Revisiting Low Resource Status of Indian Languages in Machine Translation

Indian language machine translation performance is hampered due to the lack of large scale multi-lingual sentence aligned corpora and robust benchmarks. Through this paper, we provide and analyse an automated framework to obtain such a corpus for Indian language neural machine translation (NMT) systems. Our pipeline consists of a baseline NMT system, a retrieval module, and an alignment module that is used to work with publicly available websites such as press releases by the government. The main contribution towards this effort is to obtain an incremental method that uses the above pipeline to iteratively improve the size of the corpus as well as improve each of the components of our system. Through our work, we also evaluate the design choices such as the choice of pivoting language and the effect of iterative incremental increase in corpus size. Our work in addition to providing an automated framework also results in generating a relatively larger corpus as compared to existing corpora that are available for Indian languages. This corpus helps us obtain substantially improved results on the publicly available WAT evaluation benchmark and other standard evaluation benchmarks.Comment: 10 pages, few figures, Preprint under revie

Eigen-profiles of spatio-temporal fragments for adaptive region-based tracking

We propose a novel space-time descriptor for region-based tracking which is very concise and efficient. The regions represented by covariance matrices within a temporal fragment, are used to estimate this space-time descriptor which we call the Eigenprofiles(EP). EP so obtained is used in estimating the Covariance Matrix of features over spatio-temporal fragments. The Second Order Statistics of spatio-temporal fragments form our target model which can be adapted for variations across the video. The model being concise also allows the use of multiple spatially overlapping fragments to represent the target. We demonstrate good tracking results on very challenging datasets, shot under insufficient illumination conditions

Covariance profiles: a signature representation for object sets

We consider the problem of extracting a signature representation of similar entities employing covariance descriptors. Covariance descriptors can efficiently represent objects and are robust to scale and pose changes. We posit that covariance descriptors corresponding to similar objects share a common geometrical structure which can be extracted through joint diagonalization. We term this diagonalizing matrix as the Covariance Profile (CP). CP can be used to measure the distance of a novel object to an object set through the diagonality measure. We demonstrate how CP can be employed on images as well as for videos, for applications such as face recognition and object-track clustering

Nanoflower, nanoplatelet and nanocapsule Mg(OH)(2) powders for adsorption of CO2 gas

The soft chemical synthesis of self-assembled magnesium hydroxide (Mg(OH)(2)) nanoplatelets with surface area as high as about 300 m(2) g(-1) was achieved in the present work. The nanopowders such as MHN, MHCl, MHBr were synthesized at similar to 30 A degrees C without using any catalyst or surfactant using, respectively, precursor solutions of Mg(NO3)(2), MgCl2, MgBr2 and characterized by XRD, BET surface area, BJH pore size analysis, FTIR, FE-SEM, TEM and EDX techniques. It was found that the MHN and MHCl nanopowders comprised of nanoflowers formed by self-assembly of nanoplatelets and porous nanoplatelets, while the MHBr nanopowders comprised of a random assembly of nanocapsules. The powders possessed the technologically important quality of reproducible CO2 adsorption at room temperature and its desorption at a relatively lower temperature of 75 A degrees C. Based on the experimental evidences, the mechanisms of various microstructure formations and CO2 adsorption mechanism were also proposed

Novel Growth Mechanisms of Self-assembled Mg(OH)2 Nanoplatelets

Here we report for the first time the time-dependent mechanisms of self assembly and growth of Mg(OH)2 nanoparticles. For this purpose, the nanopowders are obtained by a simple chemical precipitation route. To understand the route map of the growth process; the nanopowders are subsequently characterized by XRD, FTIR, BET, pore size distribution, FESEM and TEM analysis techniques. Based on the results obtained from aforesaid characterizations the mechanisms of self-assembly and nanoplatelets growth process as a function of reaction time are explained

Intelligently designed fly-ash based hybrid composites with very high hardness and Young's modulus

Currently, India generates annually about 112 million tones of fly ash (FA), as an industrial waste from thermal power plants. As part of the global journey to convert waste to wealth here we report the intelligent design based synthesis of FA based hybrid composites with spectacular improvement in Young's modulus and nanohardness. The novel design approach utilized alkali activation as well as simultaneous reinforcements of the porous FA matrix with a layered white china clay (WCC) and chopped E glass fiber. The developed materials were subsequently characterized by nanoindentation technique, pH measurement, alkali dissolution, FESEM, etc. techniques to evolve the structure-property correlation. The optimized design and optimal alkali activation lead to achievements of about 233% and 545% enhancements in Young's modulus and hardness, respectively. These results are rationalized in terms of chemical analysis, Si:Al ratio, presence of silicate network modifiers e.g., Na2O and CaO, microstructure, density, extent of polymerization due to alkali activation, processing condition and elastic recovery as well as the ratio of energy spent in elastic and plastic deformations during the nanoindentation processes. Finally, a schematic model is proposed to explain the experimental observations. (C) 2017 Elsevier Ltd. All rights reserved

Synthesis of mixed calcite-calcium oxide nanojasmine flowers

Here we report for the very first time a simple, inexpensive, room temperature synthesis method of formation of mixed calcite calcium oxide nanojasmines (CTCaONJs). The method involves chemical precipitation in aqueous medium at room temperature in open atmosphere in order to allow natural carbonation to occur. Aqueous solutions of calcium nitrate dihydrate (Ca(NO3)(2)center dot 2H(2)O) and sodium hydroxide are used as precursors. The nanopowder is characterized by the Fourier transform infrared (FTIR) spectrometry, X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and transmission electron microscopy (TEM), energy dispersive X-ray analysis (EDAX), BET (Brunauer-Emmett-Teller), BJH (Barrett-Joyner-Halenda) techniques. Optical properties of nanojasmines (NJs) were investigated by UV-vis spectroscopy. The powder has calcite as the major phase and calcium oxide as the minor phase. The crystallite size of calcite along (104) crystallographic direction is about 18 nm with a size strain of about 1.03%. The high (e.g., 8.8 m(2)g(-1)) surface area powder exhibits a mesoporous microstructure with 5-15 nm pore size. Further, it possesses a relatively higher optical band gap of 5.87 eV. The FESEM and TEM based evidences show that the CTCaONJ flowers mainly comprise of nanoplatelets made up of irregular nanorods and nanowires consisting of amorphous spherical nanoparticles. Based on these experimental evidences a qualitative model is proposed to explain the growth mechanism of the CTCaONJ flowers. (C) 2015 Elsevier Ltd and Techna Group S.r.l. All rights reserved