Abstract
There are several approaches to create the Humanoid robot gait planning. This problem presents a large number of unknown parameters that should be found to make the humanoid robot to walk. Optimization in simulation models can be used to find the gait based on several criteria such as energy minimization, acceleration, step length among the others. The energy consumption can also be reduced with elastic elements coupled to each joint. The presented paper addresses an optimization method, the Stretched Simulated Annealing, that runs in an accurate and stable simulation model to find the optimal gait combined with elastic elements. Final results demonstrate that optimization is a valid gait planning technique.

Abstract

Abstract
In multi-agent systems, local interactions among system components following relatively simple rules often result in complex overall systemic behavior. Complex behavioral and morphological patterns have been used to generate and organize audiovisual systems with artistic purposes. In this work, we propose to use the Actor model of social interactions to drive a concatenative synthesis engine called earGram in real time. The Actor model was originally developed to explore the emergence of complex visual patterns. In turn, earGram was originally developed to facilitate the creative exploration of concatenative sound synthesis. The integrated audiovisual system allows a human performer to interact with the system dynamics while receiving visual and auditory feedback. The interaction happens indirectly by disturbing the rules governing the social relationships amongst the actors, which results in a wide range of dynamic spatiotemporal patterns. A user-performer thus improvises within the behavioral scope of the system while evaluating the apparent connections between parameter values and actual complexity of the system output.

Abstract
The fast development in the field of Robotics has become more and more notorious throughout the past years. Nowadays technology in general and robotics in particular search for modular and flexible applications in order to answer the demands of a wide range of problems in an efficient manner. However there are several robotic solutions already implemented and some still available to be implemented that do not use modular tools. The Robotic Operative System (ROS) appears to be the unifying tool to connect all software developers allowing any developer in both education and professional areas to be able to develop complex software using small iterations of simple software. Still, despite of the several robotic solutions available, there are several robots that do not use the Robotic Operative System (ROS) and have limitations in terms of autonomously correct errors during their tasks. Moreover when developing new robots and software to the robotic area there is an important aspect to be consider: the selection of the methodology to be used. In this paper, it will be presented a challenge propose to college students using the ROS framework in a common robotic problem, the pick and place operations. The main aim for this challenge is to show how to produce software in a modular and flexible way using ROS can prompt the rapid development in all robotic applications. Moreover the challenge had one particular real end, the European Robotics Challenges (EUROC) - a challenge aiming to develop a robot for shop floor logistics and manipulation. Furthermore this challenge was based in the three tiers paradigm: 1 recognition/sensing tier, 2-effector tier and 3-the control tier and was built using the ROS framework. Another advantage of our proposed pick and place approach is the ability to have a robot safely and efficiently inserted in an unknown environment. This is possible due to the insertion of an adaptive control tier in our methodology. The proposed approach can be valuable in the field of robotics and can be potentially applied in multiple tasks and it has already allowed us to advance to the next stage of EUROC. Based on this information, the challenge propose to the students will primarily reinforce the need for modular and flexible software while showing how the ROS framework can be a simple tool for present and future developments.

Abstract
This paper presents the performance analysis of a new geometry sensing configuration for refractive index, based on surface plasmon resonance (SPR) in photonic crystal fiber (PCF) D-type optical fiber with a thin gold layer, using the finite element method (FEM). The configuration is analyzed in terms of the loss. The results are compared with a conventional SPR D-type and with a PCF D-type optical fiber sensor for refractive index measurement. The simulation results show an improvement of the sensitivity and resolution (3.70x10(3)nm/RIU and 2.72x10(-5)RIU, respectively, when considering an accurately spectral variation detection of 0.1nm).

Abstract
This paper offers a characterization of performance limits for classification and reconstruction of high-dimensional signals from noisy compressive measurements, in the presence of side information. We assume the signal of interest and the side information signal are drawn from a correlated mixture of distributions/components, where each component associated with a specific class label follows a Gaussian mixture model (GMM). We provide sharp sufficient and/or necessary conditions for the phase transition of the misclassification probability and the reconstruction error in the low-noise regime. These conditions, which are reminiscent of the well-known Slepian-Wolf and Wyner-Ziv conditions, are a function of the number of measurements taken from the signal of interest, the number of measurements taken from the side information signal, and the geometry of these signals and their interplay. © 2015 IEEE.