133 resultados para Nuisance attribute projection


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1] The poor predictability of the Indian summer monsoon ( ISM) appears to be due to the fact that a large fraction of interannual variability (IAV) is governed by unpredictable "internal'' low frequency variations. Mechanisms responsible for the internal IAV of the monsoon have not been clearly identified. Here, an attempt has been made to gain insight regarding the origin of internal IAV of the seasonal ( June - September, JJAS) mean rainfall from "internal'' IAV of the ISM simulated by an atmospheric general circulation model (AGCM) driven by fixed annual cycle of sea surface temperature (SST). The underlying hypothesis that monsoon ISOs are responsible for internal IAV of the ISM is tested. The spatial and temporal characteristics of simulated summer intraseasonal oscillations ( ISOs) are found to be in good agreement with those observed. A long integration with the AGCM forced with observed SST, shows that ISO activity over the Asian monsoon region is not modulated by the observed SST variations. The internal IAV of ISM, therefore, appears to be decoupled from external IAV. Hence, insight gained from this study may be useful in understanding the observed internal IAV of ISM. The spatial structure of the ISOs has a significant projection on the spatial structure of the seasonal mean and a common spatial mode governs both intraseasonal and interannual variability. Statistical average of ISO anomalies over the season ( seasonal ISO bias) strengthens or weakens the seasonal mean. It is shown that interannual anomalies of seasonal mean are closely related to the seasonal mean of intraseasonal anomalies and explain about 50% of the IAV of the seasonal mean. The seasonal mean ISO bias arises partly due to the broad-band nature of the ISO spectrum allowing the time series to be aperiodic over the season and partly due to a non-linear process where the amplitude of ISO activity is proportional to the seasonal bias of ISO anomalies. The later relation is a manifestation of the binomial character of rainfall time series. The remaining 50% of the IAV may arise due to land-surface processes, interaction between high frequency variability and ISOs, etc.

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Impacts of climate change on hydrology are assessed by downscaling large scale general circulation model (GCM) outputs of climate variables to local scale hydrologic variables. This modelling approach is characterized by uncertainties resulting from the use of different models, different scenarios, etc. Modelling uncertainty in climate change impact assessment includes assigning weights to GCMs and scenarios, based on their performances, and providing weighted mean projection for the future. This projection is further used for water resources planning and adaptation to combat the adverse impacts of climate change. The present article summarizes the recent published work of the authors on uncertainty modelling and development of adaptation strategies to climate change for the Mahanadi river in India.

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An approximate dynamic programming (ADP) based neurocontroller is developed for a heat transfer application. Heat transfer problem for a fin in a car's electronic module is modeled as a nonlinear distributed parameter (infinite-dimensional) system by taking into account heat loss and generation due to conduction, convection and radiation. A low-order, finite-dimensional lumped parameter model for this problem is obtained by using Galerkin projection and basis functions designed through the 'Proper Orthogonal Decomposition' technique (POD) and the 'snap-shot' solutions. A suboptimal neurocontroller is obtained with a single-network-adaptive-critic (SNAC). Further contribution of this paper is to develop an online robust controller to account for unmodeled dynamics and parametric uncertainties. A weight update rule is presented that guarantees boundedness of the weights and eliminates the need for persistence of excitation (PE) condition to be satisfied. Since, the ADP and neural network based controllers are of fairly general structure, they appear to have the potential to be controller synthesis tools for nonlinear distributed parameter systems especially where it is difficult to obtain an accurate model.

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This paper presents a robust fixed order H-2 controller design using Strengthened discrete optimal projection equations, which approximate the first order necessary optimality condition. The novelty of this work is the application of the robust H-2 controller to a micro aerial vehicle named Sarika2 developed in house. The controller is designed in discrete domain for the lateral dynamics of Sarika2 in the presence of low frequency atmospheric turbulence (gust) and high frequency sensor noise. The design specification includes simultaneous stabilization, disturbance rejection and noise attenuation over the entire flight envelope of the vehicle. The resulting controller performance is comprehensively analyzed by means of simulation.

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The increasing use of 3D modeling of Human Face in Face Recognition systems, User Interfaces, Graphics, Gaming and the like has made it an area of active study. Majority of the 3D sensors rely on color coded light projection for 3D estimation. Such systems fail to generate any response in regions covered by Facial Hair (like beard, mustache), and hence generate holes in the model which have to be filled manually later on. We propose the use of wavelet transform based analysis to extract the 3D model of Human Faces from a sinusoidal white light fringe projected image. Our method requires only a single image as input. The method is robust to texture variations on the face due to space-frequency localization property of the wavelet transform. It can generate models to pixel level refinement as the phase is estimated for each pixel by a continuous wavelet transform. In cases of sparse Facial Hair, the shape distortions due to hairs can be filtered out, yielding an estimate for the underlying face. We use a low-pass filtering approach to estimate the face texture from the same image. We demonstrate the method on several Human Faces both with and without Facial Hairs. Unseen views of the face are generated by texture mapping on different rotations of the obtained 3D structure. To the best of our knowledge, this is the first attempt to estimate 3D for Human Faces in presence of Facial hair structures like beard and mustache without generating holes in those areas.

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Separation of printed text blocks from the non-text areas, containing signatures, handwritten text, logos and other such symbols, is a necessary first step for an OCR involving printed text recognition. In the present work, we compare the efficacy of some feature-classifier combinations to carry out this separation task. We have selected length-nomalized horizontal projection profile (HPP) as the starting point of such a separation task. This is with the assumption that the printed text blocks contain lines of text which generate HPP's with some regularity. Such an assumption is demonstrated to be valid. Our features are the HPP and its two transformed versions, namely, eigen and Fisher profiles. Four well known classifiers, namely, Nearest neighbor, Linear discriminant function, SVM's and artificial neural networks have been considered and efficiency of the combination of these classifiers with the above features is compared. A sequential floating feature selection technique has been adopted to enhance the efficiency of this separation task. The results give an average accuracy of about 96.

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We present a report of our analysis of wave vector dependence of the static dielectric function of a dipolar liquid obtained by a microscopic calculation. At low values of the wave vector (k), the longitudinal dielectric function ϵ(k) increases with k, in contradiction to some assumptions reported in the literature. As the value of k is increased, ϵ(k) diverges at a critical value kc which depends on the value of the long wavelength static dielectric constant (ϵ0) of the liquid. The dielectric function is negative for values of k greater than kc. At large values of k, the calculated ϵ(k) fails to attain the limiting value of unity. We attribute this result to the failure of the point dipole assumption made in the evaluation of the polarization correlation function required by the theory. The behavior of ϵ(k) for the dipolar liquid is compared with that of one component plasma for which reliable results can be obtained over the full range of wave vectors. For both systems, the stability conditions are fulfilled at all values of k. A plausible explanation of this rather exotic behavior of ϵ(k) is given.

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The existence of icosahedral twins has been established in Al-10at.% Mn alloy. By a stereographic approach a close resemblance to the decagonal phase is pointed out. The simulation of twin diffraction patterns has been done based on the projection formalism. The physical significance of twinning in terms of hyperdimensional projection is discussed.

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Regional impacts of climate change remain subject to large uncertainties accumulating from various sources, including those due to choice of general circulation models (GCMs), scenarios, and downscaling methods. Objective constraints to reduce the uncertainty in regional predictions have proven elusive. In most studies to date the nature of the downscaling relationship (DSR) used for such regional predictions has been assumed to remain unchanged in a future climate. However,studies have shown that climate change may manifest in terms of changes in frequencies of occurrence of the leading modes of variability, and hence, stationarity of DSRs is not really a valid assumption in regional climate impact assessment. This work presents an uncertainty modeling framework where, in addition to GCM and scenario uncertainty, uncertainty in the nature of the DSR is explored by linking downscaling with changes in frequencies of such modes of natural variability. Future projections of the regional hydrologic variable obtained by training a conditional random field (CRF) model on each natural cluster are combined using the weighted Dempster-Shafer (D-S) theory of evidence combination. Each projection is weighted with the future projected frequency of occurrence of that cluster (''cluster linking'') and scaled by the GCM performance with respect to the associated cluster for the present period (''frequency scaling''). The D-S theory was chosen for its ability to express beliefs in some hypotheses, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The methodology is tested for predicting monsoon streamflow of the Mahanadi River at Hirakud Reservoir in Orissa, India. The results show an increasing probability of extreme, severe, and moderate droughts due to limate change. Significantly improved agreement between GCM predictions owing to cluster linking and frequency scaling is seen, suggesting that by linking regional impacts to natural regime frequencies, uncertainty in regional predictions can be realistically quantified. Additionally, by using a measure of GCM performance in simulating natural regimes, this uncertainty can be effectively constrained.

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Sinusoidal structured light projection (SSLP) technique, specifically-phase stepping method, is in widespread use to obtain accurate, dense 3-D data. But, if the object under investigation possesses surface discontinuities, phase unwrapping (an intermediate step in SSLP) stage mandatorily require several additional images, of the object with projected fringes (of different spatial frequencies), as input to generate a reliable 3D shape. On the other hand, Color-coded structured light projection (CSLP) technique is known to require a single image as in put, but generates sparse 3D data. Thus we propose the use of CSLP in conjunction with SSLP to obtain dense 3D data with minimum number of images as input. This approach is shown to be significantly faster and reliable than temporal phase unwrapping procedure that uses a complete exponential sequence. For example, if a measurement with the accuracy obtained by interrogating the object with 32 fringes in the projected pattern is carried out with both the methods, new strategy proposed requires only 5 frames as compared to 24 frames required by the later method.

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In some bimolecular diffusion-controlled electron transfer (ET) reactions such as ion recombination (IR), both solvent polarization relaxation and the mutual diffusion of the reacting ion pair may determine the rate and even the yield of the reaction. However, a full treatment with these two reaction coordinates is a challenging task and has been left mostly unsolved. In this work, we address this problem by developing a dynamic theory by combining the ideas from ET reaction literature and barrierless chemical reactions. Two-dimensional coupled Smoluchowski equations are employed to compute the time evolution of joint probability distribution for the reactant (P-(1)(X,R,t)) and the product (p((2))(X,R,t)), where X, as is usual in ET reactions, describes the solvent polarization coordinate and R is the distance between the reacting ion pair. The reaction is described by a reaction line (sink) which is a function of X and R obtained by imposing a condition of equal energy on the initial and final states of a reacting ion pair. The resulting two-dimensional coupled equations of motion have been solved numerically using an alternate direction implicit (ADI) scheme (Peaceman and Rachford, J. Soc. Ind. Appl. Math. 1955, 3, 28). The results reveal interesting interplay between polarization relaxation and translational dynamics. The following new results have been obtained. (i) For solvents with slow longitudinal polarization relaxation, the escape probability decreases drastically as the polarization relaxation time increases. We attribute this to caging by polarization of the surrounding solvent, As expected, for the solvents having fast polarization relaxation, the escape probability is independent of the polarization relaxation time. (ii) In the slow relaxation limit, there is a significant dependence of escape probability and average rate on the initial solvent polarization, again displaying the effects of polarization caging. Escape probability increases, and the average rate decreases on increasing the initial polarization. Again, in the fast polarization relaxation limit, there is no effect of initial polarization on the escape probability and the average rate of IR. (iii) For normal and barrierless regions the dependence of escape probability and the rate of IR on initial polarization is stronger than in the inverted region. (iv) Because of the involvement of dynamics along R coordinate, the asymmetrical parabolic (that is, non-Marcus) energy gap dependence of the rate is observed.

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The present paper deals with the study of the effects of electron (8 MeV) irradiation on the dielectric and ferroelectric properties of PbZrO3 thin films grown by sol-gel technique. The films were (0.62 mu m thick) subjected to electron irradiation using Microtron accelerator (delivered dose 80, 100, 120 kGy). The films were well crystallized prior to and after electron irradiation. However, local amorphization was observed after irradiation. There is an appreciable change in the dielectric constant after irradiation with different delivered doses. The dielectric loss showed significant frequency dispersion for both unirradiated and electron irradiated films. T (c) was found to shift towards higher temperature with increasing delivered dose. The effect of radiation induced increase of E >'(T) is related to an internal bias field, which is caused by radiation induced charges trapped at grain boundaries. The double butterfly loop is retained even after electron irradiation to the different delivered doses. The broader hysteresis loop seems to be related to radiation induced charges causing an enhanced space charge polarization. Radiation-induced oxygen vacancies do not change the general shape of the AFE hysteresis loop but they increase P (s) of the hysteresis at the electric field forced AFE to FE phase transition. We attribute the changes in the dielectric properties to the structural defects such as oxygen vacancies and radiation induced charges. The shift in T (C), increase in dielectric constant, broader hysteresis loop, and increase in P (r) can be related to radiation induced charges causing space charge polarization. Double butterfly and hysteresis loops were retained indicative of AFE nature of the films.

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A linear state feedback gain vector used in the control of a single input dynamical system may be constrained because of the way feedback is realized. Some examples of feedback realizations which impose constraints on the gain vector are: static output feedback, constant gain feedback for several operating points of a system, and two-controller feedback. We consider a general class of problems of stabilization of single input dynamical systems with such structural constraints and give a numerical method to solve them. Each of these problems is cast into a problem of solving a system of equalities and inequalities. In this formulation, the coefficients of the quadratic and linear factors of the closed-loop characteristic polynomial are the variables. To solve the system of equalities and inequalities, a continuous realization of the gradient projection method and a barrier method are used under the homotopy framework. Our method is illustrated with an example for each class of control structure constraint.

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A model comprising several servers, each equipped with its own queue and with possibly different service speeds, is considered. Each server receives a dedicated arrival stream of jobs; there is also a stream of generic jobs that arrive to a job scheduler and can be individually allocated to any of the servers. It is shown that if the arrival streams are all Poisson and all jobs have the same exponentially distributed service requirements, the probabilistic splitting of the generic stream that minimizes the average job response time is such that it balances the server idle times in a weighted least-squares sense, where the weighting coefficients are related to the service speeds of the servers. The corresponding result holds for nonexponentially distributed service times if the service speeds are all equal. This result is used to develop adaptive quasi-static algorithms for allocating jobs in the generic arrival stream when the load parameters are unknown. The algorithms utilize server idle-time measurements which are sent periodically to the central job scheduler. A model is developed for these measurements, and the result mentioned is used to cast the problem into one of finding a projection of the root of an affine function, when only noisy values of the function can be observed

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A simple but efficient algorithm is presented for linear programming. The algorithm computes the projection matrix exactly once throughout the computation unlike that of Karmarkar’s algorithm where in the projection matrix is computed at each and every iteration. The algorithm is best suitable to be implemented on a parallel architecture. Complexity of the algorithm is being studied.