Modified roaming optimization for multi-modal optima

This paper explains the algorithm of Modified Roaming Optimization (MRO) for capturing the multiple optima for multimodal functions. There are some similarities between the Roaming Optimization (RO) and MRO algorithms, but the MRO algorithm is created to overcome the problems facing while applying the RO to the problems possessing large number of solutions. The MRO mainly uses the concept of density to overcome the challenges posed by RO. The algorithm is tested with standard test functions and also discussions are made to improve the efficacy of the MRO algorithm. This paper also gives the results of MRO applied for solving Inverse Kinematics (IK) problem for SCARA and PUMA robots.

Spray: A Multi-Modal Localization System for Stationary Sensor Network Deployment

We present a localization system that targets rapid deployment of stationary wireless sensor networks (WSN). The system uses a particle filter to fuse measurements from multiple localization modalities, such as RF ranging, neighbor information or maps, to obtain position estimations with higher accuracy than that of the individual modalities. The system isolates different modalities into separate components which can be included or excluded independently to tailor the system to a specific scenario. We show that position estimations can be improved with our system by combining multiple modalities. We evaluate the performance of the system in both an indoor and outdoor environment using combinations of five different modalities. Using two anchor nodes as reference points and combining all five modalities, we obtain RMS (Root Mean Square) estimation errors of approximately 2.5m in both cases, while using the components individually results in errors within the range of 3.5 and 9 m.

SPSA Based Feature Relevance Estimation For Video Retrieval

With the availability of a huge amount of video data on various sources, efficient video retrieval tools are increasingly in demand. Video being a multi-modal data, the perceptions of ``relevance'' between the user provided query video (in case of Query-By-Example type of video search) and retrieved video clips are subjective in nature. We present an efficient video retrieval method that takes user's feedback on the relevance of retrieved videos and iteratively reformulates the input query feature vectors (QFV) for improved video retrieval. The QFV reformulation is done by a simple, but powerful feature weight optimization method based on Simultaneous Perturbation Stochastic Approximation (SPSA) technique. A video retrieval system with video indexing, searching and relevance feedback (RF) phases is built for demonstrating the performance of the proposed method. The query and database videos are indexed using the conventional video features like color, texture, etc. However, we use the comprehensive and novel methods of feature representations, and a spatio-temporal distance measure to retrieve the top M videos that are similar to the query. In feedback phase, the user activated iterative on the previously retrieved videos is used to reformulate the QFV weights (measure of importance) that reflect the user's preference, automatically. It is our observation that a few iterations of such feedback are generally sufficient for retrieving the desired video clips. The novel application of SPSA based RF for user-oriented feature weights optimization makes the proposed method to be distinct from the existing ones. The experimental results show that the proposed RF based video retrieval exhibit good performance.

Variable Sparsity Kernel Learning

This paper(1) presents novel algorithms and applications for a particular class of mixed-norm regularization based Multiple Kernel Learning (MKL) formulations. The formulations assume that the given kernels are grouped and employ l(1) norm regularization for promoting sparsity within RKHS norms of each group and l(s), s >= 2 norm regularization for promoting non-sparse combinations across groups. Various sparsity levels in combining the kernels can be achieved by varying the grouping of kernels-hence we name the formulations as Variable Sparsity Kernel Learning (VSKL) formulations. While previous attempts have a non-convex formulation, here we present a convex formulation which admits efficient Mirror-Descent (MD) based solving techniques. The proposed MD based algorithm optimizes over product of simplices and has a computational complexity of O (m(2)n(tot) log n(max)/epsilon(2)) where m is no. training data points, n(max), n(tot) are the maximum no. kernels in any group, total no. kernels respectively and epsilon is the error in approximating the objective. A detailed proof of convergence of the algorithm is also presented. Experimental results show that the VSKL formulations are well-suited for multi-modal learning tasks like object categorization. Results also show that the MD based algorithm outperforms state-of-the-art MKL solvers in terms of computational efficiency.

Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

Wave propagation in multi-walled carbon nanotube

In this paper, wave propagation in multi-walled carbon nanotubes (MWNTs) are studied by modeling them as continuum multiple shell coupled through van der Waals force of interaction. The displacements, namely, axial, radial and circumferential displacements vary along the circumferential direction. The wave propagation are simulated using the wavelet based spectral finite element (WSFE) method. This technique involves Daubechies scaling function approximation in time and spectral element approach. The WSFE Method allows the study of wave properties in both time and frequency domains. This is in contrast to the conventional Fourier transform based analysis which are restricted to frequency domain analysis. Here, first, the wavenumbers and wave speeds of carbon nanotubes (CNTs) are Studied to obtain the characteristics of the waves. These group speeds have been compared with those reported in literature. Next, the natural frequencies of a single-walled carbon nanotube (SWNT) are studied for different values of the radius. The frequencies of the first five modes vary linearly with the radius of the SWNT. Finally, the time domain responses are simulated for SWNT and three-walled carbon nanotubes.

Theory of Non-linear Waves in Multi-dimensions: with Special Reference to Surface Water Waves

The surface water waves are "modal" waves in which the "physical space" (t, x, y, z) is the product of a propagation space (t, x, y) and a cross space, the z-axis in the vertical direction. We have derived a new set of equations for the long waves in shallow water in the propagation space. When the ratio of the amplitude of the disturbance to the depth of the water is small, these equations reduce to the equations derived by Whitham (1967) by the variational principle. Then we have derived a single equation in (t, x, y)-space which is a generalization of the fourth order Boussinesq equation for one-dimensional waves. In the neighbourhood of a wave froat, this equation reduces to the multidimensional generalization of the KdV equation derived by Shen & Keller (1973). We have also included a systematic discussion of the orders of the various non-dimensional parameters. This is followed by a presentation of a general theory of approximating a system of quasi-linear equations following one of the modes. When we apply this general method to the surface water wave equations in the propagation space, we get the Shen-Keller equation.

Recognition of Interaction Interface Residues in Low-Resolution Structures of Protein Assemblies Solely from the Positions of C alpha Atoms

Background: The number of available structures of large multi-protein assemblies is quite small. Such structures provide phenomenal insights on the organization, mechanism of formation and functional properties of the assembly. Hence detailed analysis of such structures is highly rewarding. However, the common problem in such analyses is the low resolution of these structures. In the recent times a number of attempts that combine low resolution cryo-EM data with higher resolution structures determined using X-ray analysis or NMR or generated using comparative modeling have been reported. Even in such attempts the best result one arrives at is the very course idea about the assembly structure in terms of trace of the C alpha atoms which are modeled with modest accuracy. Methodology/Principal Findings: In this paper first we present an objective approach to identify potentially solvent exposed and buried residues solely from the position of C alpha atoms and amino acid sequence using residue type-dependent thresholds for accessible surface areas of C alpha. We extend the method further to recognize potential protein-protein interface residues. Conclusion/Significance: Our approach to identify buried and exposed residues solely from the positions of C alpha atoms resulted in an accuracy of 84%, sensitivity of 83-89% and specificity of 67-94% while recognition of interfacial residues corresponded to an accuracy of 94%, sensitivity of 70-96% and specificity of 58-94%. Interestingly, detailed analysis of cases of mismatch between recognition of interface residues from C alpha positions and all-atom models suggested that, recognition of interfacial residues using C alpha atoms only correspond better with intuitive notion of what is an interfacial residue. Our method should be useful in the objective analysis of structures of protein assemblies when positions of only C alpha positions are available as, for example, in the cases of integration of cryo-EM data and high resolution structures of the components of the assembly.

Efficient computation of volume fractions for multi-material cell complexes in a grid by slicing

The paper presents a novel slicing based method for computation of volume fractions in multi-material solids given as a B-rep whose faces are triangulated and shared by either one or two materials. Such objects occur naturally in geoscience applications and the said computation is necessary for property estimation problems and iterative forward modeling. Each facet in the model is cut by the planes delineating the given grid structure or grid cells. The method, instead of classifying the points or cells with respect to the solid, exploits the convexity of triangles and the simple axis-oriented disposition of the cutting surfaces to construct a novel intermediate space enumeration representation called slice-representation, from which both the cell containment test and the volume-fraction computation are done easily. Cartesian and cylindrical grids with uniform and non-uniform spacings have been dealt with in this paper. After slicing, each triangle contributes polygonal facets, with potential elliptical edges, to the grid cells through which it passes. The volume fractions of different materials in a grid cell that is in interaction with the material interfaces are obtained by accumulating the volume contributions computed from each facet in the grid cell. The method is fast, accurate, robust and memory efficient. Examples illustrating the method and performance are included in the paper.

Tribology of steel/steel interaction in oil-in-water mulsion; a rationale for lubricity

Oil droplets are dispersed in water by an anionic urfactant to form an emulsion. The lubricity of this emulsion in steel/steel interaction is explored in a ball on flat nanotribometer. The droplet size and charge are measured using dynamic light scattering, while the substrate charge density is estimated using the pH titration method. These data are combined to calculate the DLVO forces for the droplets generated for a range of surfactant concentration and two oil to water volume ratios. The droplets have a clear bi-modal size distribution. The study shows that the smaller droplets which experience weak repulsion are situated (at the highest DLVO barrier) much closer to the substrate than thebigger droplets, which experience the same DLVO force, are. We suggest that the smaller droplets thus play a more important role in lubricity than what the bigger droplets do. The largest volume of such small droplets occurs in the 0.5 mM-1 mM range of surfactant concentration and 1% oil to water volume ratio, where the coefficient of friction is also observed to be the least. (C) 2010 Elsevier Inc. All rights reserved.

Thermodynamic consistency of the interaction parameter formalism

The apparent contradiction between the exact nature of the interaction parameter formalism as presented by Lupis and Elliott and the inconsistencies discussed recently by Pelton and Bale arise from the truncation of the Maclaurin series in the latter treatment. The truncation removes the exactness of the expression for the logarithm of the activity coefficient of a solute in a multi-component system. The integrals are therefore path dependent. Formulae for integration along paths of constant Xi,or X i/Xj are presented. The expression for In γsolvent given by Pelton and Bale is valid only in the limit that the mole fraction of solvent tends to one. The truncation also destroys the general relations between interaction parameters derived by Lupis and Elliott. For each specific choice of parameters special relationships are obtained between interaction parameters.

Representation of Thermodynamic Properties of Dilute Multi-Component Solutions--Options and Constraints

The different formalisms for the representation of thermodynamic data on dilute multicomponent solutions are critically reviewed. The thermodynamic consistency of the formalisms are examined and the interrelations between them are highlighted. The options are constraints in the use of the interaction parameter and Darken's quadratic formalisms for multicomponent solutions are discussed in the light of the available experimental data. Truncatred Maclaurin series expansion is thermodynamically inconsistent unless special relations between interaction parameters are invoked. However, the lack of strict mathematical consistency does not affect the practical use of the formalism. Expressions for excess partial properties can be integrated along defined composition paths without significant loss of accuracy. Although thermodynamically consistent, the applicability of Darken's quadratic formalism to strongly interacting systems remains to be established by experiment.

Mutations in beta ` subunit of Escherichia coli RNA polymerase perturb the activator polymerase functional interaction required for promoter clearance

P>Transcription activator C employs a unique mechanism to activate mom gene of bacteriophage Mu. The activation process involves, facilitating the recruitment of RNA polymerase (RNAP) by altering the topology of the promoter and enhancing the promoter clearance by reducing the abortive transcription. To understand the basis of this multi-step activation mechanism, we investigated the nature of the physical interaction between C and RNAP during the process. A variety of assays revealed that only DNA-bound C contacts the beta' subunit of RNAP. Consistent to these results, we have also isolated RNAP mutants having mutations in the beta' subunit which were compromised in C-mediated activation. Mutant RNAPs show reduced productive transcription and increased abortive initiation specifically at the C-dependent mom promoter. Positive control (pc) mutants of C, defective in interaction with RNAP, retained the property of recruiting RNAP to the promoter but were unable to enhance promoter clearance. These results strongly suggest that the recruitment of RNAP to the mom promoter does not require physical interaction with C, whereas a contact between the beta' subunit and the activator, and the subsequent allosteric changes in the active site of the enzyme are essential for the enhancement of promoter clearance.

Influence of the Methane-Zeolite A Interaction Potential on the Concentration Dependence of Self-diffusivity

Studies on the diffusion of methane in a zeolite structure type LTA (as per IZA nomenclature) have indicated that different types of methane zeolite potentials exist in the literature in which methane is treated within the united-atom model. One set of potentials, referred to as model A, has a methane oxygen diameter of 3.14 angstrom, while another set of potential parameters, model B, employs a larger value of 3.46 angstrom. Fritzsche and co-workers (1993) have shown that these two potentials lead to two distinctly different energetic barriers for the passage of methane through the eight-ring window in the cation-free form of zeolite A. Here, we compute the variation of the self-diffusivity (D) with loading (c) for these two types of potentials and show that this slight variation in the diameter changes the concentration dependence qualitatively: thus, D decreases monotonically with c for model A, while D increases and goes through a maximum before finally decreasing for model B. This effect and the surprising congruence of the diffusion coefficients for both models at high loadings is examined in detail at the molecular level. Simulations for different temperatures reveal the Arrhenius behaviour of the self-diffusion coefficient. The apparent activation energy is found to vary with the loading. We conclude that beside the cage-to-cage jumps, which are essential for the migration of the guest molecules, at high concentrations migration within the cage and guest guest interactions with other molecules become increasingly dominant influences on the diffusion coefficient and make the guest zeolite interaction less important for both model A and model B.

Spray characterization of gasoline-ethanol blends from a multi-hole port fuel injector

This work reports the measured spray structure and droplet size distributions of ethanol-gasoline blends for a low-pressure, multi-hole, port fuel injector (PFI). This study presents previously unavailable data for this class of injectors which are widely used in automotive applications. Specifically, gasoline, ethanol, and gasoline-ethanol blends containing 10%, 20% and 50% ethanol were studied using laser backlight imaging, and particle/droplet image analysis (PDIA) techniques. The fuel mass injected, spray structure and tip penetrations, droplet size distributions, and Sauter mean diameter were determined for the blends, at two different injection pressures. Results indicate that the gasoline and ethanol sprays have similar characteristics in terms of spray progression and droplet sizes in spite of the large difference in viscosity. It appears that the complex mode of atomization utilized in these injectors involving interaction of multiple fuel jets is fairly insensitive to the fuel viscosity over a range of values. This result has interesting ramifications for existing gasoline fuel systems which need to handle blends and even pure ethanol, which is one of the renewable fuels of the future. (C) 2012 Elsevier Ltd. All rights reserved.