The formal representation of process system modelling assumptions and their implications

In order to analyse the effect of modelling assumptions in a formal, rigorous way, a syntax of modelling assumptions has been defined. The syntax of modelling assumptions enables us to represent modelling assumptions as transformations acting on the set of model equations. The notion of syntactical correctness and semantical consistency of sets of modelling assumptions is defined and methods for checking them are described. It is shown on a simple example how different modelling assumptions act on the model equations and their effect on the differential index of the resulted model is also indicated.

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.

On learning context-free and context-sensitive languages

The long short-term memory (LSTM) is not the only neural network which learns a context sensitive language. Second-order sequential cascaded networks (SCNs) are able to induce means from a finite fragment of a context-sensitive language for processing strings outside the training set. The dynamical behavior of the SCN is qualitatively distinct from that observed in LSTM networks. Differences in performance and dynamics are discussed.

Two new tools for assessing patients' knowledge and beliefs about obstructive sleep apnea and continuous positive airway pressure therapy

Background and purpose: Patients' knowledge and beliefs about their illnesses are known to influence a range of health related variables, including treatment compliance. It may, therefore, be important to quantify these variables to assess their impact on compliance, particularly in chronic illnesses such as Obstructive Sleep Apnea (OSA) that rely on self-administered treatments. The aim of this study was to develop two new tools, the Apnea Knowledge Test (AKT) and the Apnea Beliefs Scale (ABS), to assess illness knowledge and beliefs in OSA patients. Patients and methods: The systematic test construction process followed to develop the AKT and the ABS included consultation with sleep experts and OSA patients. The psychometric properties of the AKT and ABS were then investigated in a clinical sample of 81 OSA patients and 33 healthy, non-sleep disordered adults. Results: Results suggest both measures are easily understood by OSA patients, have adequate internal consistency, and are readily accepted by patients. A preliminary investigation of the validity of these tools, conducted by comparing patient data to that of the 33 healthy adults, revealed that apnea patients knew more about OSA, had more positive attitudes towards continuous positive airway pressure (CPAP) treatment, and attributed more importance to treating sleep disturbances than non-clinical groups. Conclusions: Overall, the results of psychometric analyses of these tests suggest these measures will be useful clinical tools with numerous beneficial applications, particularly in CPAP compliance studies and apnea education program evaluations. (C) 2004 Elsevier B.V. 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.