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Impact Of Ai-Generated Content On Journalism Practice: a Study Of Practicing Journalist In Enugu, Nigeria
Full text linkThis study investigates the impact of AI-generated content on journalism practices in Enugu State, Nigeria. The research employed a survey design, sampling 117 registered journalists under the Nigerian Union of Journalists (NUJ), Enugu State Chapter. The study aimed to assess journalists\u27 exposure to AI tools, their use of AI-generated content in professional practice, perceived benefits, and challenges faced in its application. Findings reveal high awareness and usage of AI tools among journalists, with ChatGPT being the most recognized (79.5%). The majority of respondents (99.1%) use AI-generated content to some degree in their work, primarily for research (81%) and writing (50%). Key benefits identified include time and resource savings (88.9% agreement) and increased efficiency and productivity (72.4% agreement). However, challenges such as lack of awareness or knowledge (58.9%), limited access to AI tools (59%), and concerns about content quality and reliability (55.5%) were also highlighted.The study concludes that while AI-generated content has become integral to journalistic practice in Enugu State, there is a need for a balanced approach that leverages AI\u27s benefits while addressing its limitations and ethical implications. Recommendations include comprehensive training programs, improved access to AI tools, development of ethical guidelines, and further research to track long-term impacts. These findings contribute to the understanding of AI\u27s role in journalism and provide insights for media professionals, organizations, and policymakers in navigating the evolving landscape of AI in journalism
Future of Outsourcing in the Era of Increased Petroleum Pricing in Nigeria: A Narrative Review.
Full text linkThis study examines the future of outsourcing in Nigeria\u27s petroleum industry amidst rising petroleum prices, focusing on impacts, challenges, and potential solutions. With outsourcing being a critical strategy for optimizing costs and enhancing efficiency, the rising cost of petroleum presents significant challenges for the industry. The review synthesizes literature and reports to understand how increased petroleum prices drive up production costs, compelling businesses to seek cost-effective outsourcing solutions, often at the expense of service quality. The study highlights the resultant operational inefficiencies and risks associated with partnering with cheaper offshore firms, which compromise the overall performance of outsourcing endeavours in Nigeria. The review identifies key challenges faced by Nigerian companies in the outsourcing domain, including inadequate technology, mismatched service quality, and increased logistics costs. The study suggests several strategic solutions, such as full outsourcing to well-capitalized service providers, implementing just-in-time concepts, improving payment durations, and establishing sustainable communication channels. These recommendations aim to mitigate the adverse effects of rising petroleum prices on outsourcing while enhancing operational efficiency and ensuring high service quality. By adopting these strategies, the Nigerian petroleum industry can better manage transaction costs and risks, ultimately contributing to broader economic stability and growth in the country
The Impact of Public Spending on Research and Development on Productivity in the Agricultural Sector in Sub-Saharan Africa
Full text linkThis study examines public agricultural research and development spending on agricultural production growth in sub-Sahara Africa. The data used for the research were obtained from the United States Development of Agriculture (USDA), World Bank database and Agricultural Science and Technology Indicator (ASTI). The objectives of the study include the following; 1) to assess the impact of public agricultural R&D investment on crop yield growth across Sub-Saharan African countries. 2) to evaluate the effect of public agricultural R&D spending on total factor productivity (TFP) growth in Sub-Saharan Africa. The statistical tools employed for the study were descriptive statistics and panel unit root test using Levin-Lin-Chu, Breitung, and Im-Pesaran-Shin unit root tests. The findings show that the crop yield variable was found to be non-stationary, implying trends or persistent shocks over time. It shows a positive and significant effect of R&D on yield. The differenced values fluctuated around zero, confirming improved stationarity. Similarly, the Total Factor Productivity (TFP) Index was established to be stationary, suggesting short-term fluctuations around a stable mean and making it a suitable dependent variable in evaluating R&D impacts. Hence, TFP and R&D are stationary which shows substantial positive correlation, supporting productivity enhancement via public R&D. The study recommends examining the role of private agricultural R&D and its interaction with public investments in enhancing productivity
Early Prediction of Dementia Using Machine Learning
Full text linkThis study explores the application of machine learning algorithms for the early prediction of dementia, aiming to improve diagnostic accuracy and reliability. Utilizing a comprehensive dataset from Kaggle, which includes both continuous and categorical variables, four machine learning models—Random Forest, Decision Tree, Logistic Regression, and Support Vector Machine (SVM)—were implemented and evaluated. The study identifies cognitive test scores, the APOE ε4 allele, and depression status as key predictors of dementia. Tree-based models demonstrated superior performance, achieving perfect scores across metrics such as accuracy, recall, precision, and F1. Despite these promising results, the study acknowledges limitations such as the reliance on a single dataset, limited predictors, and challenges in real-world validation. Future research should incorporate larger, more diverse datasets, longitudinal data, and additional predictors to improve model robustness and applicability. These findings highlight the potential of machine learning as a transformative tool in clinical settings for timely dementia diagnosis and intervention
Improving Rehabilitation And Maintenance Of Workshop Equipments Using Artificial Neural Network (Ann) Based Technique. a Case Study Of Foundry Crucible Furnace In Caritas University Amorji Nike Emene Enugu
Full text linkThe effective rehabilitation and maintenance of workshop equipment are critical for ensuring optimal performance, reducing operational downtime, and extending the lifespan of machinery. This study focuses on improving the rehabilitation and maintenance process of a foundry crucible furnace in Caritas University Amorji Nike Emene, Enugu, using an Artificial Neural Network (ANN)-based technique. The research explores the application of ANN in predictive maintenance by analyzing historical operational data and identifying patterns that indicate potential faults or performance degradation.A structured methodology was adopted, involving data collection from the crucible furnace, preprocessing, and training of the ANN model. The ANN-based system was designed to predict faults and recommend maintenance actions before critical failures occur. Results from the study demonstrated that the ANN model accurately detected anomalies and provided timely alerts, significantly reducing downtime and improving operational efficiency. The findings highlight the potential of ANN-based techniques in transforming traditional maintenance practices into proactive and intelligent systems. The study recommends the integration of ANN systems into workshop maintenance frameworks, the training of technical personnel, and the adoption of sustainable practices to enhance reliability and productivity. This approach not only optimizes equipment performance but also contributes to the advancement of intelligent maintenance technologies in educational institutions
Voltage Stability Compensation in Electronics –Saturated Network Using Unified Power Flow Controller
Full text linkVoltage stability is a critical aspect of power system operation, especially in networks with a high penetration of power electronic loads such as variable speed drives, converters, and renewable energy systems. These electronics-saturated networks often experience voltage fluctuations, harmonic distortions, and reactive power imbalances, which can lead to instability and reduced power quality. The Unified Power Flow Controller (UPFC), a key Flexible AC Transmission System (FACTS) device, offers a comprehensive solution to these challenges by providing simultaneous control of voltage, impedance, and phase angle in the transmission line. This paper presents an approach for voltage stability compensation in electronics-saturated networks using the UPFC. The shunt converter of the UPFC provides reactive power support, maintaining bus voltage levels and mitigating voltage sags caused by nonlinear electronic loads. Simultaneously, the series converter regulates line impedance and power flow, reducing line losses and improving load distribution. Additionally, the coordinated control of the shunt and series converters helps damp power oscillations and improve system resilience against sudden load variations. Advanced control strategies such as Proportional-Integral (PI) controllers, Fuzzy Logic Controllers (FLC), and Model Predictive Control (MPC) are discussed for optimizing the UPFC’s performance under varying load conditions. Simulation results demonstrate that the UPFC significantly enhances voltage stability, reduces harmonic distortion, and improves overall power quality in an electronics-saturated network. The proposed solution is suitable for applications in modern power grids, including industrial plants, electric vehicle charging stations, and smart grid environments
Optimal Integration Of Renewable Energy Into The National Grid For Improved Power Supply Using Intelligent Solid State Var Compensator
Full text linkThe conventional Grid Congestion that causes challenges of integrating renewable energy into the national grid was 82%. Meanwhile, when an intelligent solid state VAR compensator was input into the system, it instantly reduced it to75% and the conventional System Losses Increase with RES Integration that causes challenges of integrating renewable energy into the national grid was5.7%. However, when an intelligent solid state VAR compensator was incorporated into the system, it automatically reduced it to threshold of 5%. Finally, with these results obtained, the percentage optimal integration of renewable energy into the national grid for improved power supply was 0.7% when an intelligent solid state VAR compensator was integrated into the system
Healing the Nation from the Inside Out: The Role of Home and Family in National Development
Full text linkNational development transcends economic growth to social cohesion, cultural continuity, and individual well-being. This paper explores how families serve as foundational units in instilling values, fostering social stability, and contributing to national advancement. Using Systems Theory as a framework, it highlights shows strong family structures influence governance, economic productivity, and civic responsibility. However, modernization, urbanization, and shifting gender roles have led to evolving family dynamics, impacting socialization processes and traditional support systems. Results discovered that the decline of extended family networks has weakened informal social safety nets, increasing reliance on governmental welfare programs. Moreover, families act as primary agents of political socialization, shaping future leaders and fostering democratic engagement. Challenges such as economic hardship, urban migration, and cultural shifts threaten familial bonds, necessitating policies that reinforce family cohesion and resilience. Strengthening the family as a unit through policy interventions, cultural preservation, and community engagement is essential for sustainable national development. By fostering environments that promote ethical values, discipline, and communal responsibility, families serve as the bedrock of societal progress. This paper argues that national healing and sustainable development begin within the home, emphasizing the need for family-centred policies in national planning. Recognizing the role of family as a driver of social harmony, economic sustainability, and political stability is crucial for fostering a prosperous and cohesive society. Thus, the study advocates for an integrated approach that prioritizes family stability as a fundamental strategy for nation-building and long-term development
A Critical Review of Workplace Stress: Causes, Theoretical Models and Strategic Management Approaches
Full text linkWorkplace stress is a widespread concern in modern organizations, significantly affecting employee well-being, productivity, job satisfaction, and overall organizational performance. This paper explores the multifaceted nature of workplace stress by examining its causes, consequences, theoretical frameworks, and effective management strategies. The study synthesizes insights from established theories, including Cognitive-Behavioral Theory, Person-Environment Fit Theory, Equity Theory, Demand-Support-Control Theory, and the Emotional Overload Model, to analyze workplace stress dimensions. The Cognitive-Behavioral Theory explores how individual perceptions shape stress responses, while the Person-Environment Fit Theory examines stress as a result of misalignment between personal abilities and job demands. Equity Theory highlights the impact of perceived imbalances in effort and rewards, whereas the Demand-Support-Control Theory identifies excessive demands, limited autonomy, and inadequate support as key stressors. Additionally, the Emotional Overload Model emphasizes the role of excessive workloads and poor work-life balance in stress development. Research has found several causes of workplace stress, including excessive workloads, lack of recognition, toxic work environments, tight deadlines, and insufficient support systems. Effective strategies often integrate personal stress management techniques with systemic changes within the organization to create a supportive and balanced work environment. Future research could explore innovative approaches, such as virtual reality-based stress management, to enhance employee well-being, resilience, and overall organizational performance
Personality Traits and Loneliness as Predictors of Internet Addiction among University Undergraduates
Full text linkThis study investigated personality traits and loneliness as predictors of interest addiction among university undergraduates. A total of 360 university undergraduates selected across departments and faculties at Caritas University Enugu were used as sample for the study. The participants who were between the ages of 18-23 years comprise of 201 females and 159 males. Three instruments were used for data collection i.e. internet addiction test (IAT) young (1998), Big Five Personality Inventories (BFI) John and Srivastava (1990), loneliness inventory by (Laura 2014) Survey research design was adopted while career regression was used for data analysis. Findings revealed that Personality trait extroversion, shows a negative predictor of internet addiction among undergraduates (β= -.313, P< .001), Agreeableness also showed a significant negative predictor of internet addiction among undergraduates (β= -.499, P< .001). Conscientiousness did not show a significant prediction on internet addiction among undergraduates (β= .155, P> .05). Neuroticism showed a significant positive predictor of internet addiction among adolescents (β= .506, P< .001). Openness to experience showed a significant positive predictor of internet addiction among undergraduates (β= .522, P< .001).Loneliness also showed a significant positive predictor of internet addiction among undergraduates. Findings were discussed in relation with literature reviewed and recommendations were also made