Abstract
All violinists and violists face the difficulties of playing on a nonsymmetrical instrument, which makes it quite easy to create wrong techniques. A scientific methodology was developed, composed of some simple and repeatable note patterns, and this performance was analyzed in 3D by a MoCap system (Qualisys AB, Sweden) that operates at a sampling frequency of 200 Hz, capturing the positioning of retroreflective markers on the joints of the hand, wrist, left forearm, violin and bow. The resulting data were analysed in Visual 3D software (C-Motion, USA) to extract relevant parameters and metrics. Based on this study, supported by technology, and on a soon-to-be divulged anatomical-functional model of the positioning of the left hand, we are able to state that the right technique leads to less tension and injury, to a better and faster evolution, with less effort, thus being more productive.

Abstract
This work investigates outlier detection and modelling in non-Gaussian autoregressive time series models with margins in the class of a convolution closed parametric family. This framework allows for a wide variety of models for count and positive data types. The article investigates additive outliers which do not enter the dynamics of the process but whose presence may adversely influence statistical inference based on the data. The Bayesian approach proposed here allows one to estimate, at each time point, the probability of an outlier occurrence and its corresponding size thus identifying the observations that require further investigation. The methodology is illustrated using simulated and observed data sets.

Abstract
In this paper, we fill a void between information theoretic security and practical coding over the Gaussian wiretap channel using a three-stage encoder/decoder technique. Security is measured using Kullback-Leibler divergence and resolvability techniques along with a limited number of practical assumptions regarding the eavesdropper's decoder. The results specify a general coding recipe for obtaining both secure and reliable communications over the Gaussian wiretap channel, and one specific set of concatenated codes is presented as a test case for the sake of providing simulation-based evaluation of security and reliability over the network. It is shown that there exists a threshold in signal-to-noise ratio (SNR) over a Gaussian channel, such that receivers experiencing SNR below the threshold have no practical hope of receiving information about the message when the three-stage coding technique is applied. Results further indicate that the two innermost encoding stages successfully approximate a binary symmetric channel, allowing the outermost encoding stage (e.g., a wiretap code) to focus solely on secrecy coding over this approximated channel.

Abstract
Optical fiber sensors (OFS) based on long-period fiber gratings (LPFG) or on surface plasmon resonance (SPR) represent attractive solutions for detection systems in remote areas. An interrogation system consisting on wavelength modulation of fiber coupled distributed feedback (DFB) lasers was implemented and tested. The system uses a single photodetector to individually acquire the intensity of each DFB laser modulated by the OFS and the real transmission spectrum is reconstructed through curve fitting. Testing was accomplished by measuring the spectral features of an LPFG when changing the surrounding refractive index and errors lower than 1.8 nm in the 1530 to 1570 nm wavelength region were obtained.

Abstract
The residential sector is one of the sectors with the highest rates of electricity consumption worldwide. For years, many studies have been presented in order to minimize energy consumption at the residential level. The idea of such studies is that the residential customer (RC) is the interested party of their own consumption. Moreover, the algorithms that have been developed to predict and manage the energy consumption, also analyze the behavior of the loads, with the objective of minimizing the energy costs, with good safety, robustness, and comfort levels. In the context of the smart house (SH), one of the objectives of smart grids (SGs) is to enable the RC, with home energy management systems (HEM), to actively participate, allowing for higher reliability at different levels. In this work, a new model that simulates the behavior of an SH, considering heating, ventilation and air conditioning (HVAC) and sanitarian water heater (SWH) devices, is presented. For this purpose, the proposed model considers realistic physical parameters of the SH, together with customer comfort, in order to mitigate the RC disinterest. The proposed model considers the electric vehicle (EV), a battery-based energy storage system (ESS), a micro production unit, and different types of tariffs that the RC might choose, aiming to maximize the benefits, and temporarily shifting the proposed loads.

Abstract
A substantial amount of work is often overlooked due to the exponential rate of growth in global scientific output across all disciplines. Current approaches for addressing this issue are usually limited in scope and often restrict the possibility of obtaining multidisciplinary views in practice. To tackle this problem, researchers can now leverage an ecosystem of citizens, volunteers and crowd workers to perform complex tasks that are either difficult for humans and machines to solve alone. Motivated by the idea that human crowds and computer algorithms have complementary strengths, we present an approach where the machine will learn from crowd behavior in an iterative way. This approach is embodied in the architecture of SciCrowd, a crowd-powered human-machine hybrid system designed to improve the analysis and processing of large amounts of publication records. To validate the proposal's feasibility, a prototype was developed and an initial evaluation was conducted to measure its robustness and reliability. We conclude this paper with a set of implications for design.