Neural Networks (ResNets) to predict COVID-19, where the input is collected from Internet of Things (IoT) network. Using a system designed to combat a newly emerging infection in its early stages, this paper tackles the problem. In addition to tracking confirmed and reported cases, the system also keeps tabs on cures and deaths daily. This was done so that all parties involved could see the devastation that the lethal virus would cause as soon as possible. Using RNN and GRU in an ensemble, the RMSE value has been computed for various cases such as infected, cured, and dead. The results of simulation shows that the proposed ResNets for classification is effective in predicting the covid-19 cases than the other existing deep learning models.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127398654","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753860
Dapeng Qi
The real-time heart rate value can reflect a person's heart activity ability at that time, and then measure the health of the human body from the side. This article is based on shared storage and distributed cloud computing for big data mining and analysis, real-time heart rate analysis of fitness athletes, measuring the attenuated light reflected and absorbed by human blood vessels and tissues, and using embedded motion recognition to study the capture of fitness movements with heart rate detection. To trace the pulsation state of the blood vessel and measure the pulse wave. The easy-to-wear measuring device has gradually become the main method for measuring blood oxygen, pulse and heart rate under non-hospital conditions.
{"title":"Real-Time Monitoring of Fitness Exercise Heart Rate Based on Shared Storage and Embedded Motion Recognition Technology","authors":"Dapeng Qi","doi":"10.1109/ICCMC53470.2022.9753860","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753860","url":null,"abstract":"The real-time heart rate value can reflect a person's heart activity ability at that time, and then measure the health of the human body from the side. This article is based on shared storage and distributed cloud computing for big data mining and analysis, real-time heart rate analysis of fitness athletes, measuring the attenuated light reflected and absorbed by human blood vessels and tissues, and using embedded motion recognition to study the capture of fitness movements with heart rate detection. To trace the pulsation state of the blood vessel and measure the pulse wave. The easy-to-wear measuring device has gradually become the main method for measuring blood oxygen, pulse and heart rate under non-hospital conditions.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122665944","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753825
G. S, K. Raimond
In this modern medicinal world, numerous medicines with various chemical compositions have been discovered. Many individuals consume them these days because they are quick in healing. However, they have a variety of drawbacks, including the failure of internal organs, which may even lead to demise. As a result, some alternative treatment that is both effective and free of adverse effects is required. Medicinal herbs have been utilized to cure practically every disease since ancient times. It is quite effective, and it is also free of side effects. Nowadays, Machine Learning (ML) and Deep Learning (DL) algorithms are used frequently to solve many real-time problems. They predict results with much accuracy. In this paper, a systematic review is devised for identifying therapeutic plants using ML and DL models. The performance of various models as well as the features used by each model is compared to choose the best performing model.
{"title":"Deep Learning based Indigenous Herbal Medicinal Plants Recognition: A Comprehensive Review","authors":"G. S, K. Raimond","doi":"10.1109/ICCMC53470.2022.9753825","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753825","url":null,"abstract":"In this modern medicinal world, numerous medicines with various chemical compositions have been discovered. Many individuals consume them these days because they are quick in healing. However, they have a variety of drawbacks, including the failure of internal organs, which may even lead to demise. As a result, some alternative treatment that is both effective and free of adverse effects is required. Medicinal herbs have been utilized to cure practically every disease since ancient times. It is quite effective, and it is also free of side effects. Nowadays, Machine Learning (ML) and Deep Learning (DL) algorithms are used frequently to solve many real-time problems. They predict results with much accuracy. In this paper, a systematic review is devised for identifying therapeutic plants using ML and DL models. The performance of various models as well as the features used by each model is compared to choose the best performing model.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127030670","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9754106
Ying Wang
Radio communication is an important means of ensuring operations and command on the modern battlefield. Especially when commanding moving targets, it is even the only means of communication. This paper focuses on the problem of blind detection and parameter blind estimation of shortwave frequency hopping signals based on array signal processing, that is, in the absence of sufficient prior information, fully excavate the time domain, frequency domain and spatial characteristics of the signal, and combine the shortwave FH signal In this paper, a method for implementing blind detection and parameter blind estimation of shortwave signals based on broadband processing is proposed. The results show that the method improves the blind inspection efficiency by 7.2%.
{"title":"Theoretical Analysis on Blind Detection Method of Shortwave Communication Electronic Signal Based on Wireless Network","authors":"Ying Wang","doi":"10.1109/ICCMC53470.2022.9754106","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9754106","url":null,"abstract":"Radio communication is an important means of ensuring operations and command on the modern battlefield. Especially when commanding moving targets, it is even the only means of communication. This paper focuses on the problem of blind detection and parameter blind estimation of shortwave frequency hopping signals based on array signal processing, that is, in the absence of sufficient prior information, fully excavate the time domain, frequency domain and spatial characteristics of the signal, and combine the shortwave FH signal In this paper, a method for implementing blind detection and parameter blind estimation of shortwave signals based on broadband processing is proposed. The results show that the method improves the blind inspection efficiency by 7.2%.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126485518","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753698
Xiaoyan Guo, Weihua Zhai, Yifan Sun
This paper introduces the Internet of Things technology and makes full use of the perceptual advantages of the Internet of Things at the end of the network to realize the seamless connection of the sensor network, the terminal communication access network and the backbone network. It studies the mobile terminal security access authentication method combined with fingerprints, Data level and command level fusion secure exchange bus technology, machine learning-based smart whitelist technology and network transmission strategy dynamic adjustment method, and put forward innovative ideas that fit the current production and operation of power companies based on the above key technologies, and improve power information The ability to pre-check safety hazards can realize continuous empowerment of safety technology.
{"title":"Application of Internet of Things Technology in Power Terminal Communication Access Network","authors":"Xiaoyan Guo, Weihua Zhai, Yifan Sun","doi":"10.1109/ICCMC53470.2022.9753698","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753698","url":null,"abstract":"This paper introduces the Internet of Things technology and makes full use of the perceptual advantages of the Internet of Things at the end of the network to realize the seamless connection of the sensor network, the terminal communication access network and the backbone network. It studies the mobile terminal security access authentication method combined with fingerprints, Data level and command level fusion secure exchange bus technology, machine learning-based smart whitelist technology and network transmission strategy dynamic adjustment method, and put forward innovative ideas that fit the current production and operation of power companies based on the above key technologies, and improve power information The ability to pre-check safety hazards can realize continuous empowerment of safety technology.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130161500","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753743
C. Kavitha, D. Balaganesh, M. Sukumar, J. Mathan
One of the easiest ways of communication is possible through interpreting wide range of images on various applications. It is the non-structural data that does not have clear semantics. Image mining techniques implemented on the images are used to extract features/train the real time systems. This can be achieved using combination of various algorithms of image processing, machine learning and artificial intelligence. This paper discusses about those image mining techniques and the challenges faced by various researchers.
{"title":"Review of various Image Mining Techniques","authors":"C. Kavitha, D. Balaganesh, M. Sukumar, J. Mathan","doi":"10.1109/ICCMC53470.2022.9753743","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753743","url":null,"abstract":"One of the easiest ways of communication is possible through interpreting wide range of images on various applications. It is the non-structural data that does not have clear semantics. Image mining techniques implemented on the images are used to extract features/train the real time systems. This can be achieved using combination of various algorithms of image processing, machine learning and artificial intelligence. This paper discusses about those image mining techniques and the challenges faced by various researchers.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123025765","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753761
A. Gupta, Neil Gautam, D. Vishwakarma
Person Re-Identification is the process of recognizing a targeted individual across multiple views at different times, in different and challenging real-life diverse settings. It remains a conundrum due to the significant amount of intra-class variation present in same individual caught across different cameras. Most of the existing models require a large amount of data for training, as a result of which they do not generalize well on small datasets and hence decreases the robustness of the identification process. To reduce this variance, this paper introduces an end-to-end triple stream ensemble model making minimal changes in the Vision Transformer, Resnet50 and Densenet121 architectures respectively. Our model performs well on the Market1501 dataset achieving an accuracy of 90.05% and 80.45% on the Duke MTMC ReID dataset.
{"title":"Ensemble Learning using Vision Transformer and Convolutional Networks for Person Re-ID","authors":"A. Gupta, Neil Gautam, D. Vishwakarma","doi":"10.1109/ICCMC53470.2022.9753761","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753761","url":null,"abstract":"Person Re-Identification is the process of recognizing a targeted individual across multiple views at different times, in different and challenging real-life diverse settings. It remains a conundrum due to the significant amount of intra-class variation present in same individual caught across different cameras. Most of the existing models require a large amount of data for training, as a result of which they do not generalize well on small datasets and hence decreases the robustness of the identification process. To reduce this variance, this paper introduces an end-to-end triple stream ensemble model making minimal changes in the Vision Transformer, Resnet50 and Densenet121 architectures respectively. Our model performs well on the Market1501 dataset achieving an accuracy of 90.05% and 80.45% on the Duke MTMC ReID dataset.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127763954","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753782
Pradhyumna P Mohana
GANs (Generative Adversarial Networks) are a type of deep learning generative model that has lately gained popularity in recent years. GANs can learn patterns from high-dimensional complex data, making them useful for image, audio and video processing. Nonetheless, there are several significant obstacles in the training of GANs, such as instability, mode collapse and non-convergence. To address these issues, researchers have developed a variety of GAN variations by rethinking network topology, modifying the form of goal functions, and changing optimization to precise methods in recent years. This paper describes a thorough analysis of the progress of GAN architecture and optimization solutions to improve its efficiency in various computer vision applications and challenges that are to be faced while implementing the model towards CV (computer vision) is described. It is believed that GAN is strong model and further researches are needed to work in this area to solve a variety of computer vision real time applications.
{"title":"A Survey of Modern Deep Learning based Generative Adversarial Networks (GANs)","authors":"Pradhyumna P Mohana","doi":"10.1109/ICCMC53470.2022.9753782","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753782","url":null,"abstract":"GANs (Generative Adversarial Networks) are a type of deep learning generative model that has lately gained popularity in recent years. GANs can learn patterns from high-dimensional complex data, making them useful for image, audio and video processing. Nonetheless, there are several significant obstacles in the training of GANs, such as instability, mode collapse and non-convergence. To address these issues, researchers have developed a variety of GAN variations by rethinking network topology, modifying the form of goal functions, and changing optimization to precise methods in recent years. This paper describes a thorough analysis of the progress of GAN architecture and optimization solutions to improve its efficiency in various computer vision applications and challenges that are to be faced while implementing the model towards CV (computer vision) is described. It is believed that GAN is strong model and further researches are needed to work in this area to solve a variety of computer vision real time applications.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121350367","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9753908
V. Swetha, K. Sushma, N. D. Praneetha, S. Mahesh
Automatic driving systems, object detection is essential. A logic of fusion presented combining the benefits of these two types detectors of objects, taking into account the properties of classical and deep learning techniques. Theoretically, a link between detection performance and detector type can be established. The numerical study to increase detection performance is based on the established theoretical relationship. In addition, an enhancement strategy is proposed that the designs of the sub-detectors are guided by this principle for improved overall performance. The utility of this combination methodology is illustrated in the identification of pedestrians using a trained by a machine on attribute the conventional detectors or human being. On the training datasets as well as additional different datasets to complete several comparative experiments using the classical and CNN detectors have been undertaken. It is a guarantee to improve detection performance and flexibility to different application settings with a simplified network.
{"title":"Application to Pedestrian Detection and Object Detection","authors":"V. Swetha, K. Sushma, N. D. Praneetha, S. Mahesh","doi":"10.1109/ICCMC53470.2022.9753908","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753908","url":null,"abstract":"Automatic driving systems, object detection is essential. A logic of fusion presented combining the benefits of these two types detectors of objects, taking into account the properties of classical and deep learning techniques. Theoretically, a link between detection performance and detector type can be established. The numerical study to increase detection performance is based on the established theoretical relationship. In addition, an enhancement strategy is proposed that the designs of the sub-detectors are guided by this principle for improved overall performance. The utility of this combination methodology is illustrated in the identification of pedestrians using a trained by a machine on attribute the conventional detectors or human being. On the training datasets as well as additional different datasets to complete several comparative experiments using the classical and CNN detectors have been undertaken. It is a guarantee to improve detection performance and flexibility to different application settings with a simplified network.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128960429","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 : 2022-03-29DOI: 10.1109/ICCMC53470.2022.9754036
Md. Shovon Uz Zaman Siddique, Siddhartha Mohammad, Tapesh Bhowmick, Mohammad Monirujjaman Khan, Rajesh Dey
The aim of this paper is to build a GPS tracker at a very low cost so that it can be used by a lot of people in coastal areas. The main objective of the low-cost GPS tracker is used to track down ships/shipments for the coastal area people of Bangladesh. It will show the position of the people when they are in the sea for fishing so that they do not cross the border of their country. Sometimes fishermen or other people in the sea cannot identify that they have crossed the border of the country. This device is proposed for them so that they know their position in the sea. The GPS tracker system has an alarm as well which will notify the user when it crosses the coastal boundary of Bangladesh. It has been seen that there are many existing GPS trackers in the market. The available GPS trackers are in the range of 3000 BDT and above whereas the low-cost GPS tracker proposed in this project will cost around 1600 BDT. The addition of the buzzer and the website on the low-cost GPS Tracker will be a revolution in the coastal areas of Bangladesh. With the large production of the low-cost GPS Tracker, the pricing per unit will be lowered considerably. The proposed prototype of the GPS tracker if went through different combinational parts will cost even lower and this will be worked on in the future to further reduce the cost.
{"title":"Development of Low-cost GPS Tracker System for Coastal Area of Bangladesh","authors":"Md. Shovon Uz Zaman Siddique, Siddhartha Mohammad, Tapesh Bhowmick, Mohammad Monirujjaman Khan, Rajesh Dey","doi":"10.1109/ICCMC53470.2022.9754036","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9754036","url":null,"abstract":"The aim of this paper is to build a GPS tracker at a very low cost so that it can be used by a lot of people in coastal areas. The main objective of the low-cost GPS tracker is used to track down ships/shipments for the coastal area people of Bangladesh. It will show the position of the people when they are in the sea for fishing so that they do not cross the border of their country. Sometimes fishermen or other people in the sea cannot identify that they have crossed the border of the country. This device is proposed for them so that they know their position in the sea. The GPS tracker system has an alarm as well which will notify the user when it crosses the coastal boundary of Bangladesh. It has been seen that there are many existing GPS trackers in the market. The available GPS trackers are in the range of 3000 BDT and above whereas the low-cost GPS tracker proposed in this project will cost around 1600 BDT. The addition of the buzzer and the website on the low-cost GPS Tracker will be a revolution in the coastal areas of Bangladesh. With the large production of the low-cost GPS Tracker, the pricing per unit will be lowered considerably. The proposed prototype of the GPS tracker if went through different combinational parts will cost even lower and this will be worked on in the future to further reduce the cost.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128800734","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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