• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.490-492
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• 2002

본 논문은 물 속 유충인 깔따구의 움직임을 관찰한 데이터에 Active Contour Model을 적용하여 깔따구 상태의 특징을 추출하는 방법을 제안한다. 1987년 소개된 Active Contour Model은 주어진 영상에 놓인 커브를 그 커브에 의해 분할된 영상의 에너지 값을 최소화하는 방향으로 진화하게 함으로써 영상 내 객체의 경계를 찾게 하는 영상분할 방법이다. Chan과 Vese에 의해 개선된 Model을 이용하여 다이아지논이 처리되기 전과 후의 깔따구 행동 패턴의 특징을 찾아낸다. 우선 깔따구의 움직임 궤적을 0.25초를 간격으로 관찰하여 구해진 속도벡터의 위상영상을 만든다.그리고 위상영상에 Active Contour를 두어 진화시키면서 시간에 따라 감소하는 에너지 값의 그래프에서 구해진 기울기로 깔따구 행동 패턴의 특징을 추출한다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.1
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• pp.141-150
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• 2013

This study proposes technology using Active Shape Model to track the object separating it by depth-sensors. Unlike the common visual camera, the depth-sensor is not affected by the intensity of illumination, and therefore a more robust object can be extracted. The proposed algorithm removes the horizontal component from the information of the initial depth map and separates the object using the vertical component. In addition, it is also a more efficient morphology, and labeling to perform image correction and object extraction. By applying Active Shape Model to the information of an extracted object, it can track the object more robustly. Active Shape Model has a robust feature-to-object occlusion phenomenon. In comparison to visual camera-based object tracking algorithms, the proposed technology, using the existing depth of the sensor, is more efficient and robust at object tracking. Experimental results, show that the proposed ASM-based algorithm using depth sensor can robustly track objects in real-time.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1201-1206
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• 2013

Active Appearance Model(AAM) is one of the facial feature extraction techniques. In this paper, we propose the Multiple Active Appearance Model(MAAM). Proposed method uses two AAMs. Each AAM trains using different training parameters. It causes that each AAM has different strong points. One AAM complements the weak points in the other AAM. We performed the facial feature extraction on the 100 images to verify the performance of MAAM. Experiment results show that MAAM gives more accurate results than AAM with less fitting iteration.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.243-246
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• 2004

본 논문은 영상인식 방법으로 개선된 Active Model을 이용한 방법을 제안한다. 제안된 방법은 모든 격자 블록 영역이 동일한 구조를 가지며, 기존의 Active net에서 문제가 되었던 목표물을 탐지하는 능력이 개선되었다. 실험 결과로서 제안된 방법이 수직, 수평 방향에서 목표물 포착에 효과적임을 보여주었으며, 실제 도로 영상에 적용한 결과 제안한 방법의 효율성을 입증할 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.217-217
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• 2000

A decentralized robust EA(eigensoucture assignment) controller is designed for an active suspension system of a vehicle based on a full car model with 7-degree of freedom. Using overlapping decomposition, the full car model is decentralized by two half car models. For each half car model, a robust eigenstructure assignment controller can be obtained by using optimization approach. The performance of the decentralized robust EA controller is compared with that of a conventional centralized EA controller through computer simulations.

• 유공압시스템학회:학술대회논문집
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• 2010.06a
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• pp.70-73
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• 2010

In order to provide theoretical analysis for the active roll stabilizer (ARS), the simulation model based on AMESim is developed in the paper. The simplified vehicle rolling motion model is derived firstly, and then the entire ARS control system model is constructed. Furthermore, the simulation is implemented to confirm the roll control effect. The simulation results show that the derived model can be used as theoretical analysis for developing components of ARS control system.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.614-621
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• 2001

The controllers for a full car 7-DOF model with 4 active or semi-active suspension units are designed and evaluated in this research. The control algorithms for suspension systems, such as full state feedback active, full state feedback semi-active, sky-hook active, sky-hook semi-actvie, and on-off suspension systems, are analyzed and evaluated with respect to ride comfort. The vehicle dynamic performances are expressed by response curves to a bump input, performance indices for asphalt road input, and frequency characteristic curves. Heaving, rolling, and pitching inputs are applied to the vehicle dynamic system to evaluate frequency characteristics. The simulation results show that the ride quality of the sky-hook controller approaches that the full state feedback controller more closely in semi-active suspension system than in active suspension system. For the implementation of a vehicle with sky-hook suspension control systems in this paper, 7 velocity sensors are required to measure the states.

• Tuberculosis and Respiratory Diseases
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• v.86 no.3
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• pp.226-233
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• 2023

Background: Inactive or old, healed tuberculosis (TB) on chest radiograph (CR) is often found in high TB incidence countries, and to avoid unnecessary evaluation and medication, differentiation from active TB is important. This study develops a deep learning (DL) model to estimate activity in a single chest radiographic analysis. Methods: A total of 3,824 active TB CRs from 511 individuals and 2,277 inactive TB CRs from 558 individuals were retrospectively collected. A pretrained convolutional neural network was fine-tuned to classify active and inactive TB. The model was pretrained with 8,964 pneumonia and 8,525 normal cases from the National Institute of Health (NIH) dataset. During the pretraining phase, the DL model learns the following tasks: pneumonia vs. normal, pneumonia vs. active TB, and active TB vs. normal. The performance of the DL model was validated using three external datasets. Receiver operating characteristic analyses were performed to evaluate the diagnostic performance to determine active TB by DL model and radiologists. Sensitivities and specificities for determining active TB were evaluated for both the DL model and radiologists. Results: The performance of the DL model showed area under the curve (AUC) values of 0.980 in internal validation, and 0.815 and 0.887 in external validation. The AUC values for the DL model, thoracic radiologist, and general radiologist, evaluated using one of the external validation datasets, were 0.815, 0.871, and 0.811, respectively. Conclusion: This DL-based algorithm showed potential as an effective diagnostic tool to identify TB activity, and could be useful for the follow-up of patients with inactive TB in high TB burden countries.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1412-1417
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• 2014

The corpus callosum is the largest part of the brain, which is related to many neurological diseases. Snake model or active contour model is widely used in medical image processing field, especially image segmentation they look into the nearby edge, localizing them accurately. In this paper, corpus callosum segmentation using the snake model, is proposed. We tested a snake model on brain MRI. Then we compared the result with an active shape approach and found that snake model had better segmentation accuracy also faster than active shape approach.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.1
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• pp.74-80
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• 2011

Front-back vibrations of high-speed elevator need to be suppressed as in the case of lateral vibrations. The dynamic model for the front-back vibrations is different from the lateral vibration model since the supporting structure varies. In this study, a dynamic model was derived using the energy method. Based on the free vibration analysis, it was observed that the fundamental frequency for the front-back vibration is slightly lower than the fundamental frequency of the lateral vibration, which means that the active vibration control should be carried out in both directions. The PPF control algorithm was applied to the numerical model under measured rail irregularities. The numerical results show that the active vibration control of elevator front-back vibration is also possible.