35 resultados para creating environments for interaction

em Universidade do Minho


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Novel input modalities such as touch, tangibles or gestures try to exploit human's innate skills rather than imposing new learning processes. However, despite the recent boom of different natural interaction paradigms, it hasn't been systematically evaluated how these interfaces influence a user's performance or whether each interface could be more or less appropriate when it comes to: 1) different age groups; and 2) different basic operations, as data selection, insertion or manipulation. This work presents the first step of an exploratory evaluation about whether or not the users' performance is indeed influenced by the different interfaces. The key point is to understand how different interaction paradigms affect specific target-audiences (children, adults and older adults) when dealing with a selection task. 60 participants took part in this study to assess how different interfaces may influence the interaction of specific groups of users with regard to their age. Four input modalities were used to perform a selection task and the methodology was based on usability testing (speed, accuracy and user preference). The study suggests a statistically significant difference between mean selection times for each group of users, and also raises new issues regarding the “old” mouse input versus the “new” input modalities.

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Tese de Doutoramento em Ciências da Educação - Especialidade de Desenvolvimento Curricular

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Premature degradation of ordinary Portland cement (OPC) concrete infrastructures is a current and serious problem with overwhelming costs amounting to several trillion dollars. The use of concrete surface treatments with waterproofing materials to prevent the access of aggressive substances is an important way of enhancing concrete durability. The most common surface treatments use polymeric resins based on epoxy, silicone (siloxane), acrylics, polyurethanes or polymethacrylate. However, epoxy resins have low resistance to ultraviolet radiation while polyurethanes are sensitive to high alkalinity environments. Geopolymers constitute a group of materials with high resistance to chemical attack that could also be used for coating of concrete infrastructures exposed to harsh chemical environments. This article presents results of an experimental investigation on the resistance to chemical attack (by sulfuric and nitric acid) of several materials: OPC concrete, high performance concrete (HPC), epoxy resin, acrylic painting and a fly ash based geopolymeric mortar. Three types of acids, each with high concentrations of 10%, 20% and 30%, were used to simulate long term degradation by chemical attack. The results show that the epoxy resin had the best resistance to chemical attack, irrespective of the acid type and acid concentration.

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Dissertação de mestrado em Educação Especial (área de especialização em Dificuldades de Aprendizagem Específicas)

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Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1º Ciclo do Ensino Básico

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BACKGROUND: Lean Production Systems (LPS) have become very popular among manufacturing industries, services and large commercial areas. A LPS must develop and consider a set of work features to bring compatibility with workplace ergonomics, namely at a muscular, cognitive and emotional demands level. OBJECTIVE: Identify the most relevant impacts of the adoption of LPS from the ergonomics point of view and summarizes some possible drawbacks for workplace ergonomics due to a flawed application of the LPS. The impacts identified are focused in four dimensions: work pace, intensity and load; worker motivation, satisfaction and stress; autonomy and participation; and health outcome. This paper also discusses the influence that the work organization model has on workplace ergonomics and on the waste elimination previewed by LPS. METHODS: Literature review focused LPS and its impact on occupational ergonomics conditions, as well as on the Health and Safety of workers. The main focus of this research is on LPS implementations in industrial environments and mainly in manufacturing industry workplaces. This is followed by a discussion including the authors’ experience (and previous research). RESULTS: From the reviewed literature it seems that there is no consensus on how Lean principles affect the workplace ergonomics since most authors found positive (advantages) and negative (disadvantages) impacts. CONCLUSIONS: The negative impacts or disadvantages of LPS implementations reviewed may result from the misunderstanding of the Lean principles. Possibly, they also happen due to partial Lean implementations (when only one or two tools were implemented) that may be effective in a specific work context but not suitable to all possible situations as the principles of LPS should not lead, by definition, to any of the reported drawbacks in terms of workplace ergonomics.

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Self-compacting concrete (SCC) demands more studies of durability at higher temperatures when subjected to more aggressive environments in comparison to the conventional vibrated concrete (CC). This work aims at presenting results of durability indicators of SCC and CC, having the same water/binder relations and constituents. The applied methodologies were electrical resistivity, diffusion of chloride ions and accelerated carbonation experiments, among others, such as microstructure study, scanning electron microscope and microtomography experiments. The tests were performed in a research laboratory and at a construction site of the Pernambuco Arena. The obtained results shows that the SCC presents an average electrical resistivity 11.4% higher than CC; the average chloride ions diffusion was 63.3% of the CC; the average accelerated carbonation penetration was 45.8% of the CC; and the average open porosity was 55.6% of the CC. As the results demonstrated, the SCC can be more durable than CC, which contributes to elucidate the aspects related to its durability and consequent prolonged life cycle.

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The aim of this study is evaluating the interaction between several base pen grade asphalt binders (35/50, 50/70, 70/100, 160/220) and two different plastic wastes (EVA and HDPE), for a set of new polymer modified binders produced with different amounts of both plastic wastes. After analysing the results obtained for the several polymer modified binders evaluated in this study, including a commercial modified binder, it can be concluded that the new PMBs produced with the base bitumen 70/100 and 5% of each plastic waste (HDPE or EVA) results in binders with very good performance, similar to that of the commercial modified binder.

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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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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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Human activity is very dynamic and subtle, and most physical environments are also highly dynamic and support a vast range of social practices that do not map directly into any immediate ubiquitous computing functionally. Identifying what is valuable to people is very hard and obviously leads to great uncertainty regarding the type of support needed and the type of resources needed to create such support. We have addressed the issues of system development through the adoption of a Crowdsourced software development model [13]. We have designed and developed Anywhere places, an open and flexible system support infrastructure for Ubiquitous Computing that is based on a balanced combination between global services and applications and situated devices. Evaluation, however, is still an open problem. The characteristics of ubiquitous computing environments make their evaluation very complex: there are no globally accepted metrics and it is very difficult to evaluate large-scale and long-term environments in real contexts. In this paper, we describe a first proposal of an hybrid 3D simulated prototype of Anywhere places that combines simulated and real components to generate a mixed reality which can be used to assess the envisaged ubiquitous computing environments [17].

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Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1º Ciclo do Ensino Básico

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Tese de Doutoramento em Engenharia Industrial e de Sistemas

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Immersive environments (IE) are being increasingly used in order to perform psychophysical experiments. The versatility in terms of stimuli presentation and control and the less time-consuming procedures are their greatest strengths. However, to ensure that IE results can be generalized to real world scenarios we must first provide evidence that performance in IE is quantitatively indistinguishable from performance in real-world. Our goal was to perceptually validate distance perception for CAVE-like IEs. Participants performed a Frontal Matching Distance Task (Durgin & Li, 2011) in three different conditions: real-world scenario (RWS); photorealistic IE (IEPH) and non-photorealistic IE (IENPH). Underestimation of distance was found across all the conditions, with a significant difference between the three conditions (Wilks’ Lambda = .38, F(2,134)= 110.8, p<.01, significant pairwise differences with p<.01). We found a mean error of 2.3 meters for the RWS, 5 meters for the IEPH, and of 6 meters for the IENPH in a pooled data set of 5 participants. Results indicate that while having a photorealistic IE with perspective and stereoscopic depth cues might not be enough to elicit a real-world performance in distance judgment tasks, nevertheless this type of environment minimizes the discrepancy between simulation and real-world when compared with non-photorealistic IEs.