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

This paper presents a geometric framework for analysis of dynamics of flapping wing micro aerial vehicles (FWMAV) which achieve locomotion in the special Euclidean group SE(3) using internal shape changes. We review the special structure of the configuration manifold of such systems. This work addresses to extend the work in geometric locomotion to the aerial locomotion problem. Furthermore, there seems to be limited work in modelling of flapping wing bodies in a geometric framework. We derive the dynamic model of the FWMAV using Lagrangian reduction theory defined on symmetry groups. The reduction is achieved by applying Hamilton's variation principle on a reduced Lagrangian. The resultant dynamics is governed by the Euler-Poincare and Euler-Lagrange equations.

World University root node

Department of Electrical Engineering

arXiv preprint arXiv:1511.

A geometric approach to the dynamics of flapping wing micro aerial vehicles: Modelling and reduction

In this article, we consider a continuous-time state-dependent jump linear system (SDJLS), a kind of stochastic hybrid system, with the presence of uncertainties in system parameters. In SDJLS, we consider that the transition rates of the underlying random jump process depend on the state variable. In particular, we assume the transition rates to have different values across suitably defined sets to which the state of the system belongs, and address a problem of robust stability and stabilization analysis. We obtain sufficient conditions for robust stability and state-feedback stabilization in terms of linear matrix inequalities (LMIs). We validate the obtained sufficient robust stability and stabilization conditions with numerical examples. © 2015 Elsevier Ltd.

Nonlinear Analysis: Hybrid Systems

Robust stabilization of a class of state-dependent jump linear systems

Automatic Modulation Classification (AMC) is a essential component in Cognitive Radio (CR) for recognizing the modulation scheme. Many modulated signals manifest the property of cyclostationarity as a feature so it can be exploited for classification. In this paper, we study the performance of digital modulation classification technique based on the cy-clostationary features and different classifiers such as Neural Network, Support Vector Machine, k-Nearest Neighbor, Naive Bayes, Linear Discriminant Analysis and Neuro-Fuzzy classifier. In this study we considered modulations i.e. BPSK, QPSK, FSK and MSK for classification. All classification methods studied using performance matrix including classification accuracy and computational complexity (time). The robustness of these methods are studied with SNR ranging from 0 to 20dB. Based upon the result we found that combining cyclostationary features with Naive Bayes and Linear Discriminant Analysis classifiers leads to provide better classification accuracy with less computational complexity. © 2014 IEEE.

9th International Conference on Industrial and Information Systems, ICIIS 2014

Performance study of cyclostationary based digital modulation classification schemes

An automated noise-robust premature ventricular contraction (PVC) detection method is proposed based on the sparse signal decomposition, temporal features, and decision rules. In this Letter, the authors exploit sparse expansion of electrocardiogram (ECG) signals on mixed dictionaries for simultaneously enhancing the QRS complex and reducing the influence of tall P and T waves, baseline wanders, and muscle artefacts. They further investigate a set of ten generalised temporal features combined with decision-rule-based detection algorithm for discriminating PVC beats from non-PVC beats. The accuracy and robustness of the proposed method is evaluated using 47 ECG recordings from the MIT/BIH arrhythmia database. Evaluation results show that the proposed method achieves an average sensitivity of 89.69%, and specificity 99.63%. Results further show that the proposed decision-rule-based algorithm with ten generalised features can accurately detect different patterns of PVC beats (uniform and multiform, couplets, triplets, and ventricular tachycardia) in presence of other normal and abnormal heartbeats. © The Institution of Engineering and Technology 2015.

Healthcare Technology Letters

Robust detection of premature ventricular contractions using sparse signal decomposition and temporal features

Several methods have been proposed for detection and classification of power quality (PQ) disturbances using wavelet, Hilbert transform, Gabor transform, Gabor-Wigner transform, S transform, and Hilbert-Haung transform. This paper presents a new method for detection and classification of single and combined PQ disturbances using a sparse signal decomposition (SSD) on overcomplete hybrid dictionary (OHD) matrix. The method first decomposes a PQ signal into detail and approximation signals using the proposed SSD technique with an OHD matrix containing impulse and sinusoidal elementary waveforms. The output detail signal adequately captures morphological features of transients (impulsive and oscillatory) and waveform distortions (harmonics and notching). Whereas the approximation signal contains PQ features of fundamental, flicker, dc-offset, and short- and long-duration variations (sags, swells, and interruptions). Thus, the required PQ features are extracted from the detail and approximation signals. Then, a hierarchical decision-tree algorithm is used for classification of single and combined PQ disturbances. The proposed method is tested using both synthetic and microgrid simulated PQ disturbances. Results demonstrate the accuracy and robustness of the method in detection and classification of single and combined PQ disturbances under noiseless and noisy conditions. The method can be easily expanded for compressed sensing based PQ monitoring networks. © 2014 IEEE.

IEEE Transactions on Instrumentation and Measurement

Detection and classification of power quality disturbances using sparse signal decomposition on hybrid dictionaries

Voltage fed Dual Active Bridge (VF-DAB) is the simplest isolated bidirectional DC-DC converter topology with least number of high frequency tank elements. This paper addresses the issue of Phase Shift operated VF-DAB when used for energy storage applications due to their variable nature in terminal voltage based on the state of charge. Circulation currents and limitations in the softswitching range are the main drawbacks of VF-DAB when operated with phase shift control within the two active bridges and widely varying voltage at one port. This affect their overall efficiencies at low and mid loads. In this paper, a modification in VF-DAB is proposed which reduces the drawbacks of the conventional phase shift controlled DAB by having variable transformer turns ratio, thereby improving the efficiency of the overall converter at medium and light loads. The analysis and design guidelines for the proposed converter are briefly explained and validated with experimental results. © 2015 Korean Institute of Power Electronics.

9th International Conference on Power Electronics - ECCE Asia: "Green World with Power Electronics", ICPE 2015-ECCE Asia

Tap changing transformer based dual active bridge bi-directional DC-DC converter

Bilayer graphene subjected to perpendicular magnetic and electric fields displays a subtle competition between different symmetry-broken phases, resulting from an interplay between the internal spin and valley degrees of freedom. The transition between different phases is often identified by an enhancement of the conductance. Here, we propose that the enhanced conductance at the transition is due to the appearance of robust conducting edge states at domain walls between the two phases. We formulate a criterion for the existence of such conducting edge states at the domain walls. For example, for a spontaneously layer polarized state at filling factor ν=2, domain walls between regions of opposite polarization carry conducting edge modes. A microscopic analysis shows that lattice-scale interactions can favor such a layer polarized state. © 2015 American Physical Society.

Department of Physics

Fulltext

Physical Review B - Condensed Matter and Materials Physics

Spontaneous layer polarization and conducting domain walls in the quantum Hall regime of bilayer graphene

Fringe tracking and fringe order assignment have become the central topics of current research in digital photoelasticity. Isotropic points (IPs) appearing in low fringe order zones are often either overlooked or entirely missed in conventional as well as digital photoelasticity. We aim to highlight image processing for characterizing IPs in an isochromatic fringe field. By resorting to a global analytical solution of a circular disk, sensitivity of IPs to small changes in far-field loading on the disk is highlighted. A local theory supplements the global closed-form solutions of three-, four-, and six-point loading configurations of circular disk. The local theoretical concepts developed in this paper are demonstrated through digital image analysis of isochromatics in circular disks subjected to three- and four-point loads. © 2015 Society of Photo-Optical Instrumentation Engineers.

Department of Mechanical Engineering

Optical Engineering

Digital image analysis around isotropic points for photoelastic pattern recognition

Combinatorial Batch Codes (CBCs), replication-based variant of Batch Codes introduced by Ishai et al. in [IKOS04], abstracts the following data distribution problem: n data items are to be replicated among m servers in such a way that any k of the n data items can be retrieved by reading at most one item from each server with the total amount of storage over m servers restricted to N. Given parameters m, c, and k, where c and k are constants, one of the challenging problems is to construct c-uniform CBCs (CBCs where each data item is replicated among exactly c servers) which maximizes the value of n. In this work, we present explicit construction of c-uniform CBCs with Ω(mc − 1+ 1/ k) data items. The construction has the property that the servers are almost regular, i. e., number of data items stored in each server is in the range [nc/m −√n/2 ln(4m), nc/m +√n/2 ln(4m)]. The construction is obtained through better analysis and derandomization of the randomized construction presented in [IKOS04]. Analysis reveals almost regularity of the servers, an aspect that so far has not been addressed in the literature. The derandomization leads to explicit construction for a wide range of values of c (for given m and k) where no other explicit construction with similar parameters, i. e., with n = Ω(mc − 1+ 1/ k), is known. Finally, we discuss possibility of parallel derandomization of the construction. © Springer International Publishing Switzerland 2015.

Department of Computer Science and Engineering

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Derandomized construction of combinatorial batch codes

We consider the problem of recommending comment-worthy articles such as news and blog-posts. An article is defined to be comment-worthy for a particular user if that user is interested to leave a comment on it. We note that recommending commentworthy articles calls for elicitation of commenting-interests of the user from the content of both the articles and the past comments made by users. We thus propose to develop content-driven user profiles to elicit these latent interests of users in commenting and use them to recommend articles for future commenting. The difficulty of modeling comment content and the varied nature of users' commenting interests make the problem technically challenging. The problem of recommending comment-worthy articles is resolved by leveraging article and comment content through topic modeling and the co-commenting pattern of users through collaborative filtering, combined within a novel hierarchical Bayesian modeling approach. Our solution, Collaborative Correspondence Topic Models (CCTM), generates user profiles which are leveraged to provide a personalized ranking of comment-worthy articles for each user. Through these content-driven user profiles, CCTM effectively handle the ubiquitous problem of cold-start without relying on additional meta-data. The inference problem for the model is intractable with no off-the-shelf solution and we develop an effcient Monte Carlo EM algorithm. CCTM is evaluated on three real world data-sets, crawled from two blogs, ArsTechnica (AT) Gadgets (102,087 comments) and AT-Science (71,640 comments), and a news site, DailyMail (33,500 comments). We show average improvement of 14% (warm-start) and 18% (cold-start) in AUC, and 80% (warm-start) and 250% (cold-start) in Hit-Rank@5, over state of the art [1, 2]. © 2015 ACM.