Afe Babalola University Based Journals
Not a member yet
992 research outputs found
Sort by
Evaluating the Effectiveness of Radio Drama in Promoting Women’s Empowerment in Niger State
Get PDFThis study evaluated the effectiveness of radio drama as a strategic communication tool for promoting women’s empowerment in Niger State, Nigeria. Using a mixed-methods descriptive research design, data were collected from 300 women across Niger, Abuja Municipal Area Council (AMAC), and Nasarawa State. Quantitative data were complemented by focus group discussions and key informant interviews. The study was anchored in the Entertainment-Education strategy and Social Learning Theory, which underscore the capacity of storytelling to inform and transform societal norms. Findings revealed that over 78% of respondents listened to radio drama at least occasionally, with a significant majority describing the content as relevant to their lived experiences. Participants reported increased self-confidence, engagement in family decision-making, and a heightened awareness of women's rights and agency. However, the study also identified limitations, including limited feedback mechanisms, cultural resistance in some rural areas, and the absence of clear pathways for translating awareness into concrete action. The study concluded that while radio drama is a potent tool for raising consciousness and challenging patriarchal norms, its impact is mediated by socio-cultural and infrastructural factors. It recommended that programme developers localise content linguistically and culturally, incorporate listener feedback, and strengthen partnerships with community leaders and support organisations. Ultimately, the strategic use of radio drama can contribute significantly to gender equality when embedded in a holistic, participatory development communication framework.
The Evaluating Business Strategies for Attracting Foreign Direct Investment in Developing Economies: A Case Study of Nigeria
No full textThis study evaluated Nigeria’s business strategies for attracting foreign direct investment, based on the aspects of regulatory changes, infrastructure improvement, and institutions. Cross-sectional data from 467 firms were subjected to pooled regression analysis within the context of an ex-post facto comparative research design to examine the hypothesis. Regression analysis established that trade reforms had a positive and statistically significant coefficient of 7.25 (p<0.05), followed by infrastructure development with a statistically significant coefficient of 145.60(p<0.000), while institutional regulatory frameworks had a positive moderate coefficient of 6.85 (p<0.000). However, high corporate leverage negatively influenced investment (β=-4.50, p=0.007), though the results showed that the positive effect of customs integration was insignificant (β=0.85, p=0.382). Following these policies, the Foreign Direct Investment (FDI) inflow into Nigeria was 8.5 billion in the same year. This policy analysis also outlined that bureaucratic constraints, foreign exchange challenges, and reliance on foreign exchange earnings and mineral exports prompted dependence on profitable but volatile speculative capital flows, which stood at 68% of the total in 2019. The horizontal FDI include investment plans like Nestlé’s $1.8 billion in agro-processing, where it was also seen that other sectors of the economy had poor linkages with small and medium enterprises. There is the need for systemic changes that foster good governance, policy stability, and infrastructure development involving public-private partnerships for catalytic investment
Process-Composition Design of Hypoeutectic Aluminum-Silicon Alloy for High Performance Wear Resistance Application
Get PDFThis study investigates the process-composition design of hypoeutectic aluminium-silicon alloys aimed at improving the wear behaviour of the alloy for tribological application. Hypoeutectic Al-Si alloys with percentage composition of silicon ranging from 3 – 7.5% were cast at varying pouring temperatures of 700, 750 and 8000C. The impact of the process-composition parameters on wear rate and the microstructures of the alloy were determined using tribor testing apparatus and scanning electron microscopy/energy dispersive spectroscopy (SEM/EDS) respectively. The results obtained show that increasing silicon content from 3 – 7.5% significantly improved the wear rate of the alloy from 0.0360 – 0.0120 mg/m with optimum pouring temperature value at 7000C. The SEM micrographs indicate that higher percentage composition of silicon yielded the formation of more numbers of primary silicon phases with intermetallic phases that reduced material loss while optimum pouring temperature influenced solidification rate leading to a refined uniform homogeneous phases distributed in the microstructures. It was concluded that process parameter optimization carefully tailored through combination of silicon percentage composition and pouring temperature enhances the wear performance of Al-Si alloys for engineering applications in wear-critical environment
Intelligent Web App for Flash Flood Prediction in Nigeria’s Coastal Regions
Get PDFMany coastal cities in Nigeria and around the world are faced with the menace of flash floods and many times, it temporarily disrupts the socio-economic activities of residents. This project aims to address this challenge by developing a smart web application using machine learning to intelligently predict flash flood occurrence and offer recommendations. In order to achieve this, the random forest machine learning algorithm is utilized to analyze environmental data such as rainfall, river levels, and soil moisture necessary for the prediction of a flood which are captured in real-time using the OpenMeteo API. The machine learning model is then trained using these environmental variables and integrated into a web application for easy user interaction. The frontend of the web application is built with TypeScript, React.js, and Tree.js, providing an interactive and user-friendly interface for visualizing flood predictions, while the backend is built using MongoDB and python (FLASK framework). The goal is to offer accurate, real-time flood forecasts to help individuals prepare and respond effectively. This project demonstrates the integration of data science and web development to create a practical tool for disaster risk management. The random forest model was evaluated using the standard metrics for evaluating machine learning models and showed the following results; Accuracy of 96%, precision of 75% and recall of 91%. In addition, the model, showed a Real-time latency of less that one second, which is indicative of a fast response to changing environmental data input. Since flood conditions can change rapidly, this low real-time latency shows that the web is able to respond quickly to new sensor or satellite data input
Alternative Framework for Generator Coherency Analysis and Controlled-Islanding for Grids with High Penetration Levels of Inverter-Based Renewables
Get PDFThe increasing integration of inverter-based renewable energy sources has significantly altered power system dynamics and reduced inertia. Identifying coherent generators in such low-inertia systems remains a major challenge due to the dynamic influence of renewable variability. Previous research considered rotor angles and rotor speed separately. Also, the fast dynamics introduced by inverter-based renewables on power system variables make it pertinent to simultaneously consider rotor angles and rotor speed dynamics for coherency detection. Moreover, many authors have established coherency detection schemes but few have validated their methods with controlled islanding making their methods less practical for the modern grid with renewables. This paper proposes a unified coherency detection framework that combines rotor angles and rotor speeds within a dynamic state vector to capture both oscillatory and speed dynamics. An adaptive coherency threshold is computed from the geometric mean of the Euclidean distances between rotor state time series of distinct generators, allowing the threshold to adjust to changing system conditions. The framework is validated on the IEEE 30-bus system and applied to controlled islanding based on network topology and generation–load balance. The proposed framework achieved smooth dynamic responses following disturbances. These results confirm the method’s suitability for real-time application and its potential to improve resilience in modern power systems with high renewable integration
Employer-Valued Multi-Quotient Competencies and Information Technology Graduate Readiness: Insights from Seven Regions in Tanzania
Get PDFThe global IT sector increasingly demands graduates who combine technical expertise with interpersonal, emotional, and adaptive competencies. However, higher education in many developing contexts continues to emphasise cognitive and technical skills, creating an employability gap. This study examines employer-valued multi-quotient competencies, including Intelligence Quotient (IQ), Social Quotient (SQ), Emotional Quotient (EQ), and Adversity Quotient (AQ), and their role in shaping IT graduate readiness in Tanzania. Using a concurrent mixed-methods design, data were collected from 45 employers across five IT sub-sectors, 480 final-year students from ten higher learning institutions, and a curriculum review of those same institutions. Quantitative data were analysed using descriptive statistics, chi-square tests, factor analysis (KMO = 0.81; Bartlett’s p < .001), and regression modelling, while qualitative data underwent thematic analysis. Findings show that although IQ remains a baseline requirement, EQ (β = 0.39, p < 0.01) and AQ (β = 0.35, p < 0.05) are better predictors of graduate readiness. Students undervalued these dimensions, and curricula embedded them inconsistently. The study contributes new empirical evidence by integrating employer, student, and curriculum perspectives, advancing understanding of multi-quotient competence as a holistic framework for aligning IT education with workforce expectations
Responsive Web-Based Learning Platform for Early Detection of Breast Cancer
Get PDFCancer continues to be a serious global health concern. Misconceptions, stigma, and cultural beliefs exacerbate the issue of cancer awareness in many communities, leading to late-stage diagnosis when treatment options are scarce. It has been observed that early discovery and availability to trustworthy information are critical to both prevention and control. In this study, a responsive web-based platform that combines web technology and human-centered design is designed and developed with the goal of improving cancer education for the general population. The platform was developed using a modular architecture. The front end of the study design utilizes Next.js, React and TypeScript for the we-based learning platform while the back end is designed using PostgreSQL, deployed via Supabase for persistent and dynamic storage of educational content. REST and GraphQL APIs were also used to implement a seamless integration with the React-based front end. Key system components include an interactive homepage, categorized cancer information modules, and multilingual content delivery to support diverse user demographics. The platform was tested across multiple devices to ensure compatibility and responsiveness, leveraging media queries and flexible grid systems for optimal display. This implementation demonstrates the viability of web-based health education tools, particularly in regions with limited access to structured medical information. It also supports multiple languages through dynamic language selection and database-driven content localization, enhancing accessibility in multilingual communities
A Critical Discourse Analysis of Selected Hate Comments on X Social Media Platform in the 2023 Presidential Election Nigeria
No full textHate comments on social media significantly impacted Nigeria’s political discourse, particularly during the 2023 presidential election, fueling socio-political divisions and electoral tensions. While Critical Discourse Analysis (CDA) has been widely studied in other contexts, the ideological and linguistic mechanisms underlying hate comments in these elections remain underexplored. This study applies CDA to analyse selected hate comments from the election period. Using a descriptive qualitative design, 30 hate comments from X (formerly Twitter) were purposively selected based on their linguistic patterns, thematic structures, and engagement levels. Van Dijk’s socio-cognitive model, Fairclough’s three-dimensional framework, and Halliday’s Transitivity theory were applied to identify ideological patterns and discourse structures in these comments. Findings revealed that hate comments strategically employed derogatory labeling, neologisms, and metaphors to delegitimise political opponents, reinforce biases, and deepen socio-political divisions. Transitivity analysis highlighted how language shaped ideological narratives of radicalism, exclusion, and power struggles. Socio-cultural factors such as religion, ethnicity, and historical grievances further fueled these trends, impacting voter behavior, institutional trust, and electoral participation. The paper concluded that hate comments reinforced an ‘Us versus Them’ binary, exacerbating political and ethnic tensions. It recommended government-led policy interventions to regulate online hate speech and digital literacy initiatives to educate social media users on the consequences of hate-driven discourse
From ‘Adeola’ to ‘HarDeyOlar’: Unpacking the Effects of Self-Naming Trends on Identity and Language in GenZee Subcultures
Get PDFThis study explores the self-naming phenomenon among GenZee students in selected tertiary institutions in Ekiti State, Nigeria, focusing on the alteration of traditional Yoruba names (e.g., “Adeola” to “HarDeyOlar”) as a form of cultural expression and self-identity reconfiguration. Rooted in both postcolonial and sociolinguistic frameworks, the work examines how GenZees’ engagement with self-naming reflects deeper issues of indigenous language use, identity transformation and the dynamics of modernity in postcolonial African societies. The study is situated within discussive paradigms regarding the impact of globalisation on local cultures, especially indigenous naming practices which signified traditional or cultural heritage, family history and social status within the Yoruba culture. Data were collected through semi-structured interviews and focus group discussions with 60 purposively selected GenZee students from two universities and polytechnics (private and public) in Ekiti State, to capture the personal motivations behind name alterations. Using thematic analysis, the data were analysed to identify recurring themes such as perceived modernity, global identity aspirations, and the perceived obsolescence of indigenous linguistic forms. Findings reveal that self-naming serves as both an assertion of individual agency and a response to societal pressures favouring westernised or hybrid identities, potentially accelerating the erosion of indigenous language usage among youths. This study contributes to the discourse on cultural retention versus adaptation in African societies, highlighting self-naming as a significant factor in the negotiation between tradition and modernity. The implications of these trends underscore broader challenges in cultural preservation, language sustainability, and identity politics in Nigeria and similar postcolonial contexts
Childhood Trauma and the Burden of Prophecy in Chigozie Obioma's The Fishermen
Get PDFChildhood trauma has emerged as a critical subject in contemporary literary and psychological discourse, reflecting the enduring scars left by early adverse experiences. In Chigozie Obioma’s The Fishermen (2015), trauma is not merely an outcome of physical violence but is triggered by a prophecy that destabilises the Agwu brothers’ lives. The madman’s utterance functions as a psychic intrusion, dismantling familial unity and transforming youthful innocence into suspicion, paranoia, and eventual fratricide. This paper analyses the representation of childhood trauma in the novel through the lens of psychoanalytic theory, drawing on Sigmund Freud’s concepts of repression, id, ego and super-ego. The study argues that the prophecy embodies trauma’s ungraspable quality, a linguistic event whose meaning overwhelms the child’s interpretive faculties and reemerges in destructive repetitions. By foregrounding the psychic burden carried by children, the paper reveals how Obioma explores the shattering of innocence as both a personal tragedy and an allegory of Nigeria’s fractured postcolonial state. Ultimately, the paper contends that The Fishermen situates childhood trauma at the intersection of the individual and the familial, offering insight into how prophecy, fear, and violence scar not only individual lives but also the collective consciousness of a nation