Abstract
Motion sensing plays an important role in the study of human movements, motivated by a wide range of applications in different fields, such as sports, health care, daily activity, action recognition for surveillance, assisted living and the entertainment industry. In this paper, we describe how to classify a set of human movements comprising daily activities using a wearable motion capture suit, denoted as FatoXtract. A probabilistic integration of different classifiers recently proposed is employed herein, considering several spatiotemporal features, in order to classify daily activities. The classification model relies on the computed confidence belief from base classifiers, combining multiple likelihoods from three different classifiers, namely Na < ve Bayes, artificial neural networks and support vector machines, into a single form, by assigning weights from an uncertainty measure to counterbalance the posterior probability. In order to attain an improved performance on the overall classification accuracy, multiple features in time domain (e.g., velocity) and frequency domain (e.g., fast Fourier transform), combined with geometrical features (joint rotations), were considered. A dataset from five daily activities performed by six participants was acquired using FatoXtract. The dataset provided in this work was designed to be extremely challenging since there are high intra-class variations, the duration of the action clips varies dramatically, and some of the actions are quite similar (e.g., brushing teeth and waving, or walking and step). Reported results, in terms of both precision and recall, remained around 85 %, showing that the proposed framework is able to successfully classify different human activities.

Abstract
A Fabry-Perot interferometer based on an array of soda-lime glass microspheres is proposed for temperature sensing. The microspheres are introduced in a hollow-core silica tube using a tapered fiber tip. After the insertion of each microsphere the sensor is subjected to temperature measurements. The sensor exhibits non-linear behavior and a dependence on the number of microspheres is observed. A maximum sensitivity of 11.13 pm/degrees C is achieved, when there is only one microsphere inside the capillary structure.

Abstract
Large scale integration of distributed generation (DG), particularly based on variable renewable energy sources (RES), in low voltage (LV) distribution networks brings significant challenges to operation. This paper presents a new methodology for mitigating voltage problems in LV networks, in a future scenario with high integration of distributed energy resources (DER), taking advantage of these resources based on a smart grid type architecture. These resources include dispersed energy storage systems, controllable loads of residential clients under demand side management (DSM) actions and microgeneration units. The algorithm developed was tested in a real Portuguese LV network and showed good performance in controlling voltage profiles while being able to integrate all energy from renewable sources and minimizing the energy not supplied.

Abstract
Typed models of connector/component composition specify interfaces describing ports of components and connectors. Typing ensures that these ports are plugged together appropriately, so that data can flow out of each output port and into an input port. These interfaces typically consider the direction of data flow and the type of values flowing. Components, connectors, and systems are often parameterised in such a way that the parameters affect the interfaces. Typing such connector families is challenging. This paper takes a first step towards addressing this problem by presenting a calculus of connector families with integer and boolean parameters. The calculus is based on monoidal categories, with a dependent type system that describes the parameterised interfaces of these connectors. We use families of Reo connectors as running examples, and show how this calculus can be applied to Petri Nets and to BIP systems. The paper focuses on the structure of connectors—well-connectedness—and less on their behaviour, making it easily applicable to a wide range of coordination and component-based models. A type-checking algorithm based on constraints is used to analyse connector families, supported by a proof-of-concept implementation.

Abstract
The number of approaches existing to enable a smooth interaction between Java and Prolog programs testifies the growing interest in solutions that combine the strengths of both languages. Most of these approaches provide limited support to allow programmers to customise how Prolog artefacts should be reified in the Java world, or how to reason about Java objects on the Prolog side. This is an error-prone task since often a considerable amount of mappings must be developed and organised. Furthermore, appropriate mappings may depend on the particular context in which a conversion is accomplished. Although some libraries alleviate this problem by providing higher-level abstractions to deal with the complexity of custom conversions between artefacts of the two languages, such libraries are difficult to implement and evolve, because of a lack of appropriate underlying building blocks for encapsulating, categorising and applying Java-Prolog conversion routines. We therefore introduce a new library, JPC, serving as a development tool for both programmers willing to categorise context-dependent conversion constructs in their Java-Prolog systems, and for architects implementing frameworks providing higher-level abstractions for better interoperability between these two languages.

Abstract
Globalization and the rapid market changes increased the perception in the Portuguese footwear industry that success in the value chain is closely tied to information sharing, the creation and development of collaborative networks, and the management of the knowledge of the various partners. Business to Business (B2B) and e- Commerce (eC) are a key opportunity, and at the same time, a challenge for contemporary companies. We believe that the insights provided in this paper allow theory and practice to better understand the reasons for the success of the Portuguese footwear industry and of its key cluster of Felgueiras. Based on the research conducted, we argue that there is a lack of B2B-eC initiatives in the footwear industry and the existing ones are still incipient. Furthermore, the existence of only one platform that to some extent addresses B2B-eC, also indicates that there is a need for greater research and development of approaches/technology allowing companies to explore opportunities to collaborate and negotiate among themselves.