Abstract
Over the last three decades, several despeckling filters have been developed to reduce the speckle noise inherently present in ultrasound images without losing the diagnostic information. In this paper, a new intensity and feature preservation evaluation metric for full speckle reduction evaluation is proposed based contrast and feature similarities. A comparison of the despeckling methods is done, using quality metrics and visual interpretation of images profiles to evaluate their performance and show the benefits each one can contribute to noise reduction and feature preservation. To test the methods, noise-free images and simulated B-mode ultrasound images are used. This way, the despeckling techniques can be compared using numeric metrics, taking the noise-free image as a reference. In this study, a total of seventeen different speckle reduction algorithms have been documented based on adaptive filtering, diffusion filtering and wavelet filtering, with sixteen qualitative metrics estimation.

Abstract
Rekindles and false alarms are phenomena that have a significant presence in the Portuguese forest fire management system and an important impact on suppression resources in particular and fire management resources in general. In this paper, we propose a discrete-event simulation model of a forest fire suppression system designed to analyze the joint impact of ignitions, rekindles, and false alarms on the performance of the system. The model is applied to a case study of the district of Porto, Portugal, for the critical period of the forest fire season, between July and September 2010. We study the behavior of the system's point of collapse, comparing the real base scenario with a benchmark scenario built with reference values for rekindles and false alarms, and also as a function of the number of fire incidents, considering historical variations. The results of the analysis are useful for operational decision-making and provide relevant information on the trade-off between prevention and suppression efforts.

Abstract

Abstract
This paper applies genetic algorithms to optimize the operation of a transmission network with energy storage capabilities, to optimize its costs, which include both generation and storage costs, for cases when the data inherent to the system is assumed to be perfectly known. The problem is formulated through the DC optimal power flow equations, including losses across the transmission lines, therefore allowing solutions regarding the network generation costs to be obtained, with and without storage. In this way, the financial impact inherent to the usage of energy storage can be derived. Since we are dealing with a large combinatorial problem, the search throughout the solution space was done by means of the Genetic Algorithms. The solutions consist of the storage device's charging or discharging rate at which it must be operating during each sub-interval considered for the simulations. The results delivered by the GA have proven the profitability of including energy storage capabilities in the transmission network of Sao Miguel (Portugal) and the usefulness of such algorithm in a real world application.

Abstract
The acquisition camera for the GRAVITY/VLTI instrument implements four functions: a) field imager: science field imaging, tip-tilt; b) pupil tracker: telescope pupil lateral and longitudinal positions; c) pupil imager: telescope pupil imaging and d) aberration sensor: The VLTI beam higher order aberrations measurement. We present the dedicated algorithms that simulate the GRAVITY acquisition camera detector measurements considering the realistic imaging conditions, complemented by the pipeline used to extract the data. The data reduction procedure was tested with real aberrations at the VLTI lab and reconstructed back accurately. The acquisition camera software undertakes the measurements simultaneously for all four AT/UTs in 1 s. The measured parameters are updated in the instrument online database. The data reduction software uses the ESO Common Library for Image Processing (CLIP), integrated in to the ESO VLT software environment.

Abstract
The graphical quality of modern videogames are the result of a steep evolution of hardware over the last two decades, but the game controls that are part of mainstream gaming did not change much in the same time period. To change this, biofeedback techniques using physiological sensors are being studied as possible replacements for traditional videogame interaction devices. In this paper, we continue on-going research by introducing unimodal and, for the first time, multimodal biofeedback game mechanics aiming at enhanced depth and expanded game design possibilities. We developed a First-Person Shooter to test these concepts against traditional unimodal mechanisms, and conducted an empirical study with 32 players. Both unimodal and multimodal variants provided high levels of fun to players, with subtle differences suggesting that these types are best leveraged depending on the interaction context on which they are applied.