127 resultados para Labeling methods
em Indian Institute of Science - Bangalore - Índia
Resumo:
Scatter/Gather systems are increasingly becoming useful in browsing document corpora. Usability of the present-day systems are restricted to monolingual corpora, and their methods for clustering and labeling do not easily extend to the multilingual setting, especially in the absence of dictionaries/machine translation. In this paper, we study the cluster labeling problem for multilingual corpora in the absence of machine translation, but using comparable corpora. Using a variational approach, we show that multilingual topic models can effectively handle the cluster labeling problem, which in turn allows us to design a novel Scatter/Gather system ShoBha. Experimental results on three datasets, namely the Canadian Hansards corpus, the entire overlapping Wikipedia of English, Hindi and Bengali articles, and a trilingual news corpus containing 41,000 articles, confirm the utility of the proposed system.
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Structural Support Vector Machines (SSVMs) and Conditional Random Fields (CRFs) are popular discriminative methods used for classifying structured and complex objects like parse trees, image segments and part-of-speech tags. The datasets involved are very large dimensional, and the models designed using typical training algorithms for SSVMs and CRFs are non-sparse. This non-sparse nature of models results in slow inference. Thus, there is a need to devise new algorithms for sparse SSVM and CRF classifier design. Use of elastic net and L1-regularizer has already been explored for solving primal CRF and SSVM problems, respectively, to design sparse classifiers. In this work, we focus on dual elastic net regularized SSVM and CRF. By exploiting the weakly coupled structure of these convex programming problems, we propose a new sequential alternating proximal (SAP) algorithm to solve these dual problems. This algorithm works by sequentially visiting each training set example and solving a simple subproblem restricted to a small subset of variables associated with that example. Numerical experiments on various benchmark sequence labeling datasets demonstrate that the proposed algorithm scales well. Further, the classifiers designed are sparser than those designed by solving the respective primal problems and demonstrate comparable generalization performance. Thus, the proposed SAP algorithm is a useful alternative for sparse SSVM and CRF classifier design.
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Interaction of tetrathiafulvalene (TTF) and tetracyanoethylene (TCNE) with few-layer graphene samples prepared by the exfoliation of graphite oxide (EG), conversion of nanodiamond (DG) and arc-evaporation of graphite in hydrogen (HG) has been investigated by Raman spectroscopy to understand the role of the graphene surface. The position and full-width at half maximum of the Raman G-band are affected on interaction with TTF and TCNE and the effect is highest with EG and least with HG. The effect of TTF and TCNE on the 2D-band is also maximum with EG. The magnitude of interaction between the donor/acceptor molecules varies in the same order as the surface areas of the graphenes. (C) 2009 Published by Elsevier B. V.
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Conformational preferences of thiocarbonohydrazide (H2NNHCSNHNH2) in its basic and N,N′-diprotonated forms are examined by calculating the barrier to internal rotation around the C---N bonds, using the theoretical LCAO—MO (ab initio and semiempirical CNDO and EHT) methods. The calculated and experimental results are compared with each other and also with values for N,N′-dimethylthiourea which is isoelectronic with thiocarbonohydrazide. The suitability of these methods for studying rotational isomerism seems suspect when lone pair interactions are present.
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One difficulty in summarising biological survivorship data is that the hazard rates are often neither constant nor increasing with time or decreasing with time in the entire life span. The promising Weibull model does not work here. The paper demonstrates how bath tub shaped quadratic models may be used in such a case. Further, sometimes due to a paucity of data actual lifetimes are not as certainable. It is shown how a concept from queuing theory namely first in first out (FIFO) can be profitably used here. Another nonstandard situation considered is one in which lifespan of the individual entity is too long compared to duration of the experiment. This situation is dealt with, by using ancilliary information. In each case the methodology is illustrated with numerical examples.
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A comparison is made of the performance of a weather Doppler radar with a staggered pulse repetition time and a radar with a random (but known) phase. As a standard for this comparison, the specifications of the forthcoming next generation weather radar (NEXRAD) are used. A statistical analysis of the spectral momentestimates for the staggered scheme is developed, and a theoretical expression for the signal-to-noise ratio due to recohering-filteringrecohering for the random phase radar is obtained. Algorithms for assignment of correct ranges to pertinent spectral moments for both techniques are presented.
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Non-stationary signal modeling is a well addressed problem in the literature. Many methods have been proposed to model non-stationary signals such as time varying linear prediction and AM-FM modeling, the later being more popular. Estimation techniques to determine the AM-FM components of narrow-band signal, such as Hilbert transform, DESA1, DESA2, auditory processing approach, ZC approach, etc., are prevalent but their robustness to noise is not clearly addressed in the literature. This is critical for most practical applications, such as in communications. We explore the robustness of different AM-FM estimators in the presence of white Gaussian noise. Also, we have proposed three new methods for IF estimation based on non-uniform samples of the signal and multi-resolution analysis. Experimental results show that ZC based methods give better results than the popular methods such as DESA in clean condition as well as noisy condition.
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For the problem of speaker adaptation in speech recognition, the performance depends on the availability of adaptation data. In this paper, we have compared several existing speaker adaptation methods, viz. maximum likelihood linear regression (MLLR), eigenvoice (EV), eigenspace-based MLLR (EMLLR), segmental eigenvoice (SEV) and hierarchical eigenvoice (HEV) based methods. We also develop a new method by modifying the existing HEV method for achieving further performance improvement in a limited available data scenario. In the sense of availability of adaptation data, the new modified HEV (MHEV) method is shown to perform better than all the existing methods throughout the range of operation except the case of MLLR at the availability of more adaptation data.
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Fundamental investigations in ultrasonics in India date back to the early 20th century. But, fundamental and applied research in the field of nondestructive evaluation (NDE) came much later. In the last four decades it has grown steadily in academic institutions, national laboratories and industry. Currently, commensurate with rapid industrial growth and realisation of the benefits of NDE, the activity is becoming much stronger, deeper, broader and very wide spread. Acoustic Emission (AE) is a recent entry into the field of nondestructive evaluation. Pioneering efforts in India in AE were carried out at the Indian Institute of Science in the early 1970s. The nuclear industry was the first to utilise it. Current activity in AE in the country spans materials research, incipient failure detection, integrity evaluation of structures, fracture mechanics studies and rock mechanics. In this paper, we attempt to project the current scenario in ultrasonics and acoustic emission research in India.
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Abstract is not available.
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A comprehensive set of new configurations for the holographic simulation of a wide variety of mirrors is described. These holographically simulated mirrors (HSMs) have been experimentally realized and their imaging performance has been studied.
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Much progress in nanoscience and nanotechnology has been made in the past few years thanks to the increased availability of sophisticated physical methods to characterize nanomaterials. These techniques include electron microscopy and scanning probe microscopies, in addition to standard techniques such as X-ray and neutron diffraction, X-ray scattering, and various spectroscopies. Characterization of nanomaterials includes the determination not only of size and shape, but also of the atomic and electronic structures and other important properties. In this article we describe some of the important methods employed for characterization of nanostructures, describing a few case studies for illustrative purposes. These case studies include characterizations of Au, ReO3, and GaN nanocrystals; ZnO, Ni, and Co nanowires; inorganic and carbon nanotubes; and two-dimensional graphene.
Resumo:
Combustion is a complex phenomena involving a multiplicity of variables. Some important variables measured in flame tests follow [1]. In order to characterize ignition, such related parameters as ignition time, ease of ignition, flash ignition temperature, and self-ignition temperature are measured. For studying the propagation of the flame, parameters such as distance burned or charred, area of flame spread, time of flame spread, burning rate, charred or melted area, and fire endurance are measured. Smoke characteristics are studied by determining such parameters as specific optical density, maximum specific optical density, time of occurrence of the densities, maximum rate of density increase, visual obscuration time, and smoke obscuration index. In addition to the above variables, there are a number of specific properties of the combustible system which could be measured. These are soot formation, toxicity of combustion gases, heat of combustion, dripping phenomena during the burning of thermoplastics, afterglow, flame intensity, fuel contribution, visual characteristics, limiting oxygen concentration (OI), products of pyrolysis and combustion, and so forth. A multitude of flammability tests measuring one or more of these properties have been developed [2]. Admittedly, no one small scale test is adequate to mimic or assess the performance of a plastic in a real fire situation. The conditions are much too complicated [3, 4]. Some conceptual problems associated with flammability testing of polymers have been reviewed [5, 6].