18 resultados para Leadership Assessment and Selection

em Indian Institute of Science - Bangalore - Índia


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This paper presents a new approach for assessing power system voltage stability based on artificial feed forward neural network (FFNN). The approach uses real and reactive power, as well as voltage vectors for generators and load buses to train the neural net (NN). The input properties of the NN are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The performance of the trained NN is investigated on two systems under various voltage stability assessment conditions. Main advantage is that the proposed approach is fast, robust, accurate and can be used online for predicting the L-indices of all the power system buses simultaneously. The method can also be effectively used to determining local and global stability margin for further improvement measures.

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We propose a self-regularized pseudo-time marching strategy for ill-posed, nonlinear inverse problems involving recovery of system parameters given partial and noisy measurements of system response. While various regularized Newton methods are popularly employed to solve these problems, resulting solutions are known to sensitively depend upon the noise intensity in the data and on regularization parameters, an optimal choice for which remains a tricky issue. Through limited numerical experiments on a couple of parameter re-construction problems, one involving the identification of a truss bridge and the other related to imaging soft-tissue organs for early detection of cancer, we demonstrate the superior features of the pseudo-time marching schemes.

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Impacts of climate change on hydrology are assessed by downscaling large scale general circulation model (GCM) outputs of climate variables to local scale hydrologic variables. This modelling approach is characterized by uncertainties resulting from the use of different models, different scenarios, etc. Modelling uncertainty in climate change impact assessment includes assigning weights to GCMs and scenarios, based on their performances, and providing weighted mean projection for the future. This projection is further used for water resources planning and adaptation to combat the adverse impacts of climate change. The present article summarizes the recent published work of the authors on uncertainty modelling and development of adaptation strategies to climate change for the Mahanadi river in India.

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Phase diagram studies show that at ambient pressure only one ternary oxide, Cu(2)Ln(2)O(5), is stable in the ternary systems Cu-Ln-O (Ln = Tb, Dy, Ho, Er, Tm, Yb, Lu) at high temperatures. The crystal structure of Cu(2)Ln(2)O(5) can be described as a zig-zag arrangement of one-dimensional Cu2O5 chains parallel to-the a-axis with Ln atoms occupying distorted octahedral sites between these chains. Four sets of emf measurements on Gibbs energy of formation of Cu(2)Ln(2)O(5) (Ln = Tb, Dy, Ho, Er, Tm, Yb, Lu; Y) from component binary oxides and one set of high-temperature solution calorimetric data on enthalpy of formation have been reported in the literature. Except for Cu2Y2O5, the measured values for the Gibbs energies of formation of all other Cu(2)Ln(2)O(5) compounds fall in a narrow band (+/-1 kJ mol(-1)) and indicate a regular increase in stability with decreasing ionic radius of the lanthanide ion. The values for the second law enthalpy of formation, derived from the temperature dependence of emf obtained in different studies, show larger differences, as high as 25 kJ mol(-1) for Cu2Tm2O5. Though associated with an uncertainty of +/-4 kJ mol(-1), the calorimetric measurements help to identify the best set of emf data. The trends in thermodynamic data correlate well with the global instability index (GII) based on the overall deviation from the valence sum rule. Low values for the index calculated from crystallographic information indicate higher stability. Higher values are indicative of the larger stress in the structure.

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The use of energy harvesting (EH) nodes as cooperative relays is a promising and emerging solution in wireless systems such as wireless sensor networks. It harnesses the spatial diversity of a multi-relay network and addresses the vexing problem of a relay's batteries getting drained in forwarding information to the destination. We consider a cooperative system in which EH nodes volunteer to serve as amplify-and-forward relays whenever they have sufficient energy for transmission. For a general class of stationary and ergodic EH processes, we introduce the notion of energy constrained and energy unconstrained relays and analytically characterize the symbol error rate of the system. Further insight is gained by an asymptotic analysis that considers the cases where the signal-to-noise-ratio or the number of relays is large. Our analysis quantifies how the energy usage at an EH relay and, consequently, its availability for relaying, depends not only on the relay's energy harvesting process, but also on its transmit power setting and the other relays in the system. The optimal static transmit power setting at the EH relays is also determined. Altogether, our results demonstrate how a system that uses EH relays differs in significant ways from one that uses conventional cooperative relays.

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A standardized in-house reference extract from the pollen of Parthenium hysterophorus, which is responsible for the high incidence of allergic rhinitis in India, was generated and examined by skin test, radio-allergosorbent test inhibition and isoelectric focusing. Parthenium reference allergen discs and positive reference serum were also generated. These reference reagents could not only be used for the quantitation of Parthenium-specific IgE in the sera of rhinitis patients but also for the evaluation of allergenic activity (relative potency and lot-to-lot variation) of different batches of Parthenium pollen.

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Fundamental studies on a compact trapped vortex combustor indicate that cavity injection strategies play a major role on flame stability. Detailed experiments indicate that blow-out occurs for a certain range of cavity air flow velocities. An unsteady RANS-based reacting flow simulation tool has been utilized to study the basic dynamics of cavity vortex for various flow conditions. The phenomenon of flame blow-out at certain intermediate cavity air velocities is explained on the basis of transition from a cavity-stabilized mode to an opposed flow stagnation mode. A novel strategy is proposed for achieving flame stability at all conditions. This involves using a flow guide vane in the path of the main flow to direct a portion of the main flow into the cavity. This seems to result in a desirable dual vortex structure, i.e., a small clockwise vortex behind the vane and large counterclockwise vortex in the cavity. Experimental results show stable flame at all flow conditions with the flow guide vane, and pressure drop is estimated to be within acceptable limits. Cold flow simulations show self-similar velocity profiles for a range of main inlet velocities, and high reverse velocity ratios (-0.3) are observed. Such a high-velocity ratio in the reverse flow shear layer profile leads to enhanced production of turbulence imperative to compact combustors. Reacting flow simulations show even higher reverse velocity ratios (above -0.7) due to flow acceleration. The flame is observed to be stable, even though minor shear layer oscillations are present in the form of vortex shedding. Self-similarity is also observed in reacting flow temperature profiles at combustor exit over the entire range of the mainstream velocity. This indicates that the present configuration holds a promise of delivering robust performance invariant of the flow operating conditions.

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Classification of a large document collection involves dealing with a huge feature space where each distinct word is a feature. In such an environment, classification is a costly task both in terms of running time and computing resources. Further it will not guarantee optimal results because it is likely to overfit by considering every feature for classification. In such a context, feature selection is inevitable. This work analyses the feature selection methods, explores the relations among them and attempts to find a minimal subset of features which are discriminative for document classification.

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In this paper, we report a breakthrough result on the difficult task of segmentation and recognition of coloured text from the word image dataset of ICDAR robust reading competition challenge 2: reading text in scene images. We split the word image into individual colour, gray and lightness planes and enhance the contrast of each of these planes independently by a power-law transform. The discrimination factor of each plane is computed as the maximum between-class variance used in Otsu thresholding. The plane that has maximum discrimination factor is selected for segmentation. The trial version of Omnipage OCR is then used on the binarized words for recognition. Our recognition results on ICDAR 2011 and ICDAR 2003 word datasets are compared with those reported in the literature. As baseline, the images binarized by simple global and local thresholding techniques were also recognized. The word recognition rate obtained by our non-linear enhancement and selection of plance method is 72.8% and 66.2% for ICDAR 2011 and 2003 word datasets, respectively. We have created ground-truth for each image at the pixel level to benchmark these datasets using a toolkit developed by us. The recognition rate of benchmarked images is 86.7% and 83.9% for ICDAR 2011 and 2003 datasets, respectively.

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In this letter, we analyze the end-to-end average bit error probability (ABEP) of space shift keying (SSK) in cooperative relaying with decode-and-forward (DF) protocol, considering multiple relays with a threshold based best relay selection, and selection combining of direct and relayed paths at the destination. We derive an exact analytical expression for the end-to-end ABEP in closed-form for binary SSK, where analytical results agree with simulation results. For non-binary SSK, approximate analytical and simulation results are presented.

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With the progress in modern technological research, novel biomaterials are being largely developed for various biomedical applications. Over the past two decades, most of the research focuses on the development of a new generation of bioceramics as substitutes for hard tissue replacement. In reference to their application in different anatomical locations of a patient, newly developed bioceramic materials can potentially induce a toxic/harmful effect to the host tissues. Therefore, prior to clinical testing, relevant biochemical screening assays are to be performed at the cellular and molecular level, to address the issues of biocompatibility and long term performance of the implants. Along with testing strategies in the bulk material toxicity, a detailed evaluation should also be conducted to determine the toxicity of the wear products of the potential bioceramics. This is important as the bioceramics are intended to be implanted in patients with longer life expectancy and notwithstanding, the material will eventually release finer (mostly nanosized) sized debris particles due to continuous wear at articulating surfaces in the hostile corrosive environment of the human body. The wear particulates generated from a biocompatible bioceramic may act in a different way, inducing early/late aseptic loosening at the implant site, resulting in osteolysis and inflammation. Hence, a study on the chronic effects of the wear particulates, in terms of local and systemic toxicity becomes the major criteria in the toxicity evaluation of implantable bioceramics. In this broad perspective, this article summarizes some of the currently used techniques and knowledge in assessing the in vitro and in vivo cytotoxicity and genotoxicity of bioceramic implant materials. It also addresses the need to conduct a broad evaluation before claiming the biocompatibility and clinical feasibility of any new biomaterial. This review also emphasizes some of the case studies based on the experimental designs that are currently followed and its importance in the context of clinical applications.

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In an underlay cognitive radio (CR) system, a secondary user can transmit when the primary is transmitting but is subject to tight constraints on the interference it causes to the primary receiver. Amplify-and-forward (AF) relaying is an effective technique that significantly improves the performance of a CR by providing an alternate path for the secondary transmitter's signal to reach the secondary receiver. We present and analyze a novel optimal relay gain adaptation policy (ORGAP) in which the relay is interference aware and optimally adapts both its gain and transmit power as a function of its local channel gains. ORGAP minimizes the symbol error probability at the secondary receiver subject to constraints on the average relay transmit power and on the average interference caused to the primary. It is different from ad hoc AF relaying policies and serves as a new and fundamental theoretical benchmark for relaying in an underlay CR. We also develop a near-optimal and simpler relay gain adaptation policy that is easy to implement. An extension to a multirelay scenario with selection is also developed. Our extensive numerical results for single and multiple relay systems quantify the power savings achieved over several ad hoc policies for both MPSK and MQAM constellations.

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In a system with energy harvesting (EH) nodes, the design focus shifts from minimizing energy consumption by infrequently transmitting less information to making the best use of available energy to efficiently deliver data while adhering to the fundamental energy neutrality constraint. We address the problem of maximizing the throughput of a system consisting of rate-adaptive EH nodes that transmit to a destination. Unlike related literature, we focus on the practically important discrete-rate adaptation model. First, for a single EH node, we propose a discrete-rate adaptation rule and prove its optimality for a general class of stationary and ergodic EH and fading processes. We then study a general system with multiple EH nodes in which one is opportunistically selected to transmit. We first derive a novel and throughput-optimal joint selection and rate adaptation rule (TOJSRA) when the nodes are subject to a weaker average power constraint. We then propose a novel rule for a multi-EH node system that is based on TOJSRA, and we prove its optimality for stationary and ergodic EH and fading processes. We also model the various energy overheads of the EH nodes and characterize their effect on the adaptation policy and the system throughput.

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Sandalwood is an economically important aromatic tree belonging to the family Santalaceae. The trees are used mainly for their fragrant heartwood and oil that have immense potential for foreign exchange. Very little information is available on the genetic diversity in this species. Hence studies were initiated and genetic diversity estimated using RAPD markers in 51 genotypes of Santalum album procured from different geographcial regions of India and three exotic lines of S. spicatum from Australia. Eleven selected Operon primers (10mer) generated a total of 156 consistent and unambiguous amplification products ranging from 200bp to 4kb. Rare and genotype specific bands were identified which could be effectively used to distinguish the genotypes. Genetic relationships within the genotypes were evaluated by generating a dissimilarity matrix based on Ward's method (Squared Euclidean distance). The phenetic dendrogram and the Principal Component Analysis generated, separated the 51 Indian genotypes from the three Australian lines. The cluster analysis indicated that sandalwood germplasm within India constitutes a broad genetic base with values of genetic dissimilarity ranging from 15 to 91 %. A core collection of 21 selected individuals revealed the same diversity of the entire population. The results show that RAPD analysis is an efficient marker technology for estimating genetic diversity and relatedness, thereby enabling the formulation of appropriate strategies for conservation, germplasm management, and selection of diverse parents for sandalwood improvement programmes.

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An opportunistic, rate-adaptive system exploits multi-user diversity by selecting the best node, which has the highest channel power gain, and adapting the data rate to selected node's channel gain. Since channel knowledge is local to a node, we propose using a distributed, low-feedback timer backoff scheme to select the best node. It uses a mapping that maps the channel gain, or, in general, a real-valued metric, to a timer value. The mapping is such that timers of nodes with higher metrics expire earlier. Our goal is to maximize the system throughput when rate adaptation is discrete, as is the case in practice. To improve throughput, we use a pragmatic selection policy, in which even a node other than the best node can be selected. We derive several novel, insightful results about the optimal mapping and develop an algorithm to compute it. These results bring out the inter-relationship between the discrete rate adaptation rule, optimal mapping, and selection policy. We also extensively benchmark the performance of the optimal mapping with several timer and opportunistic multiple access schemes considered in the literature, and demonstrate that the developed scheme is effective in many regimes of interest.