• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.71-72
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• 2010

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1115-1121
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• 2012

This paper proposes a method to extract accurate plane of an object in unstructured environment for a humanoid robot by using a laser scanner. By panning and tilting 2D laser scanner installed on the head of a humanoid robot, 3D depth map of unstructured environment is generated. After generating the 3D depth map around a robot, the proposed plane extraction method is applied to the 3D depth map. By using the hierarchical clustering method, points on the same plane are extracted from the point cloud in the 3D depth map. After segmenting the plane from the point cloud, dimensions of the planes are calculated. The accuracy of the extracted plane is evaluated with experimental results, which show the effectiveness of the proposed method to extract planes around a humanoid robot in unstructured environment.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05c
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• pp.170-176
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• 2002

In this papers, we proposed the feature extraction method due to partial discharge type of transformers. For wavelet transform, Daubechie's filter is used, we can obtain wavelet coefficients which is used to extract feature of statistical parameters (maximum value, average value, dispersion, skewness, kurtosis) about acoustic emission signal generated from each partial discharge type. The defects which could occur in a transformer were simulated by using needle-plane electrode, IEC electrode and Void electrode. Also, these coefficients are used to identify signal of partial discharge type electrode fault in transformer. As a result, from compare of acoustic emission amplitude and acoustic average value, we are obtained results of IEC electrode> Void electrode> Needle-Plane electrode. otherwise, In case of skewness and kurtosis, we are obtained results of Needle-Plane electrode electrode> Void electrode> IEC electrode.

• Journal of Dental Rehabilitation and Applied Science
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• v.16 no.2
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• pp.93-104
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• 2000

Orthodontic treatment in conjunction with second-molar extraction has been a controversial issue among orthodontists over many decades. The aim of this study was to investigate the treatment effects of upper second molar extraction cases. The sample included 19 upper second molar extraction orthodontic cases(ten Angle's Class I's and nine Class II's, average age=13Y 6M) cared at Kyung-Hee University Department of Orthodontics. Lateral cephalometric radiographs were taken before and immediately after treatment. Seventy-nine points were digitized on each cephalogram and 38 cephalometric parameters were computed comprising 22 angular measurements, 13 linear measurements, and 3 facial proportions. The data obtained from each malocclusion group were analyzed by paired t-test. The statistical results disclosed that there was no significant change in skeletal pattern after treatment except for that accountable by growth while there was statistically significant change in dentoalveolar and soft tissue patterns. There were no significant changes in Bjork sum, posterior facial height /anterior facial height and lower anterior facial height /anterior facial height. No significant changes in anteroposterior position of maxilla and palatal plane were manifested. Although facial axis and lower facial height was slightly increased and the mandible was rotated backward and downward, there was no remarkable change in the mandibular plane. There were statistically significant changes in distal movement of upper first molar, molar key correction and overjet reduction while there was no change in the occlusal plane. The upper lip was slightly retracted simultaneously with slight increase in nasolabial angle. These results signify that distalization of upper dentition with the second molar extraction does change occlusal relationship without gross modifications in the craniofacial skeletal configurationson. Henceforth the second molar extracted would be recommended to treat severe anterior crowding and protrusion with minor skeletal discrepancy.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.37.4-37
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• 2002

$\textbullet$ Feature extraction method for robot application $\textbullet$ Using ultrasonic sensor arrays $\textbullet$ Differentiate the target as plane, corner and edge $\textbullet$ Neural network approach

• The korean journal of orthodontics
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• v.25 no.3 s.50
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• pp.299-310
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• 1995

The purpose of this study is to know about the positional change of second molar when orthodontic treatment is performed. To know about it, we andlysed cephalogram pre. and post treatment for 54 adult patients who werefinished orthodontic treatment by banding to the first molar and classify them into 4 groups Class I extraction group 15, Class I nonextraction group 12, Class II group 13, class Class III group 14. The following conclusions were obtained : 1. In the extraction group of Class I , mandibular second molar showed less extrusion and mon distal inclination than first moarl. But maxillary second molar showed more or less extrusive and mesial inclination to much the same degree of first molar. 2. Inthe non-extractio group of Class I, mandibular second molar in intrusive to first molar, it showed smilar distal inclination to first molar. But maxillary second molar is extrusive similarly to first molar. 3. In the group of Class II , mandibular second molar is less extrusive than first molar and maxillary second molar is more extrusive than first molar. 4. In the group of Class III, mandibular second molar showed similar extrusion to first molar and more distal inclination than first molar. But maxillary second molar showed less extrusion than first molar. 5. A comparision of the positional change of second molar among groups : The change of distance from FH plane to funcation point of maxillary second molar is the difference between Class I extraction group and Class II group, Class I extraction group and Class III group. The change of maxillary second molar to palatal plane and occlusal plane is the difference between Class I extraction group and Class III group. And the change of distance from mandibular plan to furcation point of mandibular second molar is difference between Class I extraction group and non-extraction group, Class I non-extraction group and Class II group, Class I non-extraction group and Class III group. But the change of angle of mandibular second molar to mandibular plane and occlusal plane is make no difference in among groups.

• The korean journal of orthodontics
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• v.25 no.1 s.48
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• pp.111-128
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• 1995

This study was investigated to assess the difference of facial height and occlusal plane inclination between pre- and post-treatment in Class I malocclusion group The subjects consisted of 35 extraction patients and 30 nonextraction patient,;, and was subdivided into Group I(overbite<0mm), Group II(04mm) in reference to overbite, and adolescent group and adult group in reference to age. Lateral cephalogram was taken with standard method, traced, and digitized for each subject. The computerized statistical analysis was carried out with SAS program The results wolf as follows. 1. In both groups of extraction and nonextraction group the anterior facial height increased after orthodontic treatment but there was no significant difference(p>0.05) between each goup. 2. There was no statstical significance in change of occlusal plane inclination in adolescent group, but significant difference(p<0.05) among three subgroup in adult group. 3. In adolescent-extraction and adolescent-nonextraction group there was significant increase of anterior facial height and posterior facial height, and was superior to adult groups in posterior facial height increment. 4 In all groups upper and lower molars were uprighted to occlusal plane. This had statistically significant effect.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.5
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• pp.505-512
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• 2008

The 3D Hough transformation is the one of the most powerful and popular algorithm for extracting plane parameters from LiDAR data. However, there are some problems when extracting building roof plane using 3D Hough transformation. This paper explains possible problems and solution for extracting roof plane. The algorithm defines peak plane, exact plane, and LESS plane for extracting accurate plane parameters in the accumulator of the 3D Hough transformation. The peak plane is the plane which is represented by peak in the accumulator. The exact plane is the plane which is represented by the accumulator cell which is closest to the actual plane. The LESS plane can be calculated from all LiDAR points in the exact plane by using least-square adjustment. Test results show that proposed algorithm can extracts building roof plane very accurately.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.22-30
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• 2011

Plane detection is very important information for mission-critical of robot in 3D environment. A representative method of plane detection is Hough-transformation. Hough-transformation is robust to noise and makes the accurate plane detection possible. But it demands excessive memory and takes too much processing time. Iterative randomized Hough-transformation has been proposed to overcome these shortcomings. This method doesn't vote all data. It votes only one value of the randomly selected data into the Hough parameter space. This value calculated the value of the parameter of the shape that we want to extract. In Hough parameters space, it is possible to detect accurate plane through detection of repetitive maximum value. A common problem in these methods is that it requires too much computational cost and large number of memory space to find the distribution of mixed multiple planes in parameter space. In this paper, we detect multiple planes only via data sampling using Self Organizing Map method. It does not use conventional methods that include transforming to Hough parameter space, voting and repetitive plane extraction. And it improves the reliability of plane detection through division area searching and planarity evaluation. The proposed method is more accurate and faster than the conventional methods which is demonstrated the experiments in various conditions.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.2
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• pp.59-64
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• 2004

Most features of nature and phenomena we encounter in many branches of science are inherently very irregular and have fractal aspects. Thus the analysis of them with the traditional methods such as a differential operator may result in their ill-posed problems. To settle these problems, one may use several type of mean filters which smooth the input signal. However when a given function or data are complex in their nature, there may be loss of some original information during these process. In this paper, we utilized the tangent plane method instead of mean filters for the purpose of less loss of information and more smoothness. After then we attempt to take more accurate edges for the irregular image on the basis of the Otzu threshold. Finally we introduce the effective edge extracting method which use the fractal dimension representing the complexity of the given image.