• Korean Journal of Head & Neck Oncology
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• v.26 no.2
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• pp.204-211
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• 2010

Background and Objectives : Boundary detection and drawing are essential in 3D reconstruction of neck mass. Manual tracing methods are popular for drawing head and neck tumor. To improve manual tracing, circular boundaries overlapping was tried. Materials and Methods : Twenty patients with neck tumors were recruited for study. Representative frames were examined for shapes of outline. They were all single closed curves. Circular boundaries were added to fill the outlines of the tumors. Inserted circles were merged to form single closed curves(Circular boundary overlapping, CBO). After surface rendering, 3 dimensional images with volumes and area data were made. Same procedures were performed with manual tracing from same cases. 3D images were compared with surgical photographs of tumors for shape similarity by 2 doctors. All data were evaluated with Mann-Whitney test(p<0.05). Results : Shapes of boundaries from CBO were similar with boundaries from manual tracing. Tumor outlines could be filled with multiple circular boundaries., While both boundary tracing gave same results in small tumors, the bigger tumors showed different data. Two raters gave the similar high scores for both manual and CBO methods. Conclusion : Circular boundary overlapping is time saver in 3 dimensional reconstruction of CT images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.1-8
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• 2000

This paper describes an algorithm for semantic video object tracking using semi automatic method. In the semi automatic method, a user specifies an object of interest at the first frame and then the specified object is to be tracked in the remaining frames. The proposed algorithm consists of three steps: object boundary projection, uncertain area extraction, and boundary refinement. The object boundary is projected from the previous frame to the current frame using the motion estimation. And uncertain areas are extracted via two modules: Me error-test and color similarity test. Then, from extracted uncertain areas, the exact object boundary is obtained by boundary refinement. The simulation results show that the proposed video object extraction method provides efficient tracking results for various video sequences compared to the previous methods.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.263-272
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• 2007

This paper proposes a skeleton-based hierarchical shape description scheme, called a skeleton tree, for accurate shape-based image retrieval. A skeleton tree represents an object shape as a hierarchical tree where high-level nodes describe parts of coarse trunk regions and low-level nodes describe fine details of boundary regions. Each node refines the shape of its parent node. Most of the noise disturbances are limited to bottom level nodes and the boundary noise is reduced by decreasing weights on the bottom levels. The similarity of two skeleton trees is computed by considering the best match of a skeleton tree to a sub-tree of another skeleton tree. The proposed method uses a hybrid similarity measure by employing both Fourier descriptors and moment invariants in computing the similarity of two skeleton trees. Several experimental results are presented demonstrating the validity of the skeleton tree scheme for the shape description and indexing.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.71-77
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• 2006

Support Vector Machine (SVM) which has roots in a statistical learning theory is a training algorithm based on structural risk minimization. Generally, SVM algorithm uses the kernel for determining a linearly non-separable boundary and classifying the data. But, classical kernels can not apply to effectively the hyperspectral image classification because it measures similarity using vector's dot-product or euclidian distance. So, This paper proposes the spectral similarity kernel to solve this problem. The spectral similariy kernel that calculate both vector's euclidian and angle distance is a local kernel, it can effectively consider a reflectance property of hyperspectral image. For validating our algorithm, SVM which used polynomial kernel, RBF kernel and proposed kernel was applied to land cover classification in Hyperion image. It appears that SVM classifier using spectral similarity kernel has the most outstanding result in qualitative and spatial estimation.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.307-317
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• 2013

The value and functionality of boundary barriers in rural villages have been neglected in the aspects as the buffer zone(boundary barrier) that links between the inside space(housing site) and the outside space(road). On this understanding, this study evaluated conservation value, economical efficiency and durability by the types and materials of the boundary barriers in rural village through Multi-attribute Decision Making. By applying to the current situations of boundary barriers on total 21 case study villages, each factor value was measured. And using Matrix Analysis Technique, the boundary barriers are classified into 4 types and the improvement ways for each type were proposed. As a result, the durability of boundary barriers in rural villages showed similarity value(more than 0.85 out of 1). But economical efficiency of those was low(less than 0.5 out of 1) and those functionalities were very lacking(about 0.3 out of 1). In the conclusion, the maintenance of boundary barriers in rural villages requires the policy that is able to complement conservation value and economical efficiency and is proper to the characteristic of each village. These renewable policies would contribute to the increase of the value of rural amenity as well as creation of economical and social value.

• Structural Engineering and Mechanics
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• v.14 no.1
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• pp.99-118
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• 2002

The scaled-boundary finite element method is a novel semi-analytical technique, combining the advantages of the finite element and the boundary element methods with unique properties of its own. The method works by weakening the governing differential equations in one coordinate direction through the introduction of shape functions, then solving the weakened equations analytically in the other (radial) coordinate direction. These coordinate directions are defined by the geometry of the domain and a scaling centre. This paper presents a general development of the scaled boundary finite-element method for two-dimensional problems where two boundaries of the solution domain are similar. Unlike three-dimensional and axisymmetric problems of the same type, the use of logarithmic solutions of the weakened differential equations is found to be necessary. The accuracy and efficiency of the procedure is demonstrated through two examples. The first of these examples uses the standard finite element method to provide a comparable solution, while the second combines both solution techniques in a single analysis. One significant application of the new technique is the generation of transition super-elements requiring few degrees of freedom that can connect two regions of vastly different levels of discretisation.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.47-60
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• 2012

Video data comes in the form of the unstructured and the complex structure. As the importance of efficient management and retrieval for video data increases, studies on the video parsing based on the visual features contained in the video contents are researched to reconstruct video data as the meaningful structure. The early studies on video parsing are focused on splitting video data into shots, but detecting the shot boundary defined with the physical boundary does not cosider the semantic association of video data. Recently, studies on structuralizing video shots having the semantic association to the video scene defined with the semantic boundary by utilizing clustering methods are actively progressed. Previous studies on detecting the video scene try to detect video scenes by utilizing clustering algorithms based on the similarity measure between video shots mainly depended on color features. However, the correct identification of a video shot or scene and the detection of the gradual transitions such as dissolve, fade and wipe are difficult because color features of video data contain a noise and are abruptly changed due to the intervention of an unexpected object. In this paper, to solve these problems, we propose the Scene Detector by using Color histogram, corner Edge and Object color histogram (SDCEO) that clusters similar shots organizing same event based on visual features including the color histogram, the corner edge and the object color histogram to detect video scenes. The SDCEO is worthy of notice in a sense that it uses the edge feature with the color feature, and as a result, it effectively detects the gradual transitions as well as the abrupt transitions. The SDCEO consists of the Shot Bound Identifier and the Video Scene Detector. The Shot Bound Identifier is comprised of the Color Histogram Analysis step and the Corner Edge Analysis step. In the Color Histogram Analysis step, SDCEO uses the color histogram feature to organizing shot boundaries. The color histogram, recording the percentage of each quantized color among all pixels in a frame, are chosen for their good performance, as also reported in other work of content-based image and video analysis. To organize shot boundaries, SDCEO joins associated sequential frames into shot boundaries by measuring the similarity of the color histogram between frames. In the Corner Edge Analysis step, SDCEO identifies the final shot boundaries by using the corner edge feature. SDCEO detect associated shot boundaries comparing the corner edge feature between the last frame of previous shot boundary and the first frame of next shot boundary. In the Key-frame Extraction step, SDCEO compares each frame with all frames and measures the similarity by using histogram euclidean distance, and then select the frame the most similar with all frames contained in same shot boundary as the key-frame. Video Scene Detector clusters associated shots organizing same event by utilizing the hierarchical agglomerative clustering method based on the visual features including the color histogram and the object color histogram. After detecting video scenes, SDCEO organizes final video scene by repetitive clustering until the simiarity distance between shot boundaries less than the threshold h. In this paper, we construct the prototype of SDCEO and experiments are carried out with the baseline data that are manually constructed, and the experimental results that the precision of shot boundary detection is 93.3% and the precision of video scene detection is 83.3% are satisfactory.

• Transactions of the Korean Society of Mechanical Engineers
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• v.3 no.3
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• pp.91-97
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• 1979

Boundary layer equations (partial differential equations) can be transformed to ordinary diffential equations with constant coeffieients in terms of similarity transformed to ordinary differential equations with constant coeffieients in terms of similarity transformations in the heat tranfer analysis on the surface of any axiaymmetric boiles. The azimuth functions can not be uniquely determined because of the singular behavior at the stagnation point(X=0.deg.).In spite of the azimuth functions behaving singularly, many of researchers have analyzed the heat transfer problem on a horizontal chlinder or a sphere, supposing the set of solutions( $H_{1}$ & G$_{1}$) of being yieled from the simple differential equation to be unique solution of therazimuth functions. In order to ascertain whether mathematical incompatibility as mentioned above can be admitted in the viewpoint of enginerring or not, condensation heat transfer coefficients on a sphere are computed for all azimuth functions( $H_{1}$ G$_{1}$ & $H_{2}$ G$_{2}$) and comparisons with the experimental result are discussed.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.1
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• pp.71-81
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• 2017

In this study, a series of full-scale extrapolation procedures based on the Granville's similarity scaling method, which was employed by Schultz (2007), is modified and then applied to compare the resistance performance between two different anti-fouling coatings. As an analysis example, the low frictional AF coating based on a novel skin-friction reducing polymer named FDR-SPC (Frictional Drag Reduction Self-Polishing Copolymer), which had been invented by the present author, is employed. The low frictional coating, which gives 25.4% skin frictional reduction in lab test, is estimated to give 18.2% total resistance reduction for a 176k DWT bulk carrier.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.225-228
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• 2022

본 논문에서는 의미적 유사도 기반의 장면 분할 방법을 제안한다. 이 방법은 의미적 접근을 통해 기존 연구에서 가졌던 한계를 극복하고 정확한 장면 분할이 가능할 것으로 기대한다. 의미적 유사도 비교를 Class 종류 비교, Class별 객체의 개수 비교, 샷 간의 Histogram비교, 객체의 관심영역(ROI) Histogram비교 총 4가지 규칙으로 정의했고 이때 도출된 4가지 유사도는 전처리를 거쳐 종합 유사도를 계산한다. 또한 의미적 접근을 통해 연속되는 Shot의 유사도를 비교하고 기준값에 따라 Shot을 묶어서 최종적으로 의미적 유사도(Semantic Similarity)에 기반한 장면의 경계(Scene Boundary) 분할 방법을 제시한다.