Saad Aljubayrin, B. Yang, Christian S. Jensen, Rui Zhang
With the rapidly growing availability of vehicle trajectory data, travel costs such as travel time and fuel consumption can be captured accurately as distributions (e.g., travel time distributions) instead of deterministic values (e.g., average travel times). We study a new path finding problem in uncertain road networks, where paths have travel cost distributions. Given a source and a destination, we find optimal, non-dominated paths connecting the source and the destination, where the optimality is defined in terms of the stochastic dominance among cost distributions of paths. We first design an A based framework that utilizes the uncertain graph to obtain the most accurate cost distributions while finding the candidate paths. Next, we propose a three-stage dominance examination method that employs extreme values in each candidate path's cost distribution for early detection of dominated paths, thus reducing the need for expensive distributions convolutions. We conduct extensive experiments using real world road network and trajectory data. The results show that our algorithm outperforms baseline algorithms by up to two orders of magnitude in terms of query response time while achieving the most accurate results.
{"title":"Finding non-dominated paths in uncertain road networks","authors":"Saad Aljubayrin, B. Yang, Christian S. Jensen, Rui Zhang","doi":"10.1145/2996913.2996964","DOIUrl":"https://doi.org/10.1145/2996913.2996964","url":null,"abstract":"With the rapidly growing availability of vehicle trajectory data, travel costs such as travel time and fuel consumption can be captured accurately as distributions (e.g., travel time distributions) instead of deterministic values (e.g., average travel times). We study a new path finding problem in uncertain road networks, where paths have travel cost distributions. Given a source and a destination, we find optimal, non-dominated paths connecting the source and the destination, where the optimality is defined in terms of the stochastic dominance among cost distributions of paths. We first design an A based framework that utilizes the uncertain graph to obtain the most accurate cost distributions while finding the candidate paths. Next, we propose a three-stage dominance examination method that employs extreme values in each candidate path's cost distribution for early detection of dominated paths, thus reducing the need for expensive distributions convolutions. We conduct extensive experiments using real world road network and trajectory data. The results show that our algorithm outperforms baseline algorithms by up to two orders of magnitude in terms of query response time while achieving the most accurate results.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"301 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89036965","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}
Marjan Alirezaie, Franziska Klügl-Frohnmeyer, A. Loutfi
This paper depicts a sensor-based map navigation approach which targets users, who due to disabilities or lack of technical knowledge are currently not in the focus of map system developments for personalized information. What differentiates our approach from the state-of-art mostly integrating localized social media data, is that our vision is to integrate real time sensor generated data that indicates the situation of different phenomena (such as the physiological functions of the body) related to the user. The challenge hereby is mainly related to knowledge representation and integration. The tentative impact of our vision for future navigation systems is reflected within a scenario.
{"title":"Knowing without telling: integrating sensing and mapping for creating an artificial companion","authors":"Marjan Alirezaie, Franziska Klügl-Frohnmeyer, A. Loutfi","doi":"10.1145/2996913.2996961","DOIUrl":"https://doi.org/10.1145/2996913.2996961","url":null,"abstract":"This paper depicts a sensor-based map navigation approach which targets users, who due to disabilities or lack of technical knowledge are currently not in the focus of map system developments for personalized information. What differentiates our approach from the state-of-art mostly integrating localized social media data, is that our vision is to integrate real time sensor generated data that indicates the situation of different phenomena (such as the physiological functions of the body) related to the user. The challenge hereby is mainly related to knowledge representation and integration. The tentative impact of our vision for future navigation systems is reflected within a scenario.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81297025","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}
RFID (Radio Frequency Identification)-based object tracking is increasingly deployed and used in indoor environments such as airports, shopping malls, etc. However, the inherent noise in the raw RFID data makes it difficult to support queries and analyses on the data. In this paper, we propose an RFID data cleansing based on regular expressions. We generate the regular expressions in an automaton that captures all possible indoor paths from the spatial and temporal aspects of indoor space and deployed readers. Given the raw data of an object, the proposed matching algorithm finds all the matching paths using the automaton. We evaluate the proposed approach by conducting experimental studies using real dataset. The results demonstrate the effectiveness of the propose approach.
{"title":"Cleansing indoor RFID data using regular expressions","authors":"A. Baba, Hua Lu, Wei-Shinn Ku, T. Pedersen","doi":"10.1145/2996913.2996979","DOIUrl":"https://doi.org/10.1145/2996913.2996979","url":null,"abstract":"RFID (Radio Frequency Identification)-based object tracking is increasingly deployed and used in indoor environments such as airports, shopping malls, etc. However, the inherent noise in the raw RFID data makes it difficult to support queries and analyses on the data. In this paper, we propose an RFID data cleansing based on regular expressions. We generate the regular expressions in an automaton that captures all possible indoor paths from the spatial and temporal aspects of indoor space and deployed readers. Given the raw data of an object, the proposed matching algorithm finds all the matching paths using the automaton. We evaluate the proposed approach by conducting experimental studies using real dataset. The results demonstrate the effectiveness of the propose approach.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"95 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76228551","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}
Public bus services in many cities in countries like India are controlled by private owners, hence, building up a database for all the bus routes is non-trivial. In this paper, we leverage smart-phone based sensing to crowdsource and populate the information repository for bus routes in a city. We have developed an intelligent data logging module for smart-phones and a server side processing mechanism to extract roads and bus routes information. From a 3 month long study involving more than 30 volunteers in 3 different cities in India, we found that the developed system, CrowdMap, can annotate bus routes with a mean error of 10m, while consuming 80% less energy compared to a continuous GPS based system.
{"title":"Unsupervised annotated city traffic map generation","authors":"Rohit Verma, Surjya Ghosh, Aviral Shrivastava, Niloy Ganguly, Bivas Mitra, Sandip Chakraborty","doi":"10.1145/2996913.2996942","DOIUrl":"https://doi.org/10.1145/2996913.2996942","url":null,"abstract":"Public bus services in many cities in countries like India are controlled by private owners, hence, building up a database for all the bus routes is non-trivial. In this paper, we leverage smart-phone based sensing to crowdsource and populate the information repository for bus routes in a city. We have developed an intelligent data logging module for smart-phones and a server side processing mechanism to extract roads and bus routes information. From a 3 month long study involving more than 30 volunteers in 3 different cities in India, we found that the developed system, CrowdMap, can annotate bus routes with a mean error of 10m, while consuming 80% less energy compared to a continuous GPS based system.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87820456","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}
The recent increase in attention to ride-sharing applications demonstrates the importance of routing algorithms for multiple users who obtain benefits from confluence, that is, traveling together on all or part of their routes. We propose novel and flexible formulation of routing optimization for multiple users who have their respective sources and a single common destination. The formulation is general enough to express each user's benefit (or cost) of confluence for every combination of users. Hence, the formulation can represent a wide range of applications and subsumes almost all formulations proposed in literature. We establish an efficient exact method for the formulation. Interestingly, we found well-known Dreyfus-Wagner Algorithm for the Minimum Steiner Tree Problem (MSTP) is extensible for ours, although our formulation is much harder than the MSTP. Our experimental results obtained on large-scale road networks reveal that our method is efficient in practical settings.
{"title":"Multi-user routing to single destination with confluence","authors":"Kazuki Takise, Yasuhito Asano, Masatoshi Yoshikawa","doi":"10.1145/2996913.2997018","DOIUrl":"https://doi.org/10.1145/2996913.2997018","url":null,"abstract":"The recent increase in attention to ride-sharing applications demonstrates the importance of routing algorithms for multiple users who obtain benefits from confluence, that is, traveling together on all or part of their routes. We propose novel and flexible formulation of routing optimization for multiple users who have their respective sources and a single common destination. The formulation is general enough to express each user's benefit (or cost) of confluence for every combination of users. Hence, the formulation can represent a wide range of applications and subsumes almost all formulations proposed in literature. We establish an efficient exact method for the formulation. Interestingly, we found well-known Dreyfus-Wagner Algorithm for the Minimum Steiner Tree Problem (MSTP) is extensible for ours, although our formulation is much harder than the MSTP. Our experimental results obtained on large-scale road networks reveal that our method is efficient in practical settings.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82841881","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}
Bo Lyu, Shijian Li, Yanhua Li, Jie Fu, Andrew C. Trapp, Haiyong Xie, Yong Liao
The fast pace of global urbanization is drastically changing the population distributions over the world, which leads to significant changes in geographical population densities. Such changes in turn alter the underlying geographical power demand over time, and drive power substations to become over-supplied (demand << capacity) or under-supplied (demand ≈ capacity). In this paper, we make the first attempt to investigate the problem of power substation-user assignment by analyzing large-scale power grid data. We develop a Scalable Power User Assignment (SPUA) framework, that takes large-scale spatial power user/substation distribution data and temporal user power consumption data as input, and assigns users to substations, in a manner that minimizes the maximum substation utilization among all substations. To evaluate the performance of our SPUA framework, we conduct evaluations on real power consumption data and user/substation location data collected from a province in China for 35 days in 2015. The evaluation results demonstrate that our SPUA framework can achieve a 20%--65% reduction on the maximum substation utilization, and 2 to 3.7 times reduction on total transmission loss over other baseline methods.
{"title":"Scalable user assignment in power grids: a data driven approach","authors":"Bo Lyu, Shijian Li, Yanhua Li, Jie Fu, Andrew C. Trapp, Haiyong Xie, Yong Liao","doi":"10.1145/2996913.2996970","DOIUrl":"https://doi.org/10.1145/2996913.2996970","url":null,"abstract":"The fast pace of global urbanization is drastically changing the population distributions over the world, which leads to significant changes in geographical population densities. Such changes in turn alter the underlying geographical power demand over time, and drive power substations to become over-supplied (demand << capacity) or under-supplied (demand ≈ capacity). In this paper, we make the first attempt to investigate the problem of power substation-user assignment by analyzing large-scale power grid data. We develop a Scalable Power User Assignment (SPUA) framework, that takes large-scale spatial power user/substation distribution data and temporal user power consumption data as input, and assigns users to substations, in a manner that minimizes the maximum substation utilization among all substations. To evaluate the performance of our SPUA framework, we conduct evaluations on real power consumption data and user/substation location data collected from a province in China for 35 days in 2015. The evaluation results demonstrate that our SPUA framework can achieve a 20%--65% reduction on the maximum substation utilization, and 2 to 3.7 times reduction on total transmission loss over other baseline methods.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74627072","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}
The analysis of Twitter data can help to predict or explain many real world phenomena. The relationships among events in the real world can be reflected among the topics on social media. In this paper, we propose the concept of topic association and the associated mining algorithms. Topics with close temporal and spatial relationship may have direct or potential association in the real world. Our goal is to mine such topic associations and show their relationships in different time-region frames. We propose to use the concepts of participation ratio and participation index to measure the closeness among topics and propose a spatiotemporal index to calculate them efficiently. With the topic filtering and the topic combination, we further optimize the mining process and the mining results. The algorithms are evaluated on a Twitter dataset with 27,956,257 tweets.
{"title":"Spatiotemporal topic association detection on tweets","authors":"Zhi Liu, Yan Huang, Joshua R. Trampier","doi":"10.1145/2996913.2996933","DOIUrl":"https://doi.org/10.1145/2996913.2996933","url":null,"abstract":"The analysis of Twitter data can help to predict or explain many real world phenomena. The relationships among events in the real world can be reflected among the topics on social media. In this paper, we propose the concept of topic association and the associated mining algorithms. Topics with close temporal and spatial relationship may have direct or potential association in the real world. Our goal is to mine such topic associations and show their relationships in different time-region frames. We propose to use the concepts of participation ratio and participation index to measure the closeness among topics and propose a spatiotemporal index to calculate them efficiently. With the topic filtering and the topic combination, we further optimize the mining process and the mining results. The algorithms are evaluated on a Twitter dataset with 27,956,257 tweets.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80303387","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}
Payam Tabrizian, A. Petrasova, B. Harmon, V. Petras, H. Mitásová, R. Meentemeyer
Tangible Landscape is a tangible interface for geographic information systems (GIS). It interactively couples physical and digital models of a landscape so that users can intuitively explore, model, and analyze geospatial data in a collaborative environment. Conceptually Tangible Landscape lets users hold a GIS in their hands so that they can feel the shape of the topography, naturally sculpt new landforms, and interact with simulations like water flow. Since it only affords a bird's-eye view of the landscape, we coupled it with an immersive virtual environment so that users can virtually walk around the modeled landscape and visualize it at a human-scale. Now as users shape topography, draw trees, define viewpoints, or route a walkthrough, they can see the results on the projection-augmented model, rendered on a display, or rendered on a head-mounted display. In this paper we present the Tangible Landscape Immersive Extension, describe its physical setup and software architecture, and demonstrate its features with a case study.
{"title":"Immersive tangible geospatial modeling","authors":"Payam Tabrizian, A. Petrasova, B. Harmon, V. Petras, H. Mitásová, R. Meentemeyer","doi":"10.1145/2996913.2996950","DOIUrl":"https://doi.org/10.1145/2996913.2996950","url":null,"abstract":"Tangible Landscape is a tangible interface for geographic information systems (GIS). It interactively couples physical and digital models of a landscape so that users can intuitively explore, model, and analyze geospatial data in a collaborative environment. Conceptually Tangible Landscape lets users hold a GIS in their hands so that they can feel the shape of the topography, naturally sculpt new landforms, and interact with simulations like water flow. Since it only affords a bird's-eye view of the landscape, we coupled it with an immersive virtual environment so that users can virtually walk around the modeled landscape and visualize it at a human-scale. Now as users shape topography, draw trees, define viewpoints, or route a walkthrough, they can see the results on the projection-augmented model, rendered on a display, or rendered on a head-mounted display. In this paper we present the Tangible Landscape Immersive Extension, describe its physical setup and software architecture, and demonstrate its features with a case study.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"75 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80664204","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}
Recent advancements in data mining coupled with the ubiquity of mobile devices has led to the possibility of mining for events in real-time. We introduce the problem of mining for an individual's encounters. As people travel, they may have encounters with one another. We are interested in detecting the encounters of traveling individuals at the exact moment in which each of them occur. A simple solution is to use a nearest neighbor search to return potential encounters, this results in slow query response times. To mine for encounters in real-time, we introduce a new algorithm that is efficient in capturing encounters by exploiting the observation that just the neighbors in a defined proximity needs to be maintained. Our evaluation demonstrates that our proposed method mines for encounters for millions of individuals in a city area within milliseconds.
{"title":"Mining city-wide encounters in real-time","authors":"Anthony Quattrone, L. Kulik, E. Tanin","doi":"10.1145/2996913.2996995","DOIUrl":"https://doi.org/10.1145/2996913.2996995","url":null,"abstract":"Recent advancements in data mining coupled with the ubiquity of mobile devices has led to the possibility of mining for events in real-time. We introduce the problem of mining for an individual's encounters. As people travel, they may have encounters with one another. We are interested in detecting the encounters of traveling individuals at the exact moment in which each of them occur. A simple solution is to use a nearest neighbor search to return potential encounters, this results in slow query response times. To mine for encounters in real-time, we introduce a new algorithm that is efficient in capturing encounters by exploiting the observation that just the neighbors in a defined proximity needs to be maintained. Our evaluation demonstrates that our proposed method mines for encounters for millions of individuals in a city area within milliseconds.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88586673","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}
The Delaunay triangulation is the standard choice for building triangulated irregular networks (TINs) to represent terrain surfaces. However, the Delaunay triangulation is based only on the 2D coordinates of the data points, ignoring their elevation. It has long been recognized that sometimes it may be beneficial to use other, non-Delaunay, criteria to build TINs. Data-dependent triangulations were introduced decades ago to address this. However, they are rarely used in practice, mostly because the optimization of data- dependent criteria often results in triangulations with many thin and elongated triangles. Recently, in the field of computational geometry, higher order Delaunay triangulations (HODTs) were introduced, trying to tackle both issues at the same time-data-dependent criteria and good triangle shape. Nevertheless, most previous studies about them have been limited to theoretical aspects. In this work we present the first extensive experimental study on the practical use of HODTs, as a tool to build data-dependent TINs. We present experiments with two USGS terrains that show that HODTs can give significant improvements over the Delaunay triangulation for the criteria identified as most important for data-dependent triangulations. The resulting triangulations have data-dependent values comparable to those obtained with pure data-dependent approaches, without compromising the shape of the triangles, and are faster to compute.
{"title":"Implementing data-dependent triangulations with higher order Delaunay triangulations","authors":"Natalia Rodríguez, Rodrigo I. Silveira","doi":"10.1145/2996913.2996958","DOIUrl":"https://doi.org/10.1145/2996913.2996958","url":null,"abstract":"The Delaunay triangulation is the standard choice for building triangulated irregular networks (TINs) to represent terrain surfaces. However, the Delaunay triangulation is based only on the 2D coordinates of the data points, ignoring their elevation. It has long been recognized that sometimes it may be beneficial to use other, non-Delaunay, criteria to build TINs. Data-dependent triangulations were introduced decades ago to address this. However, they are rarely used in practice, mostly because the optimization of data- dependent criteria often results in triangulations with many thin and elongated triangles. Recently, in the field of computational geometry, higher order Delaunay triangulations (HODTs) were introduced, trying to tackle both issues at the same time-data-dependent criteria and good triangle shape. Nevertheless, most previous studies about them have been limited to theoretical aspects. In this work we present the first extensive experimental study on the practical use of HODTs, as a tool to build data-dependent TINs. We present experiments with two USGS terrains that show that HODTs can give significant improvements over the Delaunay triangulation for the criteria identified as most important for data-dependent triangulations. The resulting triangulations have data-dependent values comparable to those obtained with pure data-dependent approaches, without compromising the shape of the triangles, and are faster to compute.","PeriodicalId":20525,"journal":{"name":"Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84464266","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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