Abstract
Discretization of continuous attributes is an important task for certain types of machine learning algorithms. Bayesian approaches, for instance, require assumptions about data distributions. Decision Trees on the other hand, require sorting operations to deal with continuous attributes, which largely increase learning times. This paper presents a new method of discretization, whose main characteristic is that it takes into account interdependencies between attributes. Detecting interdependencies can be seen as discovering redundant attributes. This means that our method performs attribute selection as a side effect of the discretization. Empirical evaluation on five benchmark datasets from UCI repository, using C4.5 and a naive Bayes, shows a consistent reduction of the features without loss of generalization accuracy.

Abstract
This paper presents an architecture (Multi-µ) being implemented to study and develop software based fault tolerant mechanisms for Real-Time Systems, using the Ada language (Ada 95) and Commercial Off-The-Shelf (COTS) components. Several issues regarding fault tolerance are presented and mechanisms to achieve fault tolerance by software active replication in Ada 95 are discussed. The Multi-µ architecture, based on a specifically proposed Fault Tolerance Manager (FTManager), is then described. Finally, some considerations are made about the work being done and essential future developments. © 1998 ACM.

Abstract
A major transport company working in a urban environment, in Portugal, has been developing an automatic vehicle location (AVL) system, based on a telemetric system to assist the optimisation of vehicle use, time-tabling and scheduling. The data is used in real time and stored on disk for later statistical analysis. Several factors can corrupt data during acquisition and transmission, and make it impossible to automatically extract useful information. A pre-processing stage is needed to extract inconsistent data. The paper describes a strategy, based on simulation, to pre-process the data in order to analyse data consistency and classify the messages as correct or incorrect. Copyright (C) 1998 IFAC.

Abstract
In this paper, we present a multimedia system named BioBeAMS (Bio-signal Behavior Attachment Multimedia System) for assessment of attachment organizations and heart rate in Strange Situation experimental procedure for mother to child attachment study (a well known psychological procedure). Attachment patterns assessed through this procedure have been conceived as different strategies to regulate the access to relevant attachment information and to process distress-related information. The psycho-physiological activation led by emotional processing of attachment experiences during the Strange Situation procedure may be a critical factor for understanding the subject's psychological attachment strategies. BioBeAMS is an application, which integrates the bio-signal, video/audio of the psychological experimental procedure and the rater's coding together, running in the MS Window 95 environment on a PC. Using this system, we can acquire ECG signal and capture video/audio in a synchronous way, It also enables the raters to subsequently analyze and evaluate psychological and physiological events during review to study possible relations.

Abstract
Parallel logic programming (PLP) systems have obtained good performance on traditional bus-based shared-memory architectures. However, the scalable multiprocessors being developed today pose new challenges. Our experience with a sophisticated PLP system, Andorra-I, demonstrates that indeed performance suffers greatly on modern architectures. In order to improve performance, we perform a detailed analysis of the cache behaviour of all Andorra-I data structures via execution-driven simulation of a DASH-like multiprocessor. Based on this analysis we optimise the Andorra-I code using 5 different techniques. Our results show that the techniques provide significant performance improvements, leading to the conclusion that PLP systems can and should perform well on modern scalable multiprocessors.

Abstract
A new heuristic approach is presented for scheduling economic lots in a multi-product single-machine environment. Given a pre-defined master sequence of product setups, an integer linear programming formulation is developed which finds an optimal subsequence and optimal economic lots. The model takes explicit account of initial inventories, setup times and allows setups to be scheduled at arbitrary epochs in continuous time, rather than restricting setups to a discrete time grid. We approximate the objective function of the model and solve to obtain an optimal capacity feasible schedule for the approximate objective. The approach was tested on a set of randomly generated problems, generating solutions that are on average 2.5% above a lower bound on the optimal cost. We also extend the approach to allow shortages. (C) 1998 Elsevier Science B.V.