• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.39-43
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• 2019

The gantry of surface mount equipment (SMD) is responsible for transferring parts from the feeder to the PCB. At this time, the moving time of the gantry affects the yield. Therefore, in this paper, we propose the fastest path from the suction to the mounting to reduce the gantry travel time. This path is a case where the velocity in front of the camera is 2m/sec due to the nature of the gantry. Therefore, the trajectory graph of this case was created through simulation and the travel time was calculated. As a result, we can see that the moving time of the moving-motion method proposed in this paper is 20% shorter than the current stop-motion method.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.73-79
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• 2021

Recently, in the field of computer animation, a method for generating motion using deep learning has been studied away from conventional finite-state machines or graph-based methods. The expressiveness of the network required for learning motions is more influenced by the diversity of motion contained in it than by the simple length of motion to be learned. This study aims to find an efficient network structure when the types of motions to be learned are diverse. In this paper, we train and compare three types of networks: basic fully-connected structure, mixture of experts structure that uses multiple fully-connected layers in parallel, recurrent neural network which is widely used to deal with seq2seq, and transformer structure used for sequence-type data processing in the natural language processing field.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.11-23
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• 2011

In this paper, an accurate and fully automatic video object segmentation method is proposed for video conferencing systems in which the real-time performance is required. The proposed method consists of two steps: 1) accurate object extraction on the initial frame, 2) real-time object extraction from the next frame using the result of the first step. Object extraction on the initial frame starts with generating a cumulative edge map obtained from frame differences in the beginning. This is because we can estimate the initial shape of the foreground object from the cumulative motion. This estimated shape is used to assign the seeds for both object and background, which are needed for Graph-Cut segmentation. Once the foreground object is extracted by Graph-Cut segmentation, real-time object extraction is conducted using the extracted object and the double edge map obtained from the difference between two successive frames. Experimental results show that the proposed method is suitable for real-time processing even in VGA resolution videos contrary to previous methods, being a useful tool for immersive video conferencing systems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.33-45
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• 2011

In this paper, we present a method for extracting video objects efficiently by using the modified graph cut algorithm based on contour information. First, we extract objects at the first frame by an automatic object extraction algorithm or the user interaction. To estimate the objects' contours at the current frame, motion information of objects' contour in the previous frame is analyzed. Block-based histogram back-projection is conducted along the estimated contour point. Each color model of objects and background can be generated from back-projection images. The probabilities of links between neighboring pixels are decided by the logarithmic based distance transform map obtained from the estimated contour image. Energy of the graph is defined by predefined color models and logarithmic distance transform map. Finally, the object is extracted by minimizing the energy. Experimental results of various test images show that our algorithm works more accurately than other methods.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.1974-1984
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• 1994

This paper presents a relative coordinate formulation for constrained mechanical systems. Relative coordinates are defined along degrees of freedom of a joint. Graph theoretic analyses are performed to identify topological paths in mechanical systems. Cut constraints are generated to handle closed loop systems. Equations of motion are derived in the Cartesian space and transformed to the joint space. Relative generalized coordinates are corrected to satisfy the cut constraints by a parametrizatiom method.

• Education of Primary School Mathematics
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• v.5 no.2
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• pp.111-119
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• 2001

Over the years, the benefits of instructional manipulatives in mathematics education have been verified by classroom practice and educational research. The purpose of this paper is to introduce how the instructional material, specifically, geoboard could be used and integrated in elementary mathematics classroom in order to develop student's mathematical concepts and process in terms of the following areas: (1) Number '||'&'||' Operation : counting, fraction '||'&'||' additio $n_traction/multiplication (2) Geometry : geometric concepts (3) Geometry : symmetry '||'&'||' motion (4) Measurement : area '||'&'||' perimeter (5) Probability '||'&'||' Statistics : table '||'&'||' graph (6) Pattern : finding patterns Further, future study will continue to foster how manipulatives will enhance children's mathematics knowledge and influence on their mathematics performance.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.10
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• pp.825-834
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• 2000

광학식 동작 포착(optical motion capture)시스템에서 신뢰할만한 3차원 좌표의 획득과 마커의 궤적 추적은 매우 중요한 문제이다. 3차원 좌표를 획득하기 이해서는 다중의 카메라로부터 2차원의 데이터 간의 대응관계를 구해야 한다. 본 논문에서는 각 카메라에서의 3차원 마커들 간의 대응관계를 k-partite graph로 모델링하고, 릴렉세이션 알고리즘을 사용하여 고스트가 제거된 신뢰성있는 클릭을 추출한다. 이를 통해 정확하고 안정적인 3차원의 좌표를 생성할 수 있다. 또한 추출된 3차원 마커의 궤적의 추적을 위해 칼만 필터를 사용한 마커의 예측과 데이터 연계 문제의 해결을 위한 전략을 제안하고. 사라진 마커의 궤적을 유지시키기 위해 다이나믹 모델을 사용한 추적 알고리즘을 제시한다.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.61-67
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• 2023

Gait analysis plays a key role in the research field of exploring and understanding human movement. By quantitatively analyzing the complexity of human movement and the various factors that influence it, it is possible to identify individual gait characteristics and abnormalities. This is especially true for people with walking difficulties or special circumstances, such as amputee, for example. This is because it can help us understand their gait characteristics and provide individualized rehabilitation plans. In this paper, we compare and analyze the differences in ankle joint motion and angles between normal and amputee. In particular, a filtering process was applied to the ankle joint angle data to obtain high accuracy results. The results of this study can contribute to a more accurate understanding and improvement of the gait patterns of normal and amputee.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.201-209
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• 2003

Virtual human models are widely used to save time and expense in vehicle safety studies. A human model is an essential tool to visualize and simulate a vehicle driver in virtual environments. This research is focused on creation and application of a human model fer virtual reality. The Korean anthropometric data published are selected to determine basic human model dimensions. These data are applied to GEBOD, a human body data generation program, which computes the body segment geometry, mass properties, joints locations and mechanical properties. The human model was constituted using MADYMO based on data from GEBOD. Frontal crash and bump passing test were simulated and the driver's motion data calculated were transmitted into the virtual environment. The human model was organized into scene graphs and its motion was visualized by virtual reality techniques including OpenGL Performer. The human model can be controlled by an arm master to test driver's behavior in the virtual environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2427-2432
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• 2009

This paper proposes an monitoring system of elder and feeble person's motion activity using an object's motion activity data. The proposed system used wireless 3-axis sensor module, product by Freescale(Wireless Sensing Triple Axis Reference Design Board (ZSTAR)). We distribute sensing data into three classes using Neural Network System SVM. We find performance of proposed system that simulate some case about walk, past walk, fallen. Classify result data and graph of sensing data present succes rate 80%.