Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

Traditionally, kernel methods rely on the representer theorem which states that the solution to a learning problem is obtained as a linear combination of the data mapped into the reproducing kernel Hilbert space (RKHS). While elegant from theoretical point of view, the theorem is prohibitive for algorithms' scalability to large datasets and the interpretability of the learned function. In this paper, instead of using the traditional representer theorem, we propose to search for a solution in RKHS that has a pre-image decomposition in the original data space, where the elements don't necessarily correspond to the elements in the training set. Our gradient-based optimisation method then hinges on optimising over possibly sparse elements in the input space and enables us to obtain a kernel-based model with both primal and dual sparsity. We give theoretical justification on the proposed method's generalization ability via a Rademacher bound. Our experiments demonstrate a better scalability and interpretability with accuracy on par with the traditional kernel-based models.

World University root node

Department of Data Science

arXiv preprint arXiv:2108.

Learning primal-dual sparse kernel machines

Ovchinnikov postulated the possibility of ferromagnetism in organic compounds having a mixed density of sp 3 and sp 2 carbon atoms. Such systems provide an interesting avenue for exploring magnetism in the absence of the quintessential d- and f-block elements as ingredients. As graphene oxide (GO) and its derivatives naturally possess a mixture of sp 3 and sp 2 carbon atoms, it is pertinent to look at them as potential candidates for Ovchinnikov ferromagnetism. We have looked at the evolution of magnetic property in a series of GO samples with a gradual increase in the degree of oxidation and hence the sp 3/sp 2 fraction. Starting with a GO sample with a high sp 3/sp 2 ratio, we utilize chemical reduction technique to prepare another set of reduced graphene oxide (rGO) samples. Magnetization measurements on these samples further illustrate the importance of sp 3/sp 2 fraction on magnetic behavior suggesting GO and its derivatives as a potential Ovchinnikov ferromagnet candidate. The evolution of magnetic moment with sp 3/sp 2 carbons can be utilized in carbon based spintronic applications. © 2021 IOP Publishing Ltd.

Department of Physics

Journal of Physics Condensed Matter

Graphene oxide and its derivatives as potential Ovchinnikov ferromagnets

Selective laser melting (SLM) is an emerging additive manufacturing (AM) technology for fabrication of complex lightweight components along with improved mechanical properties. However, the properties are highly influenced by the continual heating and cooling during deposition, variation in local temperature, size, and shape of melt pool, and solidification growth rate. Therefore, postprocessing is very often required to control various properties of additive manufactured components. The present work investigates the influence of various postprocessing methods such as heat treatment and electric discharge alloying (EDA) on ambient and elevated temperature wear behavior of selective laser melted AlSi10Mg alloy and compared with its tribological behavior with cast AlSi10Mg. The dry wear tests were conducted using a pin on disk (POD) tribometer with EN-31 as counter body. The EDA treated SLM AlSi10Mg showed the least wear-rate and coefficient of friction (COF) at both ambient and elevated temperatures (1.05×10-4 mm3/Nm and 0.434 and 3.12× 10-5 mm3/Nm and 0.531, respectively) due to its higher hardness (189.8 HV) as compared with other samples. The wear-rate and COF of cast specimen are found to be highest among all specimens at both ambient and elevated temperatures (1.34 ×10-4 mm3/Nm and 0.528 and 4.49× 10-5 mm3/Nm and 0.724, respectively). Lower wear-rate and higher COF are observed at elevated temperature due to the excessive formation of wear-resistant oxides (Al2O3, SiO2, and MgO) and glaze layers for all samples compared with ambient temperature wear behaviors of its counterparts. Abrasive wear, adhesive wear, oxidation wear, and surface delamination are the prominent wear mechanisms observed for ambient and elevated temperatures for all the specimens. Copyright © 2021 by ASME.

Department of Mechanical Engineering

Journal of Tribology

Effect of heat treatment and electric discharge alloying on the tribological performance of selective laser melted Alsi10mg

Fabrication of deep holes (depth to diameter ratio >10) using electrical discharge drilling (EDD) has gained momentum in the areas of aerospace, automotive and biomedical industries. However, formation of recirculation zones in flushing channel causes accumulation of debris particles at higher depths of drilling. This leads to secondary discharges within the flushing channel resulting in excessive tool wear, dimensional inaccuracy and hole tapering. The present paper proposes a novel tool geometry having orifices at the bottom end of tool electrode with an aim to improve debris evacuation. The effectiveness of proposed method is established through CFD simulations and experiments. © 2021 CIRP

CIRP Annals

Novel EDM deep hole drilling strategy using tubular electrode with orifice

The eternal vertex cover (EVC) problem is to compute the minimum number of guards to be placed on the vertices of a graph so that any sequence of attacks on its edges can be defended by dynamically reconfiguring the guards. The problem is NP-hard in general and polynomial time algorithms are unknown even for simple graph classes like cactus graphs and bipartite graphs. A major difficulty is that only few lower bounds, other than the trivial lower bound of vertex cover, is known in general and the known bounds are too weak to yield useful results even for the graph classes mentioned above. We introduce the notion of substructure property in the context of the EVC problem and derive a new lower bounding technique for the problem based on the property. We apply the technique to cactus graphs and chordal graphs and obtain new algorithms for solving the eternal vertex cover problem in linear time for cactus graphs and quadratic time for a family of graphs that includes all chordal graphs and cactus graphs. © 2021 Elsevier B.V.

Department of Computer Science and Engineering

Theoretical Computer Science

A substructure based lower bound for eternal vertex cover number

In this paper we define and explore the analytic spread $\ell(\mathcal I)$ of a filtration in a local ring. We show that, especially for divisorial and symbolic filtrations, some basic properties of the analytic spread of an ideal extend to filtrations, even when the filtration is non Noetherian. We also illustrate some significant differences between the analytic spread of a filtration and the analytic spread of an ideal with examples. In the case of an ideal $I$, we have the classical bounds $\mbox{ht}(I)\le\ell(I)\le \dim R$. The upper bound $\ell(\mathcal I)\le \dim R$ is true for filtrations $\mathcal I$, but the lower bound is not true for all filtrations. We show that for the filtration $\mathcal I$ of symbolic powers of a height two prime ideal $\mathfrak p$ in a regular local ring of dimension three (a space curve singularity), so that $\mbox{ht}(\mathcal I) =2$ and $\dim R=3$, we have that $0\le \ell(\mathcal I)\le 2$ and all values of 0,1 and 2 can occur. In the cases of analytic spread 0 and 1 the symbolic algebra is necessarily non-Noetherian. The symbolic algebra is non-Noetherian if and only if $\ell(\mathfrak p^{(n)})=3$ for all symbolic powers of $\mathfrak p$ and if and only if $\ell(\mathcal I_a)=3$ for all truncations $\mathcal I_a$ of $\mathcal I$.

Department of Mathematics

arXiv preprint arXiv:2104.

Analytic Spread of Filtrations and Symbolic Algebras

Coarse Grained Reconfigurable Arrays (CGRAs) are emerging as energy efficient accelerators providing a high grade of flexibility in both academia and industry. However, with the recent advancements in algorithms and performance requirements of applications, supporting only integer and logical arithmetic limits the interest of classical/traditional CGRAs. In this paper, we propose a novel CGRA architecture and associated compilation flow supporting both integer and floating-point computations for energy efficient acceleration of DSP applications. Experimental results show that the proposed accelerator achieves a maximum of 4.61× speedup compared to a DSP optimized, ultra low power RISC-V based CPU while executing seizure detection, a representative of wide range of EEG signal processing applications with an area overhead of 1.9×. The proposed CGRA achieves a maximum of 6.5× energy efficiency compared to the single core CPU. While comparing the execution with the multi-core CPU with 8 cores, the proposed CGRA achieves up to 4.4× energy gain. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.

Journal of Signal Processing Systems

Floating Point CGRA based Ultra-Low Power DSP Accelerator

AGU Fall Meeting

Global Sensitivity Analysis of an Oil Spill Model: a Regularized Regression Approach

Calibration is an essential step that is involved in the application of process based distributed hydrological models. The calibration process focuses on improving the performance index values rather than improving the process dynamics. The poor process dynamics in the model reduces its predictive power. The current study proposes a modified calibration approach (MCA) for the Soil and Water Assessment Tool (SWAT) model, which helps to improve the process dynamics in model through constraining the parameters. The modified calibration method uses the association between physically interpretable SWAT model parameters as soft data for calibration. The proposed calibration approach is validated in the Little River Experimental Watershed, USA. The results indicate that the proposed calibration method improves the process representation and spatial prediction in the calibrated model compared to the standard calibration procedure based on streamflow data. © 2021 Elsevier Ltd