Design of a FIR filter for image restoration using principal component neural networks

The neural network finds its application in many image denoising applications because of its inherent characteristics such as nonlinear mapping and self-adaptiveness. The design of filters largely depends on the a-priori knowledge about the type of noise. Due to this, standard filters are application and image specific. Widely used filtering algorithms reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated general approach to design a finite impulse response filter based on principal component neural network (PCNN) is proposed in this study for image filtering, optimized in the sense of visual inspection and error metric. This algorithm exploits the inter-pixel correlation by iteratively updating the filter coefficients using PCNN. This algorithm performs optimal smoothing of the noisy image by preserving high and low frequency features. Evaluation results show that the proposed filter is robust under various noise distributions. Further, the number of unknown parameters is very few and most of these parameters are adaptively obtained from the processed image.

Self assessment schemes for multi-agent cooperative search

In this paper, we present self assessment schemes (SAS) for multiple agents performing a search mission on an unknown terrain. The agents are subjected to limited communication and sensor ranges. The agents communicate and coordinate with their neighbours to arrive at route decisions. The self assessment schemes proposed here have very low communication and computational overhead. The SAS also has attractive features like scalability to large number of agents and fast decision-making capability. SAS can be used with partial or complete information sharing schemes during the search mission. We validate the performance of SAS using simulation on a large search space consisting of 100 agents with different information structures and self assessment schemes. We also compare the results obtained using SAS with that of a previously proposed negotiation scheme. The simulation results show that the SAS is scalable to large number of agents and can perform as good as the negotiation schemes with reduced communication requirement (almost 20% of that required for negotiation).

Polymer–filler interactions in hydroxy-terminated polybutadiene–ammonium perchlorate system in the presence of a bonding agent

Bonding between ammonium perchlorate (AP) and hydroxy-terminated polybutadiene (HTPB), constituting a nonreinforcing filler system, has been studied in the presence of a unique bonding agent (BA)–a switter ion molecule, 2,4-dinitrophenylhydrazone derivative of 1,1′-bisacetylferrocene (DNPHD AF). Extensive conjugation and a permanent ionic character makes the DNPHD AF to bond strongly with the ionic oxidizer AP. Through its terminal OH group, HTPH bonds with the NO2 groups of DNPHD AF. Bonding sites in the molecules have been located from IR studies and from the first-order rate constant measurements of the bonding of DNPHD AF and other model BAs with HTPB and AP. The bonding ability of DNPHD AF is further evidenced from SEM micrographs.

Biomimetic synthesis of silver nanoparticles by Citrus limon (lemon) aqueous extract and theoretical prediction of particle size

In the present study silver nanoparticles were rapidly synthesized at room temperature by treating silver ions with the Citrus limon (lemon) extract The effect of various process parameters like the reductant con centration mixing ratio of the reactants and the concentration of silver nitrate were studied in detail In the standardized process 10(-2) M silver nitrate solution was interacted for 411 with lemon Juice (2% citric acid concentration and 0 5% ascorbic acid concentration) in the ratio of 1 4(vol vol) The formation of silver nanoparticles was confirmed by Surface Plasmon Resonance as determined by UV-Visible spectra in the range of 400-500 nm X ray diffraction analysis revealed the distinctive facets (1 1 1 200 220 2 2 2 and 3 1 1 planes) of silver nanoparticles We found that citric acid was the principal reducing agent for the nanosynthesis process FT IR spectral studies demonstrated citric acid as the probable stabilizing agent Silver nanoparticles below 50 nm with spherical and spheroidal shape were observed from transmission electron microscopy The correlation between absorption maxima and particle sizes were derived for different UV-Visible absorption maxima (corresponding to different citric acid concentrations) employing MiePlot v 3 4 The theoretical particle size corresponding to 2% citric acid concentration was corn pared to those obtained by various experimental techniques like X ray diffraction analysis atomic force microscopy and transmission electron microscopy (C) 2010 Elsevier B V All rights reserved

Control of Agent Swarms using Generalized Centroidal Cyclic Pursuit Laws

One of the major tasks in swarm intelligence is to design decentralized but homogenoeus strategies to enable controlling the behaviour of swarms of agents. It has been shown in the literature that the point of convergence and motion of a swarm of autonomous mobile agents can be controlled by using cyclic pursuit laws. In cyclic pursuit, there exists a predefined cyclic connection between agents and each agent pursues the next agent in the cycle. In this paper we generalize this idea to a case where an agent pursues a point which is the weighted average of the positions of the remaining agents. This point correspond to a particular pursuit sequence. Using this concept of centroidal cyclic pursuit, the behavior of the agents is analyzed such that, by suitably selecting the agents' gain, the rendezvous point of the agents can be controlled, directed linear motion of the agents can be achieved, and the trajectories of the agents can be changed by switching between the pursuit sequences keeping some of the behaviors of the agents invariant. Simulation experiments are given to support the analytical proofs.

Multi-Agent Rendezvous Algorithm with Rectilinear Decision Domain

The aim of this paper is to develop a computationally efficient decentralized rendezvous algorithm for a group of autonomous agents. The algorithm generalizes the notion of sensor domain and decision domain of agents to enable implementation of simple computational algorithms. Specifically, the algorithm proposed in this paper uses a rectilinear decision domain (RDD) as against the circular decision domain assumed in earlier work. Because of this, the computational complexity of the algorithm reduces considerably and, when compared to the standard Ando's algorithm available in the literature, the RDD algorithm shows very significant improvement in convergence time performance. Analytical results to prove convergence and supporting simulation results are presented in the paper.

Positional Consensus of Multi-Agent Systems Using Linear Programming Based Decentralized Control with Rectilinear Decision Domain

In this paper we develop a Linear Programming (LP) based decentralized algorithm for a group of multiple autonomous agents to achieve positional consensus. Each agent is capable of exchanging information about its position and orientation with other agents within their sensing region. The method is computationally feasible and easy to implement. Analytical results are presented. The effectiveness of the approach is illustrated with simulation results.

Microwave assisted synthesis and UV-Vis spectroscopic studies of silver nanoparticles synthesized using vanillin as a reducing agent

The present investigation explores the adaptability of a microwave assisted route to obtain silver nanoparticles by the reduction of AgNO3 with vanillin, an environmentally benign material. Anionic surfactants such as AOT and SDS were used separately for encapsulating AgNPs and their role was compared. The UV-Visible absorption spectra present a broad SPR band consisting of two peaks suggesting the formation of silver nanoparticle with bimodal size distribution. The TEM image shows particles with spherical and hexagonal morphologies which confirms the results of UV-Vis studies. The anisotropy in the particle morphology can be attributed to the surface oxidation which in turn produces Ag@Ag2O core-shell nanostructures. Thus an intriguing feature of this system is that the obtained colloid is a mixture of AgNPs with and without Ag2O layers. Studies on the influence of pH on the stability of the synthesized nanoparticles revealed that the presence of excess Ag2O layers has a profound influence on it. Ag2O layers can be removed from AgNPs' surface by changing the solution pH to the acidic regime. The present study attests the enhanced ability of AOT in stabilizing the AgNPs in aqueous media. (C) 2011 Elsevier B.V. All rights reserved.

Automated Multi-Agent Search Using Centroidal Voronoi Configuration

This paper addresses the problem of automated multiagent search in an unknown environment. Autonomous agents equipped with sensors carry out a search operation in a search space, where the uncertainty, or lack of information about the environment, is known a priori as an uncertainty density distribution function. The agents are deployed in the search space to maximize single step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for the proposed sequential deploy and search strategy. It is shown that with the proposed control law the agent trajectories converge in a globally asymptotic manner to the centroidal Voronoi configuration. Simulation experiments are provided to validate the strategy. Note to Practitioners-In this paper, searching an unknown region to gather information about it is modeled as a problem of using search as a means of reducing information uncertainty about the region. Moreover, multiple automated searchers or agents are used to carry out this operation optimally. This problem has many applications in search and surveillance operations using several autonomous UAVs or mobile robots. The concept of agents converging to the centroid of their Voronoi cells, weighted with the uncertainty density, is used to design a search strategy named as sequential deploy and search. Finally, the performance of the strategy is validated using simulations.

Synthesis of epoxy-terminated polymers by radical polymerization using alpha-(t-butylperoxymethyl)styrene as chain transfer agent

Epoxy-terminated polystyrene has been synthesized by radical polymerization using alpha-(t-butylperoxymethyl) styrene (TPMS) as the chain transfer agent. The chain transfer constants were found to be 0.66 and 0.80 at 60 and 70 degrees C, respectively. The presence of epoxy end groups was confirmed by functional group modification of epoxide to aldehyde by treatment with BF3.Et(2)O. Thermal stability of TPMS was followed by differential scanning calorimetry and iodimetry. Thermal decomposition of TPMS in toluene follows first order kinetics with an activation energy of 23 kcal/mol. (C) 1996 John Wiley & Sons, Inc.

Propargyloxycarbonyl (Poc) amino acid chlorides as efficient coupling reagents for the synthesis of 100% diastereopure peptides and resin bound tetrathiomolybdate as an effective deblocking agent for the Poc group

Synthesis of short peptides using propargyloxycarbonyl amino acid chlorides as effective coupling reagents and polymer supported tetrathiomolybdate as an efficient deblocking agent are reported.

Two Dimensional Principal Component Analysis for Online Tamil Character Recognition

This paper presents a new application of two dimensional Principal Component Analysis (2DPCA) to the problem of online character recognition in Tamil Script. A novel set of features employing polynomial fits and quartiles in combination with conventional features are derived for each sample point of the Tamil character obtained after smoothing and resampling. These are stacked to form a matrix, using which a covariance matrix is constructed. A subset of the eigenvectors of the covariance matrix is employed to get the features in the reduced sub space. Each character is modeled as a separate subspace and a modified form of the Mahalanobis distance is derived to classify a given test character. Results indicate that the recognition accuracy using the 2DPCA scheme shows an approximate 3% improvement over the conventional PCA technique.

Multi-agent search using?sensors with heterogeneous capabilities

In this thesis we address the problem of multi-agent search. We formulate two deploy and search strategies based on optimal deployment of agents in search space so as to maximize the search effectiveness in a single step. We show that a variation of centroidal Voronoi configuration is the optimal deployment. When the agents have sensors with different capabilities, the problem will be heterogeneous in nature. We introduce a new concept namely, generalized Voronoi partition in order to formulate and solve the heterogeneous multi-agent search problem. We address a few theoretical issues such as optimality of deployment, convergence and spatial distributedness of the control law and the search strategies. Simulation experiments are carried out to compare performances of the proposed strategies with a few simple search strategies.

Multi-agent Search using Voronoi partitions

This paper addresses the problem of multiagent search in an unknown environment. The agents are autonomous in nature and are equipped with necessary sensors to carry out the search operation. The uncertainty, or lack of information about the search area is known a priori as a probability density function. The agents are deployed in an optimal way so as to maximize the one step uncertainty reduction. The agents continue to deploy themselves and reduce uncertainty till the uncertainty density is reduced over the search space below a minimum acceptable level. It has been shown, using LaSalle’s invariance principle, that a distributed control law which moves each of the agents towards the centroid of its Voronoi partition, modified by the sensor range leads to single step optimal deployment. This principle is now used to devise search trajectories for the agents. The simulations were carried out in 2D space with saturation on speeds of the agents. The results show that the control strategy per step indeed moves the agents to the respective centroid and the algorithm reduces the uncertainty distribution to the required level within a few steps.

Use of CaC12 as a chlorinating agent for oxides - A thermodynamic analysis

Presented is a thermodynamic feasibility analysis of extracting base metal chlorides fiom low-grade,multimetallic oxide ores using CaClz as a chlorinating agent in the presence of SOz undoz. The oxides react to form corresponding chlorides, while CaClz is converted to CaS04. The Ellingham diagram is usedfor comparing the standard Gibbs' fiee energy chanlpef or the su(fation-chlorinationr eaction of a large number of oxides. Except for alumina, silica and chromia, most of the other metal oxides will be converted to their respective chlorides. The volatile chlorides can be condensed, and the chlorides present in the condensed state can be leached. A process is proposed that uses a nontoxic chlorinating agent and gives an eficient sepurutiort cftlte metallic vuluesfr.om the garlgue.