various concentrated work on detection of defects on printed circuit boards (PCBs) have been done, but it is also crucial to classify these defects in order to analyze and identify the root causes of the defects. This project is aimed in detecting and classifying the defects on bare single layer PCBs by introducing a hybrid algorithm by combining the research done by Heriansyah et al [1] and Khalid [2]. This project proposes a PCB defect detection and classification system using a morphological image segmentation algorithm [1] and simple the image processing theories [2]. Based on initial studies, some PCB defects can only exist in certain groups. Thus, it is obvious that the image processing algorithm could be improved by applying a segmentation exercise. This project uses template and test images of single layer, bare, grayscale computer generated PCBs. The research improves Khalid [2] work by increasing the number of defect categories from 5 to 7, with each category classifying a minimum of 1 to a maximum 4 different types of defects and a total of 13 out of 14 defects were classified.

A variety of ways has been established to detect defects found on printed circuit boards (PCB). In previous studies, defects are categories into seven groups with a minimum of one defect and up to a maximum of 4 defects in each group. Using Matlab image processing tools this research separates two of the existing groups containing two defects each into four new groups containing one defect each by processing synthetic images of bare through-hole single layer PCBs.

pandemic which began in early 2020 has impacted the education landscape when many countries were forced to implement lockdown. As a result, many moved to online learning mode throughout 2020 and 2021. There are proven success of online learning delivery when designed using the theory of cognitive constructivism which focus on combination of authentic and active learning. One aspect of active learning is learner-tolearner engagement. This study investigates the survey questions on learner-to-learner engagement from 117 respondents of UiTM bachelor's degree students by carrying out descriptive analysis. The descriptive analysis involves finding the measures of central tendency, calculation of Relative Important Index, classifying the distribution plot and determining the correlation between variables using Spearman correlation method. Results of the survey showed that peer support to finish task ranks first among while collaborative learning rank last.

The COVID-19 pandemic has forced governments to declare a Movement Control Order that affects all sectors, including education. Students must remain in hostels or at home since they are not allowed to return to campus. Hence, university officials resort to the Open and Distance Learning (ODL) method to keep their operations running. Numerous collaborative digital platforms (e.g. Microsoft Teams and Google Meets), social networks (e.g. WhatsApp, Telegram, and Facebook), and even the telephone have emerged to aid in the learning and assessment processes. Locally, tertiary institutions have encountered various obstacles in getting their ODL systems up and running so that students can resume their studies. One of the challenges is adapting to and becoming comfortable with the various online platforms available. The inconsistency with which these platforms are used to try out and select the best one harms the learning and teaching process. This study investigates the efficacy of the ODL approach in increasing students' interest in the Electronics 1 (ELE232) course. The survey method and descriptive qualitative research are used in this study. 37 students from the J4EE1113A1 and J4EE1113B1 groups at the Faculty of Electrical Engineering, UiTM Cawangan Johor Kampus Pasir Gudang, who completed the Electronics 1 course in the 20204 semester, took part in this study. The data was collected using Google Forms, and the analysis followed Mile and Hubermen's interactive model, which had four stages: gathering data, creating data, presenting data, and drawing conclusions. According to the findings, 62% of students believe that ODL improves their ELE232 learning.

This research emphasizes on the study of Vortex transmitter and Differential Pressure (DP) transmitter performance for a laboratory pilot plant by observing process response criteria consisting of dead-time (TD), rise time (TR), overshoot (%OS) and settling time (TS) for set point changes in a Proportional-Integral-Derivative (PID) flow control architecture. Four experiments were conducted; rising set point for Vortex transmitter, rising set point for DP transmitter, falling set point for Vortex transmitter and falling set point for DP transmitter. Limit tolerance test for Vortex transmitter and DP transmitter were done to determine the operational limits. Continuous Cycling Method is applied for controller tuning. Control and data collection for the flow plant is done using Distributed Control System (DCS) in real time. It is observed that Vortex transmitter produces a smaller TD, TS, Ts and %OS compared to DP transmitter for falling SP experiment, while less conclusive results were obtained for rising SP set up where Vortex transmitter produces a larger TD and Ts but smaller TR and %OS.