Face recognition attendance system using Local Binary Pattern (LBP)

Attendance is important for university students. However, generic way of taking attendance in universities may include various problems. Hence, a face recognition system for attendance taking is one way to combat the problem. This paper will present an automated system that will automatically saves student’s attendance into the database using face recognition method. The paper will elaborate on student attendance system, image processing, face detection and face recognition. The face detection part will be done by using viola-jones algorithm method while the face recognition part will be carried on by using local binary pattern (LBP) method. The system will ensure that the attendance taking process will be faster and more accurate

A mobile phone app for the prevention of type 2 diabetes in Malaysian women with gestational diabetes mellitus: Protocol for a feasibility randomized controlled trial

Background: Over 50% of women with a history of gestational diabetes mellitus (GDM) will develop type 2 diabetes (T2D) in later life. Asian women experience a disproportionate risk of both GDM and T2D compared to women from other ethnic backgrounds. Lifestyle interventions and behavior change can delay or even prevent the onset of T2D. We have developed a digitalized diabetes prevention intervention for the prevention of T2D in Malaysian women with GDM. Objective: The protocol describes a randomized controlled trial (RCT) to test the feasibility of undertaking a definitive trial of a diabetes prevention intervention, including a smartphone app and group support. Secondary aims are to summarize anthropometric, biomedical, psychological, and lifestyle outcomes overall and by allocation group, and to undertake a process evaluation. Methods: This is a two-arm parallel feasibility RCT. A total of 60 Malaysian women with GDM will be randomized in the antenatal period to receive the intervention or standard care until 12 months post partum. The intervention is a diabetes prevention intervention delivered via a smartphone app developed based on the Information-Motivation-Behavioral Skills model of behavior change and group support using motivational interviewing. The intervention provides women with tailored information and support to encourage weight loss through adapted dietary intake and physical activity. Women in the control arm will receive standard care. The Malaysian Ministry of Health’s Medical Research and Ethics Committee has approved the trial (NMRR-21-1667-60212). Results: Recruitment and enrollment began in February 2022. Future outcomes will be published in peer-reviewed health-related research journals and presented at national, regional, or state professional meetings and conferences. This publication is based on protocol version 2, January 19, 2022. Conclusions: To our knowledge, this will be the first study in Malaysia that aims to determine the feasibility of a digital intervention in T2D prevention among women with GDM. Findings from this feasibility study will inform the design of a full-scale RCT in the future