969 resultados para optical character recognition


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The Wheeler-Feynman (WF) absorber theory of radiation though no more of interest in explaining self interaction of an electron, can be very useful in today's research in small scale optical systems. The significance of the WF absorber is the use of time-symmetrical solution of Maxwell's equations as opposed to only the retarded solution. The radiative coupling of emitters to nano wires in the near field and change in their lifetimes due to small mode volume enclosures have been elucidated with the retarded solutions before. These solutions have also been shown to agree with quantum electrodynamics, thus allowing for classical electromagnetic approaches in such problems. It is here assumed that the radiative coupling of the emitter with a body is in proportion to its contribution to the classical force of radiative reaction as derived in the WF absorber theory. Representing such nano structures as a partial WF absorber acting on the emitter makes the computations considerably easier than conventional electromagnetic solutions for full boundary conditions.

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TiO2 and Al2O3 are commonly used materials in optical thin films in the visible and near‐infrared wavelength region due to their high transparency and good stability. In this work, TiO2 and Al2O3 single, and nano composite thin films with different compositions were deposited on glass and silicon substrates at room temperature using a sol‐gel spin coater. The optical properties like reflectance, transmittance and refractive index have been studied using Spectrophotometer, and structural properties using X‐Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM).

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alpha-Fe2O3 nanoparticles were synthesized by a low temperature solution combustion method. The structural, magnetic and luminescence properties were studied. Powder X-ray diffraction (PXRD) pattern of alpha-Fe2O3 exhibits pure rhombohedral structure. SEM micrographs reveal the dumbbell shaped particles. The EPR spectrum shows an intense resonance signal at g approximate to 5.61 corresponding to isolated Fe3+ ions situated in axially distorted sites, whereas the g approximate to 2.30 is due to Fe3+ ions coupled by exchange interaction. Raman studies show A(1g) (225 cm(-1)) and E-g (293 and 409 cm(-1)) phonon modes. The absorption at 300 nm results from the ligand to metal charge transfer transitions whereas the 540 nm peak is mainly due to the (6)A(1) + (6)A(1) —> T-4(1)(4G) + T-4(1)(4G) excitation of an Fe3+-Fe3+ pair. A prominent TL glow peak was observed at 140 C at heating rate of 5 degrees C s(-1). The trapping parameters namely activation energy (E), frequency factor (s) and order of kinetics (b) were evaluated and discussed. (C) 2012 Elsevier B.V. All rights reserved.

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Benzimidazole derivatives are well known for their antibacterial, antiviral, anticonvulsant, antihistaminic, anthelmintic and antidepressant activities. Benzimidazole's unique base-selective DNA recognition property has been studied widely. However, most of the early benzimidazole systems have been targeted towards the binding of duplex DNA. Here we have shown the evolution and progress of the design and synthesis of new benzimidazole systems towards selective recognition of the double-stranded DNA first. Then in order to achieve selective recognition of the G-quadruplex DNA and utilize their potential as future anti-cancer drug candidates, we have demonstrated their selective cytotoxicity towards the cancer cells and potent telomerase inhibition ability.

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Purpose: Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. Methods: The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. Results: The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. Conclusions: The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time. (C) 2013 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4792459]

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Background: A better understanding of the quality of cellular immune responses directed against molecularly defined targets will guide the development of TB diagnostics and identification of molecularly defined, clinically relevant M.tb vaccine candidates. Methods: Recombinant proteins (n = 8) and peptide pools (n = 14) from M. tuberculosis (M.tb) targets were used to compare cellular immune responses defined by IFN-gamma and IL-17 production using a Whole Blood Assay (WBA) in a cohort of 148 individuals, i.e. patients with TB + (n = 38), TB- individuals with other pulmonary diseases (n = 81) and individuals exposed to TB without evidence of clinical TB (health care workers, n = 29). Results: M.tb antigens Rv2958c (glycosyltransferase), Rv2962c (mycolyltransferase), Rv1886c (Ag85B), Rv3804c (Ag85A), and the PPE family member Rv3347c were frequently recognized, defined by IFN-gamma production, in blood from healthy individuals exposed to M.tb (health care workers). A different recognition pattern was found for IL-17 production in blood from M.tb exposed individuals responding to TB10.4 (Rv0288), Ag85B (Rv1886c) and the PPE family members Rv0978c and Rv1917c. Conclusions: The pattern of immune target recognition is different in regard to IFN-gamma and IL-17 production to defined molecular M.tb targets in PBMCs from individuals frequently exposed to M.tb. The data represent the first mapping of cellular immune responses against M.tb targets in TB patients from Honduras.

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In this paper, we discuss the issues related to word recognition in born-digital word images. We introduce a novel method of power-law transformation on the word image for binarization. We show the improvement in image binarization and the consequent increase in the recognition performance of OCR engine on the word image. The optimal value of gamma for a word image is automatically chosen by our algorithm with fixed stroke width threshold. We have exhaustively experimented our algorithm by varying the gamma and stroke width threshold value. By varying the gamma value, we found that our algorithm performed better than the results reported in the literature. On the ICDAR Robust Reading Systems Challenge-1: Word Recognition Task on born digital dataset, as compared to the recognition rate of 61.5% achieved by TH-OCR after suitable pre-processing by Yang et. al. and 63.4% by ABBYY Fine Reader (used as baseline by the competition organizers without any preprocessing), we achieved 82.9% using Omnipage OCR applied on the images after being processed by our algorithm.

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In this paper, we describe a method for feature extraction and classification of characters manually isolated from scene or natural images. Characters in a scene image may be affected by low resolution, uneven illumination or occlusion. We propose a novel method to perform binarization on gray scale images by minimizing energy functional. Discrete Cosine Transform and Angular Radial Transform are used to extract the features from characters after normalization for scale and translation. We have evaluated our method on the complete test set of Chars74k dataset for English and Kannada scripts consisting of handwritten and synthesized characters, as well as characters extracted from camera captured images. We utilize only synthesized and handwritten characters from this dataset as training set. Nearest neighbor classification is used in our experiments.

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N-gram language models and lexicon-based word-recognition are popular methods in the literature to improve recognition accuracies of online and offline handwritten data. However, there are very few works that deal with application of these techniques on online Tamil handwritten data. In this paper, we explore methods of developing symbol-level language models and a lexicon from a large Tamil text corpus and their application to improving symbol and word recognition accuracies. On a test database of around 2000 words, we find that bigram language models improve symbol (3%) and word recognition (8%) accuracies and while lexicon methods offer much greater improvements (30%) in terms of word recognition, there is a large dependency on choosing the right lexicon. For comparison to lexicon and language model based methods, we have also explored re-evaluation techniques which involve the use of expert classifiers to improve symbol and word recognition accuracies.

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We have benchmarked the maximum obtainable recognition accuracy on five publicly available standard word image data sets using semi-automated segmentation and a commercial OCR. These images have been cropped from camera captured scene images, born digital images (BDI) and street view images. Using the Matlab based tool developed by us, we have annotated at the pixel level more than 3600 word images from the five data sets. The word images binarized by the tool, as well as by our own midline analysis and propagation of segmentation (MAPS) algorithm are recognized using the trial version of Nuance Omnipage OCR and these two results are compared with the best reported in the literature. The benchmark word recognition rates obtained on ICDAR 2003, Sign evaluation, Street view, Born-digital and ICDAR 2011 data sets are 83.9%, 89.3%, 79.6%, 88.5% and 86.7%, respectively. The results obtained from MAPS binarized word images without the use of any lexicon are 64.5% and 71.7% for ICDAR 2003 and 2011 respectively, and these values are higher than the best reported values in the literature of 61.1% and 41.2%, respectively. MAPS results of 82.8% for BDI 2011 dataset matches the performance of the state of the art method based on power law transform.

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Due to limited available therapeutic options, developing new lead compounds against hepatitis C virus is an urgent need. Human La protein stimulates hepatitis C virus translation through interaction with the hepatitis C viral RNA. A cyclic peptide mimicking the beta-turn of the human La protein that interacts with the viral RNA was synthesized. It inhibits hepatitis C viral RNA translation significantly better than the corresponding linear peptide at longer post-treatment times. The cyclic peptide also inhibited replication as measured by replicon RNA levels using real time RT-PCR. The cyclic peptide emerges as a promising lead compound against hepatitis C.

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We show that the third order optical nonlinearity of 15-atom gold clusters is significantly enhanced when in contact with indium tin oxide (ITO) conducting film. Open and close aperture z-scan experiments together with non-degenerate pump-probe differential transmission experiments were done using 80 fs laser pulses centered at 395 nm and 790 nm on gold clusters encased inside cyclodextrin cavities. We show that two photon absorption coefficient is enhanced by an order of magnitude as compared to that when the clusters are on pristine glass plate. The enhancement for the nonlinear optical refraction coefficient is similar to 3 times. The photo-induced excited state absorption using pump-probe experiments at pump wavelength of 395 nm and probe at 790 nm also show an enhancement by an order of magnitude. These results attributed to the excited state energy transfer in the coupled gold cluster-ITO system are different from the enhancement seen so far in charge donor-acceptor complexes and nanoparticle-conjugate polymer composites.

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Fine powders of beta-Ga2O3 nanostructures were prepared via low temperature reflux condensation method by varying the pH value without using any surfactant. The pH value of reaction mixture had great influence on the morphology of final products. High crystalline single phase beta-Ga2O3 nanostructures were obtained by thermal treatment at 900 degrees C which was confirmed by X-ray diffraction and Raman spectroscopy. The morphological analysis revealed rod like nanostructures at lower and higher pH values of 6 and 10, while spindle like structures were obtained at pH = 8. The phase purity and presence of vibrational bands were identified using Fourier transform infrared spectroscopy. The optical absorbance spectrum showed intense absorption features in the UV spectral region. A broad blue emission peak centered at 441 nm due to donor-acceptor gallium-oxygen vacancy pair recombination appeared. The photocatalytic activity toward Rhodamine B under visible light irradiation was higher for nanorods at pH 10.

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The optical properties and electrical conductivity of highly conducting poly(3,4-ethylenedioxythiophene) (PEDOT) doped with poly(styrenesulfonate) (PSS) are reported as a function of the processing additive conditions. The addition of dimethyl sulfoxide (DMSO) increases the conductivity and modifies the dielectric response as observed from the ellipsometric studies. Also the surface roughness and morphology change with the composition of PEDOT: PSS: DMSO and film deposition conditions. The real part of the dielectric function becomes negative in highly conducting samples, indicating the presence of delocalized charge carriers. The real and imaginary parts of the refractive index were determined as a function of wavelength. The results are consistent with the increase in conductivity upon the addition of DMSO.