A stochastic dynamical system for image segmentation

Image segmentation is formulated as a stochastic process whose invariant distribution is concentrated at points of the desired region. By choosing multiple seed points, different regions can be segmented. The algorithm is based on the theory of time-homogeneous Markov chains and has been largely motivated by the technique of simulated annealing. The method proposed here has been found to perform well on real-world clean as well as noisy images while being computationally far less expensive than stochastic optimisation techniques

Simulation of Potential and Electric Field Profiles for transmission line Insulators

Since the end of second world war, extra high voltage ac transmission has seen its development. The distances between generating and load centres as well as the amount of power to be handled increased tremendously for last 50 years. The highest commercial voltage has increased to 765 kV in India and 1,200 kV in many other countries. The bulk power transmission has been mostly performed by overhead transmission lines. The dual task of mechanically supporting and electrically isolating the live phase conductors from the support tower is performed by string insulators. Whether in clean condition or under polluted conditions, the electrical stress distribution along the insulators governs the possible flashover, which is quite detrimental to the system. Hence the present investigation aims to study accurately, the field distribution for various types of porcelain/ceramic insulators (Normal and Antifog discs) used for high-voltage transmission. The surface charge simulation method is employed for the field computation. A comparison on normalised surface resistance, which is an indicator for the stress concentration under polluted condition, is also attempted.

Top polarisation studies in H(-)t and Wt production

The polarisation of top quarks produced in high energy processes can be a very sensitive probe of physics beyond the Standard Model. The kinematical distributions of the decay products of the top quark can provide clean information on the polarisation of the produced top and thus can probe new physics effects in the top quark sector. We study some of the recently proposed polarisation observables involving the decay products of the top quark in the context of H(-)t and Wt production. We show that the effect of the top polarisation on the decay lepton azimuthal angle distribution, studied recently for these processes at leading order in QCD, is robust with respect to the inclusion of next-to-leading order and parton shower corrections. We also consider the leptonic polar angle, as well as recently proposed energy-related distributions of the top decay products. We construct asymmetry parameters from these observables, which can be used to distinguish the new physics signal from the Wt background and discriminate between different values of tan beta and m(H)- in a general type II two-Higgs doublet model. Finally, we show that similar observables may be useful in separating a Standard Model Wt signal from the much larger QCD induced top pair production background.

The local polynomial hull near a degenerate CR singularity: Bishop discs revisited

Let be a smooth real surface in and let be a point at which the tangent plane is a complex line. How does one determine whether or not is locally polynomially convex at such a p-i.e. at a CR singularity? Even when the order of contact of with at p equals 2, no clean characterisation exists; difficulties are posed by parabolic points. Hence, we study non-parabolic CR singularities. We show that the presence or absence of Bishop discs around certain non-parabolic CR singularities is completely determined by a Maslov-type index. This result subsumes all known facts about Bishop discs around order-two, non-parabolic CR singularities. Sufficient conditions for Bishop discs have earlier been investigated at CR singularities having high order of contact with . These results relied upon a subharmonicity condition, which fails in many simple cases. Hence, we look beyond potential theory and refine certain ideas going back to Bishop.

Experimental and theoretical investigation of thermoacoustic prime mover

The thermoacoustic prime mover is part of an interesting class of prime movers that can be used to generate clean energy and to drive cryogenic refrigeration systems. A thermoacoustic prime mover has been built based on the linear thermoacoustic model, which consumes thermal energy and produces acoustic energy. The objective of this article is to design a thermoacoustic prime mover that can be used as a drive for a thermoacoustic refrigerator. It is found that stack plate length and its distance from the closed end have a significant effect on the thermal efficiency of the prime mover. For different stack center positions, there is an optimum length of stack plate that has a significant effect on the performance of the thermoacoustic prime mover in terms of temperature gradient, frequency, and pressure amplitude. In this study, the experiments have been done on the thermoacoustic prime mover by varying stack position and its length with constant blockage ratio and resonator length. The results obtained from the experiments have been compared to the theoretical results acquired from DeltaEc Software.

Identification of Active Sources in Single-Channel Convolutive Mixtures Using Known Source Models

We address the problem of identifying the constituent sources in a single-sensor mixture signal consisting of contributions from multiple simultaneously active sources. We propose a generic framework for mixture signal analysis based on a latent variable approach. The basic idea of the approach is to detect known sources represented as stochastic models, in a single-channel mixture signal without performing signal separation. A given mixture signal is modeled as a convex combination of known source models and the weights of the models are estimated using the mixture signal. We show experimentally that these weights indicate the presence/absence of the respective sources. The performance of the proposed approach is illustrated through mixture speech data in a reverberant enclosure. For the task of identifying the constituent speakers using data from a single microphone, the proposed approach is able to identify the dominant source with up to 8 simultaneously active background sources in a room with RT60 = 250 ms, using models obtained from clean speech data for a Source to Interference Ratio (SIR) greater than 2 dB.

On Selection of Search Space Dimension in Compressive Sampling Matching Pursuit

Compressive Sampling Matching Pursuit (CoSaMP) is one of the popular greedy methods in the emerging field of Compressed Sensing (CS). In addition to the appealing empirical performance, CoSaMP has also splendid theoretical guarantees for convergence. In this paper, we propose a modification in CoSaMP to adaptively choose the dimension of search space in each iteration, using a threshold based approach. Using Monte Carlo simulations, we show that this modification improves the reconstruction capability of the CoSaMP algorithm in clean as well as noisy measurement cases. From empirical observations, we also propose an optimum value for the threshold to use in applications.

Subspace Pursuit Embedded in Orthogonal Matching Pursuit

Orthogonal Matching Pursuit (OMP) is a popular greedy pursuit algorithm widely used for sparse signal recovery from an undersampled measurement system. However, one of the main shortcomings of OMP is its irreversible selection procedure of columns of measurement matrix. i.e., OMP does not allow removal of the columns wrongly estimated in any of the previous iterations. In this paper, we propose a modification in OMP, using the well known Subspace Pursuit (SP), to refine the subspace estimated by OMP at any iteration and hence boost the sparse signal recovery performance of OMP. Using simulations we show that the proposed scheme improves the performance of OMP in clean and noisy measurement cases.

Reactive power and voltage control in grid connected wind farms

Wind power, as an alternative to fossil fuels, is plentiful, renewable, widely distributed, clean, produces no greenhouse gas emissions during operation, and uses little land. In operation, the overall cost per unit of energy produced is similar to the cost for new coal and natural gas installations. However, the stochastic behaviour of wind speeds leads to significant disharmony between wind energy production and electricity demand. Wind generation suffers from an intermittent characteristics due to the own diurnal and seasonal patterns of the wind behaviour. Both reactive power and voltage control are important under varying operating conditions of wind farm. To optimize reactive power flow and to keep voltages in limit, an optimization method is proposed in this paper. The objective proposed is minimization of the voltage deviations of the load buses (Vdesired). The approach considers the reactive power limits of wind generators and co-ordinates the transformer taps. This algorithm has been tested under practically varying conditions simulated on a test system. The results are obtained on a system of 50-bus real life equivalent power network. The result shows the efficiency of the proposed method.

A risk-estimation-based formulation for speech enhancement and its relation to Wiener filtering

The goal of speech enhancement algorithms is to provide an estimate of clean speech starting from noisy observations. The often-employed cost function is the mean square error (MSE). However, the MSE can never be computed in practice. Therefore, it becomes necessary to find practical alternatives to the MSE. In image denoising problems, the cost function (also referred to as risk) is often replaced by an unbiased estimator. Motivated by this approach, we reformulate the problem of speech enhancement from the perspective of risk minimization. Some recent contributions in risk estimation have employed Stein's unbiased risk estimator (SURE) together with a parametric denoising function, which is a linear expansion of threshold/bases (LET). We show that the first-order case of SURE-LET results in a Wiener-filter type solution if the denoising function is made frequency-dependent. We also provide enhancement results obtained with both techniques and characterize the improvement by means of local as well as global SNR calculations.

Synthon modularity in Cocrystals of 4-Bromobenzamide with n-Alkanedicarboxylic acids: type I and type ll Halogen center dot center dot center dot Halogen interactions

A Cambridge Structural Database (CSD) analysis on halogen center dot center dot center dot halogen contacts (X...X) in organic crystals has been carried out to review the classification criteria for type I, type II, and quasi type I/II halogen interactions. Trends observed in previous CSD analyses of the phenomenon are reinforced in the present study. The manner in which these interactions are manifested in cocrystals of 4-bromobenzamide and dicarboxylic acid is examined. The design strategy for these cocrystals uses synthon theory and follows from an understanding of the crystal structures of gamma-hydroquinone and a previously studied set of 4-hydroxybenzamide dicarboxylic acid cocrystals, making use of Br/OH isostructurality. All cocrystals are obtained by clean insertion of dicarboxylic acids between 4-bromobenzamide molecules. The strategy is deliberate and the prediction of synthons done well in advance, as evidenced from the robustness of the acid-amide heterosynthons in all nine crystal structures, with no aberrant structures in the crystallization experiments. Formation of the acid-amide synthon in these cocrystals is identified with IR spectroscopy. The packing in these cocrystals can be distinguished in terms of whether the Br...Br interactions are type I or II. Eight sets of dimorphs were retrieved from the CSD, wherein the basis of the polymorphism is that one crystal has a type I Br...Br interaction, while the other has a type II interaction.

Scientific and technological aspects of fixed bed biomass gasification

In recent years new emphasis has been placed on problems of the environmental aspects of waste disposal, especially investigating alternatives to landfill, sea dumping and incineration. There is also a strong emphasis on clean, economic and efficient processes for electric power generation. These two topics may at first appear unrelated. Nevertheless, the technological advances are now such that a solution to both can be combined in a novel approach to power generation based on waste-derived fuels, including refuse-derived fuel (RDF) and sludge power (SP) by utilising a slagging gasifier and advance fuel technology (AFT). The most appropriate gasification technique for such waste utilisation is the British Gas/Lurgi (BGL) high pressure, fixed bed slagging gasifier where operation on a range of feedstocks has been well-documented. This gasifier is particularly amenable to briquette fuel feeding and, operating in an integrated gasification combined cycle mode (IGCC), is particularly advantageous. Here, the author details how this technology has been applied to Britain's first AFT-IGCC Power Station which is now under development at Fife Energy Ltd., in Scotland, the former British Gas Westfield Development Centre.

Avoiding acidic region streaking in two-dimensional gel electrophoresis: Case study with two bacterial whole cell protein extracts

Acidic region streaking (ARS) is one of the lacunae in two-dimensional gel electrophoresis (2DE) of bacterial proteome. This streaking is primarily caused by nucleic acid (NuA) contamination and poses major problem in the downstream processes like image analysis and protein identification. Although cleanup and nuclease digestion are practiced as remedial options, these strategies may incur loss in protein recovery and perform incomplete removal of NuA. As a result, ARS has remained a common observation across publications, including the recent ones. In this work, we demonstrate how ultrasound wave can be used to shear NuA in plain ice-cooled water, facilitating the elimination of ARS in the 2DE gels without the need for any additional sample cleanup tasks. In combination with a suitable buffer recipe, IEF program and frequent paper-wick changing approach, we are able to reproducibly demonstrate the production of clean 2DE gels with improved protein recovery and negligible or no ARS. We illustrate our procedure using whole cell protein extracts from two diverse organisms, Escherichia coli and Mycobacterium smegmatis. Our designed protocols are straightforward and expected to provide good 2DE gels without ARS, with comparable times and significantly lower cost.

Combinatorial Crystal Synthesis: Structural Landscape of Phloroglucinol:1,2-bis(4-pyridyl)ethylene and Phloroglucinol:Phenazine

A large number of crystal forms, polymorphs and pseudopolymorphs, have been isolated in the phloroglucinol-dipyridylethylene (PGL:DPE) and phloroglucinol-phenazine (PGL:PHE) systems. An understanding of the intermolecular interactions and synthon preferences in these binary systems enables one to design a ternary molecular solid that consists of PGL, PHE, and DPE, and also others where DPE is replaced by other heterocycles. Clean isolation of these ternary cocrystals demonstrates synthon amplification during crystallization. These results point to the lesser likelihood of polymorphism in multicomponent crystals compared to single-component crystals. The appearance of several crystal forms during crystallization of a multicomponent system can be viewed as combinatorial crystal synthesis with synthon selection from a solution library. The resulting polymorphs and pseudopolymorphs that are obtained constitute a crystal structure landscape.

AN OPTIMUM SHRINKAGE ESTIMATOR BASED ON MINIMUM-PROBABILITY-OF-ERROR CRITERION AND APPLICATION TO SIGNAL DENOISING

We address the problem of designing an optimal pointwise shrinkage estimator in the transform domain, based on the minimum probability of error (MPE) criterion. We assume an additive model for the noise corrupting the clean signal. The proposed formulation is general in the sense that it can handle various noise distributions. We consider various noise distributions (Gaussian, Student's-t, and Laplacian) and compare the denoising performance of the estimator obtained with the mean-squared error (MSE)-based estimators. The MSE optimization is carried out using an unbiased estimator of the MSE, namely Stein's Unbiased Risk Estimate (SURE). Experimental results show that the MPE estimator outperforms the SURE estimator in terms of SNR of the denoised output, for low (0 -10 dB) and medium values (10 - 20 dB) of the input SNR.