Abstract
Renewable technologies are suitable investments to achieve a low carbon electricity production system and to reduce the external energy dependency of Portugal in a long term period. The aim of this work was to develop and evaluate a variety of scenarios to promote these goals until 2030. A long-term electricity expansion planning model is used to design these scenarios and multi-criteria analysis is applied in the evaluation. The results demonstrated that imposing a minimum contribution of renewable energy sources (RES) for the electricity system, can be more costly than imposing CO2 emissions limitations. Taking into account the technical criteria, scenarios with high coal power share are favoured. However, under a pure social approach, the best scenario would be a 100% RES electricity system. When environmental and economic dimensions are more valued, the best options seems to be the ones with higher investments on natural gas and wind power plants.

Abstract
The increased presence of parallel computing platforms brings concerns to the general purpose domain that were previously prevalent only in the specific niche of high-performance computing. As parallel programming technologies become more prevalent in the form of new emerging programming languages and extensions of existing languages, additional safety concerns arise as part of the paradigm shift from sequential to parallel behaviour. In this paper, we propose various syntax extensions to the Ada language, which provide mechanisms whereby the compiler is given the necessary semantic information to enable the implicit and explicit parallelization of code. The model is based on earlier work, which separates parallelism specification from concurrency implementation, but proposes an updated syntax with additional mechanisms to facilitate the development of safer parallel programs. Copyright 2014 ACM.

Abstract
In this work, the authors propose a new configuration for an intensity vibration sensor based on a Raman fiber laser. The linear cavity of the Raman fiber laser relies on the combination of a distributed Rayleigh mirror and fiber Bragg gratings, which are used as the sensing element and intensity filter. The sensor was able to measure vibrations with frequencies of up to 350 Hz with more than 50 dB of signal-to-noise ratio (SNR) and also the amplitude of the vibrations with a sensitivity of up to 0.57 +/- A 0.07 dB/mu I mu for vibrations with a maximum strain variation of up to 35 mu I mu. The main advantages of the proposed configuration are the simple scheme with high SNR for remote sensing and the easy possibility of multiplexing.

Abstract
We present PrologCheck, an automatic tool for property-based testing of programs in the logic programming language Prolog with randomised test data generation. The tool is inspired by the well known QuickCheck, originally designed for the functional programming language Haskell. It includes features that deal with specific characteristics of Prolog such as its relational nature (as opposed to Haskell) and the absence of a strong type discipline. PrologCheck expressiveness stems from describing properties as Prolog goals. It enables the definition of custom test data generators for random testing tailored for the property to be tested. Further, it allows the use of a predicate specification language that supports types, modes and constraints on the number of successful computations. We evaluate our tool on a number of examples and apply it successfully to debug a Prolog library for AVL search trees.

Abstract
Aggregating the Demand Response (DR) is approved as an effective solution to improve the participation of consumers to wholesale electricity markets. DR aggregator can negotiate the amount of collected DR of their customers with transmission system operator, distributors, and retailers in Demand Response eXchange (DRX) market, in addition to participate in the energy market. In this paper, a framework has been proposed to optimize the participation of a DR aggregator in day-ahead energy and intraday DRX markets. In this regard, the DR aggregator optimizes its participation schedule and offering/bidding strategy in the mentioned markets according to behavior of its customers. For this purpose, the customers' participation is modeled using a Supply Function Equilibrium (SFE) model. In addition, due to uncertainties of market prices and the behavior of consumers, an appropriate risk measurement, CVaR, is incorporated to the optimization problem. The numerical results show the effectiveness of the proposed framework.

Abstract
Starting from the main idea of Symbolic Data Analysis to extend Statistics and Data Mining methods from first-order to second-order objects, we focus on network data-as defined in the framework of Social Network Analysis-to define a graph structure and the underlying network in the context of complex data objects. A Network Symbolic description is defined according to the statistical characterization of the network topological properties. We use suitable network measures, which are represented by means of symbolic variables. Their study through multidimensional data analysis, allows for the synthetic representation of a network as a point onto a metric space. The proposed approach is discussed on the basis of a simulation study considering three classical network growth processes.