• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.462-465
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• 2002

This paper deals with the problem of synthesis of stable and optimal grasps with unknown objects by 3-finger hand. Previous robot grasp research has analyzed mainly with either unknown objects 2D by vision sensor or unknown objects, cylindrical or hexahedral objects, 3D. Extending the previous work, in this paper we propose an algorithm to analyze grasp of unknown objects 3D by vision sensor. This is archived by two steps. The first step is to make a 3D geometrical model of unknown objects by stereo matching which is a kind of 3D computer vision technique. The second step is to find the optimal grasping points. In this step, we choose the 3-finger hand because it has the characteristic of multi-finger hand and is easy to modeling. To find the optimal grasping points, genetic algorithm is used and objective function minimizing admissible farce of finger tip applied to the object is formulated. The algorithm is verified by computer simulation by which an optimal grasping points of known objects with different angles are checked.

• 복식문화연구
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• 제18권6호
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• pp.1305-1317
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• 2010

본 연구는 다양한 3D imaging 기술이 생산해낼 수 있는 환영효과를 직물에 적용할 수 있는지에 대한 가능성을 통해서, 현실과 허구의 경계가 없어지는 새로운 환경을 조성하기 위한 직물을 개발하여 변형 가능한 삼차원의 살아있는 직물 같은, 관점에 따라 패턴과 색깔의 이미지가 바뀌는 흥미로운 직물패턴의 실현 가능성을 알아본다. 본 논문은 I, II로 나뉘어 있으며, 각 논문에서 각기 다른 실험을 실시하여 결과로의 적용가능성과 제한점을 살펴봄으로써 Holography, Lenticular, 등 가상의 3D 테크놀로지를 통해 2D 평면의 구조에 3D 가상 이미지의 텍스타일 적용 가능성을 기계적 실험을 통해 확인하며, 3D imaging 기술에 대한 경험과 이해를 얻고, 3D imaging 기술을 적용할 수 있는 잠재력을 연구하기 위한 것으로, 실험은 현장에 있는 전문 텍스타일연구가, 과학자, 예술가 그리고 디자이너들의 협업으로 이루어졌다.

• 임상간호연구
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• 제26권3호
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• pp.275-284
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• 2020

Purpose: For this study the moderating and mediating effects of resilience on the relationships between work intensity, conflicts in interpersonal relationship and nurses' burnout were investigated. Methods: In this descriptive research 227 nurses who consented to participate in the study were surveyed. The tool included nurses' objective work intensity, subjective work intensity, conflicts in interpersonal relationships, resilience, and burnout. Data were collected from nurses in general hospitals in D city from July to August 2017. Collected data were analyzed using SPSS 23.0 program. Results: Participants' burnout showed a statistically significant difference according to age, marital status, total clinical experience, position, work pattern, frequency of night shifts, work department, and salary. Participants' burnout was significantly positively correlated with subjective work intensity and conflicts in interpersonal relationships, and significantly negatively correlated with resilience. Resilience moderated the relationship between participants' subjective work intensity and burnout, and mediated the relationship between conflicts in interpersonal relationships and burnout. Conclusion: Resilience had a moderating effect on the relationship between subjective work intensity and burnout, and a mediating effect on the relationship between conflicts in interpersonal relationships and burnout. Therefore, further efforts and diverse intervention measures are required to enhance resilience and reduce work intensity and conflicts in interpersonal relationships in order to prevent burnout in nurses.

• Spatial Information Research
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• 제18권5호
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• pp.143-161
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• 2010

본 연구에서는 3차원 지형공간정보를 기반으로 한 정밀한 토공량 모델링을 통해 토목 건설공사의 효율성을 향상시키기 위한 토공량 계산 프로그램인 EWS 프로그램을 개발하였다. EWS 프로그램은 LiDAR DEM을 이용한 정확한 토공량 계산과 건설장비의 단위 작업량을 기반으로 한 토공 공정계획수립이 가능하도록 개발되었다. 또한 계산된 결과를 건설현장에서 보다 직관적인 이해하고 이에 따른 분석 결과를 쉽게 공유할 수 있도록 하기 위해 Google Earth를 이용한 3D 가시화도 지원이 가능하다. 개발된 프로그램의 현장 적용성 검증을 위해 DAS 프로그램과의 토공량 계산 결과 및 토공 이동계획을 비교하였으며, 검증을 위한 대상지역으로 경기도 포천시 신북면 일원의 신포천 변전소 건설현장을 선정하였다. 최종적인 비교 결과, 본 연구에서 개발된 EWS 프로그램을 이용하는 경우 정밀한 3차원 지형공간정보를 통해 정확한 토공량 계산이 가능하며, 보다 합리적인 토량 이동계획 및 토공작업의 수립할 수 있어 건설현장에서의 생산성 향상 효과를 기대할 수 있을 것으로 판단되었다.

• 한국멀티미디어학회논문지
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• 제18권5호
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• pp.583-598
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• 2015

We need many assembly lines to produce industrial product such as automobiles that require a lot of composited parts. Big portion of such assembly line are still operated by manual works of human. Such manual works sometimes cause critical error that may produce artifacts. Also, once the assembly is completed, it is really hard to verify whether of not the product has some error. In this paper, for monitoring behaviors of manual human work in an assembly line automatically, we proposes a realtime hybrid monitoring system that combines 2D vision sensor tracking technique with 3D motion recognition sensors.

• Bulletin of the Korean Chemical Society
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• 제3권3호
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• pp.104-109
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• 1982

A method to calculate the magnetic moments for $d^1$ and $d^2$ complexes in a strong crystal field of trigonal symmetry has been developed in this work choosing the trigonal axis (Ⅲ) as the quantization axis. The calculated magnetic moments using this method for $d^1$ and $d^2$ complexes in a strong trigonal ligand field fall in the range of the experimental values. The dipolar shifts for $d^1$ and $d^2$ complexes in a strong trigonal ligand field are also calculated using the calculated magnetic susceptibility components. The calculated values of the dipolar shifts also fall in the reasonable range.

• 한국BIM학회 논문집
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• 제8권1호
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• pp.24-32
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• 2018

A construction machine guidance system is an assistance system that helps construction equipment operators dig grounds during excavation work at a construction site. This system has long been applied in the overseas countries of the United States, Japan and Europe. However, the system has not been paid much attention in Korea. The objective of this paper is to present a business model for adopting construction machine guidance systems in Korea and evaluate the effectiveness of applying the system to excavation work. The business model in this study shows a new process of applying construction machine guidance system, business stakeholders and revenues, and suggests the benefits to the business stakeholders. A field test of the construction machine guidance system proves that the system can be applied as a tool that can improve the productivity of excavation work. This productivity improvement consequently demonstrates that the business model in this study is a prospective challenge in improving the effectiveness of excavation work at the construction site.

• 한국안전학회지
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• 제22권1호
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• pp.30-35
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• 2007

With the rapid industrialization and civilization development, noise has become a major problem in cities and is a very serious issue for the environment. Noise induced in a factory has a bad influenced on operation efficiency, accuracy and detail of work. The purpose of this paper is to develop a new noise evaluation software for predicting acoustic condition including noise properties during the design of a factory. Majority of commercial softwares for this purpose have been developed in foreign countries and they are quite expensive and hard to use. A new home-made software tool has been developed in the present work, which aimed at providing a more user-friendly environment. The tool developed in this work consists of four major part; the prediction and evaluation of noise in system design, database design, noise analysis development and 3D graphic modeling. The outcome of present work is expected to provide domestic users with a more user-friendly and economic acoustic design tool.

• 한국건설순환자원학회논문집
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• 제9권3호
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• pp.330-337
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• 2021

3D 프린팅의 기술발전으로 대형물 제작이 가능하게 되면서 이를 건축물에 적용하기 위한 연구가 활발하게 진행되고 있다. 건축물에서는 구조재와 비구조재로 구분되고 비구조재는 비정형 구조물 및 내·외장패널에 적용하기 유리하다. 3D 프린팅 재료는 기본적으로 시멘트 모르타르의 압출과 적층이 가능해야하므로 시멘트 혼화용 폴리머 와 경량재료의 사용이 필수적이다. 본 연구는 3D 프린팅 적용을 위해 시멘트 모르타르에 EVA 재유화형 분말수지를 사용하였다. 경량재료 혼입 폴리머 시멘트 모르타르의 난연특성을 평가하기 위해 골재로는 규사8호와 경량재료로 경량골재, 중공글라스를 사용하여 난연 및 불연성능을 평가하였다. 연구결과, 규사8호 및 경량골재를 사용한 시험체가 충분한 난연 및 불연성능을 보였다. EVA 재유화형 분말수지를 혼입할 경우 5% 이하로 적용하여 사용하는 것이 유리하다.

• 스마트미디어저널
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• 제9권1호
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• pp.23-29
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• 2020

This paper presents an approach for dynamic hand gesture recognition by using algorithm based on 3D Convolutional Neural Network (3D_CNN), which is later extended to 3D Residual Networks (3D_ResNet), and the neural network based key frame selection. Typically, 3D deep neural network is used to classify gestures from the input of image frames, randomly sampled from a video data. In this work, to improve the classification performance, we employ key frames which represent the overall video, as the input of the classification network. The key frames are extracted by SegNet instead of conventional clustering algorithms for video summarization (VSUMM) which require heavy computation. By using a deep neural network, key frame selection can be performed in a real-time system. Experiments are conducted using 3D convolutional kernels such as 3D_CNN, Inflated 3D_CNN (I3D) and 3D_ResNet for gesture classification. Our algorithm achieved up to 97.8% of classification accuracy on the Cambridge gesture dataset. The experimental results show that the proposed approach is efficient and outperforms existing methods.