Pub Date : 2019-06-01DOI: 10.1109/MECO.2019.8760147
J. Gialelis, G. Theodorou, Maria Fokaeos, Dimitrios Karadimas
This work depicts the concept and methodology as well as the architecture and physical implementation of a low-cost Internet of Things (IoT) node for customized smart-applications. The presented node efficiently integrates state-of-the-art discrete electronic components able to support a variety of smart applications. The node comprises an ARM CortexM based microcontroller designed for low power wireless applications, a power management unit and several sensors for which special adapters have been implemented. The proposed IoT node is being validated in vineyard fields, in the framework of precision agriculture practice, with the aim of collecting critical environmental parameters, to be used as input to algorithmic models for the detection and subsequently prevention of related agricultural diseases.
{"title":"An Integrated Low Cost IoT Node based on Discrete Components for Customized Smart Applications; Use case on Precision Agriculture","authors":"J. Gialelis, G. Theodorou, Maria Fokaeos, Dimitrios Karadimas","doi":"10.1109/MECO.2019.8760147","DOIUrl":"https://doi.org/10.1109/MECO.2019.8760147","url":null,"abstract":"This work depicts the concept and methodology as well as the architecture and physical implementation of a low-cost Internet of Things (IoT) node for customized smart-applications. The presented node efficiently integrates state-of-the-art discrete electronic components able to support a variety of smart applications. The node comprises an ARM CortexM based microcontroller designed for low power wireless applications, a power management unit and several sensors for which special adapters have been implemented. The proposed IoT node is being validated in vineyard fields, in the framework of precision agriculture practice, with the aim of collecting critical environmental parameters, to be used as input to algorithmic models for the detection and subsequently prevention of related agricultural diseases.","PeriodicalId":141324,"journal":{"name":"2019 8th Mediterranean Conference on Embedded Computing (MECO)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134030929","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 : 2019-06-01DOI: 10.1109/MECO.2019.8760140
M. Vukcevic, V. Popović, E. Dervic
In this paper two clustering algorithms DBSCAN and CLARA were applied over the pedological database of Montenegro. Both algorithms clusterize data based on their density distribution. DBSCAN enables discovering clusters of arbitary shapes, without domain knowledge. On the other hand, CLARA forms clusters of approximatly equal size and shape for databases with uniformly spaced data. The used databases is composed of chemical and mechanical-physical parameters of soil samples. There are no clear transitions between different types of soil and large differences in values of their parameters at the boundary points of the clusters. Thus, CLARA is proved to be better for clustering pedologic data, which is confirmed by means of simulations. The results obtained by the CLARA are comparable with the results obtained by the analysis of soil in Montenegro by the expert.
{"title":"DBSCAN and CLARA Clustering Algorithms and their usage for the Soil Data Clustering","authors":"M. Vukcevic, V. Popović, E. Dervic","doi":"10.1109/MECO.2019.8760140","DOIUrl":"https://doi.org/10.1109/MECO.2019.8760140","url":null,"abstract":"In this paper two clustering algorithms DBSCAN and CLARA were applied over the pedological database of Montenegro. Both algorithms clusterize data based on their density distribution. DBSCAN enables discovering clusters of arbitary shapes, without domain knowledge. On the other hand, CLARA forms clusters of approximatly equal size and shape for databases with uniformly spaced data. The used databases is composed of chemical and mechanical-physical parameters of soil samples. There are no clear transitions between different types of soil and large differences in values of their parameters at the boundary points of the clusters. Thus, CLARA is proved to be better for clustering pedologic data, which is confirmed by means of simulations. The results obtained by the CLARA are comparable with the results obtained by the analysis of soil in Montenegro by the expert.","PeriodicalId":141324,"journal":{"name":"2019 8th Mediterranean Conference on Embedded Computing (MECO)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125005270","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 : 2019-06-01DOI: 10.1109/MECO.2019.8760187
R. Giorgi, Nicola Bettin, S. Ermini, Francesco Montefoschi, A. Rizzo
In this paper, we describe our methodology for designing a smart doorbell system for the homes. While the recent trend of big companies is to offer a home voice assistant, which can integrate all possible services, including the recognition of the owner (or authorized people) at the house door, privacy concerns and independence from a single service provider are requiring more freedom in the choice of the “smart objects” that surround us. The doorbell system is using both iris and voice recognition to verify the identity of the user who rings at the door. Since there is the involvement of biometric data, this information has to be properly handled. In particular, we designed our system in such a way that it can avoid to send or store any biometric data to the cloud. Machine-learning algorithms are used to perform local computations, thus implementing Edge-Computing analytics to determine the identity of the user, by combining both voice and iris biometrics. The system is implemented on reconfigurable hardware in order to accelerate some of the most intensive tasks and achieve enough performance at a reasonable power consumption. Our tests confirm that, by using our architecture, the performance is about 5x the sequential case and, at the same time, we reach about 7x less energy consumption.
{"title":"An Iris+Voice Recognition System for a Smart Doorbell","authors":"R. Giorgi, Nicola Bettin, S. Ermini, Francesco Montefoschi, A. Rizzo","doi":"10.1109/MECO.2019.8760187","DOIUrl":"https://doi.org/10.1109/MECO.2019.8760187","url":null,"abstract":"In this paper, we describe our methodology for designing a smart doorbell system for the homes. While the recent trend of big companies is to offer a home voice assistant, which can integrate all possible services, including the recognition of the owner (or authorized people) at the house door, privacy concerns and independence from a single service provider are requiring more freedom in the choice of the “smart objects” that surround us. The doorbell system is using both iris and voice recognition to verify the identity of the user who rings at the door. Since there is the involvement of biometric data, this information has to be properly handled. In particular, we designed our system in such a way that it can avoid to send or store any biometric data to the cloud. Machine-learning algorithms are used to perform local computations, thus implementing Edge-Computing analytics to determine the identity of the user, by combining both voice and iris biometrics. The system is implemented on reconfigurable hardware in order to accelerate some of the most intensive tasks and achieve enough performance at a reasonable power consumption. Our tests confirm that, by using our architecture, the performance is about 5x the sequential case and, at the same time, we reach about 7x less energy consumption.","PeriodicalId":141324,"journal":{"name":"2019 8th Mediterranean Conference on Embedded Computing (MECO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132296065","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 : 2019-06-01DOI: 10.1109/MECO.2019.8760200
R. Giorgi, David Oro, S. Ermini, Francesco Montefoschi, A. Rizzo
In this paper, we describe our methodology for designing a smart Videosurveillance system for face analysis. The system aims at increasing the security by gathering demographic statistics in highly crowded areas such as train stations, airports and shopping malls. Based on Convolutional Neural Networks (CNNs), the system architecture relies on the reconfigurable hardware to accelerate part of the computation and reduce the power consumption compared to general-purpose processors and GPUs. To achieve easy programmability, the platform makes use of the OmpSs programming model, which provides parallelization and acceleration by using simple directives to be added to the sequential code. The rsource-intensive tasks are offloaded to the reconfigurable hardware in order to achieve the desired performance levels. Our evaluation shows that we can detect more than 600 faces per frame, while keeping the power consumption at about 8W. The tests were performed by using the AXIOM hardware/software platform.
{"title":"Embedded Face Analysis for Smart Videosurveillance","authors":"R. Giorgi, David Oro, S. Ermini, Francesco Montefoschi, A. Rizzo","doi":"10.1109/MECO.2019.8760200","DOIUrl":"https://doi.org/10.1109/MECO.2019.8760200","url":null,"abstract":"In this paper, we describe our methodology for designing a smart Videosurveillance system for face analysis. The system aims at increasing the security by gathering demographic statistics in highly crowded areas such as train stations, airports and shopping malls. Based on Convolutional Neural Networks (CNNs), the system architecture relies on the reconfigurable hardware to accelerate part of the computation and reduce the power consumption compared to general-purpose processors and GPUs. To achieve easy programmability, the platform makes use of the OmpSs programming model, which provides parallelization and acceleration by using simple directives to be added to the sequential code. The rsource-intensive tasks are offloaded to the reconfigurable hardware in order to achieve the desired performance levels. Our evaluation shows that we can detect more than 600 faces per frame, while keeping the power consumption at about 8W. The tests were performed by using the AXIOM hardware/software platform.","PeriodicalId":141324,"journal":{"name":"2019 8th Mediterranean Conference on Embedded Computing (MECO)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133757719","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 : 2019-06-01DOI: 10.1109/MECO.2019.8760179
A. Sokolov, T. Fetisova, A. Bakulev, M. Bakuleva
This paper presents the approach to finding the optimal path for the number of criteria in the transport network. The aim of the work is the development of the algorithm for finding the optimal path capable of solving this problem in the conditions of constantly changing external factors. As such factors, the most common metrics are chosen - travel time and throughput. As a mathematical model reflecting the dynamics of external factors, the tensor model is used. It is based on the dynamic Floyd - Warshall algorithm for finding the shortest distances between all the vertices of a weighted oriented graph. The developed algorithm is modified for the iterative analysis of paths in the graph and finding the optimal one with constant changes in throughput.
{"title":"Development of the Algorithm for Finding the Optimal Path in a Transport Network with Dynamic Parameters based on the Multidimensional Data Model","authors":"A. Sokolov, T. Fetisova, A. Bakulev, M. Bakuleva","doi":"10.1109/MECO.2019.8760179","DOIUrl":"https://doi.org/10.1109/MECO.2019.8760179","url":null,"abstract":"This paper presents the approach to finding the optimal path for the number of criteria in the transport network. The aim of the work is the development of the algorithm for finding the optimal path capable of solving this problem in the conditions of constantly changing external factors. As such factors, the most common metrics are chosen - travel time and throughput. As a mathematical model reflecting the dynamics of external factors, the tensor model is used. It is based on the dynamic Floyd - Warshall algorithm for finding the shortest distances between all the vertices of a weighted oriented graph. The developed algorithm is modified for the iterative analysis of paths in the graph and finding the optimal one with constant changes in throughput.","PeriodicalId":141324,"journal":{"name":"2019 8th Mediterranean Conference on Embedded Computing (MECO)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121014086","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 : 2019-06-01DOI: 10.1109/MECO.2019.8760198
E. Zaev, D. Babunski, D. Trajkovski, V. Iliev, L. Trajkovski
New digital control systems open new possibilities in many areas. It is here presented design and implementation of a real-time optimal positioning and data collecting system in a newly designed laboratory wind tunnel. The wind tunnel has the possibility of changing the wind intensity in the tunnel. The control system positions the aerodynamic profile in different positions and measures the pressure along the profile in 14 points. All these data are stored in real-time in the SCADA system. This enables automatic finding of the optimum position of the profile according to various parameters: smallest resistance, maximum lifting force, smallest draft force and etc. It also allows students as well as researchers to view data in the form of graphs or tables in real-time as well as additional later offline process and review of the saved data.
{"title":"Real-Time Positioning and Data Collecting System for Aerodynamic Profiles","authors":"E. Zaev, D. Babunski, D. Trajkovski, V. Iliev, L. Trajkovski","doi":"10.1109/MECO.2019.8760198","DOIUrl":"https://doi.org/10.1109/MECO.2019.8760198","url":null,"abstract":"New digital control systems open new possibilities in many areas. It is here presented design and implementation of a real-time optimal positioning and data collecting system in a newly designed laboratory wind tunnel. The wind tunnel has the possibility of changing the wind intensity in the tunnel. The control system positions the aerodynamic profile in different positions and measures the pressure along the profile in 14 points. All these data are stored in real-time in the SCADA system. This enables automatic finding of the optimum position of the profile according to various parameters: smallest resistance, maximum lifting force, smallest draft force and etc. It also allows students as well as researchers to view data in the form of graphs or tables in real-time as well as additional later offline process and review of the saved data.","PeriodicalId":141324,"journal":{"name":"2019 8th Mediterranean Conference on Embedded Computing (MECO)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116121354","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 : 2019-06-01DOI: 10.1109/MECO.2019.8760203
E. Kurbatova, V. A. Laylina
Extraction of roads from high resolution satellite images has an important role in such tasks as urban planning, traffic management, navigation, map updating and etc. This paper presents an automatic method for roads extraction from satellite images. The proposed approach uses the method of edge segmentation on the bases of two-dimensional Markov chains. The original image is converted to the Lab color space, and the B component is used for edge detection. We use colour feature and threshold processing to separate the resulting segments into roads and backgrounds. To improve the quality of road extraction, the filtering by region size, skeletonization and morphological operations are used at the post-processing stage. Experimental results show the effectiveness of the proposed approach.
{"title":"Detection of Roads from Images Based on Edge Segmentation and Morphological Operations","authors":"E. Kurbatova, V. A. Laylina","doi":"10.1109/MECO.2019.8760203","DOIUrl":"https://doi.org/10.1109/MECO.2019.8760203","url":null,"abstract":"Extraction of roads from high resolution satellite images has an important role in such tasks as urban planning, traffic management, navigation, map updating and etc. This paper presents an automatic method for roads extraction from satellite images. The proposed approach uses the method of edge segmentation on the bases of two-dimensional Markov chains. The original image is converted to the Lab color space, and the B component is used for edge detection. We use colour feature and threshold processing to separate the resulting segments into roads and backgrounds. To improve the quality of road extraction, the filtering by region size, skeletonization and morphological operations are used at the post-processing stage. Experimental results show the effectiveness of the proposed approach.","PeriodicalId":141324,"journal":{"name":"2019 8th Mediterranean Conference on Embedded Computing (MECO)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125061880","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 : 2019-06-01DOI: 10.1109/MECO.2019.8760287
Rana H. ElMaraashly, G. Alkady, R. Daoud, Hassan H. Halawa, H. Amer, I. Adly, T. Refaat
As Networked Control Systems grow more complex in industrial applications, moving network modules and cabling decrease overall system reliability. This paper presents an FPGA-based fault tolerance technique to reduce cabling and increase the overall reliability of such a system. A sectored sensor-to-actuator networked control system architecture with sensor-level sift-out modular redundancy is modeled and analyzed. The fault models considered in this study are Single Event Upsets and hard failures. A reliability analysis is then conducted to evaluate the reliability of each block in the system and study the overall system reliability. A generic reliability analysis is presented to investigate the flexibility of the fault tolerance technique and a case study demonstrates the reliability improvements over a system that does not utilize FPGAs and cable reduction.
{"title":"On the Reliability and Flexibility of FPGAs for Fault Tolerance in Sectored Networked Control Systems","authors":"Rana H. ElMaraashly, G. Alkady, R. Daoud, Hassan H. Halawa, H. Amer, I. Adly, T. Refaat","doi":"10.1109/MECO.2019.8760287","DOIUrl":"https://doi.org/10.1109/MECO.2019.8760287","url":null,"abstract":"As Networked Control Systems grow more complex in industrial applications, moving network modules and cabling decrease overall system reliability. This paper presents an FPGA-based fault tolerance technique to reduce cabling and increase the overall reliability of such a system. A sectored sensor-to-actuator networked control system architecture with sensor-level sift-out modular redundancy is modeled and analyzed. The fault models considered in this study are Single Event Upsets and hard failures. A reliability analysis is then conducted to evaluate the reliability of each block in the system and study the overall system reliability. A generic reliability analysis is presented to investigate the flexibility of the fault tolerance technique and a case study demonstrates the reliability improvements over a system that does not utilize FPGAs and cable reduction.","PeriodicalId":141324,"journal":{"name":"2019 8th Mediterranean Conference on Embedded Computing (MECO)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121506275","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 : 2019-06-01DOI: 10.1109/MECO.2019.8760014
Dmitry A. Kolchaev, A. I. Efimov, Dmitry I. Ustukov
The work discusses basic image contrasting algorithms and noise compensation methods, an algorithm for estimating image quality based on an integral quality indicator, as well as approaches for estimating noise values in images. The results of contrasting algorithms work (with a numerical estimation) and the most prominent image filtering methods are presented. A description is given for an automatic image enhancement algorithm from a mobile synthetic vision system based on a choice of contrasting algorithms using an integral quality indicator, and a space-time filter using a pyramidal version of Lucas-Kanade optical flow algorithm is proposed.
{"title":"Automatic Image Enhancement from a Mobile Synthetic Vision System","authors":"Dmitry A. Kolchaev, A. I. Efimov, Dmitry I. Ustukov","doi":"10.1109/MECO.2019.8760014","DOIUrl":"https://doi.org/10.1109/MECO.2019.8760014","url":null,"abstract":"The work discusses basic image contrasting algorithms and noise compensation methods, an algorithm for estimating image quality based on an integral quality indicator, as well as approaches for estimating noise values in images. The results of contrasting algorithms work (with a numerical estimation) and the most prominent image filtering methods are presented. A description is given for an automatic image enhancement algorithm from a mobile synthetic vision system based on a choice of contrasting algorithms using an integral quality indicator, and a space-time filter using a pyramidal version of Lucas-Kanade optical flow algorithm is proposed.","PeriodicalId":141324,"journal":{"name":"2019 8th Mediterranean Conference on Embedded Computing (MECO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128903486","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 : 2019-06-01DOI: 10.1109/MECO.2019.8760184
V. Tishkina, A. Pylkin, A. Kroshilin, S. Kroshilina
Mobile business intelligence is in demand in modern enterprise management. This statement is relevant for small and large enterprises. The article concerns the process of developing a mobile application for analyzing the state of the enterprise. The mobile application selects the best options for the enterprise development strategy in the conditions of incomplete source data. The mobile application also provides decision support in enterprise management. The article presents the analysis method used in the mobile application. The analyzed data are parts of semantic network. Enterprise model based on the semantic network makes conclusions about each management object. The mobile app is unique in that it allows you to analyze companies of any industry and type. The article deals with the problem of using and implementing mobile solutions in small and medium-sized enterprises. The article describes the functionality of the mobile application. The work ends with short conclusions.
{"title":"The Software of a Mobile Application for Analyzing a Management Object based on Using Semantic Networks","authors":"V. Tishkina, A. Pylkin, A. Kroshilin, S. Kroshilina","doi":"10.1109/MECO.2019.8760184","DOIUrl":"https://doi.org/10.1109/MECO.2019.8760184","url":null,"abstract":"Mobile business intelligence is in demand in modern enterprise management. This statement is relevant for small and large enterprises. The article concerns the process of developing a mobile application for analyzing the state of the enterprise. The mobile application selects the best options for the enterprise development strategy in the conditions of incomplete source data. The mobile application also provides decision support in enterprise management. The article presents the analysis method used in the mobile application. The analyzed data are parts of semantic network. Enterprise model based on the semantic network makes conclusions about each management object. The mobile app is unique in that it allows you to analyze companies of any industry and type. The article deals with the problem of using and implementing mobile solutions in small and medium-sized enterprises. The article describes the functionality of the mobile application. The work ends with short conclusions.","PeriodicalId":141324,"journal":{"name":"2019 8th Mediterranean Conference on Embedded Computing (MECO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130897924","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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