6 resultados para embedded, system, entropy, pool, TRNG, random, ADC
em Universidade do Minho
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Dissertação de mestrado integrado em Engenharia Mecânica
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The Embedded Through-Section (ETS) technique is a promising technique for the shear strengthening of existing (RC) elements. According to this technique, holes are drilled through the beam section, and bars of steel or FRP material are introduced into these holes and bonded to the concrete with adhesive materials. An experimental program was carried out with RC T-cross section beams strengthened in shear using the ETS steel bars and ETS CFRP rods. The research is focused on the evaluation of the ETS efficiency on beams with different percentage of existing internal transverse reinforcement (ρsw=0.0%, ρsw=0.1% and ρsw=0.17%). The effectiveness of different ETS strengthening configurations was also investigated. The good bond between the strengthening ETS bars and the surrounding concrete allowed the yield initiation of the ETS steel bars and the attainment of high tensile strains in the ETS CFPR rods, leading to significant increase of shear capacity, whose level was strongly influenced by the inclination of the ETS bars and the percentage of internal transverse reinforcement.
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"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"
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In previous work we have presented a model capable of generating human-like movements for a dual arm-hand robot involved in human-robot cooperative tasks. However, the focus was on the generation of reach-to-grasp and reach-to-regrasp bimanual movements and no synchrony in timing was taken into account. In this paper we extend the previous model in order to accomplish bimanual manipulation tasks by synchronously moving both arms and hands of an anthropomorphic robotic system. Specifically, the new extended model has been designed for two different tasks with different degrees of difficulty. Numerical results were obtained by the implementation of the IPOPT solver embedded in our MATLAB simulator.
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There are two significant reasons for the uncertainties of water demand. On one hand, an evolving technological world is plagued with accelerated change in lifestyles and consumption patterns; and on the other hand, intensifying climate change. Therefore, with an uncertain future, what enables policymakers to define the state of water resources, which are affected by withdrawals and demands? Through a case study based on thirteen years of observation data in the Zayandeh Rud River basin in Isfahan province located in Iran, this paper forecasts a wide range of urban water demand possibilities in order to create a portfolio of plans which could be utilized by different water managers. A comparison and contrast of two existing methods are discussed, demonstrating the Random Walk Methodology, which will be referred to as the â On uncertainty pathâ , because it takes the uncertainties into account and can be recommended to managers. This On Uncertainty Path is composed of both dynamic forecasting method and system simulation. The outcomes show the advantage of such methods particularly for places that climate change will aggravate their water scarcity, such as Iran.
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Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance.