444 resultados para Modified Berlekamp-Massey algorithm
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This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices
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A density matrix renormalization group (DMRG) algorithm is presented for the Bethe lattice with connectivity Z = 3 and antiferromagnetic exchange between nearest-neighbor spins s = 1/2 or 1 sites in successive generations g. The algorithm is accurate for s = 1 sites. The ground states are magnetic with spin S(g) = 2(g)s, staggered magnetization that persists for large g > 20, and short-range spin correlation functions that decrease exponentially. A finite energy gap to S > S(g) leads to a magnetization plateau in the extended lattice. Closely similar DMRG results for s = 1/2 and 1 are interpreted in terms of an analytical three-site model.
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Boron addition to conventional titanium alloys below the eutectic limit refines the cast microstructure and improves mechanical properties. The present work explores the influence of hypoeutectic boron addition on the microstructure and texture evolution in Ti-6Al-4V alloy under beta extrusion. The beta extruded microstructure of Ti-6Al-4V is characterized by shear bands parallel to the extrusion direction. In contrast, the extruded Ti-6Al-4V-0.1B alloy shows a regular beta worked microstructure consisting of fine prior beta grains and acicular alpha-lamellae with no signs of the microstructural instability. Crystallographic texture after extrusion was almost identical for the two alloys indicating the similarity in their transformation behavior, which is attributed to complete dynamic recrystallization during beta processing. Microstructural features as well as crystallographic texture indicate dominant grain boundary related deformation processes for the boron modified alloy that leads to homogeneous deformation without instability formation. The absence of shear bands has significant technological importance as far as the secondary processing of boron added alloys in (alpha + beta)-phase field are concerned. (C) 2012 Elsevier B.V. All rights reserved.
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This paper reports the results of employing an artificial bee colony search algorithm for synthesizing a mutually coupled lumped-parameter ladder-network representation of a transformer winding, starting from its measured magnitude frequency response. The existing bee colony algorithm is suitably adopted by appropriately defining constraints, inequalities, and bounds to restrict the search space and thereby ensure synthesis of a nearly unique ladder network corresponding to each frequency response. Ensuring near-uniqueness while constructing the reference circuit (i.e., representation of healthy winding) is the objective. Furthermore, the synthesized circuits must exhibit physical realizability. The proposed method is easy to implement, time efficient, and problems associated with the supply of initial guess in existing methods are circumvented. Experimental results are reported on two types of actual, single, and isolated transformer windings (continuous disc and interleaved disc).
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This paper presents a modified cellulose acetate membrane prepared using a dry casting technique that can be used to perform lysis of erythrocytes and isolation of hemoglobin. Isolation of hemoglobin is thus achieved without the use of lysis buffers. Cellulose acetate (CA) membranes are embedded with ammonium chloride (NH4Cl) and potassium bicarbonate (KHCO3), which act as lysing agents. The presence of embedded salts is confirmed using EDS analysis. The pores in the CA membrane act as filters. The average pore size in these membranes is designed to be 1.5 mu M, as characterized by SEM analysis, so that they allow hemoglobin to pass through and block all other cells and unlysed erythrocytes present in blood. When a drop of blood is added to the membrane, the NH4Cl and KHCO3 embedded in the membrane dissolve in plasma and lyse the erythrocytes. The filtered hemoglobin is characterized using UV-Vis Spectroscopy. The results indicate extraction of higher concentration of hemoglobin compared with conventional methods.
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In this paper, the well-known Adomian Decomposition Method (ADM) is modified to solve the fracture laminated multi-directional problems. The results are compared with the existing analytical/exact or experimental method. The already known existing ADM is modified to improve the accuracy and convergence. Thus, the modified method is named as Modified Adomian Decomposition Method (MADM). The results fromMADM are found to converge very quickly, simple to apply for fracture(singularity) problems and are more accurate compared to experimental and analytical methods. MADM is quite efficient and is practically well-suited for use in these problems. Several examples are given to check the reliability of the present method. In the present paper, the principle of the decomposition method is described, and its advantages form the analyses of fracture of laminated uni-directional composites.
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A new type of covalent bulk modified glassy carbon composite electrode has been fabricated and utilized in the simultaneous determination of lead and cadmium ions in aqueous medium. The covalent bulk modification was achieved by the chemical reduction of 2-hydroxybenzoic acid diazonium tetrafluroborate in the presence of hypophosphorous acid as a chemical reducing agent. The covalent attachment of the modifier molecule was examined by studying Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy and the surface morphology was examined by scanning electron microscopy images. The electrochemistry of modified glassy carbon spheres was studied by its cyclic voltammetry to decipher the complexing ability of the modifier molecules towards Pb2+ and Cd2+ ions. The developed sensor showed a linear response in the concentration range 1-10 mu M with a detection limit of 0.18 and 0.20 mu M for lead and cadmium, respectively. The applicability of the proposed sensor has been checked by measuring the lead and cadmium levels quantitatively from sewage water and battery effluent samples.
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We develop an online actor-critic reinforcement learning algorithm with function approximation for a problem of control under inequality constraints. We consider the long-run average cost Markov decision process (MDP) framework in which both the objective and the constraint functions are suitable policy-dependent long-run averages of certain sample path functions. The Lagrange multiplier method is used to handle the inequality constraints. We prove the asymptotic almost sure convergence of our algorithm to a locally optimal solution. We also provide the results of numerical experiments on a problem of routing in a multi-stage queueing network with constraints on long-run average queue lengths. We observe that our algorithm exhibits good performance on this setting and converges to a feasible point.
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Glassy carbon electrodes (GCE) and carbon paste electrodes (CPE) were modified with imidazole functionalized polyaniline with the aim to develop a sensor for lead (II) in both acidic and basic aqueous solution. The electrodes were characterized by cyclic voltammetry and differential pulse adsorptive stripping voltammetry. The limit of detections obtained with glassy carbon electrode and carbon paste electrode are 20 ng mL(-1) and 2 ng mL(-1) of lead ion, respectively. An interference study was carried out with Cd(II), As(III), Hg(II) and Co(II) ions. Cd(II) ions interfere significantly (peak overlap) and As(III) has a depressing effect on the lead signal. The influence of pH was investigated indicating that bare and modified GCE and CPE show optimum response at pH 4.0 +/- 0.05.
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A hydrological modelling framework was assembled to simulate the daily discharge of the Mandovi River on the Indian west coast. Approximately 90% of the west-coast rainfall, and therefore discharge, occurs during the summer monsoon (June-September), with a peak during July-August. The modelling framework consisted of a digital elevation model (DEM) called GLOBE, a hydrological routing algorithm, the Terrestrial Hydrological Model with Biogeochemistry (THMB), an algorithm to map the rainfall recorded by sparse rain-gauges to the model grid, and a modified Soil Conservation Service Curve Number (SCS-CN) method. A series of discharge simulations (with and without the SCS method) was carried out. The best simulation was obtained after incorporating spatio-temporal variability in the SCS parameters, which was achieved by an objective division of the season into five regimes: the lean season, monsoon onset, peak monsoon, end-monsoon, and post-monsoon. A novel attempt was made to incorporate objectively the different regimes encountered before, during and after the Indian monsoon, into a hydrological modelling framework. The strength of our method lies in the low demand it makes on hydrological data. Apart from information on the average soil type in a region, the entire parameterization is built on the basis of the rainfall that is used to force the model. That the model does not need to be calibrated separately for each river is important, because most of the Indian west-coast basins are ungauged. Hence, even though the model has been validated only for the Mandovi basin, its potential region of application is considerable. In the context of the Prediction in Ungauged Basins (PUB) framework, the potential of the proposed approach is significant, because the discharge of these (ungauged) rivers into the eastern Arabian Sea is not small, making them an important element of the local climate system.
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Organo-clay was prepared by incorporating different amounts (in terms of CEC, ranging from 134-840 mg of quaternary ammonium cation (QACs) such as hexadecytrimethylammonium bromide (C19H42N]Br) into the montmorillonite clay. Prepared organo-clays are characterized by CHN analyser and XRD to measure the amount of elemental content and interlayer spacing of surfactant modified clay. The batch experiments of sorption of permanganate from aqueous media by organo-clays was studied at different acidic strengths (pH 1-7). The experimental results show that the rate and amount of adsorption of permanganate was higher at lower pH compared to raw montmorillonite. Laboratory fixed bed experiments were conducted to evaluate the breakthrough time and nature of breakthrough curves. The shape of the breakthrough curves shows that the initial cationic surfactant loadings at 1.0 CEC of the clay is enough to enter the permanganate ions in to the interlamellar region of the surfactant modified smectile clays. These fixed bed studies were also applied to quantify the effect of bed-depth and breakthrough time during the uptake of permanganate. Calculation of thermodynamic parameters shows that the sorption of permanganate is spontaneous and follows the first order kinetics.
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Graphene's nano-dimensional nature and excellent electron transfer properties underlie its electrocatalytic behavior towards certain substances. In this light, we have used graphene in the electrochemical detection of bisphenol A. Graphene sheets were produced via soft chemistry route involving graphite oxidation and chemical reduction. X-ray diffraction, Fourier transform infra-red (FT-IR) and Raman spectroscopy were used for the characterization of the as-synthesized graphene. Graphene exhibited amorphous structure in comparison with pristine graphite from XRD spectra. FTIR showed that graphene exhibits OH and COOH groups due to incomplete reduction. Raman spectroscopy revealed that multi-layered graphene was produced due to low intensity of the 2D-peak. Glassy carbon electrode was modified with graphene by a simple drop and dry method. Cyclic voltammetry was used to study the electrochemical properties of the prepared graphene-modified glassy carbon electrode using potassium ferricyanide as a redox probe. The prepared graphene- modified glassy carbon electrode exhibited more facile electron kinetics and enhanced current of about 75% when compared to the unmodified glassy carbon electrode. The modified electrode was used for the detection of bisphenol A. Under the optimum conditions, the oxidation peak current of bisphenol A varied linearly with concentration over a wide range of 5 x 10(-8) mol L-1 to 1 x 10(-6) mol L-1 and the detection limit of this method was as low as 4.689 x 10(-8) M. This method was also employed to determine bisphenol A in a real sample
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Vicsek et al. proposed a biologically inspired model of self-propelled particles, which is now commonly referred to as the Vicsek model. Recently, attention has been directed at modifying the Vicsek model so as to improve convergence properties. In this paper, we propose two modification of the Vicsek model which leads to significant improvements in convergence times. The modifications involve an additional term in the heading update rule which depends only on the current or the past states of the particle's neighbors. The variation in convergence properties as the parameters of these modified versions are changed are closely investigated. It is found that in both cases, there exists an optimal value of the parameter which reduces convergence times significantly and the system undergoes a phase transition as the value of the parameter is increased beyond this optimal value. (C) 2012 Elsevier B.V. All rights reserved.
Resumo:
This article aims to obtain damage-tolerant designs with minimum weight for a laminated composite structure using genetic algorithm. Damage tolerance due to impacts in a laminated composite structure is enhanced by dispersing the plies such that too many adjacent plies do not have the same angle. Weight of the structure is minimized and the Tsai-Wu failure criterion is considered for the safe design. Design variables considered are the number of plies and ply orientation. The influence of dispersed ply angles on the weight of the structure for a given loading conditions is studied by varying the angles in the range of 0 degrees-45 degrees, 0 degrees-60 degrees and 0 degrees-90 degrees at intervals of 5 degrees and by using specific ply angles tailored to loading conditions. A comparison study is carried out between the conventional stacking sequence and the stacking sequence with dispersed ply angles for damage-tolerant weight minimization and some useful designs are obtained. Unconventional stacking sequence is more damage tolerant than the conventional stacking sequence is demonstrated by performing a finite element analysis under both tensile as well as compressive loading conditions. Moreover, a new mathematical function called the dispersion function is proposed to measure the dispersion of ply angles in a laminate. The approach for dispersing ply angles to achieve damage tolerance is especially suited for composite material design space which has multiple local minima.
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This paper presents hierarchical clustering algorithms for land cover mapping problem using multi-spectral satellite images. In unsupervised techniques, the automatic generation of number of clusters and its centers for a huge database is not exploited to their full potential. Hence, a hierarchical clustering algorithm that uses splitting and merging techniques is proposed. Initially, the splitting method is used to search for the best possible number of clusters and its centers using Mean Shift Clustering (MSC), Niche Particle Swarm Optimization (NPSO) and Glowworm Swarm Optimization (GSO). Using these clusters and its centers, the merging method is used to group the data points based on a parametric method (k-means algorithm). A performance comparison of the proposed hierarchical clustering algorithms (MSC, NPSO and GSO) is presented using two typical multi-spectral satellite images - Landsat 7 thematic mapper and QuickBird. From the results obtained, we conclude that the proposed GSO based hierarchical clustering algorithm is more accurate and robust.