A Hybrid Expert System Using Symbolic Reasoning and Neural Networks for Predictive Maintenance in Mechatronic Systems Venkatesh S, Chandravadhana S, Rajesh R, Sagar Imambi S, Arivazhagan D, et al. Journal of Machine and Computing, 2025 Predictive maintenance (PdM) in mechatronic systems demands high-precision failure prediction and interpretability for real-time operational decisions. This study presents a hybrid expert system integrating symbolic reasoning and Deep Neural Networks (DNNs) to enhance predictive accuracy and semantic traceability. The symbolic layer consists of 42 fuzzy inference rules, enabling domain expert interpretability, while the neural network layer comprises a 4-layer feedforward architecture with 128-64-32-1 units using ReLU and sigmoid activations. Experiments were conducted on a real-world dataset, and the hybrid model achieved an accuracy of 96.8%, a precision of 94.22%, and a recall of 97.31%, outperforming conventional Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) models, and rule-based systems by margins of 3.2–7.8%. The proposed method reduced false positives by 21.4% and improved time-to-failure prediction by 18.7% compared to standalone models. Maintenance scheduling optimized using the proposed model yielded a 14.5% reduction in unplanned downtime. The hybrid inference strategy not only improved prediction granularity but also supported rule-based diagnostics. This framework significantly advances predictive intelligence in safety-critical mechatronic domains.
Improved Real Time User Interaction in Extended Reality Systems Using the Deployment of Adaptive Intelligent Technologies Hayder M A Ghanimi, Sathvik Bagam, Shaishav Shah, Vedaraj M, Manjunath T C, et al. Journal of Machine and Computing, 2025 The Human-Computer Interaction (HCI) field has seen rapid growth in various industries due to the introduction of Extended Reality (XR) environments. These environments require improved interface methods, real-time processing, low latency, and integrated User Experience (UE) servicing. This work aims to improve user interactions in real-time XR environments and introduces a new Hierarchical Adaptive System (HAS) to address these challenges. This study presents a Real-Time Adaptation Model (RTAM) for XR interfaces, which combines adaptive optimized performance, Deep Reinforcement Learning (DRL), and Fuzzy Logic (FL). The system addresses unpredictability, Dynamic Resource Allocation (DRA), and parallel processing pipelines. HAS did better than the best methods by 46.3% in terms of Faster Learning Integration (FLI), 63.2% in terms of Lower Error Rates (LER), and 37.4% in terms of Reduced Task Completion Times (RTCT) in a study with 60 users in different interactive settings. Despite maintaining low adaptation latency, the system achieves a score of 0.86 for resource utilization efficiency. The study also identified improvements in system responsiveness and overall satisfaction. The results support that HAS effectively solves RTAM issues in XR settings, laying the basis for next-generation immersive apps with more responsive and user-centered communication models.
Enhancing cryptographic robustness through error-correcting codes derived from network graphs Gayathri Ananthakrishnan, Hayder M. A. Ghanimi, P. Pushpa, T. K. Rama Krishna Rao, M. Vedaraj, et al. Journal of Discrete Mathematical Sciences and Cryptography, 2024 Secure data transmission is essential for securing sensitive data generated in huge volumes in today’s growing digital era. In today’s growing digital world, secure data transfer is essential for securing private information generated in enormous volumes. Data security strategies, called Cyber Security Systems (CSS), are susceptible to errors and other risks that might damage the data’s integrity. While standard Error-Correcting Codes (ECCs) function well for more standard communication errors, they cannot meet the complex rules of cryptographic functions. In order to boost the CSS size, this article provides a detailed approach that develops ECCs from network graph parameters. The error flexibility, computational speed, and use of bandwidth power of the CSS have been designed to be addressed by the graph-based ECCs. The investigation proposes an approach that analyses network graphs and employs information to develop ECCs, which are then integrated into the existing CSS. Compared with standard models, the one recommended performed more successfully when assessed under a range of error scenarios and cryptanalytic attacks.
Energy Optimized and Dynamic Design of Task Offloading in Mobile Fog Computing 15th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2024, 2024
Image Forgery Detection and Classification using Deep Learning Davinder Paul Singh, Vinith Kumar Nair, Ram Murat Singh, Puneet Bafna, M. Vedaraj, et al. 2024 Opju International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4 0 Otcon 2024, 2024
Detecting Driver Fatigue with Python and OpenCV C Pandi, T P Anish, S. Selvanayaki, P. Jagadeesan, M. Vedaraj, et al. Proceedings of the 2024 10th International Conference on Communication and Signal Processing Iccsp 2024, 2024
Early Prediction of Lung Cancer Using Gaussian Naive Bayes Classification Algorithm International Journal of Intelligent Systems and Applications in Engineering, 2023
A Depthwise Squeeze-Based Residual Recurrent Autoencoder for Accurate Plant Leaf Disease Prediction Using Multimodal Data P Jagadeesan, M Vedaraj Journal of Crop Health 78 (1), 37 , 2026 2026
Optimized slimmable pruned graph neural network with billiards-inspired algorithm for cotton disease detection and crop health improvement P Jagadeesan, M Vedaraj Iran Journal of Computer Science 8 (4), 2733-2752 , 2025 2025
Epdtnet plus-em: advanced transfer learning and subnet architecture for medical image diagnosis K Dhivya, K Sangamithrai, SI Priyadharshini, M Vedaraj COGNITIVE COMPUTATION 17 (2) , 2025 2025 Citations: 1
Graph Convolutional Networks for SEO: A Comprehensive Framework for Healthcare Information Ranking P RR, V M, AAR R Journal of The Institution of Engineers (India): Series B, 1-16 , 2025 2025 Citations: 4
A Hybrid Expert System Using Symbolic Reasoning and Neural Networks for Predictive Maintenance in Mechatronic Systems S Venkatesh, S Chandravadhana, R Rajesh, SS Imambi, D Arivazhagan, ... 2025
Improved Real-Time User Interaction in Extended Reality Systems Using the Deployment of Adaptive Intelligent Technologies HMA Ghanimi, S Bagam, S Shah, M Vedaraj, TC Manjunath, MK Sinha 2025
Energy Optimized and Dynamic Design of Task Offloading in Mobile Fog Computing. M Vedaraj, A Satwika, B Monisha, I Namratha Grenze International Journal of Engineering & Technology (GIJET) 10 , 2024 2024
Image Forgery Detection and Classification using Deep Learning DP Singh, VK Nair, RM Singh, P Bafna, M Vedaraj, VV Priya 2024 OPJU International Technology Conference (OTCON) on Smart Computing for … , 2024 2024 Citations: 1
Context-Based Psychosis Emotion Recognition System C Pandi, G Indra, V Harini, C Parthasarathy, M Vedaraj, R Kumar 2024 International Conference on Computing and Data Science (ICCDS), 1-4 , 2024 2024 Citations: 1
Detecting Driver Fatigue with Python and OpenCV C Pandi, TP Anish, S Selvanayaki, P Jagadeesan, M Vedaraj, R Sanjay 2024 10th International Conference on Communication and Signal Processing … , 2024 2024
Deep learning-based route reconfigurability for intelligent vehicle networks to improve power-constrained using energy-efficient geographic routing protocol L Syed, P Sathyaprakash, A Shobanadevi, HHC Nguyen, M Alauthman, ... Wireless Networks 30 (2), 939-960 , 2024 2024 Citations: 13
ENHANCING CRYPTOGRAPHIC ROBUSTNESS THROUGH ERROR-CORRECTING CODES DERIVED FROM NETWORK GRAPHS G ANANTHAKRISHNAN, HMA GHANIMI, P PUSHPA, T RAO, ... JOURNAL OF DISCRETE MATHEMATICAL SCIENCES AND CRYPTOGRAPHY 27 (7), 2155-2167 , 2024 2024
Machine learning based weight optimized genetic algorithm for digital video watermarking technique HZ Almngoshi, M Vedaraj, VP Sriram, MDK Dhas, V Arunraj, S Sengan, ... Journal of Autonomous Intelligence 7 (5) , 2024 2024 Citations: 4
A Novel Hyper-Spectral Model to Optimize the Prediction Rate for Heart Disease in Modern Healthcare Networks K Abinaya, D Palaniappan, M Vedaraj Engineering Proceedings 59 (1), 59081 , 2023 2023 Citations: 2
Early prediction of lung cancer using Gaussian naive Bayes classification algorithm M Vedaraj, CS Anita, A Muralidhar, V Lavanya, K Balasaranya, ... International Journal of Intelligent Systems and Applications in Engineering … , 2023 2023 Citations: 28
Prediction of COVID 19 using marching learning techniques M Vedaraj, K Saravanan, VP Srinivasan, K Balachander, AK Jaithunbi International Journal of Health Sciences, 9467-9474 , 2022 2022 Citations: 2
A Secure IoT-Cloud Based Healthcare System for Disease Classification Using Neural Network M Vedaraj, P Ezhumalai Computer Systems Science and Engineering 41 (1), 95–108 , 2021 2021 Citations: 28
HERDE-MSNB: a predictive security architecture for IoT health cloud system M Vedaraj, P Ezhumalai Journal of Ambient Intelligence and Humanized Computing 12 (7), 7333-7342 , 2021 2021 Citations: 13
Person Detection for Social Distancing and Safety Violation M Vedraj, MVY Kumar, MH Krishna, MN Gowtham Annals of the Romanian Society for Cell Biology. 25 (4), 16395-16401 , 2021 2021
Enhanced Privacy Preservation of Cloud Data by using ElGamal Elliptic Curve (EGEC) Homomorphic Encryption Scheme. M Vedaraj, P Ezhumalai KSII Transactions on Internet & Information Systems 14 (11) , 2020 2020 Citations: 3
MOST CITED SCHOLAR PUBLICATIONS
Early prediction of lung cancer using Gaussian naive Bayes classification algorithm M Vedaraj, CS Anita, A Muralidhar, V Lavanya, K Balasaranya, ... International Journal of Intelligent Systems and Applications in Engineering … , 2023 2023 Citations: 28
A Secure IoT-Cloud Based Healthcare System for Disease Classification Using Neural Network M Vedaraj, P Ezhumalai Computer Systems Science and Engineering 41 (1), 95–108 , 2021 2021 Citations: 28
Deep learning-based route reconfigurability for intelligent vehicle networks to improve power-constrained using energy-efficient geographic routing protocol L Syed, P Sathyaprakash, A Shobanadevi, HHC Nguyen, M Alauthman, ... Wireless Networks 30 (2), 939-960 , 2024 2024 Citations: 13
HERDE-MSNB: a predictive security architecture for IoT health cloud system M Vedaraj, P Ezhumalai Journal of Ambient Intelligence and Humanized Computing 12 (7), 7333-7342 , 2021 2021 Citations: 13
Graph Convolutional Networks for SEO: A Comprehensive Framework for Healthcare Information Ranking P RR, V M, AAR R Journal of The Institution of Engineers (India): Series B, 1-16 , 2025 2025 Citations: 4
Machine learning based weight optimized genetic algorithm for digital video watermarking technique HZ Almngoshi, M Vedaraj, VP Sriram, MDK Dhas, V Arunraj, S Sengan, ... Journal of Autonomous Intelligence 7 (5) , 2024 2024 Citations: 4
A hybrid data encryption technique using TWOFish and elgamal for cloud computing M Vedaraj, DMV Prem International Journal of Management, Technology And Engineering 8 (1473 … , 2018 2018 Citations: 4
Enhanced Privacy Preservation of Cloud Data by using ElGamal Elliptic Curve (EGEC) Homomorphic Encryption Scheme. M Vedaraj, P Ezhumalai KSII Transactions on Internet & Information Systems 14 (11) , 2020 2020 Citations: 3
A Novel Hyper-Spectral Model to Optimize the Prediction Rate for Heart Disease in Modern Healthcare Networks K Abinaya, D Palaniappan, M Vedaraj Engineering Proceedings 59 (1), 59081 , 2023 2023 Citations: 2
Prediction of COVID 19 using marching learning techniques M Vedaraj, K Saravanan, VP Srinivasan, K Balachander, AK Jaithunbi International Journal of Health Sciences, 9467-9474 , 2022 2022 Citations: 2
Epdtnet plus-em: advanced transfer learning and subnet architecture for medical image diagnosis K Dhivya, K Sangamithrai, SI Priyadharshini, M Vedaraj COGNITIVE COMPUTATION 17 (2) , 2025 2025 Citations: 1
Image Forgery Detection and Classification using Deep Learning DP Singh, VK Nair, RM Singh, P Bafna, M Vedaraj, VV Priya 2024 OPJU International Technology Conference (OTCON) on Smart Computing for … , 2024 2024 Citations: 1
Context-Based Psychosis Emotion Recognition System C Pandi, G Indra, V Harini, C Parthasarathy, M Vedaraj, R Kumar 2024 International Conference on Computing and Data Science (ICCDS), 1-4 , 2024 2024 Citations: 1
A Depthwise Squeeze-Based Residual Recurrent Autoencoder for Accurate Plant Leaf Disease Prediction Using Multimodal Data P Jagadeesan, M Vedaraj Journal of Crop Health 78 (1), 37 , 2026 2026
Optimized slimmable pruned graph neural network with billiards-inspired algorithm for cotton disease detection and crop health improvement P Jagadeesan, M Vedaraj Iran Journal of Computer Science 8 (4), 2733-2752 , 2025 2025
A Hybrid Expert System Using Symbolic Reasoning and Neural Networks for Predictive Maintenance in Mechatronic Systems S Venkatesh, S Chandravadhana, R Rajesh, SS Imambi, D Arivazhagan, ... 2025
Improved Real-Time User Interaction in Extended Reality Systems Using the Deployment of Adaptive Intelligent Technologies HMA Ghanimi, S Bagam, S Shah, M Vedaraj, TC Manjunath, MK Sinha 2025
Energy Optimized and Dynamic Design of Task Offloading in Mobile Fog Computing. M Vedaraj, A Satwika, B Monisha, I Namratha Grenze International Journal of Engineering & Technology (GIJET) 10 , 2024 2024
Detecting Driver Fatigue with Python and OpenCV C Pandi, TP Anish, S Selvanayaki, P Jagadeesan, M Vedaraj, R Sanjay 2024 10th International Conference on Communication and Signal Processing … , 2024 2024
ENHANCING CRYPTOGRAPHIC ROBUSTNESS THROUGH ERROR-CORRECTING CODES DERIVED FROM NETWORK GRAPHS G ANANTHAKRISHNAN, HMA GHANIMI, P PUSHPA, T RAO, ... JOURNAL OF DISCRETE MATHEMATICAL SCIENCES AND CRYPTOGRAPHY 27 (7), 2155-2167 , 2024 2024
