Ultrasonography (US) is one of the procedures to monitor the growth of renal size in diagnose kidney disease. However considering the complexity of renal size, this procedure leads to inter-observer variability and poor repeatability. Given images from Abdominal CT scan, a level set thresholding and combination of logical and arithmetic operation based method was developed to calculate the automated feature description of renal size. This is achieved by applying 2D CT scan image into image segmentation and feature extraction where thresholding and morphological segmentation method are conducted. Then, parameters of the kidney such as perimeter, area, major axis and minor axis were measured and analyzed in classification step. As a result, analysis on the kidney size between subjects who are normal and the results from the studies has shown capability to classify correctly the size of kidneys about accuracy of 80% to 81% in terms of the kidney's relative axis which is the ratio of right kidney and left kidneys. In addition, the method in measurement kidney size is compared between manual method and automated method and results shows that the accuracy of the automated method in terms of compactness is about 91% to 95.

The advancement of modern technology has greatly influenced national development, with technologies like Augmented Reality (AR) increasingly integrated into education in Malaysia and Indonesia. Despite this, no study has yet explored the specific need for AR technology in teaching Arabic vocabulary from the KSSR syllabus in primary schools. Currently, students rely on traditional teaching methods, which limit their learning experience. This study investigates the need for AR-Mufradat development among Year 5 students at Sri Al-Amin Bangi Primary School. A quantitative approach was used, involving 30 students as respondents, and data was collected through a survey. The findings, analyzed using SPSS version 26, reveal a high demand for AR-Mufradat among these students. This study aims to guide future research, suggesting that AR technology could enhance the teaching and learning of Arabic, allowing students to master the language more effectively.