Velammal Engineering College, is a private institution located in Chennai, India. Established in 1995, it was the first private engineering College to obtain an ISO 9001:2000 certificate.
Diabetic retinopathy (DR) is a leading cause of visual impairment worldwide. Early and accurate classification of disease severity using retinal fundus images is critical for timely diagnosis and prevention of vision loss. Automated systems can assist clinicians by improving screening efficiency and reducing diagnostic variability. This study proposes a novel feature-pitched classification model (FPCM) for automated classification of diabetic retinopathy stages using color fundus images, aiming to improve accuracy through enhanced feature extraction and spatial attention mechanisms. The proposed FPCM model extracts texture, intensity, and structural features from fundus images by identifying high-information regions referred to as pitch points. These features are processed using a concentric transformer learning (CTL) mechanism, which applies spatial attention across nested regions to capture both local and global patterns. The model was evaluated using the Kaggle Diabetic Retinopathy dataset. Performance metrics included accuracy, precision, and sensitivity. Statistical reliability was assessed using bootstrap-based confidence interval analysis, and results were compared with existing methods such as ERCN, EffNet-SVM, HPLBO_DMN, FCSAM, CLAHE TH, and MSTNet. The proposed model achieved an accuracy of 95.19
The present work aims to focus on the synthesis, growth, and characterization of a slow-evaporation-grown 2-amino-6-methylpyridinium hemifumarate dihydrate. X-ray diffraction analysis confirmed the crystalline quality of the compound with lattice parameters of a = 9.7112(10) Å, b = 14.4343(12) Å, c = 7.4723(7) Å and volume = 1040 Å3. Verification of the presence of functional groups was achieved through FTIR and FT-Raman studies. The identification of carbon and hydrogen molecules was confirmed via NMR analysis. UV–vis–NIR spectral studies were employed to determine the optical transmittance range and cut-off wavelength. The luminescent properties of the 2AF crystal were explored, while the dielectric properties of the 2AF crystal were analyzed through dielectric studies. Thermal analysis indicated stability up to 104 °C, with subsequent decomposition stages observed through differential thermal analysis (DTA). The crystal exhibited reverse saturable absorption (RSA) behavior, crucial for applications in optical limiting and laser protection. The microhardness analysis indicated that the crystal is classified as a soft material.
In this study, sustainable natural rubber (NR) composites reinforced with biocarbon and biosilica derived from Eleusine coracana straw waste were developed to explore eco-friendly alternatives to conventional petroleum-based fillers. Biocarbon and biosilica were incorporated individually and in hybrid form, and their effects on the mechanical, tribological, and thermal properties of NR were systematically evaluated. Hybrid biocarbon–biosilica composites exhibited a pronounced synergistic reinforcement effect compared to biosilica-only systems. The best formulation containing 10 phr biocarbon and 1.5 phr biosilica achieved superior performance, with a tensile strength of 40 MPa, tear strength of 56 N mm-1, hardness of 66 Shore A, and a controlled reduction in elongation at break. Tribological analysis revealed a significant improvement in wear resistance, with the specific wear rate reduced by 55
This study explores the reinforcement potential of modified nanosilica (mNS), derived from rice husk ash, in a 50/50 blend of chlorinated ethylene propylene diene monomer (Cl-EPDM) and chlorinated acrylonitrile butadiene rubber (Cl-NBR). The nanosilica was surface-modified using a 2:1 ratio of bis[3-(triethoxysilyl)propyl]tetrasulfide (TESPT) to polyoxyethylene(20)sorbitan monolaurate (TWEEN-20). Rubber nanocomposites were prepared via conventional two-roll mill mixing, and the effects of varying mNS content were assessed on processing behaviour, mechanical performance, swelling, oil resistance, morphology, compression set, and dynamic properties. Results showed that incorporation of mNS improved tensile strength, stress at 100
This study investigates the combined effect of di-isopropyl ether and Mn3O4-NiO nanocomposites on the performance, combustion and emission characteristics of a gasoline injection engine. Gasoline was blended with 10 % and 20 % DIPE by vol, and Mn3O4-NiO nanocomposites were incorporated at 50 and 100 ppm concentrations. The synthesized nanocomposites possessed phase purity, polycrystalline structure and particle sizes of 50-100 nm. Among the tested fuels, the blend containing 20 % DIPE and 100 ppm nanocomposite delivered the highest brake thermal efficiency of 33.5 % and the lowest specific fuel consumption of 0.305 kg/kWh, corresponding to improvements of 20 % and 19.44 % compared with gasoline. Peak cylinder pressure increased by 18 %, while unburned hydrocarbon and carbon monoxide emissions reduced by up to 47.37 % and 17.14 %, respectively. A slight rise in exhaust gas temperature was observed; however, nitrogen oxide emissions decreased by nearly 29 % lower than the D20 blend. This result highlights the potential of the DIPE-Mn3O4-NiO combination to improve combustion and emission characteristics in gasoline engines.
