Generating string solutions in BTZ

Integrability of classical strings in the BTZ black hole enables the construction and study of classical string propagation in this background. We first apply the dressing method to obtain classical string solutions in the BTZ black hole. We dress time like geodesics in the BTZ black hole and obtain open string solutions which are pinned on the boundary at a single point and whose end points move on time like geodesics. These strings upon regularising their charge and spins have a dispersion relation similar to that of giant magnons. We then dress space like geodesics which start and end on the boundary of the BTZ black hole and obtain minimal surfaces which can penetrate the horizon of the black hole while being pinned at the boundary. Finally we embed the giant gluon solutions in the BTZ background in two different ways. They can be embedded as a spiral which contracts and expands touching the horizon or a spike which originates from the boundary and touches the horizon.

Can the viscosity in astrophysical black hole accretion disks be close to its string theory bound?

String theory and gauge/gravity duality suggest the lower bound of shear viscosity (eta) to entropy density (s) for any matter to be mu h/4 pi k(B), when h and k(B) are reduced Planck and Boltzmann constants respectively and mu <= 1. Motivated by this, we explore eta/s in black hole accretion flows, in order to understand if such exotic flows could be a natural site for the lowest eta/s. Accretion flow plays an important role in black hole physics in identifying the existence of the underlying black hole. This is a rotating shear flow with insignificant molecular viscosity, which could however have a significant turbulent viscosity, generating transport, heat and hence entropy in the flow. However, in presence of strong magnetic field, magnetic stresses can help in transporting matter independent of viscosity, via celebrated Blandford-Payne mechanism. In such cases, energy and then entropy produces via Ohmic dissipation. In,addition, certain optically thin, hot, accretion flows, of temperature greater than or similar to 10(9) K, may be favourable for nuclear burning which could generate/absorb huge energy, much higher than that in a star. We find that eta/s in accretion flows appears to be close to the lower bound suggested by theory, if they are embedded by strong magnetic field or producing nuclear energy, when the source of energy is not viscous effects. A lower bound on eta/s also leads to an upper bound on the Reynolds number of the flow.

Stiff string approximations in Rayleigh-Ritz method for rotating beams

The governing differential equation of the rotating beam reduces to that of a stiff string when the centrifugal force is assumed as constant. The solution of the static homogeneous part of this equation is enhanced with a polynomial term and used in the Rayleighs method. Numerical experiments show better agreement with converged finite element solutions compared to polynomials. Using this as an estimate for the first mode shape, higher mode shape approximations are obtained using Gram-Schmidt orthogonalization. Estimates for the first five natural frequencies of uniform and tapered beams are obtained accurately using a very low order Rayleigh-Ritz approximation.

Block Sparse Estimator for Grid Matching in Single Snapshot DoA Estimation

In this work, the grid mismatch problem for a single snapshot direction of arrival estimation problem is studied. We derive a Bayesian Cramer-Rao bound for the grid mismatch problem with the errors in variables model and propose a block sparse estimator for grid matching and sparse recovery.

Adaptive selection of search space in look ahead orthogonal matching pursuit

Compressive Sensing theory combines the signal sampling and compression for sparse signals resulting in reduction in sampling rate and computational complexity of the measurement system. In recent years, many recovery algorithms were proposed to reconstruct the signal efficiently. Look Ahead OMP (LAOMP) is a recently proposed method which uses a look ahead strategy and performs significantly better than other greedy methods. In this paper, we propose a modification to the LAOMP algorithm to choose the look ahead parameter L adaptively, thus reducing the complexity of the algorithm, without compromising on the performance. The performance of the algorithm is evaluated through Monte Carlo simulations.

Projection-based atom selection in orthogonal matching pursuit for compressive sensing

For compressive sensing, we endeavor to improve the atom selection strategy of the existing orthogonal matching pursuit (OMP) algorithm. To achieve a better estimate of the underlying support set progressively through iterations, we use a least squares solution based atom selection method. From a set of promising atoms, the choice of an atom is performed through a new method that uses orthogonal projection along-with a standard matched filter. Through experimental evaluations, the effect of projection based atom selection strategy is shown to provide a significant improvement for the support set recovery performance, in turn, the compressive sensing recovery.

Using Relationships for Matching Textual Domain Models with Existing Code

We address the task of mapping a given textual domain model (e.g., an industry-standard reference model) for a given domain (e.g., ERP), with the source code of an independently developed application in the same domain. This has applications in improving the understandability of an existing application, migrating it to a more flexible architecture, or integrating it with other related applications. We use the vector-space model to abstractly represent domain model elements as well as source-code artifacts. The key novelty in our approach is to leverage the relationships between source-code artifacts in a principled way to improve the mapping process. We describe experiments wherein we apply our approach to the task of matching two real, open-source applications to corresponding industry-standard domain models. We demonstrate the overall usefulness of our approach, as well as the role of our propagation techniques in improving the precision and recall of the mapping task.

Accurate point matching based on multi-objective Genetic Algorithm for multi-sensor satellite imagery

This paper investigates a novel approach for point matching of multi-sensor satellite imagery. The feature (corner) points extracted using an improved version of the Harris Corner Detector (HCD) is matched using multi-objective optimization based on a Genetic Algorithm (GA). An objective switching approach to optimization that incorporates an angle criterion, distance condition and point matching condition in the multi-objective fitness function is applied to match corresponding corner-points between the reference image and the sensed image. The matched points obtained in this way are used to align the sensed image with a reference image by applying an affine transformation. From the results obtained, the performance of the image registration is evaluated and compared with existing methods, namely Nearest Neighbor-Random SAmple Consensus (NN-Ran-SAC) and multi-objective Discrete Particle Swarm Optimization (DPSO). From the performed experiments it can be concluded that the proposed approach is an accurate method for registration of multi-sensor satellite imagery. (C) 2014 Elsevier Inc. All rights reserved.

Fixed-orientation equilateral triangle matching of point sets

Given a point set P and a class C of geometric objects, G(C)(P) is a geometric graph with vertex set P such that any two vertices p and q are adjacent if and only if there is some C is an element of C containing both p and q but no other points from P. We study G(del)(P) graphs where del is the class of downward equilateral triangles (i.e., equilateral triangles with one of their sides parallel to the x-axis and the corner opposite to this side below that side). For point sets in general position, these graphs have been shown to be equivalent to half-Theta(6) graphs and TD-Delaunay graphs. The main result in our paper is that for point sets P in general position, G(del)(P) always contains a matching of size at least vertical bar P vertical bar-1/3] and this bound is tight. We also give some structural properties of G(star)(P) graphs, where is the class which contains both upward and downward equilateral triangles. We show that for point sets in general position, the block cut point graph of G(star)(P) is simply a path. Through the equivalence of G(star)(P) graphs with Theta(6) graphs, we also derive that any Theta(6) graph can have at most 5n-11 edges, for point sets in general position. (C) 2013 Elsevier B.V. All rights reserved.

Decentralized demand-supply matching using community microgrids and consumer demand response: A scenario analysis

Developing countries constantly face the challenge of reliably matching electricity supply to increasing consumer demand. The traditional policy decisions of increasing supply and reducing demand centrally, by building new power plants and/or load shedding, have been insufficient. Locally installed microgrids along with consumer demand response can be suitable decentralized options to augment the centralized grid based systems and plug the demand-supply gap. The objectives of this paper are to: (1) develop a framework to identify the appropriate decentralized energy options for demand supply matching within a community, and, (2) determine which of these options can suitably plug the existing demand-supply gap at varying levels of grid unavailability. A scenario analysis framework is developed to identify and assess the impact of different decentralized energy options at a community level and demonstrated for a typical urban residential community Vijayanagar, Bangalore in India. A combination of LPG based CHP microgrid and proactive demand response by the community is the appropriate option that enables the Vijayanagar community to meet its energy needs 24/7 in a reliable, cost-effective manner. The paper concludes with an enumeration of the barriers and feasible strategies for the implementation of community microgrids in India based on stakeholder inputs. (C) 2014 Elsevier Ltd. All rights reserved.

Logarithmic corrections to twisted indices from the quantum entropy function

We compute logarithmic corrections to the twisted index B-6(g) in four-dimensional N = 4 and N = 8 string theories using the framework of the Quantum Entropy Function. We find that these vanish, matching perfectly with the large-charge expansion of the corresponding microscopic expressions.

Charge Transfer Induces Formation of Stimuli-Responsive, Chiral, Cohesive Vesicles-on-a-String that Eventually Turn into a Hydrogel

A charge transfer (CT) mediated two-component, multistimuli responsive supergelation involving a L-histidine-appended pyrenyl derivative (PyHisOMe) as a donor and an asymmetric bolaamphiphilic naphthalene-diimide (Asym-NDI) derivative as an acceptor in a 2: 1 mixture of H2O/MeOH was investigated. Asym-NDI alone self-assembled into pH-responsive vesicular nanostructures in water. Excellent selectivity in CT gel formation was achieved in terms of choosing amino acid appended pyrenyl donor scaffolds. Circular di-chroism and morphological studies suggested formation of chiral, interconnected vesicular assemblies resembling ``pearls-on-a-string'' from these CT mixed stacks. XRD studies revealed the formation of monolayer lipid membranes from these CT mixed stacks that eventually led to the formation of individual vesicles. Strong cohesive forces among the interconnected vesicles originate from the protrusion of the oxyethylene chains from the surfaces of the chiral vesicles.

Reduced Look Ahead Orthogonal Matching Pursuit

Compressed Sensing (CS) is an elegant technique to acquire signals and reconstruct them efficiently by solving a system of under-determined linear equations. The excitement in this field stems from the fact that we can sample at a rate way below the Nyquist rate and still reconstruct the signal provided some conditions are met. Some of the popular greedy reconstruction algorithms are the Orthogonal Matching Pursuit (OMP), the Subspace Pursuit (SP) and the Look Ahead Orthogonal Matching Pursuit (LAOMP). The LAOMP performs better than the OMP. However, when compared to the SP and the OMP, the computational complexity of LAOMP is higher. We introduce a modified version of the LAOMP termed as Reduced Look Ahead Orthogonal Matching Pursuit (Reduced LAOMP). Reduced LAOMP uses prior information from the results of the OMP and the SP in the quest to speedup the look ahead strategy in the LAOMP. Monte Carlo simulations of this algorithm deliver promising results.

Performance analysis of 1200 kV ceramic disc insulator string under normal and faulted conditions

In the recent years there has been a considerable increase in demand for the electrical power requirement in our country. Presently the transmission system voltages has increased to 765 kV ac and 800kV dc, keeping in view of the future demand experimentation and simulation studies for 1200 kV ac and 1100kV dc transmission are under progress. In the present study an attempt is made to compute the surface potential, electric field across the string of ceramic disc insulators used for 1200kV ac systems. The studies are carried out under normal, polluted conditions and for the case of insulator string containing faulty discs. A computer code using surface charge simulation method (SCSM) is developed for the present analysis. Also a new technique which enhances the surface potential and electric field strength for the existing ceramic disc insulators is presented.

DETERMINISTIC ALGORITHMS FOR MATCHING AND PACKING PROBLEMS BASED ON REPRESENTATIVE SETS

In this work, we study the well-known r-DIMENSIONAL k-MATCHING ((r, k)-DM), and r-SET k-PACKING ((r, k)-SP) problems. Given a universe U := U-1 ... U-r and an r-uniform family F subset of U-1 x ... x U-r, the (r, k)-DM problem asks if F admits a collection of k mutually disjoint sets. Given a universe U and an r-uniform family F subset of 2(U), the (r, k)-SP problem asks if F admits a collection of k mutually disjoint sets. We employ techniques based on dynamic programming and representative families. This leads to a deterministic algorithm with running time O(2.851((r-1)k) .vertical bar F vertical bar. n log(2)n . logW) for the weighted version of (r, k)-DM, where W is the maximum weight in the input, and a deterministic algorithm with running time O(2.851((r-0.5501)k).vertical bar F vertical bar.n log(2) n . logW) for the weighted version of (r, k)-SP. Thus, we significantly improve the previous best known deterministic running times for (r, k)-DM and (r, k)-SP and the previous best known running times for their weighted versions. We rely on structural properties of (r, k)-DM and (r, k)-SP to develop algorithms that are faster than those that can be obtained by a standard use of representative sets. Incorporating the principles of iterative expansion, we obtain a better algorithm for (3, k)-DM, running in time O(2.004(3k).vertical bar F vertical bar . n log(2)n). We believe that this algorithm demonstrates an interesting application of representative families in conjunction with more traditional techniques. Furthermore, we present kernels of size O(e(r)r(k-1)(r) logW) for the weighted versions of (r, k)-DM and (r, k)-SP, improving the previous best known kernels of size O(r!r(k-1)(r) logW) for these problems.