Pub Date : 2020-09-01DOI: 10.1109/SMARTCOMP50058.2020.00077
P. Bellini, Davide Nesi, P. Nesi, M. Soderi
In the context of Smart City, it is quite frequent the usage of Smart City API for providing services at web and mobile applications. Most of the solutions using Smart City APIs are focused on a single city. This means that passing from one city/area to another, the users must change application. This happens for the lack of interoperability among Smart City APIs and/or services. In this paper, the problem of federation of smart city services is addressed by proposing a solution for federating smart city APIs. To this end, a formal model has been proposed to federate API services, with efficiency, security, scalability, and capacity of managing overlapped areas of competence, distributed searches, etc. These features are typically not all satisfied by classic GIS solutions which federate the services at level of databases. The solution has been developed in the context of Snap4City European platform enhancing former Km4City API of Sii-Mobility national project with Snap4City (https://www.snap4city.org).
{"title":"Federation of Smart City Services via APIs","authors":"P. Bellini, Davide Nesi, P. Nesi, M. Soderi","doi":"10.1109/SMARTCOMP50058.2020.00077","DOIUrl":"https://doi.org/10.1109/SMARTCOMP50058.2020.00077","url":null,"abstract":"In the context of Smart City, it is quite frequent the usage of Smart City API for providing services at web and mobile applications. Most of the solutions using Smart City APIs are focused on a single city. This means that passing from one city/area to another, the users must change application. This happens for the lack of interoperability among Smart City APIs and/or services. In this paper, the problem of federation of smart city services is addressed by proposing a solution for federating smart city APIs. To this end, a formal model has been proposed to federate API services, with efficiency, security, scalability, and capacity of managing overlapped areas of competence, distributed searches, etc. These features are typically not all satisfied by classic GIS solutions which federate the services at level of databases. The solution has been developed in the context of Snap4City European platform enhancing former Km4City API of Sii-Mobility national project with Snap4City (https://www.snap4city.org).","PeriodicalId":346827,"journal":{"name":"2020 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133990413","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 : 2020-09-01DOI: 10.1109/SMARTCOMP50058.2020.00090
Zakaria Benomar, G. Campobello, F. Longo, Giovanni Merlino, A. Puliafito
Recently, Industrial Wireless Sensor Networks (IWSN) have gained a lot of interest from both research and industry communities as an evolution of WSN specifically tailored for Industry 4.0 applications and their requirements. Thanks to the set of benefits IWSN technology introduces, it is considered to be a sustainable solution for industrial system monitoring. Yet, this approach has several drawbacks stemming from the limited resources (i.e., compute and storage) available on-board network devices. Although Cloud-based WSN data management solutions are widely adopted, issues related to this approach persist (e.g., high latency, bandwidth consumption, storage costs). This paper introduces an innovative platform enhancing IWSN architectures by adding a processing layer at the network edge: an approach that follows the Fog Computing paradigm. Remote management and programmability of the Fog layer are only some of the most challenging requirements. We show how our approach is suitable for industrial scenarios by applying it to a representative use case, i.e., the monitoring of asynchronous electric motors.
{"title":"Fog-Enabled Industrial WSNs to Monitor Asynchronous Electric Motors","authors":"Zakaria Benomar, G. Campobello, F. Longo, Giovanni Merlino, A. Puliafito","doi":"10.1109/SMARTCOMP50058.2020.00090","DOIUrl":"https://doi.org/10.1109/SMARTCOMP50058.2020.00090","url":null,"abstract":"Recently, Industrial Wireless Sensor Networks (IWSN) have gained a lot of interest from both research and industry communities as an evolution of WSN specifically tailored for Industry 4.0 applications and their requirements. Thanks to the set of benefits IWSN technology introduces, it is considered to be a sustainable solution for industrial system monitoring. Yet, this approach has several drawbacks stemming from the limited resources (i.e., compute and storage) available on-board network devices. Although Cloud-based WSN data management solutions are widely adopted, issues related to this approach persist (e.g., high latency, bandwidth consumption, storage costs). This paper introduces an innovative platform enhancing IWSN architectures by adding a processing layer at the network edge: an approach that follows the Fog Computing paradigm. Remote management and programmability of the Fog layer are only some of the most challenging requirements. We show how our approach is suitable for industrial scenarios by applying it to a representative use case, i.e., the monitoring of asynchronous electric motors.","PeriodicalId":346827,"journal":{"name":"2020 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"449 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134299967","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 : 2020-09-01DOI: 10.1109/SMARTCOMP50058.2020.00088
Bipendra Basnyat, Neha Singh, Nirmalya Roy, A. Gangopadhyay
Successful implementation of the Internet of Thing (IoT) is precursory to a thriving smart city. However, the technical, physical, and environmental conditions can often pose challenges in their successful deployments. The deployment is further complicated if the time and location of implementation are amidst a natural disaster. In this work, we use flash flood detection as a natural hazard testbed and describe various IoT deployment, our progression, and first-hand experience from those implementations. We compare and contrast three IoTs and their performance in real-time execution. Next, we discuss systems architecture and their end-to-end design and present lessons learned from these heterogeneous deployments. Additionally, we evaluate and outline our observations, challenges, and opportunities for further improvement. We also formulate standard evaluation metrics for their scoring and document our deployment journey.
{"title":"Design and Deployment of a Flash Flood Monitoring IoT: Challenges and Opportunities","authors":"Bipendra Basnyat, Neha Singh, Nirmalya Roy, A. Gangopadhyay","doi":"10.1109/SMARTCOMP50058.2020.00088","DOIUrl":"https://doi.org/10.1109/SMARTCOMP50058.2020.00088","url":null,"abstract":"Successful implementation of the Internet of Thing (IoT) is precursory to a thriving smart city. However, the technical, physical, and environmental conditions can often pose challenges in their successful deployments. The deployment is further complicated if the time and location of implementation are amidst a natural disaster. In this work, we use flash flood detection as a natural hazard testbed and describe various IoT deployment, our progression, and first-hand experience from those implementations. We compare and contrast three IoTs and their performance in real-time execution. Next, we discuss systems architecture and their end-to-end design and present lessons learned from these heterogeneous deployments. Additionally, we evaluate and outline our observations, challenges, and opportunities for further improvement. We also formulate standard evaluation metrics for their scoring and document our deployment journey.","PeriodicalId":346827,"journal":{"name":"2020 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134339646","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 : 2020-09-01DOI: 10.1109/SMARTCOMP50058.2020.00057
F. D. Rienzo, A. Virdis, C. Vallati, N. Carbonaro, A. Tognetti
Recent Information Technologies are progressively dramatically changing how industrial processes are carried out. This is leading to a new industrial revolution, Industry 4.0, in which productivity, efficiency and safety are improved significantly. Safety of workers and operators, in particular, is expected to improve thanks to pervasive technologies like wearable devices and sensors. In this paper we present a demo of a sensorized glove for industrial safety based on Near-Field Communication (NFC). The demonstration is a proof-of-concept implementation that shows how an NFC-enabled sensor installed in the glove of a worker can be exploited to monitor worker's action and report dangerous situations in advance in order to prevent accidents and injuries.
{"title":"A sensorized glove for industrial safety based on Near-Field Communication","authors":"F. D. Rienzo, A. Virdis, C. Vallati, N. Carbonaro, A. Tognetti","doi":"10.1109/SMARTCOMP50058.2020.00057","DOIUrl":"https://doi.org/10.1109/SMARTCOMP50058.2020.00057","url":null,"abstract":"Recent Information Technologies are progressively dramatically changing how industrial processes are carried out. This is leading to a new industrial revolution, Industry 4.0, in which productivity, efficiency and safety are improved significantly. Safety of workers and operators, in particular, is expected to improve thanks to pervasive technologies like wearable devices and sensors. In this paper we present a demo of a sensorized glove for industrial safety based on Near-Field Communication (NFC). The demonstration is a proof-of-concept implementation that shows how an NFC-enabled sensor installed in the glove of a worker can be exploited to monitor worker's action and report dangerous situations in advance in order to prevent accidents and injuries.","PeriodicalId":346827,"journal":{"name":"2020 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129998315","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 : 2020-09-01DOI: 10.1109/SMARTCOMP50058.2020.00084
R. Spina, Andrea Fornaia, E. Tramontana
Forecasting of imminent seismic and/or volcanic events can drastically reduce the loss of human life by evacuating the inhabitants residing in the neighboring areas. An integrated system, called Volcano-Seismic Early Warning (VSEW), is proposed, capable of classifying the alarm scenario in three levels (soft, medium and hard) for the forecast of seismic-volcanic phenomena of medium-high intensity. The system is based on threshold levels, calculated statistically, of some seismic and volcanic precursors (historical and recent earthquakes, volcanic tremor, concentration of magmatic gases, soil temperature). In active volcanic areas, the analysis of satellite images can highlight the soil temperature gradients between adjacent crustal areas, which is a critical criterion for identifying deep thermal anomalies linked to the rise of magmatic bodies. After being processed by a central server, the selected geological data are made available to mobile devices (smartphones, tablets, notebooks) to which they are presented in graphs and tables. An acoustic-luminous alarm will warn the user when the threshold values of one or more geophysical parameters have been reached or exceeded: the intensity of the signal emitted will be proportional to the risk of a potential eruption or earthquake. The implementation of this system aims at providing a valid alert instrument in areas characterized by high volcanic and seismic risk.
{"title":"VSEW: an early warning system for volcanic and seismic events","authors":"R. Spina, Andrea Fornaia, E. Tramontana","doi":"10.1109/SMARTCOMP50058.2020.00084","DOIUrl":"https://doi.org/10.1109/SMARTCOMP50058.2020.00084","url":null,"abstract":"Forecasting of imminent seismic and/or volcanic events can drastically reduce the loss of human life by evacuating the inhabitants residing in the neighboring areas. An integrated system, called Volcano-Seismic Early Warning (VSEW), is proposed, capable of classifying the alarm scenario in three levels (soft, medium and hard) for the forecast of seismic-volcanic phenomena of medium-high intensity. The system is based on threshold levels, calculated statistically, of some seismic and volcanic precursors (historical and recent earthquakes, volcanic tremor, concentration of magmatic gases, soil temperature). In active volcanic areas, the analysis of satellite images can highlight the soil temperature gradients between adjacent crustal areas, which is a critical criterion for identifying deep thermal anomalies linked to the rise of magmatic bodies. After being processed by a central server, the selected geological data are made available to mobile devices (smartphones, tablets, notebooks) to which they are presented in graphs and tables. An acoustic-luminous alarm will warn the user when the threshold values of one or more geophysical parameters have been reached or exceeded: the intensity of the signal emitted will be proportional to the risk of a potential eruption or earthquake. The implementation of this system aims at providing a valid alert instrument in areas characterized by high volcanic and seismic risk.","PeriodicalId":346827,"journal":{"name":"2020 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129486972","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 : 2020-09-01DOI: 10.1109/SMARTCOMP50058.2020.00035
Munshi Yusuf Alam, H. Anurag, Md. Shahrukh Imam, Sujoy Saha, M. Saha, S. Nandi, Sandip Chakraborty
Existing street light monitoring systems use vehicle-borne sensor platforms, LiDAR etc. which are obtrusive for in-the-wild deployments. In this paper, we propose BikeL; a crowd sensed system to monitor street lighting conditions in a novel approach using smartphone sensors during Bike navigation. We identify the underlying issues and challenges from pilot experiments to make the system phone-invariant, robust, and user-friendly. We used regression models and unsupervised clustering to resolve these issues. We have carried out extensive experiments under various road type illumination scenarios and phones type covering more than 400 km. Over 80 night trips collecting 10,000 functional light pole samples to tune the system parameters. Results show that the overall system successfully detects both functioning and non-functioning light poles with good accuracy (F1 score > 0.85) and can produce uniformly calibrated illumination levels. This viable, economical, and easy to deploy solution can work effectively for under-developed regions of low and middle-economy countries.
{"title":"Urban Safety as a Service During Bike Navigation: My Smartphone Can Monitor My Street-Lights","authors":"Munshi Yusuf Alam, H. Anurag, Md. Shahrukh Imam, Sujoy Saha, M. Saha, S. Nandi, Sandip Chakraborty","doi":"10.1109/SMARTCOMP50058.2020.00035","DOIUrl":"https://doi.org/10.1109/SMARTCOMP50058.2020.00035","url":null,"abstract":"Existing street light monitoring systems use vehicle-borne sensor platforms, LiDAR etc. which are obtrusive for in-the-wild deployments. In this paper, we propose BikeL; a crowd sensed system to monitor street lighting conditions in a novel approach using smartphone sensors during Bike navigation. We identify the underlying issues and challenges from pilot experiments to make the system phone-invariant, robust, and user-friendly. We used regression models and unsupervised clustering to resolve these issues. We have carried out extensive experiments under various road type illumination scenarios and phones type covering more than 400 km. Over 80 night trips collecting 10,000 functional light pole samples to tune the system parameters. Results show that the overall system successfully detects both functioning and non-functioning light poles with good accuracy (F1 score > 0.85) and can produce uniformly calibrated illumination levels. This viable, economical, and easy to deploy solution can work effectively for under-developed regions of low and middle-economy countries.","PeriodicalId":346827,"journal":{"name":"2020 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127623650","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}
Wearable robots provide a unique opportunity for exosuits to stimulate enhanced stability and strength. The problem is creating an exoskeleton suit for users that is powerful, but lightweight, portable, and accessible for different body shapes. The actuators' position to control the suit's movement dramatically affects how much force an exoskeleton suit can exert. In this preliminary paper, we present a simulation approach for finding optimal actuation positions towards a bio-inspired exoskeleton. This modular approach leads towards custom design of actuator positioning based on bodily measurements. We discuss our approach through modeling a soft exosuit designed for upper- extremity movement.
{"title":"Designing User-Specific Soft Robotic Wearable Muscular Interfaces with Iterative Simulation","authors":"Tiffany-Ellen Vo, Rohan Jhangiani, Ash Robbins, Aviv Elor","doi":"10.1109/SMARTCOMP50058.2020.00056","DOIUrl":"https://doi.org/10.1109/SMARTCOMP50058.2020.00056","url":null,"abstract":"Wearable robots provide a unique opportunity for exosuits to stimulate enhanced stability and strength. The problem is creating an exoskeleton suit for users that is powerful, but lightweight, portable, and accessible for different body shapes. The actuators' position to control the suit's movement dramatically affects how much force an exoskeleton suit can exert. In this preliminary paper, we present a simulation approach for finding optimal actuation positions towards a bio-inspired exoskeleton. This modular approach leads towards custom design of actuator positioning based on bodily measurements. We discuss our approach through modeling a soft exosuit designed for upper- extremity movement.","PeriodicalId":346827,"journal":{"name":"2020 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117014646","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 : 2020-09-01DOI: 10.1109/smartcomp50058.2020.00013
David Kirk
Bio David Kirk has been NVIDIA's Chief Scientist since January 1997. His contribution includes leading NVIDIA graphics technology development for today's most popular consumer entertainment platforms. In 2002, Dr. Kirk received the SIGGRAPH Computer Graphics Achievement Award for his role in bringing high-performance computer graphics systems to the mass market.
David Kirk自1997年1月起担任NVIDIA首席科学家。他的贡献包括为当今最流行的消费娱乐平台领导NVIDIA图形技术开发。2002年，Kirk博士因将高性能计算机图形系统引入大众市场而获得SIGGRAPH计算机图形成就奖。
{"title":"Keynote Talk","authors":"David Kirk","doi":"10.1109/smartcomp50058.2020.00013","DOIUrl":"https://doi.org/10.1109/smartcomp50058.2020.00013","url":null,"abstract":"Bio David Kirk has been NVIDIA's Chief Scientist since January 1997. His contribution includes leading NVIDIA graphics technology development for today's most popular consumer entertainment platforms. In 2002, Dr. Kirk received the SIGGRAPH Computer Graphics Achievement Award for his role in bringing high-performance computer graphics systems to the mass market.","PeriodicalId":346827,"journal":{"name":"2020 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117131028","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 : 2020-09-01DOI: 10.1109/SMARTCOMP50058.2020.00033
Christine Bassem
In Mobile Crowd Sensing (MCS) platforms, users are typically human participants who willingly take time out of their daily schedules to complete sensing tasks. Albeit the unreliable nature of human's behavior, existing task allocation mechanisms proposed within MCS platforms typically assume that participants will accept the tasks allocated to them and complete them successfully, which in turn affects the realized quality of task completion. In this paper, we define a novel participation reliability metric, which forgives erratic misbehavior but doesn't forget if it's repeated. Moreover, to incentivize participants to be more reliable, we integrate the defined reliability metric into an online multi-task allocation mechanism, associated with a rational payment model. Finally, we theoretically analyze the proposed components and evaluate their performance on synthesized mobility traces.
{"title":"Forgive But Don't Forget: On Reliable Multi-Task Allocation in Mobile CrowdSensing Platforms","authors":"Christine Bassem","doi":"10.1109/SMARTCOMP50058.2020.00033","DOIUrl":"https://doi.org/10.1109/SMARTCOMP50058.2020.00033","url":null,"abstract":"In Mobile Crowd Sensing (MCS) platforms, users are typically human participants who willingly take time out of their daily schedules to complete sensing tasks. Albeit the unreliable nature of human's behavior, existing task allocation mechanisms proposed within MCS platforms typically assume that participants will accept the tasks allocated to them and complete them successfully, which in turn affects the realized quality of task completion. In this paper, we define a novel participation reliability metric, which forgives erratic misbehavior but doesn't forget if it's repeated. Moreover, to incentivize participants to be more reliable, we integrate the defined reliability metric into an online multi-task allocation mechanism, associated with a rational payment model. Finally, we theoretically analyze the proposed components and evaluate their performance on synthesized mobility traces.","PeriodicalId":346827,"journal":{"name":"2020 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115356848","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 : 2020-09-01DOI: 10.1109/smartcomp50058.2020.00011
{"title":"Message from the General Chairs and TPC Chairs","authors":"","doi":"10.1109/smartcomp50058.2020.00011","DOIUrl":"https://doi.org/10.1109/smartcomp50058.2020.00011","url":null,"abstract":"","PeriodicalId":346827,"journal":{"name":"2020 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125256079","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：