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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Iza Sazanita Isa
Universiti Teknologi MARA
Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

 1 
Open distance learning simulation-based virtual laboratory experiences during COVID-19 pandemic Iza Sazanita Isa; Hasnain Abdullah; Nazirah Mohamat Kasim; Noor Azila Ismail; Zafirah Faiza
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp4042-4053

Abstract

The widespread of coronavirus disease 2019 (COVID-19) pandemic led to a discovery that open distance learning (ODL) has turned out to be the only choice for teaching and learning by most institution (s) of higher learning (IHLs). In Malaysia, ODL is considered a new approach as physical laboratory practice has always been conducted for laboratory courses. This is a quantitative study which explores the perceptions of e-Lab among the students of bachelor’s in electrical and electronic engineering (EE) by focusing on the effectiveness and readiness in conducting the e-Lab. Simulation-based model is proposed for conducting the e-Lab using an interactive media and validated with the final score performance. With the future goals of improving the e-Lab in terms of delivering methods and engaging mediums between students and laboratory instructor, this study also discovered the levels of response from students’ perception to substitute the conventional laboratory by providing an equivalent and comparable learning experiences of the students.
A new procedure for lung region segmentation from computed tomography images Mohd Firdaus Abdullah; Siti Noraini Sulaiman; Muhammad Khusairi Osman; Noor Khairiah Abdul Karim; Samsul Setumin; Iza Sazanita Isa
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4978-4987

Abstract

Lung cancer is the leading cause of cancer death among people worldwide. The primary aim of this research is to establish an image processing method for lung cancer detection. This paper focuses on lung region segmentation from computed tomography (CT) scan images. In this work, a new procedure for lung region segmentation is proposed. First, the lung CT scan images will undergo an image thresholding stage before going through two morphological reconstruction and masking stages. In between morphological and masking stages, object extraction, border change, and object elimination will occur. Finally, the lung field will be annotated. The outcomes of the proposed procedure and previous lung segmentation methods i.e., the modified watershed segmentation method is compared with the ground truth images for performance evaluation that will be carried out both in qualitative and quantitative manners. Based on the analyses, the new proposed procedure for lung segmentation, denotes better performance, an increment by 0.02% to 3.5% in quantitative analysis. The proposed procedure produced better-segmented images for qualitative analysis and became the most frequently selected method by the 22 experts. This study shows that the outcome from the proposed method outperforms the existing modified watershed segmentation method.
Co-Authors Hasnain Abdullah Mohd Firdaus Abdullah Muhammad Khusairi Osman Nazirah Mohamat Kasim Noor Azila Ismail Noor Khairiah A Karim Noor Khairiah A. Karim Noor Khairiah Abdul Karim Nur Athiqah Harron Nurul Najiha Jafery Samsul Setumin Siti Noraini Sulaiman Syafiqah Aqilah Saifudin Zafirah Faiza Zainal Hisham Che Soh