• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.153-154
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• 2009

• 대한예방의학회:학술대회논문집
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• 2002.10a
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• pp.382-383
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• 2002

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.537-542
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• 1994

본 연구에서는 최근 널리 알려져 있는 vision function들을 Robot controller에 맞게 수정하고, 또한 각종 windows에 익숙한 사용자들이 보다 쉽게 로보트를 다룰 수 있도록 하기 위해, 이러한 기본 기능들을 X-windows 상에서 vision language로 구현하였다. 기존의 기본 motion language, I/O language와 함께 Vision Langeage를 구현함으로써 Vison based Intelligent Robot system을 구축하였다.

• Korean Journal of Bronchoesophagology
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• v.1 no.1
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• pp.168-174
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• 1995

The Plummer - Vinson syndrome Is characteristic difficulty In swallowing, iron defeciency anemia, and upper esophageal or hypopharyngeal web. It is rarely disease in Korea. We have experienced a case of the Plummer-Vinson syndrome, complaining of dysphagia with iron deficient anemia, hypopharyngeal web who was thirty - two years old woman has treated with bullous pemphigoid. The patient has treated sucessfully in the fasion with microsuspentional CO2 Laser for removal of hypopharyngeal web. We report one case with review of the literature.

• Journal of Biosystems Engineering
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• v.24 no.4
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• pp.325-334
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• 1999

The aim of this study was to present a groundwork for development of a sorting system of peeled garlics using machine vision. Images of various garlic samples such as sound, partially defective, discolored, rotten and un-peeled were obtained with a B/W machine vision system. Sorting factors which were based on normalized histogram and statistical analysis(STEPDISC Method) had good separability for various garlic samples. Bayes discriminant function and neural network sorting algorithms were developed with the sample images and were experimented on various garlic samples. It was showed that garlic samples could be classified by sorting algorithm with average sorting accuracies of 88.4% by Bayes discriminant function and 93.2% by neural network.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.787-792
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• 1991

This paper proposes a steering control algorithm for non-holonomic mobile robots. The steering control algorithm is essential to navigate autonomous vehicles which employ comination of the dead reckoning and absolute sensor system such as a machine vison for detecting landmarks in order to estimate the current location of the mobile robot. The proposed algorithm is based on the minimum time BANG-BANG controller and curvature-continuity curve design method. In the BANG-BANG control scheme we introduce velocity/acceleration limiter to avoid any slippage of driving wheels. The proposed scheme is robot-independent and hence can be applied to various kinds of mobile robot or vehicles. To show the effectness of the proposed control algorithm, a series of computer simulations were conducted for two-wheel driven mobile robot.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.3
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• pp.97-107
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• 1997

Image segmentation is teh important step in image infromation extraction for computer vison sytems. Fuzzy clustering methods have been used extensively in color image segmentation. Most analytic fuzzy clustering approaches are derived from the fuzzy c-means (FCM) algorithm. The FCM algorithm uses th eprobabilistic constraint that the memberships of a data point across classes sum to 1. However, the memberships resulting from the FCM do not always correspond to the intuitive concept of degree of belongingor compatibility. moreover, the FCM algorithm has considerable trouble above under noisy environments in the feature space. Recently, the possibilistic C-mean (PCM) for solving growing for color image segmentation. In the PCM, the membersip values may be interpreted as degrees of possibility of the data points belonging to the classes. So, the problems in the FCM can be solved by the PCM. The clustering results by just PCM are not smoothly bounded, and they often have holes. So, the region growing was used as a postprocessing. In our experiments, we illustrated that the proposed method is reasonable than the FCM in noisy enviironments.

• Journal of Microbiology and Biotechnology
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• v.26 no.12
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• pp.2214-2223
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• 2016

Toll-like receptors (TLRs) can recognize conserved molecular patterns and initiate a wide range of innate and adaptive immune responses against invading infectious agents. The aim of this study was to assess the transcript profile of mink TLRs (mTLRs) in mink peripheral blood mononuclear cells (PBMCs) and a range of tissues, and to explore the potential role of mTLRs in the antiviral immune response process. The results indicated that the mTLR partial nucleotide sequences had a high degree of nucleotide identity with ferret sequences (95-98%). Phylogenetic analysis showed that mammalian TLRs grouped into five TLR families, with a closer relationship of the mTLRs with those of ferret than the other mammalian sequences. Moreover, all the mTLRs were ubiquitously expressed in lymphoid organs (spleen and lymph nodes) and PBMCs. Interestingly, the mTLR expression patterns in lung, uterus, and heart showed quite a lot of similarity. Another remarkable observation was the wide expression of mTLR1-3 mRNAs in all tissues. Among the analyzed tissues, skeletal muscle was revealed to being the lowest repertoire of mTLR expression. Additionally, mink PBMCs exposed to the canine distemper virus revealed significant upregulation of mTLR2, mTLR4, mTLR7, and mTLR8 mRNAs, indicating that mTLRs have a role in innate immunity in the mink. Collectively, our results are the first to establish the basic expression patterns of mTLRs and the relationship between mTLRs and a virus, which will contribute to better understanding of the evolution and the functions of mTLRs in the innate immune system in minks.

• Journal of International Society for Simulation Surgery
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• v.3 no.1
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• pp.1-8
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• 2016

In the field of Radiology, the Computer Aided Diagnosis is the technology which gives valuable information for surgical purpose. For its importance, several computer vison methods are processed to obtain useful information of images acquired from the imaging devices such as X-ray, Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). These methods, called pattern recognition, extract features from images and feed them to some machine learning algorithm to find out meaningful patterns. Then the learned machine is then used for exploring patterns from unseen images. The radiologist can therefore easily find the information used for surgical planning or diagnosis of a patient through the Computer Aided Diagnosis. In this paper, we present a review on three widely-used methods applied to Computer Aided Diagnosis. The first one is the image processing methods which enhance meaningful information such as edge and remove the noise. Based on the improved image quality, we explain the second method called segmentation which separates the image into a set of regions. The separated regions such as bone, tissue, organs are then delivered to machine learning algorithms to extract representative information. We expect that this paper gives readers basic knowledges of the Computer Aided Diagnosis and intuition about computer vision methods applied in this area.

• Journal of Animal Science and Technology
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• v.57 no.2
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• pp.6.1-6.5
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• 2015

The objectives of this study were to study the effects of different levels of dietary copper on organ indexes, tissular Cu, Zn and Fe deposition and fur quality of mink in the growing-furring periods. One hundred and five standard dark male mink were randomly assigned to seven groups with the following dietary treatments: basal diet with no supplemental Cu (Control); basal diet supplemented with either 6, 12, 24, 48, 96 and 192 mg/kg Cu from copper sulphate, respectively. The colour intensity scores displayed a linear trend (P = 0.057). The spleen Cu concentrations responded in a linear (P < 0.05) fashion with increasing level of Cu, but copper supplementation did not affect speen concentrations of Fe or Zn. Supplemental dose of Cu linearly increased (P < 0.05) liver Cu and Fe concentrations but did not alter (P > 0.10) liver Zn. Our results indicate that Cu plays an important role in the pigmentation in growing-furring mink, and supplemental dietary Cu in growing-furring mink improve hair colour, and copper has limited effects on liver mineral deposition.