Abstract
This paper presents a method for modelling and monitoring the individual decision process of wine tasting panelllists. The individual decision of approving or rejecting a wine is based on the panellist's evaluation of the wine characteristics. The decision process is modelled through a logistic regression where the dependent variable is the decision itself (rejected-0 or approved-1) and the independent variables are the characteristics that were considered relevant for the wine evaluation. The process is monitored using a CUSUM control chart for binomial proportions. The control chart variable is the number of disagreements observed (in a sample of size N) between the actual decisions of the panellist and the results anticipated by the logistic regression model. The method was tested in the Port Wine Institute. Such a test revealed that the logistic model is a useful tool for clarifying both the way in which the wine evaluation process is carried out, and how the decisions are taken. Furthermore, the test has also showed that the control chart is responsive to significant changes of the individual decision process.

Abstract

Abstract
Aspect Oriented Programming (AOP) is a programming paradigm that aims at solving the problem of crosscutting concerns being normally scattered throughout several units of an application. Although an important step forward in the search for modularity, by breaking the notion of encapsulation introduced by Object Oriented Programming (OOP), AOP has proven to be prone to numerous problems caused by conflicts and interferences between aspects. This paper presents work that explores the proven unit testing techniques as a mean to help developers describe the behavior of their aspects and to advise them about possible conflicts and interferences. Copyright © 2007 ACM.

Abstract

Abstract
This paper describes the technology (software & hardware) used in the Gait Analysis Laboratory of CRPG - Centro de Reabilitac (a) over tildeo Profissional de Gaia. This laboratory is mainly intended to support CRPG with quantitative data for clinical rehabilitation of patients with musculoskeletal pathologies, namely in the lower limbs. Usually, for the gait analysis is considered data obtained from several acquisition sensors, such as: image cameras, electromyographic devices, pressure devices and force plates. This paper also presents briefly how quantitative motion analysis can be used for a clinical point of view and it presents the influence of image algorithms in gait rehabilitation.

Abstract
We address the problem of tracking efficiently feature points along image sequences. To estimate the undergoing movement we use an approach based on Kalman filtering which performs the prediction and correction of the features movement in every image frame. In this paper measured data is incorporated by optimizing the global correspondence set based on efficient approximations of the Mahalanobis distances (MD). We analyze the difference between using the MD and its efficient approximation in the tracking results, and examine the related computational costs. Experimental results which validate our approach are presented.