339 resultados para Dynamic variation


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A neural-network-aided nonlinear dynamic inversion-based hybrid technique of model reference adaptive control flight-control system design is presented in this paper. Here, the gains of the nonlinear dynamic inversion-based flight-control system are dynamically selected in such a manner that the resulting controller mimics a single network, adaptive control, optimal nonlinear controller for state regulation. Traditional model reference adaptive control methods use a linearized reference model, and the presented control design method employs a nonlinear reference model to compute the nonlinear dynamic inversion gains. This innovation of designing the gain elements after synthesizing the single network adaptive controller maintains the advantages that an optimal controller offers, yet it retains a simple closed-form control expression in state feedback form, which can easily be modified for tracking problems without demanding any a priori knowledge of the reference signals. The strength of the technique is demonstrated by considering the longitudinal motion of a nonlinear aircraft system. An extended single network adaptive control/nonlinear dynamic inversion adaptive control design architecture is also presented, which adapts online to three failure conditions, namely, a thrust failure, an elevator failure, and an inaccuracy in the estimation of C-M alpha. Simulation results demonstrate that the presented adaptive flight controller generates a near-optimal response when compared to a traditional nonlinear dynamic inversion controller.

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A nonlinear stochastic filtering scheme based on a Gaussian sum representation of the filtering density and an annealing-type iterative update, which is additive and uses an artificial diffusion parameter, is proposed. The additive nature of the update relieves the problem of weight collapse often encountered with filters employing weighted particle based empirical approximation to the filtering density. The proposed Monte Carlo filter bank conforms in structure to the parent nonlinear filtering (Kushner-Stratonovich) equation and possesses excellent mixing properties enabling adequate exploration of the phase space of the state vector. The performance of the filter bank, presently assessed against a few carefully chosen numerical examples, provide ample evidence of its remarkable performance in terms of filter convergence and estimation accuracy vis-a-vis most other competing filters especially in higher dimensional dynamic system identification problems including cases that may demand estimating relatively minor variations in the parameter values from their reference states. (C) 2014 Elsevier Ltd. All rights reserved.

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Background: Coats plus syndrome is an autosomal recessive, pleiotropic, multisystem disorder characterized by retinal telangiectasia and exudates, intracranial calcification with leukoencephalopathy and brain cysts, osteopenia with predisposition to fractures, bone marrow suppression, gastrointestinal bleeding and portal hypertension. It is caused by compound heterozygous mutations in the CTC1 gene. Case presentation: We encountered a case of an eight-year old boy from an Indian family with manifestations of Coats plus syndrome along with an unusual occurrence of dextrocardia and situs inversus. Targeted resequencing of the CTC1 gene as well as whole exome sequencing (WES) were conducted in this family to identify the causal variations. The identified candidate variations were screened in ethnicity matched healthy controls. The effect of CTC1 variation on telomere length was assessed using Southern blot. A novel homozygous missense mutation c.1451A > C (p.H484P) in exon 9 of the CTC1 gene and a rare 3'UTR known dbSNP variation (c.*556 T > C) in HES7 were identified as the plausible candidates associated with this complex phenotype of Coats plus and dextrocardia. This CTC1 variation was absent in the controls and we also observed a reduced telomere length in the affected individual's DNA, suggesting its likely pathogenic nature. The reported p.H484P mutation is located in the N-terminal 700 amino acid regionthat is important for the binding of CTC1 to ssDNA through its two OB domains. WES data also showed a rare homozygous missense variation in the TEK gene in the affected individual. Both HES7 and TEK are targets of the Notch signaling pathway. Conclusions: This is the first report of a genetically confirmed case of Coats plus syndrome from India. By means of WES, the genetic variations in this family with unique and rare complex phenotype could be traced effectively. We speculate the important role of Notch signaling in this complex phenotypic presentation of Coats plus syndrome and dextrocardia. The present finding will be useful for genetic diagnosis and carrier detection in the family and for other patients with similar disease manifestations.

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We present here observations on diurnal and seasonal variation of mixing ratio and delta C-13 of air CO2, from an urban station-Bangalore (BLR), India, monitored between October 2008 and December 2011. On a diurnal scale, higher mixing ratio with depleted delta C-13 of air CO2 was found for the samples collected during early morning compared to the samples collected during late afternoon. On a seasonal scale, mixing ratio was found to be higher for dry summer months (April-May) and lower for southwest monsoon months (June-July). The maximum enrichment in delta C-13 of air CO2 (-8.04 +/- 0.02aEuro degrees) was seen in October, then delta C-13 started depleting and maximum depletion (-9.31 +/- 0.07aEuro degrees) was observed during dry summer months. Immediately after that an increasing trend in delta C-13 was monitored coincidental with the advancement of southwest monsoon months and maximum enrichment was seen again in October. Although a similar pattern in seasonal variation was observed for the three consecutive years, the dry summer months of 2011 captured distinctly lower amplitude in both the mixing ratio and delta C-13 of air CO2 compared to the dry summer months of 2009 and 2010. This was explained with reduced biomass burning and increased productivity associated with prominent La Nina condition. While compared with the observations from the nearest coastal and open ocean stations-Cabo de Rama (CRI) and Seychelles (SEY), BLR being located within an urban region captured higher amplitude of seasonal variation. The average delta C-13 value of the end member source CO2 was identified based on both diurnal and seasonal scale variation. The delta C-13 value of source CO2 (-24.9 +/- 3aEuro degrees) determined based on diurnal variation was found to differ drastically from the source value (-14.6 +/- 0.7aEuro degrees) identified based on seasonal scale variation. The source CO2 identified based on diurnal variation incorporated both early morning and late afternoon sample; whereas, the source CO2 identified based on seasonal variation included only afternoon samples. Thus, it is evident from the study that sampling timing is one of the important factors while characterizing the composition of end member source CO2 for a particular station. The difference in delta C-13 value of source CO2 obtained based on both diurnal and seasonal variation might be due to possible contribution from cement industry along with fossil fuel / biomass burning as predominant sources for the station along with differential meteorological conditions prevailed.

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Dynamic analysis techniques have been proposed to detect potential deadlocks. Analyzing and comprehending each potential deadlock to determine whether the deadlock is feasible in a real execution requires significant programmer effort. Moreover, empirical evidence shows that existing analyses are quite imprecise. This imprecision of the analyses further void the manual effort invested in reasoning about non-existent defects. In this paper, we address the problems of imprecision of existing analyses and the subsequent manual effort necessary to reason about deadlocks. We propose a novel approach for deadlock detection by designing a dynamic analysis that intelligently leverages execution traces. To reduce the manual effort, we replay the program by making the execution follow a schedule derived based on the observed trace. For a real deadlock, its feasibility is automatically verified if the replay causes the execution to deadlock. We have implemented our approach as part of WOLF and have analyzed many large (upto 160KLoC) Java programs. Our experimental results show that we are able to identify 74% of the reported defects as true (or false) positives automatically leaving very few defects for manual analysis. The overhead of our approach is negligible making it a compelling tool for practical adoption.

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Modulus variation of NiTi shape memory alloy has been investigated at microstructural level through nano dynamical mechanical analysis and compared with bulk experimental measurements. The differences between the modulus values at the macro and micro level as well as within the micro level are discussed and the corresponding variations have been explained based on the crystal structure, orientation and misorientation. The experimental results confirm a higher modulus value for the martensite phase that is in agreement with the theoretical predictions. (C) 2015 Elsevier B. V. All rights reserved.

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In the present study, amino-silane modified layered organosilicates were used to reinforce cyclic olefin copolymer to enhance the thermal, mechanical and moisture impermeable barrier properties. The optimum clay loading (4%) in the nanocomposite increases the thermal stability of the film while further loading decreases film stability. Water absorption behavior at 62 degrees C was carried out and compared with the behavior at room temperature and 48 degrees C. The stiffness of the matrix increases with clay content and the recorded strain to failure for the composite films was lower than the neat film. Dynamic mechanical analysis show higher storage modulus and low loss modulus for 2.5-4 wt% clay loading. Calcium degradation test and device encapsulation also show the evidence of optimum clay loading of 4 wt% for improved low water vapor transmission rates compared to other nanocomposite films. (C) 2014 Elsevier Ltd. All rights reserved.

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When Markov chain Monte Carlo (MCMC) samplers are used in problems of system parameter identification, one would face computational difficulties in dealing with large amount of measurement data and (or) low levels of measurement noise. Such exigencies are likely to occur in problems of parameter identification in dynamical systems when amount of vibratory measurement data and number of parameters to be identified could be large. In such cases, the posterior probability density function of the system parameters tends to have regions of narrow supports and a finite length MCMC chain is unlikely to cover pertinent regions. The present study proposes strategies based on modification of measurement equations and subsequent corrections, to alleviate this difficulty. This involves artificial enhancement of measurement noise, assimilation of transformed packets of measurements, and a global iteration strategy to improve the choice of prior models. Illustrative examples cover laboratory studies on a time variant dynamical system and a bending-torsion coupled, geometrically non-linear building frame under earthquake support motions. (C) 2015 Elsevier Ltd. All rights reserved.