International Journal of Research in Science & Engineering

Character of soursop seed (Annona muricata) as antimicrobial agent for packaging

2025-04-01T09:29:41+00:00

This study investigated the phytochemical composition of soursop (Annona muricata) seeds and assessed their potential as a bioplastic material. Phytochemical screening confirmed the presence of alkaloids, flavonoids, tannins, phenolics, and saponins, which contribute to polymer formation and antimicrobial properties. Fourier Transform Infrared Spectroscopy (FTIR) analysis identified functional groups essential for biopolymer synthesis. A bioplastic film was developed using soursop seed extracts and tested for mechanical strength, biodegradability, and antimicrobial activity. The material exhibited moderate tensile strength and flexibility, demonstrating suitability for packaging applications. Biodegradability testing showed significant weight reduction over time, indicating environmental sustainability.

Antimicrobial analysis revealed inhibition of Escherichia coli and Staphylococcus aureus, suggesting potential use in food preservation. Comparative analysis with conventional bioplastics confirmed the viability of soursop seed-based bioplastic as an eco-friendly alternative. The findings highlight the potential of agricultural by-products in biopolymer production, contributing to waste valorization and sustainable packaging solutions.

Perlas (Piezoelectric energy for residential lighting and advance solutions): an arduino uno-based piezoelectric energy harvesting system for residential lighting applications

2025-04-01T09:43:21+00:00

This study explores the development and testing of a piezoelectric energy-harvesting prototype designed to convert mechanical stress from foot traffic into electrical power for residential lighting applications. With the increasing demand for sustainable energy solutions, piezoelectric sensors present a viable alternative for generating electricity from everyday activities. The prototype consists of piezoelectric sensors integrated into a flooring system, an Arduino Uno for energy tracking, a voltage regulator, and an energy storage component. A series of experiments were conducted to evaluate the system’s efficiency, focusing on the relationship between applied force and voltage output. The results revealed a strong positive correlation (r = 0.92) between mechanical stress and energy generation, indicating that increased force leads to higher voltage output. Additionally, an ANOVA test confirmed a statistically significant difference (p < 0.05) in energy output across varying pressure levels, demonstrating the effectiveness of the system in energy harvesting. The prototype successfully stored harvested energy and powered LED lights, validating its potential for practical applications. However, improvements in energy storage capacity and circuit efficiency are necessary for large-scale implementation. This study highlights the feasibility of integrating piezoelectric energy harvesting into residential settings, contributing to the advancement of sustainable and renewable energy solutions. Future research should explore optimization techniques, larger-scale applications, and economic feasibility assessments to enhance its viability for broader use.

Elite opposition-based social spider optimization for solving benchmark problem

2025-11-06T10:37:42+00:00

Metaheuristic algorithms are powerful tools for solving complex optimization problems where traditional methods fail. The Social Spider Optimization (SSO) algorithm, inspired by the cooperative foraging behavior of spiders, is a notable swarm intelligence technique. However, it can be prone to premature convergence. This paper presents an enhanced variant, the Elite Opposition-Based Social Spider Optimization (EOSSO) algorithm, which integrates an elite opposition-based learning (OBL) strategy and an elite selection mechanism into the standard SSO framework. This integration aims to improve population diversity, enhance global exploration, and accelerate convergence. The performance of EOSSO is rigorously evaluated on a comprehensive set of 23 benchmark functions, including unimodal, multimodal, and fixed-dimension multimodal problems. Experimental results demonstrate that EOSSO significantly outperforms the standard SSO and other well-known metaheuristics in terms of solution accuracy, convergence speed, and stability. The algorithm exhibits a remarkable ability to escape local optima and refine solutions efficiently, proving its robustness and effectiveness as a high-performance optimizer for complex landscapes.