Time-dependent stochastic shortest path(s) algorithms for a scheduled transportation network

Following on from our work concerning travellers’ preferences in public transportation networks (Wu and Hartley, 2004), we introduce the concept of stochasticity to our algorithms. Stochasticity greatly increases the complexity of the route finding problem, so greater algorithmic efficiency becomes imperative. Public transportation networks (buses, trains) have two important features: edges can only be traversed at certain points in time and the weights of these edges change in a day and have an uncertainty associated with them. These features determine that a public transportation network is a stochastic and time-dependent network. Finding multiple shortest paths in a both stochastic and time-dependent network is currently regarded as the most difficult task in the route finding problems (Loui, 1983). This paper discusses the use of k-shortest-paths (KSP) algorithms to find optimal route(s) through a network in which the edge weights are defined by probability distributions. A comprehensive review of shortest path(s) algorithms with probabilistic graphs was conducted

Semantic-driven matchmaking of web services using case-based reasoning

With the rapid proliferation of Web services as the medium of choice to securely publish application services beyond the firewall, the importance of accurate, yet flexible matchmaking of similar services gains importance both for the human user and for dynamic composition engines. In this paper, we present a novel approach that utilizes the case based reasoning methodology for modelling dynamic Web service discovery and matchmaking. Our framework considers Web services execution experiences in the decision making process and is highly adaptable to the service requester constraints. The framework also utilises OWL semantic descriptions extensively for implementing both the components of the CBR engine and the matchmaking profile of the Web services

Evaluation by simulation of interpolation and acceleration algorithms for Stepper Motors

Stepper motors are used to control CNC machines for many applications. As well as following the required path precisely, it is also important that the motion be smooth and that the surface speed be controllable. Improved interpolation algorithms for individual straight lines and circular arcs have been developed using distance as a parameter [Chow et al, 2002], [Chow, 2003]. The algorithms control the motor by means of pulses and the generation of the pulse timings is based on the geometry of the shape. For high speeds it is necessary to allow smooth acceleration at the beginning and similar smooth deceleration at the end. Thus, appropriate acceleration and deceleration algorithms have been developed for use with the new interpolation algorithms. This paper describes how simulation has been used to evaluate the new algorithms and compare them with previous algorithms. The algorithms are described for the 2D case but the principle can be extended to 3D

A reconfigurable parallel processing structure for adaptive state estimation

The computational requirement of adaptive state estimation is examined, and a previously proposed chain parallel processor is extended to satisfy these requirements. An In this paper, the computational requirement of these algorithms will be examined. In particular the influence of the above parallel schemes on multiprocessing structures will be used to determine the special hardware facets required. These will then be designed into the chain multiprocessor scheme proposed in a previous pape