Universiti Sains Malaysia

About: Universiti Sains Malaysia is a education organization based out in George Town, Pulau Pinang, Malaysia. It is known for research contribution in the topics: Population & Ring (chemistry). The organization has 23231 authors who have published 39356 publications receiving 655434 citations. The organization is also known as: USM & University of Science, Malaysia.

The prehistoric peopling of Southeast Asia.

Abstract: The human occupation history of Southeast Asia (SEA) remains heavily debated Current evidence suggests that SEA was occupied by Hoabinhian hunter-gatherers until ~4000 years ago, when farming economies developed and expanded, restricting foraging groups to remote habitats Some argue that agricultural development was indigenous; others favor the "two-layer" hypothesis that posits a southward expansion of farmers giving rise to present-day Southeast Asian genetic diversity By sequencing 26 ancient human genomes (25 from SEA, 1 Japanese Jōmon), we show that neither interpretation fits the complexity of Southeast Asian history: Both Hoabinhian hunter-gatherers and East Asian farmers contributed to current Southeast Asian diversity, with further migrations affecting island SEA and Vietnam Our results help resolve one of the long-standing controversies in Southeast Asian prehistory

Bi-histogram equalization with a plateau limit for digital image enhancement

Abstract: Many histogram equalization based methods have been introduced for the use in consumer electronics in recent years. Yet, many of these methods are relatively complicated to be implemented, and mostly require a high computational time. Furthermore, some of the methods require several predefined parameters from the user, which make the optimal results cannot be obtained automatically. Therefore, this paper presents bi-histogram equalization with a plateau level (BHEPL) as one of the options for the system that requires a short processing time image enhancement. First, BHEPL divides the input histogram into two independent sub-histograms. This is done in order to maintain the mean brightness. Then, these sub-histograms are clipped based on the calculated plateau value. By doing this, excessive enhancement can be avoided. Experimental results show that this method only requires 34.20 ms, in average, to process images of size 3648 × 2736 pixels (i.e. 10 Mega pixels images). The proposed method also gives better enhancement results as compared with some multi-sections mean brightness preserving histogram equalization methods.