UPSI Digital Repository (UDRep)
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Total records found : 2 |
Simplified search suggestions : Puteri Zarina Megat Khalid |
1 | 2023 Article | Flipped classroom pedagogy in higher education in EFL contexts: findings and implications for further research Puteri Zarina binti Megat Khalid The primary aim of this article is to examine the existing findings of flipped classroom (FC) pedagogy in higher education institutions (HEIs) for teaching English as a foreign language (EFL) context. Relevant studies have been scrutinised based on keywords, such as higher education, online learning, blended or hybrid teaching, flipped classrooms, and English language instruction in EFL environment. A total of 54 out of the selected 162 articles were analysed using the critical review process as the research methodology, and data were analysed using the content analysis technique. The findings revealed that flipped classroom (FC) had been applied in different parts of the world over many years. But, most of the studies are in science and engineering. Flipped classroom (FC) in the English as foreign language context has remained untapped. Most of the studies conclude that flipped classroom (FC) has more benefits compared to its drawbacks. This review makes several recommendations for fu..... 232 hits |
2 | 2023 Article | Practical consideration in using pre-trained Convolutional Neural Network (CNN) for finger vein biometric Puteri Zarina Megat Khalid Using a pre-trained Convolutional Neural Network (CNN) model for a practical biometric authentication system requires specific procedures for training and performance evaluation. There are two criteria for a practical biometric system studied in this paper. First, the systems ability to handle identity theft or impersonation attacks. Second, the ability of the system to generate high authentication performance with minimal enrollment period. We propose the use of the Multiple Clip Contrast Limited Adaptive Histogram Equalization (MC-CLAHE) technique to process finger images before being trained by CNN. A pre-trained CNN model called AlexNet is used to extract features as well as classify the MC-CLAHE images. The authentication performance of the pre-trained AlexNet model has increased by a maximum of 30% when using this technique. To ensure that the pre-trained AlexNet model is evaluated based on its ability to prevent impersonation attacks, a procedure to generate the Receiver Operati..... 186 hits |