Afe Babalola University Based Journals
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Evaluation of Optimized Carbonized Wheat Husk-Reinforced AA6061 Composite for Automotive Components Applications
Get PDFIn the pursuit of sustainable and lightweight materials for automotive applications, metal matrix composites (MMCs) have emerged as promising candidates due to their superior strength-to-weight ratios, enhanced wear resistance, and tailored mechanical properties. Aluminum-based composites, particularly those with AA6061 as the matrix, are widely recognized for their excellent corrosion resistance, weldability, and mechanical performance. However, there remains a need to improve the environmental sustainability, mechanical properties and lightweight properties of these materials through the incorporation of eco-friendly, sustainable, light and low-cost reinforcements. In this work, the reinforcement particulate, carbonized wheat husk (CWH) was gotten after pulverizing wheat husks to increase the surface area and charging it into a muffle furnace, subjected to a temperature of 900 0C for 3 hours. Thereafter, AA6061 reinforced composites (AA6061-CWH) were produced using the stir casting method, optimized through the Taguchi's L9 orthogonal array. The composite developed at optimum parameters was then selected and compared with selected automotive components. The optimized AA6061-CWH composite offers a well-balanced mechanical profile. It delivers decent tensile strength, exceptional hardness, good impact resistance, and a lower density, making it an appealing material choice for a broad spectrum of automotive applications. Its application could support the automotive industry’s ongoing pursuit of improved performance, efficiency, and sustainability through the use of affordable and eco-friendly materials
Lightweight CNN Architectures for Fault Diagnosis of Power Generator sets: A Comparative Study of MobileNet and AlexNet
Get PDFThe use of power generator sets (3.5kVA – 5.5kVA) for domestic and commercial backup supply has become a mainstay in Nigeria due to the unstable electricity from the grid. To keep these backup supplies running, traditional diagnostic approaches that are reliant on manual inspections and physical measurements have been adopted. These are often time-consuming, reactive, and unsuitable for real-time monitoring. To address these challenges, a machine learning approach is presented by performing a comparative analysis of MobileNet and AlexNet convolutional neural networks for automated audio-based fault diagnosis in 5kVA generators. Fault signatures are obtained from acoustic data recorded from 25 generator units under five operational states—Normal, Caburetter, Exhaust, Valve, and Plug faults. Mel-Frequency Cepstral Coefficients (MFCC), Continuous Wavelet Transform (CWT), and Short-Time Fourier Transform (STFT) were employed to transform the raw audio signals into two-dimensional spectrograms that contain both temporal and spectral fault signatures. Using transfer learning, these spectrograms were utilized as input features to train versions of MobileNet and AlexNet, which were pre-trained on ImageNet weights. Their performance was evaluated using accuracy, precision, recall, F1-score, and ROC-AUC metrics. Results obtained from the evaluation metrics show that MobileNet significantly outperformed AlexNet across all feature transformations (MFCC, CWT, and SSTFT). It achieved a peak accuracy of 92% and an AUC of 0.99 with STFT spectrograms. In contrast, AlexNet achieved lower accuracies (54–59%), indicating lower discriminative power. The class-wise ROC-AUC analyses confirmed that MobileNet achieved near-perfect classification, particularly in distinguishing between Normal and any of the fault conditions, while AlexNet struggled with subtle classes, such as Plug and Valve faults. These findings indicate that STFT is the most discriminative spectrogram and MobileNet is the best-performing diagnostic framework. This makes it suitable for deployment in resource-constrained environments and edge devices. This research contributes to the advancement of intelligent, real-time condition monitoring of domestic generator sets, thereby reducing downtime and enhancing energy reliability in off-grid contexts
Development of AI Based Gesture and Voice Control Home Automation System
Get PDFThis study introduces the development and application of an AI-driven smart home system that combines voice and gesture controls to improve user convenience, accessibility, and energy conservation. The research aimed to create a system for managing home appliances through voice instructions and hand movements, assess the effectiveness of each control method, and evaluate their suitability for inclusive automation, especially for people with mobility challenges. The approach integrated hardware and software in a modular framework. High-quality microphones paired with natural language processing enabled voice recognition, while an ADXL335 accelerometer detected motion-based gestures. An Arduino UNO microcontroller served as the central hub, processing inputs and interfacing with appliances through a wireless relay module. Safety features and multi-input validation were incorporated to reduce errors from external factors like ambient noise or inconsistent gestures. Testing revealed that gesture control succeeded in 42 of 50 trials with an average response time of 1.89 seconds, while voice control achieved 44 successful trials with a quicker response time of 1.74 seconds. These findings demonstrate the potential for a reliable, inclusive, and efficient smart home automation solution
Development of an Intelligent Multi-Campus Transportation System Using Wireless Sensor Network
Get PDFThe exponential growth in multi-campus educational institutions like Edo State University, Iyamho, ESUI has created significant transportation challenges, including traffic congestion, inefficient route planning, and inadequate real-time monitoring systems. This paper presents the development of an intelligent multi-campus transportation system leveraging wireless sensor network (WSN) technology to optimize transportation efficiency, reduce operational costs, and enhance user experiences. The proposed system integrates (Internet of Things) IoT sensors, (Global Positioning System) GPS tracking, real-time data analytics, and mobile applications to create a comprehensive transportation management solution. Through simulation and theoretical analysis, the system demonstrates potential improvements of 35% in route optimization, 28% reduction in fuel consumption, and 42% enhancement in passenger satisfaction scores. The research contributes to the emerging field of smart campus transportation by providing a scalable, cost-effective framework that can be adapted across various multi-campus environments
The Problem of Evil: Evaluating its Theological and Philosophical Implications for the Attributes of the “Good God”
Get PDFThe problem of evil remains a profound challenge in theology and philosophy, particularly concerning the coherence of the attributes of a “Good God” in a world marred by suffering, injustice and moral evil. The purpose of this study is to critically evaluate the theological and philosophical implications of evil on the traditional attributes of God: goodness, omniscience and omnipotence. Employing a multidisciplinary approach, the study engages classical theodicies such as the Augustinian and Irenaean models, alongside philosophical arguments including the free will defense and process theology. Textual analysis and comparative evaluation of historical and contemporary sources guide the methodology. The findings reveal that while atheistic perspectives often present evil as incompatible with divine goodness, many theistic responses offer reasoned frameworks that preserve belief in a benevolent God. The study also uncovers existential dilemmas faced by individuals, particularly in reconciling faith with persistent natural and moral evils. The analysis shows that evil does not conclusively negate God's goodness but rather invites deeper theological reflection and ethical responsibility. Conclusively, the research affirms that a nuanced understanding of divine attributes, in light of suffering, can sustain faith and inspire moral resilience. The contribution to knowledge lies in bridging classical theodicies with contemporary existential concerns, offering insights that support both academic discourse and lived religious experience
Prayers at Dawn, Fuji at Noon: Music, Spirituality and Everyday Wellbeing among Urban Informal Workers in Ibadan
Get PDFThis study examines how music and spirituality shape everyday wellbeing among urban informal workers in Ibadan, Nigeria. In a context where market traders and motor park drivers navigate long and unpredictable workdays, auditory practices play a crucial role in regulating mood, fostering resilience, and facilitating social interaction. Despite the centrality of music and spiritual engagement in daily life, little is known about how these practices are structured and experienced across time, creating a gap in scholarship on the intersection between musicology and African urban soundscapes. Using qualitative methods, including in-depth interviews with 20 participants and non-participant observation in selected markets and motor parks, the study traces a temporal shift in sonic environments. On one hand, mornings are dominated by gospel songs, communal prayers, and exhortations with repetitive melodic and rhythmic structures that provide moral grounding, optimism, and group cohesion. On the other hand, afternoons shift to secular genres such as fuji, highlife, and afrobeats, whose polyrhythms, call-and-response motifs, and cyclical grooves sustain energy, encourage social interaction, and support coping with the demands of urban labour. Findings reveal that workers deliberately curate sacred and secular sounds to navigate both economic and social pressures, promoting personal and collective wellbeing. By situating music at the intersection of spirituality, work, and resilience, the study highlights how auditory practices function as both social and affective resources. This research contributes to African urban ethnomusicology by demonstrating the structural and emotional dimensions of music in everyday life, and its quotidian role in shaping individual and communal resilience
Beyond Carceral Responses: Intimate Partner Violence and the Structural Realities of Rural Nigeria
Get PDFIntimate Partner Violence (IPV) remains pervasive in rural Nigeria, despite the existence of national legislation such as the Violence Against Persons Prohibition Act and Nigeria’s ratification of international treaties aimed at eliminating gender-based violence. Although research has explored the general patterns of gender-based violence, limited scholarly and policy attention has been given to the structural and spatial dynamics sustaining IPV in rural contexts. This article foregrounds critical perspectives informed by abolition feminism to advance a framework for understanding the embeddedness of IPV within Nigeria’s rural socio-political fabric. We examine how histories of patriarchal control, state neglect, and familial structures produce and sustain IPV as a normalized condition of rural life. We also explore how carceral approaches to justice often fail to account for the lived realities of rural women, reinforcing cycles of silence, impunity, and harm. We argue that abolition feminist frameworks are essential for addressing the gendered and systemic nature of IPV in rural Nigeria, and for envisioning transformative alternatives rooted in community, care, and structural change.
 
Inclusive Technology and Gender Equity: Enhancing Community Participation to Curb Youth Restiveness in Marginalised Areas
Get PDFYouth restiveness remains a persistent challenge in marginalised communities across Nigeria, often fuelled by unemployment, social exclusion, and limited avenues for civic engagement. While community participation has been widely recognised as a critical mechanism for mitigating this phenomenon, the exclusion of women from digital spaces significantly undermines the inclusiveness and effectiveness of such interventions. This study explores the intersection of gender, technology, and community participation in addressing youth restiveness, with a particular focus on the impact of the digital gender gap on collective community responses. Anchored in Participatory Communication Theory and Gender and Technology Theory, the study adopts a mixed-methods design, combining quantitative survey data (N = 300) with qualitative insights from focus group discussions (n = 24) and key informant interviews (n = 6) across selected communities in Nasarawa State and the Federal Capital Territory, Nigeria. Findings reveal a significant gender disparity in digital access and participation, with only 46% of women reporting regular use ofmobile internet compared to 78% of men. The exclusion of women from digital platforms limited their participation in community-led peace and youth engagement initiatives. The study concludes that bridging the digital gender gap enhances civic inclusion, strengthens local peacebuilding efforts, and improves the sustainability of youthfocused development strategies. It recommends the implementation of gender-sensitive digital inclusion policies, expanded digital literacy training for women, and equitable access to affordable digital tools as part of broader community development and youth engagement frameworks
Implementation of a Smart Home Intruder Detection System using a Vibrometer and ESP 32 CAM
Get PDFNigeria today is rife with occurrences of intruders breaking into homes at every slight opportunity. The topic of security is quite important; hence this paper presents the development and implementation of a Smart Intruder Detection System utilizing the ESP32-CAM board, the Vibrometer and the ATMega328P microcontroller to enhance lighting, security, and surveillance functionalities. The ESP32-CAM serves as the central control unit, leveraging its built-in Wi-Fi and camera capabilities, while communicating with the ATMega328P microcontroller responsible for managing lighting, security, and surveillance components. The Vibrometer adds a vital layer of security by detecting vibrations associated with forced entry attempts. Upon sensing significant vibrations, the Vibrometer triggers the ESP32-CAM to start an immediate recording of potential intrusions. In the realm of lighting control, the ATMega328P regulates diverse light sources such as LEDs and smart bulbs. The ESP32-CAM facilitates a user-friendly experience, enabling seamless control and automation of the lighting system through a dedicated mobile application or voice commands. For surveillance purposes, the ESP32-CAM captures real-time video, streaming it to the user's mobile device or a centralized monitoring station. The ATMega328P contributes to the system's intelligence by supporting motion detection algorithms, which, in turn, trigger automated alerts and activate lighting or alarm systems in response to detected movement. The precision performance of the components was carried out and the average precision for all the components was 95%. The synergistic integration of the ESP32-CAM board and ATMega328P microcontroller results in a cohesive and intelligent smart home automation solution
Effect of Palm Kernel Shell Ash Supplement with Egg Shell Ash on Stabilized Lateritic Soil for a Road Work
Get PDFLateritic soil serves as a fundamental material in road construction; however, its engineering properties can be significantly improved through the use of additives. In Nigeria, the abundant generation of agricultural by-products—such as palm kernel shells, eggshells, and wood residues—presents challenges related to waste disposal and management. These materials can contribute to environmental degradation, including air and water pollution, and adversely affect local ecosystems. This study explores the effects of Palm Kernel Shell Ash (PKSA) and Egg Shell Ash (ESA) on the stabilization of lateritic soil for use in road pavement applications. Comprehensive geotechnical testing was conducted on natural lateritic soil to assess various parameters: Specific Gravity (SG), percentage passing sieve No. 200 (F-200), Liquid Limit (LL), Plastic Limit (PL), Plasticity Index (PI), Maximum Dry Density (MDD), Optimum Moisture Content (OMC), and both unsoaked and soaked California Bearing Ratio (CBR). These parameters were also measured for stabilized soil samples incorporating 4% PKSA and varying percentages of ESA (0%, 2%, 4%, 6%, 8%, and 10%) by dry weight of the lateritic soil, in accordance with West African Standards (WAS). The analysis revealed that the natural lateritic soil exhibited an SG of 2.53, F-200 of 27.00%, LL of 29.00%, PL of 17.20%, PI of 11.8%, MDD of 1820 kg/m³, OMC of 11.5%, and CBR of 22%. Conversely, the stabilized samples demonstrated SG values ranging from 2.3 to 2.5, F-200 between 27% and 28%, LL from 27.0% to 30.0%, PL between 10.0% and 17.2%, PI ranging from 10.3% to 11.8%, MDD between 1860 and 2000 kg/m³, OMC values between 8% and 11%, and CBR results from 25% to 80%. Notably, the combination of 4% PKSA and 8% ESA resulted in significant improvements in the engineering properties of the soil, rendering it suitable for use as sub-base material in road construction. Therefore, this blend is recommended for effectively stabilizing lateritic soil for road infrastructure projects