210 resultados para Cross-classification


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An on-line algorithm is developed for the location of single cross point faults in a PLA (FPLA). The main feature of the valgorithm is the determination of a fault set corresponding to the response obtained for a failed test. For the apparently small number of faults in this set, all other tests are generated and a fault table is formed. Subsequently, an adaptive procedure is used to diagnose the fault. Functional equivalence test is carried out to determine the actual fault class if the adaptive testing results in a set of faults with identical tests. The large amount of computation time and storage required in the determination, a priori, of all the fault equivalence classes or in the construction of a fault dictionary are not needed here. A brief study of functional equivalence among the cross point faults is also made.

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An oscillatory flow of a viscous incompressible fluid in an elastic tube of variable cross section has been investigated at low Reynolds number. The equations governing, the flow are derived under the assumption that the variation of the cross-section is slow in the axial direction for a tethered tube. The problem is then reduced to that of solving for the excess pressure from a second order ordinary differential equation with complex valued Bessel functions as the coefficients. This equation has been solved numerically for geometries of physiological interest and a comparison is made with some of the known theoretical and experimental results.

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Oscillatory flow in a tube of slowly varying cross section is investigated in the presence of a uniform magnetic field in the axial direction. A perturbation solution including steady streaming is presented. The pressure and shear stress on the wall for various parameters governing the flow are discussed. Physics of Fluids is copyrighted by The American Institute of Physics.

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This paper presents a Chance-constraint Programming approach for constructing maximum-margin classifiers which are robust to interval-valued uncertainty in training examples. The methodology ensures that uncertain examples are classified correctly with high probability by employing chance-constraints. The main contribution of the paper is to pose the resultant optimization problem as a Second Order Cone Program by using large deviation inequalities, due to Bernstein. Apart from support and mean of the uncertain examples these Bernstein based relaxations make no further assumptions on the underlying uncertainty. Classifiers built using the proposed approach are less conservative, yield higher margins and hence are expected to generalize better than existing methods. Experimental results on synthetic and real-world datasets show that the proposed classifiers are better equipped to handle interval-valued uncertainty than state-of-the-art.

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Mycobacterium smegmatis topoisomerase I exhibits several distinctive characteristics among all topoisomerases. The enzyme is devoid of Zn2+fingers found typically in other bacterial type I topoisomerases and binds DNA in a site-specific manner. Using polyclonal antibodies, we demonstrate the high degree of relatedness of the enzyme across mycobacteria but not other bacteria. This absence of cross-reactivity from other bacteria indicates that mycobacterial topoisomerase I has diverged from Escherichia coli and other bacteria. We have investigated further the immunological properties of the enzyme by raising a panel of monoclonal antibodies that recognises different antigenically active regions of the enzyme and binds it with widely varied affinity. Inhibition of a C-terminal domain-specific antibody binding by enzyme-specific and non-specific oligonucleotides suggests the possibility of using these monoclonal antibodies to probe the structure, function and in vivo role of the enzyme.

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The pulsatile flow of an incompressible viscous fluid in a cylindrical tube of varying cross section is investigated for small Reynolds numbers. The solutions consist of a stedy and an oscillatory part. The shear stress distribution on the wall is evaluated and discussed in detail for special geometries like tapered tubes, locally constricted tubes and peristaltic tubes. The existence of separation in the flow field is noticed.

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In this paper we apply to the photoproduction total cross section a model we have proposed for purely hadronic processes and which is based on QCD mini-jets and soft gluon re-summation. We compare the predictions of our model with the HERA data as well as with other models. For cosmic rays, our model predicts substantially higher cross sections at TeV energies than models based on factorization, but lower than models based on mini-jets alone, without soft gluons. We discuss the origin of this difference.

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For the non-linear bending of cantilever beams of variable cross-section, the effect of large deformations, but with linear elasticity, is considered. The governing integral equation is solved by a numerical iterative procedure. Results for some typical cases are obtained and compared with some of those available in the literature.

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Increased activation of c-src seen in colorectal cancer is an indicator of a poor clinical prognosis, suggesting that identification of downstream effectors of c-src may lead to new avenues of therapy. Guanylyl cyclase C (GC-C) is a receptor for the gastrointestinal hormones guanylin and uroguanylin and the bacterial heat-stable enterotoxin. Though activation of GC-C by its ligands elevates intracellular cyclic GMP (cGMP) levels and inhibits cell proliferation, its persistent expression in colorectal carcinomas and occult metastases makes it a marker for malignancy. We show here that GC-C is a substrate for inhibitory phosphorylation by c-src, resulting in reduced ligand-mediated cGMP production. Consequently, active c-src in colonic cells can overcome GC-C-mediated control of the cell cycle. Furthermore, docking of the c-src SH2 domain to phosphorylated GC-C results in colocalization and further activation of c-src. We therefore propose a novel feed-forward mechanism of activation of c-src that is induced by cross talk between a receptor GC and a tyrosine kinase. Our findings have important implications in understanding the molecular mechanisms involved in the progression and treatment of colorectal cancer.

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Unsteady rotating and stratified flows in geometries with non-uniform cross-sections are investigated under Oseen approximation using Laplace transform technique. The solutions are obtained in closed form and they reveal that the flow remains oscillatory even after infinitely large time. The existence of inertial waves propagating in both positive and negative directions of the flow is observed. When the Rossby or Froude number is close to a certain infinite set of critical values the blocking and back flow occur and the flow pattern becomes more and more complicated with increasing number of stagnant zones when each critical value is crossed. The analogy that is observed in the solutions for rotating and stratified flows is also discussed.

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We propose a novel technique for robust voiced/unvoiced segment detection in noisy speech, based on local polynomial regression. The local polynomial model is well-suited for voiced segments in speech. The unvoiced segments are noise-like and do not exhibit any smooth structure. This property of smoothness is used for devising a new metric called the variance ratio metric, which, after thresholding, indicates the voiced/unvoiced boundaries with 75% accuracy for 0dB global signal-to-noise ratio (SNR). A novelty of our algorithm is that it processes the signal continuously, sample-by-sample rather than frame-by-frame. Simulation results on TIMIT speech database (downsampled to 8kHz) for various SNRs are presented to illustrate the performance of the new algorithm. Results indicate that the algorithm is robust even in high noise levels.

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This paper presents two algorithms for smoothing and feature extraction for fingerprint classification. Deutsch's(2) Thinning algorithm (rectangular array) is used for thinning the digitized fingerprint (binary version). A simple algorithm is also suggested for classifying the fingerprints. Experimental results obtained using such algorithms are presented.

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Protein Kinase-Like Non-kinases (PKLNKs), which are closely related to protein kinases, lack the crucial catalytic aspartate in the catalytic loop, and hence cannot function as protein kinase, have been analysed. Using various sensitive sequence analysis methods, we have recognized 82 PKLNKs from four higher eukaryotic organisms, namely, Homo sapiens, Mus musculus, Rattus norvegicus, and Drosophila melanogaster. On the basis of their domain combination and function, PKLNKs have been classified mainly into four categories: (1) Ligand binding PKLNKs, (2) PKLNKs with extracellular protein-protein interaction domain, (3) PKLNKs involved in dimerization, and (4) PKLNKs with cytoplasmic protein-protein interaction module. While members of the first two classes of PKLNKs have transmembrane domain tethered to the PKLNK domain, members of the other two classes of PKLNKs are cytoplasmic in nature. The current classification scheme hopes to provide a convenient framework to classify the PKLNKs from other eukaryotes which would be helpful in deciphering their roles in cellular processes.