706 resultados para leaning environments
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The underground scenarios are one of the most challenging environments for accurate and precise 3d mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS measurements acquired outside the tunnel. Results from the localization strategy are presented and analyzed.
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Due to their detrimental effects on human health, scientific interest in ultrafine particles (UFP), has been increasing but available information is far from comprehensive. Children, who represent one of the most susceptible subpopulation, spend the majority of time in schools and homes. Thus, the aim of this study is to (1) assess indoor levels of particle number concentrations (PNC) in ultrafine and fine (20–1000 nm) range at school and home environments and (2) compare indoor respective dose rates for 3- to 5-yr-old children. Indoor particle number concentrations in range of 20–1000 nm were consecutively measured during 56 d at two preschools (S1 and S2) and three homes (H1–H3) situated in Porto, Portugal. At both preschools different indoor microenvironments, such as classrooms and canteens, were evaluated. The results showed that total mean indoor PNC as determined for all indoor microenvironments were significantly higher at S1 than S2. At homes, indoor levels of PNC with means ranging between 1.09 × 104 and 1.24 × 104 particles/cm3 were 10–70% lower than total indoor means of preschools (1.32 × 104 to 1.84 × 104 particles/cm3). Nevertheless, estimated dose rates of particles were 1.3- to 2.1-fold higher at homes than preschools, mainly due to longer period of time spent at home. Daily activity patterns of 3- to 5-yr-old children significantly influenced overall dose rates of particles. Therefore, future studies focusing on health effects of airborne pollutants always need to account for children’s exposures in different microenvironments such as homes, schools, and transportation modes in order to obtain an accurate representation of children overall exposure.
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EMC2 finds solutions for dynamic adaptability in open systems. It provides handling of mixed criticality multicore applications in r eal-time conditions, withscalability and utmost flexibility, full-scale deployment and management of integrated tool chains, through the entire lifecycle.
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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The vision of the Internet of Things (IoT) includes large and dense deployment of interconnected smart sensing and monitoring devices. This vast deployment necessitates collection and processing of large volume of measurement data. However, collecting all the measured data from individual devices on such a scale may be impractical and time consuming. Moreover, processing these measurements requires complex algorithms to extract useful information. Thus, it becomes imperative to devise distributed information processing mechanisms that identify application-specific features in a timely manner and with a low overhead. In this article, we present a feature extraction mechanism for dense networks that takes advantage of dominance-based medium access control (MAC) protocols to (i) efficiently obtain global extrema of the sensed quantities, (ii) extract local extrema, and (iii) detect the boundaries of events, by using simple transforms that nodes employ on their local data. We extend our results for a large dense network with multiple broadcast domains (MBD). We discuss and compare two approaches for addressing the challenges with MBD and we show through extensive evaluations that our proposed distributed MBD approach is fast and efficient at retrieving the most valuable measurements, independent of the number sensor nodes in the network.
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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In this paper we present ezGo, an electric powered wheelchair with a speech based interface and biosignal monitoring instrumentation. The user can use the voice, a natural communication method, for controlling the chair movement and obtain information about his health. Additionally a set of semi-autonomous modes with macro recording enable the execution of navigation tasks with little effort and improved precision. The main purpose of the system is to provide severely disabled persons with an assistive device that can improve their confidence and daily independence. The obtained results on usability tests showed that users consider ezGo a valuable help on their daily tasks and a very desirable addition to standard wheelchairs.
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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We present a qualitative analysis of organizational improvisation and provide a preliminary insight into the following question: how is improvisation present in tightly controlled work environments? We conducted in situ observations of, and interviews with, several emergency medical teams and complemented this information with statistical and media data. Using grounded theory, we developed four propositions that were arranged into a model that allowed the identification of two use levels of established routines: (1) the visible side that accommodates contextual requirements, and (2) the improvisational side that provides a response to activity characteristics. This dual process is related to the existence of pressures that operate at the institutional level with practical needs emerging from the operational domain. In contrast with most of the literature, this study reveals that the presence of a broad procedural organizational memory does not restrict improvisation but enables a bureaucratic system to produce flexible improvised performance.
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Esta investigação tem como tema de estudo os ambientes pessoais de aprendizagem que se podem desenvolver em e-learning. Estes ambientes com características singulares, face ao atual estado de desenvolvimento tecnológico e social, têm sido designados na doutrina científica pela expressão anglo-saxónica Personal Learning Environments, da qual derivam os acrónimos PLE ou PLEs. Este estudo tem, como objetivo, compreender o papel dos PLEs na aprendizagem dos alunos da parte letiva do Mestrado em Gestão de Sistemas de e-Learning, da Faculdade de Ciências Sociais e Humanas da Universidade Nova de Lisboa, nos biénios que decorreram de 2010-2011 a 2012-2013. Estes alunos, ao longo da sua aprendizagem, utilizaram várias ferramentas e/ou serviços associados com as TIC e Web 2.0. Esta utilização permitiu aos alunos criarem um ecossistema de aprendizagem próprio. A metodologia de investigação utilizada teve em consideração sobretudo aspetos qualitativos. A estratégia utilizada para a recolha de informações foi o inquérito por questionário. As informações recolhidas foram sujeitas a tratamento estatístico descritivo, e posterior triangulação dos resultados de algumas das variáveis.Dos resultados obtidos, é possível concluir que os alunos do Mestrado criaram os seus próprios PLEs e que estes facilitaram as suas aprendizagens. Que a sua utilização conferiu vantagens aos alunos. Que os PLEs foram fundamentais para poderem desenvolver atividades colaborativas, e que criaram um ecossistema próprio, uma rede de troca de conhecimentos.
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Nowadays, several sensors and mechanisms are available to estimate a mobile robot trajectory and location with respect to its surroundings. Usually absolute positioning mechanisms are the most accurate, but they also are the most expensive ones, and require pre installed equipment in the environment. Therefore, a system capable of measuring its motion and location within the environment (relative positioning) has been a research goal since the beginning of autonomous vehicles. With the increasing of the computational performance, computer vision has become faster and, therefore, became possible to incorporate it in a mobile robot. In visual odometry feature based approaches, the model estimation requires absence of feature association outliers for an accurate motion. Outliers rejection is a delicate process considering there is always a trade-off between speed and reliability of the system. This dissertation proposes an indoor 2D position system using Visual Odometry. The mobile robot has a camera pointed to the ceiling, for image analysis. As requirements, the ceiling and the oor (where the robot moves) must be planes. In the literature, RANSAC is a widely used method for outlier rejection. However, it might be slow in critical circumstances. Therefore, it is proposed a new algorithm that accelerates RANSAC, maintaining its reliability. The algorithm, called FMBF, consists on comparing image texture patterns between pictures, preserving the most similar ones. There are several types of comparisons, with different computational cost and reliability. FMBF manages those comparisons in order to optimize the trade-off between speed and reliability.
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Most of today’s systems, especially when related to the Web or to multi-agent systems, are not standalone or independent, but are part of a greater ecosystem, where they need to interact with other entities, react to complex changes in the environment, and act both over its own knowledge base and on the external environment itself. Moreover, these systems are clearly not static, but are constantly evolving due to the execution of self updates or external actions. Whenever actions and updates are possible, the need to ensure properties regarding the outcome of performing such actions emerges. Originally purposed in the context of databases, transactions solve this problem by guaranteeing atomicity, consistency, isolation and durability of a special set of actions. However, current transaction solutions fail to guarantee such properties in dynamic environments, since they cannot combine transaction execution with reactive features, or with the execution of actions over domains that the system does not completely control (thus making rolling back a non-viable proposition). In this thesis, we investigate what and how transaction properties can be ensured over these dynamic environments. To achieve this goal, we provide logic-based solutions, based on Transaction Logic, to precisely model and execute transactions in such environments, and where knowledge bases can be defined by arbitrary logic theories.
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As the complexity of markets and the dynamicity of systems evolve, the need for interoperable systems capable of strengthening enterprise communication effectiveness increases. This is particularly significant when it comes to collaborative enterprise networks, like manufacturing supply chains, where several companies work, communicate, and depend on each other, in order to achieve a specific goal. Once interoperability is achieved, that is once all network parties are able to communicate with and understand each other, organisations are able to exchange information along a stable environment that follows agreed laws. However, as markets adapt to new requirements and demands, an evolutionary behaviour is triggered giving space to interoperability problems, thus disrupting the sustainability of interoperability and raising the need to develop monitoring activities capable of detecting and preventing unexpected behaviour. This work seeks to contribute to the development of monitoring techniques for interoperable SOA-based enterprise networks. It focuses on the automatic detection of harmonisation breaking events during real-time communications, and strives to develop and propose a methodological approach to handle these disruptions with minimal or no human intervention, hence providing existing service-based networks with the ability to detect and promptly react to interoperability issues.