Abstract
Travel time prediction is an important tool for the planning tasks of mass transit and logistics companies. ID this paper we investigate the use of regression methods for the problem of predicting the travel time of buses in a Portuguese public transportation company. More specifically, we empirically evaluate the impact of varying parameters on the performance of different regression algorithms, such as support vector machines (SVM), random forests (RF) and projection pursuit, regression (PPR). We also evaluate the impact of the focusing tusks (example selection; domain value definition and feature selection) in the accuracy of those algorithms. Concerning the algorithms, we observe that 1) RF is quite robust to the choice of parameters and focusing methods: 2) the choice of parameters for SVM can be made independently of focusing methods while 3) for PPR they should be selected simultaneously. For the focusing methods, we observe that a stronger effect is obtained using example selection, particularly in combination with SVM.

Abstract
The purpose of this research is to develop a process capable of optimizing the capture of light in a circumscribed space, using a responsive system of skylights. Research is focused on the design of irregular dome-like pavilion spaces circumscribed by curved surfaces, but the envisioned process might be applied to other functional, formal, and spatial typologies. The design of the pavilion starts with the generation of a surface, later tessellated into a matrix of skylights depending on the geographic location and sun orientation. In the constructed pavilion, the skylights react to the variation of daylight intensity during the day to satisfy specified internal lighting needs. Simultaneously, the integration of conception and fabrication using digital tools (CAD-CAM) facilitates the construction of a non-standard, parametric geometry, thereby diminishing the costs of production and allowing for personalization, while assuring global sustainability.

Abstract
In this text is proposed a simple method for estimating or characterize the behaviour of complex systems, in particular when these are being studied throughout simulation. Usual ways of treating the complex output data obtained from the activity (real or simulated) of such a kind of systems, which in many cases people classify and analyse along the time domain, usually the most, complex perspective, is herein substituted by the idea of representing such data in the frequency domain, somehow like what is commonly done in Fourier Analysis and in Quantum Mechanics. This is expected to give the analyst a more holistic perspective oil the system's behaviour, as well as letting him/her choose almost freely the complex states in which such behaviour is to be projected. We hope this will lead to simpler processes in characterizing complex systems.

Abstract
This paper is divided into four parts: the first one introduces SADEX, a fuzzy Case Based Reasoning (CBR) System for fault diagnosis. The second focus on its observation relevance factors and shows how the results are in complete agreement with the relevance concept introduced by Robertson and Spark-Jones in their well known and proved technique for document retrieval. The third describes how equipment composition information can be used to generalize and adapt case solutions to new and unknown occurrences; this generalization is based on a taxonomic similarity between functionally autonomous modules (FAMs). Finally the MKM-Maintenance Knowledge Manager system is introduced.

Abstract
This paper is divided into three parts: the first one introduces SADEX, a fuzzy Case Based Reasoning (CBR) Expert System (ES) for fault diagnosis. The second focus on its observation relevance factors and shows how the results are in entire agreement with the relevance concept introduced by Robertson and Spark-Jones in their well known and proved technique of document retrieval. Finally we describe how the equipment composition information can be used to generalize and adapt case solutions to unknown occurrences. This generalization is based on a taxonomic similarity between functionally autonomous modules (FAM) or components. Some formulae for evaluating this similarity are derived.

Abstract
In industry, spare equipments are often shared by many workplaces with identical equipments to assure the production rate required to fulfill delivery dates. These types of systems arc called "Maintenance Float Systems". The main objective of managers that deal with these types of systems is to assure the required capacity to deliver orders on time and at minimum cost. Not delivering on time has often important consequences; it call cause loss of costumer goodwill, loss of sales and call damage organization's image. Maintenance cost is the indicator more frequently used to configure maintenance float systems and to invest in maintenance workers or spare equipments. Once the system is configured, other performance indicators must be used to characterize and measure the efficiency of the system. Different improvement initiatives call be performed to enhance the performance of maintenance float systems: performing preventive maintenance actions, implementation of autonomous maintenance, improvement of equipments maintainability, increase of maintenance crews' efficiency etc. "Carrying out improvement based on facts" is a principle of Total Quality Management (TQM) in order to step to business excellence. It requires monitoring processes through performance measures. This work aims to characterize and highlight the differences and relationships between three types of performance measures-equipment availability, equipment utilization and workplace occupation, in the context of maintenance float system. Definitions and expressions of these three indicators are developed for maintenance float systems. The relationship between maintenance float systems efficiency and the referred indicators is shown. Other indicators are also proposed and compared with the first ones (number of standby equipments, queue length etc.).