The integration of an intelligent knowledge-based system into engineering software using the blackboard structure

Over recent years there has been an increase in the use of generic Computational Fluid Dynamics (CFD) software packages spread across various application fields. This has created the need for the integration of expertise into CFD software. Expertise can be integrated into CFD software in the form of an Intelligent Knowledge-Based System (IKBS). The advantages of integrating intelligence into generic engineering software are discussed with a special view to software engineering considerations. The software modelling cycle of a typical engineering problem is identified and the respective expertise and user control needed for each modelling phase is shown. The requirements of an IKBS for CFD software are discussed and compared to current practice. The blackboard software architecture is presented. This is shown to be appropriate for the integration of an IKBS into an engineering software package. This is demonstrated through the presentation of the prototype CFD software package FLOWES.

W(h)ither phonological awareness? Literate trainee teachers’ lack of stable knowledge about the sound structure of words

Recent national developments in the teaching of literacy in the early years in the UK mean that teachers need to have explicit fluent knowledge of the sound structure of the language and its relationship to orthography in order to teach reading effectively. In this study, a group of 38 graduate trainee primary teachers were given a pencil and paper test of phonological awareness as part of a course on teaching literacy. Results from the pencil and paper test were used as the basis of teaching about the sound structure of words. The test was repeated six months later. The results showed that they did not use a consistent system for segmenting words into component sounds. Though there was substantial improvement on second testing, many trainees still did not show evidence that they had yet developed sufficient insights into the sound structure of words to be able to teach children about phonemes with certainty. It is argued that student teachers need substantial explicit training and practice in manipulating the sound structure of words to enable them to teach this aspect of language confidently.

Effects of structure of self-knowledge on mood-incongruent effect

Some people recall more positive memories in negative moods than in neutral moods, which is called mood-incongruent effect. Although previous research suggested that structure of self-knowledge influences mood-incongruent effect (Sakaki, 2004), it is possible that motivation for mood-regulation mediates relation between structure of self-knowledge and mood-incongruent effect. The present study aimed at exploring this possibility by using self-complexity. In Study 1, participants with higher self-complexity, whose self-knowledge has more self-aspects with a higher level of differentiation, recalled more positive memories in negative moods (compared to neutral moods) than participants with lower self-complexity, whose self-knowledge has a fewer self-aspects with larger overlap. Study 1 also revealed that these effects hold even when the motivation for mood-regulation was partialed out. Study 2 examined mood-incongruent effect under positive moods, in which participants are unlikely motivated to alter their moods, and it was found that participants with higher self-complexity recalled more negative memories in positive moods (compared to neutral moods) than participants with lower self-complexity.

Knowledge-Based Task Structure Planning for an Information Gathering Agent

An effective solution to model and apply planning domain knowledge for deliberation and action in probabilistic, agent-oriented control is presented. Specifically, the addition of a task structure planning component and supporting components to an agent-oriented architecture and agent implementation is described. For agent control in risky or uncertain environments, an approach and method of goal reduction to task plan sets and schedules of action is presented. Additionally, some issues related to component-wise, situation-dependent control of a task planning agent that schedules its tasks separately from planning them are motivated and discussed.

An introduction to physiology : being a course of lectures upon the most important parts of the animal oeconomy : in which the nature and seat of many diseases is pointed out, and explained ; their curative indications settled ; and the necessary connexion between regular practice, and a knowledge of the structure and uses of the parts is evinced, and illustrated /

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Industry-specific human capital, knowledge labour, and industry wage structure in Taiwan

This paper investigates the role of industry-specific human capital (ISHC) in determining industry wage structure. The model presented in this paper distinguishes between knowledge labour and physical labour. Knowledge labour is physical labour embodied with ISHC. It is postulated that more ISHC-intensive industries, such as high-tech industries, pay higher wages and the wage premiums increase with workers' experience. The hypothesis is tested using a merged sample of 1997 - 1999 manpower utilization survey data from a newly industrialized economy - Taiwan. The findings show support for the effect of ISHC.

Hybrid knowledge representation in a blackboard KBS for liquid retaining structure design

This paper highlights the importance of design expertise, for designing liquid retaining structures, including subjective judgments and professional experience. Design of liquid retaining structures has special features different from the others. Being more vulnerable to corrosion problem, they have stringent requirements against serviceability limit state of crack. It is the premise of the study to transferring expert knowledge in a computerized blackboard system. Hybrid knowledge representation schemes, including production rules, object-oriented programming, and procedural methods, are employed to express engineering heuristics and standard design knowledge during the development of the knowledge-based system (KBS) for design of liquid retaining structures. This approach renders it possible to take advantages of the characteristics of each method. The system can provide the user with advice on preliminary design, loading specification, optimized configuration selection and detailed design analysis of liquid retaining structure. It would be beneficial to the field of retaining structure design by focusing on the acquisition and organization of expert knowledge through the development of recent artificial intelligence technology. (C) 2003 Elsevier Ltd. All rights reserved.

A knowledge-based system for liquid retaining structure design with blackboard architecture

Owing to the high degree of vulnerability of liquid retaining structures to corrosion problems, there are stringent requirements in its design against cracking. In this paper, a prototype knowledge-based system is developed and implemented for the design of liquid retaining structures based on the blackboard architecture. A commercially available expert system shell VISUAL RULE STUDIO working as an ActiveX Designer under the VISUAL BASIC programming environment is employed. Hybrid knowledge representation approach with production rules and procedural methods under object-oriented programming are used to represent the engineering heuristics and design knowledge of this domain. It is demonstrated that the blackboard architecture is capable of integrating different knowledge together in an effective manner. The system is tailored to give advice to users regarding preliminary design, loading specification and optimized configuration selection of this type of structure. An example of application is given to illustrate the capabilities of the prototype system in transferring knowledge on liquid retaining structure to novice engineers. (C) 2004 Elsevier Ltd. All rights reserved.

Block GTM: Incorporating prior knowledge of covariance structure in data visualisation

Visualising data for exploratory analysis is a big challenge in scientific and engineering domains where there is a need to gain insight into the structure and distribution of the data. Typically, visualisation methods like principal component analysis and multi-dimensional scaling are used, but it is difficult to incorporate prior knowledge about structure of the data into the analysis. In this technical report we discuss a complementary approach based on an extension of a well known non-linear probabilistic model, the Generative Topographic Mapping. We show that by including prior information of the covariance structure into the model, we are able to improve both the data visualisation and the model fit.

A method for automatically eliciting node weights in a hierarchical knowledge-based structure for reasoning with uncertainty

Hierarchical knowledge structures are frequently used within clinical decision support systems as part of the model for generating intelligent advice. The nodes in the hierarchy inevitably have varying influence on the decisionmaking processes, which needs to be reflected by parameters. If the model has been elicited from human experts, it is not feasible to ask them to estimate the parameters because there will be so many in even moderately-sized structures. This paper describes how the parameters could be obtained from data instead, using only a small number of cases. The original method [1] is applied to a particular web-based clinical decision support system called GRiST, which uses its hierarchical knowledge to quantify the risks associated with mental-health problems. The knowledge was elicited from multidisciplinary mental-health practitioners but the tree has several thousand nodes, all requiring an estimation of their relative influence on the assessment process. The method described in the paper shows how they can be obtained from about 200 cases instead. It greatly reduces the experts’ elicitation tasks and has the potential for being generalised to similar knowledge-engineering domains where relative weightings of node siblings are part of the parameter space.

A Proposed Structure of Knowledge-Based Hybrid Intelligent Systems for Sophisticated Environments

The paper deals with a problem of intelligent system’s design for complex environments. There is discussed a possibility to integrate several technologies into one basic structure. One possible structure is proposed in order to form a basis for intelligent system that would be able to operate in complex environments. The basic elements of the proposed structure have found their implemented in software system. This software system is shortly presented in the paper. The most important results of experiments are outlined and discussed at the end of the paper. Some possible directions of further research are sketched.