Faculty Publications
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Item Electrospun PVDF-based composite nanofabrics: An emerging trend toward energy harvesting(Elsevier, 2021) Shetty, S.; Anandhan, S.Poly(vinylidene fluoride) (PVDF) has gained attention in energy-related applications, due to its ferroelectric, piezoelectric, and pyroelectric properties. PVDF is a semicrystalline fluoropolymer having different phase domains based on its chain conformations. The polar domains contribute to its ferroelectric and piezoelectric characteristics. Electrospinning is a facile nanofabrication technique used to produce ultrafine fibers that self-integrates into functional webs/nanofabrics. This chapter emphasizes the electrospinning/filler route to tune the electroactive properties of PVDF-based composite nanofabrics and their applicabilities toward energy-related systems. The influence of various fillers/additives on the structure, morphology, and electroactive response of PVDF composite nanofabrics, including their incorporation into energy-related systems, is described in detail. Understanding the interplay between the filler and PVDF matrix coupled with electrospinning could contribute toward the fabrication of scalable and practical energy systems. © 2021 Elsevier Inc.Item Robust two-way locking protocol for key exchange(2011) Shetty, S.; Hegde, S.; Tahiliani, M.P.Sharing of symmetric key between the sender and receiver for encryption and decryption is considered to be one of the major issues in the communication networks. It is due to the fact that the strength of cryptosystem depends not only on the strength of the key, but also on the underlying key exchange protocol. In this paper, we propose a Robust Two-way Locking Protocol which overcomes the drawback of Diffie-Hellman key exchange protocol in terms of flexibility provided to the sender for selecting the desired key. Moreover we demonstrate the applicability of the proposed protocol in TCP handshake and compare it with Secure TCP which is based on Diffie-Hellman (DH) key exchange protocol. Based on the simulation results it is observed that Robust Two-way Locking (RoToLo) Protocol incurs negligible overhead in the network while providing greater flexibility of key selection to the sender as compared to Secure TCP. © Springer-Verlag 2011.Item Electrodeposition of Sn-Ni alloy coatings and their characterization(Trans Tech Publications Ltd ttp@transtec.ch, 2015) Shetty, S.; Hegde, A.C.A new alkaline bath has been proposed for deposition of bright Sn-Ni alloy coatings on mild steel (MS). Depositions were carried out at different current densities (c.d.) and their corrosion behaviors were studied in 5% NaCl solution by electrochemical AC and DC methods. Sn-Ni coating, deposited at low c.d. i.e. at 1.0 A/dm2 was found to be the most corrosion resistant compared to those at other higher c.d., even up to 4.0 A/dm2. This least corrosion rate (CR) is attributed to high wt. % Sn in the deposit. Increase of CR at high c.d. range is due to decrease of wt. % Sn, explained by the observed anomalous type of codeposition, followed by the bath. Regardless of the deposition c.d., the bath developed bright coatings, inherent of Sn-Ni alloy. Experimental results are discussed taking in account of the phase structure, composition and surface morphology of the coatings, evidenced by X-ray diffraction (XRD), Energy Dispersive X-ray (EDX) and Scanning Electron Microscopy (SEM) analysis. © (2015) Trans Tech Publications, Switzerland.Item An exploratory analysis of rainfall: A case study on western ghats of India(IEOM Society ieom-society@iieom.org, 2018) Rao, P.S.B.; Shetty, S.; Umesh, P.; Shetty, A.In this study high resolution 0.250 ×0.250 (approximately 25Km×25Km) gridded daily rainfall data is used to analyze the effect of changing climate on distribution of rainfall in different topographical zones of Western Ghats (WG) of India over the period 1901-2013. The non parametric two tailed Mann- Kendall with Hamed and Rao's method of autocorrelation and Sen's slope estimator for obtaining magnitude of change over time period is used. The rainfall trend in annual, monsoon and post-monsoon is increasing in state of Goa and Coastal region of Karnataka state and significantly decreasing in some part of Kerala and Maharashtra state. Winter season rainfall has seen a declined trend in southern part of the study area and in high elevated region of Kerala state. Even the mean rainfall over the study area is declining from 1951-1960 with disturbance in alternate sequence of flood and drought year from period 1990. The frequency of heavy rainfall events (65mm-124.4mm) are increasing in recent decades with 40-50% contribution from 2000-2013 in regions of Maharashtra state. The trend of heavy rainfall events are increasing in West Coast of India at 5% significance level with no trend in very heavy to extreme rainfall events (>124.5mm). © IEOM Society International.Item Experiential Learning of Strength of Materials and Fluid Mechanics using Virtual Labs(Institute of Electrical and Electronics Engineers Inc., 2020) Shetty, S.; Shetty, A.; Aishwarya Hegde, A.; Salian, A.B.; Akshaya; Umesh, P.; Gangadharan, K.V.Massive Open Online Courses (MOOCs) have revolutionized the teaching and learning process. It provides personalized learning while being cost effective and highly scalable. Furthermore, the advancements in Information and Communication Technology (ICT) have made it possible to deploy high fidelity, interactive web applications that provide seamless learning experience. However, the paucity of synergetic and adequate instructional support has demanded the quest for interactivity in MOOCs. Virtual Labs, an initiative by Government of India, aims to provide an interactive web interface to perform laboratory experiments (besides theoretical understanding of the subject) without affecting the experiential learning that is otherwise gained in the actual laboratory. This paper describes the design and development of Virtual Labs for two fundamentals courses of Civil and Mechanical engineering: Strength of Material (SOM) and Fluid Mechanics (FM). Subsequently, the outcomes of this work are discussed by analyzing the data collected from past four years, which reveals that these labs are an useful means to provide easy, cost effective and scalable solutions for online experiential learning. © 2020 IEEE.Item Experiential Learning of Physio-Chemical and Bacteriological Properties of Water using Virtual Labs(Institute of Electrical and Electronics Engineers Inc., 2020) Shetty, S.; Shetty, A.; Aishwarya Hegde, A.; Salian, A.B.; Akshaya; Umesh, P.; Gangadharan, K.V.Virtual Labs, an initiative by the Government of India under the National Mission on Education through Information and Communication Technology (NMEICT), has revolutionized the teaching and learning process for laboratory courses in the science and engineering disciplines. The web-based laboratories provided by the Virtual Labs project enable personalized learning while being cost effective and highly scalable. This approach helps to quickly learn the fundamental concepts of science and engineering through virtual experimentation, fosters curiosity and innovation among students, and prevents laboratory hazards. In this paper, we describe the design and development of two web-based virtual laboratories that simulate the fundamental concepts of Civil Engineering and Environmental Engineering. The proposed virtual labs provide a detailed explanation of the experiments in the respective engineering domains, and reagents and apparatuses involved while performing the experiments. The outcomes of this work are evaluated by analyzing the feedback collected from the users of these virtual labs, which reveals that the labs are an useful means to provide easy, cost effective and scalable solutions for online experiential learning. © 2020 IEEE.Item Analysis and Prediction of Fantasy Cricket Contest Winners Using Machine Learning Techniques(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2021) Karthik, K.; S. Krishnan, G.S.; Shetty, S.; Bankapur, S.; Kolkar, R.; Ashwin, T.S.; Vanahalli, M.K.Cricket is one of the well-known sports across the world. The increasing interest of cricket in recent years resulted in different forms like T20, T10 from test and one day format. The craze of all these formats of cricket matches today has come into online fantasy cricket league games. Dream11 is one such app that is most popular in this context, along with many similar apps. Creating a dream team of 11 players from playing 11 of both teams involves skills, ideas and luck. Predicting a winner among all the joined contestants based on the previous historical data is a challenging task. In this paper, we used a feed-forward deep neural network (DNN) classifier for predicting the winning contestant for the top three positions in a fantasy league cricket contest. The performance of the DNN approach was compared against that of state-of-the-art machine learning approaches like k-nearest neighbours (KNN), logistic regression (LR), Naive Bayes (NB), random forest (RF), support vector machines (SVM) and in predicting the fantasy cricket contest winners. Among the methods used, DNN showed the best results for all three positions, showing its consistency in predicting the winners and outperforms the state-of-the-art machine learning classifiers by 13%, 8% and 9%, respectively, for first, second and third winning positions, respectively. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Lineament Extraction from Open-Source Digital Elevation Models: A Comparative Analysis(Institute of Electrical and Electronics Engineers Inc., 2021) Shetty, S.; Umesh, P.; Shetty, A.The extraction of lineaments from Digital Elevation Models plays an important role in inhospitable and inaccessible mountain forest areas. In this study, the lineaments extracted from different data acquisition techniques; stereo pairs (ALOS (30m), ASTER (30m), CARTOSAT (30m)), and InSAR (SRTM (30m, 90m), TanDEM-X (90m)) are compared. There is a quantifiable difference in the extracted lineaments from 30m and 90m resolution DEMs due to the different data acquisition methods and processing algorithms used. CARTOSAT provides a more number of lineaments than other DEMs. The length of the lineaments extracted is inversely proportional to the vertical accuracy of the DEM over the region. All the DEMs have a consistency in the orientation of the lineament extracted. The DEMs generated from stereo-images have shown higher lineament density than the DEMs acquired through the InSAR technique. This study shows the difference in the lineament extracted from the same resolution DEMs acquired through various acquisition techniques and helps in the selection of suitable DEM for lineament extraction in the dense forest area. © 2021 IEEE.Item Data Augmentation vs. Synthetic Data Generation: An Empirical Evaluation for Enhancing Radiology Image Classification(Institute of Electrical and Electronics Engineers Inc., 2023) Shetty, S.; Ananthanarayana, V.S.; Mahale, A.Radiology is a field of medicine dealing with diagnostic images to detect diseases for further treatment. Collecting and annotating diagnostic images like Magnetic Resonance Imaging (MRI) and X-Ray is a rigorous and time-consuming process. Deep Learning methods are widely utilized for disease classification and prediction from diagnostic images, but they demand substantial amounts of training data. Additionally, certain diseases are uncommon in large patient cohorts, posing difficulties in obtaining sufficient imaging samples to construct accurate deep learning models. Data augmentation techniques are commonly used to overcome this challenge of limited data. These techniques involve applying geometric transformations such as rotation, cropping, zooming, flipping, and other similar operations to the images to enlarge the dataset artificially. Another possible way of expanding the dataset is by synthesizing data to generate artificial medical images by mimicking the original images. This study presents RAD-DCGAN: A Deep Convolutional Generative Adversarial Network to produce high-resolution synthetic radiology images from the X-ray and MRI images collected from a private medical hospital (KMC Hospital, India). We aim to determine the most effective technique for enhancing the performance of radiology image classifiers by comparing and evaluating the proposed RAD-DCGAN with the standard data augmentation strategy. Our empirical evaluation, which involved eight standard deep learning models, demonstrated that deep learning classifiers trained on synthetic radiology data outperformed those trained on standard augmented data. The utilization of the RAD-DCGAN model for training and testing deep learning models on synthetic data has demonstrated a notable improvement of 4-5% in accuracy compared to conventional augmentation techniques. This signifies the state-of-the-art performance achieved by the RAD-DCGAN model in enhancing the accuracy of deep learning models. © 2023 IEEE.Item High-gain DC-DC converter with zero input ripple current : Design and Analysis*(Institute of Electrical and Electronics Engineers Inc., 2023) Mishra, S.; Shetty, S.; Vinatha Urundady, U.In this paper, a non-isolated high-gain dc-dc converter that utilizes switched-capacitor and switched-inductor (SC-SL) network is proposed and thoroughly analyzed. The proposed topology features a single switch and less number of passive elements as compared to recently emerged high-gain converters. The mathematical analysis of the proposed converter is carried out to find the converter voltage gain and stresses on power devices.The converter achieves a gain of nine times at 50% duty cycle with comparatively less voltage stress on power devices. Additionally, the converter encompasses the current mirror ripple cancellation circuit (CMRCC) to eliminate input current ripples. The converter is modelled and verified in continuous conduction mode(CCM) using MATLAB/SIMULINK. The obtained findings exhibit that the input current ripples are effectively eliminated by the CMRCC implementation. © 2023 IEEE.