Cape Institute of Technology

Abstract This research employed statistical and experimental design techniques to minimize drilling-induced delamination in a hybrid composite composed of eight alternating layers of glass and nylon fibers combined with a polyester matrix, fabricated using the hand layup method. The drill diameter, spindle speed, and feed rate were considered as input variables, while the delamination factor ( F d ) at entry and exit surfaces served as the response. Taguchi L27 orthogonal array was used to design the experiments, and the influence of each parameter was analyzed using the signal-to-noise ratio, ANOVA, Pareto, and graphical methods. Results showed that the drill diameter had the most significant effect, contributing over 60% to delamination variation with a p -value below 0.05, followed by feed rate and spindle speed. Delamination increased with larger drill sizes, higher feed rates, and lower spindle speeds, with more damage observed at the exit surface. The optimal drilling conditions of a 6-mm drill diameter, 1,250 rpm spindle speed, and 50 mm / min feed rate resulted in minimal delamination. These trends were validated through main effect plots, surface plots, and contour graphs. The regression-based model provided a reasonable fit to the experimental data, with an R 2 value above 0.95 and an average prediction error of about 0.3%. This research demonstrates that comprehensive statistical analysis and process optimization enhance drilling performance and reduce damage in hybrid composites, offering benefits for advanced manufacturing and civil engineering applications.

Video super-resolution (VSR) aims to reconstruct high-resolution video frames from their low-resolution counterparts while maintaining spatial details and temporal consistency. Unlike single-image super-resolution, VSR must exploit information distributed across neighboring frames, where motion, occlusion, blur, compression artifacts, and illumination variations can complicate reconstruction. Recent transformer-based restoration models have improved long-range temporal modeling, but their computational complexity and memory requirements remain barriers to real-time deployment. Existing VSR methods often face a trade-off between reconstruction quality and computational efficiency. Convolutional recurrent approaches provide efficient temporal propagation but may inadequately capture long-range dependencies, whereas transformer-based approaches model temporal relationships effectively but frequently require substantial computational resources. This study proposes a novel Temporal-Window Motion-Aware Transformer for Real-Time Super-Resolution (TWMAT-SR). The proposed framework combines lightweight convolutional feature extraction, motion-guided temporal alignment, localized temporal self-attention, and progressive feature reconstruction. A temporal-window attention mechanism restricts attention computation to informative neighboring frames, while a motion-aware alignment module dynamically compensates for inter-frame displacement. A recurrent feature-refinement pathway further propagates high-frequency information across successive frames without repeatedly processing the complete temporal sequence. The framework is optimized using a combined reconstruction, perceptual, and temporal-consistency objective. The experimental evaluation demonstrates that the proposed TWMAT-SR framework achieves 33.48 dB PSNR, 0.937 SSIM, and 0.110 LPIPS at the 50th training epoch on the REDS dataset for 4× video super-resolution. The model reaches an inference speed of 28.9 FPS, outperforming BasicVSR, VRT, and RVRT by 2.5, 12.8, and 9.2 FPS, respectively. The proposed method also obtains a temporal consistency error of 0.037, representing reductions of 30.2%, 22.9%, and 14.0% compared with BasicVSR, VRT, and RVRT. These results indicate that TWMAT-SR improves spatial reconstruction and perceptual fidelity while maintaining efficient inference and reduced temporal instability.

Purification water is used in many industries, such as power plants, refineries, and manufacturing for cooling the system to regulate the temperature and prevent equipment from overheating. Many chemicals process purified water as a solvent, diluents, or medium to carry out reaction without contamination. In some industries, it is used to mix with chemicals in processes. Purified water is used to clean the machinery, tools, and equipment in industries like pharmaceuticals, food, beverage and electronics fields. In some industries, like energy production, purified water is used in boilers to generate steam for power production. Various methods are available for converting saline water into purifying water. Those methods are such as desalination, vapor compression, reverse osmosis and electro dialysis. Solar water desalination is one of the most popular solar technologies. In this technology, the pure water is produced without salt content from the salty water including the bore water and seawater. A solar still is used and stores solar energy. A single basin, a single sloped solar still with a cover angle of 45 degrees covering a depth of 25 mm bore water level in the basin. Solar energy is no polluting energy and also a free renewable source of energy. Cuddappa stone is used to construct the solar still, and thermocol insulation is used to cover it in this work. Adding certain heat-absorbing materials to the solar still basin and boosting its efficiency while enhancing the rate at which bore water is purified. To assess the performance, the solar yield rate should still be compared to that of various energy-absorbing materials, such as steel balls, tin pieces, and lead balls. The steel ball gives a higher production rate than the rest of the energy materials. The maximum day yield efficiency of a solar still is 11 %, while the maximum day yield of steel balls dyed black is 1770 ml/m2/day. The lowest dayyield efficiency of a solar still without energy materials is 3 %, and its minimum daily yield is 490 ml/m2/day.

Chitosan-metal oxide nanocomposites are prospective multifunctional components with their biocompatibility and adjustable properties. The present paper describes the easy preparation of a nanocomposite made of chitosan and antimony trioxide (Sb _2 O _3 ) by modified ionotropic gelation and the accompanying physicochemical, thermal, mechanical, and biological observations. SEM, TEM, and AFM microscopy demonstrated consistent spherical particles with a diameter of ∼180 nm, and EDX, FTIR, and XRD spectroscopies indicated highly active polymer-metal interactions and the achievement of the composite. In TGA analysis, the Nanocomposites showed significant improvement in thermal stability, better glass transition temperature, and a slowdown in decomposition after being dip-coated onto glass fibers. The mechanical tests demonstrated that the nanocomposite performed better than pristine chitosan as well as Sb _2 O _3 in terms of hardness, tensile strength, flexural strength and wear resistance, which envisaged the superior structural integrity of the sample and prolonged its durability. Flame resistance applications demonstrated an optimum reduction in burning rate at a level of 3 wt% composite loading. Also, the nanocomposite displayed dose-dependent antibacterial action against Bacillus subtilis, Staphylococcus aureus and Pseudomonas aeruginosa , which were more effective than the individual components. These findings show promise of the use of chitosan-Sb _2 O _3 nanocomposites in thermal-protective, antimicrobial and structural applications, especially in coatings, textiles, and biomedical materials.