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Daily Archives: May 14, 2026

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Comparative Process Design and Modeled Performance of a Small-Scale Bioethanol Production System Using Agricultural Residues

Authors: Samriddha Sharma, Om Prakash Sondhiya

Abstract: The increasing environmental and economic concerns associated with fossil-fuel dependency have intensified global interest in renewable transportation fuels. Among alternative biofuels, bioethanol has emerged as one of the most commercially viable and widely adopted options because it can be produced from renewable biomass resources and integrated into existing fuel infrastructures. This study presents a comparative process-design assessment of a compact bioethanol production system utilizing three abundant lignocellulosic agricultural residues: rice straw, sugarcane bagasse, and corn stover. A literature-informed process model was developed for a small-scale educational bioethanol unit comprising feedstock preparation, dilute-acid pretreatment, enzymatic hydrolysis, yeast fermentation, and reflux-assisted distillation. The investigation evaluates the influence of biomass composition on fermentable sugar recovery, ethanol yield, process efficiency, and energy demand. The modeled analysis indicates that sugarcane bagasse demonstrates the most favorable conversion performance under the selected operating assumptions, yielding approximately 74 g/L fermentable sugars and 34.5 g/L ethanol prior to separation. Corn stover exhibited intermediate performance, whereas rice straw produced comparatively lower ethanol concentrations because of its elevated ash and silica content, which reduce carbohydrate accessibility during pretreatment. The results further reveal that pretreatment and distillation account for the majority of the process energy requirement, highlighting the importance of heat integration, solids management, and process optimization in improving system efficiency. The study concludes that a modular small-scale bioethanol system can serve as an effective educational and research platform for demonstrating biomass-to-fuel conversion technologies. Furthermore, transparent presentation of modeled assumptions and calculation procedures strengthens the academic reliability of design-stage biofuel studies intended for instructional and comparative analysis.

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Number Plate Recognition Using Machine Learning

Authors: Mulay tanuja suresh, Dr.N.A.Doshi, Shaikh Aslam Amir

Abstract: Number plate recognition is an image processing technology which uses number (license) plate to identify the vehicle. The objective is to design an efficient automatic authorized vehicle identification system by using the vehicle number plate. The system can be implemented on the entrance for security control of a highly restricted area like military zones or area around top government offices e.g. Parliament, Supreme Court etc. The developed system first detects the vehicle and then captures the vehicle image. Vehicle number plate region is then converted into grayscale. The number plate is then extracted. Then, using KNN (K- Nearest Neighbours) algorithm is used to recognize the digits and the alphabets. This data can be used to find vehicle’s owner, place of registration, address, etc. The system is implemented using Python, and its performance is tested on real images. It is observed from the experiment that the developed system successfully detects and recognize the vehicle number plate on real images.

DOI: https://doi.org/10.5281/zenodo.20176415

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