• ETRI Journal
• /
• v.25 no.4
• /
• pp.253-257
• /
• 2003

This study investigated the photochromic properties and characterization of acetyl-substituted diarylethene (DAMBTF6)-doped fluoroacrylates media for holographic storage. For the rewritable holographic recording media, we prepared photochromic polymer films using an acrylate matrix by simple photocuring methods. Switching light sources from a visible (532 nm) to an ultraviolet (365 nm) produced transparent films that changed from pale yellow to red. Holographic recording was performed on the photochromic films by two interfering collimated plane wave beams. Excitation with a visible or ultraviolet light completely erased the records, and the film was rewritable either by 532 nm laser or by 325 nm laser within 2 seconds. Images were recorded onto a pixelated spatial light modulator with rectangular pixel apertures and reconstructed on the photochromic films to show recovery of the original images with high resolution.

• Journal of the Korean Institute of Telematics and Electronics A
• /
• v.31A no.7
• /
• pp.55-62
• /
• 1994

Interpattern association (IPA) model which the interconnection weight matrix(IWM) is constructed by the association between patterns is effective in similar pattern recognitions. But, if the number of reference patterns is increased, the ability of recognition is decreased. Using a hierarchical recognition algorithm which adopts the tree search strategy, we classified reference patterns into sub-groups by similarity. In IPA model, if input includes random noise we make it converge to reference pattern by means of input includes random noise we make it converge to reference pattern by means of increasing the number of pixels of prohibited state in IWM. In relation to reference patterns the pixel of prohibited state made partially prohibited state of no connected state using which is not included common and feature regions by each reference patterns.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2000.04a
• /
• pp.513-518
• /
• 2000

Surface roughness is one of the most important parameters to estimate quality of products. As this reason. so many studies were carried out through various attempts that were contact or non-contact using computer vision. Even though these efforts, there were few good results in this research. However, texture analysis is making a important role to solve these problems in various fields including universe, aviatiion, living thing and fibers. In this study, texture parameter was obtained by means of position operator according to variation of angle direction and distance. As a result, it was found that surface texture was more effected by direction then distance

• 한국정보디스플레이학회:학술대회논문집
• /
• 2005.07a
• /
• pp.64-67
• /
• 2005

We fabricated an array consisting of organic TFTs(OTFT) and organic LEDs (OLED) in order to demonstrate the possible application of OTFTs to flexible active matrix OLED (AMOLED). The panel was composed of $64{\times}64$ pixels on 4 inch size polyethylene-terephehalate (PET) substrate in which each pixel had one OTFT integrated with one green OLED. The panel successfully displayed some letters and pictures by emitting green light with a luminance of $1.5\;cd/m^2$ at 6 V, which was controlled by the gate voltage of OTFT.

• Proceedings of the Korean Information Science Society Conference
• /
• 2000.10b
• /
• pp.559-561
• /
• 2000

현재 활발한 연구가 진행중인 유전자 분석과 같은 분야에서는 유전자 염기 서열과 같은 대규모 서열 정보들에 대한 효과적인 분석기술을 요구하고 있다. 본 논문은 이러한 서열 정보들 사이의 유사도를 측정하고 분석하는 작업을 효과적으로 지원하기 위한 가시화 도구의 개발을 다룬다. 본 논문에서 사용하는 유사도 가시화 기법은 유전자 정보의 유사도 가시화를 위해 제안되었던 시각적 점-행렬 도면(Graphical Dot-Matrix Plots) 기법을 이용하는데, 이 시각적 점-행렬 도면 기법은 비교 대상이 되는 서열 정보의 크기가 커지면 효율적으로 가시화하기가 힘들다는 단점을 가진다. 본 논문은 시각적 점-행렬 도면 기법의 이러한 문제를 해결하기 위해 서열 정보 유사도 비교 결과를 화면의 해상도 내에서 표현할 수 있도록 데이터를 영역별로 분할하고 각 영역별 일치도를 이분 그래프(bipartite graph)의 최대 평면 일치(maximal planar matching)를 이용하여 결정하고 이를 하나의 화소(pixel)로 출력하는 기법을 제안한다.

• Journal of IKEEE
• /
• v.24 no.3
• /
• pp.719-726
• /
• 2020

A threshold-voltage sensing circuit is proposed to compensate for pixel aging in active matrix organic light-emitting diodes. The proposed threshold-voltage sensing circuit consists of sample-hold (S/H) circuits and a single-ended successive approximation register (SAR) analog-to-digital converter (ADC) with a resolution of 10 bits. To remove a scale down converter of each S/H circuit and a voltage gain amplifier with a signl-to-differentail converter, the middle reference voltage calibration and input range calibration for the single-ended SAR ADC are performed in the capacitor digital-to-analog converter and reference driver. The proposed threshold-voltage sensing circuit is designed by using a 180-nm CMOS process with a supply voltage of 1.8 V. The ENOB and power consimption of the single-ended SAR ADC are 9.425 bit and 2.83 mW, respectively.

• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.885-888
• /
• 2000

Among the previous searching methods, there are the typical methods such as full search and three-step search, etc. Block motion estimation using exhaustive search is too computationally intensive. To apply in practice, recently proposed fast algorithms have been focused on reducing the computational complexity by limiting the number of searching points. According to the reduction of searching points, the quality performance is aggravated in those algorithms. In this paper, We present a fast and efficient search algorithm for block motion estimation that produces better quality performance and less computational time compared with a three-step search (TSS). Previously the proposed Two Step Search Algorithm (TWSS) by Fang-Hsuan Cheng and San-Nan sun is based on the ideas of dithering pattern for pixel decimation using a part of a block pixels for BMA (Block Matching Algorithm) and multi-candidate to compensate quality performance with several locations. This method has good quality performance at slow moving images, but has bad quality performance at fast moving images. To resolve this problem, the proposed algorithm in this paper considers spatial and temporal correlation using neighbor and previous blocks to improve quality performance. This performance uses neighbor motion vectors and previous motion vectors in addition, thus it needs more searching points. To compensate this weakness, the proposed algorithm uses statistical character of dithering matrix. The proposed algorithm is superior to TWSS in quality performance and has similar computational complexity

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.5
• /
• pp.1217-1230
• /
• 2010

The dynamic programming based methods, a kind of globally optimizing stereo matching methods, has the inherent advantage that the occlusion regions can be found during the process. But it also has a serious drawback of streaking phenomena. This paper focuses on reducing the streaking phenomena by adjusting the penalties in calculating the cost matrix and re-establishing the optimal path in the back-tracing process using the boundary information of the image. Especially we use a pixel expansion method in re-establishing the path, which is the results from expanding the pixel information of the ones just left the boundaries. Experiments with the four image pairs provided by the Middlebury site showed the results that the proposed method has the disparity error ratio of 6.33% and the rank is 29, which is competitive to the best method among the previously published dynamic programming based methods.

• The KIPS Transactions:PartB
• /
• v.9B no.5
• /
• pp.643-652
• /
• 2002

This paper proposes an efficient hybrid fixed-point (FP) algorithm for improving performances of the independent component analysis (ICA) based on neural networks. The proposed algorithm is the FP algorithm based on secant method and momentum for ICA. Secant method is applied to improve the separation performance by simplifying the computation process for estimating the root of objective function, which is to minimize the mutual informations of the independent components. The momentum is applied for high-speed convergence by restraining the oscillation if the process of converging to the optimal solution. It can simultaneously achieve a superior properties of the secant method and the momentum. The proposed algorithm has been applied to the composite fingerprints and the images generated by random mixing matrix in the 8 fingerprints of $256\times{256}$-pixel and the 10 images of $512\times{512}$-pixel, respectively. The simulation results show that the proposed algorithm has better performances of the separation speed and rate than those using the FP algorithm based on Newton and secant method. Especially, the secant FP algorithm can be solved the separating performances depending on initial points settings and the nonrealistic learning time for separating the large size images by using the Newton FP algorithm.

• Journal of Internet Computing and Services
• /
• v.22 no.2
• /
• pp.29-39
• /
• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.