Abstract
The Internet plays an important role in higher education institutions where Learning Management Systems (LMS) occupies a main role in the eLearning realm. In this chapter we aim to characterize the Internet and LMS usage patterns and their role in the largest Portuguese Polytechnic Institute. The usage patterns were analyzed in two components: characterization of Internet usage and the role of Internet and LMS in education. Using a quantitative approach, the data analysis describes the differences between gender, age and scientific fields. The carried qualitative analysis allows a better understanding of students' both motivations, opinions and suggestions of improvement. The outcome of this work is the presentation of the Portuguese students' profile regarding Internet and LMS usage patterns. We expect that these results can be used to select the most suitable digital pedagogical processes and tools to be adopted regarding the learning process and most adequate LMS's policies. © 2012, IGI Global.

Abstract
Compressive sensing (CS) has recently emerged and is now a subject of increasing research and discussion, undergoing significant advances at an incredible pace. The novel theory of CS provides a fundamentally new approach to data acquisition which overcomes the common wisdom of information theory, specifically that provided by the Shannon-Nyquist sampling theorem. Perhaps surprisingly, it predicts that certain signals or images can be accurately, and sometimes even exactly, recovered from what was previously believed to be highly incomplete measurements (information). As the requirements of many applications nowadays often exceed the capabilities of traditional imaging architectures, there has been an increasing deal of interest in so-called computational imaging (CI). CI systems are hybrid imagers in which computation assumes a central role in the image formation process. Therefore, in the light of CS theory, we present a transmissive single-pixel camera that integrates a liquid crystal display (LCD) as an incoherent random coding device, yielding CS-typical compressed observations, since the beginning of the image acquisition process. This camera has been incorporated into an optical microscope and the obtained results can be exploited towards the development of compressive-sensing-based cameras for pixel-level adaptive gain imaging or fluorescence microscopy.

Abstract
Protein aggregation became a widely accepted marker of many polyQ disorders, including Machado-Joseph disease (MJD), and is often used as readout for disease progression and development of therapeutic strategies. The lack of good platforms to rapidly quantify protein aggregates in a wide range of disease animal models prompted us to generate a novel image processing application that automatically identifies and quantifies the aggregates in a standardized and operator-independent manner. We propose here a novel image processing tool to quantify the protein aggregates in a Caenorhabditis elegans (C. elegans) model of MJD. Confocal microscopy images were obtained from animals of different genetic conditions. The image processing application was developed using MeVisLab as a platform to process, analyse and visualize the images obtained from those animals. All segmentation algorithms were based on intensity pixel levels. The quantification of area or numbers of aggregates per total body area, as well as the number of aggregates per animal were shown to be reliable and reproducible measures of protein aggregation in C. elegans. The results obtained were consistent with the levels of aggregation observed in the images. In conclusion, this novel imaging processing application allows the non-biased, reliable and high throughput quantification of protein aggregates in a C. elegans model of MJD, which may contribute to a significant improvement on the prognosis of treatment effectiveness for this group of disorders.

Abstract

Abstract
Collaboration programmes for coordinated replenishment in buyer-supplier dyads have become popular among companies willing to increase market responsiveness, decrease safety stocks and increase control over the supply chain. In parallel, logistic performance measures have been identified as a crucial element for defining objectives, supervise improvements and managing effectively the supply chain. We explore the use of the common scorecard to share performance measurements between buyer and supplier in collaboration projects. The common scorecard works as a tool to facilitate the communication between partners and to share transparently partners' individual objectives in a structured and objective way. Its implementation and beneficial impact is shown in a case study of a vendor managed inventory operating in an environment of high demand volatility, long lead-time and customised products. Copyright © 2011 Inderscience Enterprises Ltd.

Abstract
The integration and composition of software systems requires a good architectural design phase to speed up communications between (remote) components. However, during implementation phase, the code to coordinate such components often ends up mixed in the main business code. This leads to maintenance problems, raising the need for, on the one hand, separating the coordination code from the business code, and on the other hand, providing mechanisms for analysis and comprehension of the architectural decisions once made. In this context our aim is at developing a domain-specific language, CoordL, to describe typical coordination patterns. From our point of view, coordination patterns are abstractions, in a graph form, over the composition of coordination statements from the system code. These patterns would allow us to identify, by means of pattern-based graph search strategies, the code responsible for the coordination of the several components in a system. The recovering and separation of the architectural decisions for a better comprehension of the software is the main purpose of this pattern language.