Abstract
Replanning is often used to optimize results of an activity in an ever changing world. To address the challenge of preparing future engineers for success, a special course was created for all engineering freshmen of the Faculty of Engineering of the University of Porto, in Portugal. Presented as a case study, this special course underwent a careful replanning as a result of several years of experience in teaching practice alongside with a theoretical deepening in pedagogical and technological issues, under the aegis of the action-research methodology. Within the context of the case study course, the mentioned replanning was also based on a theoretical approach that clearly identifies teaching-learning-assessment methodologies that promote regulation from those that foster emancipation, using a specific instrument: a taxonomy of educational processes. The replanning was designed to globally boost results regarding the educational aims of the course such as furthering freshmen's integration into work environment and preparing them for success by fostering transversal skills (needed for study and work). Technology is seen as a mean of education enrichment as well as a productivity tool. The introduced innovations include fun-but-educational activities, several types of assessment over time and specific technological tools which were critical for the educational impact/achievement of this course. Success is demonstrated by encouraging feedback from the stakeholders, high students' classifications and a steady reduction in retention. It is advocated that large portions of the reasoning behind the replanning can be extrapolated to other courses.

Abstract
The presented research explores four years of newcomer engineering students at FEUP, one of the largest faculties of engineering in Portugal. The students are surveyed in a mandatory course common to all engineering programs at the mentioned faculty, totalling an involvement of about four thousand. This research explores the perceptions of 1198 newcomer students regarding learning and satisfaction, workload, integration into academic work environment and institutional support whilst trying to find gender differences regarding the following variables: engineering program, academic year and change of residence. The questionnaire used in the presented research was validated and its internal consistency was excellent. The findings reveal that students' perceptions on learning and satisfaction as well as on institutional support (two out of four factors) are consistently similar between genders throughout the four years of the study. The differences found between male and female students on integration and workload, however consistent, are small if not marginal. The study is significant because it shows the relevance of the optimization efforts for integration (in the academic work environment) introduced in a mandatory course at the start of engineering degrees in order to bridge the gap between male and female students. This research shows that we are walking towards gender equality in engineering, but we feel that there is still some effort to be done, namely through inspiring scholars to analyse and act upon academic contexts and higher education governance without prejudice and with an open mind: a commitment that is as hard as necessary.

Abstract
Localization and Mapping of autonomous robots in an harsh and unstable environment such as a steep slope vineyard is a challenging research topic. Dead Reckoning systems can fail due to the harsh conditions of the terrain, and the Global Position System can be affected by noise or even be unavailable. Agriculture is moving towards precision agriculture, with advanced monitoring systems and wireless sensor networks. These systems and wireless sensors are installed in the crop field and can be considered relevant landmarks for robot localization. In this paper the distance accuracy provided by bluetooth based sensors is deeply studied and characterized. It is considered a multi antenna receiver bluetooth system and obtained the transfer functions (from Received Signal Strength Indication (RSSI) to distance estimation) for each set of antenna and sensors. The performance of this technology is compared against Time-of-flight based technologies (Pozyx). The obtained results show that the agricultural wireless sensors can be used as redundant artificial landmarks for localization purposes. Besides, the RSSI characterization allowed to improve the previous results of our Beacon Mapping Procedure (BMP) required for accurate and reliable localization systems.

Abstract
Interest in autonomous vehicles has steadily increased in recent years. A number of tasks, like lane tracking, semaphore detection and decoding, are key features for a self-driving robot. This paper presents a path detection and tracking algorithm using the Inverse Perspective Mapping and Hough Transform methods compounded with real-time vision techniques and a semaphore recognition system based on color segmentation. An evaluation of the proposed algorithm is performed and a comparison between the results using real-time techniques is also presented. The suggested architecture has been put to test on autonomous driving robot who competed in the Portuguese autonomous vehicle competition called "Festival Nacional de Robotica". The overall process of the lane tracking algorithm, takes about 1.4 ms per image, almost 60 times faster than the first algorithm tested and a good accuracy, showing a translation error below 0.03m and a rotation error below 5 degrees. Regarding the real-time semaphore recognition, it takes about 0.35 ms to detect a semaphore and has achieved a perfect score in the laboratory tests performed.

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.

Abstract
Using 2D images in authentication systems raises the question of spoof attacks: is it possible to deceive an authentication system using fake models possessing identical visual properties of the genuine one? In this work, an anti-spoofing method approach for a wine anti-counterfeiting system is presented. The proposed method relies in two different color spaces: CIE L*u*v* and, to distinguish between a genuine instance and a spoof attack. To evaluate the proposed strategy, two databases were used: a private database, with photos/2D attacks of cork stoppers, created for this work; and the public Replay-Attack database that is used for face spoofing detection methods testing. The results on the private database show that the anti-spoofing approach is able to distinguish with high accuracy a real photo from an attack. Regarding the public database, the results were obtained with existing methods, as the best HTER results using a single frame approach.