35 resultados para Computer technology

em Universidade do Minho


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This book was produced in the scope of a research project entitled “Navigating with ‘Magalhães’: Study on the Impact of Digital Media in Schoolchildren”. This study was conducted between May 2010 and May 2013 at the Communication and Society Research Centre, University of Minho, Portugal and it was funded by the Portuguese Foundation for Science and Technology (PTDC/CCI-COM/101381/2008).

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(Excerto) In times past, learning to read, write and do arithmetic was to get on course to earn the “writ of emancipation” in society. These skills are still essential today, but are not enough to live in society. Reading and critically understanding the world we live in, with all its complexity, difficulties and challenges, require not only other skills (learning to search for and validate information, reading with new codes and grammar, etc) but, to a certain extent, also metaskills, matrixes and mechanisms that are transversal to the different and new literacies, are necessary. They are needed not just to interpret but equally to communicate and participate in the little worlds that make up our everyday activities as well as, in a broader sense, in the world of the polis, which today is a global world.

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This book was produced in the scope of a research project entitled “Navigating with ‘Magalhães’: Study on the Impact of Digital Media in Schoolchildren”. This study was conducted between May 2010 and May 2013 at the Communication and Society Research Centre, University of Minho, Portugal and it was funded by the Portuguese Foundation for Science and Technology (PTDC/CCI-COM/101381/2008). As we shall explain in more detail later in this book, the main objective of that research project was to analyse the impact of the Portuguese government programme named ´e-escolinha´ launched in 2008 within the Technological Plan for Education. This Plan responds to the principles of the Lisbon Strategy signed in 2000 and rereleased in the Spring European Council of 2005.

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Doctoral Program in Computer Science

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Marine ecosystem can be considered a rather exploited source of natural substances with enormous bioactive potential. In Mexico macro-algae study remain forgotten for research and economic purposes besides the high amount of this resource along the west and east coast. For that reason the Bioferinery Group of the Autonomous University of Coahuila, have been studying the biorefinery concept in order to recover high value byproducts of Mexican brown macro-algae including polysaccharides and enzymes to be applied in food, pharmaceutical and energy industry. Brown macroalgae are an important source of fucoidan, alginate and laminarin which comprise a complex group of macromolecules with a wide range of important biological properties such as anticoagulant, antioxidant, antitumoral and antiviral and also as rich source of fermentable sugars for enzymes production. Additionally, specific enzymes able to degrade algae matrix (fucosidases, sulfatases, aliginases, etc) are important tools to establish structural characteristics and biological functions of these polysaccharides. The aims of the present work were the integral study of bioprocess for macroalgae biomass exploitation by the use of green technologies as hydrothermal extraction and solid state fermentation in order to produce polysaccharides and enzymes (fucoidan and fucoidan hydrolytic enzymes). This work comprises the use of the different bioprocess phases in order to produce high value products with lower time and wastes.

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Relatório de projeto de mestrado em Ensino de Informática

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This work proposes a constitutive model to simulate nonlinear behaviour of cement based materials subjected to different loading paths. The model incorporates a multidirectional fixed smeared crack approach to simulate crack initiation and propagation, whereas the inelastic behaviour of material between cracks is treated by a numerical strategy that combines plasticity and damage theories. For capturing more realistically the shear stress transfer between the crack surfaces, a softening diagram is assumed for modelling the crack shear stress versus crack shear strain. The plastic damage model is based on the yield function, flow rule and evolution law for hardening variable, and includes an explicit isotropic damage law to simulate the stiffness degradation and the softening behaviour of cement based materials in compression. This model was implemented into the FEMIX computer program, and experimental tests at material scale were simulated to appraise the predictive performance of this constitutive model. The applicability of the model for simulating the behaviour of reinforced concrete shear wall panels submitted to biaxial loading conditions, and RC beams failing in shear is investigated.

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Eye tracking as an interface to operate a computer is under research for a while and new systems are still being developed nowadays that provide some encouragement to those bound to illnesses that incapacitates them to use any other form of interaction with a computer. Although using computer vision processing and a camera, these systems are usually based on head mount technology being considered a contact type system. This paper describes the implementation of a human-computer interface based on a fully non-contact eye tracking vision system in order to allow people with tetraplegia to interface with a computer. As an assistive technology, a graphical user interface with special features was developed including a virtual keyboard to allow user communication, fast access to pre-stored phrases and multimedia and even internet browsing. This system was developed with the focus on low cost, user friendly functionality and user independency and autonomy.

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Several studies have shown that people with disabilities benefit substantially from access to a means of independent mobility and assistive technology. Researchers are using technology originally developed for mobile robots to create easier to use wheelchairs. With this kind of technology people with disabilities can gain a degree of independence in performing daily life activities. In this work a computer vision system is presented, able to drive a wheelchair with a minimum number of finger commands. The user hand is detected and segmented with the use of a kinect camera, and fingertips are extracted from depth information, and used as wheelchair commands.

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Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

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"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

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Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

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Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

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Tese de Doutoramento em Ciências da Educação (área de especialização em Tecnologia Educativa)