Electrical and Electronic Engineering, Information Systems
9
Scopus Publications
76
Scholar Citations
4
Scholar h-index
4
Scholar i10-index
Scopus Publications
Recognition and Optimization of Wear Behaviour of Al 6081 with Polymeric Nanocomposites Using Machine Learning Jaidev Kumar, Sanjay R. Pawar, Ashish, V Kamalakar, R Karuppathal, Anup D Bhange Proceedings of the 4th International Conference on Smart Electronics and Communication Icosec 2023, 2023 The Al 6081 alloy is broadly used in numerous engineering requests due to its excellent mechanical properties. However, its resistance of wear parameter is not satisfactory. In this study, the wear resistance of Al 6081 alloy reinforced with Graphene nanoplatelets (GNPs) at three different percentages (0.3%, 0.6%, and 0.9%) was investigated using Taguchi L27 array design. Machine learning techniques such as Signal to Noise ratio and Neural Networks were used to forecast the responses and optimize the wear behaviour of the Al 6081 alloy. The wear track was identified using Scanning Electron Microscopy (SEM) images. The results of the study indicate that the addition of GNPs improves the wear resistance of the Al 6081 alloy. The percentage of GNPs reinforcement that gives the best wear resistance is determined using the Taguchi L27 array design. It is found that 5% GNPs additives reduces the wear compared to other composition, 1% and 3%. This study provides a deeper understanding of the wear behaviour of Al 6081 alloy reinforced with GNPs and can be used as a reference for future research in this field. The use of machine learning techniques in this study provides a new approach for the optimization of wear behaviour in Al 6081 alloy reinforced with GNPs, which can be applied in various industrial applications. Overall, the consequences of this study validate that incorporating 0.9% GNPs in Al 6081 alloy is an operative way to advance its wear resistance properties.
SATELLITE IMAGE ANALYSIS USING CONTEXTUAL DATA RETRIEVAL TECHNIQUE FOR ENVIRONMENTAL MONITORING CONDITION Journal of Environmental Protection and Ecology, 2022
Blockchain Enabled Optimal Lightweight Cryptography Based Image Encryption Technique for IIoT R. Bhaskaran, R. Karuppathal, M. Karthick, J. Vijayalakshmi, Seifedine Kadry, Yunyoung Nam Intelligent Automation and Soft Computing, 2022 Industrial Internet of Things (IIoT) and Industry 4.0/5.0 offer several interconnections between machinery, equipment, processes, and personnel in diverse application areas namely logistics, supply chain, manufacturing, transportation, and healthcare. The conventional security-based solutions in IIoT environment get degraded due to the third parties. Therefore, the recent blockchain technology (BCT) can be employed to resolve trust issues and eliminate the need for third parties. Therefore, this paper presents a novel blockchain enabled secure optimal lightweight cryptography based image encryption (BC-LWCIE) technique for industry 4.0 environment. In addition, the BC-LWCIE technique involves the design of an optimal LWC based hash function with optimal key generation using chicken swarm optimization (CSO) algorithm. Moreover, the CSO algorithm derives a fitness function with the maximization of peak signal to noise ratio (PSNR). The BC-LWCIE technique stores the cryptographic pixel values of the encrypted image in the BCT to ensure secrecy in the IIoT environment. In order to highlight the enhanced security performance of the BC-LWCIE technique, a series of simulations were carried out and the results demonstrated the betterment of the BC-LWCIE technique over the recent techniques.
Wireless sensor network based under water pipeline monitoring for using autonomous under water vehicles International Journal of Recent Technology and Engineering, 2019
An automotive approach for brain tumor segmentation based on gaussian distribution and level set method R. Karuppathal, V. Palanisamy Current Medical Imaging Reviews, 2014 In recent years a great work of the research in the field of medical imaging was focused on the brain tumor segmentation. In this paper, a novel region based active contour model for Magnetic Resonance Images (MRIs) brain tumor segmentation based on a level set origination is proposed and implemented. The image intensities are explained based on the Gaussian distributions through diverse means and variances. The attained local mean and variances are defined as variables and the Moore Gaussian distributions are described by the level set function. The energy minimization is attained by the curve evolution of level set and the approximation of the local intensity means and variances, it is an iterative process. To handle the intensity inhomogeneities and noise, the means and variances are measured as spatially varying functions. The tumor segmentation is an important early phase to solve the segmentation problem effectively. Hybrid Median Filter (HMF) is used to preserve the edges. Also, Sussman boundary condition is explored to accurately extract the tumor portions rather than the unwanted segmentations. The number of iterations used in this novel framework is quite lesser than the existing approach. Hence, the time taken for proposed tumor segmentation technique is also lesser than the existing method. The proposed system Gaussian Distribution with Level Set Method (GD-LSM) results accurate segmentation, sensitivity and specificity outcomes. Keywords: Active Contour, Brain Tumor Segmentation, Curve Evolution, Gaussian Distributions, Hybrid Median Filter (HMF), Level set, and Magnetic Resonance Images (MRIs).
Brain tumor detection and classification of normal, abnormal in MRI images Journal of Theoretical and Applied Information Technology, 2014
Fuzzy based automatic detection and classification approach for MRI-brain tumor Arpn Journal of Engineering and Applied Sciences, 2014
Hybrid GA- SVM for feature selection to improve Automatic Bayesian classification of Brain MRI Slice Life Science Journal, 2013
RECENT SCHOLAR PUBLICATIONS
Blockchain Enabled Optimal Lightweight Cryptography Based Image Encryption Technique for IIoT Y Bhaskaran, R. , Karuppathal, R. , Karthick, M. , ... Kadry, S. , Nam Intelligent Automation and Soft Computing 33 (3), 1593–1606 , 2022 2022 Citations: 16
SATELLITE IMAGE ANALYSIS USING CONTEXTUAL DATA RETRIEVAL TECHNIQUE FOR ENVIRONMENTAL MONITORING CONDITION R Bhaskaran, R. , Karuppathal, R. , Prakash, N.B. , Rajkumar Journal of Environmental Protection and Ecology 23 (1), 301–313 , 2022 2022 Citations: 1
A big data analytical approach for prediction of cancer using modified k-nearest neighbour algorithm K Muthumayil, R Karuppathal, T Jayasankar, B Aruna Devi, NB Prakash, ... Journal of Medical Imaging and Health Informatics 11 (8), 2184-2189 , 2021 2021 Citations: 17
Infrastructure for Time Critical Applications of Big Data Systems Using Light Weight YARN Architecture S AM, K Loheswaran, GNR Devi, C Balakrishnan, TS Srini 2021
Impact of Augmented Reality Education on Students Interactivity” in , 2021, vol. 14, issue. 4, pp. 1-10 K R International Journal of Pharmaceutical Research 13 (2), 690-698 , 2021 2021
Developing Secure Cloud Storage Through Quantum Secure Socket Layer Protocol K Pandeeswari N, Sivakami R International Journal for Research in Engineering Application & Management … , 2020 2020
Discovering Malicious Insiders In And Around Cloud Systems Based On Hypervisor Technology JS N Pandeeswari, R Sivakami, R Karuppathal, N Sasikala Journal of Critical Reviews 7 (19), 1-10 , 2020 2020
Wireless sensor network based under water pipeline monitoring for using autonomous under water vehicles N Bhuvaneshwari, S. , Karuppathal, R. , Kumar, A.V.A. , Pandeeswari International Journal of Recent Technology and Engineering, 2019, 7(6), pp … , 2019 2019
Hypervisor Based Anomaly Detection System in Cloud Computing Using ANFIS N Pandeeswari, R Karuppathal 網際網路技術學刊 18 (6), 1335-1344 , 2017 2017 Citations: 1
Anatomy Guidance Based Brain Tumor Segmentation and Classification VP R.Karuppathal International Journal of Printing, Packaging & Allied Sciences 8 (4 … , 2016 2016
Fuzzy based automatic detection and classification approach for MRI-brain tumor R Karuppathal, V Palanisamy ARPN Journal of Engineering and Applied Sciences 9 (12) , 2014 2014 Citations: 23
An automotive approach for brain tumor segmentation based on Gaussian distribution and level set method R Karuppathal, V Palanisamy Current Medical Imaging Reviews 10 (4), 290-296 , 2014 2014 Citations: 1
BRAIN TUMOR DETECTION AND CLASSIFICATION OF NORMAL, ABNORMAL IN MRI IMAGES. R KARUPPATHAL, V PALANISAMY Journal of Theoretical & Applied Information Technology 68 (3) , 2014 2014
Hybrid GA-SVM for feature selection to improve Automatic Bayesian classification of Brain MRI Slice R Karuppathal, V Palanisamy Life Science Journal 10 (2) , 2013 2013 Citations: 3
Copyright protection using digital watermarking DM Jose, R Karuppathal, AVA Kumar National conference on advances in computer science and applications with … , 2012 2012 Citations: 14
MOST CITED SCHOLAR PUBLICATIONS
Fuzzy based automatic detection and classification approach for MRI-brain tumor R Karuppathal, V Palanisamy ARPN Journal of Engineering and Applied Sciences 9 (12) , 2014 2014 Citations: 23
A big data analytical approach for prediction of cancer using modified k-nearest neighbour algorithm K Muthumayil, R Karuppathal, T Jayasankar, B Aruna Devi, NB Prakash, ... Journal of Medical Imaging and Health Informatics 11 (8), 2184-2189 , 2021 2021 Citations: 17
Blockchain Enabled Optimal Lightweight Cryptography Based Image Encryption Technique for IIoT Y Bhaskaran, R. , Karuppathal, R. , Karthick, M. , ... Kadry, S. , Nam Intelligent Automation and Soft Computing 33 (3), 1593–1606 , 2022 2022 Citations: 16
Copyright protection using digital watermarking DM Jose, R Karuppathal, AVA Kumar National conference on advances in computer science and applications with … , 2012 2012 Citations: 14
Hybrid GA-SVM for feature selection to improve Automatic Bayesian classification of Brain MRI Slice R Karuppathal, V Palanisamy Life Science Journal 10 (2) , 2013 2013 Citations: 3
SATELLITE IMAGE ANALYSIS USING CONTEXTUAL DATA RETRIEVAL TECHNIQUE FOR ENVIRONMENTAL MONITORING CONDITION R Bhaskaran, R. , Karuppathal, R. , Prakash, N.B. , Rajkumar Journal of Environmental Protection and Ecology 23 (1), 301–313 , 2022 2022 Citations: 1
Hypervisor Based Anomaly Detection System in Cloud Computing Using ANFIS N Pandeeswari, R Karuppathal 網際網路技術學刊 18 (6), 1335-1344 , 2017 2017 Citations: 1
An automotive approach for brain tumor segmentation based on Gaussian distribution and level set method R Karuppathal, V Palanisamy Current Medical Imaging Reviews 10 (4), 290-296 , 2014 2014 Citations: 1
Infrastructure for Time Critical Applications of Big Data Systems Using Light Weight YARN Architecture S AM, K Loheswaran, GNR Devi, C Balakrishnan, TS Srini 2021
Impact of Augmented Reality Education on Students Interactivity” in , 2021, vol. 14, issue. 4, pp. 1-10 K R International Journal of Pharmaceutical Research 13 (2), 690-698 , 2021 2021
Developing Secure Cloud Storage Through Quantum Secure Socket Layer Protocol K Pandeeswari N, Sivakami R International Journal for Research in Engineering Application & Management … , 2020 2020
Discovering Malicious Insiders In And Around Cloud Systems Based On Hypervisor Technology JS N Pandeeswari, R Sivakami, R Karuppathal, N Sasikala Journal of Critical Reviews 7 (19), 1-10 , 2020 2020
Wireless sensor network based under water pipeline monitoring for using autonomous under water vehicles N Bhuvaneshwari, S. , Karuppathal, R. , Kumar, A.V.A. , Pandeeswari International Journal of Recent Technology and Engineering, 2019, 7(6), pp … , 2019 2019
Anatomy Guidance Based Brain Tumor Segmentation and Classification VP R.Karuppathal International Journal of Printing, Packaging & Allied Sciences 8 (4 … , 2016 2016
BRAIN TUMOR DETECTION AND CLASSIFICATION OF NORMAL, ABNORMAL IN MRI IMAGES. R KARUPPATHAL, V PALANISAMY Journal of Theoretical & Applied Information Technology 68 (3) , 2014 2014
