Abstract
Recent advances in the area of computer vision has led to the development of various assisted diagnostics systems for the detection of melanoma in the patients. Texture and color are considered as two fundamental visual characteristics which are vital for the detection of melanoma. This paper proposes the use of a combination of texture and color features for the classification of dermoscopy images. The texture features consist of a variation of local binary pattern (LBP) in which the strength of the LBPs is used to extract scale adaptive patterns at each pixel, followed by the construction of a histogram. For color feature extraction, we used standard HSV histograms. The extracted features are concatenated to form a feature vector for an image, followed by classification using support vector machines. Experiments show that the proposed feature set exhibits good classification performance comparing favorably to other state-of-the-art alternatives. © 2014 IEEE.

Abstract
The success of the osseointegration concept and the Branemark protocol is highly associated to the accuracy in the production of an implant-supported prosthesis. One of most critical steps for long-term success of these prosthesis is the accuracy obtained during the impression procedure, which is affected by factors such as the impression material, implant position, angulation and depth. This paper investigates the feasibility of 3D electromagnetic motion tracking systems as an acquisition method for modeling full-arch implant-supported prosthesis. To this extent, we propose an implant acquisition method at the patient mouth and a calibration procedure, based on a 3D electromagnetic tracker that obtains combined measurements of implant's position and angulation, eliminating the use of any impression material. Three calibration algorithms (namely linear interpolation, higher-order polynomial and Hardy multiquadric) were tested to compensate for the electromagnetic tracker distortions introduced by the presence of nearby metals. Moreover, implants from different suppliers were also tested to study its impact on tracking accuracy. The calibration methodology and the algorithms employed proved to implement a suitable strategy for the evaluation of novel dental impression techniques. However, in the particular case of the evaluated electromagnetic tracking system, the order of magnitude of the obtained errors invalidates its use for the full-arch modeling of implant-supported prosthesis.

Abstract
The possibilities of combining simulation and optimization are vast and the appropriate design highly depends on the problem characteristics. Therefore, it is very important to have a good overview of the different approaches. The taxonomies and classifications proposed in the literature do not cover the complete range of methods and overlook some important criteria. We provide a taxonomy that aims at giving an overview of the full spectrum of current simulation-optimization approaches. Our study may guide researchers who want to use one of the existing methods, give insights into the cross-fertilization of the ideas applied in those methods and create a standard for a better communication in the scientific community. Future reviews can use the taxonomy here described to classify both general approaches and methods for specific application fields.

Abstract
The development of Critical Embedded Systems (CES) like Unmanned Aerial Vehicles (UAV) is complex because it needs to ensure a high degree of quality, with affordable cost and delivery time. It is also necessary to ensure security since failures in this type of system can lead to catastrophic results. In this sense, a Model-Driven Development (MDD) approach presents itself as a good alternative to the traditional development because coding complexity will be reduced by the use of high level models. In addition, it avoids the introduction of coding errors by human programmers, since the critical code will be built automatically through models transformation. From another perspective, Embedded Systems Development can benefit from Software Engineering techniques like Product Lines to reduce costs and time-to-market. While other works propose the use of Product Line techniques to improve Embedded Software development, we propose a Product Line approach to the whole Critical Embedded System development life cycle, including hardware variability management. Therefore, this paper proposes a Critical Embedded System Product Line Model Based approach, which aims to reduce the above mentioned challenges. The development approach proposes a Domain Engineering and Application Engineering focused on the system, with both software and hardware. To illustrate the proposed approach we include some artifacts from a case study in the UAV domain.

Abstract
The coordinated control of vehicle actuators is gaining more and more importance as new platforms are becoming available, with chassis endowed with many different actuators that may help controlling the vehicle motion. Furthermore, wheel individual motors allow using a single system to apply both positive and negative torques at the wheels, which can be actuated independently one from the other. In electric vehicles (EVs), moreover, such a freedom in the actuation mechanisms opens the way to the combined optimisation of performance and energy consumption issues. In this paper, the problem of minimum-time manoeuvring in EVs is addressed, and the proposed strategy is compared against a benchmark, a-causal optimal solution showing that only a negligible loss of performance is experienced.

Abstract
Life scientists often must count cells in microscopy images, which is a tedious and time-consuming task. Automatic approaches present a solution to this problem. Several procedures have been devised for this task, but the majority suffer from performance degradation in the case of cell overlap. In this article, we propose a method to determine the positions of macrophages and parasites in fluorescence images of Leishmania-infected macrophages. The proposed strategy is primarily based on blob detection, clustering, and separation using concave regions of the cells' contours. In comparison with the approaches of Nogueira (Master's thesis, Department of University of Porto Computer Science, 2011) and Leal et al. (Proceedings of the 9th international conference on Image Analysis and Recognition, Vol. II, ICIAR'12. Berlin, Heidelberg: Springer-Verlag; 2012. pp. 432-439), which also addressed this type of image, we conclude that the proposed methodology achieves better performance in the automatic annotation of Leishmania infections. (c) 2014 International Society for Advancement of Cytometry