FACULTY OF PHYSICAL SCIENCE

Inventory management is one of the activities the stock manager undertakes to ensure optimal services of goods to effectively achieve its function. This obligation could only be made possible by automating the current manual and paper based inventory system. A web based inventory management system was proposed. A literature review was conducted on three technologies used in the inventory management that is Radio Frequency Identification (RFID), Barcode Technology and Near fieldCommunication (NFC). A review was also undertaken on the related works to identify the concept that could be adopted in the proposed system. A baseline study was performed to understand the challenges faced in the inventory management of goods. The results of The baseline study were analyzed and found that the challenges were attributed to the current manual inventory management system mainly due to human errors, incorrect inventory reporting and pilferage of items. The proposed prototype system was developed and tested and proved to be faster, efficient and more reliable than the manual and paper based system.

The research project investigates the phytochemical profile of the oil fraction derived from Justicia carnea leaves, utilizing Gas Chromatography-Mass Spectrometry (GC-MS). Methanolic extraction through maceration, followed by rotary evaporation for concentration, was employed to isolate the phytoconstituents of the plant material. A portion of the concentrated crude extract was subjected to a detailed phytochemical screening, which identified bioactive classes such as flavonoids, alkaloids, and saponins, indicating the plant's rich chemical composition. For further analysis, another fraction of the crude extract underwent vacuum liquid chromatography (VLC) using a gradient of solvent systems. The hexane:ethyl acetate fraction was selected for GC-MS analysis, where phytol, a diterpenoid alcohol, was identified as the major compound with a retention time of 23.74 minutes and an abundance of 67.286%. Phytol, a well-documented diterpene, plays a significant physiological role and is associated with multiple biological activities, including anti- inflammatory, antioxidant, and antimicrobial properties. The convergence of phytochemical screening and GC-MS results underscores the chemical complexity and pharmacological relevance of Justicia carnea's oil fraction. These findings support further bioactivity-guided studies of this botanical source, which may yield novel bioactive molecules with therapeutic potential for addressing human health concerns

This study examines the essence of effective inventories control and management to manufacturing companies with particular emphasis on Ama Greenfield Breweries plc. The aim of this study is to investigate and ascertain areas of lapses by the company and offer effective ways and solutions in which the manufacturing company can explore the services of inventory management to affect its objectives. In carrying out this study, various research instruments such as questionnaires and oral interview were used to collect data from respondents and a research design was adopted with a sample size of 52. The statistical tool used for this work is Chi square. Based on the analysis, it was discovered that inventory management plays a vital role in the manufacturing company. A well functional inventory management following the recommendations can bring about proper management thereby enhancing proper and effective production and it will equally ensure the effective, efficient and adequate use of materials and resources in the manufacturing company.

This study examines the structural, mechanical, optical, and electronic properties of sodium niobate (NaNbO₃) perovskite using first-principles calculations within Density Functional Theory (DFT). The Generalized Gradient Approximation (GGA) and pseudopotentials in Quantum ESPRESSO were used for all computations. The optimized lattice parameters confirmed that NaNbO₃ crystallizes in an orthorhombic structure with space group Pbnm. The calculated elastic constants and related moduli met Born’s criteria for mechanical stability. The Pugh and Poisson ratios show that the compound is near the brittle–ductile boundary. Band structure results indicate an indirect band gap of about 0.4 eV, with the valence band maximum at the Γ point and the conduction band minimum at the X point. The density of states revealed strong interaction between Nb-4d and O-2p orbitals, confirming covalent bonding within the Nb–O octahedra. These findings show that NaNbO₃ is a stable indirect semiconductor with potential use in optoelectronic and photovoltaic devices.

In many developing regions, loan management processes remain a significant challenge due to poor record keeping, limited accountability between lenders, borrowers, and guarantors, and the absence of structured digital administration tools. This project focuses on the design and implementation of an Automated Loan Record Management System delivered through a web- based platform, the LRMS Platform. The system was developed using Object-Oriented Analysis and Design (OOAD) and a prototyping approach to ensure simplicity, usability, and scalability. The platform comprises nine modules: Administrator Login, Borrower Registration with fingerprint capture and photograph upload, Borrower and Guarantor Details with SMS reminder management, Loan Issuance, Bank Details, Repayment tracking, a Database Dashboard for visual analytics, a Saved Records interface for searchable borrower and guarantor retrieval, and an Offline Support page. Testing confirmed that the system accurately handles borrower registration, loan record management, repayment tracking, and administrator-initiated SMS reminders to borrowers and guarantors. The system is reliable, structured, and practical for lending organizations and cooperative societies seeking to improve loan administration, reduce
defaults, and strengthen accountability among all stakeholders

In conventional data envelopment analysis, decision making units are considered as a whole, that is, internal stages are generally ignored. In real life, most systems are composed of many divisions operating interdependently via the intermediate products that are created by some divisions and consumed by some others within the system. The aim of the study was to develop a formalized network mix efficiency model that can deal with both controllable and uncontrollable inputs as well as desirable and undesirable outputs by considering the internal structures of systems. A linear programming approach of data envelopment analysis was used by taking the ratio of slack based measure and directional distance function to measure the eco-efficiency of 54 African countries. The inputs into the system were classified as controllable and uncontrollable while the output as desirable and undesirable. Stage one captured agricultural production efficiency, while stage two evaluated the environmental impact of carrying out agricultural activities. The network efficiency model identified sources of inefficiencies from the components of a complex system rather than looking at the system as a black box. Controllable inputs and undesirable outputs were minimized while the desirable outputs were maximized. The approach provided policymakers with robust benchmarks for enhancing agricultural productivity while mitigating environmental degradation.

This research explores the evolving landscape of accessibility in user interface (UI) and user experience (UX) design, emphasizing the trends and innovations shaping inclusive digital environments. As technology becomes increasingly central to education, communication, and commerce, ensuring digital accessibility has grown into a fundamental design necessity rather than an afterthought. The study examines how accessibility has progressed from compliance-based frameworks to a human-centered, innovation-driven practice. Through a qualitative, descriptive case study, the research integrates literature review, prototype testing, and chat-based feedback to evaluate how accessibility-focused UI/UX design can enhance inclusivity and usability for users of varying abilities. The developed prototype demonstrates accessibility-oriented features inspired by global standards such as the Web Content Accessibility Guidelines (WCAG) and informed by current technological trends, including artificial intelligence (AI), adaptive systems, and voice-based interfaces. Participant’s feedback, analyzed through narrative analysis, revealed
that accessible design elements such as clear navigation, readable interfaces, and assistive tools improve overall usability for all users, not just those with disabilities. The study also identifies persistent challenges in awareness, design execution, and standardization, which continue to hinder the full realization of digital inclusivity. Findings from this research highlight the potential of accessibility to serve as a driver of creativity and innovation in digital design. The study concludes that the future of UI/UX accessibility lies in proactive integration, interdisciplinary collaboration, and continuous user-centered iteration. By embedding accessibility principles into every stage of design and development, the digital ecosystem can become more equitable, adaptive, and future-ready.

The management of student complaints in many tertiary institutions relies on fragmented, manual processes that lead to inefficiencies, delayed resolutions, and a lack of transparency and accountability for course representatives and faculty administration. This project addresses this systemic challenge by designing and implementing a web-based Faculty Complaint Management System. The system provides a centralized platform featuring three distinct user roles (Administrator, Lecturer, Course Representative) and utilizes PHP, MySQL, and Bootstrap for development. Its core functionality includes secure, role-based access control, an intuitive interface for course representative complaint submission and real time status tracking, and robust administrative tools for user management and automated complaint routing based on lecturer assignments. The methodology involved a systematic approach from requirements analysis and UML- based design to implementation with best practices for data integrity and security, including password hashing and protection against common web vulnerabilities. Rigorous testing across multiple levels including unit, integration, system, and user acceptance testing validated the system's functional reliability and usability. The completed system successfully replaces the manual process, providing transparency, accountability, and efficiency through centralized tracking, activity logging, and statistical reporting capabilities. The solution contributes a validated, context-specific application of open-source technology to enhance administrative service delivery in higher education

During audio mixing and mastering, particularly when using equalization and compression, manually matching the perceived volume levels before and after plugin processing is a critical yet time-consuming task. This manual process involves repeatedly analyzing audio segments to ensure volume stability, which is crucial for a balanced mix. This project aims to automate this volume matching process. The proposed solution is a Reaper Lua script (potentially incorporating JSFX for analysis) that reads both the input and output audio levels of a track or effect chain. It will then automatically balance the output audio's loudness to match the input, offering the user choices for the measurement standard, such as LUFS, RMS, or peak dB, thus ensuring efficient and accurate gain staging

The rising prevalence of mental health challenges globally, coupled with limited access to timely psychological support, has highlighted the need for innovative technological solutions. This study focuses on the development of an AI-powered chatbot designed to provide mental health support by offering real-time, accessible, and personalized interactions to users experiencing stress, anxiety, or depressive symptoms. The research involved designing and implementing a conversational agent capable of understanding natural language inputs, delivering evidence-based interventions, and directing users to professional help when necessary. A prototype system was developed using machine learning and natural language processing techniques, with performance evaluated through user engagement, response accuracy, and perceived helpfulness. Findings indicate that AI-powered chatbots can serve as a supplementary tool for mental health support, offering continuous availability and reducing barriers to care. The study underscores the potential of integrating artificial intelligence into mental health services, providing an accessible platform for early intervention and emotional assistance.