which should conform to basic physical intuition about distance. Thus, first, the only point y at distance 0 from a point x is y = x itself. Second, distance does not depend on direction: the distance from x to y is the same as the distance from y to x. Third, thinking that the distance from x to y should correspond to a shortest route of some kind from x to y, the distance from x to y should b...

With distance learning becoming more of a reality than a novelty in many undergraduate and graduate training programs, web-based clinical simulations can be identified as an instructional option in distance education that has both a sound pedagogical foundation and clinical relevance. The purpose of this article is to report on the instructional effectiveness of a web-based pure-tone audiometry...

INTRODUCTION Research in the field of distance education has recognized the need for a change and modification of the faculty role in teaching at a distance technological advancements are an important part of the distance-learning environment, basic changes in teaching methods, technique, and motivation are needed to make distance education more effective (Purdy & Wright, 1992). Many studies ci...

vspace{0.2cm}In this paper, we design a data structure for the following problem. Let $pi$ be an $x$-monotone trajectory with $n$ vertices in the plane and $epsilon >0$. We show how to preprocess $pi$ and $epsilon$ into a data structure such that for any horizontal query segment $Q$ in the plane, one can quickly determine the minimal continuous fraction of $pi$ whose Fr{'e}chet and Hausdo...

Stochastic watershed is an image segmentation technique based on mathematical morphology which produces a probability density function of image contours. Estimated probabilities depend mainly on local distances between pixels. This paper introduces a variant of stochastic watershed where the probabilities of contours are computed from a gaussian model of image regions. In this framework, the ba...

The watershed line is the basic tool for segmenting images in mathematical morphology. A rigorous definition is given in terms of a distance function called topographic distance. If the topographical function is itself a distance function, then the topographical distance becomes identical with the geodesic distance function and the watershed becomes identical with the skeleton by zone of influe...

Many distance-related algorithms, such as knearest neighbor learning algorithms, locally weighted learning algorithms etc, depend upon a good distance metric to be successful. In this kind of algorithms, a key problem is how to measure the distance between each pair of instances. In this paper, we provide a survey on distance metrics for nominal attributes, including some basic distance metrics...