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.

Common-mode filter design for PWM rectifier-based motor drives

A common-mode (CM) filter based on the LCL filter topology is proposed in this paper, which provides a parallel path for ground currents and which also restricts the magnitude of the EMI noise injected into the grid. The CM filter makes use of the components of a line to line LCL filter, which is modified to address the CM voltage with minimal additional components. This leads to a compact filtering solution. The CM voltage of an adjustable speed drive using a PWM rectifier is analyzed for this purpose. The filter design is based on the CM equivalent circuit of the drive system. The filter addresses the adverse effects of the PWM rectifier in an adjustable speed drive. Guidelines are provided on the selection of the filter components. Different variants of the filter topology are evaluated to establish the effectiveness of the proposed circuit. Experimental results based on EMI measurement on the grid side and the CM current measurement on the motor side are presented. These results validate the effectiveness of the filter.

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.

Integrated higher-order pulse-width modulation filter-transformer structure for single-phase static compensator

A power filter is necessary to connect the output of a power converter to the grid so as to reduce the harmonic distortion introduced in the line current and voltage by the power converter. Many a times, a transformer is also present before the point of common coupling. Magnetic components often constitute a significant part of the overall weight, size and cost of the grid interface scheme. So, a compact inexpensive design is desirable. A higher-order LCL-filter and a transformer are increasingly being considered for grid interconnection of the power converter. This study proposes a design method based on a three-winding transformer, that generates an integrated structure that behaves as an LCL-filter, with both the filter inductances and the transformer that are merged into a single electromagnetic component. The parameters of the transformer are derived analytically. It is shown that along with a filter capacitor, the transformer parameters provide the filtering action of an LCL-filter. A single-phase full-bridge power converter is operated as a static compensator for performance evaluation of the integrated filter transformer. A resonant integrator-based single-phase phase locked loop and stationary frame AC current controller are employed for grid frequency synchronisation and line current control, respectively.

Data assimilation using ensemble transform Kalman filter (ETKF) in ROMS model for Indian Ocean

Study of Oceans dynamics and forecast is crucial as it influences the regional climate and other marine activities. Forecasting oceanographic states like sea surface currents, Sea surface temperature (SST) and mixed layer depth at different time scales is extremely important for these activities. These forecasts are generated by various ocean general circulation models (OGCM). One such model is the Regional Ocean Modelling System (ROMS). Though ROMS can simulate several features of ocean, it cannot reproduce the thermocline of the ocean properly. Solution to this problem is to incorporates data assimilation (DA) in the model. DA system using Ensemble Transform Kalman Filter (ETKF) has been developed for ROMS model to improve the accuracy of the model forecast. To assimilate data temperature and salinity from ARGO data has been used as observation. Assimilated temperature and salinity without localization shows oscillations compared to the model run without assimilation for India Ocean. Same was also found for u and v-velocity fields. With localization we found that the state variables are diverging within the localization scale.

A naturally occurring amino acid substitution in the voltage-dependent sodium channel selectivity filter affects channel gating

The pore of sodium channels contains a selectivity filter made of 4 amino acids, D/E/K/A. In voltage sensitive sodium channel (Nav) channels from jellyfish to human the fourth amino acid is Ala. This Ala, when mutated to Asp, promotes slow inactivation. In some Nav channels of pufferfishes, the Ala is replaced with Gly. We studied the biophysical properties of an Ala-to-Gly substitution (A1529G) in rat Nav1.4 channel expressed in Xenopus oocytes alone or with a beta 1 subunit. The Ala-to-Gly substitution does not affect monovalent cation selectivity and positively shifts the voltage-dependent inactivation curve, although co-expression with a beta 1 subunit eliminates the difference between A1529G and WT. There is almost no difference in channel fast inactivation, but the beta 1 subunit accelerates WT current inactivation significantly more than it does the A1529G channels. The Ala-to-Gly substitution mainly influences the rate of recovery from slow inactivation. Again, the beta 1 subunit is less effective on speeding recovery of A1529G than the WT. We searched Nav channels in numerous databases and noted at least four other independent Ala-to-Gly substitutions in Nav channels in teleost fishes. Thus, the Ala-to-Gly substitution occurs more frequently than previously realized, possibly under selection for alterations of channel gating.

Time variant reliability model updating in instrumented dynamical systems based on Girsanov’s transformation

The problem of updating the reliability of instrumented structures based on measured response under random dynamic loading is considered. A solution strategy within the framework of Monte Carlo simulation based dynamic state estimation method and Girsanov’s transformation for variance reduction is developed. For linear Gaussian state space models, the solution is developed based on continuous version of the Kalman filter, while, for non-linear and (or) non-Gaussian state space models, bootstrap particle filters are adopted. The controls to implement the Girsanov transformation are developed by solving a constrained non-linear optimization problem. Numerical illustrations include studies on a multi degree of freedom linear system and non-linear systems with geometric and (or) hereditary non-linearities and non-stationary random excitations.

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.

Comparison of OpAmp based and comparator based switched capacitor filter

Comparator based switched capacitor circuits provide an excellent opportunity to design sampled data systems where the virtual ground condition is detected rather than being continuously forced with negative feedback in Opamp based circuits. This work is an application of this concept to design a 1 st order 330 KHz cutoff frequency Lowpass filter operating at 10 MHz sampling frequency in 0.13μm technology and 1.2 V supply voltage. The Comparator Based Switched Capacitor (CBSC) filter is compared with conventional Two stage Miller compensated Operational amplifier based switched capacitor filter. It is shown that CBSC filter relaxes the constraints like speed ,linearity, gain, stability which would otherwise be hard to satisfy in scaled technologies in Opamp based circuits. The designed CBSC based lowpass filter provides significant power savings compared to traditional Opamp based switched capacitor filter.

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.