The intersectorial approach in providing guidance and school support. The perspective of counsellors, tutors and principals

The provision of guidance and educational support requires joint work and the collaboration of different professionals and institutions, especially when we face complex problems that require a high level of specialization and the combination of knowledge from different areas. The research has aimed to examine the proximity of the institutional system of guidance and support to school in nine Autonomous Communities, to the intersectorial approach of counselling. We present the results of a descriptive study using the survey method, which allows knowing the opinions of counsellors, tutors and principals of Primary and Secondary Compulsory Education about the collaboration with the local public services (social, health, education, and employment) in the specialized support to students and schools. The final sample consisted of 9732 subjects who were selected from a random sampling proportional to the size of the subpopulations of each Autonomous Community. Results indicate how, in general terms, there is collaboration among the school and the local public services, although not as frequently as it would be desirable. In the same way, the professionals that were interviewed believe that the collaboration with social and educational services is quite adequate, but the assessment is not as positive when health and employment services are analysed. Finally, taking into account the different professionals considered, tutors from both educational stages are the ones that show a higher degree of satisfaction with the collaboration between the school and the local public services, except in the case of social services.

Intralogistik als Anwendungsgebiet der Antwortmengenprogrammierung – Potenzialanalyse

Der Stellenwert der Intralogistik ist in den vergangenen Jahren aufgrund eines zunehmend beschleunigten und globalen Marktes deutlich gestiegen. Die Intralogistik bietet Problemstellungen, deren Lösung respektive Lösungsunterstützung weiterer Forschung bedarf. Antwortmengenprogrammierung auf der anderen Seite bietet hervorragende Eigenschaften zur Lösung komplexer Probleme, deren Lösung eine enge Verknüpfung mit vorhandenem Wissen erfordert. In diesem Artikel wird das Paradigma der Antwortmengenprogrammierung mit den Problemstellungen der Intralogistik in einer Potenzialanalyse abgeglichen.

Digital Humanities Research Through Design

Humanities Computing gave rise to the Digital Humanities, which brought considerations of a wider scope of the digital turn to humanities research. Increasingly, the area is understood to include the field of design, exemplified by definitions that describe the Digital Humanities as a “generative enterprise”. We suggest that design contributes not only to the making of digital artefacts. Design practiced with the aim to generate new knowledge constitues a research method. Design research contributes to the Digital Humanities expertise in addressing complex problems and methods for making the knowledge that is generated during a design process explicit.

Climbing Up the Leaderboard: An Empirical Study of Applying Gamification Techniques to a Computer Programming Class

Conventional taught learning practices often experience difficulties in keeping students motivated and engaged. Video games, however, are very successful at sustaining high levels of motivation and engagement through a set of tasks for hours without apparent loss of focus. In addition, gamers solve complex problems within a gaming environment without feeling fatigue or frustration, as they would typically do with a comparable learning task. Based on this notion, the academic community is keen on exploring methods that can deliver deep learner engagement and has shown increased interest in adopting gamification – the integration of gaming elements, mechanics, and frameworks into non-game situations and scenarios – as a means to increase student engagement and improve information retention. Its effectiveness when applied to education has been debatable though, as attempts have generally been restricted to one-dimensional approaches such as transposing a trivial reward system onto existing teaching materials and/or assessments. Nevertheless, a gamified, multi-dimensional, problem-based learning approach can yield improved results even when applied to a very complex and traditionally dry task like the teaching of computer programming, as shown in this paper. The presented quasi-experimental study used a combination of instructor feedback, real time sequence of scored quizzes, and live coding to deliver a fully interactive learning experience. More specifically, the “Kahoot!” Classroom Response System (CRS), the classroom version of the TV game show “Who Wants To Be A Millionaire?”, and Codecademy’s interactive platform formed the basis for a learning model which was applied to an entry-level Python programming course. Students were thus allowed to experience multiple interlocking methods similar to those commonly found in a top quality game experience. To assess gamification’s impact on learning, empirical data from the gamified group were compared to those from a control group who was taught through a traditional learning approach, similar to the one which had been used during previous cohorts. Despite this being a relatively small-scale study, the results and findings for a number of key metrics, including attendance, downloading of course material, and final grades, were encouraging and proved that the gamified approach was motivating and enriching for both students and instructors.

Mikroyrityksen ja tilitoimiston välisten prosessien kehittäminen sähköistämisen avulla

Tämä tutkielma käsittelee mikroyrityksen ja tilitoimiston välistä yhteistyötä sekä sen edistämistä sähköistämisen keinoin. Aihetta käsitellään ulkoistamisen näkökulmasta, jolloin taloushallinnon prosessit käsittävät tilitoimiston ja yrityksen välisen tiedonvaihdon ja yhteistyön. Tutkielmassa käsitellään taloushallinnon roolia ja prosesseja sekä taloushallinnon ulkoistamisen teoreettisia lähtökohtia. Tämän jälkeen syvennytään taloushallinnon sähköistämiseen sekä sen etuihin ja haittoihin. Aiheita pyritään käsittelemään sekä yleisellä tasolla että mikroyritysten näkökulmasta. Tutkielman tavoitteena on teorian ja empiirisen tutkimuksen avulla selvittää, millaisia sähköisiä keinoja valitun kohdeyrityksen ja tilitoimiston yhteistyön kehittämiseen on tarjolla ja kuinka nämä keinot edistäisivät osapuolten välistä yhteistyötä. Työssä käytetty tutkimusmenetelmä on kvalitatiivinen ja tutkittavaa ilmiötä on tarkasteltu tapaustutkimuksen keinoin. Tutkimusaineisto kerättiin kohdeyrityksen omistajayrittäjältä keskusteluin sekä kohdeyrityksen käyttämälle tilitoimistolle sähköpostitse lähetetyllä kyselyllä. Tutkielmassa päädyttiin siihen, että sähköisistä menetelmistä on saatu apua esimerkiksi kuittikirjanpidossa. Käytössä olevien sähköisten palveluiden määrää sen sijaan voitaisiin vähentää ainakin poistamalla yksi laskujenhallintaohjelma käytöstä. Tämä edistäisi tositteiden kulkua yritykseltä kirjanpitäjälle ja samalla päästäisiin eroon myös yhdestä käyttöominaisuuksiltaan kehnosta laskujenhallintajärjestelmästä. Toisaalta todettiin, että ydinongelmat eivät loppujen lopuksi liity heikkoon teknologiaan vaan ihmisten välisiin suhteisiin eivätkä nämä ongelmat ole ratkaistavissa teknologian keinoin.

Contributions to 3D Data Registration and Representation

Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.

Impacto da prevenção quaternária no envelhecimento bem sucedido

"Quaternary prevention is more than a Philosophy , it is a concrete answer and a solution to many complex problems that affect Medicine. In 1981, Illich recognized iatrogenic complications, as clinical, social and cultural. The first, gained such a dimension that has become the third leading cause of death in the U.S. , in 2000 as referred by Starfield. When you live more, much more, you want quality of life and not just life subject of increasing comorbidities, with all the parade of treatments, medications that we already know are not without riscs, far from it, we know that over five drugs per day represent the 50% probability of drug-drug interactions and seven drugs 100 %. In elderly attending the reduction of functional reserve, there is a greater risk of iatrogenic problems, adverse reactions and drug interactions, truly unpredictable , these highly medicalized societies in which are accounted diagnoses instead of investigating patterns of disease. So quaternary prevention reminds us that both preventive and curative care in excess behave as risk factors for health , reaching in the case of using preventive medications, millions of individuals who are confident in Medicine. The idea of extending the use of drugs to healthy populations, as preventive actions, expands the pharmaceutical market, which accounts simultaneously increasing profits and losses in economies around the world. Quaternary prevention itineraries in health and disease, may contribute to successful aging about witch many important authors have spoken on."

UT Austin | Portugal Workshop on Nonlinear Mechanics and Applications in Life Sciences

This is a CoLab Workshop organized as an initiative of the UT Austin | Portugal Program to reinforce the Portuguese competences in Nonlinear Mechanics and in complex problems arising from applications to the mathematical modeling and simulations in the Life Sciences. The Workshop provides a place to exchange recent developments, discoveries and progresses in this challenging research field. The main goal is to bring together doctoral candidates, postdoctoral scientists and graduates interested in the field, giving them the opportunity to make scientific interactions and new connections with established experts in the interdisciplinary topics covered by the event. Another important goal of the Workshop is to promote collaboration between members of the different areas of the UT Austin | Portugal community.

Lusitanian Amphorae in Carthago Nova (Cartagena, Spain): Distribution and Research Questions

The presence of Lusitanian amphorae in the region of Carthago Nova (Cartagena, Spain) has been known for a few years, and yet it has never been the subject of a monographic study. Integrated in the commercial networks of the western Mediterranean, these products circulated within the harbour system of this city between the 1st and the 5th century AD. This paper aims to present a synthesised review of the main Lusitanian imports that were detected: Dressel 14 and Almagro 50, Almagro 51a-b and Almagro 51c. The difficulty in identifying the ceramic fabrics and the scarce documentation regarding some finds pose complex problems. This study extends to the hinterland of the colony and to other nearby settlements, such as Portmán and Puerto de Mazarrón.

Framework for anomaly detection on photovoltaic plants

Technological advancement has undergone exponential growth in recent years, and this has brought significant improvements in the computational capabilities of computers, which can now perform an enormous amount of calculations per second. Taking advantage of these improvements has made it possible to devise algorithms that are very demanding in terms of the computational resources needed to develop architectures capable of solving the most complex problems: currently the most powerful of these are neural networks and in this thesis I will combine these tecniques with classical computer vision algorithms to improve the speed and accuracy of maintenance in photovoltaic facilities.

Solving complex optimal control problems at no cost with PSOPT

This paper introduces PSOPT, an open source optimal control solver written in C++. PSOPT uses pseudospectral and local discretizations, sparse nonlinear programming, automatic differentiation, and it incorporates automatic scaling and mesh refinement facilities. The software is able to solve complex optimal control problems including multiple phases, delayed differential equations, nonlinear path constraints, interior point constraints, integral constraints, and free initial and/or final times. The software does not require any non-free platform to run, not even the operating system, as it is able to run under Linux. Additionally, the software generates plots as well as LATEX code so that its results can easily be included in publications. An illustrative example is provided.

Application of complex extreme learning machine to multiclass classification problems with high dimensionality: a THz spectra classification problem

We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.