Caritas University Journals
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Leveraging Social Media for Youth Employment and Entrepreneurship in Enugu State, Nigeria
Full text linkThis study explores the role of social media in job creation among youths in Enugu State, Nigeria. The objectives include identifying the types of jobs created through social media, assessing its economic impact on youth employment, examining challenges faced by young entrepreneurs leveraging social media, and providing recommendations for optimizing social media use for job creation. The study adopts a descriptive survey research design, sampling 400 respondents aged 18-35. The research is anchored on the Diffusion of Innovations Theory and the Uses and Gratifications Theory. Statistical analysis was conducted to test hypotheses and draw conclusions. The findings reveal that social media serves as a vital tool for employment generation, providing opportunities for networking, job-seeking, skill acquisition, and business promotion. Platforms such as Facebook, LinkedIn, and Instagram facilitate job searches and networking, while YouTube and WhatsApp support digital learning and entrepreneurship. However, significant barriers—such as digital illiteracy, unstable internet connectivity, and limited financial resources—hinder the full realization of social media’s potential in job creation. The study underscores the need for strategic interventions, including digital literacy programs, improved internet infrastructure, and access to financial support, to enhance youth employment prospects through social media. The findings provide practical insights for policymakers, educators, and digital platform developers in fostering sustainable employment solutions through digital innovation
Rehabilitation And Upgrade For The Configuration Techniques Of a Spark Ignition Engine Test Bed. a Case Study Of Caritas University Amorji Nike Emene Enugu
Full text linkThis paper presents the configuration of a spark ignition engine test bed, a device which allow measurement on engines by making them run in a static way, where there is no need to use the vehicle to which the motor was made, used specifically for research and development department of motor manufacture, in order to ensure the design and the operation of prototypes, and to evaluate the performance of spark ignition engines. The testing bed incorporates a dynamometer, fuel measurement system, emissions measurement system, and data acquisition system to measure engine performance parameters, including power output, torque, fuel consumption, and emissions. The configuration of the testing bed is discussed in detail, including the selection of components which thousands of different component where manufactured in different factories with high degree of accuracy and interchangeability, integrated to the systems. A case study is also presented at the Caritas University, a configured internal combustion engine testing bed to demonstrate the effectiveness of the testing bed in evaluating the performance of a spark ignition engine. The results show that the testing bed is capable of accurately measuring engine performance parameters, making it a valuable tool for engine development, testing and research.  
Affordable Micro-Controller Arduino-Based Board Experimental Training Kit Implementation in Nigerian Universities
Full text linkEngineering and technology education in Nigeria faces challenges, including limited access to practical learning tools and high-cost laboratory equipment. To bridge this gap, this paper proposes the development of an affordable, Arduino-based experimental training kit tailored for Nigerian universities. The kit aims to provide hands-on experience in embedded systems, electronics, and programming, fostering practical skills and innovation among students. The training kit is designed with cost-effective components, modularity, and scalability, ensuring it can support a wide range of experiments, from basic circuit design to advanced microcontroller-based projects. The Arduino platform was selected for its affordability, open-source ecosystem, and ease of integration with various sensors and actuators. To validate its effectiveness, the training kit was piloted in selected Nigerian universities, where it demonstrated improved student engagement, better understanding of theoretical concepts, and enhanced problem-solving abilities. Additionally, the kit\u27s affordability makes it accessible to institutions with limited budgets, promoting inclusive education. This study highlights the potential of low-cost, locally adaptable solutions in addressing the practical learning challenges in Nigerian higher education, emphasizing the importance of integrating such tools into engineering curricula to produce industry-ready graduates
Optimal Integration Of Renewable Energy Into The National Grid For Improved Power Supply Using Ann Based Supercapacitor
Full text linkThe increasing global demand for clean and sustainable energy has accelerated the integration of renewable energy sources (RES) such as solar photovoltaic (PV) and wind power into national grids. In Nigeria, the adoption of RES is hindered by challenges including variability in power generation, grid instability, and insufficient energy storage capacity. These limitations often result in unreliable power supply, frequency deviations, and voltage fluctuations. This study presents an Artificial Neural Network (ANN)-based super capacitor control system designed to achieve the optimal integration of renewable energy into the national grid for improved power supply stability and reliability. The ANN serves as an intelligent controller capable of learning complex nonlinear relationships between renewable generation patterns, grid demand, and storage behavior, enabling adaptive and precise charge–discharge control of the super capacitor. The super capacitor, with its high power density and rapid response time, mitigates the effects of renewable intermittency by providing fast frequency regulation, voltage support, and peak shaving. Simulation results obtained from a MATLAB/Simulink model of the Nigerian grid integrated with RES demonstrate that the proposed ANN-based supercapacitor system significantly improves grid stability, reduces voltage deviation by up to 18%, and enhances renewable energy utilization efficiency by 25% compared to conventional storage control methods. The findings indicate that ANN-driven supercapacitor storage systems offer a viable solution for optimizing renewable energy integration, ensuring improved operational reliability, and supporting Nigeria’s transition towards a more sustainable power infrastructure. The results obtained were the conventional intermittency and rapid generation variability that causes unoptimal integration of renewable energy into the national grid for unimproved power supply was 52 MW. On the other hand when an ANN based super capacitor was integrated into the system, it instantly reduced to 47.5 MW and the conventional intermittency and Poor generation forecasting that causes unoptimal integration of renewable energy into the national grid for unimproved power supply was31MW. Meanwhile when an ANN based super capacitor was introduced into the system, it automatically reduced to28.3 MW. Finally, with these results obtained, it definitely meant that the percentage optimized integration of renewable energy into the national grid for improved power supply when an ANN based super capacitor was imbibed into the system was8.7%
Assessment Of Social Media News Credibility Among The Residents Of Enugu Metropolis
Full text linkThe study investigated social media news credibility among the residents of Enugu Metropolis. The survey research design was used in the study. The sample size was 369 and the population comprised the residents of Enugu Metropolis which is 764,289. Multi-stage sampling technique was employed in selecting the sample systematically after which the questionnaire was distributed online and some physically. The findings in the study shows that the most used social media platforms among residents of Enugu Metropolis are Facebook, Instagram and WhatsApp more than the other platforms and they use these platforms mostly for information and communication. The Majority of the participants had the opinion that social media news are credible based on timeliness, source, citations and credibility of the author or organization. Based on the findings of this study, the following were recommended; that necessary codes of conduct and ethics should be adopted by social media owners to guarantee credibility and accuracy of information. Media literacy should be encouraged among the users of social media to enable them control and determine what they do with the information that they receive over the media. It is recommended that effort should be made on the part of the audience to compare information obtained from social media with other available news sources before accepting or even fleeting the same information to other helpless users and many more
Chemical Constituents Of Allium Sativum (Garlic) And Curcuma Longa (Tumeric) Essential Oil
Full text linkCurcuma longa (turmeric) and Allium sativum (garlic) are spices that have been indicated to have several pharmacological potentials. The current study assessed the chemical constituents of turmeric and garlic. The essential oils were hydro distilled from the rhizomes of turmeric and bulbs of garlic in a yield of 0.80% (w/w) and 0.75% (w/w) respectively. The oils were analyzed by gas chromatography (GC) and gas chromatography and mass spectrometry (GC-MS). A total of fifty-four constituents were identified for both oils representing 96.3% (A. sativum) and 96.5% (C. longa). The main constituents of the oil of C. longa were ar-tumerone (28.6%), atlantone (21.9%) and curlone (18.8%). The main constituents in A. sativum were sulfur derivative (94.1%), diallyldisulphide (15.7%), diallytrisulfied (53.9%), diallyltetrasulfide (11.7%), methylallytrisulphide (9.2%). This research shows that oil from turmeric and garlic comprises a total of 54 constituents and has 4 components in common
Rehabilitation And Maintenance Of Workshop Equipments Using Convolutional Neural Network (Cnn). a Case Study Of Safety In Caritas University Workshop Enugu
Full text linkThe effective rehabilitation and maintenance of workshop equipment are crucial for ensuring operational efficiency and safety in academic and industrial environments. This study explores the application of Convolution Neural Networks (CNN) in the rehabilitation and maintenance of workshop equipment at Caritas University Workshop, Enugu, with a focus on enhancing safety protocols. The primary aim of the research is to develop a predictive maintenance system that can detect potential equipment failures and prevent safety hazards through real-time data analysis. A CNN model was trained using sensor data and images from the workshop equipment to identify anomalies such as unusual vibrations, temperature fluctuations, and wear and tear that may signal impending failure. The results demonstrated the model\u27s ability to accurately predict equipment failures, allowing for timely maintenance interventions and reducing downtime. Additionally, the system significantly contributed to improving safety by detecting unsafe operating conditions before they led to accidents. The study found that integrating AI-driven predictive maintenance and safety protocols could optimize workshop operations, increase equipment lifespan, and enhance the overall safety of workshop environments. This research provides valuable insights into the potential of AI technologies, particularly CNNs, to revolutionize maintenance practices and safety management in educational and industrial settings. Future work should focus on expanding the dataset, optimizing computational resources, and exploring the scalability of the model for broader industrial applications
Optimizing The Rehabilitation And Upgrading The Performance Evaluation Of Internal Combustion Engine System Using Intelligent Ultracapacitor
Full text linkThe rehabilitation and performance optimization of internal combustion engine (ICE) systems are critical for improving energy efficiency, reducing emissions and enhancing operational reliability. This study focuses on integrating an intelligent ultra-capacitor system to enhance the performance evaluation and upgrade the functionality of ICE systems at Caritas University, Amorji Nike, Enugu. By leveraging intelligent control algorithms and advanced energy storage technologies, the proposed system ensures efficient energy management, improved engine start-stop functionality and reduced wear on critical components. A comprehensive evaluation framework is developed to assess the impact of the intelligent ultra-capacitor on the engine\u27s performance, fuel efficiency and environmental sustainability. The findings demonstrate significant improvements in operational efficiency and a reduction in maintenance costs. This study provides a practical blueprint for implementing intelligent energy solutions in ICE systems contributing to sustainable engineering practices in academic and industrial settings
The Transformative Role of Medical Wearable Devices in Healthcare: Benefits, Challenges, and Future Directions
Full text linkMedical wearable devices are revolutionizing healthcare by enabling continuous monitoring, early disease detection, and improved patient engagement. This study explores the concepts, architecture, and impact of these devices, focusing on their benefits and challenges. Employing a qualitative approach, the research highlights the potential of wearables to mitigate medication errors and improve healthcare delivery. While benefits such as real-time monitoring and personalized care are evident, challenges like data inconsistency, cybersecurity risks, and interoperability remain. The findings provide actionable insights for advancing the adoption of medical wearable devices in modern healthcare
Implementation of Fatigue Strength Analysis of Washing Machine Drum Using Von Mises Approach
Full text linkThe fatigue strength analysis of washing machine drum was analyzed using von mises approach. The expected life time of the washing machine drum with respect to fatigue strain at the welded parts was successfully estimated using Miner’s rule. From the results obtained it was observed that increasing the speed of the washing machine from 400 to 2200 rpm resultedto decrease in its life time from 120 to 20 months and this were attributed to increase in stress – strain concentration and then fatigue failure of the welded parts. Autodesk simulation of the washing drum activities at speeds and temperatures ranging from 400 to 2200 rpm and 30℃ to 120℃ respectively increased the von mises stress of the machine from 62 to 549Mpa. The simulation shows that increase in speed and temperature of the machine drum, decreased the fatigue limits of the welded thin sheets. Node shell element result of the strains at front, rear, and middle of the welded parts of the drum produced varying results at speeds in the range of 400 to 2200 rpm. Higher strains values ranging from 11 to 278 Mpa. Were obtained in the middle of the drum were stress concentration was more, which could be as a result of location of greater washing activity than in the front and rear side of the cylinder with less strain values (-1104 to -58Mpa), increase in speed (400- 2200 rpm) and the loads (10 to 100kg) in the washing machine drum were observed to increase the strain effects at the rear, front and middle of the cylinder