Abstract
Automatic and simultaneous electrocardiogram (ECG) and phonocardiogram (PCG) segmentation is a good example of current challenges when designing multi-channel decision support systems for healthcare. In this paper, we implemented and tested a Montazeri coupled hidden Markov model (CHMM), where two HMM's cooperate to recreate the "true" state sequence. To evaluate its performance, we tested different settings (two fully connected and two partially connected channels) on a real dataset annotated by an expert. The fully connected model achieved 71% of positive predictability (P+) on the ECG channel and 67% of P+ on the PCG channel. The partially connected model achieved 90% of P+ on the ECG channel and 80% of P+ in the PCG channel. These results validate the potential of our approach for real world multichannel application systems.

Abstract
Imbalanced domains are an important problem that arises in predictive tasks causing a loss in the performance of the most relevant cases for the user. This problem has been intensively studied for classification problems. Recently it was recognized that imbalanced domains occur in several other contexts and for a diversity of types of tasks. This paper focus on imbalanced regression tasks. Resampling strategies are among the most successful approaches to imbalanced domains. In this work we propose variants of existing resampling strategies that are able to take into account the information regarding the neighborhood of the examples. Instead of performing sampling uniformly, our proposals bias the strategies for reinforcing some regions of the data sets. In an extensive set of experiments we provide evidence of the advantage of introducing a neighborhood bias in the resampling strategies.

Abstract
Long period fiber gratings (LPFGs) were over coated with iron (Fe) and subjected to oxidation in air and in solutions of water containing different sodium chloride (NaCl) concentrations. The formation of iron oxides and hydroxides was monitored in real time by following the features of the gratings attenuation band. Preliminary results show that Fe coated LPFGs can be used as sensors for early warning of corrosion in offshore and in coastal projects where metal structures made of iron alloys are in contact with sea or brackish water.

Abstract
Nowadays, the prevalence of computing systems in our lives is so ubiquitous that it would not be far-fetched to state that we live in a cyber-physical world dominated by computer systems. These systems demand for more and more computational performance to process large amounts of data from multiple data sources, some of them with guaranteed processing response times. In other words, systems are required to deliver their results within pre-defined (and sometimes extremely short) time bounds. Examples can be found for instance in intelligent transportation systems for fuel consumption reduction in cities or railway, or autonomous driving of vehicles. To cope with such performance requirements, chip designers produced chips with dozens or hundreds of cores, interconnected with complex networks on chip. Unfortunately, the parallelization of the computing activities brings many challenges, among which how to provide timing guarantees, as the timing behaviour of the system running within a many-core processor depends on interactions on shared resources that are most of the time not know by the system designer. P-SOCRATES (Parallel Software Framework for Time-Critical Many-core Systems) is an FP7 European project, which developed a novel methodology to facilitate the deployment of standardized parallel architectures for real-time applications. This methodology was implemented (based on existent models and components) to provide an integrated software development kit, the UpScale SDK, to fully exploit the huge performance opportunities brought by the most advanced many-core processors, whilst ensuring a predictable performance and maintaining (or even reducing) development costs of applications. The presentation will provide an overview of the UpScale SDK, its underlying methodology, and the results of its application on relevant industrial use-cases.

Abstract
This paper presents an algorithm developed for the optimization of Low Voltage (LV) grids that takes advantage of Distributed Energy Resources (DER) such as storage devices and flexible loads. The proposed approach is based on a multi-temporal Optimal Power Flow (OPF) algorithm that feeds from forecasting tools for load and renewable generation, which means the optimization model looks at a 24-hours horizon with hourly resolution. Specific constraints to the OPF are added to adequately model storage devices, namely their State-of-Charge (SOC) limits as well as their charging and discharging efficiencies. Moreover, a full three-phase model was built due to the unbalanced nature of LV grids motivated by the presence of single-phase load and generation. The algorithm developed has been extensively tested through simulation using a real LV Portuguese network data to illustrate the performance of the algorithm in different scenarios with good results.

Abstract
This paper investigates the utilization of two different six-leg configurations of single-phase to three-phase converters. One of the topologies is transformerless and the other is transformer based. The studied converters allow feeding the load voltage with sinusoidal voltages with constant amplitude and frequency, and to operate with sinusoidal grid current with high power factor. The system model and pulse-width modulation techniques for one of the topologies are given. Control strategies for both topologies are provided. The studied topologies are compared with the conventional in terms of dc-link specification, voltages harmonic distortions, semiconductor losses, and other characteristics. Simulation and experimental results are provided to illustrate the operation of the systems.