Interactive Architectural Compositions in 3D Real-Time Virtual Environments

This paper presents an interactive computational system for developing architectural compositions within a 3D real-time virtual environment. The features of implemented system within the interface of Activeworlds platform includes (a) providing a set of 3D building objects that are made available within the virtual environment and can be utilized by the user to construct architectural compositions, (b) allowing users to modify both geometrical and non-geometrical properties of these objects, and (c) maintaining interrelationships between these objects using constrain-based rules automated by the developed system in real-time. The developed IAMVE (Interactive Architectural Modelling in Virtual Environments) system provides more flexibility to architectural designers and develops an edge to multi-user real time 3D virtual environments to be better utilized in the context of architectural desig

Two-Phase Flow in Pipes: Numerical Improvements and Qualitative Analysis for a Refining Process

Two-phase flow in pipes occurs frequently in refineries, oil and gas production facilities and petrochemical units. The accurate design of such processing plants requires that numerical algorithms be combined with suitable models for predicting expected pressure drops. In performing such calculations, pressure gradients may be obtained from empirical correlations such as Beggs and Brill, and they must be integrated over the total length of the pipe segment, simultaneously with the enthalpy-gradient equation when the temperature profile is unknown. This paper proposes that the set of differential and algebraic equations involved should be solved as a Differential Algebraic Equations (DAE) System, which poses a more CPU-efficient alternative to the “marching algorithm” employed by most related work. Demonstrating the use of specific regularization functions in preventing convergence failure in calculations due to discontinuities inherent to such empirical correlations is also a key feature of this study. The developed numerical techniques are then employed to examine the sensitivity to heat-transfer parameters of the results obtained for a typical refinery two-phase flow design problem

A knowledge-based diagnostic clinical decision support system for musculoskeletal disorders of the shoulder for use in a primary care setting

Background Twenty percent of cases seen by primary care clinicians (general practitioners; GPs) are musculoskeletal in nature, and approximately one-quarter of these are shoulder complaints. GPs are increasingly overloaded with clinical information and unfamiliarity with current research can easily lead to misdiagnosis and, in turn, to unnecessary test requests or onward specialist referrals. Well-designed diagnostic clinical decision support systems (CDSS) have been shown to facilitate clinical decision-making and reduce diagnostic errors. However, no CDSS have been developed or tested for musculoskeletal disorders.Methods We have developed a prototype knowledge-based diagnostic CDSS for musculoskeletal shoulder conditions. The CDSS uses Bayesian reasoning to diagnose six common musculoskeletal shoulder pathologies, based on current evidence and expert opinion. The CDSS was tested by comparing its diagnostic outcome against 50 case studies with known diagnosis by radiological imaging.Results The CDSS diagnostic validity and reliability was shown to be 88% with a Kappa value of 0.85 to a confidence level of 99% compared to known diagnosis by radiological imaging.Conclusions The results suggest that a Bayesian network-based CDSS is a promising instrument in the diagnosis of musculoskeletal shoulder conditions, having been shown to be valid and reliable for 50 case studies.Peer reviewe