自动监视系统的软件设计

“自动监视系统”是一种用于安全保卫的自动化装置。本文仅介绍该系统的软件设计。整个软件分为系统管理、功能管理、实时管理及扫描切换四个部分,并且精心设计了与系统相适应的数据结构及查询技术。     

城市网络视角下的中国科技创新功能区划研究

开展科技创新功能区划是全局把握国家科技创新总体布局并指导提升区域科技创新能力极为重要的基础性工作,然而相关研究仍较滞后。本文从城市间创新合作关系网络的角度,结合已有地理区划理论和创新地理研究,设计了一种科技创新功能区划方法,基于中国357个城市间2017—2019年的专利合作关系数据,研制了一套中国科技创新功能区划方案。研究认为,将网络空间拓扑关系与地理空间位置关系相结合,借助空间邻接约束下的层次聚类与以模块度为依据的图分割技术,可以得到内部联系紧密且占据一定连续地表的区划结果,是一种科技创新功能区划的有效方法。在城市科技创新网络拓扑结构分析和二值与加权网络分区结果对比分析的基础上,研制出一套包含4个一级区和20个二级区的中国科技创新功能区划参考方案,将中国大致划分为北方、南方、东部、西部4个科技创新功能板块,每个板块包含4~6个二级功能区。这一方案的分区边界与省级行政边界具有较高的吻合性,可为国家从宏观层面进行科技创新统筹管理提供辅助参考。建议未来依托科技创新功能区的建设与区域科技创新中心的引领,因地制宜实施区域创新发展战略,更好地为国家创新驱动发展战略实施贡献力量。     

Planning hierarchical hospital service areas for maternal care using a network optimization approach: A case study in Hubei,China

Improving maternal health is one of the Sustainable Development Goals. Hospital service areas (HSAs), which contain most hospitalization behaviors at the local scale, are crucial for health care planning. However, little attention has been given to HSAs for maternal care and the hierarchy structure. Considering Hubei, central China, as a case study, this study aims to fill these gaps by developing a method for delineating hierarchical HSAs for maternal care using a network optimization approach. The approach is driven by actual patient flow data and has an explicit objective to maximize the modularity. It also establishes the hierarchical structure of maternal care HSAs, which is fundamental for the planning of hierarchical maternal care and referral systems. In our case study, 45 secondary HSAs and 22 tertiary HSAs are delineated to achieve maximal modularity. The HSAs perform well in terms of indices such as the Localization Index and Market Share Index. Furthermore, there is a complementary relationship between secondary and tertiary hospitals, which suggests the need for referral system planning. This study can provide evidence for the validity of the HSA and the planning of maternal care HSAs in China. It also provides transferable methods for planning hierarchical HSAs in other developing countries.     

A Review of: “Remote Sensing of Soils and Vegetation in the USSR”. By P. J. CURRAN,G. M. FOODY,K. YA. KONDRATYEV,V. V. KOZODEROV and P. P. FEDCHENKO. (London: Taylor & Francis, 1990.) [Pp. 200.] Price £30·00. ISBN 085066 4020.

As they increase in popularity, social media are regarded as important sources of information on geographical phenomena. Studies have also shown that people rely on social media to communicate during disasters and emergency situation, and that the exchanged messages can be used to get an insight into the situation. Spatial data mining techniques are one way to extract relevant information from social media. In this article, our aim is to contribute to this field by investigating how graph clustering can be applied to support the detection of geo-located communities in Twitter in disaster situations. For this purpose, we have enhanced the fast-greedy optimization of modularity (FGM) clustering algorithm with semantic similarity so that it can deal with the complex social graphs extracted from Twitter. Then, we have coupled the enhanced FGM with the varied density-based spatial clustering of applications with noise spatial clustering algorithm to obtain spatial clusters at different temporal snapshots. The method was experimented with a case study on typhoon Haiyan in the Philippines, and Twitter’s different interaction modes were compared to create the graph of users and to detect communities. The experiments show that communities that are relevant to identify areas where disaster-related incidents were reported can be extracted, and that the enhanced algorithm outperforms the generic one in this task.     

Distributed object‐based software environment for urban system integrated simulation under urban‐scale hazard—Part II: Application

A software prototype of a simulation service software environment, called DOSE (distributed object‐based software environment), is developed to realize the integrated simulation of an urban system under the risk of urban‐scale hazards such as earthquakes. DOSE infrastructure is built on three basic building blocks, namely: modularity, scalability, and interoperability. In this paper, the application of DOSE to real‐world urban systems is described in order to provide an evidence for DOSE modularity and scalability. An overview of DOSE is presented and then followed by a beverage application to simulate earthquake hazard in an urban system. The urban system is developed for the city of Kobe (Kobe district) with dimensions of 700 × 500 (m) and Bunkyo ward (Tokyo district) with dimensions of 800 × 600 (m) where DOSE simulation participants are identified for each district. The effectiveness of data exchange among different participants through a distributed service exchange network is described as an evidence for DOSE modularity that facilitates the integration process. On the other hand, the effectiveness of processing time when applying the simulation to different urban system sizes and/or using different third‐party applications is described as an evidence for DOSE scalability. The details of the underlying infrastructure of DOSE are beyond the scope of this paper and are presented in an accompanying paper work. Copyright © 2007 John Wiley & Sons, Ltd.     

Distributed object‐based software environment for urban system integrated simulation under urban‐scale hazard—Part I: Infrastructure

In this paper, a distributed object‐based software environment (DOSE) has been developed to facilitate the integrated simulation of an urban system under the risk of urban‐scale hazards such as earthquakes. It is understood that individual simulation participants perform their simulation services in separate environments, bartering service exchange relationships to get what they need to resolve their part of the problem. This is the communication gap between the scientists on one side and the end users who need to understand knowledge and employ it on the other side. The authors envision a distributed simulation service software environment running in parallel with the activities of simulation participants. DOSE has lent itself to integrate interdisciplinary participants through an infrastructure that has three basic building blocks, namely: modularity, scalability, and interoperability. The modular, object‐based, design of DOSE architecture is described in terms of key functionalities of four distinct layers, namely: resource, core, domain, and interface layers. DOSE scalability in terms of urban system size and participant third‐party application complexity is enabled through the interface layer. A message passing model is developed using the Message Passing Interface standard and a control room is provided to schedule the interaction/communication among model processes. DOSE interoperability with the vulnerability analysis third‐party applications is enabled through the Industry Foundation Classes (IFC) standard. An adopted analogy between DOSE and construction industry is employed to provide interpretation and implementation for DOSE interoperability. While interfacing IFC object model to solve DOSE interoperability questions, an extension model for the structural view of IFC is proposed and accepted by the International Alliance for Interoperability. The DOSE application for real‐world urban systems is beyond the scope of this paper and is presented in an accompanying paper work. Copyright © 2007 John Wiley & Sons, Ltd.     

Finding community structure in spatially constrained complex networks

One feature discovered in the study of complex networks is community structure, in which vertices are gathered into several groups where more edges exist within groups than between groups. Many approaches have been developed for identifying communities; these approaches essentially segment networks based on topological structure or the attribute similarity of vertices, while few approaches consider the spatial character of the networks. Many complex networks are spatially constrained such that the vertices and edges are embedded in space. In geographical space, nearer objects are more related than distant objects. Thus, the relations among vertices are defined not only by the links connecting them but also by the distance between them. In this article, we propose a geo-distance-based method of detecting communities in spatially constrained networks to identify communities that are both highly topologically connected and spatially clustered. The algorithm is based on the fast modularity maximisation (CNM) algorithm. First, we modify the modularity to geo-modularity Q^geo by introducing an edge weight that is the inverse of the geographic distance to the power of n. Then, we propose the concept of a spatial clustering coefficient as a measure of clustering of the network to determine the power value n of the distance. The algorithm is tested with China air transport network and BrightKite social network data-sets. The segmentation of the China air transport network is similar to the seven economic regions of China. The segmentation of the BrightKite social network shows the regionality of social groups and identifies the dynamic social groups that reflect users’ location changes. The algorithm is useful in exploring the interaction and clustering properties of geographical phenomena and providing timely location-based services for a group of people.     

边界层风廓线雷达相控阵天线子阵设计与应用

对比研究了国内外风廓线雷达产品天线系统和子阵的类型,设计了一款5波束有限相扫相控阵微带天线子阵。此天线系统由21个相同的正方形子阵组成,每个子阵包含16个阵元,4×4的正方形对称划分,每个阵元采用东西向、南北向2点同轴背馈馈电,子阵内双方向分别设计了等幅等相馈电网络,进而实现了东西向和南北向的水平极化。天线子阵各端口驻波小于1.2,提高了天线探测灵敏度,缩小了相控阵天线阵面面积,减轻了天线阵重量。结合子阵划分,优化了相控阵天线系统泰勒加权。天线具有两维步进电扫功能,在空域形成5个波束的探测。应用在TWP3型边界层风廓线雷达上,雷达探测高度大于5km。     

考虑地理距离的复杂网络社区挖掘算法

复杂网络具有社区结构的性质,即社区内节点的连接比社区间的连接更为紧密。目前,具有复杂网络拓扑结构的社区挖掘算法已有很多,但在很多地理空间的复杂网络中节点间的紧密度,不仅与其连接关系有关,同时与它们之间的距离有关。因此,本文提出将节点间的地理距离考虑到社区挖掘的过程中,修改基于模块度增量矩阵的Newman快速算法(简称CNM算法),将1 din(jd为节点i与节点j之间的距离)作为边权,对加权网络进行社区挖掘,从而发现既相互联系紧密又在地理空间上相互接近的社区。最后,本文用国内航线网络作为实例,将算法用于挖掘航线网络中城市的社区结构,得到10个在航线网络中联系紧密且在空间分布上具有一定地域性的城市社区,与我国的主要经济区域分布比较一致。本算法考虑地理相关性和连接紧密性,较好地识别出空间网络的社区结构。