Abstract
The Intensive Care Units (ICUs) of several Portuguese hospitals have been using the intensive.care information system (ICS) for the past three years. This system was developed under specification of Medical Doctors (MDs) from ICUs. As the main focus of the initial project was on adding functionality to the system, little attention was given to non-functional requirements such as usability. This paper describes the current ICS and the results of preliminary interviews with its main stakeholders to determine high-level functional and non-functional evolution requirements. The objective of the overall study is to propose usability requirements for such system, in particular from MDs and nurses, its main users. A prototype of an improved user interface will be evaluated to support the development of the next version of the system. The interviews with a key developer and several MDs resulted so far in the conclusion that ICS is a very helpful tool but requires improvements in several modules, such as Patient Entrance and Patient Evolution. However, more advanced modules, such as Infections Management, will also require some adaptations of work processes in ICUs, in order to benefit from the full support that ICS can provide.

Abstract
This paper develops measures, based on the Malmquist index, that enable the decision making units' internal inefficiencies to be distinguished from those associated with their group (or program) characteristics. The applicability of these measures is illustrated with the assessment of bank branches' performance. The analysis involves the construction of an index reflecting the relative performance of branches in four different regions, which can be decomposed into an index for the comparison of within-group efficiency spread, evaluating internal managerial efficiencies, and an index for the comparison of frontier productivity, reflecting the impact of environmental factors and regional managerial policies on branches' productivity.

Abstract
We compare two link analysis ranking methods of web pages in a site. The first, called Site Rank, is an adaptation of PageRank to the granularity of a web site and the second, called Popularity Rank, is based on the frequencies of user clicks on the outlinks in a page that are captured by navigation sessions of users through the web site. We ran experiments on artificially created web sites of different sizes and on two real data sets, employing the relative entropy to compare the distributions of the two ranking methods. For the real data sets we also employ a nonparametric measure, called Spearman's footrule, which we use to compare the top-ten web pages ranked by the two methods. Our main result is that the distributions of the Popularity Rank and Site Rank are surprisingly close to each other, implying that the topology of a web site is very instrumental in guiding users through the site. Thus, in practice, the Site Rank provides a reasonable first order approximation of the aggregate behaviour of users within a web site given by the Popularity Rank.

Abstract
This paper describes the study on example selection in regression problems using mu-SVM (Support Vector Machine) linear as prediction algorithm. The motivation case is a study done on real data for a problem of bus trip time prediction. In this study we use three different training sets: all the examples, examples from past days similar to the day where prediction is needed, and examples selected by a CART regression tree. Then, we verify if the CART based example selection approach is appropriate on different regression data sets. The experimental results obtained are promising.

Abstract
In this article 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 on 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
The nature of warehouse design requires the manipulation of large amounts of data and is often an iterative process that forces the designer to go through the different design phases several times before reaching the final solution. This suggests an integrated computer environment that can give support to the user during all the design phases. The need for a flexible tool, easier to use, lead to the development of a Decision Support System: AWARD (Advanced WARehouse Design). This paper presents further developments of the DSS and shows a successful example of application of the new functionalities: a simulation model of a full automated warehouse developed for EFACEC, a large Portuguese company in the warehouse design, building and consultancy business.