Abstract
The main goals of this conference session was to present an overview of a model for fine-grained parallelism in Ada based on the notion of tasklets. The session presented and discussed a general execution model that would support parallelism constructs being considered for possible inclusion in a future version of the Ada standard. The session also presented and discussed a real-time model that provided consistency with the general model while providing enough flexibility to accommodate a wide range of real-time systems with the intent supporting real-time analysis and maintaining or improving the safety features of the language.

Abstract
A multi-wavelengths analysis for pulse waveform extraction using laser speckle is conducted. The proposed system consists of three coherent light sources (532 nm, 635 nm, 850 nm). A bench-test composed of a moving skin-like phantom (silicone membrane) is used to compare the results obtained from different wavelengths. The system is able to identify a skin-like phantom vibration frequency, within physiological values, with a minimum error of 0.5 mHz for the 635 nm and 850 nm wavelengths and a minimum error of 1.3 mHz for the 532 nm light wavelength using a FFT-based algorithm. The phantom velocity profile is estimated with an error ranging from 27% to 9% using a bidimensional correlation coefficient-based algorithm. An in vivo trial is also conducted, using the 532 nm and 635 nm laser sources. The 850 nm light source has not been able to extract the pulse waveform. The heart rate is identified with a minimum error of 0.48 beats per minute for the 532 nm light source and a minimal error of 1.15 beats per minute for the 635 nm light source. Our work reveals that a laser speckle-based system with a 532 nm wavelength is able to give arterial pulse waveform with better results than those given with a 635 nm laser.

Abstract
Conventional sleep analysis relies primarily on electroencephalogram (EEG) waveform features assessed in concert with eye movements, respiration and muscle tone. We explore a complementary 'complexity domain' approach based on multiscale entropy (MSE) analysis of EEG signals and discuss its relationships to standard sleep analysis and to that based on electrocardiogram (ECG)-derived cardiopulmonary coupling (CPC). We observe a progressive decrease in complexity associated with decreased arousability, as measured by both conventional sleep scoring and CPC analysis. Furthermore, complexity analysis supports the contention that stage 2 non-REM sleep has distinct sub-phases that map to CPC high- and low-frequency coupled dynamics. © 2016 IEEE.

Abstract
When engaged in a repetitive task our performance fluctuates from trial-to trial. In particular, inter-trial reaction time variability has been the subject of considerable research. It has been claimed to be a strong biomarker of attention deficits, increases with frontal dysfunction, and predicts age-related cognitive decline. Thus, rather than being just a consequence of noise in the system, it appears to be under the control of a mechanism that breaks down under certain pathological conditions. Although the underlying mechanism is still an open question, consensual hypotheses are emerging regarding the neural correlates of reaction time inter-trial intra-individual variability. Sensory processing, in particular, has been shown to covary with reaction time, yet the spatio-temporal profile of the moment-to-moment variability in sensory processing is still poorly characterized. The goal of this study was to characterize the intra-individual variability in the time course of single-trial visual evoked potentials and its relationship with inter trial reaction time variability. For this, we chose to take advantage of the high temporal resolution of the electroencephalogram (EEG) acquired while participants were engaged in a 2-choice reaction time task. We studied the link between single trial event-related potentials (ERPs) and reaction time using two different analyses: (1) time point by time point correlation analyses thereby identifying time windows of interest; and (2) correlation analyses between single trial measures of peak latency and amplitude and reaction time. To improve extraction of single trial [RP measures related with activation of the visual cortex, we used an independent component analysis (ICA) procedure. Our FRP analysis revealed a relationship between the N1 visual evoked potential and reaction time. The earliest time point presenting a significant correlation of its respective amplitude with reaction time occurred 175 ms after stimulus onset, just after the onset of the N1 peak. Interestingly, single trial N1 latency correlated significantly with reaction time, while N1 amplitude did not. In conclusion, our findings suggest that inter-trial variability in the timing of extrastriate visual processing contributes to reaction time variability.

Abstract
With this study we aim at assessing if a mini iPad device is a usable option for digital interaction to perform selection, manipulation, and insertion tasks by people with intellectual disabilities. This study builds on previous studies where usability was evaluated for universal tasks using the keyboard and a mouse input device [1]. This allowed us to assess the usability of a small mini iPad and compare it with other two input devices, namely keyboards and the mouse. For usability assessment we registered the following variables: successful conclusion of activities, type of difficulties found, errors and satisfaction indicators. The results showed that this group was much motivated to learn how to handle with the iPad, several asked to repeat the task and no one quit any task requested. Despite the number of errors as registered in their interaction, they always knew how to overcome the error and never showed frustration or demotivation. Furthermore, they had a good performance (relation between variables: time to conclude the task, number of errors and difficulties felt) with the mini iPad device, however when compared with the keyboard and mouse, their performance increased.

Abstract
In the European Union (EU), the greenhouse emissions from the transportation sector increased around 36% since 1990, which degraded the environmental quality. This sector, owing to its oil dependency, is responsible for around a quarter of EU greenhouse emissions, and the road transportation represents about 20% of the total CO[[inf]]2[[/inf]] emissions in EU. Moreover, concerns such as the dependency on oil supply and the foreseen prices increase during this century have motivated a wide range of policy and technological measures for the transportation sector. A large part of these measures were to incentivize the electric vehicle (EV) adoption, which is one element with great potential to decarbonize the transportation sector and decrease its oil dependency. This chapter describes relevant methodologies to actively manage EV charging/discharging (as distributed storage devices) to achieve different goals, such as avoid grid congestion, the EV participation in primary frequency control, and the coordination of EV charging with renewable generation. To contextualize the methodologies described, a brief state of the art in active management functionalities for EV is provided. Some of the results obtained with the described approaches are also presented to demonstrate their overall performance. © 2016 John Wiley & Sons, Ltd. All rights reserved.