SIMULATION

Background: Simulation-based learning is essential for preparing and training undergraduate students for their professional roles and enhancing their experiences and skills. Simulation-based learning (SBL), however, has not been widespread, despite its integration in the university curriculum. There is a gap in understanding how undergraduate students perceive and engage with simulation base learning. Objective: This study aims to assess the knowledge, attitude and practice of simulation based learning among undergraduate students in university of Benin. Subjects and Methods: A descriptive cross-sectional study design was utilized for this study using a self-administered questionnaire administered to 620 undergraduate students of university of Benin. Data collected was analyzed using IBM Statistical Package for Social Science (SPSS) 27.0. with statistical significance set at p<0.05 and 95% Confidence Interval. Categorical data was presented using frequency tables. Chi-square and Fischer’s Exact tests examined relationship between demographic characteristics and respondent’s knowledge, attitude, practice and challenges towards simulation-based learning. Results: The mean age and parity of respondents studied was 21.1 ± 3.1 years. In terms of sex, 54.8% of the respondents were male, and 45.2% were female. The tribal distribution of the respondents showed Benin (34.5%) with the highest proportion. Five hundred and twenty-five (84.7%) respondents were aware of simulation-based learning with 193 (36.7%) having good knowledge of SBL. Department and academic level were significant predictors of good SBL knowledge with respondents form Medicine and 600 level students showing a p-value of 0.042 and 1 respectively. In relation to attitude, 447 (85.1%) respondents had positive attitude towards simulation based learning while only 78 (14.9%) had negative attitude. Good knowledge and Academic level were significant predictors of attitude toward simulation-based learning with respondents from fourth-year having a coefficient of 0.836 with a p-value of 0.053, suggesting a near-significant positive influence on supportive attitudes, while respondents from sixth-year and respondents with good knowledge of SBL as reference category. In relation to practice, 53.9% (334) had participated in simulation-based learning activities, while 46.1% (286) had not. The academic level of study of respondents in their sixth year, good knowledge and attitude had a strong predictive value and significantly influenced participation of simulation-based learning. Conclusion: The study revealed that while awareness of simulation-based learning is high, over two-thirds of students showed limited understanding of its concepts, especially younger and less advanced students. Over four-fifths had a positive outlook on simulation-based learning, recognizing its value in enhancing knowledge and skills. Although more than half had participated in SBL activities, current engagement was lower, with only four-tenths actively involved. High-fidelity mannequins and virtual patients were commonly used, indicating a preference for realistic simulations. Notably, over one-fifth of respondents reported challenges, such as inadequate infrastructure, limited resources, technical issues, and time constraints, which hinder effective simulation-based learning implementation.

The increasing complexity of Electric Vehicle (EV) powertrains necessitates a robust, integrated, and flexible control strategy, centralized within the Electric Vehicle Control Unit (EVCU). This study shows the implementation of the Id = control strategy using the MATLAB/Simulink Motor Control Blockset under varying loading conditions and speed requirements. This study further goes on to show an implementation of a CC-CV charging controller for a Li-ion battery with multiple current control loops. The study is designed for compliance with the AUTOSAR (Automotive Open System Architecture) Classic Platform for compliance – ensuring modularity, portability and adherence to industry standards. The study results validate the performance of the Interior PMSM and the ability to generate C implementation and header files from the model-based engineering (MBE) design approach which can be further used for hardware-in-the-loop testing. This study concludes that the MBE and AUTOSAR approach produces a highly efficient framework for developing, validating and iterating on complex, multi-domain electric vehicle components.

Traditional cybersecurity awareness programs often struggle with engagement, scalability, and the ability to measure real behavioral change among users. To address these challenges, this project presents the development of a Phishing Simulation and Awareness Portal using Google Workspace tools. The system is designed to simulate real-world phishing attacks in a controlled environment and educate users through interactive, micro-based lessons. Built with Google Apps Script, Gmail, and Google Sheets, the platform automates the creation, deployment, and tracking of phishing campaigns, while maintaining real-time event logging and analytics. It also provides administrators with a simple, centralized interface for managing email templates, campaign configurations, recipient data, and awareness metrics. By integrating simulation and training within the familiar Google ecosystem, the system eliminates the need for external applications and ensures ease of deployment across organizations. Ultimately, this project aims to enhance user vigilance, reduce susceptibility to phishing threats, and promote a culture of proactive cybersecurity awareness through continuous education and data-driven feedback

The growing demand for compact, high-performance electronic devices has intensified the challenge of managing heat generation, which can significantly affect system reliability, efficiency, and lifespan. This study focuses on the design and simulation of a mechatronic cooling system for electronic devices, integrating thermal, electrical, and control subsystems into a unified framework for intelligent temperature regulation. The primary aim was to develop a system capable of maintaining thermal stability and optimizing energy consumption under varying operating conditions. The design approach employed a Battery Management System (BMS) architecture enhanced with active thermal management, including temperature sensors, actuators, and adaptive control logic. The simulation was conducted under dynamic load conditions using a multi-module configuration to emulate real-world electronic systems such as electric vehicle battery packs. Key parameters evaluated included vehicle speed, battery pack temperature, pump power, and refrigerant power. Results showed that the system effectively reduced and maintained the battery pack temperature from approximately 30°C to 20°C, demonstrating efficient heat dissipation and temperature stability. The pump and refrigerant subsystems exhibited adaptive behavior, automatically adjusting power consumption in response to real-time temperature variations. This confirmed the system’s ability to achieve energy-efficient cooling and dynamic thermal control without manual intervention. The findings indicate that the proposed mechatronic cooling system successfully integrates sensors, actuators, and intelligent control algorithms to ensure effective and autonomous thermal regulation. The system’s energy optimization, realtime adaptability, and scalability make it suitable for diverse applications such as battery cooling, processor thermal management, and power electronics systems. In conclusion, the study validates the potential of mechatronic-based cooling systems as a reliable, efficient, and sustainable solution for modern electronic devices. Future work should focus on hardware prototyping, controller optimization using advanced algorithms, and exploration of alternative cooling fluids to further enhance system performance and sustainability.

This study models and simulates the wave energy potential along Nigeria’s coastline to evaluate its feasibility as a sustainable power source. With the nation facing persistent energy deficits and heavy dependence on fossil fuels, wave energy offers a clean and renewable alternative. Using real world oceanographic data from the Copernicus Marine Service (ERA5 dataset), key wave parameters significant wave height (Hs) and mean wave period (Te) were extracted and processed in MATLAB. A dynamic heaving point absorber Wave Energy Converter (WEC) model was then developed in Simulink to simulate power generation over a one year period (September 2024–September 2025). The simulation results show that a single 5-meter wide point absorber can generate approximately 13.88 MWh annually, with peak outputs during the summer months when wave activity findings confirm that Nigeria’s wave climate, though moderate, is consistent and technically viable for decentralized, off grid energy applications, particularly for coastal communities and small industries. This research provides a quantitative foundation for future investment, policy development, and pilot projects aimed at integrating marine renewable energy into Nigeria’s sustainable energy mix.