基于多层体系结构的网络教学系统

为解决大规模网络教学应用中系统可集成性和教学资源与系统模块互操作性的问题,基于多层体系结构的网络教学系统,提出了规范化的接口设计、自描述结构化的数据表示方法、基于主题的发布/订阅通信机制、以及异步的数据交换协调执行模型。系统已经用于清华大学继续教育学院和东南大学远程教育学院,开设500多门课程,支持3万人以上用户在线使用,平均单条信息查询时间在10m s以内。实际应用表明:系统在用户并发数量和数据批处理效率等指标上基本满足大规模远程网络教学的实用业务需求。     

Ontology-Based Context-Aware Middleware for Smart Spaces

Context-awareness enhances human-centric, intelligent behavior in a smart environment; however, context-awareness is not widely used due to the lack of effective infrastructure to support context-aware ap- plications. This paper presents an agent-based middleware for providing context-aware services for smart spaces to afford effective support for context acquisition, representation, interpretation, and utilization to ap- plications. The middleware uses a formal context model, which combines first order probabilistic logic (FOPL) and web ontology language (OWL) ontologies, to provide a common understanding of contextual in- formation to facilitate context modeling and reasoning about imperfect and ambiguous contextual informa- tion and to enable context knowledge sharing and reuse. A context inference mechanism based on an ex- tended Bayesian network approach is used to enable automated reactive and deductive reasoning. The middleware is used in a case study in a smart classroom, and performance evaluation result shows that the context reasoning algorithm is good for non-time-critical applications and that the complexity is highly sensi- tive to the size of the context dataset.