Abstract
Monitor, control and process data on top of distributed networks has been a trending topic in the past few years, with ubiquity being adjective to computing and, gradually, the Internet of Things becoming a reality in home and factory automation or Ambient Assisted Living (aal). Still, there is a general lack of knowledge and best practices on how to build systems that integrate devices and services from third-parties which connect dynamically with each other. Recurring problems such as security, clustering, message passing, deployment and other orchestration details also lack a standardized solution. The authors describe a platform that simplifies the bootstrap and maintenance of such complex systems, presenting its application in an aal scenario. Such platform could orchestrate most distributed systems, possibly setting a pattern for distributed ubiquitous computing. © 2013 Springer-Verlag Berlin Heidelberg.

Abstract
In this paper, a new efficient algorithm named combined local search heuristics which comprise two local search heuristics, Variable Neighborhood Descent (VND) and Random Neighbor Selection (RNS), is designed and proposed to solve two-dimensional guillotine bin packing problems. The objective of these problems is to pack smaller pieces of rectangular items into large rectangular bins without overlapping such that the total number of used bins is minimized. A constructive heuristic (CH) is conceived to construct a solution by packing items into bins with the use of a defined item packing sequence. VND and RNS, which consist of three deterministic neighborhood structures and three random neighbor selection operators, respectively, are used for improving a solution given by the CH. Benchmark instances were adopted to verify the effectiveness of the designed algorithm via computational experiments. Computational results show that, in terms of the quality of solutions, the proposed approach is better than other heuristics and metaheuristics. In terms of computational times, the proposed algorithm cannot be compared to other algorithms and the computational experiments cannot offer enough evidence of showing any good running-time behavior of the proposed algorithm because of different models of computers used. However, from a practical point of view, easy implementation and reasonable and affordable computational times confirm the usefulness of the proposed algorithm.

Abstract
In this paper we describe a methodology for heart sound classification and results obtained at PASCAL Classifying Heart Sounds Challenge. The results of competing methodologies are shown. The approach has two steps: segmentation and classification of heart sounds. We also describe the data collection procedure.

Abstract
We present and compare two short-term statistical forecasting models for hourly average electric power production forecasts of photovoltaic (PV) plants: the analytical PV power forecasting model (APVF) and the multiplayer perceptron PV forecasting model (MPVF). Both models use forecasts from numerical weather prediction (NWP) tools at the location of the PV plant as well as the past recorded values of PV hourly electric power production. The APVF model consists of an original modeling for adjusting irradiation data of clear sky by an irradiation attenuation index, combined with a PV power production attenuation index. The MPVF model consists of an artificial neural network based model (selected among a large set of ANN optimized with genetic algorithms, GAs). The two models use forecasts from the same NWP tool as inputs. The APVF and MPVF models have been applied to a real-life case study of a grid-connected PV plant using the same data. Despite the fact that both models are quite different, they achieve very similar results, with forecast horizons covering all the daylight hours of the following day, which give a good perspective of their applicability for PV electric production sale bids to electricity markets.

Abstract
In this paper we present an autonomous ground robot developed for outdoor applications in unstructured scenarios. The robot was developed as a versatile robotics platform for development, test and validation of research in navigation, control, perception and multiple robot coordination on all terrain scenarios. The hybrid systems approach to the control architecture is discussed in the context of multiple robot coordination. The robot modular hardware and software architecture allows for a wide range of mission applications. A precise navigation system based on high accuracy GPS is used for accurate 3D environment mapping tasks. The vision system is also presented along with some example results from stereo target tracking in operational environment.

Abstract
In recent years, there has been increasing interest on using task-level pipelining to accelerate the overall execution of applications mainly consisting of Producer-Consumer tasks. This paper proposes an approach to achieve pipelining execution of Producer-Consumer pairs of tasks in FPGA-based multi-core architectures. Our approach is able to speedup the overall execution of successive, data-dependent tasks, by using multiple cores and specific customization features provided by FPGAs. An important component of our approach is the use of customized inter-stage buffer schemes to communicate data and to synchronize the cores associated to the Producer-Consumer tasks. In order to improve performance, we propose a technique to optimize out-of-order Producer-Consumer pairs where the consumer uses more than once each data element produced, a behavior present in many applications (e.g., in image processing). All the schemes and optimizations proposed in this paper were evaluated with FPGA implementations. The experimental results show the feasibility of the approach in both in-order and out-of-order Producer-Consumer tasks. Furthermore, the results using our approach to task-level pipelining and a multi-core architecture reveal noticeable performance improvements for a number of benchmarks over a single core implementation without using task-level pipelining. Copyright 2013 ACM.