Negative sequence compensation within fundamental positive sequence reference frame for a stiff micro-grid generation in a wind power system using slip ring induction machine

An isolated wind power generation scheme using slip ring induction machine (SRIM) is proposed. The proposed scheme maintains constant load voltage and frequency irrespective of the wind speed or load variation. The power circuit consists of two back-to-back connected inverters with a common dc link, where one inverter is directly connected to the rotor side of SRIM and the other inverter is connected to the stator side of the SRIM through LC filter. Developing a negative sequence compensation method to ensure that, even under the presence of unbalanced load, the generator experiences almost balanced three-phase current and most of the unbalanced current is directed through the stator side converter is the focus here. The SRIM controller varies the speed of the generator with variation in the wind speed to extract maximum power. The difference of the generated power and the load power is either stored in or extracted from a battery bank, which is interfaced to the common dc link through a multiphase bidirectional fly-back dc-dc converter. The SRIM control scheme, maximum power point extraction algorithm and the fly-back converter topology are incorporated from available literature. The proposed scheme is both simulated and experimentally verified.

A Team of Continuous-Action Learning Automata for Noise-Tolerant Learning of Half-Spaces

Learning automata are adaptive decision making devices that are found useful in a variety of machine learning and pattern recognition applications. Although most learning automata methods deal with the case of finitely many actions for the automaton, there are also models of continuous-action-set learning automata (CALA). A team of such CALA can be useful in stochastic optimization problems where one has access only to noise-corrupted values of the objective function. In this paper, we present a novel formulation for noise-tolerant learning of linear classifiers using a CALA team. We consider the general case of nonuniform noise, where the probability that the class label of an example is wrong may be a function of the feature vector of the example. The objective is to learn the underlying separating hyperplane given only such noisy examples. We present an algorithm employing a team of CALA and prove, under some conditions on the class conditional densities, that the algorithm achieves noise-tolerant learning as long as the probability of wrong label for any example is less than 0.5. We also present some empirical results to illustrate the effectiveness of the algorithm.

R1STM: One-class support tensor machine with randomised kernel

Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Relative electrical distance concept for evaluation of network reactive power and loss contributions in a deregulated system

With the liberalisation of electricity market it has become very important to determine the participants making use of the transmission network.Transmission line usage computation requires information of generator to load contributions and the path used by various generators to meet loads and losses. In this study relative electrical distance (RED) concept is used to compute reactive power contributions from various sources like generators, switchable volt-amperes reactive(VAR) sources and line charging susceptances that are scattered throughout the network, to meet the system demands. The transmission line charge susceptances contribution to the system reactive flows and its aid extended in reducing the reactive generation at the generator buses are discussed in this paper. Reactive power transmission cost evaluation is carried out in this study. The proposed approach is also compared with other approaches viz.,proportional sharing and modified Y-bus.Detailed case studies with base case and optimised results are carried out on a sample 8-bus system. IEEE 39-bus system and a practical 72-bus system, an equivalent of Indian Southern grid are also considered for illustration and results are discussed.

The composition dependence of electrical switching behavior of Ge7Se93-xSbx glasses

Bulk Ge7Se93-xSbx (21 <= x <= 32) glasses are prepared by melt quenching method and electrical switching studies have been undertaken on these samples to elucidate the type of switching and the composition and thickness dependence of switching voltages. On the basis of the compressibility and atomic radii, it has been previously observed that Se-based glasses exhibit memory switching behavior. However, the present results indicate that Ge7Se93-xSbx glasses exhibit threshold type electrical switching with high switching voltages. Further, these samples are found to show fluctuations in the current-voltage (I-V) characteristics. The observed threshold behavior of Ge7Se93-xSbx glasses has been understood on the basis of larger atomic radii and lesser compressibilities of Sb and Ge. Further. the high switching voltages and fluctuations in the I-V characteristics of Ge-Se-Sb samples can be attributed to the high resistance of the samples and the difference in thermal conductivities of different structural units constituting the local structure of these glasses. The switching voltages of Ge7Se93-xSbx glasses have been found to decrease with the increase in the Sb concentration. The observed composition dependence of switching voltages has been understood on the basis of higher metallicity of the Sb additive and also in the light of the Chemically Ordered Network (CON) model. Further, the thickness dependence of switching voltages has been studied to reassert the mechanism of switching.

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.

Aircraft trajectory clustering techniques using circular statistics

This paper presents a statistical aircraft trajectory clustering approach aimed at discriminating between typical manned and expected unmanned traffic patterns. First, a resampled version of each trajectory is modelled using a mixture of Von Mises distributions (circular statistics). Second, the remodelled trajectories are globally aligned using tools from bioinformatics. Third, the alignment scores are used to cluster the trajectories using an iterative k-medoids approach and an appropriate distance function. The approach is then evaluated using synthetically generated unmanned aircraft flights combined with real air traffic position reports taken over a sector of Northern Queensland, Australia. Results suggest that the technique is useful in distinguishing between expected unmanned and manned aircraft traffic behaviour, as well as identifying some common conventional air traffic patterns.

Synthesis of liquid crystalline benzothiazole base derivatives: A study of their optical and electrical properties

Two new donor-acceptor type liquid crystalline semiconductors based on benzothiazole have been synthesized. Their structural, photophysical and electronic properties were investigated using X-ray diffraction, atomic force microscopy, cyclic voltammetry, UV-Vis, photoluminescence, and Raman spectroscopy. The liquid crystalline behaviour of the molecules was thoroughly examined by differential scanning calorimetry (DSC) and optical polarizing microscope. The DSC and thermogravimetric analysis (TGA) show that these materials posses excellent thermal stability and have decomposition temperatures in excess of 300 degrees C. Beyond 160 degrees C both molecules show a smectic A liquid crystalline phase that exists till about 240 degrees C. Field-effect transistors were fabricated by vacuum evaporating the semiconductor layer using standard bottom gate/top contact geometry. The devices exhibit p-channel behaviour with hole mobilities of 10(-2) cm(2)/Vs. (C) 2009 Elsevier B.V. All rights reserved.

Time Domain Characteristics of Electrical Measures for a Piezoelectric Thin Film to Identify Defects in the Substrate

A reduced 3D continuum model of dynamic piezoelectricity in a thin-film surface-bonded to the substrate/host is presented in this article. While employing large area flexible thin piezoelectric films for novel applications in device/diagnostics, the feasibility of the proposed model in sensing the surface and/or sub-surface defects is demonstrated through simulations - which involve metallic beams with cracks and composite beam with delaminations of various sizes. We have introduced a set of electrical measures to capture the severity of the damage in the existing structures. Characteristics of these electrical measures in terms of the potential difference and its spatial gradients are illustrated in the time domain. Sensitivity studies of the proposed measures in terms of the defected areas and their region of occurence relative to the sensing film are reported. The simulations' results for electrical measures for damaged hosts/substrates are compared with those due to undamaged hosts/substrates, which show monotonicity with high degree of sensitivity to variations in the damage parameters.

A blind indic script recognizer for multi-script documents

We report a hierarchical blind script identifier for 11 different Indian scripts. An initial grouping of the 11 scripts is accomplished at the first level of this hierarchy. At the subsequent level, we recognize the script in each group. The various nodes of this tree use different feature-classifier combinations. A database of 20,000 words of different font styles and sizes is collected and used for each script. Effectiveness of Gabor and Discrete Cosine Transform features has been independently, evaluated using nearest neighbor linear discriminant and support vector machine classifiers. The minimum and maximum accuracies obtained, using this hierarchical mechanism, are 92.2% and 97.6%, respectively.

High field electrical switching behavior of Ge10Se90-xTlx glasses

Electrical Switching Studies on bulk Ge10Se90-xTlx ( 15 <= x <= 34) glasses have been undertaken to examine the type of switching, composition and thickness dependence of switching voltages. Unlike Ge-Se-Tl thin films which exhibit memory switching, the bulk Ge10Se90-xTlx glasses are found to exhibit threshold type switching with fluctuations seen in their current-voltage (I-V) characteristics. Further, it is observed that the switching voltages (V-T) of Ge10Se90-xTlx glasses decrease with the increase in the Tl concentration. An effort has been made to understand the observed composition dependence on the basis of nature of bonding of Tl atoms and a decrease in the chemical disorder with composition. In addition. the network connectivity and metallicity factors also contribute for the observed decrease in the switching voltages of Ge10Se90-xTlx glasses with Tl addition. It is also interesting to note that the composition dependence of switching voltages of Ge10Se90-xTlx glasses exhibit a small Cusp around the composition x = 22. which is understood on the basis of a thermally reversing window in this system in the composition range 22 <= x <= 30. The thickness dependence of switching voltages has been found to provide an insight about the type of switching mechanism involved in these samples. (C) 2009 Elsevier B.V. All rights reserved

Cost-efficient virtual machine management in data centers

Virtual Machine (VM) management is an obvious need in today's data centers for various management activities and is accomplished in two phases— finding an optimal VM placement plan and implementing that placement through live VM migrations. These phases result in two research problems— VM placement problem (VMPP) and VM migration scheduling problem (VMMSP). This research proposes and develops several evolutionary algorithms and heuristic algorithms to address the VMPP and VMMSP. Experimental results show the effectiveness and scalability of the proposed algorithms. Finally, a VM management framework has been proposed and developed to automate the VM management activity in cost-efficient way.

Effect of indium doping on the electrical switching behaviour of Ge-Te glasses

Bulk Ge15Te85-xInx (1 <= x <= 11) series of glasses have been found to exhibit a threshold switching behaviour for an input current of 2 mA. An initial decrease is seen in the switching voltages (V-T) with the addition of indium, which is due to the higher metallicity of indium. An increase is seen in V-T above 3 at.% of indium, which proceeds until 8 at.%, with a change in slope (lower to higher) seen around 7 at.%. Beyond x = 8, a reversal in trend is exhibited in the variation of V-T, with a well-defined minimum around x = 9 at.%. Based on the composition dependence of V-T, it is proposed that Ge15Te85-xInx glasses exhibit an extended rigidity percolation threshold. The composition, x = 3, at which the V-T starts to increase and the composition, x = 7, at which a slope change is exhibited correspond to the onset and completion, respectively, of the extended stiffness transition. Thermal studies and photoconductivity e85-xInx glasses. In addition, the minimum seen in V-T at x = 9 is associated with the chemical threshold (CT) of this glassy system.

Electrical switching and in situ Raman scattering studies on the set-reset processes in Ge-Te-Si glass

Bulk Ge15Te83Si2 glass has been found to exhibit memory-type switching for 1 mA current with a threshold electric field of 7.3 kV/cm. The electrical set and reset processes have been achieved with triangular and rectangular pulses, respectively, of 1 mA amplitude. In situ Raman scattering studies indicate that the degree of disorder in Ge15Te83Si2 glass is reduced from off to set state. The local structure of the sample under reset condition is similar to that in the off state. The Raman results are consistent with the switching results which indicate that the Ge15Te83Si2 glass can be set and reset easily. (C) 2007 American Institute of Physics.

Electrical Properties of Thermal Evaporated Cd1−xMnxS Nanocrystalline Films

Thin films of Cd1−xMnxS (0<=x<=0.5) were deposited on glass substrates by thermal evaporation. All the films were deposited at 300 K and annealed at 373, 473, and 573 K for 1 h in a high vacuum in the range 10−4 Pa. The as-deposited and the annealed films were characterized for composition, structure, and microstructure by using energy-dispersive X-ray, X-ray diffraction, scanning electron microscopy, and atomic force microscopy (AFM). The electrical properties were studied by Hall effect measurement. Electrical conductivity was studied in the temperature range 190–450 K. AFM studies showed that all the films were in nanocrystalline form with grain size varying in the range between 36 and 82 nm. Grain size studies showed a definite increase with annealing temperature. All the films exhibited wurtzite structure of the host material. The lattice parameter varied linearly with composition, following Vegard's law in the entire composition range. Grain size, electrical conductivity, Hall mobility, carrier concentration, and activation energy varied, exhibiting either maxima or minima at x=0.3.