Role of macadamia shell nut extracted silicon carbide and natural fiber-reinforced PVA composite and its mechanical, thermal conductivity, dielectric and EMI shielding effectiveness Seeniappan Kaliappan, Naveen Kilari, L. Natrayan, M. Muthukannan, M. Ramya, Sathish Kannan, Vinayagam Mohanavel, Manzoore Elahi M. Soudagar Journal of Thermoplastic Composite Materials, 2026 The present study investigates the role of silicon carbide (SiC) extracted from macadamia nut shells and natural short fibers in reinforcing polyvinyl alcohol (PVA) composites. The composite materials were prepared by integrating SiC, derived through pyrolysis and chemical processing, with PVA and natural fibers to evaluate their mechanical, thermal, dielectric, and electromagnetic interference (EMI) shielding properties. The prepared composites performance is evaluated as per ASTM standard. The result demonstrated that the ideal ratio of matrix, fibers f 40 vol%, and 3 vol% silicon carbide, PCS2 had the maximum tensile strength (142 MPa), tear strength (33 MPa), Izod impact strength (4.7 Joules (J)), and Shore-D hardness (82). Additionally, PCS2 had the highest EMI shielding performance, peaking at 64.84 dB at 18 GHz, as a result of the fibers and fillers working in concert to increase wave absorption and reflection through improved interfacial bonding and polarization. While, the composite PCS3 with reinforcement of 40 vol% of fiber and 5 vol% of SiC shows improved thermal conductivity of 0.23 W/mK, and maximum dielectric permittivity of 4.8 and dielectric loss of 0.73. This work emphasizes the potential of natural fibers and SiC obtained from macadamia shells as high-performance, sustainable fillers in innovative composite materials and it could be applied in areas such as communication, military, signal processing and navigation performance.
Diffusion-driven adaptive radiance refinement with PPO-based optimization for robust solar irradiance forecasting Natrayan L, Chenga Reddy Peddamangari, M Prem Kumar Reddy, Seeniappan Kaliappan, Ramya Maranan, Anand Rajendran Results in Engineering, 2026 • Introduces a novel fusion of diffusion-based refinement and reinforcement learning to enhance solar irradiance forecasting and PV control. • PPO-based controller continuously self-corrects prediction errors in real time, ensuring adaptive and resilient PV system performance. • Achieves around 8% improvement in prediction accuracy and notable reduction in forecast volatility compared to advanced deep learning and hybrid models. • Delivers a scalable, real-time, and autonomous forecasting-and-control framework suitable for smart grid and distributed solar energy applications. Rapid global transition toward renewable energy sources has amplified the importance of accurate solar irradiance forecasting for reliable PV system operation. Conventional models such as LSTM, ANN, and optimization-based hybrids face challenges in capturing nonlinear irradiance variations, mitigating atmospheric noise, and adapting to sudden weather changes. To address these limitations, this study introduces a novel Diffusion-Based Adaptive Radiance Refinement Layer (ARRL) integrated with Proximal Policy Optimization (PPO) to enhance denoising, adaptivity, and real-time error correction. The ARRL suppresses stochastic irradiance noise, while PPO continuously refines prediction outputs through reinforcement-guided optimization. The proposed framework was implemented in Python using TensorFlow 2.15 and evaluated on the Kaggle Solar Irradiance and Weather Forecasting Dataset, consisting of 1000 temporal records sampled at 30-minute intervals. Experimental results reveal that the proposed Diffusion and PPO model achieved a MAE of 10.28 W/m², RMSE of 14.17 W/m², MAPE of 2.25 and an R² score of 0.97, representing an approximate 8% improvement in prediction accuracy compared to advanced LSTM and hybrid optimization benchmarks. Moreover, the framework demonstrated robust generalization under cloud-induced fluctuations and significant reductions in forecast volatility. The synergistic fusion of diffusion denoising and reinforcement-based adaptive learning delivers a self-correcting and scalable solution for solar forecasting. In conclusion, the proposed model establishes a highly interpretable and resilient architecture, setting a new direction for intelligent, autonomous, and data-driven solar irradiance prediction systems in dynamic environmental conditions.
Enhanced mechanical properties of kenaf fibres with fly ash, and Al2O3 nanofillers epoxy hybrid composites Sustainable Structural Materials from Fundamentals to Manufacturing Properties and Applications, 2025
Impact of fibre hybridisation and titanium oxide concentration on the thermomechanical properties of sisal-reinforced polymer nanocomposites Sustainable Structural Materials from Fundamentals to Manufacturing Properties and Applications, 2025
Fault Tolerant 3D VLSI System for Real-Time Wearable Health Monitoring L. Natrayan, Seeniappan Kaliappan, Beena Stanislaus Arputharaj, T. Roseline Velankanni, M Ramya Proceedings of the 6th International Conference on Electronics and Sustainable Communication Systems Icesc 2025, 2025
Enhancing Trust and Security in Digital Ecosystems with Blockchain Technology L. Natrayan, Seeniappan Kaliappan, Subramaniyan V., George Fernandez Raj A., Nishma Bhaskarani, Lakshmi Chandrakanth Kasireddy Proceedings of the 2025 International Conference on Technology Enabled Economic Changes Intech 2025, 2025
Transfer Learning Approaches for Improved Thyroid Detection D. M. Kalai Selvi, Kireet Joshi, Vani V, Daxa Vekariya, Natrayan L, Harshal Patil 5th International Conference on Electronics and Sustainable Communication Systems Icesc 2024 Proceedings, 2024
Machine Learning-Based Fault Diagnosis for Rotating Machinery in Industrial Settings Arun Francis G, Sophia Alamanda, S. B G Tilak Babu, K. Kavita, Prathyusha Reddy Pesaru, Natrayan L Proceedings of 9th International Conference on Science Technology Engineering and Mathematics the Role of Emerging Technologies in Digital Transformation Iconstem 2024, 2024
Leveraging AI for Real-Time Anomaly Detection in IoT Data Streams R G Gokila, Sanjeev Kukreti, R.S.S. Raju Battula, Santhosh Kumar Kuchoor, Abhijit Vasmatkar, Natayan L International Conference on Distributed Systems Computer Networks and Cybersecurity Icdscnc 2024, 2024
Blockchain-Enhanced Access Control for IoT Systems in Smart Cities Santhosh Kumar Kuchoor, Sanjeev Kukreti, R.S.S. Raju Battula, Suruchi Singh, Ashutosh Panchbhai, et al. International Conference on Distributed Systems Computer Networks and Cybersecurity Icdscnc 2024, 2024
Deep Learning Methods for Detecting ImageBased Defects in Manufacturing Processes Banshi Prasad Agrawal, Prabha Shreeraj Nair, S. B G Tilak Babu, R. Rajprabu, Prathyusha Reddy Pesaru, et al. Proceedings of 9th International Conference on Science Technology Engineering and Mathematics the Role of Emerging Technologies in Digital Transformation Iconstem 2024, 2024
Deep Learning-Enabled Human Resource Analytics in Predicting Employee Performance P. Deepthi, Mohsin Shaikh, Amarja Satish Nargunde, Rajesh Faldu, Gurunadham Goli, et al. Proceedings of 9th International Conference on Science Technology Engineering and Mathematics the Role of Emerging Technologies in Digital Transformation Iconstem 2024, 2024
Smart Trap Detecting the Whitefly Pest using Deep Neural Networks Manenalli Deepika, Kavitha P, Afshan Zareen, Swapnil Parikh, Harshal Patil, et al. 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things Idciot 2024, 2024
Investigation of the Use of Renewable Energy in Microgrid Applications Keerthi Kumar N, Saravana Selvan, G. Ravindra, Seeniappan. Kallappan, L. Natrayan, Nadanakumar Vinayagam Proceedings of 9th International Conference on Science Technology Engineering and Mathematics the Role of Emerging Technologies in Digital Transformation Iconstem 2024, 2024
Long non-coding RNAs: controversial roles in drug resistance of solid tumors mediated by autophagy Mohamed J. Saadh, Muhammad Ali Abdulllah Almoyad, Meryelem Tania Churampi Arellano, Renato R. Maaliw, Roxana Yolanda Castillo-Acobo, Sarah Salah Jalal, Kumaraswamy Gandla, Mohammed Obaid, Asmaa Jamal Abdulwahed, Azher A. Ibrahem, Ioan Sârbu, Ashima Juyal, Natrayan Lakshmaiya, Reza Akhavan-Sigari Cancer Chemotherapy and Pharmacology, 2023
Progressing nanotechnology to improve targeted cancer treatment: overcoming hurdles in its clinical implementation Mohammad Chehelgerdi, Matin Chehelgerdi, Omer Qutaiba B. Allela, Renzon Daniel Cosme Pecho, Narayanan Jayasankar, Devendra Pratap Rao, Tamilanban Thamaraikani, Manimaran Vasanthan, Patrik Viktor, Natrayan Lakshmaiya, Mohamed J. Saadh, Ayesha Amajd, Mabrouk A. Abo-Zaid, Roxana Yolanda Castillo-Acobo, Ahmed H. Ismail, Ali H. Amin, Reza Akhavan-Sigari Molecular Cancer, 2023
miR-199a-3p suppresses neuroinflammation by directly targeting MyD88 in a mouse model of bone cancer pain Mohamed J. Saadh, Amera Bekhatroh Rashed, Azfar Jamal, Roxana Yolanda Castillo-Acobo, Mohammad Azhar Kamal, Juan Carlos Cotrina-Aliaga, José Luis Arias Gonzáles, Abdulaziz S. Alothaim, Wardah A. Alhoqail, Fuzail Ahmad, Natrayan Lakshmaiya, Ali H. Amin, Dhuha Ghassan Younus, Gregorio Gilmer Rosales Rojas, Abolfazl Bahrami, Reza Akhavan-Sigari Life Sciences, 2023
Artificial Intelligence-Based Control Strategies for Unmanned Aerial Vehicles S. Prabagar, Ali Khudhair Al-Jiboory, Prabha Shreeraj Nair, Pawan Mandal, Komal Mohan Garse, Natrayan L 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical Electronics and Computer Engineering Upcon 2023, 2023
Deep Learning Techniques for Autonomous Navigation of Underwater Robots J.Priscilla Sasi, Karuna Nidhi Pandagre, Angelina Royappa, Suchita Walke, Pavithra G, Natrayan L 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical Electronics and Computer Engineering Upcon 2023, 2023
The Role of AI in Biochips for Early Disease Detection C. Sukumaran, K. Indhumathi, P. Balamurugan, R.P. Ambilwade, P. Mohana Sunthari, et al. Proceedings International Conference on Technological Advancements in Computational Sciences Ictacs 2023, 2023
Intelligent Systems For Predictive Maintenance In Industrial IoT M. Vijayakumar, Prabha Shreeraj Nair, S. B G Tilak Babu, Kommabatla Mahender, T S Venkateswaran, Natrayan L 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical Electronics and Computer Engineering Upcon 2023, 2023
AI and ML for Enhancing Crop Yield and Resource Efficiency in Agriculture Ehtesham Siddiqui, Mohammed Siddique, Safeer Pasha M, Prasanthi Boyapati, Pavithra G, Natrayan L 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical Electronics and Computer Engineering Upcon 2023, 2023
Intelligent Control Systems for Industrial Automation and Robotics Vijaykumar S. Biradar, Ali Khudhair Al-Jiboory, Gaurav Sahu, S. B G Tilak Babu, Kommabatla Mahender, Natrayan L 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical Electronics and Computer Engineering Upcon 2023, 2023
Optimization of squeeze casting process parameters on aa2024/al2o3/sic/gr hybrid composite using taguchi and jaya algorithm International Journal of Control and Automation, 2020
Design and performance analysis of low speed vertical axis windmill International Journal of Recent Technology and Engineering, 2019
Structural performance of non-linear analysis of turbo generator building using seismic protection techniques International Journal of Recent Technology and Engineering, 2019
Optimization of tribological behaviour on squeeze cast al6061/al2o3/sic/gr hmmcs based on taguchi methodandartificial neural network Journal of Advanced Research in Dynamical and Control Systems, 2019
Smart clothes with bio-sensors for ECG monitoring International Journal of Innovative Technology and Exploring Engineering, 2019
Characterization of Al6061 reinforced Al2O3 hybrid metal matrix composites with variable squeeze pressure Journal of Advanced Research in Dynamical and Control Systems, 2019
Mechanical, microstructure and wear behavior of the material aa6061 reinforced sic with different leaf ashes using advanced stir casting method International Journal of Engineering and Advanced Technology, 2018