Abstract
Optimization studies often require very large computational resources to execute experiments. Furthermore, most of the time, the experiments are repetitions (same problem instances and same algorithm with the same parameters) that were carried out in past studies. In this work, we propose a framework for the execution of optimization experiments in a distributed environment and for the storage of the results as well as of the experimental conditions. The framework can support not only the organized execution of experiments but it also enables the reuse of the results in future studies.

Abstract
Companies are nowadays placed in very complex and dynamic environments, making their competitiveness mandatory. This competitiveness can also be achieved through the reconfiguration of systems' network. In this paper, high level of self-organization of service-oriented multi-agent systems is explored, aiming to achieve more trustworthy and automatic reconfiguration processes, in dynamic and open environments. The correct self-organization model directly impacts the success of agents' behaviours to actively change or create new appropriate services dynamically. This paper advocates on the influence, in a distributed and cooperative way, of risk management, similarities and incentives to work together in order to speed up the self-organization agent's network. By leveraging the SOA and MAS benefits it is possible to reduce time, effort and money. Based on identified benefits and needs, several research leads for my thesis plan are here proposed towards the realization of self-organization capabilities aiming to accomplish more trustworthy and automatic reconfiguration processes, in volatile and open environments.

Abstract
Redundancy both in space and time has been widely used to detect and in some cases correct errors in High Performance Computing (HPC) systems. With the HPC community seeking exascale class supercomputers by the end of the decade, unrealistic expectations for correct system behavior will result in exorbitant costs in terms of performance lost and energy expended. Resilience strategies will need to find balance between fault coverage and the overheads incurred. In this work, we propose an adaptive approach that factors in application level knowledge together with runtime inference about the fault tolerance state of the system to dynamically enable redundant multithreading (RMT). Our approach is based on simple programming language extensions, tightly integrated with a compiler infrastructure and a runtime framework that enables managing the performance overheads of redundant computation. © 2014 Springer-Verlag Berlin Heidelberg.

Abstract
A critical question in tapping behavior is to understand whether the temporal control is exerted on the duration and trajectory of the downward-upward hand movement or on the pause between hand movements. In the present study, we determined the duration of both the movement execution and pauses of monkeys performing a synchronization-continuation task (SCT), using the speed profile of their tapping behavior. We found a linear increase in the variance of pause-duration as a function of interval, while the variance of the motor implementation was relatively constant across intervals. In fact, 96% of the variability of the duration of a complete tapping cycle (pause + movement) was due to the variability of the pause duration. In addition, we performed a Bayesian model selection to determine the effect of interval duration (450 -1,000 ms), serial-order (1-6 produced intervals), task phase (sensory cued or internally driven), and marker modality (auditory or visual) on the duration of the movement-pause and tapping movement. The results showed that the most important parameter used to successfully perform the SCT was the control of the pause duration. We also found that the kinematics of the tapping movements was concordant with a stereotyped ballistic control of the hand pressing the push-button. The present findings support the idea that monkeys used an explicit timing strategy to perform the SCT, where a dedicated timing mechanism controlled the duration of the pauses of movement, while also triggered the execution of fixed movements across each interval of the rhythmic sequence.

Abstract
The estimation of crop evapotranspiration (ETc) from the reference evapotranspiration (ETo) and a standard crop coefficient (K-c) in olive orchards requires that the latter be adjusted to planting density and height. The use of the dual K-c approach may be the best solution because the basal crop coefficient K-cb represents plant transpiration and the evaporation coefficient reproduces the soil coverage conditions and the frequency of wettings. To support related computations for a super intensive olive orchard, the model SIMDualKc was adopted because it uses the dual K-c approach. Alternatively, to consider the physical characteristics of the vegetation, the satellite-based surface energy balance model METRIC (TM) - Mapping EvapoTranspiration at high Resolution using Internalized Calibration - was used to estimate ETc and to derive crop coefficients. Both approaches were compared in this study. SIMDualKc model was calibrated and validated using sap-flow measurements of the transpiration for 2011 and 2012. In addition, eddy covariance estimation of ETc was also used. In the current study, METRIC (TM), was applied to Landsat images from 2011 to 2012. Adaptations for incomplete cover woody crops were required to parameterize METRIC. It was observed that ETc obtained from both approaches was similar and that crop coefficients derived from both models showed similar patterns throughout the year. Although the two models use distinct approaches, their results are comparable and they are complementary in spatial and temporal scales.

Abstract
This paper investigates numerically the performance of a design for an optical sensor of the refractive index of gases and liquids based on smart or functional metamaterial films (smart optical metamembranes).