Lattice-dome design using a knowledge-based system approach

In the design of lattice domes, design engineers need expertise in areas such as configuration processing, nonlinear analysis, and optimization. These are extensive numerical, iterative, and lime-consuming processes that are prone to error without an integrated design tool. This article presents the application of a knowledge-based system in solving lattice-dome design problems. An operational prototype knowledge-based system, LADOME, has been developed by employing the combined knowledge representation approach, which uses rules, procedural methods, and an object-oriented blackboard concept. The system's objective is to assist engineers in lattice-dome design by integrating all design tasks into a single computer-aided environment with implementation of the knowledge-based system approach. For system verification, results from design examples are presented.

Assessment of body composition by bioelectrical impedance analysis without the need for measurement of height

Conventional whole-body single frequency bioelectrical impedance analysis (BIA) of body composition typically uses height as a surrogate measure of conductor length. A new method of BIA analysis for the prediction of body cell mass (BCM) and extracellular water (ECW, as % body weight) not using height has been introduced-the Soft Tissue Analyser (STA(TM), Akern Sri, Florence, Italy)-making it ideal for use in subjects where measurement of height is difficult or impossible. The performance of the new analytical method in predicting BCM and ECW in 139 normal control subjects was assessed by comparison with reference data obtained from a four-component (4-C) model of body composition and with predictions obtained from conventional BIA analysis. Both predicted BCM and ECW were strongly (r = 0.82, SEE = 6.3 kg and 0.89, SEE = 1.3 kg respectively) correlated with the corresponding 4-C model measurements although differing significantly from the lines of identity (P < 0.0001). Fat-free mass, calculated from STA estimates of BCM and ECW, was better predicted (r = 0.91, SEE = 5.6 kg). The significant differences in STA-group mean values for BCM and ECW and wide limits of agreement compared with the reference data indicate that the method cannot be used with confidence for prediction of these body compartments despite the obvious advantage of not requiring an accurate measurement of height. (C) 2001 Harcourt Publishers Ltd.