967 resultados para Dynamic environments


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Borderline hypertension (BH) has been associated with an exaggerated blood pressure (BP) response during laboratory stressors. However, the incidence of target organ damage in this condition and its relation to BP hyperreactivity is an unsettled issue. Thus, we assessed the Doppler echocardiographic profile of a group of BH men (N = 36) according to office BP measurements with exaggerated BP in the cycloergometric test. A group of normotensive men (NT, N = 36) with a normal BP response during the cycloergometric test was used as control. To assess vascular function and reactivity, all subjects were submitted to the cold pressor test. Before Doppler echocardiography, the BP profile of all subjects was evaluated by 24-h ambulatory BP monitoring. All subjects from the NT group presented normal monitored levels of BP. In contrast, 19 subjects from the original BH group presented normal monitored BP levels and 17 presented elevated monitored BP levels. In the NT group all Doppler echocardiographic indexes were normal. All subjects from the original BH group presented normal left ventricular mass and geometrical pattern. However, in the subjects with elevated monitored BP levels, fractional shortening was greater, isovolumetric relaxation time longer, and early to late flow velocity ratio was reduced in relation to subjects from the original BH group with normal monitored BP levels (P<0.05). These subjects also presented an exaggerated BP response during the cold pressor test. These results support the notion of an integrated pattern of cardiac and vascular adaptation during the development of hypertension.

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Utilizar robôs autônomos capazes de planejar o seu caminho é um desafio que atrai vários pesquisadores na área de navegação de robôs. Neste contexto, este trabalho tem como objetivo implementar um algoritmo PSO híbrido para o planejamento de caminhos em ambientes estáticos para veículos holonômicos e não holonômicos. O algoritmo proposto possui duas fases: a primeira utiliza o algoritmo A* para encontrar uma trajetória inicial viável que o algoritmo PSO otimiza na segunda fase. Por fim, uma fase de pós planejamento pode ser aplicada no caminho a fim de adaptá-lo às restrições cinemáticas do veículo não holonômico. O modelo Ackerman foi considerado para os experimentos. O ambiente de simulação de robótica CARMEN (Carnegie Mellon Robot Navigation Toolkit) foi utilizado para realização de todos os experimentos computacionais considerando cinco instâncias de mapas geradas artificialmente com obstáculos. O desempenho do algoritmo desenvolvido, A*PSO, foi comparado com os algoritmos A*, PSO convencional e A* Estado Híbrido. A análise dos resultados indicou que o algoritmo A*PSO híbrido desenvolvido superou em qualidade de solução o PSO convencional. Apesar de ter encontrado melhores soluções em 40% das instâncias quando comparado com o A*, o A*PSO apresentou trajetórias com menos pontos de guinada. Investigando os resultados obtidos para o modelo não holonômico, o A*PSO obteve caminhos maiores entretanto mais suaves e seguros.

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O Dynamic Gait Index (DGI) é um teste que avalia o equilíbrio e marcha do corpo humano. OBJETIVOS: Os objetivos deste estudo foram adaptar culturalmente o DGI para o português e avaliar a sua confiabilidade. MATERIAL E MÉTODO: Seguiu-se o método de Guillemin et al. (1993) para a adaptação cultural do instrumento. Trata-se de estudo prospectivo em que 46 pacientes foram avaliados na fase de adaptação cultural e os itens que apresentaram 20% ou mais de incompreensão foram reformulados e reaplicados. A versão final do DGI em português foi aplicada em 35 idosos para examinar a confiabilidade intra e inter-observadores. O coeficiente de Spearman foi utilizado para correlacionar os escores inter e intra-observador e o teste de Wilcoxon para comparar as pontuações. A consistência interna foi analisada pelo coeficiente alfa de Cronbach. RESULTADOS: Houve correlações estatisticamente significantes entre os escores obtidos às avaliações inter e intra-observadores para todos os itens (p<0,001), classificadas como boa a muito forte (com de variação de r=0,655 a r=0,951). O DGI mostrou alta consistência interna entre seus itens nas avaliações inter e intra-observadores (variação de µ ou = 0,820 a a=0,894). CONCLUSÃO: O DGI foi adaptado culturalmente para o português brasileiro, mostrando-se um instrumento confiável.

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According to the opinion of clinicians, emerging medical conditions can be timely detected by observing changes in the activities of daily living and/or in the physiological signals of a person. To accomplish such purpose, it is necessary to properly monitor both the person’s physiological signals as well as the home environment with sensing technology. Wireless sensor networks (WSNs) are a promising technology for this support. After receiving the data from the sensor nodes, a computer processes the data and extracts information to detect any abnormality. The computer runs algorithms that should have been previously developed and tested in real homes or in living-labs. However, these installations (and volunteers) may not be easily available. In order to get around that difficulty, this paper suggests the making of a physical model to emulate basic actions of a user at home, thus giving autonomy to researchers wanting to test the performance of their algorithms. This paper also studies some data communication issues in mobile WSNs namely how the orientation of the sensor nodes in the body affects the received signal strength, as well as retransmission aspects of a TDMA-based MAC protocol in the data recovery process.

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This paper aims to describe the processes of teaching illustration and animation, together, in the context of a masters degree program. In Portugal, until very recently, illustration and animation higher education courses, were very scarce and only provided by a few private universities, which offered separated programs - either illustration or animation. The MA in Illustration and Animation (MIA) based in the Instituto Politécnico do Cávado e Ave in Portugal, dared to join these two creative areas in a common learning model and is already starting it’s third edition with encouraging results and will be supported by the first international conference on illustration and animation (CONFIA). This masters program integrates several approaches and techniques (in illustration and animation) and integrates and encourages creative writing and critique writing. This paper describes the iterative process of construction, and implementation of the program as well as the results obtained on the initial years of existence in terms of pedagogic and learning conclusions. In summary, we aim to compare pedagogic models of animation or illustration teaching in higher education opposed to a more contemporary and multidisciplinary model approach that integrates the two - on an earlier stage - and allows them to be developed separately – on the second part of the program. This is based on the differences and specificities of animation (from classic techniques to 3D) and illustration (drawing the illustration) and the intersection area of these two subjects within the program structure focused on the students learning and competencies acquired to use in professional or authorial projects.

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Carpooling initiated in America in the 1970s due to the oil crisis. However, over the past years, carpooling has increased significantly across the world. Some countries have created a High Occupancy Vehicle (HOV) lane to encourage commuters not to travel alone. In additional, carpool websites has been developed to facilitate the connection between the commuters, making it possible to create a compatible match in a faster and efficient manner. This project focuses on carpooling, especially in an academic environment since younger people are more likely to choose carpool. Initially, an intense research was made to examine carpool studies that occurred all over the world, following with a research of higher education institutes that use carpooling as a transportation mode. Most websites created carpools by targeting people from a specific country. These commuters have different origins and destinations making it more complicated to create compatible matches. The objective of this project is to develop a system helping teachers and students from an academic environment to create carpool matches. This objective makes it easier to create carpools because these students and teachers have the same destination. During the research, it was essential to explore, as many as possible, existing carpool websites that are available across the world. After this analysis, several sketches were made to develop the layout and structure of the web application that’s being implemented throughout the project. Once the layout was established, the development of the web application was initiated. This project had its ups and downs but it accomplished all the necessary requirements. This project can be accessed on the link: http://ipcacarpool.somee.com. Once the website was up and running, a web-based survey was developed to study the reasons that motivate people to consider carpooling as an alternative to driving alone. To develop this survey was used a tool called Survey Planet. This survey contained 408 respondents, which 391 are students and 17 are teachers. This study concludes that a majority of the respondents don’t carpool, however they will consider carpooling if there was a dedicated parking space. A majority of the respondents that carpool initiated less than a year ago, indicating that this mean of transportation is recent.

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In order to sustain their competitive advantage in the current increasingly globalized and turbulent context, more and more firms are competing globally in alliances and networks that oblige them to adopt new managerial paradigms and tools. However, their strategic analyses rarely take into account the strategic implications of these alliances and networks, considering their global relational characteristics, admittedly because of a lack of adequate tools to do so. This paper contributes to research that seeks to fill this gap by proposing the Global Strategic Network Analysis - SNA - framework. Its purpose is to help firms that compete globally in alliances and networks to carry out their strategic assessments and decision-making with a view to ensuring dynamic strategic fit from both a global and relational perspective.

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This paper presents a predictive optimal matrix converter controller for a flywheel energy storage system used as Dynamic Voltage Restorer (DVR). The flywheel energy storage device is based on a steel seamless tube mounted as a vertical axis flywheel to store kinetic energy. The motor/generator is a Permanent Magnet Synchronous Machine driven by the AC-AC Matrix Converter. The matrix control method uses a discrete-time model of the converter system to predict the expected values of the input and output currents for all the 27 possible vectors generated by the matrix converter. An optimal controller minimizes control errors using a weighted cost functional. The flywheel and control process was tested as a DVR to mitigate voltage sags and swells. Simulation results show that the DVR is able to compensate the critical load voltage without delays, voltage undershoots or overshoots, overcoming the input/output coupling of matrix converters.

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A mathematical model for the purpose of analysing the dynamic of the populations of infected hosts anf infected mosquitoes when the populations of mosquitoes are periodic in time is here presented. By the computation of a parameter lambda (the spectral radius of a certain monodromy matrix) one can state that either the infection peters out naturally) (lambda <= 1) or if lambda > 1 the infection becomes endemic. The model generalizes previous models for malaria by considering the case of periodic coefficients; it is also a variation of that for gonorrhea. The main motivation for the consideration of this present model was the recent studies on mosquitoes at an experimental rice irrigation system, in the South-Eastern region of Brazil.

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A biomonitoring study, using transplanted lichens Flavoparmelia caperata, was conducted to assess the indoor air quality in primary schools in urban (Lisbon) and rural (Ponte de Sor) Portuguese sites. The lichens exposure period occurred between April and June 2010 and two types of environments of the primary schools were studied: classrooms and outdoor/courtyard. Afterwards, the lichen samples were processed and analyzed by instrumental neutron activation analysis (INAA) to assess a total of 20 chemical elements. Accumulated elements in the exposed lichens were assessed and enrichment factors (EF) were determined. Indoor and outdoor biomonitoring results were compared to evaluate how biomonitors (as lichens) react at indoor environments and to assess the type of pollutants that are prevalent in those environments.

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Reinforcement Learning is an area of Machine Learning that deals with how an agent should take actions in an environment such as to maximize the notion of accumulated reward. This type of learning is inspired by the way humans learn and has led to the creation of various algorithms for reinforcement learning. These algorithms focus on the way in which an agent’s behaviour can be improved, assuming independence as to their surroundings. The current work studies the application of reinforcement learning methods to solve the inverted pendulum problem. The importance of the variability of the environment (factors that are external to the agent) on the execution of reinforcement learning agents is studied by using a model that seeks to obtain equilibrium (stability) through dynamism – a Cart-Pole system or inverted pendulum. We sought to improve the behaviour of the autonomous agents by changing the information passed to them, while maintaining the agent’s internal parameters constant (learning rate, discount factors, decay rate, etc.), instead of the classical approach of tuning the agent’s internal parameters. The influence of changes on the state set and the action set on an agent’s capability to solve the Cart-pole problem was studied. We have studied typical behaviour of reinforcement learning agents applied to the classic BOXES model and a new form of characterizing the environment was proposed using the notion of convergence towards a reference value. We demonstrate the gain in performance of this new method applied to a Q-Learning agent.

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In recent works large area hydrogenated amorphous silicon p-i-n structures with low conductivity doped layers were proposed as single element image sensors. The working principle of this type of sensor is based on the modulation, by the local illumination conditions, of the photocurrent generated by a light beam scanning the active area of the device. In order to evaluate the sensor capabilities is necessary to perform a response time characterization. This work focuses on the transient response of such sensor and on the influence of the carbon contents of the doped layers. In order to evaluate the response time a set of devices with different percentage of carbon incorporation in the doped layers is analyzed by measuring the scanner-induced photocurrent under different bias conditions.

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Recent literature has proved that many classical pricing models (Black and Scholes, Heston, etc.) and risk measures (V aR, CV aR, etc.) may lead to “pathological meaningless situations”, since traders can build sequences of portfolios whose risk leveltends to −infinity and whose expected return tends to +infinity, i.e., (risk = −infinity, return = +infinity). Such a sequence of strategies may be called “good deal”. This paper focuses on the risk measures V aR and CV aR and analyzes this caveat in a discrete time complete pricing model. Under quite general conditions the explicit expression of a good deal is given, and its sensitivity with respect to some possible measurement errors is provided too. We point out that a critical property is the absence of short sales. In such a case we first construct a “shadow riskless asset” (SRA) without short sales and then the good deal is given by borrowing more and more money so as to invest in the SRA. It is also shown that the SRA is interested by itself, even if there are short selling restrictions.

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Object-oriented programming languages presently are the dominant paradigm of application development (e. g., Java,. NET). Lately, increasingly more Java applications have long (or very long) execution times and manipulate large amounts of data/information, gaining relevance in fields related with e-Science (with Grid and Cloud computing). Significant examples include Chemistry, Computational Biology and Bio-informatics, with many available Java-based APIs (e. g., Neobio). Often, when the execution of such an application is terminated abruptly because of a failure (regardless of the cause being a hardware of software fault, lack of available resources, etc.), all of its work already performed is simply lost, and when the application is later re-initiated, it has to restart all its work from scratch, wasting resources and time, while also being prone to another failure and may delay its completion with no deadline guarantees. Our proposed solution to address these issues is through incorporating mechanisms for checkpointing and migration in a JVM. These make applications more robust and flexible by being able to move to other nodes, without any intervention from the programmer. This article provides a solution to Java applications with long execution times, by extending a JVM (Jikes research virtual machine) with such mechanisms. Copyright (C) 2011 John Wiley & Sons, Ltd.