Keynote Speakers/主讲嘉宾

Keynote Speakers/主讲嘉宾

Keynote Speeches

A. Prof. Shengjun Zhou (周圣军副教授)

Wuhan University, China

Title: High brightness GaN-based light-emitting diodes

GaN-based LEDs have been considered as a candidate of next generation solid-state light sources for replacement of general lighting sources such as florescent lamps due to their environmentally friendly properties and long lifetime (~40,000 hrs). The light extraction efficiency is relatively low due to total internal reflection (TIR) of the generated light at the nitride-air interface resulting from their very different refractive indices. Our group employ various light extraction methods, including surface texturing, patterned ITO, current blocking layer, patterned sapphire substrate, wavy sidewalls, embedded air void microstructure, distributed Bragg reflector (DBR), micro/nano polymer grating, laser stealth dicing, and nanoscale Ni/Au wire gird, to improve light extraction efficiency of LEDs. We also develop two types of GaN-based flip-chip LEDs with highly reflective Ag/TiW and indium-tin oxide (ITO)/DBR p-type ohmic contacts. We show that a direct ohmic contact to p-GaN layer using pure Ag is obtained when annealed at 600°C in N2 ambient. Our demonstration of highly reflective pure Ag ohmic contact with superior current spreading paves the way for the realization of highly efficient ultra-high power flip-chip LEDs. 

Oral Presentation

Xiaocheng Chang (常小铖)

Wuhan University, China

Title: Comprehensive Analysis of Conductor Selection

With the continuous improvement of people's living standard, the consumption of electricity also increased, which requires a larger capacity of the conductor for electricity transmission. Therefore, comprehensive selection of conductor type made higher requirements. Based on the analysis, this paper divided the basic indication of conductor selection into two types: cost type and efficiency type, then each category divided into a number of specific indicators based on needs, finally, using the grey relational analysis method to compare and analyzes the cost indication and efficiency indication of conductors, drawing the optimization scheme of conductor selection, and using it to guide the type selection of conductor type.

Yali Ren(任雅丽)

Southeast University, China

Title: A GP-ELM Gesture Recognition Algorithm for Tactile Animation

Artificial Neural Network (ANN) is one of the most important techniques in gesture recognition with high accuracy, but its slow response limited its real-time applications. Extreme Learning Machine (ELM), a novel ANN with fast learning ability, has the potential to solve the above problem. The extant recognition methods based on ELM focus on Local Variant Features (LVF) of gesture images and a small number of data are used to represent many features. However, the locality of these features may lead to an inadequate representation of real world information. In this paper, a new algorithm based on Global Pixels (GP) and ELM is proposed. It includes two parts: image pre-processing and GP-ELM identification. Through the processing of segmentation, filtering and standardization, a raw gesture image is transformed into a binarization and unified-size image. And then the GP of the picture are used as the ELM inputs to be trained or identified. The algorithm using GP instead of LVF for training simplifies the pre-processing without losing information. Experiment results show that the average recognition accuracy can reach 96.67%, while the recognition time is only 0.041 milliseconds. With more hidden nodes, the accuracy can be improved to be 100% with negligible increase in recognition time.