Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology

Industrial waste valorization for sustainable self-healing epoxy vitrimer hybrid composites: Taguchi optimization and machine learning-based performance prediction

This study investigates the development of sustainable self-healing vitrimer composites reinforced with recycled carbon fibers (rCF), waste cotton textile fibers (WCTF), and graphene nanoplatelets (GNP). The rCF, WCTF and GNP were in the range of 20–30%, 10–20%, and 0.5–1%, respe...

Real-time partial shading detection and prediction in photovoltaic systems

The occurrence of partial shading (PS) in photovoltaic (PV) systems has a profound impact on their operational performance, as it triggers the formation of hotspots, ultimately resulting in localized heat and potential irreversible damage to the PV modules. In response to these c...

Design and analysis of an X-band low-RCS A-sandwich radome based on double-layer frequency-selective surface for modern defence systems

This article presents the design of an X-band A-sandwich radome based on a double-layer frequency-selective surface (FSS) to reduce the radar cross-section (RCS) of the co-designed antenna. The proposed radome is designed with bandstop FSS elements on the top and bottom surfaces...

Explainable AI-assisted sustainable performance optimization of Nano-enhanced rapeseed oil blends in ci engines for optimized engine operation

This study investigates the influence of advanced fuel injection timing on the performance, combustion, and emission characteristics of a compression ignition engine fueled with a rapeseed oil emulsion–pentanol blend (70D25GS5P) supplemented with 150 ppm TiO₂ nanoparticles. Exper...

Seed yield optimization in soybean: integrating biochemical and environmental factors using TabPFN for precision agriculture

Precision agriculture seeks yields and optimizes the value of resources consumed by data-driven decisions. Soybean is an important crop worldwide, significant for food and industrial use. Traditional methods fail to accurately predicting seed yield because plant growth is complex...

DTARNU-Net: Dense Tiered Attention Residual Nested U-Net for CT Liver Tumor Segmentation

Liver tumor segmentation is a significant task in clinical imaging that involves detecting liver tumors and distinguishing them from the surrounding liver tissue in CT scans. Precision segmentation performs important roles in the initial detection of liver cancer, treatment plann...

Leveraging IoT‐Aided Robotics for Enhanced Efficiency in Urban Traffic Management Utilizing Multi‐Component Attention Graph Convolutional Neural Network Intended for Real‐Time Traffic Monitoring Systems

ABSTRACT Maintaining traffic restrictions has become more difficult because growing number of vehicles on the road, particularly in locations with high populations. Efficient traffic monitoring and road safety management have become critical challenges due to the rapid increase i...

FEA-Assisted nanostructured piezoelectric sensor and deep learning framework for noninvasive tumor detection and tissue stiffness analysis

Biosensors have long been used in environmental monitoring and clinical diagnostics for detecting harmful bacteria, viruses, and biomolecules, evolving from simple biological sensing systems to advanced nanofabrication-based devices. With help of nanotechnology, nano-biosensors h...

Hierarchical grouped convolution and multi-scale vision transformer for uncertainty-aware early breast cancer detection using mammography

Abstract Early breast cancer detection using mammography remains challenging because existing deep learning methods often emphasize either local lesion characteristics or global contextual information, while providing limited uncertainty quantification and clinically reliable pre...

A comprehensive review of nanomaterial advances in green hydrogen production and storage systems

Green hydrogen is a clean and flexible carrier of energy that has a bright future due to the shift in the entire world to sustainable energy systems. The review explores how nanomaterials are vital towards improving the performance, efficiency, and sustainability of the green hyd...

Exploring the importance of flexible manufacturing system performance variables for textile industries

Purpose Manufacturing firms in the textile sector face simultaneous pressure to enhance responsiveness, maintain quality, shorten lead times, and align production with sustainability expectations. In the current Industry 4.0/5.0 environment, flexible manufacturing systems (FMS) a...

A comparative finite element study of bioinspired porous hip implant stems optimized using nTopology-based lattice architectures

One major cause of implant loosening after total hip replacement is the mismatch in stiffness properties between the metallic prostheses and the cortical bones. This paper evaluates the structural effectiveness of four different bioinspired porous structures, specifically Honeyco...

Fatigue Damage of AA2024 Fiber–Metal Laminates With Architected TPU Interlayers and Graphene‐Modified Interfaces

ABSTRACT This study investigates the fatigue behavior of Aluminum 2024 fiber–metal laminates incorporating three‐dimensionally printed thermoplastic polyurethane core architectures and graphene‐modified adhesive interfaces. Three core geometries, namely, diagonal, diamond, and he...