血糖生成指数(glycemic index,GI)是医学及食品领域研究的热点,目前尚无学者对该领域学术研究现状进行系统分析。该研究选取1992—2022年WOS(Web Of Science)及中国知网(CNKI)数据库中关于GI相关的学术期刊文献作为研究资料,采用文献计...血糖生成指数(glycemic index,GI)是医学及食品领域研究的热点,目前尚无学者对该领域学术研究现状进行系统分析。该研究选取1992—2022年WOS(Web Of Science)及中国知网(CNKI)数据库中关于GI相关的学术期刊文献作为研究资料,采用文献计量学研究思路与方法,以CiteSpace、VOSviewer、Excel等软件为工具,对所纳入的1389篇外文文献及365篇中文文献进行可视化分析。从文献的作者、发文机构、期刊类别、关键词共现分析、聚类分析、突现分析等7个方面对文献资料进行系统分析。结果显示,影响食物GI高低的因素、GI饮食干预慢性病患者的效果、低GI食品的开发等作为主要的研究方向。食品GI的研究已有40多年历史,国外文献偏向于基础研究,国内侧重于应用研究。国外研究从研究深度、学术影响力、团队实力都强于国内,但国内GI研究发展势头乐观。未来GI研究领域,各研究机构及团队应强化跨地域、跨国界、跨学科的合作交流,增加GI在相关领域的高质量证据支持。展开更多
Adaptive rendering large and complex spatial data has become an important research issue in a 3DGIS application. In order to transmit the data to the client efficiently, this paper proposes a node-layer data model to ...Adaptive rendering large and complex spatial data has become an important research issue in a 3DGIS application. In order to transmit the data to the client efficiently, this paper proposes a node-layer data model to manage the 3D scene. Because the large spatial data and limited network bandwidth are the main bottlenecks of web-based 3DGIS, a client/server architecture including progressive transmission methods and multiresolution representations, together with the spatial index, are developed to improve the performance. All this makes the application quite scalable. Experimental results reveal that the application works appropriately.展开更多
With the increasing complexity of power systems and the widespread penetration of renewable energy sources(RES),real-time situational awareness for power systems is of great significance for operational scheduling.Con...With the increasing complexity of power systems and the widespread penetration of renewable energy sources(RES),real-time situational awareness for power systems is of great significance for operational scheduling.Considering the impact of RES on power system operations,a situational awareness key performance index(KPI)system for power systems with a high proportion of RES is proposed in this paper,which consists of reserve capacity abundance,ramp resource abundance,center of inertia(COI)frequency deviation,interface power flow margin,synthesized voltage stability,and angle stability margin.Then,the KPIs are synthesized and visualized by the decision tree method and radar chart method,respectively,for monitoring the operation states(i.e,normal,alert,and emergency states)of power systems with a high proportion of RES.Numerical simulations are conducted in a revised New England 16-machine 68-bus power system and an actual CEPRI-RE power system in the northwest region of China with a high proportion of RES.The results show that the proposed KPI-based situational awareness method is able to accurately monitor the real-time state of power systems with a high proportion of RES,and can assist power dispatchers to make effective decisions.展开更多
Motif-based graph local clustering(MGLC)is a popular method for graph mining tasks due to its various applications.However,the traditional two-phase approach of precomputing motif weights before performing local clust...Motif-based graph local clustering(MGLC)is a popular method for graph mining tasks due to its various applications.However,the traditional two-phase approach of precomputing motif weights before performing local clustering loses locality and is impractical for large graphs.While some attempts have been made to address the efficiency bottleneck,there is still no applicable algorithm for large scale graphs with billions of edges.In this paper,we propose a purely local and index-free method called Index-free Triangle-based Graph Local Clustering(TGLC^(*))to solve the MGLC problem w.r.t.a triangle.TGLC^(*)directly estimates the Personalized PageRank(PPR)vector using random walks with the desired triangleweighted distribution and proposes the clustering result using a standard sweep procedure.We demonstrate TGLC^(*)’s scalability through theoretical analysis and its practical benefits through a novel visualization layout.TGLC^(*)is the first algorithm to solve the MGLC problem without precomputing the motif weight.Extensive experiments on seven real-world large-scale datasets show that TGLC^(*)is applicable and scalable for large graphs.展开更多
文摘血糖生成指数(glycemic index,GI)是医学及食品领域研究的热点,目前尚无学者对该领域学术研究现状进行系统分析。该研究选取1992—2022年WOS(Web Of Science)及中国知网(CNKI)数据库中关于GI相关的学术期刊文献作为研究资料,采用文献计量学研究思路与方法,以CiteSpace、VOSviewer、Excel等软件为工具,对所纳入的1389篇外文文献及365篇中文文献进行可视化分析。从文献的作者、发文机构、期刊类别、关键词共现分析、聚类分析、突现分析等7个方面对文献资料进行系统分析。结果显示,影响食物GI高低的因素、GI饮食干预慢性病患者的效果、低GI食品的开发等作为主要的研究方向。食品GI的研究已有40多年历史,国外文献偏向于基础研究,国内侧重于应用研究。国外研究从研究深度、学术影响力、团队实力都强于国内,但国内GI研究发展势头乐观。未来GI研究领域,各研究机构及团队应强化跨地域、跨国界、跨学科的合作交流,增加GI在相关领域的高质量证据支持。
基金the National High-Tech Research & Development Program of China (Grant Nos. 2006AA12Z220, 2006AA12Z114)the National Basic Research Program of China (Grant No. 2007CB714403)the National Natural Science Foundation of China (Grant No. 60502008)
文摘Adaptive rendering large and complex spatial data has become an important research issue in a 3DGIS application. In order to transmit the data to the client efficiently, this paper proposes a node-layer data model to manage the 3D scene. Because the large spatial data and limited network bandwidth are the main bottlenecks of web-based 3DGIS, a client/server architecture including progressive transmission methods and multiresolution representations, together with the spatial index, are developed to improve the performance. All this makes the application quite scalable. Experimental results reveal that the application works appropriately.
基金supported in part by the National Key R&D Program of China(2016YFB0900100)the National Natural Science Foundation of China(52077195).
文摘With the increasing complexity of power systems and the widespread penetration of renewable energy sources(RES),real-time situational awareness for power systems is of great significance for operational scheduling.Considering the impact of RES on power system operations,a situational awareness key performance index(KPI)system for power systems with a high proportion of RES is proposed in this paper,which consists of reserve capacity abundance,ramp resource abundance,center of inertia(COI)frequency deviation,interface power flow margin,synthesized voltage stability,and angle stability margin.Then,the KPIs are synthesized and visualized by the decision tree method and radar chart method,respectively,for monitoring the operation states(i.e,normal,alert,and emergency states)of power systems with a high proportion of RES.Numerical simulations are conducted in a revised New England 16-machine 68-bus power system and an actual CEPRI-RE power system in the northwest region of China with a high proportion of RES.The results show that the proposed KPI-based situational awareness method is able to accurately monitor the real-time state of power systems with a high proportion of RES,and can assist power dispatchers to make effective decisions.
基金supported by the Fundamental Research Funds for the Central Universities(No.2020JS005).
文摘Motif-based graph local clustering(MGLC)is a popular method for graph mining tasks due to its various applications.However,the traditional two-phase approach of precomputing motif weights before performing local clustering loses locality and is impractical for large graphs.While some attempts have been made to address the efficiency bottleneck,there is still no applicable algorithm for large scale graphs with billions of edges.In this paper,we propose a purely local and index-free method called Index-free Triangle-based Graph Local Clustering(TGLC^(*))to solve the MGLC problem w.r.t.a triangle.TGLC^(*)directly estimates the Personalized PageRank(PPR)vector using random walks with the desired triangleweighted distribution and proposes the clustering result using a standard sweep procedure.We demonstrate TGLC^(*)’s scalability through theoretical analysis and its practical benefits through a novel visualization layout.TGLC^(*)is the first algorithm to solve the MGLC problem without precomputing the motif weight.Extensive experiments on seven real-world large-scale datasets show that TGLC^(*)is applicable and scalable for large graphs.
