Acoustic Research Group (ARG)
Acoustics Research Group (ARG) is composed of researchers in the field of acoustics that branch out the study and experimental works in the area of room acoustics and environmental noise, flexible Surface Acoustics Wave (SAW) and microwave sensory devices, nanomaterial, microwave propagation, microwave dielectric measurements, and numerical methods in electromagnetic
Head of Research Group
Expertise: room acoustics; speech; speech intelligibility
You Kok Yeow
Expertise: microwave sensors; dielectric measurements; numerical modeling
Connecting the dots. Some children are fast learner but some are slow. Knowing which part of the brain they engage the most during specific tasks help us help them to overcome their difficulties.
Figuring Out How Our Children Writes
A great deal of study has been performed to figure out the reasons of poor handwriting. Cortical information pathway is one of the intrinsic factors that is worth considering in understanding this difficulty yet received less attention from researchers. We asked ten pre-school children to trace three basic geometric shapes, and then monitor their brain signals using electroencephalograph. Interesting enough, we found out that most of the below-average young hand-writers had to plan their hand movement before tracing the shapes while average hand-writers just only needed to recall their related experience to trace the basic shapes. Such findings would definitely open up possibility of research to further understand the difference and how the educators can improve hand-writing for below-average children.
Tea Leaves Moisture Monitoring
In the recent years of technology advancement, the use of sensor technology has been widely accepted by many as a method in industry as well as research facility for determine the contents in samples, including our interest here; the moisture content of tea leaves. Drying the leaves (or in controlling the moisture content of the tea leaves) ensure higher quality tea leaves and hence higher market values. While existing sensors are available for this purpose which typically use standard gravimetric method, we take it one step further by trying to introduce a true, non-destructive, contact-less method using radio frequency antenna. Incorporating a horn antenna we found out the estimation of moisture content is accurate for moisture content less than 10.5% with the maximum error only at 3%.
Blowing the horn. Tea leaves business still has room to grow from the moisture monitoring technology prespective.