264 resultados para micro neural probe


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This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.

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The development of a neural network based power system damping controller (PSDC) for a static VAr compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system

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The development of a neural network based power system damping controller (PSDC) for a static Var compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system.

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This paper presents the development of a neural network based power system stabilizer (PSS) designed to enhance the damping characteristics of a practical power system network representing a part of Electricity Generating Authority of Thailand (EGAT) system. The proposed PSS consists of a neuro-identifier and a neuro-controller which have been developed based on functional link network (FLN) model. A recursive on-line training algorithm has been utilized to train the two neural networks. Simulation results have been obtained under various operating conditions and severe disturbance cases which show that the proposed neuro-PSS can provide a better damping to the local as well as interarea modes of oscillations as compared to a conventional PSS

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As power systems grow in their size and interconnections, their complexity increases. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems be operated closer to design limits. Hence power system voltage stability and voltage control are emerging as major problems in the day-to-day operation of stressed power systems. For secure operation and control of power systems under normal and contingency conditions it is essential to provide solutions in real time to the operator in energy control center (ECC). Artificial neural networks (ANN) are emerging as an artificial intelligence tool, which give fast, though approximate, but acceptable solutions in real time as they mostly use the parallel processing technique for computation. The solutions thus obtained can be used as a guide by the operator in ECC for power system control. This paper deals with development of an ANN architecture, which provide solutions for monitoring, and control of voltage stability in the day-to-day operation of power systems.

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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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The present work is aimed at studying the influence of electrolyte chemistry on the voltage-time (V-T) response characteristics, phase structure, surface morphology, film growth rate and corrosion properties of titania films fabricated by micro arc oxidation (MAO) on Cp Ti. The titania films were developed with a sodium phosphate based reference electrolyte comprising the additives such as sodium carbonate (Na2CO3), sodium nitrite (NaNO2) and urea (CO(NH2)(2)). The phase composition, surface morphology, elemental composition and thickness of the films were assessed by X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) techniques. The corrosion characteristics of the fabricated films were studied under Kokubo simulated body fluid (SBF) condition by potentiodynamic polarization, long term potential and linear polarization resistance (LPR) measurements and electrochemical impedance spectroscopy (EIS) methods. In addition, the corrosion characteristics of the grown films were analyzed by EIS curve fitting and equivalent circuit modeling. Salt spray test (SST) as per ASTM B 117 standard was also conducted to verify the corrosion resistance of the grown films. The XRD results showed that the titania films were composed of both anatase and rutile phases at different proportions. Besides, the films grown in carbonate and nitrite containing electrolyte systems showed an enhanced growth of their rutile phase in the 1 0 1] direction which could be attributed to the modifications introduced in the growth process by the abundant oxygen available during the process. The SEM-EDX and elemental mapping results showed that the respective electrolyte borne elements were incorporated and distributed uniformly in all the films. Among all the grown films under study, the film developed in carbonate containing electrolyte system exhibited considerably improved corrosion resistance due to suitable modifications in its structural and morphological characteristics. The rate of anatase to rutile phase transformation and the rutile growth direction were strongly influenced by the abundant oxidizing species available during the film growth process. (C) 2012 Elsevier B. V. All rights reserved.

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Background and aim of the study: The quantification of incidentally found aortic valve calcification on computed tomography (CT) is not performed routinely, as data relating to the accuracy of aortic valve calcium for estimating the severity of aortic stenosis (AS) is neither consistent nor validated. As aortic valve calcium quantification by CT is confounded by wall and coronary ostial calcification, as well as motion artifact, the ex-vivo micro-computed tomography (micro-CT) of stenotic aortic valves allows a precise measurement of the amounts of calcium present. The study aim, using excised aortic valves from patients with confirmed AS, was to determine if the amount of calcium on micro-CT correlated with the severity of AS. Methods: Each of 35 aortic valves that had been excised from patients during surgical valve replacement were examined using micro-CT imaging. The amount of calcium present was determined by absolute and proportional values of calcium volume in the specimen. Subsequently, the correlation between calcium volume and preoperative mean aortic valve gradient (MAVG), peak transaortic velocity (V-max), and aortic valve area (AVA) on echocardiography, was evaluated. Results: The mean calcium volume across all valves was 603.2 +/- 398.5 mm(3), and the mean ratio of calcium volume to total valve volume was 0.36 +/- 0.16. The mean aortic valve gradient correlated positively with both calcium volume and ratio (r = 0.72, p <0.001). V-max also correlated positively with the calcium volume and ratio (r = 0.69 and 0.76 respectively; p <0.001). A logarithmic curvilinear model proved to be the best fit to the correlation. A calcium volume of 480 mm(3) showed sensitivity and specificity of 0.76 and 0.83, respectively, for a diagnosis of severe AS, while a calcium ratio of 0.37 yielded sensitivity and specificity of 0.82 and 0.94, respectively. Conclusion: A radiological estimation of calcium amount by volume, and its proportion to the total valve volume, were shown to serve as good predictive parameters for severe AS. An estimation of the calcium volume may serve as a complementary measure for determining the severity of AS when aortic valve calcification is identified on CT imaging. The Journal of Heart Valve Disease 2012;21:320-327

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Compositional dependent investigations of the bulk GeTe chalcogenides alloys added with different selenium concentrations are carried out by X-ray diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), electron probe micro-analyzer (EPMA) and differential scanning calorimetry (DSC). The measurements reveal that GeTe crystals are predominant in alloys up to 0.20 at.% of Se content indicating interstitial occupancy of Se in the Ge vacancies. Raman modes in the GeTe alloys changes to GeSe modes with the addition of Se. Amorphousness in the alloy increases with increase of Se and 0.50 at.% Se alloy forms a homogeneous amorphous phase with a mixture of Ge-Se and Te-Se bonds. Structural changes are explained with the help of bond theory of solids. Crystallization temperature is found to be increasing with increase of Se, which will enable the amorphous stability. For the optimum 0.50 at.% Se alloy, the melting temperature has reduced which will reduce the RESET current requirement for the phase change memory applications. (C) 2012 Elsevier B.V. All rights reserved.

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Nanoindentation and scratch experiments on 1:1 donor-acceptor complexes, 1 and 2, of 1,2,4,5-tetracyanobenzene with pyrene and phenanthrene, respectively, reveal long-range molecular layer gliding and large interaction anisotropy. Due to the layered arrangements in these crystals, these experiments that apply stress in particular directions result in the breaking of interlayer interactions, thus allowing molecular sheets to glide over one another with ease. Complex 1 has a layered crystal packing wherein the layers are 68° skew under the (002) face and the interlayer space is stabilized by van der Waals interactions. Upon indenting this surface with a Berkovich tip, pile-up of material was observed on just one side of the indenter due to the close angular alignment of the layers with the half angle of the indenter tip (65.35°). The interfacial differences in the elastic modulus (21 ) and hardness (16 ) demonstrate the anisotropic nature of crystal packing. In 2, the molecular stacks are arranged in a staggered manner; there is no layer arrangement, and the interlayer stabilization involves C-H�N hydrogen bonds and ��� interactions. This results in a higher modulus (20 ) for (020) as compared to (001), although the anisotropy in hardness is minimal (4 ). The anisotropy within a face was analyzed using AFM image scans and the coefficient of friction of four orthogonal nanoscratches on the cleavage planes of 1 and 2. A higher friction coefficient was obtained for 2 as compared to 1 even in the cleavage direction due to the presence of hydrogen bonds in the interlayer region making the tip movement more hindered. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Experimental crystal structures of mono and polyfluorinated benzoic acids correspond to high energy computed crystal structures of benzoic acid itself, thereby permitting access to its structural landscape.

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Small quantity of energetic material coated on the inner wall of a polymer tube is proposed as a new method to generate micro-shock waves in the laboratory. These micro-shock waves have been harnessed to develop a novel method of delivering dry particle and liquid jet into the target. We have generated micro-shock waves with the help of reactive explosive compound high melting explosive (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) and traces of aluminium] coated polymer tube, utilising 9 J of energy. The detonation process is initiated electrically from one end of the tube, while the micro-shock wave followed by the products of detonation escape from the open end of the polymer tube. The energy available at the open end of the polymer tube is used to accelerate tungsten micro-particles coated on the other side of the diaphragm or force a liquid jet out of a small cavity filled with the liquid. The micro-particles deposited on a thin metal diaphragm (typically 100-mu m thick) were accelerated to high velocity using micro-shock waves to penetrate the target. Tungsten particles of 0.7 mu m diameter have been successfully delivered into agarose gel targets of various strengths (0.6-1.0 %). The device has been tested by delivering micro-particles into potato tuber and Arachis hypogaea Linnaeus (ground nut) stem tissue. Along similar lines, liquid jets of diameter 200-250 mu m (methylene blue, water and oils) have been successfully delivered into agarose gel targets of various strengths. Successful vaccination against murine salmonellosis was demonstrated as a biological application of this device. The penetration depths achieved in the experimental targets are very encouraging to develop a future device for biological and biomedical applications.

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The structure of the hydrogen bond network is a key element for understanding water's thermodynamic and kinetic anomalies. While ambient water is strongly believed to be a uniform, continuous hydrogen-bonded liquid, there is growing consensus that supercooled water is better described in terms of distinct domains with either a low-density ice-like structure or a high-density disordered one. We evidenced two distinct rotational mobilities of probe molecules in interstitial supercooled water of polycrystalline ice Banerjee D, et al. (2009) ESR evidence for 2 coexisting liquid phases in deeply supercooled bulk water. Proc Natl Acad Sci USA 106: 11448-11453]. Here we show that, by increasing the confinement of interstitial water, the mobility of probe molecules, surprisingly, increases. We argue that loose confinement allows the presence of ice-like regions in supercooled water, whereas a tighter confinement yields the suppression of this ordered fraction and leads to higher fluidity. Compelling evidence of the presence of ice-like regions is provided by the probe orientational entropy barrier which is set, through hydrogen bonding, by the configuration of the surrounding water molecules and yields a direct measure of the configurational entropy of the same. We find that, under loose confinement of supercooled water, the entropy barrier surmounted by the slower probe fraction exceeds that of equilibrium water by the melting entropy of ice, whereas no increase of the barrier is observed under stronger confinement. The lower limit of metastability of supercooled water is discussed.

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In situ powder X-ray diffraction (XRD) studies on 3D micro-crystalline tin (II) sulfide (SnS) were carried out at different temperatures. While increasing temperature, the crystal structure of SnS remains stable as orthorhombic, whereas its lattice parameters and unit-cell volume are considerably varied. Further, these 3D micro-crystalline structures have showed a negative thermal expansion along the a-axis and positive expansion along the b- and c-axes. However, the overall drop along the a-axis of SnS crystals is nearly equal to their expansion along the c-axis. The observed changes in the structural properties of SnS micro-crystallites with temperature are discussed and reported.