Adaptive control charts for attributes

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.

A fast electric load forecasting using adaptive neural networks

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.

Applying a genetic neuro-model reference adaptive controller in drilling optimization

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.

A genetic neuro-model reference adaptive controller for petroleum wells drilling operations

Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the 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 the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.

Do men and women use similar adaptive locomotion to clear static and dynamic obstacles?

Purpose. The purpose of this study was to analyze the influence of gender on the adaptive locomotion in the clearance of obstacles. Specifically, it was evaluated if there are differences in the space-temporal parameters between male and female in the clearance of and dynamic obstacles moving at both slow and fast speeds. Basic procedures. Five young male adults and five young female adults took part in this study. The task was performed in three conditions: static obstacle and dynamic obstacle - clearance perpendicular to the participant's trajectory at slow speed (1.07 m/s) and at fast speed (1.71 m/s). The trials were recorded by two digital cameras and spatial-temporal information was obtained. Main findings. The dynamic obstacle conditions required more visual inspection. The results showed different adaptive locomotion between the sexes. The distinct gait patterns were evidenced for the spatial and temporal variables and cadence in the three conditions. Conclusions. The women presented a more conservative behavior, which was evidenced by the increase of the length in the penultimate step and in the toe clearance.

Adaptive filter feature identification for structural health monitoring in aeronautical panel

This paper presents an approach for structural health monitoring (SHM) by using adaptive filters. The experimental signals from different structural conditions provided by piezoelectric actuators/sensors bonded in the test structure are modeled by a discrete-time recursive least square (RLS) filter. The biggest advantage to use a RLS filter is the clear possibility to perform an online SHM procedure since that the identification is also valid for non-stationary linear systems. An online damage-sensitive index feature is computed based on autoregressive (AR) portion of coefficients normalized by the square root of the sum of the square of them. The proposed method is then utilized in a laboratory test involving an aeronautical panel coupled with piezoelectric sensors/actuators (PZTs) in different positions. A hypothesis test employing the t-test is used to obtain the damage decision. The proposed algorithm was able to identify and localize the damages simulated in the structure. The results have shown the applicability and drawbacks the method and the paper concludes with suggestions to improve it. ©2010 Society for Experimental Mechanics Inc.

Necessary and sufficient condition for generalized passivity, passification and application to multivariable adaptive systems

Recently, a generalized passivity concept for linear multivariable systems was obtained which allows circumventing the restrictiveness of the usual passivity concept. The latter is associated with the classical SPR (Strictly Positive Real) condition whereas the new concept of passivity is associated with the so called WSPR condition and its advantage in multivariable systems is that it does not require a restrictive symmetry condition of SPR systems. As a result, it allows the design of multivariable adaptive control that, unlike some existing factorization approaches, does not imply in additional overparameterization of the adaptive controller. In this paper, we complete a previously established WSPR sufficient condition and prove that it is also necessary. We also propose some methods of passification by either premultiplying the system output tracking error vector or the system input vector by an adequate passifying matrix multiplier, so that the resulting input/output transfer function becomes WSPR. The efficiency of our proposals are illustrated by simulation utilizing a well known robotics adaptive visual servoing problem. © 2011 IFAC.

Adaptive walking in alzheimer's disease

The aim of this study is to analyze dual-task effects on free and adaptive gait in Alzheimer's disease (AD) patients. Nineteen elders with AD participated in the study. A veteran neuropsychiatrist established the degree of AD in the sample. To determine dual-task effects on free and adaptive gait, patients performed five trials for each experimental condition: free and adaptive gait with and without a dual-task (regressive countdown). Spatial and temporal parameters were collected through an optoelectronic tridimensional system. The central stride was analyzed in free gait, and the steps immediately before (approaching phase) and during the obstacle crossing were analyzed in adaptive gait. Results indicated that AD patients walked more slowly during adaptive gait and free gait, using conservative strategies when confronted either with an obstacle or a secondary task. Furthermore, patients sought for stability to perform the tasks, particularly for adaptive gait with dual task, who used anticipatory and online adjustments to perform the task. Therefore, the increase of task complexity enhances cognitive load and risk of falls for AD patients. © 2012 Diego Orcioli-Silva et al.

An analog model for quantum lightcone fluctuations in nonlinear optics

We propose an analog model for quantum gravity effects using nonlinear dielectrics. Fluctuations of the spacetime lightcone are expected in quantum gravity, leading to variations in the flight times of pulses. This effect can also arise in a nonlinear material. We propose a model in which fluctuations of a background electric field, such as that produced by a squeezed photon state, can cause fluctuations in the effective lightcone for probe pulses. This leads to a variation in flight times analogous to that in quantum gravity. We make some numerical estimates which suggest that the effect might be large enough to be observable. © 2012 Elsevier Inc.

Dengue Virus Type 3 Adaptive Changes during Epidemics in Sao Jose de Rio Preto, Brazil, 2006-2007

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Modulation of cell proliferation, survival and gene expression by RAGE and TLR signaling in cells of the innate and adaptive immune response: role of p38 MAPK and NF-KB

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Adaptive morphology of the heart of Southern-Fur-Seal (Arctocephalus australis - Zimmermamm, 1783)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A Reference Architecture based on Reflection for Self-adaptive Software

Self-adaptive Software (SaS) presents specific characteristics compared to traditional ones, as it makes possible adaptations to be incorporated at runtime. These adaptations, when manually performed, normally become an onerous, error-prone activity. In this scenario, automated approaches have been proposed to support such adaptations; however, the development of SaS is not a trivial task. In parallel, reference architectures are reusable artifacts that aggregate the knowledge of architectures of software systems in specific domains. They have facilitated the development, standardization, and evolution of systems of those domains. In spite of their relevance, in the SaS domain, reference architectures that could support a more systematic development of SaS are not found yet. Considering this context, the main contribution of this paper is to present a reference architecture based on reflection for SaS, named RA4SaS (Reference Architecture for SaS). Its main purpose is to support the development of SaS that presents adaptations at runtime. To show the viability of this reference architecture, a case study is presented. As result, it has been observed that RA4SaS has presented good perspective to efficiently contribute to the area of SaS.