• Structural Engineering and Mechanics
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• v.39 no.1
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• pp.93-113
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• 2011

The explicit nonlinear dynamic relaxation method (DRM) is applied to the nonlinear geodesic shape finding analysis by introducing fictional tensioned 'strings' along the desired seams with a three or four-node membrane element. A number of results from the numerical example for the nonlinear geodesic shape finding and patterning analysis are obtained by the proposed method to demonstrate the accuracy and efficiency of the developed method. Therefore, the proposed geodesic shape finding algorithm may improve the applicability of a four-node membrane element to membrane structural engineering and design analysis simultaneously for the shape finding, stress, and patterning analysis.

• Journal of Korean Association for Spatial Structures
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• v.21 no.4
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• pp.49-56
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• 2021

This study aims to develop a form-finding algorithm for a single-layered pneumatic membrane. The initial shape of this pneumatic membrane, which is an air-supported type pneumatic membrane, is to find a state in which a given initial tension and internal pneumatic pressure are in equilibrium. The algorithm developed to satisfy these conditions is that a nonlinear optimization problem based on the force method considering the deformed shape is formulated, and, it's able to find the shape by iteratively repeating the process of obtaining a solution of the governing equations. An computational technique based on the Gauss-Newton method was used as a method for obtaining solutions of nonlinear equations. In order to verify the validity of the proposed form-finding algorithm, a single-curvature pneumatic membrane example and a double-curvature air pneumatic membrane example were adopted, respectively. In the results of these examples, it was possible to well observe the step-by-step convergence process of the shape of the pneumatic membrane, and it was also possible to confirm the change in shape according to the air pressure. In addition, the calculation results of the shape and internal force after deformation due to initial tension, air pressure, and self-weight were obtained.

• Journal of Korean Society of Steel Construction
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• v.22 no.1
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• pp.33-42
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• 2010

Patterning with a geodesic line is essential for economical or efficient usage of membrane materialsin fabric tension membrane structural engineering and analysis. The numerical algorithm to determine the geodesic line for membrane structures is generally classified into two. The first algorithm finds a non-linear shape using a fictitious geodesic element with an initial pre-stress, and the other algorithm is the geodesic line cutting or searching algorithm for arbitrarily curved 3D surface shapes. These two algorithms are still being used only for the three-node plane stress membrane element, and not for the four-node element. The lack of a numerical algorithm for geodesic lines with four-node membrane elements is the main reason for the infrequent use of the four-node membrane element in membrane structural engineering and design. In this paper, a modified numerical algorithm is proposed for the generation of a geodesic line that can be applied to three- or four-node elements at the same time. The explicit non-linear static Dynamic Relaxation Method (DRM) was applied to the non-linear geodesic shape-finding analysis by introducing the fictitiously tensioned 'strings' along the desired seams with the three- or four-node membrane element. The proposed algorithm was used for the numerical example for the non-linear geodesic shape-finding and patterning analysis to demonstrate the accuracy and efficiency, and thus, the potential, of the algorithm. The proposed geodesic shape-finding algorithm may improve the applicability of the four-node membrane element for membrane structural engineering and design analysis simultaneously in terms of the shape-finding analysis, the stress analysis, and the patterning analysis.

• Journal of Korean Association for Spatial Structures
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• v.20 no.4
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• pp.35-44
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• 2020

In the study, a shape finding procedure for the tensegrity system model inspired by the movement pattern of animal backbone was presented. The proposed system is allowing a dynamic movement by introducing the concept of "saddle" for the variable tensegrity structure. Mathematical process and an algorithm for movable tensegrity to specified points were established. Several examples have applied with in established shape finding analysis procedure. The final tensegrity structures were determined well to a object shape.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.497-502
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• 2016

Shape Contexts Recognition(SCR) is a technology recognizing shapes such as figures and objects, greatly supporting technologies such as character recognition, motion recognition, facial recognition, and situational recognition. However, generally SCR makes histograms for all contours and maps the extracted contours one to one to compare Shape A and B, which leads to slow progress speed. Thus, this paper has made simple yet more effective algorithm with optimized contour, finding the outlines according to shape figures and using the improved Douglas-Peucker algorithm and Harris corner detector. With this improved method, progress speed is recognized as faster.

• The Journal of Korea Robotics Society
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• v.5 no.2
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• pp.152-159
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• 2010

Finding a head of a person in a scene is very important for taking a well composed picture by a robot photographer because it depends on the position of the head. So in this paper, we propose a robust head tracking algorithm using a hybrid of an omega shape tracker and local binary pattern (LBP) AdaBoost face detector for the robot photographer to take a fine picture automatically. Face detection algorithms have good performance in terms of finding frontal faces, but it is not the same for rotated faces. In addition, when the face is occluded by a hat or hands, it has a hard time finding the face. In order to solve this problem, the omega shape tracker based on active shape model (ASM) is presented. The omega shape tracker is robust to occlusion and illuminationchange. However, whenthe environment is dynamic,such as when people move fast and when there is a complex background, its performance is unsatisfactory. Therefore, a method combining the face detection algorithm and the omega shape tracker by probabilistic method using histograms of oriented gradient (HOG) descriptor is proposed in this paper, in order to robustly find human head. A robot photographer was also implemented to abide by the 'rule of thirds' and to take photos when people smile.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.202-205
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• 2000

In this paper we propose an algorithm that detects, tracks a moving object, and classify whether it is human from the video clip captured under the fixed video camera. It detects the outline of the moving object by finding out the local maximum points of the modulus image, which is the magnitude of the motion vectors. It also estimates the size and the center of the moving object. When the object is detected, the algorithm discriminates whether it is human by segmenting the face. It is segmented by searching the elliptic shape using Hough transform and grouping the skin color region within the elliptic shape.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.11a
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• pp.309-313
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• 2004

This paper presents an algorithm of detecting changed intervals with step-type shape in motor's speed response data. The proposed method is composed of 4 parts such as noise filtering, decision making of reference value's change, finding entrance point of steady state and detecting changed intervals. According to simulation results for three cases, we see that changed intervals can be found well.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.3
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• pp.98-108
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• 2005

The assembly line balancing problem has been focused by many research works because the efficient management of the assembly line might influence not only the quality of the products but also the working conditions for the workers. This paper deals with U-shape mixed-model assembly line balancing and considers both the processing time and the physical workloads. We suggest the goal programming approach for this situation and to overcome some difficulties of finding optimal solution, we adopt the genetic algorithm that is one of the most promising solution techniques. We tested several test problems and present the results that indicate some improvement for the line balancing as well as the stable performance of the algorithm.

• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.665-675
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• 2007

The morphological change of ECG is the important diagnostic parameter to finding the malfunction of a heart. Generally ST segment deviation is concerned with myocardial abnormality. The aim of this study is to detect the change of ST in shape using a polynomial approximation method and the reference ST type. The developed algorithm consists of feature point detection, ST level detection and ST shape classification. The detection of QRS complex is accomplished using it's the morphological characteristics such as the steep slope and high amplitude. The developed algorithm detects the ST level change, and then classifies the ST shape type using the polynomial approximation. The algorithm finds the least squares curve for the data between S wave and T wave in ECG. This curve is used for the classification of the ST shapes. ST type is classified by comparing the slopes of the specified points between the reference ST set and the least square curve. Through the result from the developed algorithm, we can know when the ST level change occurs and what the ST shape type is.