Variance-Reduced Particle Filters for Structural System Identification Problems

A few variance reduction schemes are proposed within the broad framework of a particle filter as applied to the problem of structural system identification. Whereas the first scheme uses a directional descent step, possibly of the Newton or quasi-Newton type, within the prediction stage of the filter, the second relies on replacing the more conventional Monte Carlo simulation involving pseudorandom sequence with one using quasi-random sequences along with a Brownian bridge discretization while representing the process noise terms. As evidenced through the derivations and subsequent numerical work on the identification of a shear frame, the combined effect of the proposed approaches in yielding variance-reduced estimates of the model parameters appears to be quite noticeable. DOI: 10.1061/(ASCE)EM.1943-7889.0000480. (C) 2013 American Society of Civil Engineers.

Motion segmentation using curve fitting on Lagrangian particle trajectories

In this paper we present a segmentation algorithm to extract foreground object motion in a moving camera scenario without any preprocessing step such as tracking selected features, video alignment, or foreground segmentation. By viewing it as a curve fitting problem on advected particle trajectories, we use RANSAC to find the polynomial that best fits the camera motion and identify all trajectories that correspond to the camera motion. The remaining trajectories are those due to the foreground motion. By using the superposition principle, we subtract the motion due to camera from foreground trajectories and obtain the true object-induced trajectories. We show that our method performs on par with state-of-the-art technique, with an execution time speed-up of 10x-40x. We compare the results on real-world datasets such as UCF-ARG, UCF Sports and Liris-HARL. We further show that it can be used toper-form video alignment.

Determination of favorable inter-particle interactions for formation of substitutionally ordered solid phases from a binary mixture of oppositely charged colloidal suspensions

The solid phase formed by a binary mixture of oppositely charged colloidal particles can be either substitutionally ordered or substitutionally disordered depending on the nature and strength of interactions among the particles. In this work, we use Monte Carlo molecular simulations along with the Gibbs-Duhem integration technique to map out the favorable inter-particle interactions for the formation of substitutionally ordered crystalline phases from a fluid phase. The inter-particle interactions are modeled using the hard core Yukawa potential but the method can be easily extended to other systems of interest. The study obtains a map of interactions depicting regions indicating the type of the crystalline aggregate that forms upon phase transition.

A peer-peer particle swarm optimizer

Particle Swarm Optimization is a parallel algorithm that spawns particles across a search space searching for an optimized solution. Though inherently parallel, they have distinct synchronizations points which stumbles attempts to create completely distributed versions of it. In this paper, we attempt to create a completely distributed peer-peer particle swarm optimization in a cluster of heterogeneous nodes. Since, the original algorithm requires explicit synchronization points we modified the algorithm in multiple ways to support a peer-peer system of nodes. We also modify certain aspect of the basic PSO algorithm and show how certain numerical problems can take advantage of the same thereby yielding fast convergence.

Feature weighting for clustering by particle swarm optimization

Clustering has been the most popular method for data exploration. Clustering is partitioning the data set into sub-partitions based on some measures say the distance measure, each partition has its own significant information. There are a number of algorithms explored for this purpose, one such algorithm is the Particle Swarm Optimization(PSO) which is a population based heuristic search technique derived from swarm intelligence. In this paper we present an improved version of the Particle Swarm Optimization where, each feature of the data set is given significance accordingly by adding some random weights, which also minimizes the distortions in the dataset if any. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The experimental results shows that our proposed methodology performs significantly better than the previously performed experiments.

Multiobjective discrete particle swarm optimization for multisensor image alignment

A new technique is proposed for multisensor image registration by matching the features using discrete particle swarm optimization (DPSO). The feature points are first extracted from the reference and sensed image using improved Harris corner detector available in the literature. From the extracted corner points, DPSO finds the three corresponding points in the sensed and reference images using multiobjective optimization of distance and angle conditions through objective switching technique. By this, the global best matched points are obtained which are used to evaluate the affine transformation for the sensed image. The performance of the image registration is evaluated and concluded that the proposed approach is efficient.

Modified particle swarm optimization for pattern clustering

Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning and data mining. Clustering is grouping of a data set or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait according to some defined distance measure. In this paper we present the genetically improved version of particle swarm optimization algorithm which is a population based heuristic search technique derived from the analysis of the particle swarm intelligence and the concepts of genetic algorithms (GA). The algorithm combines the concepts of PSO such as velocity and position update rules together with the concepts of GA such as selection, crossover and mutation. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The performance of our method is better than k-means and PSO algorithm.

Simultaneous feature selection and clustering using particle swarm optimization

Data clustering groups data so that data which are similar to each other are in the same group and data which are dissimilar to each other are in different groups. Since generally clustering is a subjective activity, it is possible to get different clusterings of the same data depending on the need. This paper attempts to find the best clustering of the data by first carrying out feature selection and using only the selected features, for clustering. A PSO (Particle Swarm Optimization)has been used for clustering but feature selection has also been carried out simultaneously. The performance of the above proposed algorithm is evaluated on some benchmark data sets. The experimental results shows the proposed methodology outperforms the previous approaches such as basic PSO and Kmeans for the clustering problem.

Cooperative Particle Swarm Optimization Based Receiver for Large-Dimension MIMO-ZPSC Systems

In this paper, we propose a cooperative particle swarm optimization (CPSO) based channel estimation/equalization scheme for multiple-input multiple-output zero-padded single-carrier (MIMO-ZPSC) systems with large dimensions in frequency selective channels. We estimate the channel state information at the receiver in time domain using a PSO based algorithm during training phase. Using the estimated channel, we perform information symbol detection in the frequency domain using FFT based processing. For this detection, we use a low complexity OLA (OverLap Add) likelihood ascent search equalizer which uses minimum mean square (MMSE) equalizer solution as the initial solution. Multiple iterations between channel estimation and data detection are carried out which significantly improves the mean square error and bit error rate performance of the receiver.

Chromium isotope variations (delta Cr-53/52) in mantle-derived sources and their weathering products: Implications for environmental studies and the evolution of delta Cr-53/52 in the Earth's mantle over geologic time

Here we report chromium isotope compositions, expressed as delta Cr-53/ 52 in per mil (&) relative to NIST 979, measured in selected Cr-rich minerals and rocks formed by the primary magmatic as well as the secondary metamorphic and weathering processes. The main objectives of this study were: (i) to further constrain the isotope composition of the Earth's mantle Cr inventory and its possible variation during geological history, based on the analysis of globally distributed and stratigraphically constrained mantle-derived chromites; and (ii) to investigate the magnitude and systematics of Cr isotope fractionation during oxidative weathering and secondary alteration (i. e., hydration, serpentinization) of the magmatic Cr sources. Specifically, we analyzed delta Cr-53/ 52 in a set of globally distributed mantle-derived chromites (FeMgCr2O4, n = 30) collected from various locations in Europe, Asia, Africa and South America, and our results confirm that a chromite-hosted Earth's mantle Cr inventory is uniform at - 0.079 +/- 0.129& (2SD), which we named here as a ` canonical' mantle d 53/ 52 Cr signature. Furthermore our dataset of stratigraphically constrained chromites, whose crystallization ages cover most of the Earth's geological history, indicate that the bulk Cr isotope composition of the chromite-hosted mantle inventory has remained uniform, within about +/- 0.100&, since at least the Early Archean times (similar to 3500 million years ago, Ma). To investigate the systematics of Cr isotope fractionation associated with alteration processes we analyzed a number of secondary Cr-rich minerals and variably altered ultramafic rocks (i. e., serpentinized harzburgites, lherzolites) that revealed large positive delta Cr-53/ 52 anomalies that are systematically shifted to higher values with an increasing degree of alteration and serpentinization. The degree of aqueous alteration and serpentinization was quantified by the abundances of fluid-mobile (Rb, K) elements, and by the Loss On Ignition (LOI) parameter, which determines the amount of structurally bound water (OH/ H2O) present in secondary hydrated minerals like serpentine. Overall, we observed that altered ultramafic rocks that yielded the highest LOI values, and the lowest amounts of fluid mobile elements, also yielded the heaviest delta Cr-53/ 52 signatures. Therefore, we conclude that secondary alteration (i.e., hydration, serpentinization) of ultramafic rocks in near-surface oxidative environments tend to shift the bulk Cr isotope composition of the weathered products to isotopically heavier values, pointing to a dynamic redox cycling of Cr in the Earth's crustal and near-surface environments. Hence, if validated by future

Environments of extended radio sources in the Australia Telescope Low-Brightness Survey

We present a study of the environments of extended radio sources in the Australia Telescope Low-Brightness Survey (ATLBS). The radio sources were selected from the ATLBS Extended Source Sample, which is a well defined sample containing the most extended of radio sources in the ATLBS sky survey regions. The environments were analysed using 4-m Cerro-Tololo Inter-American Observatory Blanco telescope observations carried out for ATLBS fields in the Sloan Digital Sky Survey r(') band. We have estimated the properties of the environments using smoothed density maps derived from galaxy catalogues constructed using these optical imaging data. The angular distribution of galaxy density relative to the axes of the radio sources has been quantified by defining anisotropy parameters that are estimated using a new method presented here. Examining the anisotropy parameters for a subsample of extended double radio sources that includes all sources with pronounced asymmetry in lobe extents, we find good evidence for environmental anisotropy being the dominant cause for lobe asymmetry in that higher galaxy density occurs almost always on the side of the shorter lobe, and this validates the usefulness of the method proposed and adopted here. The environmental anisotropy parameters have been used to examine and compare the environments of Fanaroff-Riley Class I (FRI) and Fanaroff-Riley Class II (FRII) radio sources in two redshift regimes (z < 0.5 and z > 0.5). Wide-angle tail sources and head-tail sources lie in the most overdense environments. The head-tail source environments (for the HT sources in our sample) display dipolar anisotropy in that higher galaxy density appears to lie in the direction of the tails. Excluding the head-tail and wide-angle tail sources, subsamples of FRI and FRII sources from the ATLBS appear to lie in similar moderately overdense environments, with no evidence for redshift evolution in the regimes studied herein.

Particle size, morphology and color tunable ZnO:Eu3+ nanophosphors via plant latex mediated green combustion synthesis

Efficient ZnO:Eu3+ (1-11 mol%) nanophosphors were prepared for the first time by green synthesis route using Euphorbia tirucalli plant latex. The final products were well characterized by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-visible spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), etc. The average particle size of ZnO:Eu3+ (7 mol%) was found to be in the range 27-47 nm. With increase of plant latex, the particle size was reduced and porous structure was converted to spherical shaped particles. Photoluminescence (PL) spectra indicated that the peaks situated at similar to 590, 615, 648 and 702 nm were attributed to the D-5(0) -> F-7(j(j=1,2,3,4)) transitions of Eu3+ ions. The highest PL intensity was recorded for 7 mol% with Eu3+ ions and 26 ml plant latex concentration. The PL intensity increases with increase of plant latex concentration up to 30 ml and there after it decreases. The phosphor prepared by this method show spherical shaped particles, excellent chromaticity co-ordinates in the white light region which was highly useful for WLED's. Further, present method was reliable, environmentally friendly and alternative to economical routes. (c) 2013 Elsevier B.V. All rights reserved.

Recrystallization and Ag3Sn Particle Redistribution During Thermomechanical Treatment of Bulk Sn-Ag-Cu Solder Alloys

Sn-Ag-Cu (SAC) solders are susceptible to appreciable microstructural coarsening during storage or service. This results in evolution of joint properties over time and thereby influences the long-term reliability of microelectronic packages. Accurate reliability prediction of SAC solders requires prediction of microstructural evolution during service. Microstructure evolution in two SAC solder alloys, such as, Sn-3.0Ag-0.5Cu (SAC 305) and Sn-1.0Ag-0.5 Cu (SAC 105), under different thermomechanical excursions, including isothermal aging at 150 degrees C and thermomechanical cycling (TMC) was studied. In general, between 200 and 600 cycles during TMC, recrystallization of the Sn matrix was observed, along with redistribution of Ag3Sn particles because of dissolution and reprecipitation. These latter effects have not been reported before. It was also observed that the Sn grains recrystallized near precipitate clusters in eutectic channels during extended isothermal aging. The relative orientation of Sn grains in proeutectic colonies did not change during isothermal aging.

Large deviation function and fluctuation theorem for classical particle transport

We analytically evaluate the large deviation function in a simple model of classical particle transfer between two reservoirs. We illustrate how the asymptotic long-time regime is reached starting from a special propagating initial condition. We show that the steady-state fluctuation theorem holds provided that the distribution of the particle number decays faster than an exponential, implying analyticity of the generating function and a discrete spectrum for its evolution operator.

Effect of nanoscale boron carbide particle addition on the microstructural evolution and mechanical response of pure magnesium

In this study, the effect of nano-B4C addition on the microstructural and the mechanical behavior of pure Mg are investigated. Pure Mg-metal reinforced with different amounts of nano-size B4C particulates were synthesized using the disintegrated melt deposition technique followed by hot extrusion. Microstructural characterization of the developed Mg/x-B4C composites revealed uniform distribution of nano-B4C particulates and significant grain refinement. Electron back scattered diffraction (EBSD) analyses showed presence of relatively more recrystallized grains and absence of fiber texture in Mg/B4C nanocomposites when compared to pure Mg. The evaluation of mechanical properties indicated a significant improvement in tensile properties of the composites. The significant improvement in tensile ductility (similar to 180% increase with respect to pure Mg) is among the highest observed when compared to the pure Mg based nanocomposites existing in the current literature. The superior mechanical properties of the Mg/B4C nanocomposites are attributed to the uniform distribution of the nanoparticles and the tendency for texture randomization (absence of fiber texture) achieved due to the nano-B4C addition. (C) 2013 Elsevier Ltd. All rights reserved.