967 resultados para function approximation


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A novel series of vesicle-forming ion-paired amphiphiles, bis(hexadecyldimethylammonium)alkane dipalmitate (1a-1h), containing four chains were synthesized with two isolated headgroups. In each of these amphiphiles, the two headgroup charges are separated by a flexible polymethylene spacer chain -[(CH2)(m)]- of varying lengths (m) such that the length and the conformation of the spacer chain determine the intra-"monomer" headgroup separation. Transmission electron microscopy indicated that each of these forms bilayer membranes upon dispersion in aqueous media. The vesicular properties of these aggregates have been examined by differential scanning calorimetry and temperature-dependent fluorescence anisotropy measurements. Interestingly, their T-m values decreased with the increase in the m value. Thus while the apparent T-m of the lipid with m = 2 (1a) is 74.1 degrees C, the corresponding value observed for the lipid with m = 12 (1h) is 38.9 degrees C. The fluorescence anisotropy values (r) for 1b-1g were quite high (r similar to 0.3) compared to that of 1h (r similar to 0.23) at 20-30 degrees C in their gel states. On the other hand, the r value for vesicular 1b beyond melting was higher (0.1) compared to any of those for 1c-1h (similar to 0.04-0.06). X-ray diffraction of the cast films was performed to understand the nature and the thickness of these membrane organizations. The membrane widths ranged from 30 to 51 A as the m values varied. The entrapment of a small water-soluble solute, riboflavin, by the individual vesicular aggregates, and their sustenance: under an imposed transmembrane pH gradient have also been examined. These results show that all lipid vesicles entrap riboflavin and that generally the resistance to OH- permeation decreases with the increase in m value. Finally,all the above observations were comparatively analyzed, and on the basis of the calculated structures of these lipids, it was possible to conclude that membrane propel-ties can be modulated by spacer chain length variation of the ion-paired amphiphiles.

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We consider the problem of wireless channel allocation to multiple users. A slot is given to a user with a highest metric (e.g., channel gain) in that slot. The scheduler may not know the channel states of all the users at the beginning of each slot. In this scenario opportunistic splitting is an attractive solution. However this algorithm requires that the metrics of different users form independent, identically distributed (iid) sequences with same distribution and that their distribution and number be known to the scheduler. This limits the usefulness of opportunistic splitting. In this paper we develop a parametric version of this algorithm. The optimal parameters of the algorithm are learnt online through a stochastic approximation scheme. Our algorithm does not require the metrics of different users to have the same distribution. The statistics of these metrics and the number of users can be unknown and also vary with time. Each metric sequence can be Markov. We prove the convergence of the algorithm and show its utility by scheduling the channel to maximize its throughput while satisfying some fairness and/or quality of service constraints.

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We consider the problem of scheduling a wireless channel among multiple users. A slot is given to a user with a highest metric (e.g., channel gain) in that slot. The scheduler may not know the channel states of all the users at the beginning of each slot. In this scenario opportunistic splitting is an attractive solution. However this algorithm requires that the metrics of different users form independent, identically distributed (iid) sequences with same distribution and that their distribution and number be known to the scheduler. This limits the usefulness of opportunistic splitting. In this paper we develop a parametric version of this algorithm. The optimal parameters of the algorithm are learnt online through a stochastic approximation scheme. Our algorithm does not require the metrics of different users to have the same distribution. The statistics of these metrics and the number of users can be unknown and also vary with time. We prove the convergence of the algorithm and show its utility by scheduling the channel to maximize its throughput while satisfying some fairness and/or quality of service constraints.

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This paper presents the design of a full fledged OCR system for printed Kannada text. The machine recognition of Kannada characters is difficult due to similarity in the shapes of different characters, script complexity and non-uniqueness in the representation of diacritics. The document image is subject to line segmentation, word segmentation and zone detection. From the zonal information, base characters, vowel modifiers and consonant conjucts are separated. Knowledge based approach is employed for recognizing the base characters. Various features are employed for recognising the characters. These include the coefficients of the Discrete Cosine Transform, Discrete Wavelet Transform and Karhunen-Louve Transform. These features are fed to different classifiers. Structural features are used in the subsequent levels to discriminate confused characters. Use of structural features, increases recognition rate from 93% to 98%. Apart from the classical pattern classification technique of nearest neighbour, Artificial Neural Network (ANN) based classifiers like Back Propogation and Radial Basis Function (RBF) Networks have also been studied. The ANN classifiers are trained in supervised mode using the transform features. Highest recognition rate of 99% is obtained with RBF using second level approximation coefficients of Haar wavelets as the features on presegmented base characters.

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A vast amount of literature has accumulated on the characterization of DNA methyltransferases. The HhaI DNA methyltransferase, a C5-cytosine methyltransferase, has been the subject of investigation for the last 2 decades. Biochemical and kinetic characterization have led to an understanding of the catalytic and kinetic mechanism of the methyltransfer reaction. The HhaI methyltransferase has also been subjected to extensive structural analysis, with the availability of 12 structures with or without a cofactor and a variety of DNA substrates. The mechanism of base flipping, first described for the HhaI methyltransferase, is conserved among all DNA methyltransferases and is also found to occur in numerous DNA repair enzymes. Studies with other methyltransferase reveal a significant structural and functional similarity among different types of methyltransferases. This review aims to summarize the available information on the HhaI DNA methyltransferase.

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An entirely different approach for localisation of winding deformation based on terminal measurements is presented. Within the context of this study, winding deformation means, a discrete and specific change externally imposed at a particular position on the winding. The proposed method is based on pre-computing and plotting the complex network-function loci e.g. driving-point impedance (DPI)] at a selected frequency, for a meaningful range of values for each element (increasing and decreasing) of the ladder network which represents the winding. This loci diagram is called the nomogram. After introducing a discrete change, amplitude and phase of DPI are measured. By plotting this single measurement on the nomogram, it is possible to estimate the location and identify the extent of change. In contrast to the existing approach, the proposed method is fast, non-iterative and yields reasonably good localisation. Experimental results for actual transformer windings (interleaved and continuous disc) are presented.

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We explore a pseudodynamic form of the quadratic parameter update equation for diffuse optical tomographic reconstruction from noisy data. A few explicit and implicit strategies for obtaining the parameter updates via a semianalytical integration of the pseudodynamic equations are proposed. Despite the ill-posedness of the inverse problem associated with diffuse optical tomography, adoption of the quadratic update scheme combined with the pseudotime integration appears not only to yield higher convergence, but also a muted sensitivity to the regularization parameters, which include the pseudotime step size for integration. These observations are validated through reconstructions with both numerically generated and experimentally acquired data. (C) 2011 Optical Society of America

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In engineering design, the end goal is the creation of an artifact, product, system, or process that fulfills some functional requirements at some desired level of performance. As such, knowledge of functionality is essential in a wide variety of tasks in engineering activities, including modeling, generation, modification, visualization, explanation, evaluation, diagnosis, and repair of these artifacts and processes. A formal representation of functionality is essential for supporting any of these activities on computers. The goal of Parts 1 and 2 of this Special Issue is to bring together the state of knowledge of representing functionality in engineering applications from both the engineering and the artificial intelligence (AI) research communities.

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In Saccharomyces cerevisiae, Prp17p is required for the efficient completion of the second step of pre-mRNA splicing. The function and interacting factors for this protein have not been elucidated. We have performed a mutational analysis of yPrp17p to identify protein domains critical for function. A series of deletions were made throughout the region spanning the N-terminal 158 amino acids of the protein, which do not contain any identified structural motifs. The C-terminal portion (amino acids 160–455) contains a WD domain containing seven WD repeats. We determined that a minimal functional Prp17p consists of the WD domain and 40 amino acids N-terminal to it. We generated a three-dimensional model of the WD repeats in Prp17p based on the crystal structure of the [beta]-transducin WD domain. This model was used to identify potentially important amino acids for in vivo functional characterization. Through analysis of mutations in four different loops of Prp17p that lie between [beta] strands in the WD repeats, we have identified four amino acids, 235TETG238, that are critical for function. These amino acids are predicted to be surface exposed and may be involved in interactions that are important for splicing. Temperature-sensitive prp17 alleles with mutations of these four amino acids are defective for the second step of splicing and are synthetically lethal with a U5 snRNA loop I mutation, which is also required for the second step of splicing. These data reinforce the functional significance of this region within the WD domain of Prp17p in the second step of splicing.

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One of the assumptions of the van der Waals and Platteeuw theory for gas hydrates is that the host water lattice is rigid and not distorted by the presence of guest molecules. In this work, we study the effect of this approximation on the triple-point lines of the gas hydrates. We calculate the triple-point lines of methane and ethane hydrates via Monte Carlo molecular simulations and compare the simulation results with the predictions of van der Waals and Platteeuw theory. Our study shows that even if the exact intermolecular potential between the guest molecules and water is known, the dissociation temperatures predicted by the theory are significantly higher. This has serious implications to the modeling of gas hydrate thermodynamics, and in spite of the several impressive efforts made toward obtaining an accurate description of intermolecular interactions in gas hydrates, the theory will suffer from the problem of robustness if the issue of movement of water molecules is not adequately addressed.

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In this paper, expressions for convolution multiplication properties of MDCT are derived starting from the equivalent DFT representations. Using these expressions, methods for implementing linear filtering through block convolution in the MDCT domain are presented. The implementation is exact for symmetric filters and approximate for non-symmetric filters in the case of rectangular window based MDCT. For a general MDCT window function, the filtering is done on the windowed segments and hence the convolution is approximate for symmetric as well as non-symmetric filters. This approximation error is shown to be perceptually insignificant for symmetric impulse response filters. Moreover, the inherent $50 \%$ overlap between adjacent frames used in MDCT computation does reduce this approximation error similar to smoothing of other block processing errors. The presented techniques are useful for compressed domain processing of audio signals.

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In this paper, we consider the problem of selecting, for any given positive integer k, the top-k nodes in a social network, based on a certain measure appropriate for the social network. This problem is relevant in many settings such as analysis of co-authorship networks, diffusion of information, viral marketing, etc. However, in most situations, this problem turns out to be NP-hard. The existing approaches for solving this problem are based on approximation algorithms and assume that the objective function is sub-modular. In this paper, we propose a novel and intuitive algorithm based on the Shapley value, for efficiently computing an approximate solution to this problem. Our proposed algorithm does not use the sub-modularity of the underlying objective function and hence it is a general approach. We demonstrate the efficacy of the algorithm using a co-authorship data set from e-print arXiv (www.arxiv.org), having 8361 authors.

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A methodology termed the “filtered density function” (FDF) is developed and implemented for large eddy simulation (LES) of chemically reacting turbulent flows. In this methodology, the effects of the unresolved scalar fluctuations are taken into account by considering the probability density function (PDF) of subgrid scale (SGS) scalar quantities. A transport equation is derived for the FDF in which the effect of chemical reactions appears in a closed form. The influences of scalar mixing and convection within the subgrid are modeled. The FDF transport equation is solved numerically via a Lagrangian Monte Carlo scheme in which the solutions of the equivalent stochastic differential equations (SDEs) are obtained. These solutions preserve the Itô-Gikhman nature of the SDEs. The consistency of the FDF approach, the convergence of its Monte Carlo solution and the performance of the closures employed in the FDF transport equation are assessed by comparisons with results obtained by direct numerical simulation (DNS) and by conventional LES procedures in which the first two SGS scalar moments are obtained by a finite difference method (LES-FD). These comparative assessments are conducted by implementations of all three schemes (FDF, DNS and LES-FD) in a temporally developing mixing layer and a spatially developing planar jet under both non-reacting and reacting conditions. In non-reacting flows, the Monte Carlo solution of the FDF yields results similar to those via LES-FD. The advantage of the FDF is demonstrated by its use in reacting flows. In the absence of a closure for the SGS scalar fluctuations, the LES-FD results are significantly different from those based on DNS. The FDF results show a much closer agreement with filtered DNS results. © 1998 American Institute of Physics.