Flat connections, geometric invariants and energy of harmonic functions on compact Riemann surfaces

A geometric invariant is associated to the space of fiat connections on a G-bundle over a compact Riemann surface and is related to the energy of harmonic functions.

The goals of cognitive science

In this paper cognitive science is defined as the study of intelligence as a computational process. The several disciplines which contribute to the study of cognitive science are briefly described so as to glean a birds-eye view of the subject of cognitive science.

Generation of an eight node brick element using Papcovitch-Neuber functions

Some conventional finite elements suffer from drawbacks, such as shear locking, membrane locking, etc. To overcome them researchers have developed various techniques, termed as tricks by some and variational crimes by others. Many attempts have been made, but satisfactory explanations for why some of these techniques work have not been obtained, especially in the case of solid elements. This paper attempts a simple non-conforming solid element using assumed displacement fields which satisfy the Navier equation exactly. Its behaviour under simple loadings like bending, torsion and tension is examined and comparisons are made with existing elements.

Uniform algebras generated by holomorphic and close-to-harmonic functions

The initial motivation for this paper is to discuss a more concrete approach to an approximation theorem of Axler and Shields, which says that the uniform algebra on the closed unit disc (D) over bar generated by z and h, where h is a nowhere-holomorphic harmonic function on D that is continuous up to partial derivative D, equals C((D) over bar). The abstract tools used by Axler and Shields make harmonicity of h an essential condition for their result. We use the concepts of plurisubharmonicity and polynomial convexity to show that, in fact, the same conclusion is reached if h is replaced by h + R, where R is a non-harmonic perturbation whose Laplacian is ``small'' in a certain sense.

Violin string shape functions for finite element analysis of rotating Timoshenko beams

Violin strings are relatively short and stiff and are well modeled by Timoshenko beam theory. We use the static part of the homogeneous differential equation of violin strings to obtain new shape functions for the finite element analysis of rotating Timoshenko beams. For deriving the shape functions, the rotating beam is considered as a sequence of violin strings. The violin string shape functions depend on rotation speed and element position along the beam length and account for centrifugal stiffening effects as well as rotary inertia and shear deformation on dynamic characteristics of rotating Timoshenko beams. Numerical results show that the violin string basis functions perform much better than the conventional polynomials at high rotation speeds and are thus useful for turbo machine applications. (C) 2011 Elsevier B.V. All rights reserved.

The effect of temperature on the surface tension and adsorption functions of the Fe-S-O melts - an analysis based on interaction parameters

The present investigation analyses the thermodynamic behaviour of the surfaces and adsorption as a function of temperature and composition in the Fe-S-O melts based on the Butler's equations. The calculated-values of the surface tensions exhibit an elevation or depression depending on the type of the added solute at a concentration which coincides with that already present in the system. Generally, the desorption of the solutes as a function of temperature results in an initial increase followed by a decrease in the values of the surface tension. The observations are analyzed based on the surface interaction parameters which are derived in the present research.

Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions

In this paper we consider the problem of learning an n × n kernel matrix from m(1) similarity matrices under general convex loss. Past research have extensively studied the m = 1 case and have derived several algorithms which require sophisticated techniques like ACCP, SOCP, etc. The existing algorithms do not apply if one uses arbitrary losses and often can not handle m > 1 case. We present several provably convergent iterative algorithms, where each iteration requires either an SVM or a Multiple Kernel Learning (MKL) solver for m > 1 case. One of the major contributions of the paper is to extend the well knownMirror Descent(MD) framework to handle Cartesian product of psd matrices. This novel extension leads to an algorithm, called EMKL, which solves the problem in O(m2 log n 2) iterations; in each iteration one solves an MKL involving m kernels and m eigen-decomposition of n × n matrices. By suitably defining a restriction on the objective function, a faster version of EMKL is proposed, called REKL,which avoids the eigen-decomposition. An alternative to both EMKL and REKL is also suggested which requires only an SVMsolver. Experimental results on real world protein data set involving several similarity matrices illustrate the efficacy of the proposed algorithms.

Exact spectral functions of a non-Fermi liquid in one dimension

We study the exact one-electron propagator and spectral function of a solvable model of interacting electrons due to Schulz and Shastry. The solution previously found for the energies and wave functions is extended to give spectral functions that turn out to be computable, interesting, and nontrivial. They provide one of the few examples of cases where the spectral functions are known asymptotically as well as exactly.

Quadratic Lyapunov functions for linear systems Journal

The paper deals with the existence of a quadratic Lyapunov function V = x′P(t)x for an exponentially stable linear system with varying coefficients described by the vector differential equation S0305004100044777_inline1 The derivative dV/dt is allowed to be strictly semi-(F) and the locus dV/dt = 0 does not contain any arc of the system trajectory. It is then shown that the coefficient matrix A(t) of the exponentially stable sy

Acquisition time improvement of PLLs using some aiding functions

Analytical studies are carried out to minimize acquisition time in phase-lock loop (PLL) applications using aiding functions. A second order aided PLL is realized with the help of the quasi-stationary approach to verify the acquisition behavior in the absence of noise. Time acquisition is measured both from the study of the LPF output transient and by employing a lock detecting and indicating circuit to crosscheck experimental and analytical results. A closed form solution is obtained for the evaluation of the time acquisition using different aiding functions. The aiding signal is simple and economical and can be used with state of the art hardware.