Abstract

Abstract
High-maturity software development processes, making intensive use of metrics and quantitative methods, such as the Team Software Process (TSP) and the accompanying Personal Software Process (PSP), can generate a significant amount of data that can be periodically analyzed to identify performance problems, determine their root causes and devise improvement actions. However, there is a lack of tool support for automating the data analysis and the recommendation of improvement actions, and hence diminish the manual effort and expert knowledge required. So, we propose in this paper a comprehensive performance model, addressing time estimation accuracy, quality and productivity, to enable the automated (tool based) analysis of performance data produced in the context of the PSP, namely, identify performance problems and their root causes, and subsequently recommend improvement actions. Performance ranges and dependencies in the model were calibrated and validated, respectively, based on a large PSP data set referring to more than 30,000 finished projects. © 2014 ACM.

Abstract
This review is focused on microstructured optical fiber sensors developed in recent years for liquid RI sensing. The review is divided into three parts: the first section introduces a general view of the most relevant refractometric sensors that have been reported over the last thirty years. Section 2 discusses several microstructured optical fiber designs, namely, suspended-core fiber, photonic crystal fiber, large-core air-clad photonic crystal fiber, and others. This part is also divided into two main groups: the interferometric-based and resonance-based configurations. The sensing methods rely either on full/selective filling of the microstructured fiber air holes with a liquid analyte or by simply immersing the sensing fiber into the liquid analyte. The sensitivities and resolutions are tabled at the end of this section followed by a brief discussion of the obtained results. The last section concludes with some remarks about the microstructured fiber-based configurations developed for RI sensing and their potential for future applications. © 2014 by the authors.

Abstract
This work draws upon the theoretical foundations of Special Education for People with Disability, Environmental Education and the Human Computer Interaction (HCI), from the Activity Theory perspective, to propose the MusicPaint software. Initially, the design considerations of MusicPaint are presented. Then, its pilot use by seven students with disability is described. From the qualitative and quantitative evidence of performance that was gathered, the key findings are presented and discussed. Despite the limited number of participants in the experimental validation scenarios, the findings reveal the potentiality of the MusicPaint to enhance the accessibility of students with disability to Environmental Education opportunities, contributing to the HCI-based enhancement of accessibility in the educational settings. © 2014 Springer International Publishing.

Abstract
In this paper we address the problem of musical genre recognition for a dancing robot with embedded microphones capable of distinguishing the genre of a musical piece while moving in a real-world scenario. For this purpose, we assess and compare two state-of-the-art musical genre recognition systems, based on Support Vector Machines and Markov Models, in the context of different real-world acoustic environments. In addition, we compare different preprocessing robot audition variants (single channel and separated signal from multiple channels) and test different acoustic models, learned a priori, to tackle multiple noise conditions of increasing complexity in the presence of noises of different natures (e.g., robot motion, speech). The results with six different musical genres suggest improved results, in the order of 43.6pp for the most complex conditions, when recurring to Sound Source Separation and acoustic models trained in similar conditions to the testing scenarios. A robot dance demonstration session confirms the applicability of the proposed integration for genre-adaptive dancing robots in real-world noisy environments.

Abstract
Direct methods are becoming the most used technique to solve nonlinear optimal control problems. Regular time meshes having equidistant spacing are most frequently used. However, in some cases, these meshes cannot cope accurately with nonlinear behaviour unless a very large number of mesh nodes is used. One way to improve the solution involves adaptive mesh refinement algorithms which allow a non uniform node collocation. In the method presented in this paper, a time mesh refinement strategy based on the local error is developed. The technique was applied to solve two problems involving nonholonomic vehicles and it led to results with higher accuracy and yet with lower overall computational time when compared to a mesh having equidistant nodes. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).