Effect of surface on the conductance characteristics of Au‐Bi2Sr2CaCu2O8+δ (single crystal) point contact junctions

We report the effect of surface treatments on the dynamic conductance curves (G=dI/dV‐V) of Au‐Bi2Sr2CaCu2O8+δ (single crystal) point contact junctions of variable junction conductances (100 mS≳G≳100 μS). We find that if the crystal surface is cleaved freshly just prior to making contacts, all irreproducible sharp multiple features often observed in tunneling data of Bi(2212) oxide superconductors disappear. If the cleaved crystal surfaces are left under ambient conditions for a few days and the tunneling experiments are repeated, these multiple features reappear. We also find that if the current in the junction is made to pass predominantly through the bulk (and not along the surface), gap features are sharper. The observed conductance curves are fitted to a modified model [G. E. Blonder et al., Phys. Rev. B 25, 4515 (1982)] and estimated gap values are Δ≂28 to 30 meV corresponding to the ratio 2Δ/kBTc ≂ 7.5 with lifetime broadening Γ/Δ≂0.2. We conclude that the sharp multiple features observed in Bi(2212) tunneling curves has no intrinsic origin in the bulk and they arise from the surface only.

New Concepts for Three-Dimensional Shape Analysis

A new approach to machine representation and analysis of three-dimensional objects is presented. The representation, based on the notion of "skeleton" of an object leads to a scheme for comparing two given object views for shape relations. The objects are composed of long, thin, rectangular prisms joined at their ends. The input picture to the program is the digitized line drawing portraying the three-dimensional object. To compare two object views, two characteristic vertices called "cardinal point" and "end-cardinal point," occurring consistently at the bends and open ends of the object are detected. The skeletons are then obtained as a connected path passing through these points. The shape relationships between the objects are then obtained from the matching characteristics of their skeletons. The method explores the possibility of a more detailed and finer analysis leading to detection of features like symmetry, asymmetry and other shape properties of an object.

Object Tracking Using Motion Direction Detection

We present an algorithm for tracking objects in a video sequence, based on a novel approach for motion detection. We do not estimate the velocity �eld. In-stead we detect only the direction of motion at edge points and thus isolate sets of points which are moving coherently. We use a Hausdor� distance based matching algorithm to match point sets in local neighborhood and thus track objects in a video sequence. We show through some examples the e�ectiveness of the algo- rithm.

Construction of equivalent circuit of a transformer winding from driving-point impedance function - analytical approach

Analytical solution is presented to convert a given driving-point impedance function (in s-domain) into a physically realisable ladder network with inductive coupling between any two sections and losses considered. The number of sections in the ladder network can vary, but its topology is assumed fixed. A study of the coefficients of the numerator and denominator polynomials of the driving-point impedance function of the ladder network, for increasing number of sections, led to the identification of certain coefficients, which exhibit very special properties. Generalised expressions for these specific coefficients have also been derived. Exploiting their properties, it is demonstrated that the synthesis method essentially turns out to be an exercise of solving a set of linear, simultaneous, algebraic equations, whose solution directly yields the ladder network elements. The proposed solution is novel, simple and guarantees a unique network. Presently, the formulation can synthesise a unique ladder network up to six sections.

Sum rules and three point functions

Sum rules constraining the R-current spectral densities are derived holographically for the case of D3-branes, M2-branes and M5-branes all at finite chemical potentials. In each of the cases the sum rule relates a certain integral of the spectral density over the frequency to terms which depend both on long distance physics, hydrodynamics and short distance physics of the theory. The terms which which depend on the short distance physics result from the presence of certain chiral primaries in the OPE of two it-currents which are turned on at finite chemical potential. Since these sum rules contain information of the OPE they provide an alternate method to obtain the structure constants of the two R-currents and the chiral primary. As a consistency check we show that the 3 point function derived from the sum rule precisely matches with that obtained using Witten diagrams.

Supervised matching of comments with news article segments

Comments constitute an important part of Web 2.0. In this paper, we consider comments on news articles. To simplify the task of relating the comment content to the article content the comments are about, we propose the idea of showing comments alongside article segments and explore automatic mapping of comments to article segments. This task is challenging because of the vocabulary mismatch between the articles and the comments. We present supervised and unsupervised techniques for aligning comments to segments the of article the comments are about. More specifically, we provide a novel formulation of supervised alignment problem using the framework of structured classification. Our experimental results show that structured classification model performs better than unsupervised matching and binary classification model.

On the Erdos-Szekeres n-interior point problem

The n-interior point variant of the Erdos-Szekeres problem is to show the following: For any n, n-1, every point set in the plane with sufficient number of interior points contains a convex polygon containing exactly n-interior points. This has been proved only for n-3. In this paper, we prove it for pointsets having atmost logarithmic number of convex layers. We also show that any pointset containing atleast n interior points, there exists a 2-convex polygon that contains exactly n-interior points.

Efficient Regular Expression Pattern Matching for Network Intrusion Detection Systems using Modified Word-based Automata

Network Intrusion Detection Systems (NIDS) intercept the traffic at an organization's network periphery to thwart intrusion attempts. Signature-based NIDS compares the intercepted packets against its database of known vulnerabilities and malware signatures to detect such cyber attacks. These signatures are represented using Regular Expressions (REs) and strings. Regular Expressions, because of their higher expressive power, are preferred over simple strings to write these signatures. We present Cascaded Automata Architecture to perform memory efficient Regular Expression pattern matching using existing string matching solutions. The proposed architecture performs two stage Regular Expression pattern matching. We replace the substring and character class components of the Regular Expression with new symbols. We address the challenges involved in this approach. We augment the Word-based Automata, obtained from the re-written Regular Expressions, with counter-based states and length bound transitions to perform Regular Expression pattern matching. We evaluated our architecture on Regular Expressions taken from Snort rulesets. We were able to reduce the number of automata states between 50% to 85%. Additionally, we could reduce the number of transitions by a factor of 3 leading to further reduction in the memory requirements.

Queueing delay - error probability tradeoff for point-to-point channels with fixed length block codes

We study the tradeoff between the average error probability and the average queueing delay of messages which randomly arrive to the transmitter of a point-to-point discrete memoryless channel that uses variable rate fixed codeword length random coding. Bounds to the exponential decay rate of the average error probability with average queueing delay in the regime of large average delay are obtained. Upper and lower bounds to the optimal average delay for a given average error probability constraint are presented. We then formulate a constrained Markov decision problem for characterizing the rate of transmission as a function of queue size given an average error probability constraint. Using a Lagrange multiplier the constrained Markov decision problem is then converted to a problem of minimizing the average cost for a Markov decision problem. A simple heuristic policy is proposed which approximately achieves the optimal average cost.

Point Spread Function Engineering for Super-Resolution Single-Photon and Multiphoton Fluorescence Microscopy

Super-resolution imaging techniques are of paramount interest for applications in bioimaging and fluorescence microscopy. Recent advances in bioimaging demand application-tailored point spread functions. Here, we present some approaches for generating application-tailored point spread functions along with fast imaging capabilities. Aperture engineering techniques provide interesting solutions for obtaining desired system point spread functions. Specially designed spatial filters—realized by optical mask—are outlined both in a single-lens and 4Pi configuration. Applications include depth imaging, multifocal imaging, and super-resolution imaging. Such an approach is suitable for fruitful integration with most existing state-of-art imaging microscopy modalities.

On Selection of Search Space Dimension in Compressive Sampling Matching Pursuit

Compressive Sampling Matching Pursuit (CoSaMP) is one of the popular greedy methods in the emerging field of Compressed Sensing (CS). In addition to the appealing empirical performance, CoSaMP has also splendid theoretical guarantees for convergence. In this paper, we propose a modification in CoSaMP to adaptively choose the dimension of search space in each iteration, using a threshold based approach. Using Monte Carlo simulations, we show that this modification improves the reconstruction capability of the CoSaMP algorithm in clean as well as noisy measurement cases. From empirical observations, we also propose an optimum value for the threshold to use in applications.

Subspace Pursuit Embedded in Orthogonal Matching Pursuit

Orthogonal Matching Pursuit (OMP) is a popular greedy pursuit algorithm widely used for sparse signal recovery from an undersampled measurement system. However, one of the main shortcomings of OMP is its irreversible selection procedure of columns of measurement matrix. i.e., OMP does not allow removal of the columns wrongly estimated in any of the previous iterations. In this paper, we propose a modification in OMP, using the well known Subspace Pursuit (SP), to refine the subspace estimated by OMP at any iteration and hence boost the sparse signal recovery performance of OMP. Using simulations we show that the proposed scheme improves the performance of OMP in clean and noisy measurement cases.