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The industrial environment offers many potential applications for image processing, especially in inspection for quality, automatic assembly and the guidance of robotic devices. But development of an appropriate algorithm may require the testing of very many image processing methods. However, a computer system by British Robotic Systems allows easy and interactive testing.

Downtime data have been acquired from a 1980 MW capacity coal‐fired power station. These data refer to a pulverised fuel system which comprises ten mills, each of which, for the purpose of reliability analysis, has six sets of components liable to failure. The majority voting of the mills was a seven‐out‐of‐ten system. Individual unit failure patterns are determined using a family of exponential models and are used to provide total group reliability patterns, and a computerised alogorithm for analysis of the voting system is developed. A methodology for scheduling majority vote equipment working with non‐symmetrical overhaul downtimes is presented.

In this paper jobshop scheduling problem was considered on automated manufacturing systems with the closed loop and unidirectional material handling system. The objective of this research is to develop and evaluate heuristic scheduling procedures to improve productivity by minimizing makespan. Especially travel time of material handling system as well as processing time was considered in the proposed alogorithm. The heiristic algorithms are implemented for various cases. The results show that the proposal algorithms provide better solutions in productivity, frequency, job waiting time and the number of waiting jobs than the random scheduling algorithm.

This study describes the structure and function of a new financial modeling technique, namely, the Artificial Neutral Network (ANN) in predicting financial markets’ behavior. With the advancement of the computer technology to date, ANN allows us to imitate human reasoning and thought processes in identifying the optimal trading strategies in the financial markets. The paper identifies the theory and steps involved in performing ANN and Generic Alogorithm in financial markets, the accuracy of the computer learning process, and the appropriate ways to use this process in developing trading strategies. It further discusses the superiority of ANN over traditional methodologies. The study concludes with the description of successful use of ANN by various financial institutions.

Nowadays, applications dealing with information extracted from images are commonplace. The widespread use of multimedia information (images, video, audio etc.) makes necessary applications capable of storing, and therefore retrieving, it. Information extracted from images is usually complex and high dimensional. The extraction of non‐textual low‐level indexing features from images is now a research field, and this process principally suffers because of the computational cost of the high dimensionality of those features. A new way to classify and match low‐level features extracted from images, for retrieval purposes, is presented in this paper. M‐tree and R‐tree structures are used, as well as an incremental version of the k‐means classification alogrithm. This set of alogrithms is used to solve the problem of low performance when retrieving previously catalogued images.

Looks at memetics, a new science of memes (a unit of cultural material propagated by an imitation process). Examines its origins and attempts to show its significance for the business audience in relation to understanding customer behaviour. Concludes that memetics is still in its infancy and, because of this, it still has philosophical and methodological issues that need to be addressed before it can be considered to be a new paradigm for understanding customer behaviour.

The experimental online catalogue Okapi has been running at one of the Polytechnic of Central London's (PCL) library sites for the last eighteen months. The work of this British Library project has been reported previously in VINE and the report itself which recorded the development of Okapi and outlined the rationale behind its design has been extensively discussed since its publication.

Presents research on human memory modelling. Gives a description of the memory process (as a whole) in its functional details by means of adding, processing and synthesizing psychological data using the creation of a model base. Compares the created psychological equivalent to the adequate mathematical‐algorithmic multi‐apparatus descriptions. Presents the programme‐developed human memory model as a precondition for micro‐electronic realizations (robot technique, computers and other bionic‐cybernetical systems).

The grouping of parts and machines for design of cellular manufacturing systems is carried out by clustering analysis. Two major drawbacks of some clustering algorithms have been identified in handling bottleneck machines for forming machine cells. These drawbacks include solution inconsistency and possible misclustering which result in unnecessary bottleneck machines required. Presents a more robust clustering algorithm to overcome these drawbacks. The algorithm consists of four stages: selection of initial cluster centres; cluster‐seeking analysis; eliminating unnecessary bottleneck machines; and new parts assignments. The decision functions based on the formed machine cells are defined to assign new parts to the machine cells. The algorithm is capable of selecting an ideal set of initial cluster centres, and minimizing the number of bottleneck machines required for forming the desired number of machine cells. It can also provide alternative design of machine cells to accommodate the existing production environment.