NIL

This study examines the Asaba Massacre as one of the most tragic and controversial events of the Nigerian Civil War, exploring its historical significance, collective memory, and enduring impact on Nigerian society between 1970 and 2020. The massacre occurred in October 1967 when federal troops entered Asaba, a predominantly Igbo community in present-day Delta State, during the Nigeria–Biafra conflict. Hundreds of unarmed civilians, particularly men and boys, were reportedly killed after being accused of supporting the secessionist Biafran cause. Despite its magnitude, the event remained inadequately documented in official national narratives for decades, surviving largely through oral testimonies, community commemorations, and personal memoirs. Using historical and qualitative approaches, this study draws upon archival materials, eyewitness accounts, memoirs, scholarly publications, media reports, and commemorative records to reconstruct the events surrounding the massacre and analyze how memories of the tragedy have been preserved and transmitted across generations. The study investigates the socio-political circumstances that led to the massacre, the experiences of survivors, and the ways in which remembrance practices have shaped identity, reconciliation efforts, and historical consciousness among the people of Asaba and Nigeria at large. The findings reveal that the Asaba Massacre remains a significant symbol of wartime suffering, ethnic tensions, and the challenges of post-war reconciliation in Nigeria. The persistence of survivor narratives and memorialization efforts demonstrates the importance of collective memory in preserving historical truth and seeking justice for victims. The study further argues that acknowledging and documenting such traumatic historical events is essential for national healing, conflict prevention, and the promotion of historical accountability. The research concludes that the memoirs and memories associated with the Asaba Massacre constitute an important aspect of Nigeria’s civil war historiography and provide valuable insights into the broader consequences of armed conflict, state violence, and the struggle for reconciliation in post-war societies

This study explores the semiotic significance of Yoruba dressing styles, examining how traditional attire functions as a cultural symbol, a means of communication, and an expression of identity, spirituality, and social hierarchy. Using Ferdinand de Saussure’s theory of signs and Roland Barthes’ concepts of denotation and connotation, the research analyzes the deeper meanings embedded in Yoruba clothing, colors, fabrics, and accessories. The study reveals that Yoruba dressing styles are more than just fashion; they convey social status, religious beliefs, and ancestral connections. Key attires such as agbádá, aṣọ-òkè, gèlè, bùbá, and adìrẹ serve specific purposes in ceremonial, religious, and daily life contexts. The research also highlights the symbolism of colors—for example, white (funfun) signifies purity and spirituality, red (pupa) represents power and aggression, while gold (òwú) is associated with wealth and royalty. Additionally, Yoruba festivals such as Ojúde Ọba, Ẹyọ, Egúngún, and the Sàngó festival provide a platform for cultural preservation through dressings. Furthermore, the study examines the impact of modernization and globalization on Yoruba dressing, noting a shift towards hybrid fashion that blends traditional elements with contemporary styles. The method of data collections employs structure interview, photography and the analysis of the Yoruba fashion materia

Phishing attacks, which use phoney emails and misleading websites to target people and organisations, have emerged as one of the most common cybersecurity threats. These attacks cause serious security breaches by tricking users into divulging private information, including login credentials and financial information. This project offers a machine learning-based phishing detection tool for emails and web browsers that uses logistic regression to efficiently detect and stop phishing threats. To improve the accuracy of phishing detection, the study investigates different feature extraction methods, dataset preprocessing, and model training approaches. Python was used to develop the system, and the Scikit-learn library was used to implement the model. Both authentic and phishing URLs and emails made up the dataset, which was preprocessed using techniques like feature scaling and outlier removal. Key performance metrics, such as accuracy, precision, recall, F1-score, and a confusion matrix, were used to train and assess the model. The outcomes showed that the suggested model was successful in differentiating between phishing and authentic entities, as evidenced by its high classification accuracy. Notwithstanding its encouraging results, the system has certain drawbacks, including the difficulty of balancing false positives and false negatives and vulnerability to new phishing tactics. To further enhance detection capabilities, future studies could use ensemble approaches or sophisticated deep learning models. By offering users and organisations a reliable and effective detection mechanism, this project supports the continuous efforts to strengthen cybersecurity defences against phishing attacks.

This project examined the role of Artificial Intelligence (AI) in shaping religious programmes in Living Faith Church Worldwide and the ethical concerns connected with its use in church activities. The study aimed to examine how AI is being used in religious programs in Winners’ Chapel, its effects on church activities, and the ethical issues associated with its application. The thesis adopted a qualitative research method. Data were collected through document analysis, observation of modern technological practices, and the use of published interviews and academic materials related to AI in religion. Relevant books, journal articles, church publications, online materials, and previous studies were also reviewed to provide a broad understanding of the subject. Thematic analysis was used to examine the information collected and to identify important patterns and themes related to AI in church programs. Findings from the research revealed that AI is gradually becoming part of modern religious practice in Winners’ Chapel through television evangelism, radio broadcasting, online streaming, mobile applications, social media communication, and administrative management. The researcher found that AI improves communication, sermon preparation, translation, media production, teaching, and church administration. It also showed that AI can support children’s ministry, adult Bible studies, and global outreach programs such as Shiloh. However, the thesis further revealed major ethical concerns, including privacy and data protection, algorithmic bias, overdependence on technology, reduction of human interaction, questions about spiritual authenticity, and the possibility of replacing important human roles in ministry.

This study focused on the optimization of organic fertilizer production from Chromolaena odorata (Siam weed) with the aim of determining the most suitable drying conditions for nutrient preservation and evaluating its effects on soil fertility and maize (Zea mays) growth performance. Fresh C. odorata leaves were collected, air-dried, and oven-dried under varying temperature (30–85 °C) and time (30–120 min) conditions. The effects of these parameters on nutrient composition (particularly nitrogen (N), phosphorus (P), and potassium (K)) were analyzed using Response Surface Methodology (RSM) based on a Central Composite Design (CCD). The optimized fertilizer product was applied to soil samples to assess changes in nutrient levels before and after maize cultivation. Results revealed that both drying temperature and time significantly influenced the nutrient composition of C. odorata. Nitrogen and phosphorus contents decreased with increasing temperature, whereas potassium concentration increased due to moisture reduction and mineral concentration effects. The optimal drying condition was found to be approximately 55 °C for 90 minutes, which preserved the highest levels of essential nutrients. Post-sowing soil analysis indicated improved macronutrient and micronutrient concentrations following the application of the optimized organic fertilizer. Maize plants grown in treated soil exhibited superior vegetative growth compared to the control, with notable increases in plant height, stem diameter, and dry biomass yield. The findings demonstrate that Chromolaena odorata can serve as an effective and sustainable source of organic fertilizer. Its utilization not only enhances soil fertility and crop productivity but also provides an environmentally friendly means of managing this invasive weed species.

Lithium-ion batteries have completely changed our world, powering everything from the smartphones in our pockets to electric cars and solar power grids. However, these batteries have a major flaw: they are highly sensitive and can easily get damaged, fail early, or even catch fire if they get too hot, overcharge, or drain too deeply. Traditional battery systems usually react only after a problem has already happened, which is not safe enough for modern technology. The main goal of this project was to design and test a Smart Management System (SMS) that acts as an intelligent brain for lithium-ion battery packs, actively keeping them safe, helping them last longer, and making them work more efficiently. To achieve this, the project used MATLAB and Simulink software to build a detailed, realistic model of a lithium-ion battery pack. Inside this virtual setup, special control logic was built to constantly track individual battery cell voltages, current, and the overall State of Charge (how much energy is left) in real time. Safety boundaries were explicitly programmed into the system to flag an error the moment voltage crossed unsafe limits—specifically setting an upper overvoltage limit of 16.6 V and a lower under-voltage limit of 11.2 V. The simulation was run under different lifelike work situations and heavy loads to see how well the smart system would respond to sudden changes. The results clearly showed that the system works exactly as planned. The moment an unsafe voltage limit was crossed, the smart system reacted immediately, flagging the error and stabilizing the voltage safely within its target boundaries to prevent any damage to the battery cells. The system also smoothly tracked the steady drop in the battery's energy capacity as it discharged over time. Ultimately, this project proves that using an intelligent, software-based management system is a highly reliable and affordable way to protect modern energy systems before moving on to building expensive physical hardware.

This research provides an in-depth analysis of workplace discrimination against persons with disabilities (PWDs) in Nigeria, assessing the adequacy of the legal, institutional, and policy measures designed to protect their rights and foster inclusion. The study evaluates the extent to which Nigeria fulfils its obligations under the UN Convention on the Rights of Persons with Disabilities (CRPD) and the International Labour Organization (ILO) Convention No. 159. Using a doctrinal and comparative legal approach, it examines statutory provisions, case law, and the functions of enforcement institutions, notably the National Commission for Persons with Disabilities (NCPWD), the National Human Rights Commission (NHRC), Nigeria Social Insurance Trust Fund and the National Industrial Court of Nigeria (NICN). The findings indicate that although Nigeria’s legislative framework is progressive, implementation is undermined by weak institutional capacity, inadequate funding, low awareness, and enduring societal prejudice. Judicial responses, while occasionally advancing disability rights, face obstacles such as prolonged litigation, high legal costs, and limited judicial expertise. Persistent issues include discriminatory hiring, inadequate infrastructure accessibility, non-compliance with the statutory 5% public sector employment quota, and unclear reasonable accommodation guidelines. The study identifies legal ambiguities, enforcement weaknesses, and policy gaps, recommending reforms such as strengthening institutional mandates, creating sector-specific compliance frameworks, expanding public education on disability rights, and improving access to affordable legal remedies. The research concludes that realising workplace equality for PWDs in Nigeria requires more than legal provisions, it demands effective enforcement, structural reforms, and a cultural shift towards genuine inclusion, recognising disability rights as both a human rights priority and a driver of national development.

This study investigates the simulation of the actual maximum stress in Tungsten Inert Gas (TIG) weldment using SIMUFACT Welding software. The research aimed to compare the simulated stress values with experimental results obtained in a controlled environment under varying process parameters such as current, voltage, and gas flow rate. During the design of experiment, twenty experimental runs was generated by the Central composite design and it was used to carry out TIG welding on mild steel plates. A universal testing machine was used to record the actual maximum stress on the welded joint and recorded as experimental values. The data generated from the CCD matrix was then feed into an expert system (SIMUFACT 2024) which was used to carry out TIG welding simulations with its corresponding actual maximum stress recorded alongside as the SIMUFACT result. Results from this study revealed that that increasing welding current reduces the maximum stress due to higher heat input and lower cooling rate, while voltage variation influences arc width and stress distribution. The actual maximum stress values from both datasets were analyzed and compared. The results revealed close agreement between experimental and simulated values, a fitted line plot was used to ascertain the degree of correlation between both results and a correlation coefficient of 0.98 was observed, indicating a very strong positive correlation degree between the experimental result and the SIMUFACT result. A time series plot was then used to compare if both data sets assumed the same trend. The SIMUFACT welding simulation analysis proved to be a reliable tool for simulating and predicting the actual maximum stress in TIG-welded joints thereby aiding in the optimization of welding parameters for an improved structural integrity

This project report presents the findings of a route survey conducted for the Evbhuku community road in Oredo Local Government Area, Edo State, Nigeria. The survey employed Differential Global Positioning System (DGPS) technology. The primary goal was to collect accurate topographic and cadastral data required for designing a new road and determining the necessary Right-of-Way. Fieldwork was carried out using two Hi-Target V300 GNSS receivers operating in Real-Time Kinematic (RTK) mode. This setup was used to map a 2-kilometer proposed corridor connecting Obe, Evbhuku, and Amagba communities. Data collected included the road's centerline, ground elevations at 25-meter intervals, and the locations of all existing features and property encroachments. The collected data was processed using Autodesk Civil 3D software. This involved converting coordinates to the local map grid and creating a detailed digital model of the terrain. From this model, engineering drawings were produced, including road plans, elevation profiles, and cross-sections. The survey also calculated earthwork volumes, identifying a net requirement to excavate approximately 13,115 cubic meters of material. The results confirm the survey achieved the necessary accuracy for road design. A major finding was the identification of significant land encroachment by buildings and a market along the first 350 meters of the route, which must be resolved before construction can begin. This project provides the essential mapped foundation for the subsequent stages of the road's development.

The rapid growth of online food delivery platforms has introduced challenges in supporting multiple restaurants on a single system. This research proposes a multi-tenant backend system for food delivery platforms, enabling each restaurant to operate independently while sharing the same backend infrastructure. The system ensures that tenants maintain full control over orders, menus, and operational data, eliminating the risk of conflicts or data overlap. Unlike traditional single-tenant or loosely structured multi-vendor systems, this implementation ensures strong tenant isolation by design which means each restaurant experiences the system as if it were built specifically for them. All operations including order processing, background jobs, inventory updates, and notifications are executed in a tenant-aware context. This work contributes a practical approach for anyone building a multi-vendor platform and not just in food delivery but also in areas where clean isolation, predictable behavior, and efficient resource sharing are required.