Improved optical character recognition by matched filtering

The effectiveness of linear matched filters for improved character discrimination in presence of random noise and poorly defined characters has been investigated. We have found that although the performance of the filter in presence of random noise is reasonably good (16 dB gain in signal-to-noise-ratio) its performance is poor when the unknown character is distorted (linear shift and rotation).

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.

On the Specificity of Carbohydrate-Lectin Recognition The Interaction of a Lectin from Ricinus communis Beans with Simple Saccharides and Concanavalin A

A galactose-specific protein (RC1) isolated from Ricinus communis beans was found to give a precipitin reaction with concanavalin A. Its carbohydrate content amounted to 8–9% of the total protein and was found to be rich in mannose. The interaction of RC1 with galactose and lactose was measured in 0.05 M phosphate buffer containing 0.2 M NaCl (pH 6.8) by the method of conventional equilibrium dialysis. From the analysis of the binding data according to Scatchard method the association constant (Ka) at 5°C was calculated as 3.8 mM−1 and 1.2 mM−1 for lactose and galactose, respectively. In both cases the number of binding sites per molecule of RC1 with molecular weight of 120000 was found to be 2. From the temperature-dependent Ka values for the binding of lactose, the values of –5.7 kcal/mol and –4.3 cal × mol−1× K−1 were calculated for ΔH and ΔS, respectively. The addition of concanavalin A to RC1 or vice versa led to the formation of the insoluble complex RC1· ConA4 containing one molecule of RC1 and one molecule of tetrameric concanavalin A (ConA4) which could be dissociated upon addition of concanavalin A-specific sugars. The complex formation results in a time-dependent appearance of turbidity in the time range from 10s to 10 min. From the measurement of the time-dependent appearance and disappearance of the turbidity the formation (kf) and dissociation (kd) rate constants were calculated as 3 mM−1× s−1 and 0.07 ks−1 respectively. The ratio kf/kd (43μM −1), that corresponds to the association constant of complex RC1· ConA4, is higher than that of mannoside · ConA4 and thereby suggests that protein-protein interaction contributes significantly in stabilising glycoprotein · lectin complexes. The relevance of this finding to the understanding of the chemical specificities that are involved in a model cell-lectin interaction is discussed.

Identification of key DNA elements involved in promoter recognition by Mxr1p, a master regulator of methanol utilization pathway in Pichia pastoris

Mxr1p (methanol expression regulator 1) functions as a key regulator of methanol metabolism in the methylotrophic yeast Pichia pastoris. In this study, a recombinant Mxr1p protein containing the N-terminal zinc finger DNA binding domain was overexpressed and purified from E coli cells and its ability to bind to promoter sequences of AOXI encoding alcohol oxidase was examined. In the AOXI promoter, Mxr1p binds at six different regions. Deletions encompassing these regions result in a significant decrease in AOXI promoter activity in vivo. Based on the analysis of AOXI promoter sequences, a consensus sequence for Mxr1p binding consisting of a core 5' CYCC 3' motif was identified. When the core CYCC sequence is mutated to CYCA, CYCT or CYCM (M = 5-methylcytosine), Mxr1p binding is abolished. Though Mxr1p is the homologue of Saccharomyces cerevisiae Adr1p transcription factor, it does not bind to Adr1p binding site of S. cerevisiae alcohol dehydrogenase promoter (ADH2UAS1). However, two point mutations convert ADH2UAS1 into an Mxr1p binding site. The identification of key DNA elements involved in promoter recognition by Mxr1p is an important step in understanding its function as a master regulator of the methanol utilization pathway in P. pastoris.

Joint evaluation of multiple speech patterns for speech recognition and training

We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.

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.

Recognition and alignment of homologous DNA sequences between minichromosomes and single-stranded DNA promoted by RecA protein

The incorporation of DNA into nucleosomes and higher-order forms of chromatin in vivo creates difficulties with respect to its accessibility for cellular functions such as transcription, replication, repair and recombination. To understand the role of chromatin structure in the process of homologous recombination, we have studied the interaction of nucleoprotein filaments, comprised of RecA protein and ssDNA, with minichromosomes. Using this paradigm, we have addressed how chromatin structure affects the search for homologous DNA sequences, and attempted to distinguish between two mutually exclusive models of DNA-DNA pairing mechanisms. Paradoxically, we found that the search for homologous sequences, as monitored by unwinding of homologous or heterologous duplex DNA, was facilitated by nucleosomes, with no discernible effect on homologous pairing. More importantly, unwinding of minichromosomes required the interaction of nucleoprotein filaments and led to the accumulation of circular duplex DNA sensitive to nuclease P1. Competition experiments indicated that chromatin templates and naked DNA served as equally efficient targets for homologous pairing. These and other findings suggest that nucleosomes do not impede but rather facilitate the search for homologous sequences and establish, in accordance with one proposed model, that unwinding of duplex DNA precedes alignment of homologous sequences at the level of chromatin. The potential application of this model to investigate the role of chromosomal proteins in the alignment of homologous sequences in the context of cellular recombination is considered.

CD4+ alpha beta T cell and gamma delta T cell responses to Mycobacterium tuberculosis. Similarities and differences in Ag recognition, cytotoxic effector function, and cytokine production.

CD4+ and gamma delta T cells are activated readily by Mycobacterium tuberculosis. To examine their role in the human immune response to M. tuberculosis, CD4+ and gamma delta T cells from healthy tuberculin-positive donor were studied for patterns of Ag recognition, cytotoxicity, and cytokine production in response to M. tuberculosis-infected mononuclear phagocytes. Both T cell subsets responded to intact M. tuberculosis and its cytosolic Ags. However, CD4+ and gamma delta T cells differed in the range of cytosolic Ags recognized: reactivity to a wide m.w. range of Ags for CD4+ T cells, and a restricted pattern for gamma delta T cells, with dominance of Ags of 10 to 15 kDa. Both T cell subsets were equally cytotoxic for M. tuberculosis-infected monocytes. Furthermore, both CD4+ and gamma delta T cells produced large amounts of IFN-gamma: mean pg/ml of IFN-gamma in supernatants was 2458 +/- 213 for CD4+ and 2349 +/- 245 for gamma delta T cells. By filter-spot ELISA (ELISPOT), the frequency of IFN-gamma-secreting gamma delta T cells was one-half of that of CD4+ T cells in response to M. tuberculosis, suggesting that gamma delta T cells on a per cell basis were more efficient producers of IFN-gamma than CD4+ T cells. In contrast, CD4+ T cells produced more IL-2 than gamma delta T cells, which correlated with diminished T cell proliferation of gamma delta T cells compared with CD4+ T cells. These results indicate that CD4+ and gamma delta T cell subsets have similar effector functions (cytotoxicity, IFN-gamma production) in response to M. tuberculosis-infected macrophages, despite differences in the Ags recognized, IL-2 production, and efficiency of IFN-gamma production.

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.

Joint decoding of multiple speech patterns for robust speech recognition

We are addressing a new problem of improving automatic speech recognition performance, given multiple utterances of patterns from the same class. We have formulated the problem of jointly decoding K multiple patterns given a single Hidden Markov Model. It is shown that such a solution is possible by aligning the K patterns using the proposed Multi Pattern Dynamic Time Warping algorithm followed by the Constrained Multi Pattern Viterbi Algorithm The new formulation is tested in the context of speaker independent isolated word recognition for both clean and noisy patterns. When 10 percent of speech is affected by a burst noise at -5 dB Signal to Noise Ratio (local), it is shown that joint decoding using only two noisy patterns reduces the noisy speech recognition error rate to about 51 percent, when compared to the single pattern decoding using the Viterbi Algorithm. In contrast a simple maximization of individual pattern likelihoods, provides only about 7 percent reduction in error rate.

Kernels for large margin time-series classification

In this paper we propose a novel family of kernels for multivariate time-series classification problems. Each time-series is approximated by a linear combination of piecewise polynomial functions in a Reproducing Kernel Hilbert Space by a novel kernel interpolation technique. Using the associated kernel function a large margin classification formulation is proposed which can discriminate between two classes. The formulation leads to kernels, between two multivariate time-series, which can be efficiently computed. The kernels have been successfully applied to writer independent handwritten character recognition.

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%.

Line removal and restoration of handwritten strokes

In document images, we often find printed lines over-lapping with hand written elements especially in case of signatures. Typical examples of such images are bank cheques and payment slips. Although the detection and removal of the horizontal lines has been addressed, the restoration of the handwritten area after removal of lines, persists to be a problem of interest. lit this paper, we propose a method for line removal and restoration of the erased areas of the handwritten elements. Subjective evaluation of the results have been conducted to analyze the effectiveness of the proposed method. The results are promising with an accuracy of 86.33%. The entire Process takes less than half a second for completion on a 2.4 GHz 512 MB RAM Pentium IV PC for a document image.

Learning Feature Trajectories Using Gabor Filter Bank for Human Activity Segmentation and Recognition

We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human actions like walking, running, jogging, boxing, hand-waving etc. Since human silhouette can be modeled by a set of rectangles, the elementary human actions can be modeled as a sequence of a set of rectangles with different orientations and scales. The activity segmentation is based on Gabor filter-bank features and normalized spectral clustering. The feature trajectories of an action category are learnt from training example videos using dynamic time warping. The combined segmentation and the recognition processes are very efficient as both the algorithms share the same framework and Gabor features computed for the former can be used for the later. We have also proposed a simple shadow detection technique to extract good silhouette which is necessary for good accuracy of an action recognition technique.