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.

Abstract
The recent technological advancements and market trends are causing an interesting phenomenon towards the convergence of High-Performance Computing (HPC) and Embedded Computing (EC) domains. Many recent HPC applications require huge amounts of information to be processed within a bounded amount of time while EC systems are increasingly concerned with providing higher performance in real-time. The convergence of these two domains towards systems requiring both high performance and a predictable time-behavior challenges the capabilities of current hardware architectures. Fortunately, the advent of next-generation many-core embedded platforms has the chance of intercepting this converging need for predictability and high-performance, allowing HPC and EC applications to be executed on efficient and powerful heterogeneous architectures integrating general-purpose processors with many-core computing fabrics. However, addressing this mixed set of requirements is not without its own challenges and it is now of paramount importance to develop new techniques to exploit the massively parallel computation capabilities of many-core platforms in a predictable way. © Vincent Nélis, Patrick Meumeu Yomsi, Luís Miguel Pinho, José Carlos Fonseca, Marko Bertogna, Eduardo Quiñones, Roberto Vargas, and Andrea Marongiu.

Abstract
This paper describes the implementation and the technical specifications of a geolocation database assisted by a spectrum-monitoring outdoor network. The geolocation database is populated according to Electronic Communications Committee (ECC) report 186 methodology. The application programming interface (API) between the sensor network and the geolocation database implements an effective and secure connection to successfully gather sensing data and sends it to the geolocation database for post-processing. On the other hand, the testbed allows authorized TV white space devices to gain access to the services of the geolocation database, according to a draft implementation of Internet Engineering Task Force (IETF) Protocol to Access White Space (PAWS) Two experimental methodologies are available with the testbed: one focused on coexistence studies with commercial wireless microphones, when the testbed is used for sensing only, and another for demonstration purposes, when the testbed is also used to emulate wireless microphone signals. Overall, this hybrid approach is a promising solution for the effective use of TV white spaces and for the coexistence with digital TV broadcast signals, or dynamic incumbent systems, such as unregistered wireless microphones.