769 resultados para Springboard diving, practice, representative learning design, practice task constraints, task decomposition
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Mode of access: Internet.
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This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine's previous operational performance, the DFIG's stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.
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Caffeine is the most consumed psychostimulant, with effects on attention, memory, and arousal. But when this substance is ingested near to bedtime there is a decrease on sleep, interfering on mnemonic processes. So, our ain was to investigate how the caffeine ingested near to sleep onset acts on sleep and memory in marmosets. We used 16 adult marmosets, single housed, in a 12:12h light-dark cycle. For registering locomotor activity were used two kinds of sensors. The gyroscope sensor registers activity each 30 sec and detects motion with good accuracy. Because of this we used this sensor for detecting nocturnal activity. The second sensor was based on infrared and accumulates activity each 5 min and it’s not able to detect nocturnal activity, just diurnal activity. We also used camera for registering Rest phase of one marmoset. For the cognitive task, the animals needed to learn a rewarded context (CR) when compared to a non-rewarded context CNR). This experiment comprises 5 phases: 1) Two days of habituation to apparatus; 2)Training for 8 days; 3) oral administration of caffeine (10 mg/kg) or placebo administration ±1h before sleep onset, for 8 days, with marmosets receiving placebo or caffeine; 4) retraining to apparatus and after that, placebo administration (placebo group-GP), or caffeine administration (with continuous group-GC and acute groupGA); 5) Test, for evaluating learning to CR. The sessions were filmed and each one had 8 min of duration. At 7 am started the habituation, training and test sessions, and at 3:15 pm started retraining. The results for gyroscope sensor showed that there was coincidence of 68,57% with nocturnal register of the cameras. Then, the gyroscope sensors detected nocturnal activity for all experimental groups Moreover, when compared sensor gyroscope with sensor based on infrared, was observed that both sensor presented similarity on patterns of activity curve. When we observed the effects of caffeine on Activity-Rest Cycle in GP, GA and GC, is possible to see that that gyroscope sensors and based on infrared presented only intra group differences. As behavioral results, the marmosets learned to discriminate CR when compared to CNR. Moreover, GP presented deficits on memory recall during the test, and GA increased the memory recall, when both were compared to GP. We concluded that the marmosets were able to learning the cognitive task and that the caffeine ingested near to sleep onset acts modulating memory in these animals. Moreover the gyroscope sensor can be used as alternative tool for investigating nocturnal activity. Then, the utilization of this non-invasive device allows marmosets exhibit their behavior within the laboratory conditions as natural as possible.
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The real-time embedded systems design requires precise control of the passage of time in the computation performed by the modules and communication between them. Generally, these systems consist of several modules, each designed for a specific task and restricted communication with other modules in order to obtain the required timing. This strategy, called federated architecture, is already becoming unviable in front of the current demands of cost, required performance and quality of embedded system. To address this problem, it has been proposed the use of integrated architectures that consist of one or few circuits performing multiple tasks in parallel in a more efficient manner and with reduced costs. However, one has to ensure that the integrated architecture has temporal composability, ie the ability to design each task temporally isolated from the others in order to maintain the individual characteristics of each task. The Precision Timed Machines are an integrated architecture approach that makes use of multithreaded processors to ensure temporal composability. Thus, this work presents the implementation of a Precision Machine Timed named Hivek-RT. This processor which is a VLIW supporting Simultaneous Multithreading is capable of efficiently execute real-time tasks when compared to a traditional processor. In addition to the efficient implementation, the proposed architecture facilitates the implementation real-time tasks from a programming point of view.
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Différents courants théoriques, principalement les courants collaboratifs et égocentriques, ont été élaborés pour expliquer l’adaptation de la production verbale lors d’une interaction avec une autre personne. Toutefois, ces courants s’opposent concernant la considération des besoins réels de l’interlocuteur dans la planification initiale des productions verbales. Ce mémoire comprend deux expérimentations réalisées sous un même devis expérimental. Une tâche a été développée pour départager différents types d’adaptation et sources d’information possibles. Les résultats suggèrent que généralement, les personnes produisent de l’information qu’elles-mêmes connaissent et rajoutent de l’information dans un deuxième temps, lorsque nécessaire. Toutefois, lorsqu’elles rencontrent une personne aux connaissances atypiquement restreintes, elles peuvent prendre en considération le vrai niveau de connaissance et produire les informations les plus utiles. Les résultats suggèrent donc que les personnes sont collaboratives pour produire leurs expressions référentielles et qu’elles s’ajustent au réel niveau de connaissances tôt dans l’interaction, lorsqu’elles peuvent utiliser une heuristique de connaissances prototypiques. Avec un interlocuteur aux connaissances atypiquement restreintes, elles produisent cependant des références ciblées, mais spécifiquement lorsqu’il est rencontré avant un interlocuteur prototypique.
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Linking real-time schedulability directly to the Quality of Control (QoC), the ultimate goal of a control system, a hierarchical feedback QoC management framework with the Fixed Priority (FP) and the Earliest-Deadline-First (EDF) policies as plug-ins is proposed in this paper for real-time control systems with multiple control tasks. It uses a task decomposition model for continuous QoC evaluation even in overload conditions, and then employs heuristic rules to adjust the period of each of the control tasks for QoC improvement. If the total requested workload exceeds the desired value, global adaptation of control periods is triggered for workload maintenance. A sufficient stability condition is derived for a class of control systems with delay and period switching of the heuristic rules. Examples are given to demonstrate the proposed approach.
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This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.
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Exhaust noise in engines has always been a major source of automotive noise. Challenges for muffler design have been constraints on size, back pressure, and, of course, the cost. Designing for sufficient insertion loss at the engine firing frequency and the first few harmonics has been the biggest challenge. Most advances in the design of efficient mufflers have resulted from linear plane wave theory, making use of the transfer matrix method. This review paper deals with evaluating approximate source characteristics required for prediction of the unmuffled intake and exhaust noise, making use of the electroacoustical analogies. In the last few years, significant advances have been made in the analysis of variable area perforated ducts, transverse plane wave analysis of short elliptical as well as circular chambers, double-tuned expansion chambers and concentric tube resonators, catalytic converters, diesel particulate filters, air cleaners, etc. The development of long strand fibrous materials that can be used in hot exhaust systems without binders has led to the use of combination mufflers in exhaust systems. Breakthroughs have been achieved in the prediction and control of breakout noise from the elliptical and circular muffler shell as well as the end plates of typical mufflers. Diesel particulate filters and inlet air cleaners have also been modeled acoustically. Some of these recent advances are the subject of this review paper.
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The inverted pendulum is a popular model for describing bipedal dynamic walking. The operating point of the walker can be specified by the combination of initial mid-stance velocity (v(0)) and step angle (phi(m)) chosen for a given walk. In this paper, using basic mechanics, a framework of physical constraints that limit the choice of operating points is proposed. The constraint lines thus obtained delimit the allowable region of operation of the walker in the v(0)-phi(m) plane. A given average forward velocity v(x,) (avg) can be achieved by several combinations of v(0) and phi(m). Only one of these combinations results in the minimum mechanical power consumption and can be considered the optimum operating point for the given v(x, avg). This paper proposes a method for obtaining this optimal operating point based on tangency of the power and velocity contours. Putting together all such operating points for various v(x, avg,) a family of optimum operating points, called the optimal locus, is obtained. For the energy loss and internal energy models chosen, the optimal locus obtained has a largely constant step angle with increasing speed but tapers off at non-dimensional speeds close to unity.
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The Hamilton Jacobi Bellman (HJB) equation is central to stochastic optimal control (SOC) theory, yielding the optimal solution to general problems specified by known dynamics and a specified cost functional. Given the assumption of quadratic cost on the control input, it is well known that the HJB reduces to a particular partial differential equation (PDE). While powerful, this reduction is not commonly used as the PDE is of second order, is nonlinear, and examples exist where the problem may not have a solution in a classical sense. Furthermore, each state of the system appears as another dimension of the PDE, giving rise to the curse of dimensionality. Since the number of degrees of freedom required to solve the optimal control problem grows exponentially with dimension, the problem becomes intractable for systems with all but modest dimension.
In the last decade researchers have found that under certain, fairly non-restrictive structural assumptions, the HJB may be transformed into a linear PDE, with an interesting analogue in the discretized domain of Markov Decision Processes (MDP). The work presented in this thesis uses the linearity of this particular form of the HJB PDE to push the computational boundaries of stochastic optimal control.
This is done by crafting together previously disjoint lines of research in computation. The first of these is the use of Sum of Squares (SOS) techniques for synthesis of control policies. A candidate polynomial with variable coefficients is proposed as the solution to the stochastic optimal control problem. An SOS relaxation is then taken to the partial differential constraints, leading to a hierarchy of semidefinite relaxations with improving sub-optimality gap. The resulting approximate solutions are shown to be guaranteed over- and under-approximations for the optimal value function. It is shown that these results extend to arbitrary parabolic and elliptic PDEs, yielding a novel method for Uncertainty Quantification (UQ) of systems governed by partial differential constraints. Domain decomposition techniques are also made available, allowing for such problems to be solved via parallelization and low-order polynomials.
The optimization-based SOS technique is then contrasted with the Separated Representation (SR) approach from the applied mathematics community. The technique allows for systems of equations to be solved through a low-rank decomposition that results in algorithms that scale linearly with dimensionality. Its application in stochastic optimal control allows for previously uncomputable problems to be solved quickly, scaling to such complex systems as the Quadcopter and VTOL aircraft. This technique may be combined with the SOS approach, yielding not only a numerical technique, but also an analytical one that allows for entirely new classes of systems to be studied and for stability properties to be guaranteed.
The analysis of the linear HJB is completed by the study of its implications in application. It is shown that the HJB and a popular technique in robotics, the use of navigation functions, sit on opposite ends of a spectrum of optimization problems, upon which tradeoffs may be made in problem complexity. Analytical solutions to the HJB in these settings are available in simplified domains, yielding guidance towards optimality for approximation schemes. Finally, the use of HJB equations in temporal multi-task planning problems is investigated. It is demonstrated that such problems are reducible to a sequence of SOC problems linked via boundary conditions. The linearity of the PDE allows us to pre-compute control policy primitives and then compose them, at essentially zero cost, to satisfy a complex temporal logic specification.
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How to regulate phytoplankton growth in water supply reservoirs has continued to occupy managers and strategists for some fifty years or so, now, and mathematical models have always featured in their design and operational constraints. In recent years, rather more sophisticated simulation models have begun to be available and these, ideally, purport to provide the manager with improved forecasting of plankton blooms, the likely species and the sort of decision support that might permit management choices to be selected with increased confidence. This account describes the adaptation and application of one such model, PROTECH (Phytoplankton RespOnses To Environmental CHange) to the problems of plankton growth in reservoirs. This article supposes no background knowledge of the main algal types; neither does it attempt to catalogue the problems that their abundance may cause in lakes and reservoirs.
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介绍了一个较为通用的基于知识的计算机辅助工艺设计(CAPP)系统结构,包括知识表达和关联函数,知识库管理,任务分解与综合策略,解释机制,与其他系统的接口。
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Livestock are a key asset for the global poor. However, access to relevant information is a critical issue for both livestock development practitioners and the poor themselves. Therefore, the following paper details the creation of an on-line Animal Health Resource Room. The aim was to create an immersive environment, which mimics the benefits of a 3D Virtual Learning Environment without the constraints on download times. Therefore, in the following paper key issues in the dissemination of such a platform such as connectivity and speed are explored within the wider context of the development of the tool itself.
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Conventional dual-rail precharge logic suffers from difficult implementations of dual-rail structure for obtaining strict compensation between the counterpart rails. As a light-weight and high-speed dual-rail style, balanced cell-based dual-rail logic (BCDL) uses synchronised compound gates with global precharge signal to provide high resistance against differential power or electromagnetic analyses. BCDL can be realised from generic field programmable gate array (FPGA) design flows with constraints. However, routings still exist as concerns because of the deficient flexibility on routing control, which unfavourably results in bias between complementary nets in security-sensitive parts. In this article, based on a routing repair technique, novel verifications towards routing effect are presented. An 8 bit simplified advanced encryption processing (AES)-co-processor is executed that is constructed on block random access memory (RAM)-based BCDL in Xilinx Virtex-5 FPGAs. Since imbalanced routing are major defects in BCDL, the authors can rule out other influences and fairly quantify the security variants. A series of asymptotic correlation electromagnetic (EM) analyses are launched towards a group of circuits with consecutive routing schemes to be able to verify routing impact on side channel analyses. After repairing the non-identical routings, Mutual information analyses are executed to further validate the concrete security increase obtained from identical routing pairs in BCDL.
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Presentamos una descomposición genética del concepto de recta tangente vista como una trayectoria hipotética de aprendizaje. Para generar esta descomposición genética se ha realizado un análisis histórico de la génesis del concepto, un análisis de libros de texto de Bachillerato, una síntesis de los resultados de las investigaciones sobre la comprensión de la recta tangente y hemos tenido en cuenta los resultados de un cuestionario respondido por alumnos de Bachillerato. La descomposición genética integra las perspectivas analítica local y geométrica como medio para favorecer la tematización del esquema de recta tangente.