Faculty Publications
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Item Automated versus Manual Approach of Web Application Penetration Testing(Institute of Electrical and Electronics Engineers Inc., 2020) Singh, N.; Meherhomji, V.; Chandavarkar, B.R.The main aim of this work is to find and explain certain scenarios that can demonstrate the differences in automated and manual approaches for penetration testing. There are some scenarios in which manual testing works better than automatic scripts/vulnerability scanners for finding security issues in web applications. In some other scenarios, the opposite may be true. The concepts of various web application vulnerabilities have been used for testing, including OWASP1Open Web Application Security Project; online community dedicated to web security Top 10, using both manual and automatic approaches. Automation tools and scripts have been used and tested to see what could potentially go wrong if attackers exploit such vulnerabilities. Also, certain scenarios have been used which determine whether one approach is better than the other for finding/detecting security issues in web applications. Finally, the work concludes by providing results in the form of pros-and-cons of both approaches, which it realises after carrying this out. © 2020 IEEE.Item Hybrid Model of Multifactor Analysis with RNN-LSTM to Predict Stock Price(Springer Science and Business Media Deutschland GmbH, 2022) Singh, N.; Mohan, B.R.; Naik, N.Prediction on the stock market is one of the most difficult tasks to do in real life. There are so many aspects on which the stock market depends—physical factors versus psychological, rational, and irrational behavior, etc. Proposed research work consists of different aspects on which stock markets are based on. It consists of three models to forecast a stock price on State Bank of India (SBI) stock data. In the current research, we proposed a hybrid model followed by recurrent neural network-long short-term memory (RNN-LSTM) to predict a next-day closing price of SBI. A hybrid model is the combination of two different aspects related to the prediction of stock price. The first technique used other companies’ stock data to predict the target company’s next-day closing price. Other companies lie in the same sector so that they are correlated to each other. For training and testing, we have used multilayer perceptron (MLP) regression model. It is a neural network model in deep learning. The second technique is to predict the stock price of an SBI company using historical data of the target company followed by the auto-regressive integrated moving average—gated recurrent unit (ARIMA-GRU) model. ARIMA-GRU model is a combined model which gives better accuracy for predicting stock price data. In the hybrid model, we take the result of both the models as an input. This paper aims to compare the proposed hybrid model with other two single-aspect models on which stock price depends and proves in terms of accuracy that the hybrid model of all aspects gives better results in comparison to single-aspect models. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Experimental Modal Analysis Using Impact Hammer Testing with Random Forest-Based Prediction of Magnetorheological Elastomer Dynamics(Institute of Physics, 2025) Shenoy, P.; Kamath, N.; Pawar, K.; Singh, N.; Soundarya; Afnan, S.; Mayya D, S.This study presents a novel integration of impact hammer-based experimental modal analysis with Random Forest Regression (RFR) to rapidly characterise the frequency-domain dynamic behaviour of Carbonyl Iron Particle (CIP)-based Magnetorheological Elastomers (MREs) under varying magnetic fields. Using only applied current and excitation frequency as input features, the RFR model predicts FRF amplitude, phase, and coherence with R2 values exceeding 0.96 across both low-frequency (0-70 Hz) and high-frequency (> 70 Hz) regimes. This hybrid experimental-computational framework significantly reduces the number of repeated tests required, enabling faster parametric studies and paving the way for real-time, AI-enhanced tuning of smart vibration isolation systems. © Published under licence by IOP Publishing Ltd.Item Defence applications of polymer nanocomposites(Defense Scientific Information and Documentation Centre, 2010) Kurahatti, R.V.; Surendranathan, A.O.; Kori, S.A.; Singh, N.; Kumar, A.V.R.; Srivastava, S.The potential opportunities promised by nanotechnology for enabling advances in defence technologies are staggering. Although these opportunities are likely to be realised over a few decades, many advantages are currently being explored, particularly for defence applications. This review provides an insight into the capabilities offered by nanocomposites which include smart materials, harder/lighter platforms, new fuel sources and storage as well as novel medical applications. It discusses polymer-based nanocomposite materials, nanoscale fillers and provides examples of the actual and potential uses of nanocomposite materials in defence with practical examples. © 2010, DESIDOC.Item Role of zirconia filler on friction and dry sliding wear behaviour of bismaleimide nanocomposites(2011) Kurahatti, R.V.; Surendranathan, A.O.; Srivastava, S.; Singh, N.; Ramesh Kumar, A.V.; Suresha, B.This paper discusses the friction and dry sliding wear behaviour of nano-zirconia (nano-ZrO2) filled bismleimide (BMI) composites. Nano-ZrO2 filled BMI composites, containing 0.5, 1, 5 and 10wt.% were prepared using high shear mixer. The influence of these particles on the microhardness, friction and dry sliding wear behaviour were measured with microhardness tester and pin-on-disc wear apparatus. The experimental results indicated that the frictional coefficient and specific wear rate of BMI can be reduced at rather low concentration of nano-ZrO2. The lowest specific wear rate of 4×10-6mm3/Nm was observed for 5wt.% nano-ZrO2 filled composite which is decreased by 78% as compared to the neat BMI. The incorporation of nano-ZrO2 particles leads to an increased hardness of BMI and wear performance of the composites shows good correlation with the hardness up to 5wt.% of filler loading. The results have been supplemented with scanning electron micrographs to help understand the possible wear mechanisms. © 2011 Elsevier Ltd.Item Role of nickel filler on friction and dry sliding wear behavior of bismaleimide nanocomposite(2011) Kurahatti, R.V.; Surendranathan, A.O.; Srivastava, S.; Singh, N.; Ramesh Kumar, A.V.; Kori, S.A.Nano-sized metal particles filled polymer composites are finding numerous tribological applications in recent years. In the present work, the matrix properties were investigated by introducing nickel (Ni) nanoparticles (60-100 nm, weight fractions of 0.5-10 %) into a bismaleimide (BMI) resin. The influence of these particles on the microhardness, friction and dry sliding wear behavior were measured using microhardness tester, pin-ondisc wear set up. The experimental results indicated that the coefficient of friction and the specific wear rate (SWR) of BMI resin can be reduced at rather low weight fraction of Ni particles. The lowest SWR of 9 ×10 -6 mm 3/Nm (i.e. 50% lower than the value of neat BMI) was observed for the nanocomposite with Ni weight fraction of 1%. The incorporation of Ni particles leads to an increased hardness of BMI and the wear performance of the composites shows good correlation with the hardness. The results have been supplemented with scanning electron micrographs to help understand the possible wear mechanisms. © 2011 CAFET-INNOVA TECHNICAL SOCIETY.Item A compact and efficient graphene FET based RF energy harvester for green communication(Elsevier GmbH, 2020) Singh, N.; Kumar, S.; Kumar Kanaujia, B.K.; Beg, M.T.; Mainuddin, M.; Kumar, S.This paper presents a graphene field effect transistor (FET) based rectenna with substrate-integrated waveguide (SIW) broadband approach for RF energy harvesting application. The proposed structure of integrated rectenna consists of a graphene FET rectifier and an SIW antenna operating in the (S11 < ?10 dB) range of 29–46 GHz. The peak gain of the SIW antenna observed is 8.12 dBi. In addition, a new matched circuit consisting of microstrip line and butterfly stub (without using any lumped elements) is designed. The matched circuit provides a miniaturized block by reducing the size and eliminating parasitic reactance in the integrated rectenna. The proposed rectenna is implemented and fabricated using two superimposed layers: RT/duroid 5880 and graphene substrate with a compatible approach. A measured conversion efficiency of 80.32% is obtained. The dimensions of the proposed antenna and rectifier are 3.2 × 3.2 × 0.4 mm3 and 3.2 × 10 × 0.4 mm3, respectively. The proposed rectenna covers Ka- and Q-band applications and could be a potential candidate for contemporary energy harvesting systems. © 2019 Elsevier GmbHItem A compact broadband GFET based rectenna for RF energy harvesting applications(Springer, 2020) Singh, N.; Kumar, S.; Kumar Kanaujia, B.K.; Beg, M.T.; Mainuddin, M.; Kumar, S.In this paper, a compact GFET-based rectifier integrated with a monopole antenna is proposed for wireless energy harvesting applications. The GFET increases impedance bandwidth of the rectifying circuit, thus covering a range of 22.5–27.5 GHz. The sensing antenna is a triangular monopole with truncated corners for realizing circular polarization at the frequencies 24.25 GHz and 27 GHz. By the help of ?/4 transformer, the sensing antenna is matched with the proposed GFET rectifier. The RF-DC conversion efficiency realized is 80% at 5 dBm for the load of 5 K?, and the output DC voltage observed is 6.8 V. The modified ground plane triangular monopole antenna shows a peak gain of 7.8 dBi. The designed rectenna prototype is fabricated and found simulated and measured results are in good agreement. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.Item Hybrid Plasmonic Circular Aperture Waveguide for Blood Glucose Sensing(Institute of Electrical and Electronics Engineers Inc., 2024) Vankalkunti, S.; Singh, N.; Singh, M.A novel approach for blood glucose (or blood sugar) sensing utilizing a hybrid plasmonic circular aperture waveguide (HPCAW)-based nanostructure is proposed. The reported sensor combines the unique optical properties of plasmonic waveguides and circular aperture to achieve higher sensitivity and specificity in glucose detection. The HPCAW structure is designed to efficiently confine and propagate surface plasmon polaritons (SPPs) along the circular aperture, enabling enhanced light-matter interaction within the sensing region. Through rigorous numerical simulations and validation, we demonstrate the superior performance of the HPCAW sensor in terms of sensitivity (391.72 nm/RIU), figure of merit (FOM) (7.08 RIU-1), and detection accuracy (DA) (0.018 nm-1) compared to conventional glucose sensing techniques. Moreover, the proposed sensor offers inherent advantages, such as label-free detection, compact footprint, and compatibility with microfluidic systems. HPCAW provides a promising platform for the next-generation blood glucose monitoring applications with potential clinical translation. 1558-1748 © 2024 IEEE.