We introduce a new approach to three important problems in ray tracing: antialiasing, distributed light sources, and fuzzy reflections of lights and other surfaces. For antialiasing, our approach combines the quality of supersampling with the advantages of adaptive supersampling. In adaptive supersampling, the decision to partition a ray is taken in image‐space, which means that small or thin objects may be missed entirely. This is particularly problematic in animation, where the intensity of such objects may appear to vary. Our approach is based on considering pyramidal rays (pyrays) formed by the viewpoint and the pixel. We test the proximity of a pyray to the boundary of an object, and if it is close (or marginal), the pyray splits into 4 sub‐pyrays; this continues recursively with each marginal sub‐pyray until the estimated change in pixel intensity is sufficiently small. The same idea also solves the problem of soft shadows from distributed light sources, which can be calculated to any required precision. Our approach also enables a method of defocusing reflected pyrays, thereby producing realistic fuzzy reflections of light sources and other objects. An interesting byproduct of our method is a substantial speedup over regular supersampling even when all pixels are supersampled. Our algorithm was implemented on polygonal and circular objects, and produced images comparable in quality to stochastic sampling, but with greatly reduced run times.

The system requirements for an integrated telecare system are presented by using a modification of the CORE methodology. The resulting system model uses viewpoint analysis to establish the needs and requirements of both the client and the care providers within a system context and discusses the implications for a user-centered, technology-based solution referred to as "CarerNet." The implementation of CarerNet is considered in terms of the enabling technologies required within the local environment of the client and identifies the monitoring, networking requirements, and system intelligence necessary to the provision of a comprehensive telecare service. A hypothetical case study based on patient aftercare following discharge from the hospital is presented to illustrate the points discussed.

An approximation to the existing optimal algorithm for simultaneously tracking several moving targets is proposed which greatly reduces the required memory and number of calculations, but nevertheless retains reasonable accuracy (as is shown by analytic consideration and by Monte Carlo simulations) when the number of states is much greater than the number of targets. It is shown where errors arise in the approximation and how the errors tend to stabilize as the process evolves. Computational results on a highly idealized biological population surveillance problem are given that tend to confirm assertions concerning the relative computational efficiency and accuracy of the suboptimal rule in comparison to the optimal solution. A more realistic radar simulation study (20 targets and 10 000 states) is reported that suggests the scope of application of thc methodology proposed here.