Pub Date : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9334012
Cong Tran, Won-Yong Shin
Due to practical reasons such as limited resources and privacy settings specified by users on social media, most network data tend to be only partially observed with both missing nodes and missing edges. Thus, it is of paramount importance to infer the missing parts of the networks since incomplete network data may severely degrade the performance of downstream analyses. In this paper, we provide a comprehensive survey on network completion, which is a more challenging task than the well-studied low-rank matrix completion problem in the sense that a row and a column of an adjacency matrix shall be entirely unobservable when a node is completely missing from the given network. Specifically, we first define the problem of network completion. Then, we review two state-of-the-art algorithms for discovering the missing part of an underlying network, namely KronEM and DeepNC. We also show a performance comparison between the two algorithms via experimental evaluation. Finally, we discuss the potentials and limitations of the two algorithms.
{"title":"Network Completion: Beyond Matrix Completion","authors":"Cong Tran, Won-Yong Shin","doi":"10.1109/ICOIN50884.2021.9334012","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9334012","url":null,"abstract":"Due to practical reasons such as limited resources and privacy settings specified by users on social media, most network data tend to be only partially observed with both missing nodes and missing edges. Thus, it is of paramount importance to infer the missing parts of the networks since incomplete network data may severely degrade the performance of downstream analyses. In this paper, we provide a comprehensive survey on network completion, which is a more challenging task than the well-studied low-rank matrix completion problem in the sense that a row and a column of an adjacency matrix shall be entirely unobservable when a node is completely missing from the given network. Specifically, we first define the problem of network completion. Then, we review two state-of-the-art algorithms for discovering the missing part of an underlying network, namely KronEM and DeepNC. We also show a performance comparison between the two algorithms via experimental evaluation. Finally, we discuss the potentials and limitations of the two algorithms.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"136 1","pages":"667-670"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75778800","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 : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9334026
P. Aravinda, S. Sooriyaarachchi, C. Gamage, N. Kottege
This paper proposes a method for RSSI based indoor localization and tracking in cluttered environments using Deep Neural Networks. We implemented a real-time system to localize people using wearable active RF tags and RF receivers fixed in an industrial environment with high RF noise. The proposed solution is advantageous in analysing RSSI data in cluttered-indoor environments with the presence of human body attenuation, signal distortion, and environmental noise. Simulations and experiments on a hardware testbed demonstrated that receiver arrangement, number of receivers and amount of line of sight signals captured by receivers are important parameters for improving localization and tracking accuracy. The effect of RF signal attenuation through the person who carries the tag was combined with two neural network models trained with RSSI data pertaining to two walking directions. This method was successful in predicting the walking direction of the person.
{"title":"Optimization of RSSI based indoor localization and tracking to monitor workers in a hazardous working zone using Machine Learning techniques","authors":"P. Aravinda, S. Sooriyaarachchi, C. Gamage, N. Kottege","doi":"10.1109/ICOIN50884.2021.9334026","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9334026","url":null,"abstract":"This paper proposes a method for RSSI based indoor localization and tracking in cluttered environments using Deep Neural Networks. We implemented a real-time system to localize people using wearable active RF tags and RF receivers fixed in an industrial environment with high RF noise. The proposed solution is advantageous in analysing RSSI data in cluttered-indoor environments with the presence of human body attenuation, signal distortion, and environmental noise. Simulations and experiments on a hardware testbed demonstrated that receiver arrangement, number of receivers and amount of line of sight signals captured by receivers are important parameters for improving localization and tracking accuracy. The effect of RF signal attenuation through the person who carries the tag was combined with two neural network models trained with RSSI data pertaining to two walking directions. This method was successful in predicting the walking direction of the person.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"36 1","pages":"305-310"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73856849","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 : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333984
Muhammad Diyan, Murad Khan, Zhenbo Cao, Bhagya Nathali Silva, Jihun Han, K. Han
The dynamic nature of the electricity market need an efficient energy management and control system to take perfect decisions accordingly. House hold appliances is the contemporary study being adopted to improve the performance and balance the fluctuation between power system and smart home. This article proposes an intelligent home energy management system (IHEMS) incorporated with a prediction model and optimization model. To address the uncertainty of future energy load and its cost, a suitable prediction model based on Bi-directional long short Term memory (Bi-LSTM) is contributed. In collaboration with the prediction model, an optimization model based on reinforcement learning is presented to schedule the home appliances by taking optimal decisions. To validate the performance of the proposed scheme, Intensive simulation is performed with adoptable, un-adoptable and manageable loads of household appliances. The results confirm that the proposed scheme address the problem of energy management for numerous appliances, reduce the total energy consumption with total energy bill and minimize the user comfort level.
{"title":"Intelligent Home Energy Management System based on Bi-directional Long-short Term Memory and Reinforcement Learning","authors":"Muhammad Diyan, Murad Khan, Zhenbo Cao, Bhagya Nathali Silva, Jihun Han, K. Han","doi":"10.1109/ICOIN50884.2021.9333984","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333984","url":null,"abstract":"The dynamic nature of the electricity market need an efficient energy management and control system to take perfect decisions accordingly. House hold appliances is the contemporary study being adopted to improve the performance and balance the fluctuation between power system and smart home. This article proposes an intelligent home energy management system (IHEMS) incorporated with a prediction model and optimization model. To address the uncertainty of future energy load and its cost, a suitable prediction model based on Bi-directional long short Term memory (Bi-LSTM) is contributed. In collaboration with the prediction model, an optimization model based on reinforcement learning is presented to schedule the home appliances by taking optimal decisions. To validate the performance of the proposed scheme, Intensive simulation is performed with adoptable, un-adoptable and manageable loads of household appliances. The results confirm that the proposed scheme address the problem of energy management for numerous appliances, reduce the total energy consumption with total energy bill and minimize the user comfort level.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"101 1","pages":"782-787"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73874162","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 : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9334018
Md. Faisal Ahmed, Md. Osman Ali, Md. Habibur Rahman, Y. Jang
A dramatic increase in internet-of-things-based remote health monitoring systems can be observed in recent times. The majority of them use a technology based on radio frequency (RF), whose adverse effects on human health are continuously addressed in the literature. We have designed a system using a pulse oximeter sensor to monitor the health conditions of the patient and transmit data through the LED and received using a camera. The camera captures the image and extracts the data from the receiver in the Python environment. The data is modulated using a color shift keying technique, and based on the different colors the data is retrieved from the receiver.
{"title":"Real-time health monitoring system design based on optical camera communication","authors":"Md. Faisal Ahmed, Md. Osman Ali, Md. Habibur Rahman, Y. Jang","doi":"10.1109/ICOIN50884.2021.9334018","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9334018","url":null,"abstract":"A dramatic increase in internet-of-things-based remote health monitoring systems can be observed in recent times. The majority of them use a technology based on radio frequency (RF), whose adverse effects on human health are continuously addressed in the literature. We have designed a system using a pulse oximeter sensor to monitor the health conditions of the patient and transmit data through the LED and received using a camera. The camera captures the image and extracts the data from the receiver in the Python environment. The data is modulated using a color shift keying technique, and based on the different colors the data is retrieved from the receiver.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"284 1","pages":"870-873"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72726210","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 : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333859
Seunghyun Lee, Changhee Joo
The Content Delivery Network (CDN) appears as a solution for the rapidly growing demand of Internet traffic. Through distributed surrogate servers, the CDN can manage higher traffic demand and improve the overall efficiency. Since the CDN is included in the conventional Internet traffic delivery chain, and becomes popular as a new passage between users and content providers, it starts playing a significant role in the market. In this paper, we investigate the strategies of the players in the Internet market with the CDN, taking into consideration the network factors that impacts on the players’ decision as well as the objective and the regulations.
{"title":"On the CDN Pricing Strategies in the Internet Traffic Delivery Chain","authors":"Seunghyun Lee, Changhee Joo","doi":"10.1109/ICOIN50884.2021.9333859","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333859","url":null,"abstract":"The Content Delivery Network (CDN) appears as a solution for the rapidly growing demand of Internet traffic. Through distributed surrogate servers, the CDN can manage higher traffic demand and improve the overall efficiency. Since the CDN is included in the conventional Internet traffic delivery chain, and becomes popular as a new passage between users and content providers, it starts playing a significant role in the market. In this paper, we investigate the strategies of the players in the Internet market with the CDN, taking into consideration the network factors that impacts on the players’ decision as well as the objective and the regulations.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"39 1","pages":"680-682"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73117682","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 : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333881
Tsuyoshi Arai, Y. Okabe, Yoshinori Matsumoto
CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) is commonly utilized as a technology for avoiding attacks to Web sites by bots. State-of-the-art CAPTCHAs vary in difficulty based on the client’s behavior, allowing for efficient bot detection without sacrificing simplicity. In this research, we focus on detecting bots by supervised machine learning from access-log time series in the past. We have analysed access logs to several Web services which are using a commercial cloud-based CAPTCHA service, Capy Puzzle CAPTCHA. Experiments show that bot detection in attacks over a month can be performed with high accuracy by precursory analysis of the access log in only the first day as training data. In addition, we have manually analyzed the data that are found to be False Positive in the discrimination results, and it is found that the proposed model actually detects access by bots, which had been overlooked in the first-stage manual discrimination of flags in preparation of training data.
{"title":"Precursory Analysis of Attack-Log Time Series by Machine Learning for Detecting Bots in CAPTCHA","authors":"Tsuyoshi Arai, Y. Okabe, Yoshinori Matsumoto","doi":"10.1109/ICOIN50884.2021.9333881","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333881","url":null,"abstract":"CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) is commonly utilized as a technology for avoiding attacks to Web sites by bots. State-of-the-art CAPTCHAs vary in difficulty based on the client’s behavior, allowing for efficient bot detection without sacrificing simplicity. In this research, we focus on detecting bots by supervised machine learning from access-log time series in the past. We have analysed access logs to several Web services which are using a commercial cloud-based CAPTCHA service, Capy Puzzle CAPTCHA. Experiments show that bot detection in attacks over a month can be performed with high accuracy by precursory analysis of the access log in only the first day as training data. In addition, we have manually analyzed the data that are found to be False Positive in the discrimination results, and it is found that the proposed model actually detects access by bots, which had been overlooked in the first-stage manual discrimination of flags in preparation of training data.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"14 1","pages":"295-300"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73261793","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 : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333962
Kazuya Anazawa, Toru Mano, Takeru Inoue, Atsushi Taniguchi, K. Mizuno
Transport networks are being used to exchange traffic among communication sites. Current transport networks are mostly static, because existing traffic patterns do not fluctuate wildly. However, given that demand fluctuations are likely to become significant due to the emerging diversity of network services, current static networks will have great difficulty in accommodating all future demands. In this paper, we propose a network architecture that can accommodate more demands by employing fiber cross-connects (FXCs) connected with dark fibers; FXCs, e.g., robotic patch panels and micro-electromechanical system, are optical switches that perform circuit-switching on a per-fiber basis. Because the FXCs can satisfy demand changes by reconfiguring the physical network topology, it can accommodate greater demand variations than traditional fixed networks; this is confirmed by numerical simulations. The reconfigurable network is particularly effective when the network has many nodes with significant demand fluctuations; it accommodates up to 2.5 times more demand than the fixed equivalent.
{"title":"Reconfigurable Transport Networks to Accommodate Much More Traffic Demand","authors":"Kazuya Anazawa, Toru Mano, Takeru Inoue, Atsushi Taniguchi, K. Mizuno","doi":"10.1109/ICOIN50884.2021.9333962","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333962","url":null,"abstract":"Transport networks are being used to exchange traffic among communication sites. Current transport networks are mostly static, because existing traffic patterns do not fluctuate wildly. However, given that demand fluctuations are likely to become significant due to the emerging diversity of network services, current static networks will have great difficulty in accommodating all future demands. In this paper, we propose a network architecture that can accommodate more demands by employing fiber cross-connects (FXCs) connected with dark fibers; FXCs, e.g., robotic patch panels and micro-electromechanical system, are optical switches that perform circuit-switching on a per-fiber basis. Because the FXCs can satisfy demand changes by reconfiguring the physical network topology, it can accommodate greater demand variations than traditional fixed networks; this is confirmed by numerical simulations. The reconfigurable network is particularly effective when the network has many nodes with significant demand fluctuations; it accommodates up to 2.5 times more demand than the fixed equivalent.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"155 1","pages":"361-366"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79812571","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 : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333957
Chalee Thammarat, Chian Techapanupreeda
Mobile payment protocols have attracted widespread attention over the past decade, due to advancements in digital technology. The use of these protocols in online industries can dramatically improve the quality of online services. However, the central issue of concern when utilizing these types of systems is their accountability, which ensures trust between the parties involved in payment transactions. It is, therefore, vital for researchers to investigate how to handle the accountability of mobile payment protocols. In this research, we introduce a secure mobile payment protocol to overcome this problem. Our payment protocol combines all the necessary security features, such as confidentiality, integrity, authentication, and authorization that are required to build trust among parties. In other words, is the properties of mutual authentication and non-repudiation are ensured, thus providing accountability. Our approach can resolve any conflicts that may arise in payment transactions between parties. To prove that the proposed protocol is correct and complete, we use the Scyther and AVISPA tools to verify our approach formally.
{"title":"A Secure Mobile Payment Protocol for Handling Accountability with Formal Verification","authors":"Chalee Thammarat, Chian Techapanupreeda","doi":"10.1109/ICOIN50884.2021.9333957","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333957","url":null,"abstract":"Mobile payment protocols have attracted widespread attention over the past decade, due to advancements in digital technology. The use of these protocols in online industries can dramatically improve the quality of online services. However, the central issue of concern when utilizing these types of systems is their accountability, which ensures trust between the parties involved in payment transactions. It is, therefore, vital for researchers to investigate how to handle the accountability of mobile payment protocols. In this research, we introduce a secure mobile payment protocol to overcome this problem. Our payment protocol combines all the necessary security features, such as confidentiality, integrity, authentication, and authorization that are required to build trust among parties. In other words, is the properties of mutual authentication and non-repudiation are ensured, thus providing accountability. Our approach can resolve any conflicts that may arise in payment transactions between parties. To prove that the proposed protocol is correct and complete, we use the Scyther and AVISPA tools to verify our approach formally.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"25 1","pages":"249-254"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80000002","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 : 2021-01-13DOI: 10.1109/ICOIN50884.2021.9333876
Su-keun Kwak, Joohyung Lee
As the development of smart cities, energy management systems have been changing from centralized management systems to distributed energy management systems for better energy efficiency. In the distributed energy management systems, while producing the energy from distributed users, there can be two types of users such that 1) users who have surplus energy generations and 2) users who lack energy generations compared to their demands. In this paper, to alleviate such imbalance of energy generation between distributed users, a peer to peer (P2P) based energy trading platform is proposed. Specifically, blockchain is one of emerging solutions in which transactions can be made reliably to achieve P2P transactions without any centralized broker intervention. Correspondingly, we implement the P2P energy trading platform under Ethereum’s smart contract for reliable trading. The energy generated from distributed users at the proposed platform can be traded by utilizing the characteristics of Decentralize Application. Specifically, we provide the details of implementations of the proposed platform, which includes both hardware platform and software platform. Further, we establish a web page and an mobile application for monitoring the transaction information such as transaction details and energy prices, which can enhance users’ accessibility. Finally, the demonstration of process of energy trading via web interface is represented.
{"title":"Implementation of Blockchain based P2P Energy Trading Platform","authors":"Su-keun Kwak, Joohyung Lee","doi":"10.1109/ICOIN50884.2021.9333876","DOIUrl":"https://doi.org/10.1109/ICOIN50884.2021.9333876","url":null,"abstract":"As the development of smart cities, energy management systems have been changing from centralized management systems to distributed energy management systems for better energy efficiency. In the distributed energy management systems, while producing the energy from distributed users, there can be two types of users such that 1) users who have surplus energy generations and 2) users who lack energy generations compared to their demands. In this paper, to alleviate such imbalance of energy generation between distributed users, a peer to peer (P2P) based energy trading platform is proposed. Specifically, blockchain is one of emerging solutions in which transactions can be made reliably to achieve P2P transactions without any centralized broker intervention. Correspondingly, we implement the P2P energy trading platform under Ethereum’s smart contract for reliable trading. The energy generated from distributed users at the proposed platform can be traded by utilizing the characteristics of Decentralize Application. Specifically, we provide the details of implementations of the proposed platform, which includes both hardware platform and software platform. Further, we establish a web page and an mobile application for monitoring the transaction information such as transaction details and energy prices, which can enhance users’ accessibility. Finally, the demonstration of process of energy trading via web interface is represented.","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"70 1","pages":"5-7"},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83734944","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 : 2021-01-13DOI: 10.1109/icoin50884.2021.9334031
{"title":"ICOIN 2021 Organizing Committee Memberse","authors":"","doi":"10.1109/icoin50884.2021.9334031","DOIUrl":"https://doi.org/10.1109/icoin50884.2021.9334031","url":null,"abstract":"","PeriodicalId":6741,"journal":{"name":"2021 International Conference on Information Networking (ICOIN)","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73456287","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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