• Journal of Information Processing Systems
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• 제15권1호
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• pp.47-54
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• 2019

This study is concerned with the mechanism and structure of an optical microscope and an automatic multi-focus algorithm for automatically selecting sharp images from multiple foci of a cell. To obtain precise cell images quickly, a z-axis actuator with a resolution of $0.1{\mu}m$ was designed to control an optical microscope Moreover, a lighting control system was constructed to select the color and brightness of light that best suit the object being viewed. Cell images are captured by the instrument and the sharpness of each image is determined using Gaussian and Laplacian filters. Next, cubic spline interpolation and peak detection algorithms are applied to automatically find the most vivid points among multiple images of a single object. A cancer cell imaging experiment using propidium iodide staining confirmed that a sharp multipoint image can be obtained using this microscope. The proposed system is expected to save time and effort required to extract suitable cell images and increase the convenience of cell analysis.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2002년도 추계학술발표논문집 (하)
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• pp.2115-2118
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• 2002

이 논문에서는 정형적 명세를 이용하여 테스트 데이터를 추출하는 방법을 제안한다. 복잡하고 구성요소가 다양한 웹 프로그램의 기능을 Object-Z 정형 명세 언어를 이용하여 핵심적으로 나타낸다. 이로부터 상태 모델을 구성하고 최상위 레벨의 STD 에서 세부적으로 STD 를 추가하여 테스트 시나리오를 추출한다. 실험 대상은 웹 뱅킹 업무로 정하고 계좌개설 과정의 테스트 데이터를 추출하였다. 제안한 방법은 사용기반 테스트 기법과 결합하여 웹 소프트웨어의 테스트 자동화에 중요한 요소가 될 것이다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2008년도 춘계학술대회 논문집
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• pp.917-918
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• 2008

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.202-207
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• 1993

A theoretical and experimental study is presented for the force holding control of a miniature robotic ringer which is driven by a pair of piezoelectric unimorph cells. In the theoretical analysis, one finger is modeled as a flexible cantilever with a tactile force sensor at the tip and the mate of the finger is a solid beam supposed with sufficient stiffness. Further, the force sensor is modeled by a one-degree-of-freedom, mass-spring system and the output of sensor is then described by the sensor stiffness multiplied by the relative displacement. The problem investigated in this paper is that two typical holding tasks of the human finger are picked up and applied to the robotic finger. One is the work holding a stationary object with a prescribed, time-varying force and the other one is to keep the contacted force constant even if the object is in motion. The simple PID feedback control scheme is used to control the minute gripping force of order 0.01 Newton. It is shown both experimentally and theoretically that the artificial finger with the piezoelectric actuator works well in the minute force holding of the tiny object.

• 디지털산업정보학회논문지
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• 제10권2호
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• pp.13-20
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• 2014

In this paper, we implemented the object scanning with nxtOSEK which is an open source platform. nxtOSEK consists of device driver of leJOS NXJ C/Assembly source code, TOPPERS/ATK(Automotive real time Kernel) and TOPPERS/JSP Real-Time Operating System source code that includes ARM7 specific porting part, and glue code make them work together. nxtOSEK can provide ANSI C by using GCC tool chain and C API and apply for real-time multi tasking features. We experimented the 3D scanning with ultra sonic and laser sensor which are made directly by laser module diode and experimented the measurement of scanning the object by knowing x, y, and z coordinates for every points that it scans. In this paper, the laser module is the dimension of $6{\times}10[mm]$ requiring 5volts/5[mW], and used the laser light of wavelength in the 650[nm] range. For detecting the object, we used the beacon detection algorithm and as the laser light swept the objects, the photodiode monitored the ambient light at interval of 10[ms] which is called a real time. We communicated the 3D scanning platform via bluetooth protocol with host platform and the results are displayed via DPlot graphic tool. And therefore we enhanced the functionality of the 3D scanner for identifying the image scanning with laser sensor modules compared to ultra sonic sensor.

• 제어로봇시스템학회논문지
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• 제15권11호
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• pp.1080-1087
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• 2009

This paper presents an algorithm to acquire 3D geometric information using a virtual plane method. The method to measure 3D information on the plane is easy, because it's not concerning value on the z-axis. A plane can be made by arbitrary three points in the 3D space, so the algorithm is able to make a number of virtual planes from feature points on the target object. In this case, these geometric relations between the origin of each virtual plane and the origin of the target object coordinates should be expressed as known homogeneous matrices. To include this idea, the algorithm could induce simple matrix formula which is only concerning unknown geometric relation between the origin of target object and the origin of camera coordinates. Therefore, it's more fast and simple than other methods. For achieving the proposed method, a regular pin-hole camera model and a perspective projection matrix which is defined by a geometric relation between each coordinate system is used. In the final part of this paper, we demonstrate the techniques for a variety of applications, including measurements in industrial parts and known patches images.

• 대한토목학회논문집
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• 제10권4호
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• pp.103-112
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• 1990

본 연구는 실제크기의 첨성대 모형을 피사체로 선정하여 측정용 카메라에 의해 원형 strip과 Block을 형성한 후, bundle조성으로 촬영거리와 기준점 배치에 따른 정확도를 다양하게 분석하고 strip조합해석의 특성을 규명하므로써 전면(全面)해석을 요하는 각종 문화재 특히 원통형 구조물에 대한 최적 해석기법을 제시한 것이다. 연구결과 어느 일면에 배치된 기준점 만으로도 전면해석이 가능하며, 기준점수에 비해 그 배치가 정도에 보다 큰 영향을 미침을 알 수 있었다. 또한 구조물의 전면해석시 기준점은 X, Y, Z축 평면상에 고루 배치하는 것이 이상적이며, 근접촬영하여 strip조합수에 증가시킴에 따라 정확도가 현저히 향상되었다.

• 로봇학회논문지
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• 제14권4호
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• pp.357-362
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• 2019

This paper proposes a model and train method that can real-time detect objects and distances estimation based on a monocular camera by applying deep learning. It used YOLOv2 model which is applied to autonomous or robot due to the fast image processing speed. We have changed and learned the loss function so that the YOLOv2 model can detect objects and distances at the same time. The YOLOv2 loss function added a term for learning bounding box values x, y, w, h, and distance values z as 클래스ification losses. In addition, the learning was carried out by multiplying the distance term with parameters for the balance of learning. we trained the model location, recognition by camera and distance data measured by lidar so that we enable the model to estimate distance and objects from a monocular camera, even when the vehicle is going up or down hill. To evaluate the performance of object detection and distance estimation, MAP (Mean Average Precision) and Adjust R square were used and performance was compared with previous research papers. In addition, we compared the original YOLOv2 model FPS (Frame Per Second) for speed measurement with FPS of our model.

• 한국BIM학회 논문집
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• 제13권4호
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• pp.96-105
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• 2023

This study focuses on developing a building object recognition technology for efficient use in the remodeling of buildings constructed without drawings. In the era of the 4th industrial revolution, smart technologies are being developed. This research contributes to the architectural field by introducing a deep learning-based method for automatic object classification and recognition, utilizing point cloud data. We use a TD3D network with voxels, optimizing its performance through adjustments in voxel size and number of blocks. This technology enables the classification of building objects such as walls, floors, and roofs from 3D scanning data, labeling them in polygonal forms to minimize boundary ambiguities. However, challenges in object boundary classifications were observed. The model facilitates the automatic classification of non-building objects, thereby reducing manual effort in data matching processes. It also distinguishes between elements to be demolished or retained during remodeling. The study minimized data set loss space by labeling using the extremities of the x, y, and z coordinates. The research aims to enhance the efficiency of building object classification and improve the quality of architectural plans by reducing manpower and time during remodeling. The study aligns with its goal of developing an efficient classification technology. Future work can extend to creating classified objects using parametric tools with polygon-labeled datasets, offering meaningful numerical analysis for remodeling processes. Continued research in this direction is anticipated to significantly advance the efficiency of building remodeling techniques.

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2006년도 추계학술발표회
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• pp.303-308
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• 2006

이 연구의 목적은 부산항에 입항하는 대형 콘테이너 선박의 안전 접안 조종을 위한 한계풍속을 설정하는데 있다. 계산결과, 정상풍속 13.5m/sec 이하의 바람에서는 예선 4500H.P.의 Z. peller 2척을 이용하여 안전 접안 조선하는데 큰 위험이 없음을 알았다. 그러나 돌풍율 25%를 포함한 강풍 16.9m/sec 이상의 기상상태에서는 선박조종이 위험하게 됨을 알았고, 돌풍율을 포함하여 풍속이 16.9m/sec 에 달하는 강풍하에서 대형 콘테이너 선박을 부득이 접안 조종할 때는 4500 H.P.Z. peller 3척으로 조선보조를 받아야 함을 알았다.