SIMULATION

The comprehensive study of high-frequency transmission lines, including stripline, microstripline, differential microstriplines and differential striplines configuration is ritical for advanced RF and microwave engineering education. Fundamentals of some transmission line phenomenon such as impedance matching, reflection coefficient and the effect of open and short circuits, relies greatly on practical hands-on experience alongside theoretical tools like the Smith chart. Furthermore, many academic institutions face challenges in providing laboratory systems that accurately represent high-frequency transmission line structures on common PCB substrates such as FR4. The absence of versatile and cost-effective experimental circuits limits students’ opportunities to explore and solve real-world transmission line problems, thereby hindering the development of essential engineering skills. This project aims to develop an integrated high-frequency transmission line experimentation systems for university laboratories, incorporating stripline, microstripline, differential microstriplines and differential striplines configuration on FR4 substrates. The system will facilitate direct measurement and analysis of transmission line behavior, enabling students to visualize various experiments, and investigate the proposed applications (e.g. open and short circuit effects, s-parameters, transmission line as a filter etc.) within a controlled environment. By linking theoretical concepts with practical experiments, specifically through the application of Smith chart and transmission line theory, this system will enhance RF engineering education, equipping students with the competence needed to address modern communication system challenges effectively.

The study examines the firm specific determinants of the performance of insurance firms in Nigeria over the period 2019 – 2023, using descriptive statistics, correlation analysis and panel least squares regression techniques. A causal research design was adopted for the study. The firm specific factors considered in this study include firm size, capital adequacy, leverage, liquidity and firm age while insurance firm performance was proxy by return on asset. It adopts a multivariate panel least squares analysis for the estimation process. The finding of the study reveals that firm size, liquidity and firm age has a positive and insignificant effect on performance of insurance companies while capital adequacy and leverage has a negative and insignificant influence on performance of insurance firms. The study recommends among others that management of insurance firms should focus less on growing the size of insurance firms in Nigeria. Also, regulatory authorities should ensure that insurance firms comply strictly with capital adequacy set by the regulatory authorities.

This research presents the design and implementation of an integrated fuzzy logic–based decision-making system for autonomous vehicle navigation, focusing on intelligent speed regulation, steering control, and lane keeping. A three-degree-of-freedom (3-DoF) dual-track vehicle dynamics model was developed in MATLAB/Simulink to capture longitudinal, lateral, and yaw behaviors. The control architecture uses a Takagi–Sugeno fuzzy inference system to process speed error, distance error, and yaw deviation, generating throttle and steering actions that emulate human driving intuition. A simulation-based framework was developed for both ego and target vehicles, enabling the evaluation of inter-vehicle distance, trajectory following, and lane stability across straight and curved road sections. Results show that the fuzzy controller reduced longitudinal speed error to below 0.25 m/s, maintained lateral deviation within ±0.12 m on curved paths, and improved yaw rate tracking with a settling time of 1.8 s compared to 3.1 s without fuzzy control. The controller also limited throttle oscillations to less than 5% and sustained a safe inter-vehicle distance with less than 7% deviation from the desired headway. Overall, the research establishes a computationally efficient fuzzy-logic framework suitable for autonomous-vehicle applications, and the findings confirm the controller's robustness and adaptability in a virtual test environment.