• 소성∙가공
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• 제11권7호
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• pp.620-627
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• 2002

The purpose of this paper is the development of an automated measurement system for micro spring based on the digital image processing technique. This micro spring can be used in various engineering applications such as filament, load bearing springs, hard disk suspension and many others. Main functionality of the micro spring inspection system is to measure the representative pitch of the micro spring. The derivative operators are used for edge detection in gray level image. Measurement system developed in this paper consisted of new auto feeding mechanism to take advantage of air pressure. In the process of development of the micro spring inspection system based on the image processing and analysis, strong background technology and know-how have been accumulated to measure micro mechanical parts.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.417-420
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• 2004

Caenorhabditis (C) elegans is often used in genetic analysis in neuroscience because its simple organism; an adult hermaphrodite contains only 302 neuron. So the worm is often used to study of cancer, alzheimer disease, aging, etc. To analysis mutant type of the worm, an experienced observer was able to subjectively before, but requirements for objective analysis are now increasing. For this reason, we use automated tracking systems to extract global movement coordinate of the worm. In this paper, we extract features, which are related on reversal and movement of the worm. Using these features, we quantitatively analysis 6 type mutant by movement and reversal characteristic.

• 한국콘텐츠학회논문지
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• 제9권11호
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• pp.80-89
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• 2009

유비쿼터스 컴퓨팅이 발전하면서, 스마트 홈 환경에서 개인화 서비스의 중요성이 부각되고 있다. 본 논문에서는 음성인식을 이용한 상황정보 기반의 스마트 홈 개인화 서비스를 제안한다. 제안된 서비스에서는 OSGi 프레임워크 기반의 서비스 이동 관리자, 서비스 관리자, 음성인식 관리자, 위치 관리자로 구성된다. 스마트 홈 공간을 정의하고 정의된 공간에서 가장 많이 사용하는 유닛의 명령어 및 센서 정보, 사용자 정보를 상황정보로 구성하였다. 특히, 본 서비스는 음성인식의 훈련모델과 패턴매칭 분석을 통하여 RFID로 구별하기 어려운 동일한 공간의 사용자들을 구별하고 상황 및 개인 정보를 사용하여 스마트 홈 어플리케이션의 개인화 서비스를 지원한다. 실험 결과, 동일 공간에서 사용자 확인을 통한 OSGi 기반의 자동화되고 개인화 된 서비스가 가능함을 확인하였다.

• 수면정신생리
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• 제26권1호
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• pp.16-22
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• 2019

목 적: 본 연구의 목적은 청소년에서 전산화 신경인지 검사를 이용하여 수면 부족과 시공간 기억력 사이의 연관성에 대해 알아보는 것이다. 방 법: 심각한 내외과적 질환이 없는 만 16세에서 만 18세 사이의 고등학생 103명(남자 26명, 여자 77명, 평균 연령 $17.11{\pm}0.50$세)이 연구에 참여하였다. 모든 대상자에게 주중 총 수면 시간과 주말 총 수면 시간에 대한 자가 보고식 설문지를 작성하도록 하였다. 주간 졸음과 우울 증상의 정도를 평가하기 위해 엡워스 졸음 척도와 벡 우울 척도를 자가 작성하도록 하였다. 시공간 기억을 평가하기 위해 캠브리지 신경정신검사 자동화 총집의 7개 하부 검사를 실시하였다. 결 과: 나이와 성별, 엡워스 졸음 척도, 벡 우울 척도를 보정한 상관 분석의 결과는 다음과 같다. 주말 총 수면 시간이 길수록 지연 표본 대응(r = -0.312, p = 0.002)와 패턴 재인 기억의 즉각 회상(r = -0.225, p = 0.025)의 정답률이 낮았다. 주말 수면 보충 시간이 길수록 지연 표본 대응(r = -0.236, p = 0.018)과 패턴 재인 기억의 즉각 회상(r = -0.220, p = 0.029), 패턴 재인 기억의 지연 회상(r = -0.211, p = 0.036)의 정답률을 낮았다. 결 론: 주중 수면 부족를 반영하는 주말 수면 보충 시간이 길수록 시각 기억의 지연 회상에서 낮은 수행도를 보였다. 본 연구의 결과는 청소년기에 수면 부족이 심할수록 청소년의 시공간 기억력이 저하될 수 있다는 것을 시사한다.

• IEIE Transactions on Smart Processing and Computing
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• 제6권1호
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• pp.21-26
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• 2017

In this paper, we suggest an automated sleep scoring method using machine learning algorithms on accelerometer data from a wristband device. For an experiment, 36 subjects slept for about eight hours while polysomnography (PSG) data and accelerometer data were simultaneously recorded. After the experiments, the recorded signals from the subjects were preprocessed, and significant features for sleep stages were extracted. The extracted features were classified into each sleep stage using five machine learning algorithms. For validation of our approach, the obtained results were compared with PSG scoring results evaluated by sleep clinicians. Both accuracy and specificity yielded over 90 percent, and sensitivity was between 50 and 80 percent. In order to investigate the relevance between features and PSG scoring results, information gains were calculated. As a result, the features that had the lowest and highest information gain were skewness and band energy, respectively. In conclusion, the sleep stages were classified using the top 10 significant features with high information gain.

• Structural Monitoring and Maintenance
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• 제1권1호
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• pp.111-130
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• 2014

The increased use of carbon fiber reinforced polymer (CFRP) in retrofitting reinforced concrete (RC) members has led to the need to develop non-destructive techniques that can monitor and characterize the unique damage mechanisms exhibited by such structural systems. This paper presented the damage characterization results of six CFRP retrofitted RC beam specimens tested in the laboratory and monitored using acoustic emission (AE). The focus of this study was to continuously monitor the change in AE parameters and analyze them both qualitatively and quantitatively, when brittle failure modes such as debonding occur in these beams. Although deterioration of structural integrity was traceable and can be quantified by monitoring the AE data, individual failure mode characteristics could not be identified due to the complexity of the system failure modes. In all, AE was an effective non-destructive monitoring tool that can trace the failure progression in RC beams retrofitted with CFRP. It would be advantageous to isolate signals originating from the CFRP and concrete, leading to a more clear understanding of the progression of the brittle damage mechanism involved in such a structural system. For practical applications, future studies should focus on spectral analysis of AE data from broadband sensors and automated pattern recognition tools to classify and better correlate AE parameters to failure modes observed.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.802-811
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• 1996

Farmers need alternatives for weed control due to the desire to reduce chemicals used in farming. However, conventional mechanical cultivation cannot selectively remove weeds located in the seedline between crop plants and there are no selective heribicides for some crop/weed situations. Since hand labor is costly , an automated weed control system could be feasible. A robotic weed control system can also reduce or eliminate the need for chemicals. Currently no such system exists for removing weeds located in the seedline between crop plants. The goal of this project is to build a real-time , machine vision weed control system that can detect crop and weed locations. remove weeds and thin crop plants. In order to accomplish this objective , a real-time robotic system was developed to identify and locate outdoor plants using machine vision technology, pattern recognition techniques, knowledge-based decision theory, and robotics. The prototype weed control system is composed f a real-time computer vision system, a uniform illumination device, and a precision chemical application system. The prototype system is mounted on the UC Davis Robotic Cultivator , which finds the center of the seedline of crop plants. Field tests showed that the robotic spraying system correctly targeted simulated weeds (metal coins of 2.54 cm diameter) with an average error of 0.78 cm and the standard deviation of 0.62cm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권3호
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• pp.172-179
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• 2015

Because of the development of computers and high-technology applications, all devices that we use have become more intelligent. In recent years, security and surveillance systems have become more complicated as well. Before new technologies included video surveillance systems, security cameras were used only for recording events as they occurred, and a human had to analyze the recorded data. Nowadays, computers are used for video analytics, and video surveillance systems have become more autonomous and automated. The types of security cameras have also changed, and the market offers different kinds of cameras with integrated software. Even though there is a variety of hardware, their capabilities leave a lot to be desired. Therefore, this drawback is trying to compensate by dint of computer program solutions. Image processing is a very important part of video surveillance and security systems. Capturing an image exactly as it appears in the real world is difficult if not impossible. There is always noise to deal with. This is caused by the graininess of the emulsion, low resolution of the camera sensors, motion blur caused by movements and drag, focus problems, depth-of-field issues, or the imperfect nature of the camera lens. This paper reviews image processing, pattern recognition, and image digitization techniques, which will be useful in security services, to analyze bio-images, for image restoration, and for object classification.

• 대한원격탐사학회지
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• 제21권5호
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• pp.383-392
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• 2005

Vegetation classes, especially grass and tree classes, are often confused in classification when conventional spectral pattern recognition techniques are used to classify urban areas. This paper reports on a study to improve the classification results by using an automated process of considering height information in separating urban vegetation classes, specifically tree and grass, using three-band, high-spatial resolution, digital aerial imagery. Height information was derived photogrammetrically from stereo pair imagery using cross correlation image matching to estimate differential parallax for vegetation pixels. A threshold value of differential parallax was used to assess whether the original class was correct. The average increase in overall accuracy for three test stereo pairs was $7.8\%$, and detailed examination showed that pixels reclassified as grass improved the overall accuracy more than pixels reclassified as tree. Visual examination and statistical accuracy assessment of four test areas showed improvement in vegetation classification with the increase in accuracy ranging from $3.7\%\;to\;18.1\%$. Vegetation classification can, in fact, be improved by adding height information to the classification procedure.

• 대한조선학회논문집
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• 제46권6호
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• pp.675-687
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• 2009

In general, the forming process of the curved hull plates consists of sub tasks, such as roll bending, line heating, and triangle heating. In order to complement the automated curved hull forming system, it is necessary to develop an algorithm to classify the curved hull plates of a ship into standard shapes with respect to the techniques of forming task, such as the roll bending, the line heating, and the triangle heating. In this paper, the curved hull plates are classified by four standard shapes and the combination of them, or saddle, convex, flat, cylindrical shape, and the combination of them, that are related to the forming tasks necessary to form the shapes. In preprocessing, the Gaussian curvature and the mean curvature at the mid-point of a mesh of modeling surface by Coon's patch are calculated. Then the nearest neighbor method to classify the input plate type is applied. Tests to verify the developed algorithm with sample plates of a real ship data have been performed.