Abstract
The use of keyboard and mouse combinations to navigate 3D environments of virtual worlds requires the coordination of both hands in order for the 2D degrees of motion of the mice to transform into the variety of motions available in a 3D space. Such coordination may pose a challenge to people with motor disabilities. 3D controllers known as "3D mice" are presented by manufacturers as significant interface alternatives. To establish the feasibility of such claims, we have conducted a usability test of two 3D mice marketed by 3Dconnexion, in parallel with a keyboard+mouse test. The 10 participants had motor disabilities due to medullary lesions on vertebrae C5-D11, and performed 13 different tasks in the Second Life virtual world: 5 participants used 3D mice, 5 used keyboard+mouse. We have concluded that 2-3 of the 5 most challenging tasks in the keyboard+mouse combination become less challenging using 3D mice. Participants' feedback was more positive regarding 3D mice, but with significant differences between mice. Contrary to our initial expectations, the least stable mouse, Space Navigator, originated the best feedback. (C) 2012 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of the Scientific Programme Committee of the 4th International Conference on Software Development for Enhancing Accessibility and Fighting Info-exclusion (DSAI 2012)

Abstract
In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals' transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey's biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention.

Abstract
The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i.e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

Abstract
This work focus on a coexistence study between wireless microphone systems and secondary users of the TV White Spaces, using a Monte-Carlo methodology. Exclusion areas around wireless microphone receivers, for co-channel and adjacent channel interference, are computed, considering indoor and outdoor scenarios. Using this methodology, impact and tendencies of several parameters over the probability of interference are analyzed, like spectral channel spacing, separation distance and propagation scenario. As an example, for outdoor scenarios, the spectral spacing between primary system and secondary users, ranging from 0 MHz (co-channel operation) to 16 MHz (2 DVB-T channels) results in a protection distance of 13.9 km and 2.2 km, respectively.

Abstract

Abstract
Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM provides several dynamic strategies for agents' behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Network, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.