一种支持科技信息资源共享的数据服务模型

提出一种用于科技信息资源共享的数据服务模型,支持以服务的形式发布并共享各类科技数据,特别是能在服务层面对数据的容量、冗余度、异常情况,以及完整性等数据本身的质量信息加以描述,并给出了这些质量信息的获取和更新方法.在服务层面为用户提供数据特征和数据质量的参考信息,有利于用户对科技信息资源的选择和使用,能够实现科技信息资源的有效共享,通过在全国科技信息服务网项目中的应用,初步验证了其效果.

基于云“微服务”装配软件开发方法的研究

实现一种基于云支撑、微服务环境平台为核心的装配式软件开发方法,在基于云的微服务架构下,以拆分与装配为基本手段实现从微服务到系统软件的过程,通过微代码加载到云容器,构建微服务实体对象,再加以配置组装,从而完成应用系统的开发测试与部署及运行。本软件开发方法研究将有助于快速开发基于云计算的应用软件,也有助于将传统软件快速升级成云环境应用软件。

外网模型不全下的网络分析优化方案研究与应用

为了解决以特高压电网为代表的跨省、跨大区互联电网持续加强,导致分中心和省调等下级调度维护的在线模型无法满足能源互联网格局下开断本网边界设备后调度员潮流等分析结果准确性要求的问题,在分析现有国调—分中心—省调模型数据信息流及现有解决方案的基础上,提出了基于服务的上级模型数据共享方案,并在华北分中心与河北省调部署成功,减小了下级电网因外网模型数据不全造成本地网络分析偏差,并进一步设计了基于国网总部一级部署的网络分析系统架构,可供长远解决该问题提供参考。

元数据的数据解析技术及在卫星设计中的应用

为解决卫星设计数据的实时采集、快速存储的要求,在航天器的数字化研制过程中,引入元数据的处理技术,目前已经形成大量元数据库。由于元数据特有的逻辑结构,元数据的业务还原、数据再利用方面存在瓶颈,提出一套统一的数据服务模型,用于元数据的数据解析,提高设计数据的检索、分析和再利用的能力。深入讨论了卫星设计元数据的解析策略,具体描述了统一数据服务模型的异步处理消息队列、插件式应用开发服务及派生的OLAP数据库的实现方法,并以卫星低频电缆网辅助设计系统为例,具体说明采用这种方法,实现元数据解析和利用的过程,验证了方法的可行性,在实际工作中获得了较好的效果。

Gaussian mixture models for clustering and classifying traffic flow in real-time for traffic operation and management

Based on Gaussian mixture models（GMM）, speed, flow and occupancy are used together in the cluster analysis of traffic flow data. Compared with other clustering and sorting techniques, as a structural model, the GMM is suitable for various kinds of traffic flow parameters. Gap statistics and domain knowledge of traffic flow are used to determine a proper number of clusters. The expectation-maximization （E-M） algorithm is used to estimate parameters of the GMM model. The clustered traffic flow pattems are then analyzed statistically and utilized for designing maximum likelihood classifiers for grouping real-time traffic flow data when new observations become available. Clustering analysis and pattern recognition can also be used to cluster and classify dynamic traffic flow patterns for freeway on-ramp and off-ramp weaving sections as well as for other facilities or things involving the concept of level of service, such as airports, parking lots, intersections, interrupted-flow pedestrian facilities, etc.

Accessing Alignments of Ontologies via IoT Based on SKOS Data Model

Many ontologies are provided to representing semantic sensors data.However,heterogeneity exists in different sensors which makes some service operators of Internet of Thing(IoT) difficult(such as such as semantic inferring,non-linear inverted index establishing,service composing) .There is a great deal of research about sensor ontology alignment dealing with the heterogeneity between the different sensor ontologies,but fewer solutions focus on exploiting syntaxes in a sensor ontology and the pattern of accessing alignments.Our solution infers alignments by extending structural subsumption algorithms to analyze syntaxes in a sensor ontology,and then combines the alignments with the SKOS model to construct the integration sensor ontology,which can be accessed via the IoT.The experiments show that the integration senor ontology in the SKOS model can be utilized via the IoT service,and the accuracy of our prototype,in average,is higher than others over the four real ontologies.

A Quarter Century of Work to Revolutionize Architecture, Engineering and Construction Enterprise Information Systems

More than two decades ago, object-oriented representation of AEC （architecture engineering and construction） projects started to offer the promise of seamless communication of semantic data models between computer-based systems used from the design stage to the operation of the facilities. BIM （building information modelling） emerged and appeared as a means to store all relevant data generated during the life-cycle of the facilities. But this upstream view of the built environment, arising from the design and construction stages, extended to the downstream operations where building and industrial facilities appeared more and more as huge dynamic data producers and concentrators while being operated. This created new challenges leading to what is referred to as ISCs （intelligent and smart constructions）. The current state of the art is that final constructions still contain various and increasingly versatile control and service systems, which are hardly standardised, and not interconnected among themselves. Monitoring, maintenance and services are done by specialised companies, each responsible of different systems, which are relying on customised software and techniques to meet specific user needs and are based on monolithic applications that require manual configuration for specific uses, maintenance and support. We demonstrate in this paper that the early promises of integration across the actors and along the life-time of facilities have gone a long way but will only be delivered through enhanced standardisation of computerized models, representations, services and operations still not yet fully accomplished 25 years after work started.

A Web-based Geographic Hypermedia System:Data Model,System Design and Prototype Applications

Geographic Hypermedia(GH)is a rich and interactive map document with geo-tagged graphics,sound and video ele-ments.A Geographic Hypermedia System(GHS)is designed to manage,query,display and explore GH resources.Recognizing emerging geo-tagged videos and measurable images as valuable geographic data resources,this paper aims to design a web-based GHS using web mapping,geoprocessing,video streaming and XMLHTTP services.The concept,data model,system design and implementation of this GHS are discussed in detail.Geo-tagged videos are modeled as temporal,spatial and metadata entities such as video clip,video path and frame-based descriptions.Similarly,geo-tagged stereo video and derived data are modeled as interre-lated entities:original video,rectified video,stereo video,video path,frame-based description and measurable image(rectified and disparity image with baseline,interior and exterior parameters).The entity data are organized into video files,GIS layers with linear referencing and XML documents for web publishing.These data can be integrated in HTML pages or used as Rich Internet Appli-cations(RIA)using standard web technologies such as the AJAX,ASP.NET and RIA frameworks.An SOA-based GHS is designed using four types of web services:ArcGIS Server 9.3 web mapping and geoprocessing services,Flash FMS 3.0 video streaming ser-vices and GeoRSS XMLHTTP services.GHS applications in road facility management and campus hypermapping indicate that the GH data models and technical solutions introduced in this paper are useful and flexible enough for wider deployment as a GHS.

Network-based naive Bayes model for social network

Naive Bayes(NB) is one of the most popular classification methods. It is particularly useful when the dimension of the predictor is high and data are generated independently. In the meanwhile, social network data are becoming increasingly accessible, due to the fast development of various social network services and websites. By contrast, data generated by a social network are most likely to be dependent. The dependency is mainly determined by their social network relationships. Then, how to extend the classical NB method to social network data becomes a problem of great interest. To this end, we propose here a network-based naive Bayes(NNB) method, which generalizes the classical NB model to social network data. The key advantage of the NNB method is that it takes the network relationships into consideration. The computational efficiency makes the NNB method even feasible in large scale social networks. The statistical properties of the NNB model are theoretically investigated. Simulation studies have been conducted to demonstrate its finite sample performance.A real data example is also analyzed for illustration purpose.