14 resultados para Human Information Processing

em Instituto Politécnico do Porto, Portugal


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7th Mediterranean Conference on Information Systems, MCIS 2012, Guimaraes, Portugal, September 8-10, 2012, Proceedings Series: Lecture Notes in Business Information Processing, Vol. 129

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All over the world Distributed Generation is seen as a valuable help to get cleaner and more efficient electricity. Under this context distributed generators, owned by different decentralized players can provide a significant amount of the electricity generation. To get negotiation power and advantages of scale economy, these players can be aggregated giving place to a new concept: the Virtual Power Producer. Virtual Power Producers are multi-technology and multi-site heterogeneous entities. Virtual Power Producers should adopt organization and management methodologies so that they can make Distributed Generation a really profitable activity, able to participate in the market. In this paper we address the integration of Virtual Power Producers into an electricity market simulator –MASCEM – as a coalition of distributed producers.

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Swarm Intelligence generally refers to a problem-solving ability that emerges from the interaction of simple information-processing units. The concept of Swarm suggests multiplicity, distribution, stochasticity, randomness, and messiness. The concept of Intelligence suggests that problem-solving approach is successful considering learning, creativity, cognition capabilities. This paper introduces some of the theoretical foundations, the biological motivation and fundamental aspects of swarm intelligence based optimization techniques such Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Artificial Bees Colony (ABC) algorithms for scheduling optimization.

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In the last years there has been a considerable increase in the number of people in need of intensive care, especially among the elderly, a phenomenon that is related to population ageing (Brown 2003). However, this is not exclusive of the elderly, as diseases as obesity, diabetes, and blood pressure have been increasing among young adults (Ford and Capewell 2007). As a new fact, it has to be dealt with by the healthcare sector, and particularly by the public one. Thus, the importance of finding new and cost effective ways for healthcare delivery are of particular importance, especially when the patients are not to be detached from their environments (WHO 2004). Following this line of thinking, a VirtualECare Multiagent System is presented in section 2, being our efforts centered on its Group Decision modules (Costa, Neves et al. 2007) (Camarinha-Matos and Afsarmanesh 2001).On the other hand, there has been a growing interest in combining the technological advances in the information society - computing, telecommunications and knowledge – in order to create new methodologies for problem solving, namely those that convey on Group Decision Support Systems (GDSS), based on agent perception. Indeed, the new economy, along with increased competition in today’s complex business environments, takes the companies to seek complementarities, in order to increase competitiveness and reduce risks. Under these scenarios, planning takes a major role in a company life cycle. However, effective planning depends on the generation and analysis of ideas (innovative or not) and, as a result, the idea generation and management processes are crucial. Our objective is to apply the GDSS referred to above to a new area. We believe that the use of GDSS in the healthcare arena will allow professionals to achieve better results in the analysis of one’s Electronically Clinical Profile (ECP). This attainment is vital, regarding the incoming to the market of new drugs and medical practices, which compete in the use of limited resources.

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The paper discusses mental imagery as an important part of information processing performed during interpreting. Mental imagery is examined to see if visual processing used to remember the source text or to facilitate its understanding helps to ‗off-load‘ other cognitive (mainly linguistic) resources in interpreting. The discussion is based on a neurocognitively-oriented depictivist model by Kosslyn (1994). The overview of mental imagery processes and systems is followed by the discussion of imagery used in interpreting. First, imagery development in student interpreters is described on the basis of a note-taking course for would-be consecutive interpreters organized by the author at AMU. The initial part of the course devoted to imagery involves visualizations of geographical, descriptive and narrative texts. The description abounds in authentic examples and presents conclusions for interpreting trainers. Later, imagery as employed by professional interpreters is discussed on the basis of a qualitative survey. General implications of the use of mental imagery for cognitive processing limitations in interpreting are presented in the concluding section.

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In Distributed Computer-Controlled Systems (DCCS), both real-time and reliability requirements are of major concern. Architectures for DCCS must be designed considering the integration of processing nodes and the underlying communication infrastructure. Such integration must be provided by appropriate software support services. In this paper, an architecture for DCCS is presented, its structure is outlined, and the services provided by the support software are presented. These are considered in order to guarantee the real-time and reliability requirements placed by current and future systems.

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Consider the problem of designing an algorithm for acquiring sensor readings. Consider specifically the problem of obtaining an approximate representation of sensor readings where (i) sensor readings originate from different sensor nodes, (ii) the number of sensor nodes is very large, (iii) all sensor nodes are deployed in a small area (dense network) and (iv) all sensor nodes communicate over a communication medium where at most one node can transmit at a time (a single broadcast domain). We present an efficient algorithm for this problem, and our novel algorithm has two desired properties: (i) it obtains an interpolation based on all sensor readings and (ii) it is scalable, that is, its time-complexity is independent of the number of sensor nodes. Achieving these two properties is possible thanks to the close interlinking of the information processing algorithm, the communication system and a model of the physical world.

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Radio interference drastically affects the performance of sensor-net communications, leading to packet loss and reduced energy-efficiency. As an increasing number of wireless devices operates on the same ISM frequencies, there is a strong need for understanding and debugging the performance of existing sensornet protocols under interference. Doing so requires a low-cost flexible testbed infrastructure that allows the repeatable generation of a wide range of interference patterns. Unfortunately, to date, existing sensornet testbeds lack such capabilities, and do not permit to study easily the coexistence problems between devices sharing the same frequencies. This paper addresses the current lack of such an infrastructure by using off-the-shelf sensor motes to record and playback interference patterns as well as to generate customizable and repeat-able interference in real-time. We propose and develop JamLab: a low-cost infrastructure to augment existing sensornet testbeds with accurate interference generation while limiting the overhead to a simple upload of the appropriate software. We explain how we tackle the hardware limitations and get an accurate measurement and regeneration of interference, and we experimentally evaluate the accuracy of JamLab with respect to time, space, and intensity. We further use JamLab to characterize the impact of interference on sensornet MAC protocols.

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In heterogeneous environments, diversity of resources among the devices may affect their ability to perform services with specific QoS constraints, and drive peers to group themselves in a coalition for cooperative service execution. The dynamic selection of peers should be influenced by user’s QoS requirements as well as local computation availability, tailoring provided service to user’s specific needs. However, complex dynamic real-time scenarios may prevent the possibility of computing optimal service configurations before execution. An iterative refinement approach with the ability to trade off deliberation time for the quality of the solution is proposed. We state the importance of quickly finding a good initial solution and propose heuristic evaluation functions that optimise the rate at which the quality of the current solution improves as the algorithms have more time to run.

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Remote experimentation laboratories are systems based on real equipment, allowing students to perform practical work through a computer connected to the internet. In engineering fields lab activities play a fundamental role. Distance learning has not demonstrated good results in engineering fields because traditional lab activities cannot be covered by this paradigm. These activities can be set for one or for a group of students who work from different locations. All these configurations lead to considering a flexible model that covers all possibilities (for an individual or a group). An inter-continental network of remote laboratories supported by both European and Latin American institutions of higher education has been formed. In this network context, a learning collaborative model for students working from different locations has been defined. The first considerations are presented.

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No ambiente empresarial actual, cada vez mais competitivo e exigente, é um factor fundamental para o sucesso das empresas a sua capacidade de atingir e melhorar os níveis de satisfação exigidos pelos clientes. Para identificar as melhorias a implementar, as empresas devem ser capazes de monitorizar e controlar todas as suas actividades e processos. O acompanhamento realizado às actividades delegadas a empresas externas, como por exemplo o transporte de mercadorias, é dificultado quando os prestadores destes serviços não possuem ferramentas de apoio que disponibilizem informação necessária para o efeito. A necessidade de colmatar esta dificuldade na recolha da informação durante a distribuição de uma encomenda na empresa Caetano Parts, uma empresa de revenda de peças de substituição automóvel, levou ao desenvolvimento de uma ferramenta que permite fazer o seguimento de uma encomenda em todas as suas fases, permitindo ao responsável pelas operações acompanhar o estado da encomenda desde o instante em que a encomenda é colocada, passando pelo seu processamento dentro das instalações, até à sua entrega ao cliente. O sistema desenvolvido é composto por dois componentes, o front-end e o back-end. O front-end é composto por uma aplicação web, e por uma aplicação Android para dispositivos móveis. A aplicação web disponibiliza a gestão da base de dados, o acompanhamento do estado da encomenda e a análise das operações. A aplicação Android é disponibilizada às empresas responsáveis pelo transporte das encomendas e possibilita a actualização online da informação acerca do processo de entrega. O back-end é composto pela unidade de armazenamento e processamento da informação e encontra-se alojado num servidor com ligação à internet, disponibilizando uma interface com o serviço móvel do tipo serviço web. A concepção, desenvolvimento e descrição das funcionalidades desta ferramenta são abordadas ao longo do trabalho. Os testes realizados ao longo do desenvolvimento validaram o correcto funcionamento da ferramenta, estando pronta para a realização de um teste piloto.

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Mestrado em engenharia electrotécnica e de computadores - Área de Especialização de Sistemas Autónomos

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International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2015). 7 to 9, Apr, 2015. Singapure, Singapore.

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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.