996 resultados para Public ambient displays
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática
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Dissertação de Mestrado em Engenharia Informática 2º Semestre, 2011/2012
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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With increasing concerns about the impact of global warming on human life, policy makers around the world and researchers have sought for technological solutions that have the potential to attenuate this process. This thesis describes the design and evaluation of an information appliance that aims to increase the use of public transportation. We developed a mobile glanceable display that, being aware of the user’s transportation routines, provides awareness cues about bus arrival time, grounded upon the vision of Ambient Intelligence. We present the design process we followed, from ideation to building a prototype and conducting a field study, and conclude with a set of guidelines for the design of relevant personal information systems. More specifically we seek to test the following hypotheses: 1) That the tangible prototype that provides ambient cues will be used more frequently than a similar purpose mobile app, 2) That the tangible prototype will reduce the waiting time at the bus stop, 3) That the tangible prototype will result to reduced anxiety on passengers, 4) That the tangible prototype will result to an increase in the perceived reliability of the transit service, 5) That the tangible prototype will enhance users’ efficiency in reading the bus schedules and 6) That the tangible prototype will make individuals more likely to use public transit. In a field study, we compare the tangible prototype against the mobile app and a control condition where participants were given no external support in obtaining bus arrival information, other than their existing routines. Using qualitative and quantitative data, we test the aforementioned hypotheses and explore users’ reactions to the prototype we developed.
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With increasing concerns about the impact of global warming on human life, policy makers around the world and researchers have sought for technological solutions that have the potential to attenuate this process. This thesis describes the design and evaluation of an information appliance that aims to increase the use of public transportation. We developed a mobile glanceable display that, being aware of the user’s transportation routines, provides awareness cues about bus arrival time, grounded upon the vision of Ambient Intelligence. We present the design process we followed, from ideation to building a prototype and conducting a field study, and conclude with a set of guidelines for the design of relevant personal information systems. More specifically we seek to test the following hypotheses: 1) That the tangible prototype that provides ambient cues will be used more frequently than a similar purpose mobile app, 2) That the tangible prototype will reduce the waiting time at the bus stop, 3) That the tangible prototype will result to reduced anxiety on passengers, 4) That the tangible prototype will result to an increase in the perceived reliability of the transit service, 5) That the tangible prototype will enhance users’ efficiency in reading the bus schedules and 6) That the tangible prototype will make individuals more likely to use public transit. In a field study, we compare the tangible prototype against the mobile app and a control condition where participants were given no external support in obtaining bus arrival information, other than their existing routines. Using qualitative and quantitative data, we test the aforementioned hypotheses and explore users’ reactions to the prototype we developed.
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The present study aimed to verify the time course of the effects of environmental levels of urban air pollution toxicity on lung arterioles. BALB/c mice (n = 56) were continuously exposed to selective chambers equipped with (filtered, F) or without (non-filtered, NF) filter devices for particles and toxic gases for 24 h/day, over 14, 21, 30 or 45 days. After exposure, we evaluated the lumen-wall relationship (an estimator of arteriolar narrowing), endothelial nitric oxide synthase (eNOS) and endothelin type A receptor (ETAr) expression in the vascular wall and inflammatory influx of the peribronchiolar area. Concentrations of fine particulate matter (PM <= 2.5 mu g/m(3)), nitrogen dioxide (NO(2)), black smoke (BS), humidity and temperature in both the environment and inside the chambers were measured daily. Filters cleared 100% of BS and 97% of PM inside the F chamber. The arteriole wall of the lungs of mice from NF chamber had an increased ETAr expression (p <= 0.042) concomitant to a decrease in the lumen/wall ratio (p = 0.02) on the early days of exposure, compared to controls. They also presented a progressive increment of inflammatory influx in the peribronchiolar area during the study (p = 0.04) and decrement of the eNOS expression on the 45th day of exposure in both vascular layers (p <= 0.03). We found that after 14 days of exposure, the ambient levels of air pollutants in Sao Paulo induced vasoconstriction that was associated with an increase in ETAr expression. These vascular results do not appear to be coupled to the progressive inflammatory influx in lung tissue, suggesting a down-regulation of vasoconstrictive mechanisms through an imbalance in the cytokines network. It is likely that these responses are protective measures that decrease tissue damage brought about by continuous exposure to air pollutants. (C) 2010 Elsevier Inc. All rights reserved.
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Tese apresentada para cumprimento dos requisitos necessários à obtenção do grau de Doutor em Geografia e Planeamento Territorial - Especialidade: Geografia Humana
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Non-typable Haemophilus influenzae (NTHi) is a Gram negative pathogen that causes acute respiratory infections and is associated with the progression of chronic respiratory diseases. Previous studies have established the existence of a remarkable genetic variability among NTHi strains. In this study we show that, in spite of a high level of genetic heterogeneity, NTHi clinical isolates display a prevalent molecular feature, which could confer fitness during infectious processes. A total of 111 non-isogenic NTHi strains from an identical number of patients, isolated in two distinct geographical locations in the same period of time, were used to analyse nine genes encoding bacterial surface molecules, and revealed the existence of one highly prevalent molecular pattern (lgtF+, lic2A+, lic1D+, lic3A+, lic3B+, siaA−, lic2C+, ompP5+, oapA+) displayed by 94.6% of isolates. Such a genetic profile was associated with a higher bacterial resistance to serum mediated killing and enhanced adherence to human respiratory epithelial cells.
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Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.
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Article
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Objectives: We investigated effects of chronic exposure (2 months) to ambient levels of particulate matter (PM) on development of protease-induced emphysema and pulmonary remodeling in mice. Methods: Balb/c mice received nasal drop of either papain or normal saline and were kept in two exposure chambers situated in an area with high traffic density. One of them received ambient air and the other had filters for PM. Results: mean concentration of PM10 was 2.68 +/- 0.38 and 33.86 +/- 2.09 mu g/m(3), respectively, in the filtered and ambient air chambers (p<0.001). After 2 months of exposure, lungs from papain-treated mice kept in the chamber with ambient air presented greater values of mean linear intercept, an increase in density of collagen fibers in alveolar septa and in expression of 8-isoprostane (p = 0.002, p < 0.05 and p = 0.002, respectively, compared to papain-treated mice kept in the chamber with filtered air). We did not observe significant differences between these two groups in density of macrophages and in amount of cells expressing matrix metalloproteinase-12. There were no significant differences in saline-treated mice kept in the two chambers. Conclusions: We conclude that exposure to urban levels of PM worsens protease-induced emphysema and increases pulmonary remodeling. We suggest that an increase in oxidative stress induced by PM exposure influences this response. These pulmonary effects of PM were observed only in mice with emphysema. (C) 2009 Elsevier Inc. All rights reserved.