Papers by Author: Chang Hyun Kim

Abstract: We have investigated the electrical and physical properties of the oxidized-SiN with or without post oxidation annealing (POA) in N2 gas. A significant reduction in interface-trap density (Dit) has been observed in the oxidized-SiN with N2 POA for 60 min if compared with other oxides. The reason for this has been explained in this paper.

Abstract: In this research, we used nondestructive test based on ultrasonic test as inspection method, and made up inspection robot in order to control of ultrasonic probe on the SWP surface, and programmed to signal processing code and pattern classifying code by user made programming code. For evaluation of flaw signal is reflected on welding flaw, user-made program codes are composed of signal processing and probability neural network (PNN) and backpropagation neural network (BPNN). And then, we actually confirmed to the theoretical advantage of each neural network method compared probability neural network with backpropagation neural network for classification and recognition rate. For the application of classifier to SWP inspection system, BPNN classifier is adequate in the first stage. And then, the application of PNN classifier is adequate as the next stage. Because of PNN application need enough sample data that is due to probabilistic density function.

Abstract: The purpose of this research is stability estimation of plant structure through classification and recognition about welding flaw in SWP(Spiral Welding Pipe). And, In this research, we used nondestructive test based on ultrasonic test as inspection method, and made up inspection robot in order to control of ultrasonic probe on the SWP surface, and programmed to signal processing code and pattern classifying code by user made programming code. Inspection robot is simply constructed as 2-axes because of welding bead with fixed pitch. So, inspection of welding part can be possible as composition of inspection part for tracking on welding line. For evaluation of flaw signal is reflected on welding flaw, user-made program codes are composed of signal processing and Bayesian classifier and perceptron neural network and back-propagation neural network. And then, we confirmed to superiority of neural network method compared with Bayesian classifier for classification and recognition rate. According to this result, we selected back-propagation neural network as classification and recognition method about the system of SWP stability Estimation[2]. Through this process, we proved efficiency on the system of SWP stability Estimation, and constructed on the base of the system of SWP stability Estimation for the application in industrial fields.

Abstract: Indium-zinc oxide (IZO), with Zn/(Zn+In)=0.33 - 0.78, films were deposited by the sol-gel method. Effects of Zn/(Zn+In) atomic ratio and annealing temperature on the structural, electrical and optical properties of IZO thin film were investigated. Films of Zn/(Zn+In)=0.33 prepared at 600°C had the lowest resistivity value, 4.48X10 ^-2 Ω cm (carrier concentration=3.83X 10¹⁸ cm^-3 and mobility=25.54 cm2/Vs), and the structure of these films matched that of Zn₂In₂O₅ film. Average optical transmittances of all films were above 80% in the visible range. The highest average transmittance was observed at Zn/(Zn+In)=0.5, with 86.8% in the visible range.