• Journal of Hospice and Palliative Care
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• 제24권4호
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• pp.245-253
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• 2021

Purpose: This study aimed to explore the experiences of hospice and palliative care (HPC) nurses at inpatient hospice centers in South Korea during the coronavirus disease 2019 pandemic. Methods: Data collection was conducted through individual interviews with 15 HPC nurses using face-to-face interviews, telephone calls, or Zoom videoconferencing. Data were analyzed using the thematic analysis method. Results: This study found that HPC nurses experienced practical and ethical dilemmas that reinforced the essential meaning and value of hospice and palliative care. The participants emphasized their practical roles related to compliance with infection prevention measures and their roles as rebuilders of hospice and palliative care. Conclusion: The findings of this study indicate that inpatient hospice centers must mitigate the practical and ethical dilemmas experienced by nurses, consider establishing explanation nursing units, and provide education to support nurses' highlighted roles during the pandemic. This study can be used to prepare inpatient hospice centers and the nurses that work there for future infectious disease outbreaks.

• 한국산학기술학회논문지
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• 제15권9호
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• pp.5750-5757
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• 2014

본 논문은 의도하지 않게 카메라에 입력되는 회전, 병진 움직임뿐만 아니라 확대 축소에 의한 움직임을 SIFT 기법을 이용하여 추정하고 제거하는 영상 안정화 기법을 제시한다. 또한 영상 분할 및 통합 방법을 이용하여 움직이는 물체가 영상에 입력되었을 경우에도 이러한 외란을 제거하고 영상 안정화를 수행하도록 한다. 제시된 방법은 다른 방법과 결과를 비교하는 실험을 수행하여 성능이 우수함을 검증한다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2084-2087
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• 2003

본 논문에서는 MPEG 압축 도메인 상에서 카메라 움직임 정보를 추출하는 효과적인 방법을 제안한다. 카메라 움직임 정보는 동영상에서의 주요 장면과 프레임간의 관계를 기술할 수 있는 실마리를 제공한다. 본 논문에서는 MPEG Video의 모션벡터를 이용하여 카메라 움직임 정보를 추출한다. 카메라 움직임에 따라 모션벡터는 특징적으로 분포하는 특성이 있다. 본 논문에서는 이러한 특징들을 이용하여 MPEG 모션벡터의 방향성과 크기를 이용하여 각 모션벡터끼리 교차점과 평행성분을 구한다. 그리고 이것을 이용하여 같은 교차점과 평행성분끼리 모션벡터 Clustering 을 수행한다 본 논문에서는 클러스터링 된 모션벡터를 Fuzzy inference rule을 이용하여 카메라 움직임이 Zoom, Pan, Tilt 인지 여부를 판단한다. 실험은 전통적인 방법 중에 하나인 Affine Model 방법과 비교하며 본 논문의 방법이 어느정도 우수함을 입증한다.

• 제어로봇시스템학회논문지
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• 제10권8호
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• pp.673-679
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• 2004

In this paper, we develop the displacement measurement system of multiple moving objects based on image processing techniques. The image processing method adopts inertia moment theory for obtaining the centroid measurement of the targets and basic processing algorithm of gray, binary, closing, labeling and so on. To get precise displacement measurement in spite of multiple moving targets, a CGD camera with zoom is used and the position of camera is changed by a pan/tilt system. The fiducial marks on the fixed positions are used as the sensing points for the image processing to recognize the position errors in direction of XY-coordinates. The precise alignment device is pan/tilt of XY-type and the pan/tilt is controlled by DC servomotors which are driven by a microprocessor. Morover, the centers of fiducial marks are obtainted by an inertia moment method. By applying the developed precise position control system for multiple targets, the displacement of multiple moving targets are detected automatically and are also stored in the database system in a real time. By using database system and internet, the displacement datum can be confirmed at a great distance and analyzed. Finally, the effectiveness of developed system is shown in experimental results and realized the precision about 0.12[mm] in the position control of XY-coordinates.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.764-769
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• 2003

The paper introduces a development result for displacement measurement system of multiple moving objects based on image processing technique. The image processing method adopts inertia moment theory for obtaining the centroid of the targets and basic processing algorithms of gray, binary, closing, labeling and etc. To get precise displacement measurement in spite of multiple moving targets, a CCD camera with zoom is used and the position of camera is changed by a pan/tilt system. The fiducial marks on the fixed positions are used as the sensing points for the image processing to recognize the position errors in directions of X -Y coordinates. The precise alignment device is pan /tilt of X - Y type and the pan/tilt is controlled by DC servomotors which are driven by 80c196kc microprocessor based controller. The centers of the fiducial marks are obtained by a inertia moment method. By applying the developed precise position control system for multiple targets, the displacement of multiple moving targets are detected automatically and are stored in the database system in a real time. By using database system and internet, displacement data can be confirmed at a great distance and analyzed. The developed system shows the effectiveness such that it realizes the precision about 0.12mm in the position control of X -Y coordinates.

• 한국멀티미디어학회논문지
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• 제22권2호
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• pp.167-177
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• 2019

Even though so much progresses have been achieved in Multiple Object Tracking (MOT), most of reported MOT methods are not still satisfactory for commercial embedded products like Pan-Tilt-Zoom (PTZ) camera. In this paper, we propose a real-time multiple pedestrians tracking method for embedded environments. First, we design a new light weight convolutional neural network(CNN)-based pedestrian detector, which is constructed to detect even small size pedestrians, as well. For further saving of processing time, the designed detector is applied for every other frame, and Kalman filter is employed to predict pedestrians' positions in frames where the designed CNN-based detector is not applied. The pose orientation information is incorporated to enhance object association for tracking pedestrians without further computational cost. Through experiments on Nvidia's embedded computing board, Jetson TX2, it is verified that the designed pedestrian detector detects even small size pedestrians fast and well, compared to many state-of-the-art detectors, and that the proposed tracking method can track pedestrians in real-time and show accuracy performance comparably to performances of many state-of-the-art tracking methods, which do not target for operation in embedded systems.

• Journal of Ecology and Environment
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• 제41권5호
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• pp.145-151
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• 2017

Background: Conventional bird observation methods are line survey or point count method by bare eyes or through binoculars or telescopes. But in this study, the possibility of monitoring waterbirds using drones beyond the conventional research methods was explored. It also describes the direction of producing and accumulating images of waterbird habitats as a method to efficiently determine changes in waterbird habitats. Results: From the study, it was concluded that waterbird monitoring using drones was a new monitoring technique which could be applied to the field and 26 kinds of waterbirds were observed. In the case of a drone with a single lens, it was difficult to identify objects because the size of the subject was too small at a certain altitude. In this case, zoom lens can be an alternative. It has also been verified that image analysis software can be used to accumulate images of waterbird habitats. Conclusions: If various kinds of advanced drones and cameras are used, it would be possible to monitor larger areas including the areas that are difficult for human access and to observe more waterbirds and wider habitats.

• 복식
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• 제55권4호
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• pp.95-106
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• 2005

The purpose of this study was to research the design methods to express jacquard design using CAD. For this study, two design patterns were divided; in addition, each design pattern is applied to two different weaving types, single woven fabric and double well cloths. As a result, 16 samples were produced by applying 4 design methods (warp shrunk as half size design/weft shrunk as half size design - A, warp shrunk as half size design/weft original size design - B, warp original size design/weft shrunk as half size design - C, warp original size design/weft original size design - D) to the two design patterns with the two weaving types. The result of this study can be summarized as follows. 1. The most delicate design method was Method D. However, Method B which took half the time less than Method D was almost as delicate as the Method D on the surface. 2. Method B was judged as a considerably efficient method for time and cost. 3. Method D was considered as most suitable for elaborate parts and delicate lines. However, it was considered uneconomical since it took the longest time. 4. Mettled A took 2.5 times less time than Method D. Therefore, Method A was more applicable to producing high density design. 5. Method C is not considered as a useful method as it showed rough surface and took long time by applying high design zoom except intentional design.

• 한국인터넷방송통신학회논문지
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• 제22권4호
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• pp.171-176
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• 2022

CNN은 딥러닝의 한 종류로 이미지나 영상 데이터를 처리할 때 사용하는 신경망이다. 필터가 이미지를 순회하며 이미지의 특징을 추출하여 이미지를 구분한다. 딥러닝은 데이터가 많을수록 좋은 모델을 만들 수 있는 특징이 있고, CNN에서는 적은 데이터의 약점을 보완하기 위해 회전, 확대, 이동, 뒤집기 같은 방법의 데이터 증강이라는 기법으로 데이터의 양을 인위적으로 늘리는 방법을 사용한다. 외곽선 이미지 학습은 이미지 데이터에서 외곽선에 해당하는 영역을 추출하는 것이다. CNN 학습 시, 외곽선 이미지 학습이 기존의 데이터 증강기법과 비교하여 성능 향상의 도움이 되는지 확인하고자 한다.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2003년도 춘계종합학술대회논문집
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• pp.416-420
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• 2003

본 논문에서는 내삽법을 이용하여 빠른 육안 검색을 위한 이중 해상도 영상 데이터베이스 시스템을 구현하였다. 단일 고해상도 방식에서 발생하는 블록킹 현상과 두 개의 해상도를 가진 영상들을 각각 데이터베이스에 저장할 때 발생하는 큰 저장 공간의 두 가지 단점을 극복하였다. 제안한 방식은 원 영상을 부샘플링하여 부샘플링 영상을 만들고, 내삽법을 이용하여 부샘플링된 영상의 보간 영상을 만든다. 이 보간 영상과 원영상과의 차영상을 근간으로 복합 이중 해상도 영상 데이터베이스를 구성한다. 60명의 실험 영상으로 실험한 결과 제안한 방식의 검색 시간이 평균 0.003초로, 단순 고해상도 방식의 0.014초에 비해 빠르다, 또한 원영상 하나만을 저장하는 방식에 비해 19,821 byte에서 16,910 byte로 14.7% 개선 효과가 있다.