Abstract
Air temperature data from many locations worldwide are only available as series of daily minima and maxima temperatures. Historically, several different approaches have been used to estimate the actual daily mean temperature, as only in the last two or three decades automatic thermometers are able to compute its actual value. The most common approach is to estimate it by averaging the daily minima and maxima. When only daily minima and maxima are available, an alternative approach, proposed by Dall'Amico and Hornsteiner in 2006, uses the two daily extremes together with next day minima temperature and a coefficient related to the local daily astronomical sunset time. Additionally, the method uses two optimizable coefficients related to the region's temperature profile. In order to use this approach it is necessary to optimize the region's unknown parameters. For this optimization, it is necessary a dataset containing the maxima, minima, and the actual daily mean temperatures for at least one year. In this research, for the period 2007-2014, we used three datasets of minima, maxima and actual mean temperatures obtained at three automatic meteorological stations located in the Douro Valley to optimize the two unknown parameters in the Dall'Amico and Hornsteiner approach. Moreover, we compared the actual mean daily temperatures available from the three datasets with the correspondent values estimated by using i) the usual approach of averaging the daily maxima and minima temperatures and ii) the Dall'Amico and Hornsteiner approach. Results show that the former approach overestimates, on average, the daily mean temperatures by 0.5 degrees C. The Dall'Amico and Hornsteiner approach showed to be a better approximation of mean temperatures for the three meteorological stations used in this research, being unbiased relative to the actual mean values of daily temperatures. In conclusion, this research confirms that the Dall'Amico and Hornsteiner is a better approach to estimate the mean daily temperatures and provides the optimized parameters for three sites located at each of the three sub-regions of the Douro Valley (Baixo Corgo, Cima Corgo and Douro Superior).

Abstract
Current market demands require several degrees of flexibility, speed, and repetitiveness of manufacture and logistic processes. Considering that a fourth industrial revolution is to be expected in a near future - which is highly based on smart machines, storage systems, and production facilities that cooperate to allow dynamic businesses and engineering processes - robotics presents itself as an increasingly sought-after solution, since it is often associated with such concepts. Hence, it is of no wonder that the worldwide operational stock of industrial robots has been increasing in a steady pace for the past decades and is expected to progress in such a trend. Within the several activities for robots on industrial applications, handling operations are regarded as predominant on the European market. Subsequently, palletizing applications are amongst the handling operations that have played an important role in the end stages of modern supply chains. In this context, this work aims to contextualise and develop an application for palletizing robots. This application, together with an off-line programming software (RobotStudio), allows for automatic programming of a robot's palletizing functions. Developed in the robot's native language (RAPID), the application has a basic user interface written in XML and can provide different pallet patterns. © 2018 IEEE.

Abstract
In this work a fully automatic system to identify the extensor tendon on ultrasound images of the metacarpophalangeal joint is proposed. These images are used to diagnose rheumatic diseases which are one of the main causes of impairment and pain in developed countries. The early diagnosis of these conditions is crucial to a proper treatment and follow-up and so, a system such as the one proposed here, could be useful to automatically extract relevant information from the resulting images. This work is an extension of a previous published work which uses manual annotations of the skin line, metacarpus and phalange to guide the extensor tendon segmentation. By introducing automatic segmentations of all structures, we expect to create a fully automatic system, which is more interesting to the possible end-users. Results show that, despite an expected loss in the performance, it is still possible to correctly identify the extensor tendon with a Confidence of 88% considering a maximum allowed Modified Hausdorff Distance of 0.5mm. © 2018 IEEE.

Abstract
Habitat mapping is an important task to manage ecosystems. This task becomes most challenging when it comes to marine habitats as it is hard to get good images in underwater conditions and to precisely locate them. In this paper we present a novel technique for performing habitat mapping automating all phases, from data collection to classification, lowering costs and increasing efficiency throughout the process. For mapping habitats in a vast coastal region, we use visible light cameras mounted on autonomous underwater vehicles, capable of collecting and geo-locating all acquired data. The optic images are enhanced using Computer Vision techniques, to help specialists identify the habitats they contain (during training phase). In a later stage, we employ convolutional neural networks to automatically identify habitats in all imagery. Habitats are classified according to the European Nature Information System, an European classification standard for habitats.

Abstract
The main objective of this work was to answer the question 'How are videogames implemented in healthcare organizations to be used as therapy instruments?'. This question emerged in the intersection of the recent increasing interest in the use of this type of technologies in therapy, with the importance of the implementation process for organizations to use a technology in its full potential. A multiple case study was performed, using three cases of implementations of Nintendo Wii console as a therapy instrument in rehabilitation clinics. The cases were used to compare the implementation of the same technology in organizations with the same core activity. The implementation processes were characterized and compared in light of the well-established literature about implementations of technologies, which led to a preliminary conceptual generalization of the implementation of videogames in healthcare organizations when they are intended to be used as therapy tools, highlighting the key characteristics of such projects. From this research it was possible to conclude that when adopting a console such as Nintendo Wii with rehabilitation purposes, the adoption decision seems to be predominantly informal; the stage of preparation of the implementation (when therapists conveniently prepare themselves to start using the console in their treatments) is quite important for the implementation process; the implementation of a technology such as Nintendo Wii occurs as a mutual adaptation process although with characteristics of a learning implementation, where adaptations occur mostly in the adopter; and, even though there may not be in place the best conditions to use the technology in its full potential, the efforts to routinize it may help overcoming the resistance to use it that results from those lack of conditions © 2017 IEEE.

Abstract
Unique Objects (UNOs) are relevant for real-world applications such as anti-counterfeiting systems. In this work, cork is demonstrated as a UNO, part of the Physical Unclonability and Disorder (PUD) system. An adequate measurement kit (illumination device) and recognition method are also devised and evaluated. Natural hills and valleys of the cork are enhanced using the illumination device and the overall robustness of the recognition application inherent to UNOs is presented. The lighting device is based on grazing light and the recognition task is based on a local feature detector and descriptor called ORB - Oriented FAST (Features from Accelerated Segment Test) and Rotated BRIEF (Binary Robust Independent Elementary Features). The performance evaluation utilizes a private cork database (1500 photos of 500 cork stoppers) and three public iris databases. In the tests carried out on the illumination device, the results clearly show the success of capturing stable/repeatable features needed for the recognition task in the cork database. This achievement is also reflected in the perfect recognition score achieved in the cork database, in the intra-distance measure mu(intra), which gives the notion of average noise between measures, and in the inter-distance mu(inter) which provides hints about the randomness/uniqueness of a cork. Regarding the recognition application, its effectiveness is further tested using the iris databases. Regardless of the fact that the recognition algorithm was not designed for the iris recognition problem, the results show that the proposed approach is capable of competing with the techniques found in the literature specially designed for iris recognition. Furthermore, the evaluation shows that the three requirements that constitute a UNO (Disorder, Operability, and Unclonability) are fulfilled, thus supporting the main assertion of this work: that cork is a UNO.