This paper shows how it is possible to represent the complex data structures needed to support electronic commerce applications in the semantic web using ontologies. The conventional mereological or subtype-oriented refinement of the ontology is supplemented by a method of coordinated refinement...

We compare several geometrical theories based on mereology () in a unified framework. Most theories in this area lack in formalization and this prevents any systematic logical analysis. We overcome this problem by isolating a common domain in R and, selecting natural interpretations, we use this...

In the present paper we present the application of machine learning in building decision making models used for consuiting about the clothing style, cost range, colour etc. of young people. Such models can be used in designing, planing the production, marketing and fashion forecasting of...

Pseudo random number generators (PRNGs) are the basic input to the stochastic selection, recombination, and mutation operations of genetic algorithms (GAs). Although it does not seem like a crucial decision, recent studies suggest that the choice of PRNG can affect the performance of GAs. The...

The FIRST survey (Faint Images of the Radio Sky at Twenty-cm) is scheduled to cover 10,000 square degrees of the northern and southern galactic caps. Until recently, astronomers classified radio-emitting galaxies through a visual inspection of FIRST images. Besides being subjective, prone to...

In this paper, first we construct a railway circuit based on three types of switches and on crossings. Such a circuit is able to simulate the computation of any Turing machine, in particular of a universal one. That result was proved by Ian Stewart in [3], In this paper, we give another...

Support vector machines are increasingly being used for problems involving both regression and classification. An inherent limitation of the original model formulation meant that the models output could not be interpreted probabilistic framework. This issue has recently been addressed, so that...

Reinforcement learning systems improve behaviour based on scalar rewards from a critic. In this work vision based behaviours, servoing and wandering, are learned through a Q-learning method which handles continuous states and actions. There is no requirement for camera calibration, an actuator...

We present a process-algebraic approach to situated multi-agent systems which incorporates syntax for agent systems as well as for the environments (workspaces) they live in. Agent states are characterized by (1) a belief state, (2) a goal (desire, need) state and (3) a capabilities state....

An intelligent optimal control system is proposed for the tracking control of an n-link robot manipulator to achieve high-precision position control. In the intelligent optimal control system, a fuzzy neural network (FNN) controller is used to learn a nonlinear function in the optimal control...