166 resultados para Electronic document


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The electronic absorption peak at around 2 eV of polyaniline (in the emeraldine base form) solution is found to be highly sensitive to the dielectric constant of the solvent, showing a bathochromic shift. An increase in electron density on the imine nitrogen of the polymer, on ‘2 eV’ excitation, has been concluded.

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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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Extraction of text areas from the document images with complex content and layout is one of the challenging tasks. Few texture based techniques have already been proposed for extraction of such text blocks. Most of such techniques are greedy for computation time and hence are far from being realizable for real time implementation. In this work, we propose a modification to two of the existing texture based techniques to reduce the computation. This is accomplished with Harris corner detectors. The efficiency of these two textures based algorithms, one based on Gabor filters and other on log-polar wavelet signature, are compared. A combination of Gabor feature based texture classification performed on a smaller set of Harris corner detected points is observed to deliver the accuracy and efficiency.

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Many transition metal oxide materials of high chemical purity are not necessarily monophasic. Thus, single crystals of chemically pure rare earth manganites and cobaltates of the general formula Ln1-xAxMO3 (Ln=rare earth metal, A=alkaline earth metal, M=Mn, Co) exhibit the phenomenon of electronic phase separation wherein phases of different electronic and magnetic properties coexist. Such phase separation, the length scale of which can vary anywhere between a few nanometers to microns, gives distinct signatures in X-ray and neutron diffraction patterns, electrical and magnetic properties, as well as in NMR and other spectroscopies. While the probe one employs to investigate electronic phase separation depends on the length scale, it is noteworthy that direct imaging of the inhomogeneities has been accomplished. Some understanding of this phenomenon has been possible on the basis of some of the theoretical models, but we are far from unraveling the varied aspects of this new phenomenon. Herein, we present the highlights of experimental techniques and theoretical approaches, and comment on the future outlook for this fascinating phenomenon

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Electronic absorption spectra of a variety of thiocarbonyl and selenocarbonyl compounds have been compared to point out their similarities. Interesting correlations between the absorption maxima and electronegativities of substituents in both the seleno- and thio-carbonyl compounds have been reported.

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Energy loss spectra of superconducting YBa2Cu3O6.9' Bi1.5Pb0.5Ca2.5Sr1.5Cu3O10+δ and Tl2CaBa2Cu3O8 obtained at primary electron energies in the 170–310 eV range show features reflecting the commonalities in their electronic structures. The relative intensity of the plasmon peak shows a marked drop across the transition temperature. Secondary electron emission spectra of the cuprates also reveal some features of the electronic structure.

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An electron energy loss spectroscopic study of the formic acid dimer has shown bands centred around 7.2, 8.5, 9.8, and 11.1 eV, of which the first and the third bands are assigned to n- rc* transitions and the other two to n-n* transitions; similar transitions are found in the acetic acid dimer.

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Orbital energies and electronic transition energies of BH3·H2S and BH3·CO obtained from ultraviolet (HeI) photoelectron spectroscopy and electron energy loss spectroscopy are discussed in the light of quantum mechanical calculations. BH3·H2O has been characterized, for the first time, by means of the HeI spectrum and the ionization energies assigned to the various orbitals based on calculations.

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We have investigated the electronic structure of Ba1-xKxBiO3 (0

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In this paper, we use reinforcement learning (RL) as a tool to study price dynamics in an electronic retail market consisting of two competing sellers, and price sensitive and lead time sensitive customers. Sellers, offering identical products, compete on price to satisfy stochastically arriving demands (customers), and follow standard inventory control and replenishment policies to manage their inventories. In such a generalized setting, RL techniques have not previously been applied. We consider two representative cases: 1) no information case, were none of the sellers has any information about customer queue levels, inventory levels, or prices at the competitors; and 2) partial information case, where every seller has information about the customer queue levels and inventory levels of the competitors. Sellers employ automated pricing agents, or pricebots, which use RL-based pricing algorithms to reset the prices at random intervals based on factors such as number of back orders, inventory levels, and replenishment lead times, with the objective of maximizing discounted cumulative profit. In the no information case, we show that a seller who uses Q-learning outperforms a seller who uses derivative following (DF). In the partial information case, we model the problem as a Markovian game and use actor-critic based RL to learn dynamic prices. We believe our approach to solving these problems is a new and promising way of setting dynamic prices in multiseller environments with stochastic demands, price sensitive customers, and inventory replenishments.

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Disordered Sr2FeMoO6 shows a drastic reduction in saturation magnetization compared to highly ordered samples, moreover magnetization as a function of the temperature for different disordered samples shows qualitatively different behaviours. We investigate the origin of such diversity by performing spatially resolved photoemission spectroscopy on various disordered samples. Our results establish that extensive electronic inhomogeneity, arising most probably from an underlying chemical inhomogeneity in disordered samples, is responsible for the observed magnetic inhomogeneity. It is further pointed out that these inhomogeneities are connected with composition fluctuations of the type Sr2Fe1+xMo1-xO6 with Fe-rich (x > 0) and Mo-rich (x < 0) regions.

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Using the configuration-interaction approach, we show that various core-level spectroscopic observations on the high-Tc superconducting oxides can be consistently described in terms of mixing between d9 and d10 configurations, with a negligible amount of the d8 (Cu3+) state. From our analysis of the existing experimental data, we provide evidence of a wide and continuous valence transition in these systems as a function of temperature. The changes in the hybridization strengths deduced here are indicative of structural modifications of the square-planar CuO4 clusters with decreasing temperature.

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The results of spin-polarized MSXagr calculations show that the ground state of the CuO 4 6– cluster is essentially non-magnetic in spite of odd number of electrons in the system for short Cu–O distances (1.90 Å) as found in the highT c superconductors. This arises due to the fact that the unpaired electron resides in a molecular orbital with primarily oxygen 3s character. The stability of this molecular orbital is found to be sensitive to the cluster geometry and thus, increase in Cu–O distance (as well as other changes affecting oxygen-oxygen distance) tend to favour a magnetic state. From these calculations we have also estimated the Coulomb correlation strength within the Cu 3d to be about 5.3 eV.