From virtual worlds to the therapist's office

The increasing recognition of the importance of emotional state in both disease and health makes imperative the need for health care providers to evaluate the psychological status of patients. In primary care medical practice, between 30 and 60% of complaints prompting visits to the physician's office have a significant emotional component. In addition, rates of depressive illness are estimated to be as high as 20% in the general population. Prompt recognition of anxiety, depression, personality disorder, and psychosis is important for correct interpretation of historical and physical findings during examination and evaluation of patients. The establishment of a caring and trusting relationship is crucial so that patients can comfortably express concerns, and so that a discussion leading to an agreeable therapeutic plan can be decided upon. This process has traditionally taken place in the one-on-one format between the health care provider and patient. Many physicians and therapists are interested in exploring whether virtual reality can augment the therapeutic process, and thus improve diagnostic capabilities     

A Polygonal Approximation for General 4-Contours Corresponding to Weakly Simple Curves

Journal of Mathematical Imaging and Vision - The paper proposes a polygonal approximation for closed 4-paths obtained from standard contour following under 4-connectivity. Those 4-contours generate...     

Unsupervised multiresolution segmentation for images with low depthof field

Unsupervised segmentation of images with low depth of field (DOF) is highly useful in various applications. This paper describes a novel multiresolution image segmentation algorithm for low DOF images. The algorithm is designed to separate a sharply focused object-of-interest from other foreground or background objects. The algorithm is fully automatic in that all parameters are image independent. A multi-scale approach based on high frequency wavelet coefficients and their statistics is used to perform context-dependent classification of individual blocks of the image. Unlike other edge-based approaches, our algorithm does not rely on the process of connecting object boundaries. The algorithm has achieved high accuracy when tested on more than 100 low DOF images, many with inhomogeneous foreground or background distractions. Compared with he state of the art algorithms, this new algorithm provides better accuracy at higher speed     

Knowledge and Database Management

Artificial intelligence techniques are effective in dealing with the complexity of large databases. Their use can move well-understood human decision-making processes into the computer system.     

Evaluating recursive queries in distributed databases

The execution of logic queries in a distributed database environment is studied. Conventional optimization strategies, such as the early evaluation of selection conditions and the clustering of processing to manipulate and exchange large sets of tuples, are redefined in view of the additional difficulties due to logic queries, in particular to recursive rules. In order to allow efficient processing of these logic queries, several program transformation techniques that attempt to minimize distribution costs based on the idea of semijoins and generalized semijoins in conventional databases are presented. Although local computation of semijoins is not possible for the general case, classes of programs are indicated for which these transformations succeed in producing set-oriented computation. Processes evaluating the recursive program in a distributed network are described, and an efficient method for testing the termination of the computation is developed. The approach is compared with sequential as well as dataflow-oriented evaluation