Indian Institute of Technology Madras

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  • Publication
    Premature Deindustrialisation and Income Inequality Dynamics: Evidence from Middle-Income Economies
    (01-01-2023)
    Ravindran, Rekha
    ;
    Babu, M. Suresh
    The structural transformation path in most developing economies follows an employment shift towards service activities, skipping an industrialisation phase. In this paper, we explore how this premature deindustrialisation trend affects the inclusive growth trajectory of middle-income economies. Considering the trends in manufacturing employment and value-added share, we identify premature deindustrialisation phases in economies. We apply panel fixed-effects and bootstrap-corrected dynamic fixed-effects models to empirically examine the relationship between premature deindustrialisation and income inequality. Our findings suggest that income inequality rises with premature deindustrialisation if the displaced workers are absorbed into market services (especially with employment movement towards non-business market services such as trade, transport, hotels, and accommodation). In contrast, if non-market services (such as education and health) or business services (such as banking and financial services) are the dominant employment provider, it helps to reduce income inequality even in the presence of premature deindustrialisation.
  • Publication
    CIAMS: clustering indices-based automatic classification model selection
    (01-01-2023)
    Santhiappan, Sudarsun
    ;
    Shravan, Nitin
    ;
    Ravindran, Balaraman
    Classification model selection is a process of identifying a suitable model class for a given classification task on a dataset. Traditionally, model selection is based on cross-validation, meta-learning, and user preferences, which are often time-consuming and resource-intensive. The performance of any machine learning classification task depends on the choice of the model class, the learning algorithm, and the dataset’s characteristics. Our work proposes a novel method for automatic classification model selection from a set of candidate model classes by determining the empirical model fitness for a dataset based only on its clustering indices. Clustering Indices measure the ability of a clustering algorithm to induce good-quality neighborhoods with similar data characteristics. We propose a regression task for a given model class, where the clustering indices of a given dataset form the features and the dependent variable represents the expected classification performance. We compute the dataset clustering indices and directly predict the expected classification performance using the learned regressor for each candidate model class to recommend a suitable model class for dataset classification. We evaluate our model selection method through cross-validation with 60 publicly available binary class datasets and show that our top3 model recommendation is accurate for over 45 of 60 datasets. We also propose an end-to-end Automated ML system for data classification based on our model selection method. We evaluate our end-to-end system against popular commercial and noncommercial Automated ML systems using a different collection of 25 public domain binary class datasets. We show that the proposed system outperforms other methods with an excellent average rank of 1.68.
  • Publication
    Secret Image Sharing Schemes: A Comprehensive Survey
    (01-01-2023)
    Saha, Sanchita
    ;
    Chattopadhyay, Arup Kumar
    ;
    Barman, Anup Kumar
    ;
    Nag, Amitava
    ;
    Nandi, Sukumar
    The safeguarding of digitized data against unwanted access and modification has become an issue of utmost importance as a direct result of the rapid development of network technology and internet applications. In response to this challenge, numerous secret image sharing (SIS) schemes have been developed. SIS is a method for protecting sensitive digital images from unauthorized access and alteration. The secret image is fragmented into a large number of arbitrary shares, each of which is designed to prevent the disclosure of any information to the trespassers. In this paper, we present a comprehensive survey on SIS schemes along with their pros and cons. We review various existing verifiable secret image sharing (VSIS) schemes that are immune to different types of cheating. We have identified various aspects of developing secure and efficient SIS schemes. In addition to that, a comparison and contrast of several SIS methodologies based on various properties is included in this survey work.We also highlight some of the applications based on SIS. Finally, we present open challenges and future directions in the field of SIS.
  • Publication
    CERAMICS: METALLURGY OF CERAMIC CUTTING TOOLS
    (01-01-2023)
    Senthil Kumar, S. B.
    ;
    Krishnamurthy, R.
    ;
    Gokularathnam, C. V.
    Recent developments in ceramics have found application in high performance structural components such as cutting tools. Today, the development of this group tends to oxidic mixed ceramics, also called dispersion ceramics. These are combinations of Al2O3 + ZrO2(PSZ). With ZrO2 additions - very fine grained structures of high hardness with increased strength and toughness values can be obtained. The metastable tetragonal phase present in the partially stabilized zirconia can be made to undergo transformation to monoclinic phase on application of stress, thereby enhancing the fracture toughness (Kinetic stabilization). In general tool materials with finer grain size have shown a trend of greater strengths with more uniformity. In practice it has been found that a certain optimum grain size exists for each material and a narrow range around this optimum value is used for manufacturing. The role of grain size and microstructure on the strength of the sintered oxides are well established. Detailed knowledge of the microstructure of ceramic cutting tool materials is paramount to understand and control of tool wear. For example, with dispersion strengthened ceramic matrix (Al2O3-TiC) it is possible to deflect the propagating crack and thereby enhancing its toughness and consequently the performance. Thus knowledge of microstructure is the key to the control of mechanical and thermal properties and hence performance of ceramic cutting tools.
  • Publication
    Y2O3 electrodeposited TiO2 nanotube arrays as photoanode for enhanced photoelectrochemical water splitting
    (01-01-2023)
    Sharma, Shuchi
    ;
    Shanmugam, Ramasamy
    ;
    Harikrishna, R. B.
    ;
    Prasad, U.
    ;
    Ranga Rao, G.
    ;
    Kannan, A. M.
    Y2O3 deposited TiO2 nanotubes (Y-TNTs) are investigated as photoanodes for efficient photoelectrochemical water splitting. Y2O3 is electrodeposited on TiO2 nanotubes for 5–15 min. The physicochemical and optical properties of Y-TNTs reveal that Y2O3 anchored on the TNTs enhances the visible light absorption. The Y-TNTs show good photocurrent response compared to pristine TNTs. Y2O3 deposition for 10 min on TNTs produces highest photocurrent of 609 μA cm−2 at 1.23 VRHE. Presence of Y2O3 increases the lifetime of the charge carriers as revealed by the Nyquist plot analysis and Mott-Schottky analysis. Y-TNTs-10 min sample shows 2.75 times higher photoconversion efficiency compared to pristine TNTs. Computational analysis shows that Y–TiO2 has negative free energy of adsorption for OER intermediates as compared to bare TiO2 which has positive values. The rare earth metal electrodeposition on TiO2 nanotubes is another approach to improve the photoelectrochemical water splitting activity without distorting the nanotube structure.