736 resultados para adaptive walking
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Recent studies have shown that adaptive X control charts are quicker than traditional X charts in detecting small to moderate shifts in a process. In this article, we propose a joint statistical design of adaptive X and R charts having all design parameters varying adaptively. The process is subjected to two independent assignable causes. One cause changes the process mean and the other changes the process variance. However, the occurrence of one kind of assignable cause does not preclude the occurrence of the other. It is assumed that the quality characteristic is normally distributed and the time that the process remains in control has exponential distribution. Performance measures of these adaptive control charts are obtained through a Markov chain approach. (c) 2005 Elsevier B.V. All rights reserved.
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Stress-induced vascular adaptive response in SHR was investigated, focusing on the endothelium. Noradrenaline responses were studied in intact and denuded aortas from 6-week-old (prehypertensive) and 14-week-old (hypertensive) SHR and age-matched Wistar rats submitted or not to acute stress (20-min swimming and I-h immobilization 25 min apart), preceded or not by chronic stress (2 sessions 2 days apart of 1-h day immobilization for 5-consecutive days). Stress did not alter the reactivity of denuded aorta. Moreover, no alteration in the EC50 values was observed after stress exposure. In intact aortas, acute stress-induced hyporeactivity to noradrenaline similar between strains at both age. Chronic stress potentiated this adaptive response in 6- and 14-week-old Wistar but not in 6-week-old SHR, and did not alter the reactivity of 14-week-old SHR. Maximum response (g) in intact aortas [6-week-old: Wistar 3.25 +/- 0.12, Wistar/acute 1.95 +/- 0.12*, Wistar/chronic 1.36 +/- 0.21*(+), SHR 1.75 +/- 0.11, SHR/acute 0.88 +/- 0.08*, SHR/chronic 0.85 +/- 0.05*; 14-week-old: Wistar 3.83 +/- 0.13, Wistar/acute 2.72 +/- 0.13*, Wistar/chronic 1.91 +/- 0.19*', SHR 4.03 +/- 0.17, SHR/acute 2.26 +/- 0.12*, SHR/chronic 4.10 +/- 0.23; inside the same strain: *P < 0.05 relate to non-stressed rat, (+)P < 0.05 related to acute stressed rat; n = 6-18]. Independent of age and strain, L-NAME and endothelium removal abolished the stress-induced aorta hyporeactivity. Conclusion: the vascular adaptive response to stress is impaired in SHR, independently of the hypertensive state. Moreover, this vascular adaptive response is characterized by endothelial nitric oxide-system hyperactivity in both strains. (c) 2006 Elsevier B.V. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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An adaptive scheme is shown by the authors of the above paper (ibid. vol. 71, no. 2, pp. 275-276, Feb. 1983) for continuous time model reference adaptive systems (MRAS), where relays replace the usual multipliers in the existing MRAS. The commenter shows an error in the analysis of the hyperstability of the scheme, such that the validity of this configuration becomes an open question.
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An algorithm for adaptive IIR filtering that uses prefiltering structure in direct form is presented. This structure has an estimation error that is a linear function of the coefficients. This property greatly simplifies the derivation of gradient-based algorithms. Computer simulations show that the proposed structure improves convergence speed.
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The present work introduces a new strategy of induction machines speed adjustment using an adaptive PID (Proportional Integral Derivative) digital controller with gain planning based on the artificial neural networks. This digital controller uses an auxiliary variable to determine the ideal induction machine operating conditions and to establish the closed loop gain of the system. The auxiliary variable value can be estimated from the information stored in a general-purpose artificial neural network based on CMAC (Cerebellar Model Articulation Controller).
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We develop a general model for adaptive c, np, u and p control charts in which one, two or three design parameters (sample size, sampling interval and control limit width) switch between two values, according to the most recent process information. For a given in-control average sampling rate and a given false alarm rate, the adaptive chart detects changes in the process much faster than a chart with fixed parameters. Moreover, this study also offers general guidance on how to choose an effective design.
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This work presents a procedure for electric load forecasting based on adaptive multilayer feedforward neural networks trained by the Backpropagation algorithm. The neural network architecture is formulated by two parameters, the scaling and translation of the postsynaptic functions at each node, and the use of the gradient-descendent method for the adjustment in an iterative way. Besides, the neural network also uses an adaptive process based on fuzzy logic to adjust the network training rate. This methodology provides an efficient modification of the neural network that results in faster convergence and more precise results, in comparison to the conventional formulation Backpropagation algorithm. The adapting of the training rate is effectuated using the information of the global error and global error variation. After finishing the training, the neural network is capable to forecast the electric load of 24 hours ahead. To illustrate the proposed methodology it is used data from a Brazilian Electric Company. © 2003 IEEE.
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Dental bleaching represents an effective, conservative, and relatively low-cost method for improving the appearance of discolored pulpless teeth. Among the bleaching techniques, the walking bleach technique with sodium perborate associated with water or hydrogen peroxide stands out because of its esthetic results and safety. A modified walking bleach technique with the use of 37% carbamide peroxide as the bleaching agent is presented. Additionally, the adverse effects of dental bleaching in the following restorative procedures are discussed, showing the advantages with the use of 37% carbamide peroxide.
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Motivated by rising drilling operation costs, the oil industry has shown a trend toward real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated with parameters modeling. One of the drillbit performance evaluators, the Rate Of Penetration (ROP), has been used as a drilling control parameter. However, relationships between operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on an auto-regressive with extra input signals, or ARX model and on a Genetic Algorithm (GA) to control the ROP. © [2006] IEEE.