Pub Date : 2021-04-01DOI: 10.1109/MSMC.2021.3062892
Fei-yue Wang, I. Rudas, Dongrui Wu, Xiao Wang, Yong Yuan, J. Zhang, Yidong Li, Gisele Bennett, Nazanin Bassiri-Gharb
This article describes several opportunities and synergies between the IEEE Council on Radio-Frequency Identification (CRFID) and IEEE Systems, Man, and Cybernetics Society (SMCS) to initiate a roadmap study and working plan for a new model of support and collaboration among IEEE Societies and Councils in the future. We hope this will stimulate more communication and discussion for deep and effective coordination and collaboration among IEEE Councils and Societies.
{"title":"Artificial Identification, Blockchain, Cyberphysical Social Systems, Digital Twins, and Parallel Intelligence: Opportunities and Synergies Between the IEEE Council on Radio-Frequency Identification and Systems, Man, and Cybernetics Society [Essay]","authors":"Fei-yue Wang, I. Rudas, Dongrui Wu, Xiao Wang, Yong Yuan, J. Zhang, Yidong Li, Gisele Bennett, Nazanin Bassiri-Gharb","doi":"10.1109/MSMC.2021.3062892","DOIUrl":"https://doi.org/10.1109/MSMC.2021.3062892","url":null,"abstract":"This article describes several opportunities and synergies between the IEEE Council on Radio-Frequency Identification (CRFID) and IEEE Systems, Man, and Cybernetics Society (SMCS) to initiate a roadmap study and working plan for a new model of support and collaboration among IEEE Societies and Councils in the future. We hope this will stimulate more communication and discussion for deep and effective coordination and collaboration among IEEE Councils and Societies.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"117 1","pages":"61-C4"},"PeriodicalIF":3.2,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77041315","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 : 2021-02-21DOI: 10.1109/MSMC.2021.3086989
Shadi Ghafghazi, Amarie Carnett, Leslie C. Neely, Arun Das, P. Rad
Autism spectrum disorder is a developmental disorder characterized by significant social, communication, and behavioral challenges. Individuals diagnosed with autism, intellectual, and developmental disabilities (AUIDD) typically require long-term care and targeted treatment and teaching. Effective treatment of AUIDD relies on efficient and careful behavioral observations done by trained applied behavioral analysts (ABAs). However, this process overburdens ABAs by requiring the clinicians to collect and analyze data, identify the problem behaviors, conduct pattern analysis to categorize and predict categorical outcomes, hypothesize responsiveness to treatments, and detect the effects of treatment plans. Successful integration of digital technologies into clinical decision-making pipelines and the advancements in automated decision making using artificial intelligence (AI) algorithms highlights the importance of augmenting teaching and treatments using novel algorithms and high-fidelity sensors. In this article, we present an AI-augmented learning and applied behavior analytics (AI-ABA) platform to provide personalized treatment and learning plans to AUIDD individuals. By defining systematic experiments along with automated data collection and analysis, AI-ABA can promote self-regulative behavior using reinforcement-based augmented or virtual reality and other mobile platforms. Thus, AI-ABA could assist clinicians to focus on making precise data-driven decisions and increase the quality of individualized interventions for individuals with AUIDD.
{"title":"AI-Augmented Behavior Analysis for Children With Developmental Disabilities: Building Toward Precision Treatment","authors":"Shadi Ghafghazi, Amarie Carnett, Leslie C. Neely, Arun Das, P. Rad","doi":"10.1109/MSMC.2021.3086989","DOIUrl":"https://doi.org/10.1109/MSMC.2021.3086989","url":null,"abstract":"Autism spectrum disorder is a developmental disorder characterized by significant social, communication, and behavioral challenges. Individuals diagnosed with autism, intellectual, and developmental disabilities (AUIDD) typically require long-term care and targeted treatment and teaching. Effective treatment of AUIDD relies on efficient and careful behavioral observations done by trained applied behavioral analysts (ABAs). However, this process overburdens ABAs by requiring the clinicians to collect and analyze data, identify the problem behaviors, conduct pattern analysis to categorize and predict categorical outcomes, hypothesize responsiveness to treatments, and detect the effects of treatment plans. Successful integration of digital technologies into clinical decision-making pipelines and the advancements in automated decision making using artificial intelligence (AI) algorithms highlights the importance of augmenting teaching and treatments using novel algorithms and high-fidelity sensors. In this article, we present an AI-augmented learning and applied behavior analytics (AI-ABA) platform to provide personalized treatment and learning plans to AUIDD individuals. By defining systematic experiments along with automated data collection and analysis, AI-ABA can promote self-regulative behavior using reinforcement-based augmented or virtual reality and other mobile platforms. Thus, AI-ABA could assist clinicians to focus on making precise data-driven decisions and increase the quality of individualized interventions for individuals with AUIDD.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"12 1","pages":"4-12"},"PeriodicalIF":3.2,"publicationDate":"2021-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87423405","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 : 2021-02-01DOI: 10.1109/MSMC.2021.3062018
P. Nardelli, Hafiz Majid Hussain, A. Narayanan, Yongheng Yang
Digitalization has led to radical changes in the distribution of goods across various sectors. The tendency is to move from traditional buyer-seller markets to subscriptionbased, on-demand "smart" matching platforms enabled by pervasive information and communications technologies (ICTs). The driving force behind this lies in the fact that assets, which were scarce in the past, are readily abundant, approaching a regime of zero marginal costs. This is also becoming a reality in electrified energy systems because of the substantial growth of distributed renewable energy sources, such as solar and wind; the increasing number of small-scale storage units, such as batteries and heat pumps; and the availability of flexible loads that enable demand-side management (DSM).
{"title":"Virtual Microgrid Management via Software-Defined Energy Network for Electricity Sharing: Benefits and Challenges","authors":"P. Nardelli, Hafiz Majid Hussain, A. Narayanan, Yongheng Yang","doi":"10.1109/MSMC.2021.3062018","DOIUrl":"https://doi.org/10.1109/MSMC.2021.3062018","url":null,"abstract":"Digitalization has led to radical changes in the distribution of goods across various sectors. The tendency is to move from traditional buyer-seller markets to subscriptionbased, on-demand \"smart\" matching platforms enabled by pervasive information and communications technologies (ICTs). The driving force behind this lies in the fact that assets, which were scarce in the past, are readily abundant, approaching a regime of zero marginal costs. This is also becoming a reality in electrified energy systems because of the substantial growth of distributed renewable energy sources, such as solar and wind; the increasing number of small-scale storage units, such as batteries and heat pumps; and the availability of flexible loads that enable demand-side management (DSM).","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"20 1","pages":"10-19"},"PeriodicalIF":3.2,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85177481","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 : 2021-01-14DOI: 10.1109/MSMC.2020.3035955
S. Nahavandi
{"title":"Using Technology to Overcome COVID-19 Challenges [Editorial]","authors":"S. Nahavandi","doi":"10.1109/MSMC.2020.3035955","DOIUrl":"https://doi.org/10.1109/MSMC.2020.3035955","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"20 1","pages":"3-3"},"PeriodicalIF":3.2,"publicationDate":"2021-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82569258","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 : 2021-01-01DOI: 10.1109/MSMC.2020.3017936
Tianyi Wang, Yanglei Gan, Scott D. Arena, Lubomir T. Chitkushev, Guanglan Zhang, Reza Rawassizadeh
There is growing consumer demand for digital technologies that help users track, motivate, and receive coaching for both aerobic and anaerobic activities. In this article, we provide a review of existing technological advances in tracking, coaching, and motivating users during indoor training in contexts such as gymnasiums. This study lists the advantages and limitations of various apparatuses and applications used for this purpose. Our review and discussion are intended to help entrepreneurs and engineers improve their products to better meet users? needs and aid researchers in identifying potential new areas.
{"title":"Advances for Indoor Fitness Tracking, Coaching, and Motivation: A Review of Existing Technological Advances","authors":"Tianyi Wang, Yanglei Gan, Scott D. Arena, Lubomir T. Chitkushev, Guanglan Zhang, Reza Rawassizadeh","doi":"10.1109/MSMC.2020.3017936","DOIUrl":"https://doi.org/10.1109/MSMC.2020.3017936","url":null,"abstract":"There is growing consumer demand for digital technologies that help users track, motivate, and receive coaching for both aerobic and anaerobic activities. In this article, we provide a review of existing technological advances in tracking, coaching, and motivating users during indoor training in contexts such as gymnasiums. This study lists the advantages and limitations of various apparatuses and applications used for this purpose. Our review and discussion are intended to help entrepreneurs and engineers improve their products to better meet users? needs and aid researchers in identifying potential new areas.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"59 1","pages":"4-14"},"PeriodicalIF":3.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85733490","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 : 2021-01-01DOI: 10.1109/MSMC.2020.3007131
Hossein Jamshidifarsani, S. Garbaya, T. Lim, P. Blazevic
The ability to read has become an indispensable skill in modern ages, and any reading difficulty, such as dyslexia, can seriously impair the aspirations of the individual. Orthographically opaque languages such as English lay a heavy burden on learners. In this article, a gamified intervention program for the remediation of dyslexia is proposed for opaque orthographies. Current technology-based approaches of reading acquisition in the literature lack sophistication in terms of training design, game design, and adaptivity. This approach is based on the principles of automaticity acquisition and the gamification of learning as well as intelligent instruction. For the latter, an optimization model is proposed to maximize the educational value of each training session while respecting the capabilities of each individual.
{"title":"Intelligent Games for Learning and the Remediation of Dyslexia: Using Automaticity Principles","authors":"Hossein Jamshidifarsani, S. Garbaya, T. Lim, P. Blazevic","doi":"10.1109/MSMC.2020.3007131","DOIUrl":"https://doi.org/10.1109/MSMC.2020.3007131","url":null,"abstract":"The ability to read has become an indispensable skill in modern ages, and any reading difficulty, such as dyslexia, can seriously impair the aspirations of the individual. Orthographically opaque languages such as English lay a heavy burden on learners. In this article, a gamified intervention program for the remediation of dyslexia is proposed for opaque orthographies. Current technology-based approaches of reading acquisition in the literature lack sophistication in terms of training design, game design, and adaptivity. This approach is based on the principles of automaticity acquisition and the gamification of learning as well as intelligent instruction. For the latter, an optimization model is proposed to maximize the educational value of each training session while respecting the capabilities of each individual.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"3 1","pages":"15-24"},"PeriodicalIF":3.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75503321","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 : 2021-01-01DOI: 10.1109/msmc.2021.3124031
{"title":"2021 Index IEEE Systems, Man, and Cybernetics Vol. 7","authors":"","doi":"10.1109/msmc.2021.3124031","DOIUrl":"https://doi.org/10.1109/msmc.2021.3124031","url":null,"abstract":"","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"8 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74371992","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 : 2021-01-01DOI: 10.1109/MSMC.2020.3012304
Richard A. Nelson, R. Roberts
Principal component analysis (PCA) has long been used in computer vision applications such as face recognition. Here, we present an overview of some variants of PCA, including 2D PCA (2DPCA), bidirectional 2DPCA (B2DPCA), and coupled subspace analysis (CSA). Unlike conventional PCA, the variants 2DPCA, B2DPCA, and CSA preserve the original image structure, often providing better recognition and reconstruction results than those obtained with PCA. This article considers the background for these techniques and steps involved in applying these methods, including typical preprocessing of sample images, algorithm description, and classification. These variants of PCA have been successfully used in a number of different areas such as identification of wood species, biometrics (not limited to face recognition), medical imaging, and image compression, to name a few examples; we briefly mention some of these to provide an idea of the scope of applications. We address some advantages and disadvantages of these variants in relation to PCA. Utilizing the Modified National Institute of Standards and Technology (MNIST) digits and Fashion-MNIST image sets, we demonstrate application of CSA for image recognition and reconstruction compared to PCA. Finally, we mention how these PCA variants fit into a more general framework using tensors.
{"title":"Some Multilinear Variants of Principal Component Analysis: Examples in Grayscale Image Recognition and Reconstruction","authors":"Richard A. Nelson, R. Roberts","doi":"10.1109/MSMC.2020.3012304","DOIUrl":"https://doi.org/10.1109/MSMC.2020.3012304","url":null,"abstract":"Principal component analysis (PCA) has long been used in computer vision applications such as face recognition. Here, we present an overview of some variants of PCA, including 2D PCA (2DPCA), bidirectional 2DPCA (B2DPCA), and coupled subspace analysis (CSA). Unlike conventional PCA, the variants 2DPCA, B2DPCA, and CSA preserve the original image structure, often providing better recognition and reconstruction results than those obtained with PCA. This article considers the background for these techniques and steps involved in applying these methods, including typical preprocessing of sample images, algorithm description, and classification. These variants of PCA have been successfully used in a number of different areas such as identification of wood species, biometrics (not limited to face recognition), medical imaging, and image compression, to name a few examples; we briefly mention some of these to provide an idea of the scope of applications. We address some advantages and disadvantages of these variants in relation to PCA. Utilizing the Modified National Institute of Standards and Technology (MNIST) digits and Fashion-MNIST image sets, we demonstrate application of CSA for image recognition and reconstruction compared to PCA. Finally, we mention how these PCA variants fit into a more general framework using tensors.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"3 1","pages":"25-35"},"PeriodicalIF":3.2,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76645001","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 : 2020-10-01DOI: 10.1109/MSMC.2019.2962226
Congcong Ma, Wenfeng Li, Raffaele Gravina, Juan Du, Qimeng Li, G. Fortino
In the emerging wearable world, a plethora of smart devices are being designed to facilitate our daily life. More activities, such as student learning, desk office work, or driving are requiring human beings to spend a significant portion of their daily life sitting on a chair. As a result, there is increasing interest in the development of technologies that monitor and support seated users. The most iconic examples of this are the smart chair and the smart cushion. To prompt users to maintain healthy sitting posture and to encourage them to have a short break after prolonged sitting, several studies focus on the detection, monitoring, and analysis of sitting postures. The smart cushion, in particular, is a very promising device in this context because it is noninvasive and can be conveniently deployed on the seat or backrest, making an ordinary chair, sofa, or even a car seat suddenly smart. This article reviews our previous research studies and the results related to sitting posture recognition using the smart cushion. We will show that very diversified applications can be enabled, spanning medical applications (e.g., back pain or pressure ulcers avoidance) and even human communication (body language detection).
{"title":"Smart Cushion-Based Activity Recognition: Prompting Users to Maintain a Healthy Seated Posture","authors":"Congcong Ma, Wenfeng Li, Raffaele Gravina, Juan Du, Qimeng Li, G. Fortino","doi":"10.1109/MSMC.2019.2962226","DOIUrl":"https://doi.org/10.1109/MSMC.2019.2962226","url":null,"abstract":"In the emerging wearable world, a plethora of smart devices are being designed to facilitate our daily life. More activities, such as student learning, desk office work, or driving are requiring human beings to spend a significant portion of their daily life sitting on a chair. As a result, there is increasing interest in the development of technologies that monitor and support seated users. The most iconic examples of this are the smart chair and the smart cushion. To prompt users to maintain healthy sitting posture and to encourage them to have a short break after prolonged sitting, several studies focus on the detection, monitoring, and analysis of sitting postures. The smart cushion, in particular, is a very promising device in this context because it is noninvasive and can be conveniently deployed on the seat or backrest, making an ordinary chair, sofa, or even a car seat suddenly smart. This article reviews our previous research studies and the results related to sitting posture recognition using the smart cushion. We will show that very diversified applications can be enabled, spanning medical applications (e.g., back pain or pressure ulcers avoidance) and even human communication (body language detection).","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"26 1","pages":"6-14"},"PeriodicalIF":3.2,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79129462","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 : 2020-10-01DOI: 10.1109/MSMC.2019.2961160
M. Palaniswami, A. S. Rao, Dheeraj Kumar, Punit Rathore, S. Rajasegarar
The Internet of Things (IoT) is playing a vital role in shaping today?s technological world, including our daily lives. By 2025, the number of connected devices due to the IoT is estimated to surpass a whopping 75 billion. It is a challenging task to discover, integrate, and interpret processed big data from such ubiquitously available heterogeneous and actively natural resources and devices. Cluster analysis of IoT-generated big data is essential for the meaningful interpretation of such complex data. However, we often have very limited knowledge of the number of clusters actually present in the given data. The problem of finding whether clusters are present even before applying clustering algorithms is termed the assessment of clustering tendency. In this article, we present a set of useful visual assessment of cluster tendency (VAT) tools and techniques developed with major contributions from James C. Bezdek. The article further highlights how these techniques are advancing the IoT through large-scale IoT implementations.
物联网(IoT)在塑造当今世界的过程中发挥着至关重要的作用。科技世界，包括我们的日常生活。到2025年，物联网连接设备的数量预计将超过750亿。从这种无处不在的异构和活跃的自然资源和设备中发现、整合和解释处理过的大数据是一项具有挑战性的任务。对物联网生成的大数据进行聚类分析对于有意义地解释此类复杂数据至关重要。然而，我们通常对给定数据中实际存在的簇的数量知之甚少。在应用聚类算法之前发现聚类是否存在的问题被称为聚类倾向的评估。在本文中，我们提出了一套有用的集群趋势(VAT)可视化评估工具和技术，这些工具和技术是由James C. Bezdek的主要贡献开发的。本文进一步强调了这些技术如何通过大规模物联网实施来推进物联网。
{"title":"The Role of Visual Assessment of Clusters for Big Data Analysis: From Real-World Internet of Things","authors":"M. Palaniswami, A. S. Rao, Dheeraj Kumar, Punit Rathore, S. Rajasegarar","doi":"10.1109/MSMC.2019.2961160","DOIUrl":"https://doi.org/10.1109/MSMC.2019.2961160","url":null,"abstract":"The Internet of Things (IoT) is playing a vital role in shaping today?s technological world, including our daily lives. By 2025, the number of connected devices due to the IoT is estimated to surpass a whopping 75 billion. It is a challenging task to discover, integrate, and interpret processed big data from such ubiquitously available heterogeneous and actively natural resources and devices. Cluster analysis of IoT-generated big data is essential for the meaningful interpretation of such complex data. However, we often have very limited knowledge of the number of clusters actually present in the given data. The problem of finding whether clusters are present even before applying clustering algorithms is termed the assessment of clustering tendency. In this article, we present a set of useful visual assessment of cluster tendency (VAT) tools and techniques developed with major contributions from James C. Bezdek. The article further highlights how these techniques are advancing the IoT through large-scale IoT implementations.","PeriodicalId":43649,"journal":{"name":"IEEE Systems Man and Cybernetics Magazine","volume":"42 1","pages":"45-53"},"PeriodicalIF":3.2,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80877572","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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