No abstract

Terrestrial gamma radiation dose rate measurement has been conducted around Kampung Sungai Durian (Kg. Sg. Durian), Kinta District, Malaysia. The mean value of outdoor terrestrial gamma radiation (TGR) dose rate and indoor in the area are 458 nGy h -1 and 286 nGy h

This project is funded by The Atomic Energy Licensing Board of Malaysia (Vot no. 68876

Monitoring systems for the early detection of diabetes are essential to avoid potential expensive medical costs. Currently, only invasive monitoring methods are commercially available. These methods have significant disadvantages as patients experience discomfort while obtaining blood samples. A non-invasive method of blood glucose level (BGL) monitoring that is painless and low-cost would address the limitations of invasive techniques. Photoplethysmography (PPG) collects a signal from a finger sensor using a photodiode, and a nearby infrared LED light. The combination of the PPG electronic circuit with artificial intelligence makes it possible to implement the classification of BGL. However, one major constraint of deep learning is the long training phase. We try to overcome this limitation and offer a concept for classifying type 2 diabetes (T2D) using a machine learning algorithm based on PPG. We gathered 400 raw datasets of BGL measured with PPG and divided these points into two classification levels, according to the National Institute for Clinical Excellence, namely, “normal” and “diabetes”. Based on the results for testing between the models, the ensemble bagged trees algorithm achieved the best results with an accuracy of 98%.

The activity concentrations of 238 U, 232 Th and 40 K in soil samples from different soil types has been collected in the state of Perak, Malaysia. The samples were determined using a high resolution co-axial HPGe gamma ray spectrometry system. Th in soil samples in the study area are higher than the reference value.