Abstract
Skin cancer represents a serious public health problem because of its increasing incidence and subsequent mortality. Among skin cancers, malignant melanoma is by far the most deadly form. Because the early detection of melanoma significantly increases the survival rate of the patient, several noninvasive imaging techniques, such as dermoscopy, have been developed to aid the screening process [1]. Dermoscopy involves the use of an optical instrument paired with a powerful lighting system, allowing the examination of skin lesions in a higher magnification. Therefore, dermoscopic images provide a more detailed view of the morphological structures and patterns than normally magnified images of the skin lesions [1, 2]. However, the visual interpretation and examination of dermoscopic images can be a time-consuming task and, as shown by Kittler et al. [3], the diagnosis accuracy of dermoscopy significantly depends on the experience of the dermatologists. Several medical diagnosis procedures have been introduced in order to guide dermatologists and other health care professionals, for example, pattern analysis, the ABCD rule, the 7-point checklist, and the Menzies method. A number of dermoscopic criteria (i.e., asymmetry, border, colors, differential structures) have to be assessed in these methods to produce the final clinical diagnosis. However, the diagnosis of skin lesions is still a challenging task, even using these medical procedures, mainly due to the subjectivity of clinical interpretation and lack of reproducibility [1, 2]. © 2016 by Taylor and Francis Group, LLC.

Abstract
Temporal logics targeting real-time systems are traditionally undecidable. Based on a restricted fragment of MTL-integral, we propose a new approach for the runtime verification of hard real-time systems. The novelty of our technique is that it is based on incremental evaluation, allowing us to effectively treat duration properties (which play a crucial role in real-time systems). We describe the two levels of operation of our approach: offline simplification by quantifier removal techniques; and online evaluation of a three-valued interpretation for formulas of our fragment. Our experiments show the applicability of this mechanism as well as the validity of the provided complexity results.

Abstract
In the last few decades, optical trapping has played an unique role concerning contactless trapping and manipulation of biological specimens. More recently, optical fiber tweezers (OFTs) are emerging as a desirable alternative to bulk optical systems. In this paper, an overview of the state of the art of OFTs is presented, focusing on the main fabrication methods, their features and main achievements. In addition, new OFTs fabricated by guided wave photo polymerization are reported. Their theoretical and experimental characterization is given and results demonstrating its application in the manipulation of yeast cells and the organelles of plant cells are presented.

Abstract
Over the past years, inverse perspective mapping has been successfully applied to several problems in the field of Intelligent Transportation Systems. In brief, the method consists of mapping images to a new coordinate system where perspective effects are removed. The removal of perspective associated effects facilitates road and obstacle detection and also assists in free space estimation. There is, however, a significant limitation in the inverse perspective mapping: the presence of obstacles on the road disrupts the effectiveness of the mapping. The current paper proposes a robust solution based on the use of multimodal sensor fusion. Data from a laser range finder is fused with images from the cameras, so that the mapping is not computed in the regions where obstacles are present. As shown in the results, this considerably improves the effectiveness of the algorithm and reduces computation time when compared with the classical inverse perspective mapping. Furthermore, the proposed approach is also able to cope with several cameras with different lenses or image resolutions, as well as dynamic viewpoints.

Abstract
Optimization in current decision support systems has a highly interdisciplinary nature related with the need to integrate different techniques and paradigms for solving real-world complex problems. Computing optimal solutions in many of these problems are unmanageable. Heuristic search methods are known to obtain good results in an acceptable time interval. However, parameters need to be adjusted to allow good results. In this sense, learning strategies can enhance the performance of a system, providing it with the ability to learn, for instance, the most suitable optimization technique for solving a particular class of problems, or the most suitable parameterization of a given algorithm on a given scenario. Hyper-heuristics arise in this context as efficient methodologies for selecting or generating (meta) heuristics to solve NP-hard optimization problems. This paper presents the specification of a hyper-heuristic for selecting techniques inspired in nature, for solving the problem of scheduling in manufacturing systems, based on previous experience. The proposed hyper-heuristic module uses a reinforcement learning algorithm, which enables the system with the ability to autonomously select the meta-heuristic to use in optimization process as well as the respective parameters. A computational study was carried out to evaluate the influence of the hyper-heuristics on the performance of a scheduling system. The obtained results allow to conclude about the effectiveness of the proposed approach.

Abstract
With this study we aim to assess if the touch screen input device can be a more usable option for digital interaction by people with intellectual disabilities, when compared to a traditional mouse input. In previous studies, we observed that many users with intellectual disabilities struggle to interact with digital content when using traditional input devices, such as the keyboard or mouse. This can lead to a decrease in their motivation to access digital content. Therefore, it is important to evaluate other options, such as touch screens, in order to present a more usable option of interaction for this specific group. For that, we present a case study where the participants were invited to perform primitive selection tasks in a colouring activity, using a painting Web application. The results showed that this group presented a better performance and made less errors when interacting with the touch screen, rather than when compared with the traditional mouse input. We also registered an increase regarding their motivation and satisfaction, when using the touch screen as the input device.