Abstract

Abstract
Using multiple classifiers for increasing learning accuracy is an active research area. In this paper we present two related methods for merging classifiers. The first method, Cascade Generalization, couples classifiers loosely. It belongs to the family of stacking algorithms. The basic idea of Cascade Generalization is to use sequentially the set of classifiers, at each step performing an extension of the original data by the insertion of new attributes. The new attributes are derived from the probability class distribution given by a base classifier. This constructive step extends the representational language for the high level classifiers, relaxing their bias. The second method exploits tight coupling of classifiers, by applying Cascade Generalization locally. At each iteration of a divide and conquer algorithm, a reconstruction of the instance space occurs by the addition of new attributes. Each new attribute represents the probability that an example belongs to a class given by a base classifier. We have implemented three Local Generalization Algorithms. The first merges a linear discriminant with a decision tree, the second merges a naive Bayes with a decision tree, and the third merges a linear discriminant and a naive Bayes with a decision tree. All the algorithms show an increase of performance, when compared with the corresponding single models. Cascade also outperforms other methods for combining classifiers, like Stacked Generalization, and competes well against Boosting at statistically significant confidence levels.

Abstract
This paper describes the requirements analysis and system specification of an Order Promise module to be used as part of a broader Decision Support System for production and operations planning of a Virtual Enterprise. This work is part of a broader project with a particular focus on the microelectronics industry which is a good example of Virtual Enterprise, and where a quick response to the customers needs and to unpredictable changes in production conditions is considered a major factor for success. First, the analysis and specification are presented within a development framework that involves the study of organizational issues of semiconductor enterprises. The use of ontological engineering for supporting the communication and shared understanding of the system concepts is explained and a virtual enterprise ontology is outlined. Following the clarification of the concept of virtual enterprise, the generic techno-organizational requirements for the information system are derived. Finally, a specification of the global planning module and a more detailed one regarding the order promise module is presented.

Abstract
From the general trend towards global markers and a growing customer orientation, new concepts and forms of organisation are emerging, such as distributed or networked enterprises. One key requirement of these new paradigms is the availability of models and tools to support order negotiation with the optimisation of manufacturing routes and logistics and ensuring the co-ordination of all participating entities. We address the problem of planning an incoming customer order to be produced in a distributed (multi-site) and multi-stage production system, in particular, we have used as a case study the industry of semiconductors (in the business area of application specific integrated circuits). The problem is tackled in a hierarchical model, in two levels: there is a global network planning procedure, and a set of local capacity models associated to the different production units reflecting their particular features. An approach based on simulated annealing is presented, as well as a specially designed constructive heuristic, that takes into account many of the real world constraints and complexities. The general performance of the simulated annealing algorithm is assessed through some preliminary computational experiments. Finally, some concluding remarks and current directions of research are presented.

Abstract
Formal approaches to the design of interactive systems rely on reasoning about properties of the system at a very high level of abstraction. Specifications to support such an approach typically provide little scope for reasoning about presentations and the representation of information in the presentation. In contrast, psychological theories such as distributed cognition place a strong emphasis on the role of representations, and their perception by the user, in the cognitive process. However, the post-hoc techniques for the observation and analysis of existing systems which have developed out of the theory do not help us in addressing such issues at the design stage. Mn this paper we show how a formalisation can be used to investigate the representational aspects of an interface. Our goal is to provide a framework to help identify and resolve potential problems with the representation of information, and to support understanding of representational issues in design. We present a model for linking properties at the abstract and perceptual levels, and illustrate its use in a case study of a flight deck instrument. There is a widespread consensus that proper tool support is a prerequisite for the adoption of formal techniques, but the use of such tools can have a profound effect on the process itself. In order to explore this issue, we apply a higher-order logic theorem prover to the analysis.

Abstract
Wisdom is a new software engineering method addressing the specific needs of small reams that develop and maintain interactive systems. Because Wisdom defines a process, notation, and project philosophy, it can smoothly be applied in small companies leveraging on their communication, speed, and flexibility.