• Earthquakes and Structures
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• 제24권6호
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• pp.439-453
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• 2023

Older brick masonry structures generally suffer from low strength defects. Using a cement mortar layer (CML) or steel-meshed cement mortar layer (S-CML) to reinforce existing low-strength brick masonry structures (LBMs) is still an effective means of increasing seismic performance. However, performance indices such as lateral displacement ratios and skeleton curves for LBMs reinforced with CML or S-CML need to be clarified in performance-based seismic design and evaluation. Therefore, research into the failure mechanisms and seismic performance of LBMs reinforced with CML or S-CML is imperative. In this study, thirty low-strength brick walls (LBWs) with different cross-sectional areas, bonding mortar types, vertical loads, and CML/S-CML thicknesses were constructed. The failure modes, load-carrying capacities, energy dissipation capacity and lateral drift ratio limits in different limits states were acquired via quasi-static tests. The results show that 1) the primary failure modes of UBWs and RBWs are "diagonal shear failure" and "sliding failure through joints." 2) The acceptable drift ratios of Immediate Occupancy (IO), Life Safety (LS), and Collapse Prevention (CP) for UBWs can be 0.04%, 0.08%, and 0.3%, respectively. For 20-RBWs, the acceptable drift ratios of IO, LS, and CP for 20-RBWs can be 0.037%, 0.09%, and 0.41%, respectively. Moreover, the acceptable drift ratios of IO, LS, and CP for 40-RBWs can be 0.048%, 0.09%, and 0.53%, respectively. 3) Reinforcing low-strength brick walls with CML/S-CML can improve brick walls' bearing capacity, deformation, and energy dissipation capacity. Using CML/S-CML reinforcement to improve the seismic performance of old masonry houses is a feasible and practical choice.

• 전자공학회논문지
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• 제50권9호
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• pp.136-143
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• 2013

본 논문에서는 마커를 부착하기 어려운 소형도마뱀의 관절을 측정하기 위한 마커리스 모션 캡쳐 알고리즘을 제안하였다. 제안한 알고리즘에서는 먼저 스테레오 비젼과 같은 다시점 영상에서 적응적 이진화를 통해 도마뱀의 실루엣 영상을 획득하고 세선화를 수행하여 도마뱀의 뼈대 영상을 획득한다. 이후, 직교-대각 성분 제거 알고리즘 및 A* Search를 통해 머리와 꼬리점, 및 머리와 꼬리를 잇는 척추라인을 구한다. 어깨관절과 고관절의 좌표는 $3{\times}3$ 마스크를 이용하여 척추라인과 다리가 만나는 지점을 구하여 획득하고 모폴로지 닫기 영상을 통해 발바닥 좌표들을 검출한다. 최종적으로 각각의 다리에서 어깨관절 및 고관절 좌표와 발바닥 좌표를 잇는 직선과 해당 다리의 뼈대 좌표간의 직교 거리 비교를 통해 무릎과 팔꿈치 좌표를 구한다. 최종적으로 제안한 알고리즘으로 검출된 각 관절의 다시점 영상의 2차원 좌표들로부터 각 관절의 3차원 좌표를 복원한다. 실제 도마뱀을 촬영한 스테레오 영상에 제안된 알고리즘을 적용하여 2차원 주요 관절 지점 검출 및 3차원 복원을 수행하여 제안된 알고리즘의 성능을 검증하였다.

• 치과방사선
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• 제21권2호
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• pp.405-413
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• 1991

상악골 골수염을 수반한 골화석증에 이환된 33세의 남자환자에서 다음과 같은 사항이 관찰되었다. 1. 간비대, 비장비대, 궁다리소견 등을 볼 수 있었다. 2. X선사진상에서 전반적인 골밀도의 증가와 부비동의 폐색등을 볼 수 있었다. 3. 대퇴골과 좌골의 여러 부위에서 오래된 골절이 관찰되었으며 고관절의 아탈구도 관찰되었다. 4. 상ㆍ하악골 모두 골밀도가 증가되어 있었으며 다수의 기형치와 매복치가 관찰되었다. 5. 골주사 소견에서 큰 관절과 장골에서 다발성의 불규칙한 섭취증가를 볼 수 있었다.

• International Journal of Internet, Broadcasting and Communication
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• 제12권1호
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• pp.122-129
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• 2020

The circumference of the body is not only an indicator in order to buy clothes in our life but an important factor which can increase the effectiveness healing properly after figuring out the shape of body in a hospital. There are several measurement tools and methods so as to know this, however, it spends a lot of time because of the method measured by hand for accurate identification, compared to the modern advanced societies. Also, the current equipments for automatic body scanning are not easy to use due to their big volume or high price generally. In this papers, OpenPose model which is a deep learning-based Skeleton Tracking is used in order to solve the problems previous methods have and for ease of application. It was researched to find joints and an approximation by applying the data of the deep camera via reference data of the measurement parts provided by the hospitals and to develop a program which is able to measure the circumference of the body lighter and easier by utilizing the elliptical circumference formula.

• Advances in robotics research
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• 제2권2호
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• pp.129-140
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• 2018

With the increasing demand for the development of human pose estimation, such as human-computer interaction and human activity recognition, there have been numerous approaches to detect the 2D poses of people in images more efficiently. Despite many years of human pose estimation research, the estimation of human poses with images remains difficult to produce satisfactory results. In this study, we propose a robust 2D human body pose estimation method using an RGB camera sensor. Our pose estimation method is efficient and cost-effective since the use of RGB camera sensor is economically beneficial compared to more commonly used high-priced sensors. For the estimation of upper-body joint positions, semantic segmentation with a fully convolutional network was exploited. From acquired RGB images, joint heatmaps accurately estimate the coordinates of the location of each joint. The network architecture was designed to learn and detect the locations of joints via the sequential prediction processing method. Our proposed method was tested and validated for efficient estimation of the human upper-body pose. The obtained results reveal the potential of a simple RGB camera sensor for human pose estimation applications.

• 한국정밀공학회지
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• 제29권1호
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• pp.25-32
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• 2012

In this study, we present a gripping mechanism that is inspired by caterpillar's proleg. A caterpillar's proleg has planta that gives compliance to the proleg by greatly deforming its shape. In the bio-inspired gripper, the planta is implemented by flexure joints. The flexures buckle when end force and end moment is applied on the joint in opposite direction. Using this characteristic, the gripping structure is designed so that the flexure buckling can occur. Flexure buckling increases the region where gripping force is constant and this region leads to increasing in gripping range. At the same time, flexure buckling decouples all spines and therefore all spines can move differentially and independently. With this simple but effective mechanism, the bioinspire gripper can achieve adaptive gripping on rough and rugged surfaces. A prototype is built to demonstrate adaptive gripping on rough and rugged surfaces such as cement block, brick.

• The Korean Journal of Pain
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• 제10권1호
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• pp.117-120
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• 1997

Cancer is a devastating disease, and the treatment of related pain is an extremely challenging task. Providing adequate analgesia while avoiding unnecessary drug effects often requires a polypharmacologic approach in cancer pain management. A 36-year old woman with breast cancer metastatic to the axial skeleton and bilateral hip joints was admitted to hemato-oncology service with complaints of intractable abdominal and hip pain. Despite rapidly increasing doses of intravenous morphine up to 350 mg per day; transdermal fentanyl; midazolam; ketorolac; lorazepam; dexamethasone, the patient continued to describe her pain as 10 of 10, refusing all surgical/diagnostic interventions not directly related to pain control. She did, however, consent to lumbar epidural catheter placement. The patient was sedated with titrating doses of propofol to assist with positioning. Even though the procedure was not successful due to significant thoracolumbar scoliosis, the patient admitted feeling better than she has in months during attempted placement. After continuous infusion of propofol was initiated at subhypnotic dose, the patient's analgesic demand was drastically reduced and described her pain as "1 to 3" of "10". Approximately 96 hours after the propofol infusion was started, the patient expired comfortably. There had been no change in her medical regimen during fecal 48 hours. In the case described, propofol was extremely advantageous as an adjuvant in the management of cancer related pain.

• 한국정보통신학회논문지
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• 제19권6호
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• pp.1296-1300
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• 2015

본 논문에서는 초음파 영상에서 결절종을 추출하는 방법을 제안한다. 제안된 방법은 초음파 영상에서 퍼지 스트레칭 기법을 적용하여 명암 대비를 증가시킨다. 퍼지 스트레칭 기법이 적용된 초음파 영상에서 퍼지 이진화 기법을 적용한다. 퍼지 이진화 기법이 적용된 영상에서 잡음 영역을 제거하기 위해 8방향 윤곽선 추적 기법을 적용한후, 결절종 후보 영역을 추출한다. 추출된 결절종 후보 영역에서 침식과 팽창 기법을 적용한 후, labelling 기법을 적용하여 결절종이 형태학적으로 타원 형태를 가지는 정보를 이용하여 결절종 영역을 추출한다. 제안된 방법을 결절종 초음파 영상을 대상으로 실험한 결과, 결절종 초음파 영상에서 결절종 영역이 비교적 정확히 추출되는 것을 확인할 수 있었다.

• 한국CDE학회논문집
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• 제12권6호
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• pp.429-440
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• 2007

The purpose of this research is to develop the Human-centered CAD system in which human factors can be considered during the design stage. For this system there are several issues to research, like the digital human modeling technology, the definition of interactions between human and product, the simulation of human motion when using the product, and the bio-mechanical analysis of human, etc. This paper introduces how to construct the kinematical structure of the digital human model. For our digital human model H-ANIM, the international specification of humanoid animation is referenced. And we added the skeleton geometry and the skin surfaces to our model. And it can manipulate its joints by forward kinematics. Also the IKAN inverse kinematics algorithm is adopted to support the posture prediction of the digital human model in the product environment. All of these ideas are implemented using CAD API so that we can apply these functions to the current commercial CAD systems. In this manner, the human factor issues can be effectively taken into account at the early design phase and the costs of bio-mechanical evaluation will be significantly reduced.

• 한국산업융합학회 논문집
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• 제24권6_1호
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• pp.693-698
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• 2021

As technology advances, there is increasing need for research in different fields where this technology is applied. On of the most researched topic in computer vision is Human activity recognition (HAR), which has widely been implemented in various fields which include healthcare, video surveillance and education. We therefore present in this paper a human activity recognition system based on scale and rotation while employing the Kinect depth sensors to obtain the human skeleton joints. In contrast to previous approaches that use joint angles, in this paper we propose that each limb has an angle with the X, Y, Z axes which we employ as feature vectors. The use of the joint angles makes our system scale invariant. We further calculate the body relative direction in the egocentric coordinates in order to provide the rotation invariance. For the system parameters, we employ 8 limbs with their corresponding angles each having the X, Y, Z axes from the coordinate system as feature vectors. The extracted features are finally trained and tested with the Long short term memory (LSTM) Network which gives us an average accuracy of 98.3%.