Choice of Classifiers in Hierarchical Recognition of Online Handwritten Kannada and Tamil Aksharas

In this paper, we propose a novel dexterous technique for fast and accurate recognition of online handwritten Kannada and Tamil characters. Based on the primary classifier output and prior knowledge, the best classifier is chosen from set of three classifiers for second stage classification. Prior knowledge is obtained through analysis of the confusion matrix of primary classifier which helped in identifying the multiple sets of confused characters. Further, studies were carried out to check the performance of secondary classifiers in disambiguating among the confusion sets. Using this technique we have achieved an average accuracy of 92.6% for Kannada characters on the MILE lab dataset and 90.2% for Tamil characters on the HP Labs dataset.

Effect of Prior Ultraviolet Irradiation on Thermal Decomposition and Ignition of Coal

Prior ultraviolet irradiation of coal results in catalysing the subsequent thermal decomposition and ignition of coal. Mechanically, it is shown that ultraviolet radiation brings about the catalysis by acting on the inorganic components of coal.

Fluorescent labelling of strychnine: A novel approach for recognition of strychnine binding sites on neuronal membrane

trychnine was coupled to fluorescein isothiocyanate to mark strychnine binding sites in spinal cord of rat. Specific binding of strychnine could be demonstrated in synaptosomal fraction. Addition of glycine to the strychninised membrane led to a decrease in fluorescence indicating same receptor loci.

Dynamic Space Warping Of Strokes For Recognition Of Online Handwritten Characters

This paper suggests a scheme for classifying online handwritten characters, based on dynamic space warping of strokes within the characters. A method for segmenting components into strokes using velocity profiles is proposed. Each stroke is a simple arbitrary shape and is encoded using three attributes. Correspondence between various strokes is established using Dynamic Space Warping. A distance measure which reliably differentiates between two corresponding simple shapes (strokes) has been formulated thus obtaining a perceptual distance measure between any two characters. Tests indicate an accuracy of over 85% on two different datasets of characters.

A model for visual recognition of alphanumerics

In this paper we propose a hypothetical scheme for recognizing the alphanumerics. The scheme is based on the known physiological structure of the visual cortex and the concept of a short Lino extractor nouron (SLEN). We assumo four basic typca of such units for extracting vertical, horizontal, right and left inclined straight line segments. The patterns reconstructed from the scheme show perfect agreement with the test patterns. The model indicates that the recognition of letters T and H requires extraction of the largest number of features.

Recognition of nonstructural protein-peptides by cytotoxic t-lymphocytes raised against japanese encephalitis-virus

We have previously reported that Lyt(2+) cytotoxic T lymphocytes (CTL) can be raised against Japanese encephalitis virus (JEV) in BALB/c mice. In order to confirm the presence of H-2K(d)-restricted CTL and to examine their cross-recognition of West Wile virus (WNV), we tested the capacity of anti-JEV CTL to lyse uninfected syngeneic target cells that were pulsed with synthetic peptides. The sequence of the synthetic peptides was predicted based upon the H-2K(d) binding consensus motif. We show here that preincubation of uninfected syngeneic targets (P388D1) with JEV NS1- and NS3-derived peptides [NS1 (891-899) and NS3 (1804-1812)], but not with JEV NS5-derived peptide [NS5 (3370-3378)], partially sensitized them for lysis by polyclonal anti-JEV CTL. These results indicate the CTL recognition of NS1- and NS3-derived peptides of JEV.

Recognition of Interaction Interface Residues in Low-Resolution Structures of Protein Assemblies Solely from the Positions of C alpha Atoms

Background: The number of available structures of large multi-protein assemblies is quite small. Such structures provide phenomenal insights on the organization, mechanism of formation and functional properties of the assembly. Hence detailed analysis of such structures is highly rewarding. However, the common problem in such analyses is the low resolution of these structures. In the recent times a number of attempts that combine low resolution cryo-EM data with higher resolution structures determined using X-ray analysis or NMR or generated using comparative modeling have been reported. Even in such attempts the best result one arrives at is the very course idea about the assembly structure in terms of trace of the C alpha atoms which are modeled with modest accuracy. Methodology/Principal Findings: In this paper first we present an objective approach to identify potentially solvent exposed and buried residues solely from the position of C alpha atoms and amino acid sequence using residue type-dependent thresholds for accessible surface areas of C alpha. We extend the method further to recognize potential protein-protein interface residues. Conclusion/Significance: Our approach to identify buried and exposed residues solely from the positions of C alpha atoms resulted in an accuracy of 84%, sensitivity of 83-89% and specificity of 67-94% while recognition of interfacial residues corresponded to an accuracy of 94%, sensitivity of 70-96% and specificity of 58-94%. Interestingly, detailed analysis of cases of mismatch between recognition of interface residues from C alpha positions and all-atom models suggested that, recognition of interfacial residues using C alpha atoms only correspond better with intuitive notion of what is an interfacial residue. Our method should be useful in the objective analysis of structures of protein assemblies when positions of only C alpha positions are available as, for example, in the cases of integration of cryo-EM data and high resolution structures of the components of the assembly.

An Insight to the Dynamics of Conserved Water Molecular Triad in IMPDH II (Human): Recognition of Cofactor and Substrate to Catalytic Arg 322

Inosine 5' monophosphate dehydrogenase (IMPDH II) is a key enzyme involved in the de novo biosynthesis pathway of purine nucleotides and is also considered to be an excellent target for cancer inhibitor design. The conserve R 322 residue (in human) is thought to play some role in the recognition of inhibitor and cofactor through the catalytic D 364 and N 303. The 15 ns simulation and the water dynamics of the three different PDB structures (1B3O, 1NF7, and 1NFB) of human IMPDH by CHARMM force field have clearly indicated the involvement of three conserved water molecules (W-L, W-M, and W-C) in the recognition of catalytic residues (R 322, D 364, and N 303) to inhibitor and cofactor. Both the guanidine nitrogen atoms (NH1 and NH 2) of the R 322 have anchored the di- and mono-nucleotide (cofactor and inhibitor) binding domains via the conserved W-C and W-L water molecules. Another conserved water molecule W-M seems to bridge the two domains including the R 322 and also the W-C and W-L through seven centers H-bonding coordination. The conserved water molecular triad (W-C - W-M - W-L) in the protein complex may thought to play some important role in the recognition of inhibitor and cofactor to the protein through R 322 residue.

Recognition of active and inactive catalytic triads: A template based approach

It Is well established that a sequence template along with the database is a powerful tool for identifying the biological function of proteins. Here, we describe a method for predicting the catalytic nature of certain proteins among the several protein structures deposited in the Protein Data Bank (PDB) For the present study, we considered a catalytic triad template (Ser-His-Asp) found in serine proteases We found that a geometrically optimized active site template can be used as a highly selective tool for differentiating an active protein among several inactive proteins, based on their Ser-His-Asp interactions. For any protein to be proteolytic in nature, the bond angle between Ser O-gamma-Ser H-gamma His N-epsilon 2 in the catalytic triad needs to be between 115 degrees and 140 degrees The hydrogen bond distance between Ser H-gamma His N-epsilon 2 is more flexible in nature and it varies from 2 0 angstrom to 27 angstrom while in the case of His H-delta 1 Asp O-delta 1, it is from 1.6 angstrom to 2.0 angstrom In terms of solvent accessibility, most of the active proteins lie in the range of 10-16 angstrom(2), which enables easy accessibility to the substrate These observations hold good for most catalytic triads and they can be employed to predict proteolytic nature of these catalytic triads (C) 2010 Elsevier B V All rights reserved.

Machine recognition of online handwritten Devanagari characters

In this paper, we describe a system for the automatic recognition of isolated handwritten Devanagari characters obtained by linearizing consonant conjuncts. Owing to the large number of characters and resulting demands on data acquisition, we use structural recognition techniques to reduce some characters to others. The residual characters are then classified using the subspace method. Finally the results of structural recognition and feature-based matching are mapped to give final output. The proposed system Ifs evaluated for the writer dependent scenario.

Applicability of Statistical Learning Algorithms for Spatial Variability of Rock Depth

Two algorithms are outlined, each of which has interesting features for modeling of spatial variability of rock depth. In this paper, reduced level of rock at Bangalore, India, is arrived from the 652 boreholes data in the area covering 220 sqa <.km. Support vector machine (SVM) and relevance vector machine (RVM) have been utilized to predict the reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth. The support vector machine (SVM) that is firmly based on the theory of statistical learning theory uses regression technique by introducing epsilon-insensitive loss function has been adopted. RVM is a probabilistic model similar to the widespread SVM, but where the training takes place in a Bayesian framework. Prediction results show the ability of learning machine to build accurate models for spatial variability of rock depth with strong predictive capabilities. The paper also highlights the capability ofRVM over the SVM model.

Memory-based reasoning approach for pattern recognition of binary images

Template matching is concerned with measuring the similarity between patterns of two objects. This paper proposes a memory-based reasoning approach for pattern recognition of binary images with a large template set. It seems that memory-based reasoning intrinsically requires a large database. Moreover, some binary image recognition problems inherently need large template sets, such as the recognition of Chinese characters which needs thousands of templates. The proposed algorithm is based on the Connection Machine, which is the most massively parallel machine to date, using a multiresolution method to search for the matching template. The approach uses the pyramid data structure for the multiresolution representation of templates and the input image pattern. For a given binary image it scans the template pyramid searching the match. A binary image of N × N pixels can be matched in O(log N) time complexity by our algorithm and is independent of the number of templates. Implementation of the proposed scheme is described in detail.

CHITRA: Cognitive handprinted input-trained recursively analyzing system for recognition of alphanumeric characters

A novel system for recognition of handprinted alphanumeric characters has been developed and tested. The system can be employed for recognition of either the alphabet or the numeral by contextually switching on to the corresponding branch of the recognition algorithm. The two major components of the system are the multistage feature extractor and the decision logic tree-type catagorizer. The importance of ldquogoodrdquo features over sophistication in the classification procedures was recognized, and the feature extractor is designed to extract features based on a variety of topological, morphological and similar properties. An information feedback path is provided between the decision logic and the feature extractor units to facilitate an interleaved or recursive mode of operation. This ensures that only those features essential to the recognition of a particular sample are extracted each time. Test implementation has demonstrated the reliability of the system in recognizing a variety of handprinted alphanumeric characters with close to 100% accuracy.

Recognition of Polycyclic Aromatic Hydrocarbons and Their Derivatives by the 1,3-Dinaphthalimide Conjugate of Calix4]arene: Emission, Absorption, Crystal Structures, and Computational Studies

Polycyclic aromatic hydrocarbons (PAHs) are environmental pollutants as well as well-known carcinogens. Therefore, it is important to develop an effective receptor for the detection and quantification of such molecules in solution. In view of this, a 1,3-dinaphthalimide derivative of calix4]arene (L) has been synthesized and characterized, and the structure has been established by single crystal XRD. In the crystal lattice, intermolecular arm-to-arm pi center dot center dot center dot pi overlap dominates and thus L becomes a promising receptor for providing interactions with the aromatic species in solution, which can be monitored by following the changes that occur in its fluorescence and absorption spectra. On the basis of the solution studies carried out with about 17 derivatives of the aromatic guest molecular systems, it may be concluded that the changes that occur in the fluorescence intensity seem to be proportional to the number of aromatic rings present and thus proportional to the extent of pi center dot center dot center dot pi interaction present between the naphthalimide moieties and the aromatic portion of the guest molecule. Though the nonaromatic portion of the guest species affects the fluorescence quenching, the trend is still based on the number of rings present in these. Four guest aldehydes are bound to L with K-ass of 2000-6000 M-1 and their minimum detection limit is in the range of 8-35 mu M. The crystal structure of a naphthaldehyde complex, L.2b, exhibits intermolecular arm-to-arm as well as arm-to-naphthaldehyde pi center dot center dot center dot pi interactions. Molecular dynamics studies of L carried out in the presence of aromatic aldehydes under vacuum as well as in acetonitrile resulted in exhibiting interactions observed in the solid state and hence the changes observed in the fluorescence and absorption spectra are attributable for such interactions. Complex formation has also been delineated through ESI MS studies. Thus L is a promising receptor that can recognize PAHs by providing spectral changes proportional to the aromatic conjugation of the guest and the extent of aromatic pi center dot center dot center dot pi interactions present between L and the guest.

A tutorial survey of reinforcement learning

This paper gives a compact, self-contained tutorial survey of reinforcement learning, a tool that is increasingly finding application in the development of intelligent dynamic systems. Research on reinforcement learning during the past decade has led to the development of a variety of useful algorithms. This paper surveys the literature and presents the algorithms in a cohesive framework.