Localization of handwritten text in documents using moment invariants and Delaunay triangulation

This paper describes an approach based on Zernike moments and Delaunay triangulation for localization of hand-written text in machine printed text documents. The Zernike moments of the image are first evaluated and we classify the text as hand-written using the nearest neighbor classifier. These features are independent of size, slant, orientation, translation and other variations in handwritten text. We then use Delaunay triangulation to reclassify the misclassified text regions. When imposing Delaunay triangulation on the centroid points of the connected components, we extract features based on the triangles and reclassify the text. We remove the noise components in the document as part of the preprocessing step so this method works well on noisy documents. The success rate of the method is found to be 86%. Also for specific hand-written elements such as signatures or similar text the accuracy is found to be even higher at 93%.

Frechet distance based approach for searching online handwritten documents

We propose a novel, language-neutral approach for searching online handwritten text using Frechet distance. Online handwritten data, which is available as a time series (x,y,t), is treated as representing a parameterized curve in two-dimensions and the problem of searching online handwritten text is posed as a problem of matching two curves in a two-dimensional Euclidean space. Frechet distance is a natural measure for matching curves. The main contribution of this paper is the formulation of a variant of Frechet distance that can be used for retrieving words even when only a prefix of the word is given as query. Extensive experiments on UNIPEN dataset(1) consisting of over 16,000 words written by 7 users show that our method outperforms the state-of-the-art DTW method. Experiments were also conducted on a Multilingual dataset, generated on a PDA, with encouraging results. Our approach can be used to implement useful, exciting features like auto-completion of handwriting in PDAs.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

"Standards are living documents ..."

"Standards are living documents which reflect progress in science, technology and systems" - Standards Australia.

Electronic excitations in solids studied using inelastic x-ray scattering

Inelastic x-ray scattering can be used to study the electronic structure of matter. The x rays scattered from the target both induce and carry information on the electronic excitations taking place in the system. These excitations are the manifestations of the electronic structure and the physics governing the many-body system. This work presents results of non-resonant inelastic x-ray scattering experiments on a range of materials including metallic, insulating and semiconducting compounds as well as an organic polymer. The experiments were carried out at the National Synchrotron Light Source, USA and at the European Synchrotron Radiation Facility, France. The momentum transfer dependence of the experimental valence- and core-electron excitation spectra is compared with the results of theoretical first principles computations that incorporate the electron-hole interaction. A recently developed method for analyzing the momentum transfer dependence of core-electron excitation spectra is studied in detail. This method is based on real space multiple scattering calculations and is used to extract the angular symmetry components of the local unoccupied density of final states.

Studies of electronic structure by x-ray Raman and emission spectroscopy: applications to MgB2 superconductors and high pressure physics

X-ray Raman scattering and x-ray emission spectroscopies were used to study the electronic properties and phase transitions in several condensed matter systems. The experimental work, carried out at the European Synchrotron Radiation Facility, was complemented by theoretical calculations of the x-ray spectra and of the electronic structure. The electronic structure of MgB2 at the Fermi level is dominated by the boron σ and π bands. The high density of states provided by these bands is the key feature of the electronic structure contributing to the high critical temperature of superconductivity in MgB2. The electronic structure of MgB2 can be modified by atomic substitutions, which introduce extra electrons or holes into the bands. X ray Raman scattering was used to probe the interesting σ and π band hole states in pure and aluminum substituted MgB2. A method for determining the final state density of electron states from experimental x-ray Raman scattering spectra was examined and applied to the experimental data on both pure MgB2 and on Mg(0.83)Al(0.17)B2. The extracted final state density of electron states for the pure and aluminum substituted samples revealed clear substitution induced changes in the σ and π bands. The experimental work was supported by theoretical calculations of the electronic structure and x-ray Raman spectra. X-ray emission at the metal Kβ line was applied to the studies of pressure and temperature induced spin state transitions in transition metal oxides. The experimental studies were complemented by cluster multiplet calculations of the electronic structure and emission spectra. In LaCoO3 evidence for the appearance of an intermediate spin state was found and the presence of a pressure induced spin transition was confirmed. Pressure induced changes in the electronic structure of transition metal monoxides were studied experimentally and were analyzed using the cluster multiplet approach. The effects of hybridization, bandwidth and crystal field splitting in stabilizing the high pressure spin state were discussed. Emission spectroscopy at the Kβ line was also applied to FeCO3 and a pressure induced iron spin state transition was discovered.

Nickel(II) meso-hydroxyporphyrin complexes revisited: Palladium-catalysed synthesis, electronic structures of derived oxy radicals, and oxidative coupling to a dioxoporphodimethene dyad

We report the synthesis and characterisation of new examples of meso-hydroxynickel(II) porphyrins with 5,15-diphenyl and 10-phenyl-5,15-diphenyl/diaryl substitu- tion. The OH group was introduced by using carbonate or hydroxide as nucleophile by using palladium/phosphine cat- alysis. The NiPor OHs exist in solution in equilibrium with the corresponding oxy radicals NiPor OC. The 15-phenyl group stabilises the radicals, so that the 1H NMR spectra of {NiPor OH} are extremely broad due to chemical exchange with the paramagnetic species. The radical concentration for the diphenylporphyrin analogue is only 1%, and its NMR line-broadening was able to be studied by variable-tempera- ture NMR spectroscopy. The EPR signals of NiPor OC are con- sistent with somewhat delocalised porphyrinyloxy radicals, and the spin distributions calculated by using density func- tional theory match the EPR and NMR spectroscopic obser- vations. Nickel(II) meso-hydroxy-10,20-diphenylporphyrin was oxidatively coupled to a dioxo-terminated porphodimethene dyad, the strongly red-shifted electronic spectrum of which was successfully modelled by using time-dependent DFT calculations.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Electronic structure and bonding of beta-rhombohedral boron using cluster fragment approach

Theoretical studies using density functional theory are carried out to understand the electronic structure and bonding and electronic properties of elemental beta-rhombohedral boron. The calculated band structure of ideal beta-rhombohedral boron (B-105) shows valence electron deficiency and depicts metallic behavior. This is in contrast to the experimental result that it is a semiconductor. To understand this ambiguity we discuss the electronic structure and bonding of this allotrope with cluster fragment approach using our recently proposed mno rule. This helps us to comprehend in greater detail the structure of B-105 and materials which are closely related to beta-rhombohedral boron. The molecular structures B12H12-2, B28H21+1, BeB27H21, LiB27H21-1, CB27H21+2, B57H36+3, Be3B54H36, and Li2CB54H36, and corresponding solids Li8Be3B102 and Li10CB102 are arrived at using these ideas and studied using first principles density functional theory calculations.

Selective dissemination of XML documents using GAs and SVM

XML has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Self Adaptive Migration Model Genetic Algorithm (SAMCA)[5] and multi class Support Vector Machine (SVM) are used to learn a user model. Based on the feedback from the users the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Flow driven electronic transport in carbon nan otubes

The flow of a liquid on single-walled carbon nanotube bundles induces an electrical signal (voltage/current) in the sample along the direction of the flow. The electrical response is found to be logarithmic in the flow speed over a wide range. The magnitude of the flow induced electrical signal generated depends sensitively on the ionic conductivity and the polar nature of the liquid, and electrical biasing of the nanotubes can control its direction. Our measurements suggest that the dominant mechanism responsible for this highly sub-linear response should involve a direct forcing of the free charge carriers in the nanotubes by the fluctuating Coulombic field of the liquid flowing past it.