• 한국방사선학회논문지
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• 제11권2호
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• pp.79-85
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• 2017

본 연구에서는 유방촬영검사에서 사전조사 관전압과 실제조사 관전압 편차에 따른 원인분석을 유방압박두께, 유방크기, 체질량지수와 연관하여 규명하고 개선책을 찾고자 하였다. 국민건강보험공단에서 실시하는 유방촬영 검진자 중 40세 이상 여자 377명을 대상으로 조사하였다. 유방촬영검사에서 상하방향촬영에 의한 영상을 참고하여 의료영상저장정보시스템으로 전송되어진 선량 보고서(dose report)의 파라메타 중 사전조사 관전압과 실제조사 관전압의 편차에 따른 유방압박두께, 유방크기, 체질량지수를 분석하였다. 결과로는 유방압박두께가 얇을수록, 유방크기가 작을수록, 체질량지수가 작을수록 관전압 편차가 크게 나타났다. 결론적으로 유방촬영검사에서 유방압박두께와 유방크기에 따른 관전압 설정을 하기 위해 우리나라 실정에 맞는 유방촬영기기의 최소 관전압이 재설정 되어야 할 것이며, 또한 유방압박두께가 얇은 환자나 유방크기가 작은 환자를 검사할 경우 정확한 조사조건 매뉴얼을 만들어 검사함으로서 촬영조건의 편차를 줄여 방사선피폭 경감과 좋은 영상의 화질을 만드는데 노력해야 할 것으로 사료된다.

• 한국융합학회논문지
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• 제12권6호
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• pp.107-112
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• 2021

이 연구는 현대농구의 빠른 템포와 공격적인 흐름에 맞추어 보다 정확한 득점방법을 연구하고자 디지털압력센서를 탑재한 스마트 농구공을 설계, 개발하는데 목적이 있다. 농구는 드리블, 패스, 슈팅 등의 복합적 결합으로 구성된 스포츠종목으로 지구상의 모든 스포츠에서 가장 많은 득점이 이루어지는 경기방식을 가지고 있다. 특히 경기의 승패를 좌우하는 슈팅은 득점과 가장 직접적으로 연결되는 기술이다. 이 연구는 슈팅 시 공의 투사각을 측정할 수 있는 스마트 농구공을 설계함으로써 농구경기 현장에서 슈팅 성공률을 향상시키는데 유용한 보조기구를 제시하였다. 스마트 농구공은 일정한 포물선의 각도를 유지하여 슈팅의 정확성을 높이는 훈련이 가능하며, 선수의 경기력 향상을 기대할 수 있다.

• Korean Journal of Radiology
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• 제2권1호
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• pp.8-13
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• 2001

Objective: To determine the incidence and etiologies of celiac axis stenosis in asymptomatic individuals. Materials and Methods: This prospective study involved 400 consecutive patients (male: 319, female: 81) referred to us for celiac arteriography between April and July 1999. When celiac axis branches were opacified by collateral circulation during superior mesenteric arteriography, the presence of celiac axis stenosis was suspected; lateral projection celiac arteriography was performed and the pressure gradient was measured. The indicators used to determine whether or not celiac axis stenosis was significant were luminal narrowing of more than 50% and a resultant pressure gradient of at least 10 mmHg. Its etiology was determined on the basis of angiographic appearances and CT findings. Results: Twenty-nine patients (7.3%) had celiac axis stenosis. The etiology of the condition was extrinsic compression due to the median arcuate ligament in 16 patients (55%) and atherosclerosis in three (10%), while in ten (35%) it was not determined. The incidence of celiac axis stenosis did not vary significantly according to sex, age and the presence of calcified aortic plaque representing atherosclerosis. Conclusion: The incidence of hemodynamically significant celiac axis stenosis in this asymptomatic Korean population was 7.3% and the most important etiology was extrinsic compression by the median arcuate ligament of the diaphragm. Atherosclerosis was only a minor cause of the condition.

• 대한기계학회논문집A
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• 제20권3호
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• pp.775-787
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• 1996

An optimization procedure is proposed for the design of cylindrically laminated composite shell having midplane symmetry and subjected to axial force, torsion and internal pressure. Tsai-Wu and Tsai-Hill failure criteria are taken as objective functions. The stacking sequence represents the design variable. The optimal design formulation based on state space method is adopted and solution proccedure is described with the emphasis on the method of calculations of the design sensitivities. A gradient projection algorithm is employed for the optimization process. Numerical results are presented for the several test problems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.107-109
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• 2004

In this paper, authors propose the sensor fusion system that can recognize multiple 3D objects from 2D projection images and tactile information. The proposed system focuses on improving recognition performance of 3D object. Unlike the conventional object recognition system that uses image sensor alone, the proposed method uses tactual sensors in addition to visual sensor. Neural network is used to fuse these informations. Tactual signals are obtained from the reaction force by the pressure sensors at the fingertips when unknown objects are grasped by four-fingered robot hand. The experiment evaluates the recognition rate and the number of teaming iterations of various objects. The merits of the proposed systems are not only the high performance of the learning ability but also the reliability of the system with tactual information for recognizing various objects even though visual information has a defect. The experimental results show that the proposed system can improve recognition rate and reduce learning time. These results verify the effectiveness of the proposed sensor fusion system as recognition scheme of 3D object.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.112-115
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• 2009

The research of climate change impact in hydrometeorology often relies on climate change information. In this paper, neural networks models such as support vector machine neural networks model (SVM-NNM) and multilayer perceptron neural networks model (MLP-NNM) are proposed statistical downscaling of the monthly precipitation. The input nodes of neural networks models consist of the atmospheric meteorology and the atmospheric pressure data for 2 grid points including $127.5^{\circ}E/35^{\circ}N$ and $125^{\circ}E/35^{\circ}N$, which produced the best results from the previous study. The output node of neural networks models consist of the monthly precipitation data for Seoul station. For the performances of the neural networks models, they are composed of training and test performances, respectively. From this research, we evaluate the impact of SVM-NNM and MLP-NNM performances for the downscaling of the monthly precipitation data. We should, therefore, construct the credible monthly precipitation data for Seoul station using statistical downscaling method. The proposed methods can be applied to future climate prediction/projection using the various climate change scenarios such as GCMs and RCMs.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.125-128
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• 2009

The research of climate change impact in hydrometeorology often relies on climate change information. In this paper, neural networks models such as generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM) are proposed statistical downscaling of the daily precipitation. The input nodes of neural networks models consist of the atmospheric meteorology and the atmospheric pressure data for 4 grid points including $127.5^{\circ}E/37.5^{\circ}N$, $127.5^{\circ}E/35^{\circ}N$, $125^{\circ}E/37.5^{\circ}N$ and $125^{\circ}E/35^{\circ}N$, respectively. The output node of neural networks models consist of the daily precipitation data for Seoul station. For the performances of the neural networks models, they are composed of training and test performances, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM performances for the downscaling of the daily precipitation data. We should, therefore, construct the credible daily precipitation data for Seoul station using statistical downscaling method. The proposed methods can be applied to future climate prediction/projection using the various climate change scenarios such as GCMs and RCMs.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문집
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• pp.410-415
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• 2002

In this article, spatial filtering procedures with application to spherical acoustical holography are discussed. Planar and cylindrical holography are the most widely used amongst the various nearfield acoustical holography techniques. However, when the geometry of a source is similar to a sphere, spherical holography may yield better results than other types of holography since there are no errors due to truncation of the sound field in the spherical case. Spatial filtering affects the accuracy of spherical acoustical holography critically, especially in the case of backward projection. Thus spatial filtering is essential for successful application of spherical holography. In the present work, various filtering methods were evaluated in simulations made using sound pressure fields of various types and with different levels of random spatial noise. It was found that a procedure based on eliminating spherical harmonic coefficients that contribute insignificantly to the total sound power of the source gave the best results on average of the different procedures considered here. Spherical holography procedures were also verified experimentally. Reliable results were obtained using the power filtering algorithm. Thus it was concluded that spherical holography combined with power filtering may prove to be a useful tool for noise source identification.

• Ocean Systems Engineering
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• 제7권3호
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• pp.299-318
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• 2017

The paper aims at illustrating several key issues and ongoing efforts for development of a reliable fully-Lagrangian particle-based solver for simulation of hydroelastic slamming. Fluid model is founded on the solution of Navier-Stokes along with continuity equations via an enhanced version of a projection-based particle method, namely, Moving Particle Semi-implicit (MPS) method. The fluid model is carefully coupled with a structure model on the basis of conservation of linear and angular momenta for an elastic solid. The developed coupled FSI (Fluid-Structure Interaction) solver is applied to simulations of high velocity impact of an elastic aluminum wedge and hydroelastic slammings of marine panels. Validations are made both qualitatively and quantitatively in terms of reproduced pressure as well as structure deformation. Several remaining challenges as well as important key issues are highlighted. At last, a recently developed multi-scale MPS method is incorporated in the developed FSI solver towards enhancement of its adaptivity.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권3호
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• pp.156-165
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• 2005

Human being recognizes the physical world by integrating a great variety of sensory inputs, the information acquired by their own action, and their knowledge of the world using hierarchically parallel-distributed mechanism. In this paper, authors propose the sensor fusion system that can recognize multiple 3D objects from 2D projection images and tactile informations. The proposed system focuses on improving recognition performance of 3D objects. Unlike the conventional object recognition system that uses image sensor alone, the proposed method uses tactual sensors in addition to visual sensor. Neural network is used to fuse the two sensory signals. Tactual signals are obtained from the reaction force of the pressure sensors at the fingertips when unknown objects are grasped by four-fingered robot hand. The experiment evaluates the recognition rate and the number of learning iterations of various objects. The merits of the proposed systems are not only the high performance of the learning ability but also the reliability of the system with tactual information for recognizing various objects even though the visual sensory signals get defects. The experimental results show that the proposed system can improve recognition rate and reduce teeming time. These results verify the effectiveness of the proposed sensor fusion system as recognition scheme for 3D objects.