An expert system on design of liquid-retaining structures with blackboard architecture

The design of liquid-retaining structures involves many decisions to be made by the designer based on rules of thumb, heuristics, judgement, codes of practice and previous experience. Structural design problems are often ill structured and there is a need to develop programming environments that can incorporate engineering judgement along with algorithmic tools. Recent developments in artificial intelligence have made it possible to develop an expert system that can provide expert advice to the user in the selection of design criteria and design parameters. This paper introduces the development of an expert system in the design of liquid-retaining structures using blackboard architecture. An expert system shell, Visual Rule Studio, is employed to facilitate the development of this prototype system. It is a coupled system combining symbolic processing with traditional numerical processing. The expert system developed is based on British Standards Code of Practice BS8007. Explanations are made to assist inexperienced designers or civil engineering students to learn how to design liquid-retaining structures effectively and sustainably in their design practices. The use of this expert system in disseminating heuristic knowledge and experience to practitioners and engineering students is discussed.

Differences in sharing knowledge interpersonally and via databases: The role of evaluation apprehension and perceived benefits

Knowledge sharing is an essential component of effective knowledge management. However, evaluation apprehension, or the fear that your work may be critiqued, can inhibit knowledge sharing. Using the general framework of social exchange theory, we examined the effects of evaluation apprehension and perceived benefit of knowledge sharing ( such as enhanced reputation) on employees' knowledge sharing intentions in two contexts: interpersonal (i.e., by direct contact between two employees) and database (i.e., via repositories). Evaluation apprehension was negatively associated with knowledge sharing intentions in both contexts while perceived bene. it was only positively associated with knowledge sharing intentions in the database context. Moreover, compared to the interpersonal context, evaluation apprehension was higher and knowledge sharing lower in the database context. Finally, the negative effects of evaluation apprehension upon knowledge sharing intentions were worse when perceived benefits were low compared to when perceived benefits were high.

Scalable location management for context-aware systems

Location information is commonly used in context-aware applications and pervasive systems. These applications and systems may require knowledge, of the location of users, devices and services. This paper presents a location management system able to gather, process and manage location information from a variety of physical and virtual location sensors. The system scales to the complexity of context-aware applications, to a variety of types and large number of location sensors and clients, and to geographical size of the system. The proposed location management system provides conflict resolution of location information and mechanisms to ensure privacy.