210 resultados para Cross-classification


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This paper studies the problem of constructing robust classifiers when the training is plagued with uncertainty. The problem is posed as a Chance-Constrained Program (CCP) which ensures that the uncertain data points are classified correctly with high probability. Unfortunately such a CCP turns out to be intractable. The key novelty is in employing Bernstein bounding schemes to relax the CCP as a convex second order cone program whose solution is guaranteed to satisfy the probabilistic constraint. Prior to this work, only the Chebyshev based relaxations were exploited in learning algorithms. Bernstein bounds employ richer partial information and hence can be far less conservative than Chebyshev bounds. Due to this efficient modeling of uncertainty, the resulting classifiers achieve higher classification margins and hence better generalization. Methodologies for classifying uncertain test data points and error measures for evaluating classifiers robust to uncertain data are discussed. Experimental results on synthetic and real-world datasets show that the proposed classifiers are better equipped to handle data uncertainty and outperform state-of-the-art in many cases.

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Our ability to infer the protein quaternary structure automatically from atom and lattice information is inadequate, especially for weak complexes, and heteromeric quaternary structures. Several approaches exist, but they have limited performance. Here, we present a new scheme to infer protein quaternary structure from lattice and protein information, with all-around coverage for strong, weak and very weak affinity homomeric and heteromeric complexes. The scheme combines naive Bayes classifier and point group symmetry under Boolean framework to detect quaternary structures in crystal lattice. It consistently produces >= 90% coverage across diverse benchmarking data sets, including a notably superior 95% coverage for recognition heteromeric complexes, compared with 53% on the same data set by current state-of-the-art method. The detailed study of a limited number of prediction-failed cases offers interesting insights into the intriguing nature of protein contacts in lattice. The findings have implications for accurate inference of quaternary states of proteins, especially weak affinity complexes.

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A general analysis of squeezing transformations for two-mode systems is given based on the four-dimensional real symplectic group Sp(4, R). Within the framework of the unitary (metaplectic) representation of this group, a distinction between compact photon-number-conserving and noncompact photon-number-nonconserving squeezing transformations is made. We exploit the U(2) invariant squeezing criterion to divide the set of all squeezing transformations into a two-parameter family of distinct equivalence classes with representative elements chosen for each class. Familiar two-mode squeezing transformations in the literature are recognized in our framework and seen to form a set of measure zero. Examples of squeezed coherent and thermal states are worked out. The need to extend the heterodyne detection scheme to encompass all of U(2) is emphasized, and known experimental situations where all U(2) elements can be reproduced are briefly described.

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beta protein, a key component of Red-pathway of phage lambda is necessary for its growth and general genetic recombination in recombination-deficient mutants of Escherichia coli. To facilitate studies on structure-function relationships, we overexpressed beta protein and purified it to homogeneity. A chemical cross-linking reagent, glutaraldehyde, was used to stabilize the physical association of beta protein in solution. A 67-kDa band, corresponding to homodimer, was identified after separation by SDS-polyacrylamide gel electrophoresis. Stoichiometric measurements indicated a site-size of 1 monomer of beta protein/5 nucleotide residues. Electrophoretic gel mobility shift assays suggested that beta protein formed stable nucleoprotein complexes with 36-mer, but not with 27- or 17-mer DNA. Interestingly, the interaction of beta protein with DNA and the stability of nucleoprotein complexes was dependent on the presence of MgCl2, and the binding was abolished by 250 mM NaCl. The K-d of beta protein binding to 36-mer DNA was on the order of 1.8 x 10(-6) M. Photochemical cross-linking of native beta protein or its fragments, generated by chymotrypsin, to 36-mer DNA was performed to identify its DNA-binding domain. Characterization of the cross-linked peptide disclosed that amino acids required for DNA-binding specificity resided within a 20-kDa peptide at the N-terminal end. These findings provide a basis for further understanding oi the structure and function of beta protein.

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Peristaltic transport of two fluids occupying the peripheral layer and the core in an elliptic tube is, investigated in elliptic cylindrical co-ordinate system, under long wavelength and low Reynolds number approximations. The effect of peripheral-layer viscosity on the flow rate and the frictional force for a slightly elliptic tube is discussed. The limiting results for the one-fluid model are obtained for different eccentricities of the undisturbed tube cross sections with the same area. As a result of non-uniformity of the peristaltic wave, two different amplitude ratios are defined and the time-averaged flux and mechanical efficiency are studied for different eccentricities. It is observed that the time-averaged flux is not affected significantly by the pressure drop when the eccentricity is large. For the peristaltic waves with same area variation, the pumping seems to improve with the eccentricity.

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In the past few years there have been attempts to develop subspace methods for DoA (direction of arrival) estimation using a fourth?order cumulant which is known to de?emphasize Gaussian background noise. To gauge the relative performance of the cumulant MUSIC (MUltiple SIgnal Classification) (c?MUSIC) and the standard MUSIC, based on the covariance function, an extensive numerical study has been carried out, where a narrow?band signal source has been considered and Gaussian noise sources, which produce a spatially correlated background noise, have been distributed. These simulations indicate that, even though the cumulant approach is capable of de?emphasizing the Gaussian noise, both bias and variance of the DoA estimates are higher than those for MUSIC. To achieve comparable results the cumulant approach requires much larger data, three to ten times that for MUSIC, depending upon the number of sources and how close they are. This is attributed to the fact that in the estimation of the cumulant, an average of a product of four random variables is needed to make an evaluation. Therefore, compared to those in the evaluation of the covariance function, there are more cross terms which do not go to zero unless the data length is very large. It is felt that these cross terms contribute to the large bias and variance observed in c?MUSIC. However, the ability to de?emphasize Gaussian noise, white or colored, is of great significance since the standard MUSIC fails when there is colored background noise. Through simulation it is shown that c?MUSIC does yield good results, but only at the cost of more data.

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Measurement of dipolar couplings using separated local field (SLF) NMR experiment is a powerful tool for structural and dynamics studies of oriented molecules such as liquid crystals and membrane proteins in aligned lipid bilayers. Enhancing the sensitivity of such SLF techniques is of significant importance in present-day solid-state NMR methodology. The present study considers the use of adiabatic cross-polarization for this purpose, which is applied for the first time to one of the well-known SLF techniques, namely, polarization inversion spin exchange at the magic angle (PISEMA). The experiments have been carried out on a single crystal of a model peptide, and a dramatic enhancement in signal-to-noise up to 90% has been demonstrated.

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Three classification techniques, namely, K-means Cluster Analysis (KCA), Fuzzy Cluster Analysis (FCA), and Kohonen Neural Networks (KNN) were employed to group 25 microwatersheds of Kherthal watershed, Rajasthan into homogeneous groups for formulating the basis for suitable conservation and management practices. Ten parameters, mainly, morphological, namely, drainage density (D-d), bifurcation ratio (R-b), stream frequency (F-u), length of overland flow (L-o), form factor (R-f), shape factor (B-s), elongation ratio (R-e), circulatory ratio (R-c), compactness coefficient (C-c) and texture ratio (T) are used for the classification. Optimal number of groups is chosen, based on two cluster validation indices Davies-Bouldin and Dunn's. Comparative analysis of various clustering techniques revealed that 13 microwatersheds out of 25 are commonly suggested by KCA, FCA and KNN i.e., 52%; 17 microwatersheds out of 25 i.e., 68% are commonly suggested by KCA and FCA whereas these are 16 out of 25 in FCA and KNN (64%) and 15 out of 25 in KNN and CA (60%). It is observed from KNN sensitivity analysis that effect of various number of epochs (1000, 3000, 5000) and learning rates (0.01, 0.1-0.9) on total squared error values is significant even though no fixed trend is observed. Sensitivity analysis studies revealed that microwatershecls have occupied all the groups even though their number in each group is different in case of further increase in the number of groups from 5 to 6, 7 and 8. (C) 2010 International Association of Hydro-environment Engineering and Research, Asia Pacific Division. Published by Elsevier B.V. All rights reserved.

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We study the total inelastic gamma gamma cross-section and discuss predictions from different models, with a special attention to their dependence on the input parameters. In particular we examine the results from a simple extension of the Regge Pomeron exchange model and those from the eikonalized mini-jet model. We then compare both of them with recent LEP data.

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We report Doppler-only radar observations of Icarus at Goldstone at a transmitter frequency of 8510 MHz (3.5 cm wavelength) during 8-10 June 1996, the first radar detection of the object since 1968. Optimally filtered and folded spectra achieve a maximum opposite-circular (OC) polarization signal-to-noise ratio of about 10 and help to constrain Icarus' physical properties. We obtain an OC radar cross section of 0.05 km(2) (with a 35% uncertainty), which is less than values estimated by Goldstein (1969) and by Pettengill et al. (1969), and a circular polarization (SC/OC) ratio of 0.5+/-0.2. We analyze the echo power spectrum with a model incorporating the echo bandwidth B and a spectral shape parameter it, yielding a coupled constraint between B and n. We adopt 25 Hz as the lower bound on B, which gives a lower bound on the maximum pole-on breadth of about 0.6 km and upper bounds on the radar and optical albedos that are consistent with Icarus' tentative QS classification. The observed circular polarization ratio indicates a very rough near-surface at spatial scales of the order of the radar wavelength. (C) 1999 Elsevier Science Ltd. All rights reserved.

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Owing to the increased customer demands for make-to-order products and smaller product life-cycles, today assembly lines are designed to ensure a quick switch-over from one product model to another for companies' survival in market place. The complexity associated with the decisions pertaining to the type of training and number of workers and their exposition to the different tasks especially in the current era of customized production is a serious problem that the managers and the HRD gurus are facing in industry. This paper aims to determine the amount of cross-training and dynamic deployment policy caused by workforce flexibility for a make-to-order assembly. The aforementioned issues have been dealt with by adopting the concept of evolutionary fuzzy system because of the linguistic nature of the attributes associated with product variety and task complexity. A fuzzy system-based methodology is proposed to determine the amount of cross-training and dynamic deployment policy. The proposed methodology is tested on 10 sample products of varying complexities and the results obtained are in line with the conclusions drawn by previous researchers.

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In this paper, we show that it is possible to reduce the complexity of Intra MB coding in H.264/AVC based on a novel chance constrained classifier. Using the pairs of simple mean-variances values, our technique is able to reduce the complexity of Intra MB coding process with a negligible loss in PSNR. We present an alternate approach to address the classification problem which is equivalent to machine learning. Implementation results show that the proposed method reduces encoding time to about 20% of the reference implementation with average loss of 0.05 dB in PSNR.

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Cross polarisation is extensively used in solid state NMR for enhancing signals of nuclei with low gyromagnetic ratio. However, the use of the method for providing quantitative structural and dynamics information is limited. This arises due to the fact that the mechanism which is responsible for cross polarisation namely, the dipolar interaction, has a long range and is also anisotropic. In nematic liquid crystals these limitations are easily overcome since molecules orient in a magnetic field. The uniaxial ordering of the molecules essentially removes problems associated with the angular dependence of the interactions encountered in powdered solids. The molecular motion averages out intermolecular dipolar interaction, while retaining partially averaged intramolecular interaction. In this article the use of cross polarisation for obtaining heteronuclear dipolar couplings and hence the order parameters of liquid crystals is presented. Several modifications to the basic experiment were considered and their utility illustrated. A method for obtaining proton-proton dipolar couplings, by utilizing cross polarisation from the dipolar reservoir, is also presented.