Afe Babalola University Based Journals
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Niger Delta Poetry and Traumatic Inscriptions: A Reading of Sophia Obi’s Tears in a Basket
Get PDFEnvironmental degradation, beyond being a global phenomenon, is fast becoming a major cause of concern in Africa with severe impacts on humans and non-humans. This mindless exploitation of natural resources, particularly in the Niger Delta region of Nigeria, does not only adversely affect aquatic and terrestrial habitats, making them endangered species, but also leaves scathing impacts on humans, which range from physical to psychological. Previous studies have largely focused on analysing the destructive consequences of environmental degradation on non-humans and the effects on the material well-being of humans in Sophia Obi’s Tears in a Basket. However, this study argues that the destruction of the environment in the Niger Delta region directly affects the psychological and mental health of the inhabitants in the affected communities, causing trauma. Therefore, this study is a critical reading of Sophia Obi’s Tears in a Basket as a narrative of trauma. The study adopts ecocriticism (the study of nature in literature), Stef Craps’ model of trauma theory, which redefines trauma to include unending, quotidian kinds of brutality that befall persons in lower factions, and engages Rob Nixon’s concept of “slow violence”, which focuses on the accretive, cumulative impact of environmental degradation on marginalised communities. The text is subjected to literary and critical textual analysis to examine its preoccupation with the subject of trauma, through the prisms of individual and collective suffering among the Niger Delta people. The study establishes that environmental degradation possesses the potential to generate trauma
From Myth to Reality: The Transformative Power of Online Education for Nigerian Development: Lesson for Africa
Get PDFAccess to education is essential for the progress of society, fostering innovation, driving economic development, and facilitating political advancement (Hanushek, E. A, & Woessmann, L. 2015).While developed nations have successfully integrated online education into their systems, developing countries, such as Nigeria, encounter significant obstacles in transitioning to e-learning due to a limited online tutors and inadequate infrastructure. This research examines secondary data to assess the effects of online education in Nigeria and across Africa. Despite an increasing acceptance of e-learning, the findings highlight considerable challenges, including a deficiency of skilled online instructors, infrastructural shortcomings, high costs of internet access, and widespread negative attitudes among students, educators, and policymakers. Furthermore, there exists a bias from employers against graduates of online programs, a lack of sufficient investment in online educational initiatives by school administrations and the Nigerian government, and a persistent risk of misinformation and miseducation. Consequently, the study advocates for investments in digital infrastructure and teacher training initiatives, shifts in attitudes towards online education, the promotion of public-private partnerships to optimize resources, expertise, and funding for online education projects, the establishment of quality assurance measures to uphold the integrity of e-learning, and the encouragement of international collaborations to share best practices, resources, and expertise in online education. These steps are vital for transforming online education into a powerful tool for development
Effect of Lithium Mining on Quality of Water using Atomic Absorption Spectrometer (A Case Study of Toto Lithium Mine)
Get PDFThe study focused on the evaluation of effect of lithium mining in water in Toto community. Lithium has a substantial negative impact on both human and the environment particularly on the contamination of water and water depletion. Lithium processing requires hazardous chemicals. Therefore, communities, ecosystems and agricultural production may suffer as a result of the release of such chemicals through leaching, spills, or air emissions. Water samples were obtained from Lithium site and taken for Atomic Absorption Spectrometer (AAS) analysis. The possible effect of heavy metals present in the water were evaluated and analyzed to offer solutions. Random Sampling method was used to obtain five (5) water samples from the mine site. The study revealed that out of the thirteen (13) elements considered, the concentrations of four of them were varied from a very high concentration to low concentration. The elements are Li, Mg, Fe and Ca with an average of 62.4173 micrograms per litre (µg/L), 29.3130 µg/L, 2.6518 µg/L and 0.9773 µg/L respectively. That of lithium which is 62.4173 µg/L is far above the allowable and acceptable standard limit given by the World Health Organization (WHO) and is therefore considered inimical for human consumption
Derivation of Glaze from Cathode Ray Tubes (CRTs) for Ceramic Wares
Get PDFIntroduction of digital display makes cathode ray tube to be largely obsolete. The tube with its screen becomes waste at the end of the products lifecycle. This study, which combined laboratory experimentation and studio practices, aimed at production of glass glaze with cathode ray tube screen. Cathode ray tubes of four different colours were used for the study. The tubes were washed, pulverized and sieved according to their colour, elementally analysed using Particle Induce X-ray Emission, and milled into two batches per colour with first batch mixed with ball clay and second batch mixed with ball clay and additive chemical material of borax. The glaze batches were applied on eight bisque-fired tiles and fired at 1100 0C. The glazes yielded greenish grey, greyish purple, transparent grey and dark grey. This is significance towards the diversification of Nigeria’s economy for solving solid waste disposal challenges for a better and safe environment. The study has proven that cathode ray tubes with addition of borax and ball clay are suitable for glaze production and provided elemental information to guide the glaze formulation
Upgrading and Optimization of Pyrolysis Oil from Corncob (Euphorbia mammillaris) and Peanut (Arachis hypogaea) Shells by Liquid-Liquid Extraction Process
Get PDFThe bio-oils from peanut shells and corncobs have limited applications due to high oxygen content, viscosity, acidity, and organic compounds, necessitating upgrading. This study employed liquid-liquid extraction to improve oil quality due to its affordability. Bio-oils were produced via intermediate pyrolysis in a fixed-bed reactor at 450 °C, followed by physicochemical and GC-MS analysis. The need for further treatment led to the use of a low-cost, simple liquid-liquid extraction method. A Box-Behnken experimental design was applied, considering temperature, time, and solvent as parameters. Extraction temperatures of 25 °C, 40 °C, and 55 °C were tested alongside extraction times of 30, 60, and 90 minutes using n-hexane and ethanol as solvents in a 1:2 ratio with bio-oil. N-hexane achieved higher phenolic compound extraction efficiency, yielding 68.21% for corncob bio-oil and 66.94% for peanut shell bio-oil, compared to 60.95% and 58.87% using ethanol at 55 °C. The process also improved pH values from 4.7 to 5.7 for peanut oil and from 4.5 to 5.8 for corncob oil, reducing acidity and operational costs. It was concluded that higher extraction temperatures increased bio-oil yield up to a critical limit, while n-hexane proved more effective than ethanol in enhancing oil quality and reducing acidity, thereby solving transportation and storage challenges
Network Congestion Tracking and Detection in Banking Industry Using Machine Learning Models
No full textThe escalating threat of congestion in wireless networks on a global scale prompts the need for effective detection and management techniques. This study investigates the tracking and detection of congestion in wireless networks, particularly within the banking industry, where digital transactions are rapidly increasing. It addresses the challenge of congestion management through machine learning (ML) models, aiming to enhance network performance and service quality. This research evaluates various ML algorithms, including Support Vector Machines, Decision Trees, and Random Forests, to identify the most effective approach for congestion detection. This research utilizes a dataset sourced from MainOne Limited, which covered August 18th, 20th, 22nd, 23rd, and 24th, 2023, and included banking operation hours from 7 AM to 4 PM each day. Preprocessing of data is conducted to optimize model training. Following training, various performance metrics including accuracy, precision, recall, F1 score, response time, and confusion matrix are assessed. Results demonstrate that Random Forest outperforms other models in accuracy, precision, recall, F1 score, and response time, with an accuracy of 98.90%. This research discusses the importance of continuous innovation in banking network analytics to tackle evolving congestion challenges. Future recommendations include leveraging advanced ML techniques like deep learning and reinforcement learning and exploring ensemble learning methods to enhance congestion detection models further
Models Development for Prediction of Blast Efficiency and Total Charge in a Typical Quarry
Get PDFThe prediction of blast efficiency is usually achieved by using models; this in turn, gives better and more efficient rock fragmentation. However, the accuracy of the prediction often times relies on the model development validation. In this study, models were developed and compared upon validation for predicting the blast efficiency and total charge required for efficient fragmentation using artificial neural network (ANN). Rock samples were gathered from the study are, and the uniaxial compressive strength (UCS) test was carried out on all the samples based on international standard. The average UCS obtained from the rock samples at the Eminent quarry (EQ) is 153.61 MPa. The dimension of in-situ rock mass considered in the study area is 60 m x 40 m, and the in-situ block sizes obtained vary from 2.02 m2 to 3.20 m2. The average percentage value of F50 obtained from the Split-Desktop image analyses is approximately 72.44 cm. The various results obtained from the UCS, in-situ block size distribution, image analysis of the blasted rocks and the total charge were used to develop the models for the prediction of blast efficiency. The key issue of concern about these models is that they are mostly site specific and the fact that if they perform well in a location does not guarantee the other. Hence, the validation and suitability of these models on the mine site. The blast efficiency prediction using ANN is compared with measured efficiency and the value of coefficient of determination, R2 obtained is 0.9733. The value of the coefficient of determination, R2 obtained from ANN by comparing the prediction of the total charge and the measured total charge is 0.9773. The findings showed that, the proposed ANN based mathematical models are suitable and thus, give better prediction to blasting efficiency and the possible total charge
Modelling of Cyber Attack Detection and Response System for 5G Network Using Machine Learning Technique
Get PDFThe rapid increase in the adoption of 5G networks has revolutionized communication technologies, enabling high-speed data transmission and connectivity across various domains. However, the advent of 5G technology comes with an increased risk of cyber-attacks and security breaches, necessitating the development of robust defence mechanisms to safeguard network infrastructure and mitigate potential threats. The work presents a novel approach for modelling a cyber-attack response system tailored specifically for 5G networks, leveraging machine learning techniques to enhance threat detection and response capabilities. The study introduced innovative methodologies, including the integration of standard backpropagation and dropout regularization technique. Furthermore, an intelligent cyber threat classification model that proactively detects and mitigates malware threats in 5G networks was developed. Additionally, a comprehensive cyber-attack response model designed to isolate threats from the network infrastructure and mitigate potential security risks was formulated. The result of testing the response algorithm with simulation, and considering quality of service such as throughput, latency and packet loss, showed 80.05%, 24.9ms and 4.09% respectively. During system integration of the model on 5G network with stimulated malware, the throughput reported 71.81%. Also, packet loss reported loss rate of 23.18%, while latency reported 178.98ms. Our findings contribute to the advancement of cybersecurity in 5G environments and lay the foundation for the development of robust cyber defence systems to safeguard critical network infrastructure against emerging threats
Green Hydrogen Synthesis from Human Urine as Sustainable Bioenergy Resources
No full textWith the earths cry for help as pollution rate increases, researchers are faced with a common task of tackling pollution resulting from dependence on fossil fuel as well as delivering sustainable energy. Renewable energy resources such as solar, wind, hydro to mention a few are currently finding applications within the world energy mix but some limitations which range from meteorology of locations to expected maximum energy output attainable. Hydrogen, the most abundant element in the world stand chance of abating this problem. However conventional method of its producing, poses severe treat to the atmospheric environment with the release of oxides of carbon hence, referred as blue hydrogen. Contrarily, green hydrogen from human urine stands a more sustainable and environmentally friendly energy resource. This study was aimed to empirically model the synthesis of green hydrogen from urea in human urine by an electrolytic process. The synthesized hydrogen was characterized on physiochemical properties of conductivity, turbidity, pH, specific gravity and colour, while the precursor urine characterized on gender, exposure duration and storage temperature. The synthesis process was modelled using Microsoft excel solver for the overall cell energy or polarization curve model, the Faraday’s efficiency model and gas purity model at electrolyte concentrations of 25 wt./wt., 30 wt./wt. and 35 wt./wt. of potassium oxide (buffer} to urea over a five-temperature interval range of 45 to 85 oC. Findings revealed that the gas produced was 99.88% hydrogen at the cathode. Also, hydrogen produced increased with increase in electrolyte concentration and moderate temperature with optimal conditions at 35 w/w electrolyte concentration and 65 oC. However, the minimum cell voltage was 2.06 V at 85 oC and 35 w/w electrolyte concentration. With an exception of the Faraday’s efficiency model at 30 wt./wt. electrolyte concentration across the system’s operating temperature range yielding an R2 value of 0.711, all the models yielded coefficient of determination values in the range of 0.96 and 0.99, indicating good fit for the alkaline urine electrolysis for green hydrogen synthesis from human urine
A Semantic Analysis of Selected Nigerian Newspaper Reports on the Effect of the 2023 Naira Redesign
Get PDFThis study is a semantic analysis of news reports on the effect of the 2023 Nigerian Naira redesign from selected Nigerian newspapers. A total of 40 news reports were purposively sampled from four Nigerian newspapers (The Sun, Vanguard, The Guardian and Premium Times). Fillmore’s (1982) Frame Semantic Theory, which proposed that language is composed of semantic frames, which are mental representations of situations or scenarios, was adopted for this study. A qualitative research design was employed in the data analysis to examine the elements of Frame Semantic Theory evident in the extracted data. The findings revealed that all the four newspapers consistently framed the effects of the Naira redesign within the context of economic hardship. It also revealed that the newspapers predominantly conveyed negative perspectives regarding the Naira redesign. The cross-newspaper comparative analysis also highlighted the widespread and varied effects of the Naira redesign