957 resultados para K-Fold Accuracy


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We report on Raman and Ni K-edge x-ray absorption investigations of a NiS2-xSex (with x = 0.00, 0.50/0.55, 0.60, and 1.20) pyrite family. The Ni K-edge absorption edge shows a systematic shift going from an insulating phase (x = 0.00 and 0.50) to a metallic phase (x = 0.60 and 1.20). The near-edge absorption features show a clear evolution with Se doping. The extended x-ray absorption fine structure data reveal the evolution of the local structure with Se doping which mainly governs the local disorder. We also describe the decomposition of the NiS2-xSex Raman spectra and investigate the weights of various phonon modes using Gaussian and Lorentzian profiles. The effectiveness of the fitting models in describing the data is evaluated by means of Bayes factor estimation. The Raman analysis clearly demonstrates the disorder effects due to Se alloying in describing the phonon spectra of NiS2-xSex pyrites.

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In this paper, we present a novel algorithm for piecewise linear regression which can learn continuous as well as discontinuous piecewise linear functions. The main idea is to repeatedly partition the data and learn a linear model in each partition. The proposed algorithm is similar in spirit to k-means clustering algorithm. We show that our algorithm can also be viewed as a special case of an EM algorithm for maximum likelihood estimation under a reasonable probability model. We empirically demonstrate the effectiveness of our approach by comparing its performance with that of the state of art algorithms on various datasets. (C) 2014 Elsevier Inc. All rights reserved.

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Designing a robust algorithm for visual object tracking has been a challenging task since many years. There are trackers in the literature that are reasonably accurate for many tracking scenarios but most of them are computationally expensive. This narrows down their applicability as many tracking applications demand real time response. In this paper, we present a tracker based on random ferns. Tracking is posed as a classification problem and classification is done using ferns. We used ferns as they rely on binary features and are extremely fast at both training and classification as compared to other classification algorithms. Our experiments show that the proposed tracker performs well on some of the most challenging tracking datasets and executes much faster than one of the state-of-the-art trackers, without much difference in tracking accuracy.

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Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mgha(-1)) at spatial scales ranging from 5 to 250m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial ``dilution'' bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

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An increase in the hyperpolarization-activated cyclic nucleotide-gated (HCN) channel conductance reduces input resistance, whereas the consequent increase in the inward h current depolarizes the membrane. This results in a delicate and unique conductance-current balance triggered by the expression of HCN channels. In this study, we employ experimentally constrained, morphologically realistic, conductance-based models of hippocampal neurons to explore certain aspects of this conductance-current balance. First, we found that the inclusion of an experimentally determined gradient in A-type K+ conductance, but not in M-type K+ conductance, tilts the HCN conductance-current balance heavily in favor of conductance, thereby exerting an overall restorative influence on neural excitability. Next, motivated by the well-established modulation of neuronal excitability by synaptically driven high-conductance states observed under in vivo conditions, we inserted thousands of excitatory and inhibitory synapses with different somatodendritic distributions. We measured the efficacy of HCN channels, independently and in conjunction with other channels, in altering resting membrane potential (RMP) and input resistance (R-in) when the neuron received randomized or rhythmic synaptic bombardments through variable numbers of synaptic inputs. We found that the impact of HCN channels on average RMP, R in, firing frequency, and peak-to-peak voltage response was severely weakened under high-conductance states, with the impinging synaptic drive playing a dominant role in regulating these measurements. Our results suggest that the debate on the role of HCN channels in altering excitability should encompass physiological and pathophysiological neuronal states under in vivo conditions and the spatiotemporal interactions of HCN channels with other channels.

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Visual tracking is an important task in various computer vision applications including visual surveillance, human computer interaction, event detection, video indexing and retrieval. Recent state of the art sparse representation (SR) based trackers show better robustness than many of the other existing trackers. One of the issues with these SR trackers is low execution speed. The particle filter framework is one of the major aspects responsible for slow execution, and is common to most of the existing SR trackers. In this paper,(1) we propose a robust interest point based tracker in l(1) minimization framework that runs at real-time with performance comparable to the state of the art trackers. In the proposed tracker, the target dictionary is obtained from the patches around target interest points. Next, the interest points from the candidate window of the current frame are obtained. The correspondence between target and candidate points is obtained via solving the proposed l(1) minimization problem. In order to prune the noisy matches, a robust matching criterion is proposed, where only the reliable candidate points that mutually match with target and candidate dictionary elements are considered for tracking. The object is localized by measuring the displacement of these interest points. The reliable candidate patches are used for updating the target dictionary. The performance and accuracy of the proposed tracker is benchmarked with several complex video sequences. The tracker is found to be considerably fast as compared to the reported state of the art trackers. The proposed tracker is further evaluated for various local patch sizes, number of interest points and regularization parameters. The performance of the tracker for various challenges including illumination change, occlusion, and background clutter has been quantified with a benchmark dataset containing 50 videos. (C) 2014 Elsevier B.V. All rights reserved.

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The structural effects of a representative disallowed conformation of Aib on the 3(10)-helical fold of an octapeptidomimetic are explored. The 1D (H-1, C-13) & 2D NMR, FT-IR and CD data reveal that the octapeptide 1, adopts a 3(10)-helical conformation in solution, as it does in its crystal structure. The C-terminal methyl carboxylate (CO2Me) of 1 was modified into an 1,3-oxazine (Oxa) functional group in the peptidomimetic 2. This modification results in the stabilization of the backbone of the C-terminal Aib (Aib*-Oxa) of 2, in a conformation (phi, =180, 0) that is natively disallowed to Aib. Consequent to the presence of this natively disallowed conformation, the 3(10)-helical fold is not disrupted in the body of the peptidomimetic 2. But the structural distortions that do occur in 2 are primarily in residues in the immediate vicinity of the natively disallowed conformation, rather than in the whole peptide body. Non-native electronic effects resulting from modifications in backbone functional groups can be at the origin of stabilizing residues in natively disallowed conformations. (c) 2014 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 104: 21-36, 2015.

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Large-scale estimates of the area of terrestrial surface waters have greatly improved over time, in particular through the development of multi-satellite methodologies, but the generally coarse spatial resolution (tens of kms) of global observations is still inadequate for many ecological applications. The goal of this study is to introduce a new, globally applicable downscaling method and to demonstrate its applicability to derive fine resolution results from coarse global inundation estimates. The downscaling procedure predicts the location of surface water cover with an inundation probability map that was generated by bagged derision trees using globally available topographic and hydrographic information from the SRTM-derived HydroSHEDS database and trained on the wetland extent of the GLC2000 global land cover map. We applied the downscaling technique to the Global Inundation Extent from Multi-Satellites (GIEMS) dataset to produce a new high-resolution inundation map at a pixel size of 15 arc-seconds, termed GIEMS-D15. GIEMS-D15 represents three states of land surface inundation extents: mean annual minimum (total area, 6.5 x 10(6) km(2)), mean annual maximum (12.1 x 10(6) km(2)), and long-term maximum (173 x 10(6) km(2)); the latter depicts the largest surface water area of any global map to date. While the accuracy of GIEMS-D15 reflects distribution errors introduced by the downscaling process as well as errors from the original satellite estimates, overall accuracy is good yet spatially variable. A comparison against regional wetland cover maps generated by independent observations shows that the results adequately represent large floodplains and wetlands. GIEMS-D15 offers a higher resolution delineation of inundated areas than previously available for the assessment of global freshwater resources and the study of large floodplain and wetland ecosystems. The technique of applying inundation probabilities also allows for coupling with coarse-scale hydro-climatological model simulations. (C) 2014 Elsevier Inc All rights reserved.

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Iron-based layered chalcogenides are interesting because of their structural magnetic and superconducting properties. Single crystals of the parent binary chalcogenides, Fe1+y Te, and intercalated ternary chalcogenides, K0.8Fe2Se2, are grown and investigated in detail. Single crystals are grown by modified horizontal Bridgman method. Fe1+y Te demonstrates an antiferromagnetic (AFM) transition at T (N) =67 K which is identified as a magnetostructural transition. By varying the concentration of excess Fe, we have tuned T (N) over a range of temperature from 67 to 57 K. The superconducting properties of K0.8Fe2Se2 crystals are explored by magnetization measurements. A superconducting transition is observed at T (C) =31 K. The lower critical field of K0.8Fe2Se2 is estimated from field variation of magnetization measurements.

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SARAS is a correlation spectrometer connected to a frequency independent antenna that is purpose-designed for precision measurements of the radio background at long wavelengths. The design, calibration, and observing strategies admit solutions for the internal additive contributions to the radiometer response, and hence a separation of these contaminants from the antenna temperature. We present here a wideband measurement of the radio sky spectrum by SARAS that provides an accurate measurement of the absolute brightness and spectral index between 110 and 175MHz. Accuracy in the measurement of absolute sky brightness is limited by systematic errors of magnitude 1.2%; errors in calibration and in the joint estimation of sky and system model parameters are relatively smaller. We use this wide-angle measurement of the sky brightness using the precision wide-band dipole antenna to provide an improved absolute calibration for the 150 MHz all-sky map of Landecker and Wielebinski: subtracting an offset of 21.4 K and scaling by a factor of 1.05 will reduce the overall offset error to 8 K (from 50 K) and scale error to 0.8% (from 5%). The SARAS measurement of the temperature spectral index is in the range -2.3 to -2.45 in the 110-175MHz band and indicates that the region toward the Galactic bulge has a relatively flatter index.

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This work reports a detailed temperature dependent Raman study on the mixed crystals of K-0.9(NH4)(0.1)H2AsO4 (KADA) from 5K to 300K in the spectral range of 60-1200cm(-1), covering tetragonal to orthorhombic structural phase transition accompanied by paraelectric to ferroelectric transition at T-c* similar to 60K. Multiple phase transitions below transition temperature (Tc* similar to 60K) are marked by the appearance of new modes, splitting of existing ones as well as anomalies in the self-energy parameters (i.e. mode frequencies and damping coefficient) of the phonon modes. Temperature independent behaviour of damping coefficient and abrupt jump in the mode frequency of some of the internal vibrations of AsO4 tetrahedra as well as external vibrations clearly signal long range ferroelectric ordering and proton ordering below T-c*. In addition, we observed that temperature dependence of many prominent phonon modes diverges significantly from their normal anharmonic behaviour below T-c* suggesting potential coupling between pseudospins and phonons. (C) 2015 Author(s).

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We show that in studies of light quark- and gluon-initiated jet discrimination, it is important to include the information on softer reconstructed jets (associated jets) around a primary hard jet. This is particularly relevant while adopting a small radius parameter for reconstructing hadronic jets. The probability of having an associated jet as a function of the primary jet transverse momentum (PT) and radius, the minimum associated jet pi, and the association radius is computed up to next-to-double logarithmic accuracy (NDLA), and the predictions are compared with results from Herwig++, Pythia6 and Pythia8 Monte Carlos (MC). We demonstrate the improvement in quark-gluon discrimination on using the associated jet rate variable with the help of a multivariate analysis. The associated jet rates are found to be only mildly sensitive to the choice of parton shower and hadronization algorithms, as well as to the effects of initial state radiation and underlying event. In addition, the number of k(t) subjets of an anti-k(t) jet is found to be an observable that leads to a rather uniform prediction across different MC's, broadly being in agreement with predictions in NDLA, as compared to the often used number of charged tracks observable.

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The inversion of canopy reflectance models is widely used for the retrieval of vegetation properties from remote sensing. This study evaluates the retrieval of soybean biophysical variables of leaf area index, leaf chlorophyll content, canopy chlorophyll content, and equivalent leaf water thickness from proximal reflectance data integrated broadbands corresponding to moderate resolution imaging spectroradiometer, thematic mapper, and linear imaging self scanning sensors through inversion of the canopy radiative transfer model, PROSAIL. Three different inversion approaches namely the look-up table, genetic algorithm, and artificial neural network were used and performances were evaluated. Application of the genetic algorithm for crop parameter retrieval is a new attempt among the variety of optimization problems in remote sensing which have been successfully demonstrated in the present study. Its performance was as good as that of the look-up table approach and the artificial neural network was a poor performer. The general order of estimation accuracy for para-meters irrespective of inversion approaches was leaf area index > canopy chlorophyll content > leaf chlorophyll content > equivalent leaf water thickness. Performance of inversion was comparable for broadband reflectances of all three sensors in the optical region with insignificant differences in estimation accuracy among them.

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Background: The heterotrimeric M. tuberculosis RecBCD complex, or each of its individual subunits, remains uncharacterized. Results: MtRecD exists as a homodimer in solution, catalyzes ssDNA-dependent ATP hydrolysis, unwinding of DNA replication/recombination intermediates, and interacts with RecA. Conclusion: MtRecD possesses strong 5 3- and weak 3 5-helicase activities. Significance: These findings provide insights into the mechanism underlying DSB repair and homologous recombination in mycobacteria. The annotated whole-genome sequence of Mycobacterium tuberculosis revealed the presence of a putative recD gene; however, the biochemical characteristics of its encoded protein product (MtRecD) remain largely unknown. Here, we show that MtRecD exists in solution as a stable homodimer. Protein-DNA binding assays revealed that MtRecD binds efficiently to single-stranded DNA and linear duplexes containing 5 overhangs relative to the 3 overhangs but not to blunt-ended duplex. Furthermore, MtRecD bound more robustly to a variety of Y-shaped DNA structures having 18-nucleotide overhangs but not to a similar substrate containing 5-nucleotide overhangs. MtRecD formed more salt-tolerant complexes with Y-shaped structures compared with linear duplex having 3 overhangs. The intrinsic ATPase activity of MtRecD was stimulated by single-stranded DNA. Site-specific mutagenesis of Lys-179 in motif I abolished the ATPase activity of MtRecD. Interestingly, although MtRecD-catalyzed unwinding showed a markedly higher preference for duplex substrates with 5 overhangs, it could also catalyze significant unwinding of substrates containing 3 overhangs. These results support the notion that MtRecD is a bipolar helicase with strong 5 3 and weak 3 5 unwinding activities. The extent of unwinding of Y-shaped DNA structures was approximate to 3-fold lower compared with duplexes with 5 overhangs. Notably, direct interaction between MtRecD and its cognate RecA led to inhibition of DNA strand exchange promoted by RecA. Altogether, these studies provide the first detailed characterization of MtRecD and present important insights into the type of DNA structure the enzyme is likely to act upon during the processes of DNA repair or homologous recombination.