Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
Browse
7 results
Search Results
Item Development of low-cost real-time driver drowsiness detection system using eye centre tracking and dynamic thresholding(Springer Verlag service@springer.de, 2020) Khan, F.; Sharma, S.One in every five vehicle accidents on the road today is caused simply due to driver fatigue. Fatigue or otherwise drowsiness, significantly reduces the concentration and vigilance of the driver thereby increasing the risk of inherent human error leading to injuries and fatalities. Hence, our primary motive being - to reduce road accidents using a non-intrusive image processing based alert system. In this regard, we have built a system that detects driver drowsiness by real time tracking and monitoring the pattern of the driver’s eyes. The stand alone system consists of 3 interconnected components - a processor, a camera and an alarm. After initial facial detection, the eyes are located, extracted and continuously monitored to check whether they are open or closed on the basis of a pixel-by-pixel method. When the eyes are seen to be closed for a certain amount of time, drowsiness is said to be detected and an alarm is issued accordingly to alert the driver and hence, prevent a casualty. © Springer Nature Switzerland AG 2020.Item Multiple response optimisation of process parameters during drilling of GFRP composite with a solid carbide twist drill(Elsevier Ltd, 2020) Bhat, R.; Mohan, N.; Sharma, S.; Dayananda Pai, D.; Kulkarni, S.M.The article focuses on investigating the effect of operational parameters like feed and speed along with the composite material thickness on the damages caused in the glass fibre reinforced polymer (GFRP) composites during the drilling process. The GFRP composite studied in the presented work comprises E-glass fibre as the reinforcing material and the marine-grade isophthalic polyester as the binding matrix. Multiple responses considered in work comprises Peel-up delamination, push-down delamination and surface roughness. The technique for order of preference by similarity to ideal solution (TOPSIS) is used to develop the performance index and optimise the multiple response problem. Stepwise analysis of variance (S-ANOVA) is used to investigate the significance of each input parameter. The interaction effects of the variables are investigated using the response surface plots. The results indicate that the composite thickness contributes maximum towards the variance in the overall performance index (21.30%) and the optimum combination obtained using TOPSIS approach within the experimental limits for the selected GFRP is N3f1t1 with the maximum value of Pi (0.888). The regression model developed proves to have high goodness of fit with just 6.01% average error between predicted and experimental values. © 2019 Elsevier Ltd.Item Mitigating Man-in-the-Middle Attack in Digital Signature(Institute of Electrical and Electronics Engineers Inc., 2020) Jain, S.; Sharma, S.; Chandavarkar, B.R.We all are living in the digital era, where the maximum of the information is available online. The digital world has made the transfer of information easy and provides the basic needs of security like authentication, integrity, nonrepudiation, etc. But, with the improvement in security, cyber-attacks have also increased. Security researchers have provided many techniques to prevent these cyber-attacks; one is a Digital Signature (DS). The digital signature uses cryptographic key pairs (public and private) to provide the message's integrity and verify the sender's identity. The private key used in the digital signature is confidential; if attackers find it by using various techniques, then this can result in an attack. This paper presents a brief introduction about the digital signature and how it is vulnerable to a man-in-the-middle attack. Further, it discusses a technique to prevent this attack in the digital signature. © 2020 IEEE.Item Nonce: Life Cycle, Issues and Challenges in Cryptography(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2021) Sharma, S.; Jain, S.; Chandavarkar, B.R.We all are living in the era of online processing, where the maximum of the information is available online. As the facilities of computer technology have increased, threats of losing personal and sensitive information have also increased. Cryptographic software and algorithms are good at some extent but as we all are seeing several attacks like Plaintext attack, Replay attack on Apply pay, Interleaving attack on PKMv2, etc. show us that our cryptographic software is less likely to be broken due to the weakness in the underlying deterministic cryptographic algorithms. A nonce is another attempt to improve security from these kinds of attacks. A nonce is an input value that will not repeat in a given context. Nonce use to prevent replay and interleaving attacks. Nonce also protects websites against malicious exploits that are based on Cross-Site Request Forgery (CSRF). The main aim of this paper is to introduce, What is Nonce, how it works and what are the issues and challenges in cryptography that we can solve with Nonce. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Crop Classification Based on Optimal Hyperspectral Narrow Bands Using Machine Learning and Hyperion Data(Institute of Electrical and Electronics Engineers Inc., 2023) Reddy, B.S.; Sharma, S.; Shwetha, H.R.In view of global climate change and the limited availability of cropland, crop classification plays a critical role in maintaining food security. Hyperspectral remote sensing has emerged as a valuable tool for classifying crops using detailed spectral information. To explore the potential of hyperspectral data for nationwide crop classification, the research uses the GHISACONUS library to identify Optimal Hyperspectral Narrow Bands (OHNBs) across seven Agricultural Experimental Zones (AEZ) in the USA. Principal Component Analysis (PCA) techniques are employed to identify 24 OHNBs from the data. OHNBs achieved notable accuracy rates, ranging from 75% to 91% when classifying different crop types and their growth stages. However, accuracy drops below 90% in significant cases, likely due to the limited selection of 24 OHNBs and the variation in crop phenology across the seven study areas. The research indicates that systematically selecting OHNBs based on crop phenological stages consistently achieves satisfactory classification accuracy. This approach effectively classifies crops in any Hyperion image. Overall, the study contributes significantly to our knowledge of using OHNBs for nationwide crop classification, highlighting the importance of considering phenological stages and data acquisition conditions to enhance accuracy. © 2023 IEEE.Item Reliability Analysis Using Bayesian Belief Network on Drone System: A Case Study(Institute of Electrical and Electronics Engineers Inc., 2024) Das, M.; Mohan, B.R.; Ram Mohana Reddy, G.; Chhaparwal, E.; Krishna Kumar, K.; Chowdhury, S.; Sharma, S.Ensuring the reliability of software components is of paramount importance in safety-critical systems. Grave consequences might occur if software failures in such systems. Hence, predicting software reliability is important in these systems. This research uses Bayesian Belief Network(BBN) and leverages historical failure data to find fault interdependencies, giving much more insights than methodologies like Fault Tree Analysis (FTA) and Reliability Block Diagrams (RBD). By comparing BBNs with these traditional methods, the research shows the dynamic capabilities of BBNs. BBN also shows the capability of using real-time data and machine learning together to increase the software reliability of the software components, making this system much safer. © 2024 IEEE.Item Fabrication of β-Phase PVDF/MWCNTs Nanofibers on a Flexible Substrate for Energy Harvesting Application(Institute of Electrical and Electronics Engineers Inc., 2024) Chauhan, S.S.; Sharma, S.; Muhiuddin, M.; Rahman, M.R.It is challenging to deposit the pristine polyvinylidene difluoride (PVDF) in β crystalline phase on a flexible substrate since pristine PVDF exists in the α-phase. This paper presents a novel formation of nanofibers membrane of PVDF in which multiwall carbon nanotubes (MWCNT) is added as the composite in PVDF for transformation from α to β phase. The PVDF/MWCNTs nanofibers is electro spun after adding carboxyl functionalized MWCNT with PVDF to form the β phase. The field emission scanning electron microscope (FE-SEM) is used to characterize the presence of the nanofiber's membrane. X-ray diffraction (XRD) is used to characterize the β phase and Fourier-transform infrared spectroscopy (FTIR) is used to detect the functionalized bonds in the formation of PVDF/MWCNTs nanofibers on a flexible Polyethylene Terephthalate (PET). The measurement of the polarization of electric field hysteresis shows good characteristics with Ps, Pr, and EC are 9.58 μC/m2, 4 μC/m2, and 1 MV/m, respectively. The optimized film has a high potential for application as the piezoelectric material in energy harvesting devices fabricated on a flexible PET film. © 2024 IEEE.