• Nutrition Research and Practice
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• v.11 no.4
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• pp.290-299
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• 2017

BACKGROUND/OBJECTIVES: Spirulina is a known a functional food related to lipid profiles, immune functions, and antioxidant capacity. Circulating monocyte chemoattractant protein-1 (MCP-1) level is associated with inflammation markers. Single nucleotide polymorphism in the MCP-1 promoter region -2518 have been identified and shown to affect gene transcription. Gene variation may also impact functional food supplementary effects. The current study investigated the interaction of MCP-1 -2518 polymorphism with spirulina supplements on anti-inflammatory capacity in Korean elderly. SUBJECTS/METHODS: After genotyping, healthy elderly subjects (n = 78) were included in a randomized, double blind, and placebo controlled study. Baseline characteristic, body composition, and dietary intake were measured twice (baseline vs. week 16). For 16 weeks, subjects consumed 8 g either spirulina or placebo daily. Plasma MCP-1, interleukin (IL) -2, IL-6, tumor necrosis factor (TNF)-${\alpha}$, complement (C) 3, immunoglobulin (Ig) G, and Ig A concentrations and lymphocyte proliferation rate (LPR) were analyzed as inflammatory markers. RESULTS: In the placebo group with A/A genotype, MCP-1 level was significantly increased, but the spirulina group with A/A genotype was unchanged. IL-2 was significantly increased only in subjects with spirulina supplementation. TNF-${\alpha}$ was significantly reduced in subjects with the G carrier. C3 was significantly increased in the placebo group, particularly when A/A increased more than G, but not when spirulina was ingested. LPR was significantly different only in subjects with A/A genotype; there was a significant increase in phytohemagglutinin and lipopolysaccharide induced LPR in the spirulina group. CONCLUSION: In healthy Korean elderly, spirulina supplementation may influence different inflammatory markers by the MCP-1 genotype. These results may be useful for customized dietary guidelines to improve immune function in Koreans.

• Annual Conference of KIPS
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• 2018.10a
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• pp.733-735
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• 2018

최근의 차량 주차관리 시설, 출입통제가 필요한 장소 그리고 도로 방범카메라를 통한 단속 등 다양한 곳에서 차량 번호판 자동 인식 기술들이 활용되고 있다. 하지만 현재 사용되고 있는 LPR(License Plate Recognition) 시스템에는 많은 장비와 비용이 들어간다는 큰 단점이 존재한다. 본 논문에서는 하나의 컴퓨터와 최소의 카메라를 가지고 할 수 있는 기계학습을 통한 영상처리를 제안하려 한다. 먼저 딥러닝 프레임워크 중 하나인 YOLO(You Only Look Once) [4]를 활용하여 자동차의 번호판 부분의 영역을 검출하고 Grayscale를 통해 햇빛 또는 조명 등의 영향을 감소시켜 번호판의 특징을 보존시킨다. 전처리 작업이 끝난 후 번호판에서 숫자를 인식 하는 부분에서는 k-NN(k-Nearest Neighbor) 알고리즘을 사용하였으며 한글 문자 인식부분은 Template Matching을 이용하였다. 제안한 알고리즘을 사용하여 기존 LPR 시스템에서 획득한 차량이미지를 대상으로 시뮬레이션 한 결과 좋은 결과를 얻을 수 있어 향후 연구 방향의 시스템 확장성의 가능성을 발견할 수 있었다.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.509-512
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• 2005

The aim of this work is to design a real-time reusable image enhancement architecture for video signals, based on a spatial processing of the video sequence. The VHDL hardware description language has been used in order to make possible a top-down design methodology. By adding proposed algorithms to the LPR(License Plate Recognition) system, the system is implemented with reliability and safety on a rainy day. Spartan-2E XC2s300E is used as implementation platforms for real-time system.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.601-603
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• 2003

최근에 차량수의 증가로 인하여 교통량이 증가하고 그로 인하여 ITS(Intelligent Transport System)에 대한 관심이 증가하게 되었다. 그 중에서도 LPR system(License Plate Recognition system)은 ITS에서 중요한 역할을 한다. 본 논문에서는 차량의 번호를 인식하기 위해 선행되어야 하는 과정인 대상 차량의 번호판 영역을 추출하고 구성 숫자들을 분리하는 알고리즘을 제안한다. 이 알고리즘은 영상에서 차량의 번호판 영역을 찾는 부분과 번호판의 숫자를 분리하는 부분으로 구성이 되어 있다. 먼저 입력 영상에서 gradient를 구하게 된다. 구해진 gradient에서 차량의 구조와 transition의 횟수를 조사를 통해서 번호판 영역을 찾게 된다. 찾아진 번호판 영역에서 adaptive threshold를 적용하여 숫자들을 분리하게 된다. 실내 주차장 환경에서 촬영된 영상을 대상으로 실험을 수행하고 그 결과를 정리하였다.

• Journal of IKEEE
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• v.18 no.4
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• pp.471-477
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• 2014

In this paper, we propose a low-cost license plate recognition system based on smart cam system using Android. The proposed system consists of a portable device and server. Potable device Hardware consists of ARM Cortex-A9 (S5PV210) processor control unit, a power supply device, wired and wireless communication, input/output unit. We develope Linux kernel and dedicated device driver for WiFi module and camera. The license plate recognition algorithm is consisted of setting candidate plates areas with canny edge detector, extracting license plate number with Labeling, recognizing with template matching, etc. The number that is recognized by the device is transmitted to the remote server via the user mobile phone, and the server re-transfer the vehicle information in the database to the portable device. To verify the utility of the proposed system, user photographs the license plate of any vehicle in the natural environment. Confirming the recognition result, the recognition rate was 95%. The proposed system was suitable for low cost portable license plate recognition device, it enabled the stability of the system when used long time by using the Android operating system.

• Corrosion Science and Technology
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• v.9 no.3
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• pp.137-141
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• 2010

Sodium nitrite is widely used as one of the popular corrosion inhibitors for the protection of ferrous metal in closed cooling water system, such as a diesel engine and a chiller. The optimum treatment conditions are studied through laboratory tests using linear polarization resistance (LPR) technique. Corrosion rate of the carbon steel electrode could be maintained less than $2.5{\times}10^{-3}$ mmpy in the test condition of 500 ppm as ${NO_2}^-$, 200 ppm as $Cl^-$, $70^{\circ}C$ and pH 6.8. The pH control is confirmed not to be an important factor in the protection of carbon steel by sodium nitrite inhibitor. The addition of tolyltriazole was needed for the protection of the copper alloy in the sodium nitrite treatment system.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.361-368
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• 2014

The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.108-110
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• 2004

Automatic license plate recognition (LPR) is one of the critical techniques of the intelligent transportation system (ITS), in which license plate location plays an important role. In this paper, through surveying the international existing techniques, a new method for locating license plate is proposed: utilize row scan method to locate up and down boundary of the plate; and based on the location of up and down boundary, take advantage of the feature of plate area to locate left and right boundary of the plate. The tests of using the proposed algorithms have been conducted. The experimental results show that the proposed approaches are reasonable and accurate.

• Corrosion Science and Technology
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• v.3 no.3
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• pp.118-126
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• 2004

The correlation between sensor output and corrosion rate of reinforcing steel was evaluated by laboratory electrochemical tests in saturated $Ca(OH)_2$ with 3.5 wt.% NaCl and confirmed in concrete environment. In this paper, two types of electrochemical probes were developed: galvanic cells containing of steel/copper and steel/stainless steel couples. Potentiodynamic test, weight loss measurement, monitoring of open-circuit potential, linear polarization resistance (LPR) measurement and electrochemical impedance spectroscopy (EIS) were used to evaluate the corrosion behavior of steel bar embedded in concrete. Also, galvanic current measurements were conducted to obtain the charge of sensor embedded in concrete. In this study, steel/copper and steel/stainless steel sensors showed a good correlation in simulated concrete solution between sensor output and corrosion rate of steel bar. However, there was no linear relationship between steel/stainless steel sensor output and corrosion rate of steel bar in concrete environment due to the low galvanic current output. Thus, steel/copper sensor is a reliable corrosion monitoring sensor system which can detect corrosion rate of reinforcing steel in concrete structures.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.103-113
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• 2019

License plate recognition camera is dedicated device designed for acquiring images of the target vehicle for recognizing letters and numbers in a license plate. Mostly, it is used as a part of the system combined with server and image analysis module rather than as a single use. However, building a system for vehicle license plate recognition is costly because it is required to construct a facility with a server providing the management and analysis of the captured images and an image analysis module providing the extraction of numbers and characters and recognition of the vehicle's plate. In this study, we would like to develop an embedded type convergent camera (Edge Base) which can expand the function of the camera to not only the license plate recognition but also the security CCTV function together and to perform two functions within the camera. This embedded type convergence camera equipped with a high resolution 4K IP camera for clear image acquisition and fast data transmission extracted license plate area by applying YOLO, a deep learning software for multi object recognition based on open source neural network algorithm and detected number and characters of the plate and verified the detection accuracy and recognition accuracy and confirmed that this camera can perform CCTV security function and vehicle number plate recognition function successfully.