GAP-RBF based NR image quality measurement for JPEG coded images

In this paper, we present a growing and pruning radial basis function based no-reference (NR) image quality model for JPEG-coded images. The quality of the images are estimated without referring to their original images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity factors such as edge amplitude, edge length, background activity and background luminance. Image quality estimation involves computation of functional relationship between HVS features and subjective test scores. Here, the problem of quality estimation is transformed to a function approximation problem and solved using GAP-RBF network. GAP-RBF network uses sequential learning algorithm to approximate the functional relationship. The computational complexity and memory requirement are less in GAP-RBF algorithm compared to other batch learning algorithms. Also, the GAP-RBF algorithm finds a compact image quality model and does not require retraining when the new image samples are presented. Experimental results prove that the GAP-RBF image quality model does emulate the mean opinion score (MOS). The subjective test results of the proposed metric are compared with JPEG no-reference image quality index as well as full-reference structural similarity image quality index and it is observed to outperform both.

Gas turbine diagnostics using a soft computing approach

A fuzzy system is developed using a linearized performance model of the gas turbine engine for performing gas turbine fault isolation from noisy measurements. By using a priori information about measurement uncertainties and through design variable linking, the design of the fuzzy system is posed as an optimization problem with low number of design variables which can be solved using the genetic algorithm in considerably low amount of computer time. The faults modeled are module faults in five modules: fan, low pressure compressor, high pressure compressor, high pressure turbine and low pressure turbine. The measurements used are deviations in exhaust gas temperature, low rotor speed, high rotor speed and fuel flow from a base line 'good engine'. The genetic fuzzy system (GFS) allows rapid development of the rule base if the fault signatures and measurement uncertainties change which happens for different engines and airlines. In addition, the genetic fuzzy system reduces the human effort needed in the trial and error process used to design the fuzzy system and makes the development of such a system easier and faster. A radial basis function neural network (RBFNN) is also used to preprocess the measurements before fault isolation. The RBFNN shows significant noise reduction and when combined with the GFS leads to a diagnostic system that is highly robust to the presence of noise in data. Showing the advantage of using a soft computing approach for gas turbine diagnostics.

Study of the growth of capped ZnO nanocrystals: A route to rational synthesis

We report the study of complex and unexpected dependencies of nanocrystal size as well as nanocrystalsize distribution on various reaction parameters in the synthesis of ZnO nanocrystals using poly(vinyl pyrollidone) (PVP) as a capping agent. This method establishes a qualitatively different growth mechanism to the anticipated Ostwald ripening behavior. The study of size-distribution kinetics and an understanding of the observed non-monotonic behaviors provides a route to rational synthesis. We used a simple, but accurate, approach to estimate the size-distribution function of nanocrystals from the UV-absorption spectrum. Our results demonstrate the accuracy and generality of this approach, and we also illustrate its application to various semiconducting nanocrystals, such as ZnO, ZnS, and CdSe, over a wide size range (1.8-5.3 nm).

Voltage and Temperature Aware Statistical Leakage Analysis Framework Using Artificial Neural Networks

Artificial neural networks (ANNs) have shown great promise in modeling circuit parameters for computer aided design applications. Leakage currents, which depend on process parameters, supply voltage and temperature can be modeled accurately with ANNs. However, the complex nature of the ANN model, with the standard sigmoidal activation functions, does not allow analytical expressions for its mean and variance. We propose the use of a new activation function that allows us to derive an analytical expression for the mean and a semi-analytical expression for the variance of the ANN-based leakage model. To the best of our knowledge this is the first result in this direction. Our neural network model also includes the voltage and temperature as input parameters, thereby enabling voltage and temperature aware statistical leakage analysis (SLA). All existing SLA frameworks are closely tied to the exponential polynomial leakage model and hence fail to work with sophisticated ANN models. In this paper, we also set up an SLA framework that can efficiently work with these ANN models. Results show that the cumulative distribution function of leakage current of ISCAS'85 circuits can be predicted accurately with the error in mean and standard deviation, compared to Monte Carlo-based simulations, being less than 1% and 2% respectively across a range of voltage and temperature values.

An efficient reduction algorithm for computation of interconnect delay variability for statistical timing analysis in clock tree planning

In this paper, we propose a novel and efficient algorithm for modelling sub-65 nm clock interconnect-networks in the presence of process variation. We develop a method for delay analysis of interconnects considering the impact of Gaussian metal process variations. The resistance and capacitance of a distributed RC line are expressed as correlated Gaussian random variables which are then used to compute the standard deviation of delay Probability Distribution Function (PDF) at all nodes in the interconnect network. Main objective is to find delay PDF at a cheaper cost. Convergence of this approach is in probability distribution but not in mean of delay. We validate our approach against SPICE based Monte Carlo simulations while the current method entails significantly lower computational cost.

Complexation of siRNA with Dendrimer: A Molecular Modeling Approach

This paper reports the structural behavior and thermodynamics of the complexation of siRNA with poly(amidoamine) (PAMAM) dendrimers of generation 3 (G3) and 4 (G4) through fully atomistic molecular dynamics (MD) simulations accompanied by free energy calculations and inherent structure determination. We have also done simulation with one siRNA and two dendrimers (2 x G3 or 2xG4) to get the microscopic picture of various binding modes. Our simulation results reveal the formation of stable siRNA-dendrimer complex over nanosecond time scale. With the increase in dendrimcr generation, the charge ratio increases and hence the binding energy between siRNA and dendrimer also increases in accordance with available experimental measurements. Calculated radial distribution functions of amines groups of various subgenerations in a given generation of dendrimer and phosphate in backbone of siRNA reveals that one dendrimer of generation 4 shows better binding with siRNA almost wrapping the dendrimer when compared to the binding with lower generation dendrimer like G3. In contrast, two dendrimers of generation 4 show binding without siRNA wrapping the den-rimer because of repulsion between two dendrimers. The counterion distribution around the complex and the water molecules in the hydration shell of siRNA give microscopic picture of the binding dynamics. We see a clear correlation between water. counterions motions and the complexation i.e. the water molecules and counterions which condensed around siRNA are moved away from the siRNA backbone when dendrimer start binding to the siRNA back hone. As siRNA wraps/bind to the dendrimer counterions originally condensed onto siRNA (Na-1) and dendrimer (Cl-) get released. We give a quantitative estimate of the entropy of counterions and show that there is gain in entropy due to counterions release during the complexation. Furthermore, the free energy of complexation of IG3 and IG4 at two different salt concentrations shows that increase in salt concentration leads to the weakening of the binding affinity of siRNA and dendrimer.

Spiral states in the square-lattice Hubbard model

We present a variety of physical implications of a mean-field theory for spiral spin-density-wave states in the square-lattice Hubbard model for small deviations from half filling. The phase diagram with the paramagnetic metal, two spiral (semimetallic) states, and ferromagnet is calculated. The momentum distribution function and the (quasiparticle) density of states are discussed. There is a significant broadening of the quasiparticle bands when the antiferromagnetic insulator is doped. The evolution of the Fermi surface and the variation of the plasma frequency and a charge-stiffness constant with U/t and δ are calculated. The connection to results based on the Schwinger-boson-slave-fermion formalism is made.

On a Ratio of Functions of Exponential Random Variables and Some Applications

Consider L independent and identically distributed exponential random variables (r.vs) X-1, X-2 ,..., X-L and positive scalars b(1), b(2) ,..., b(L). In this letter, we present the probability density function (pdf), cumulative distribution function and the Laplace transform of the pdf of the composite r.v Z = (Sigma(L)(j=1) X-j)(2) / (Sigma(L)(j=1) b(j)X(j)). We show that the r.v Z appears in various communication systems such as i) maximal ratio combining of signals received over multiple channels with mismatched noise variances, ii)M-ary phase-shift keying with spatial diversity and imperfect channel estimation, and iii) coded multi-carrier code-division multiple access reception affected by an unknown narrow-band interference, and the statistics of the r.v Z derived here enable us to carry out the performance analysis of such systems in closed-form.

Incipient motion design of sand bed channels affected by bed suction

Seepage through sand bed channels in a downward direction (suction) reduces the stability of particles and initiates the sand movement. Incipient motion of sand bed channel with seepage cannot be designed by using the conventional approach. Metamodeling techniques, which employ a non-linear pattern analysis between input and output parameters and solely based on the experimental observations, can be used to model such phenomena. Traditional approach to find non-dimensional parameters has not been used in the present work. Parameters, which can influence the incipient motion with seepage, have been identified and non-dimensionalized in the present work. Non-dimensional stream power concept has been used to describe the process. By using these non-dimensional parameters; present work describes a radial basis function (RBF) metamodel for prediction of incipient motion condition affected by seepage. The coefficient of determination, R-2 of the model is 0.99. Thus, it can be said that model predicts the phenomena very well. With the help of the metamodel, design curves have been presented for designing the sand bed channel when it is affected by seepage. (C) 2010 Elsevier B.V. All rights reserved.

A molecular dynamics study of a PbO.SiO2 glass and melt

The structures of a PbO.SiO2 glass and melt have been studied using molecular dynamics simulation employing Born-Mayer-Huggins pair potentials. Various pair distribution functions are presented and discussed. Pb-Pb correlations persist in the melt, in agreement with experimental observations. The calculated and experimental radial distribution functions are compared.

Path integral description of polymers using fractional Brownian walks

The statistical properties of fractional Brownian walks are used to construct a path integral representation of the conformations of polymers with different degrees of bond correlation. We specifically derive an expression for the distribution function of the chains’ end‐to‐end distance, and evaluate it by several independent methods, including direct evaluation of the discrete limit of the path integral, decomposition into normal modes, and solution of a partial differential equation. The distribution function is found to be Gaussian in the spatial coordinates of the monomer positions, as in the random walk description of the chain, but the contour variables, which specify the location of the monomer along the chain backbone, now depend on an index h, the degree of correlation of the fractional Brownian walk. The special case of h=1/2 corresponds to the random walk. In constructing the normal mode picture of the chain, we conjecture the existence of a theorem regarding the zeros of the Bessel function.

Modified conformation and physical properties in conducting polymers due to varying conjugation and solvent interactions

Small angle X-ray scattering (SAXS) studies of poly2-methoxy-5-(2'-ethyl-hexyloxy)-1,4-phenylene vinylene] (MEH-PPV) with varying conjugation, and polyethylene dioxythiophene complexed with polystyrene sulfonate (PEDOT-PSS) in different solvents have shown the importance of the role of pi-electron conjugation and solvent-chain interactions in controlling the chain conformation and assembly. In MEH-PPV, by increasing the extent of conjugation from 30 to 100%, the persistence length (l(p)) increases from 20 to 66 angstrom. Moreover, a pronounced second peak in the pair distribution function has been observed in the fully conjugated chain, at larger length scales. This feature indicates that the chain segments tend to self-assemble as the conjugation along the chain increases. In the case of PEDOT-PSS, the chains undergo solvent induced expansion and enhanced chain organization. The clusters formed by chains are better correlated in dimethyl sulfoxide (DMSO) solution than water, as observed in the scattered intensity profiles. The values of radius of gyration and the exponent (water: 2.6, DMSO: 2.31) of power-law decay, obtained from the unified scattering function (Beaucage) analysis, give evidence for chain expansion from compact (in water) to an extended coil in DMSO solutions, which is consistent with the Kratky plot analysis. The mechanism of this transition and the increase in dc conductivity of PEDOT-PSS in DMSO solution are discussed. The onset frequency for the increase in ac conduction, as well as its temperature dependence, probes the extent of the connectivity in the PEDOT-PSS system. The enhanced charge transport in PEDOT-PSS in DMSO is attributed to the extended chain conformation, as observed in the SAXS results.

Importance of orientational rearrangement during vitrification of hydrocarbons: dependence on molecular shape

On the basis of Monte Carlo calculations of 2,2-dimethylpropane (neopentane), n-pentane, and 2,2-dimethylbutane (neohexane) at several temperatures, thermodynamic properties and radial distribution functions as well as dimerization and bonding energy distribution functions are reported for both liquid and glassy states. Changes in the radial distribution functions on cooling depend on whether the groups are accessible (peripheral) or inaccessible. Peaks in the radial distribution functions corresponding to peripheral groups do not shift to lower distances on cooling and at times display a large increase in the intensity of the first peak. The peaks due to inaccessible groups, on the other hand, shift to lower distances on cooling. The magnitude of the reorientational contribution in determining the resulting structure of the glass is estimated for the different hydrocarbon molecules investigated. The reorientational contribution is highest for neopentane (26%) followed by isopentane (24%), neohexane (22%), and n-pentane (0%). It appears that molecular geometry has an important role in determining the magnitude of the reorientational contribution to the structure of the glass.

Non-Fermi liquid behavior in a mean-field study of the t-J model: Role of zero-point spin fluctuations

We present analytic results to show that the Schwinger-boson hole-fermion mean-field state exhibits non-Fermi liquid behavior due to spin-charge separation. The physical electron Green's function consists of three additive components. (a) A Fermi-liquid component associated with the bose condensate. (b) A non-Fermi liquid component which has a logarithmic peak and a long tail that gives rise to a linear density of states that is symmetric about the Fermi level and a momentum distribution function with a logarithmic discontinuity at the Fermi surface. (c) A second non-Fermi liquid component associated with the thermal bosons which leads to a constant density of states. It is shown that zero-point fluctuations associated with the spin-degrees of freedom are responsible for the logarithmic instabilities and the restoration of particle-hole symmetry close to the Fermi surface.

Sorbate properties of xenon in cloverite: A molecular dynamics study

Molecular dynamics calculations on xenon adsorbed in the cubic cavity of cloverite, a gallophosphate, is presented. Guest-host radial distribution functions, guest-host energy distribution functions, power spectra, and diffusion coefficients for xenon are reported at 397, 494, and 716 K. Results suggest that xenon is highly mobile at 700 K. A shift in the peak position of the power spectra toward lower frequency is observed with increase in temperature. (C) 1994 Academic Press, Inc.