• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.403-405
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• 2002

지금까지 TCP 혼잡 제어를 위한 여러 종류의 메커니즘들이 Connection을 적응성 있게 제어하기 위하여 사용되어 왔지만, TCP 혼잡 제어 메커니즘들은 성능상의 여러 문제점을 가지고 있는게 사실이다. 이에 IETF에서는 AQM(Active Queue Management) 메커니즘으로 RED 알고리즘을 권고했다. 그러나 이 또한 상이한 네트워크에서는 파래메터 설정에 따른 문제점이 있어, 네트워크 상황에 적절하게 대응하지 못하는 단점이 있다. 이러한 RED알고리즘의 문제점을 극복하고, 효율성을 개선하기 위해서 SRED, BLUE, FRED, DRED 등 다양한 AQM 메커니즘들이 제시되고 있다. 본 논문에서는 네트워크 트래픽 상황에 따라 적응성을 갖고 Threshold의 변경에 사용되는 패킷 손실율을 구하는데 있어 트래픽을 고려한가중치를 줌으로써 트래픽 상황을 반영하도록 했고, Threshold 설정에 있어 적응성 있는 단계를 통하여 큐 안정성을 개선하도록 하였다. 제안한 알고리즘의 성능 분석은 NS 시뮬레이터를 사용하였고, 제안한 Load Adaptive DRED 알고리즘과 DRED 알고리즘의 버퍼 관리 기법의 성능 비교 분석을 통하여 큐 안정성의 개선된 성능을 확인하였다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.4
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• pp.70-79
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• 2014

In this paper, I propose a method for detection of look-alike offenders by using hidden face information. For extraction of moving objects, PRA matching is used to extract moving components, and brightness changes can be dealt with by an adaptive threshold adjusting in the proposed method. Moving objects extracted in the territory of the face region is extracted using the complexion, facial area, eyes, nose, mouth. The extracted information detected by the presence of these characteristics were likely to help judge a person. Results of the extracted face makes the recognition rate of possible murderers 90% so the usefulness of the proposed method was confirmed.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.65-70
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• 2018

This paper describes a effective information compressor algorithm for the fourth industrial technology. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because input images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a effective information algorithm for variable environment variable under outdoor is proposed, which apply the Kalman Estimation Modeling and adaptive threshold on pixel level to separate foreground and background images from current input image. In results, the better SNR of about 3dB~5dB and about 10%~25% noise distribution rate in the proposed method. Furthermore, it was showed that the moving objects can be detected on various shadows under outdoor and better result Information.

• Journal of the Semiconductor & Display Technology
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• v.10 no.1
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• pp.113-118
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• 2011

This paper proposes computer visual inspection algorithms for PCB defects which are found in a manufacturing process. The proposed method can detect open circuit and short circuit on bare PCB without using any reference images. It performs adaptive threshold processing for the ROI (Region of Interest) of a target image, median filtering to remove noises, and then analyzes connected components of the binary image. In this paper, the connected components of circuit pattern are defined as 6 types. The proposed method classifies the connected components of the target image into 6 types, and determines an unclassified component as a defect of the circuit. The analysis of the original target image detects open circuits, while the analysis of the complement image finds short circuits. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.31-36
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• 2020

Most of the background subtraction algorithms show good performance in static scenes. In the case of dynamic scenes, they frequently cause false alarm to "temporal clutter", a repetitive motion within a certain area. In this paper, we propose a robust technique for the multiple interval pixel sampling (MIS) algorithm to handle highly dynamic scenes. An adaptive threshold scheme is used to suppress false alarms in low-confidence regions. We also utilize multiple background models in the foreground segmentation process to handle repetitive background movements. Experimental results revealed that our approach works well in handling various temporal clutters.

• Journal of the Semiconductor & Display Technology
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• v.9 no.3
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• pp.59-63
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• 2010

This paper proposes computer visual inspection algorithms for various LCD defects which are found in a manufacturing process. Modular vision processing steps are required in order to detect different types of LCD defects. Those key modules include RGB filtering for pixel defects, gray-scale morphological processing and Hough transform for line defects, and adaptive threshold for spot defects. The proposed algorithms can give users detailed information on the type of defects in the LCD panel, the size of defect, and its location. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.69-71
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• 2020

Principal Component Analysis (PCA) is an effective data analysis technique which is commonly used for fault detection on collected data of Wireless Sensor Networks (WSN), However, applying PCA on the whole data make the detection performance low. In this paper, we propose Joint PCA and Adaptive Threshold for Fault Detection (JPATAD). Experimental results on a real dataset show a remarkably higher performance of JPATAD comparing to conventional PCA model in detection of noise which is a popular fault in collected data of sensors.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.389-395
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• 2013

Ethernet is the most widely deployed access network protocol around the world. IEEE 802.3az WG released the EEE standard based on LPI mode to improve the energy efficiency of Ethernet. This paper proposes improved adaptive power control mechanism that can enhance energy-efficiency based on EEE from small Ethernet switch. The feature of this mechanism is that it predicts the traffic characteristic of next cycle by measuring the amount of traffic flowing in during certain period and adjusts the optimal threshold value to relevant traffic load. Performance evaluation results indicate that the proposed mechanism improves overall performance compared to traditional mechanism, since it significantly reduces energy consumption rate, even though average packet delay increases a little bit.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.738-744
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• 2016

In this paper, a robust visual odometry system has been proposed and implemented in an environment with dynamic illumination. Visual odometry is based on stereo images to estimate the distance to an object. It is very difficult to realize a highly accurate and stable estimation because image quality is highly dependent on the illumination, which is a major disadvantage of visual odometry. Therefore, in order to solve the problem of low performance during the feature detection phase that is caused by illumination variations, it is suggested to determine an optimal threshold value in the image binarization and to use an adaptive threshold value for feature detection. A feature point direction and a magnitude of the motion vector that is not uniform are utilized as the features. The performance of feature detection has been improved by the RANSAC algorithm. As a result, the position of a mobile robot has been estimated using the feature points. The experimental results demonstrated that the proposed approach has superior performance against illumination variations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1047-1062
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• 2018

In this paper the problem of massive multiple input multiple output (MIMO) channel estimation with sparsity aware adaptive algorithms for $5^{th}$ generation mobile systems is investigated. These channels are shown to be non-stationary along with being sparse. Non-stationarity is a feature that implies channel taps change with time. Up until now most of the adaptive algorithms that have been presented for channel estimation, have only considered sparsity and very few of them have been tested in non-stationary conditions. Therefore we investigate the performance of several newly proposed sparsity aware algorithms in these conditions and finally propose an enhanced version of RZA-LMS/F algorithm with variable threshold namely VT-RZA-LMS/F. The results show that this algorithm has better performance than all other algorithms for the next generation channel estimation problems, especially when the non-stationarity gets high. Overall, in this paper for the first time, we estimate a non-stationary Rayleigh fading channel with sparsity aware algorithms and show that by increasing non-stationarity, the estimation performance declines.