Afe Babalola University Based Journals
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Digital Twin Model of a Solar Panel for Intelligent Monitoring Using Artificial Neural Network
No full textThe growing demand for renewable energy has sparked interest in optimizing the performance and reliability of solar panels and solar-powered installations. Reliability, a key quality of any power system, can be improved through early fault detection and predictive maintenance in solar power plants. Detecting faults early in solar panels significantly reduces maintenance costs and minimizes downtime, making efficient and cost-effective monitoring methods essential for enhancing the reliability of solar power systems. In this paper, a digital twin prototype of a 30W solar panel was developed for intelligent monitoring, fault detection, and fault classification using MATLAB/Simulink and Bayesian regularization Artificial Neural Networks. The digital twin consists of several layers: a hardware layer consisting of voltage, current, temperature, humidity, and light sensors interfaced with an Arduino microcontroller; a data synchronization layer that transfers data from the microcontroller to Google Cloud Logging using serial communication, a GET request in a Python script, and a corresponding JavaScript code on Google Cloud Platform to capture and store the data; an analytics layer implemented in the MATLAB Machine Learning Toolbox; and a virtual representation layer in Simulink for real-time visualization and monitoring. This real-world data was collected and pre-processed before training nineteen artificial intelligence models. The dataset was split into 80 % for training and 20 % for the testing sets. The models’ performance was measured using metrics such as Root Mean Square Error, Mean Square Error, and coefficient of determination. The Bayesian regularization model achieved the lowest root mean square error and an overall prediction accuracy of 81 %, outperforming linear regression, support vector machines, and other gaussian process regression models. After the fault detection by the chosen algorithm, these faults were categorized into three based on the deviations between predicted and measured voltage and current profiles. The digital twin demonstrated how Bayesian regularization improves generalization performance on limited PV datasets, while providing a virtual replica capable of real-time monitoring. This research provides a scalable low-cost solution for intelligent monitoring in solar installations, particularly in large-scale solar PV solutions
EMD-Based Amplify Quantized and Forward Cooperative Relaying Technique for Wireless Communication System
Full text linkWireless communication system is crucial to telecommunications infrastructure and has played an essential role in national growth. However, the system's performance is hindered by multipath propagation, which has negatively impact in its performance. Amplify Quantized and Forward (AQF) cooperative relaying technique is ineffective because signal quality is degraded by amplification and blockages during transmission from the relay to the destination. Hence, an EMD-based AQF cooperative relaying for wireless communication system is proposed to enhance the existing AQF. The relays responsible for sending data to the second hub were determined by the multiple relay selection process. The selected relays processed the signal by passing it through EMD and amplifying it with the relay gain. Subsequently, the boosted signal was uniformly quantized at the relay nodes before its final send-off to the destination in the second transmission phase. The results showed that the proposed EMD-AQF technique outperformed the existing AQF, achieving a 74.5% reduction in bit error rate and a 65.8% increase in throughput
BRICS and the Politics of Multi-Polarity: Rethinking Global Governance
Full text linkThe BRICS countries (Brazil, Russia, India, China, and South Africa), and its recent expansion, has evolved beyond its economic foundations to emerge as a formidable actor influencing global governance. This article critiqued portrayals of BRICS as a merely symbolic or disjointed alliance, arguing that it offers a viable alternative to the Western-dominated global order. It challenges the representativeness of traditional institutions like the UN, IMF, and World Bank, while examining BRICS' initiatives such as the New Development Bank and de-dollarisation efforts. Being a qualitative research, secondary data was utilized to analyze BRICS' institutional strategies, ideological narratives, and policy tools that seek to reshape global power configurations. The study is anchored on two theories, the Neo-Gramscian and Structural Realism. The study argued that BRICS functions both as a symbol and agent of multi-polarity and examines whether the coalition can consolidate a coherent global vision beyond being a protest bloc. The study established in its findings that, BRICS is the alternative to Western dominated global institutions, thus, providing a change in the unipolar grips on global politics. One of the recommendations given is that as an alternative to unipolarity, BRICS should promote South-South alliances so as to strengthen its New Development Bank that will measure up with the global institutions such as the World Bank and IMF. Its evolving role may be pivotal to the future of global governance
Hybridization of Polyester- Fiberglass Woven Mat and Banana Pseudo-Stem Fiber Reinforced Composite for the Production of a Light Weight Car Bumper
No full textIn order to improve mechanical properties of reinforced composite materials, one method of yielding mechanical improvement is hybridization. The purpose of this study was to research the structure and materials employed for a light weight car bumper. This paper has an already existing car bumper acting as a master model, which was used to create scale and full size molds for production of hybrid reinforced composite. Hand layup process was employed for production with varying weight percentages of fiberglass/banana pseudo-stem fiber as reinforcement and polyester resin as the matrix. Eighteen (18) scale specimens were produced, and the best results obtained from them were applied to the production of the full-size car bumper. The best results obtained were tensile strength of 34.76 N/mm2, compression strength of 131.37 N/mm2, flexural strength of 86.5 N/mm2, and impact strength of 17.95 KJ/m2 respectively. The same mechanical tests were carried out on the existing car bumper (made of ABS plastic) with the result obtained being tensile strength of 20.71 N/mm2, compression strength of 4.85 N/mm2, flexural strength of 17.73 N/mm2, and impact strength of 31.96 KJ/m2 respectively. The mechanical properties tests were also supplemented with other characterizations: XRF, XRD, TGA, FTIR, SEM, water absorption, and slake durability index to gather information regarding crystal structure, chemical composition, and functional groups present in the hybrid fiber reinforced polymer composite manufactured. Comparing the results, one can observe remarkable enhancement in the mechanical properties of the fabricated car bumper as compared to the existing one. On the strength of the optimization results, 25% synthetic and 5% natural fiber in weight percentage were selected to produce the full-size car bumper. Weight comparison of similar car bumper shows alloy steel weighs 12.2 kg, alloy aluminum weighs 9.57 kg, ABS plastic weighs 6.04 kg, and hybrid weighs 4.09 kg, respectively
Recent advancement in Photo-Fenton like processes for decontamination of wastewater: A short review
No full textThe Photo-Fenton-like (PFL) process has emerged as a highly effective advanced oxidation technology for wastewater decontamination due to its ability to generate hydroxyl radicals for degrading persistent organic pollutants. Recent advancements have focused on overcoming the limitations of conventional homogeneous Photo-Fenton processes, particularly their dependence on acidic conditions, narrow light response, and challenges in catalyst recovery. Novel heterogeneous catalysts, including iron-based nanocomposites, doped metal oxides, carbon-supported materials, and metal-organic frameworks (MOFs), have demonstrated enhanced stability, reusability, and efficiency under visible and even solar light irradiation. Furthermore, strategies such as coupling PFL with adsorption, membrane separation, ozonation, and electrochemical systems have improved degradation kinetics and broadened the scope of treatable contaminants. Despite these promising developments, issues such as catalyst leaching, radical scavenging in complex wastewater matrices, and long-term performance remain critical barriers to industrial application. This review highlights recent progress in catalyst design, process integration, while identifying future research needs aimed at enhancing sustainability, cost-effectiveness, and large-scale implementation in real wastewater treatment
Commodity Dependence, Product Diversification, and the Implementation of the Biat Action Plan in West Africa, 2012–2022
Full text linkWest African economies exhibit a pronounced reliance on primary commodities, a structural characteristic that has historically impeded industrialization, trade competitiveness, and regional integration. This study critically examines the relationship between commodity dependence, product diversification, and the implementation of the Boosting Intra-African Trade (BIAT) Action Plan in West Africa over the period from 2012 to 2022. Drawing upon structural transformation theory and trade complementarity theory, the research investigates how limited diversification constrains the capacity of West African nations to fully capitalize on BIAT, while also exploring the potential of diversification as a catalyst for enhanced intra-regional trade. Employing a mixed-methods approach, the study integrates quantitative indicators—including export diversification indices, trade concentration ratios, and intra-regional trade shares—sourced from the UNCTAD and ECOWAS databases. This quantitative analysis is complemented by qualitative examinations of policy documents and expert insights. The findings suggest that persistent commodity dependence has significantly restricted the outcomes of BIAT. Conversely, while diversification efforts have been uneven across member states, they have positively contributed to trade complementarity and regional integration. This study highlights the dual challenge of reducing commodity dependence and fostering diversification as essential preconditions for the successful implementation of BIAT in West Africa. Furthermore, the paper contributes to the existing literature on African trade policy by linking structural economic transformation with the execution of continental integration frameworks, offering policy recommendations aimed at advancing sustainable regional trade
Leveraging Parliamentary Friendship Groups to Strengthen Nigeria’s Strategic Alliances: A Foreign Policy Perspective
Full text linkThis paper interrogates the underutilisation of Parliamentary Friendship Groups (PFGs) in advancing Nigeria’s strategic alliances in pursuit of its foreign policy objectives. Despite their growing global relevance as informal diplomatic channels, PFGs have had limited impact in the foreign policy space of African countries. In Nigeria, the full potential of PFGs for strategic partnerships is not being maximised. Extant literature identifies challenges limiting the impact of PFGs to include; underfunding, overlapping mandates, lack of continuity and insufficient integration of PFGs into the broader foreign policy framework. Beyond these, there are other challenges which have not received adequate scholarly attention. Amid the growing proliferation of PFGs, there is a dearth of national interest-driven PFGs and absence of tact in their inter-parliamentary engagements. The objective of this paper is to explore how these challenges are undermining the potential of Nigeria’s PFGs for strategic alliances. The study employed qualitative-descriptive method, relying on secondary data sources, including policy documents and scholarly literature. It adopted the soft power theory, which emphasises attraction, persuasion and informal influence over hard power in inter-state relations. It argues that PFGs, as a soft power instrument, could offer Nigeria a flexible and relational approach to international diplomacy, complementing formal channels and fostering mutual understanding in inter-state engagements. It recommends leveraging Nigeria’s PFGs as a deliberate tool of soft power diplomacy – aligned with national interest and embedded within foreign policy strategy. Additionally, there is a need for tact in the operations of Nigeria’s PFGs and capacity-building for legislators in inter-parliamentary diplomacy
Polycyclic Aromatic Hydrocarbons, Thermal, Textural and Quality Properties of Grilled African Snail (Acharchatina Marginata)
No full textGrilling is one of the processing methods of raw meat into edible meat product. These have tendencies to impact quality of the meat product. This study evaluated the impact of grilling on polycyclic aromatic hydrocarbons, thermal, textural, proximate, mineral and colour properties of African giant snails. The grilling of fasted and processed snail meat was carried out using electrical grilling machine (MODEL KWS-170) at different time interval of 0 min (BF6), 14 min (FHA), 28 min (LTB), 42 min (ZAK) and 56 min (YAB), respectively. This study revealed that the textural characteristics of the grilled snail meat with increase in grilling time. The mineral composition (calcium, iron, potassium, sodium, zinc and magnesium) of the grilled snails fell within the range of 182.50 - 242.50 mg/100g, 6.90 - 8.40 mg/100g, 22.50 - 32.50 mg/100g, 205.00 – 292.00 mg/100g, 0.13 - 0.32 mg/100g and 62.50, respectively. The grilled African snail at varying grilling time indicated that identified Polycyclic aromatic hydrocarbon (PAH) : Fluoranthene, Anthracene, Acenaphthene, pyrene Naphthalene, Acenaphthylene, , Fluorene, Phelanthrene, Benzo (a) anthracene, chrysene, Benzo (b) fluoranthene, the Benzo (k) fluoranthene and the Benzo (a) were below the recommended critical limits
The Dark Web of Cryptocurrency: Unpacking the Nexus between Digital Currencies, Cybercrime, and Global Governance
Full text linkThis study explores the intersection of cryptocurrency, cybercrime, and global governance. It focuses on identifying criminal techniques, analyzing forensic and regulatory countermeasures, and evaluating the broader governance dilemmas that arise. A qualitative desk-based approach was employed, synthesizing secondary data from peer-reviewed studies, institutional policy papers (FATF, IMF, Europol), and industry reports (Chainalysis, Elliptic, TRM Labs). Thematic content analysis was used to trace patterns in illicit cryptocurrency use, law enforcement responses, and regulatory innovations. The findings indicate that while advances in blockchain forensics and policy coordination have strengthened oversight, criminals increasingly exploit decentralized finance platforms, cross-chain laundering, privacy coins, and mixers to evade detection. Enforcement remains uneven, hindered by fragmented regulations and gaps in cross-border cooperation. Overall, the study concludes that cryptocurrency-enabled cybercrime remains a resilient and evolving threat that challenges the stability of the global financial system and exposes weaknesses in governance frameworks. Without stronger coordination, adaptive regulation, and robust technological capabilities, the risks of illicit finance will continue to outpace control efforts. To mitigate these risks, the study recommends enhancing cross-border collaboration, investing in advanced blockchain forensic tools, and adopting flexible, multi-stakeholder governance models that balance innovation with accountability
Text Mining and Machine Learning Framework for Predicting Sickle Cell Disease Research Findings in Nigeria
No full textSickle cell disease (SCD) is a prevalent and complex genetic disorder with a significant impact on public health in Nigeria. The extensive volume of research conducted on SCD underscores the urgent need for effective strategies to analyse and predict research findings to enhance patient care and inform future interventions. This paper reviews an ongoing research seeking to develop a text mining system that leverages advanced computational techniques to predict research outcomes related to SCD in Nigeria. Existing research on SCD in Nigeria has provided valuable insights into various aspects of the disease. However, the sheer magnitude of published research papers, coupled with the unstructured nature of textual data, presents challenges for researchers and healthcare practitioners seeking to gain actionable knowledge from this vast corpus. By harnessing the power of text mining, this research proposes a novel solution to automatically categorise and analyse SCD research findings, enabling efficient retrieval of pertinent information and accelerating the translation of research into practice. The text mining system will employ state-of-the-art natural language processing and machine learning algorithms to extract meaningful information from diverse sources such as biomedical databases and online journals. Through the systematic analysis of these textual data, the system will categorise and predict key findings, including interventions, outcomes, and their relevance to the Nigerian context. Additionally, it will explore patterns, trends, and gaps in the existing research landscape, providing valuable insights for researchers, healthcare practitioners, and policymakers