• International Journal of CAD/CAM
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• 제9권1호
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• pp.111-120
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• 2010

In this paper, we propose a volume rendering method using grid computing for large-scale volume data. Grid computing is attractive because medical institutions and research facilities often have a large number of idle computers. A large-scale volume data is divided into sub-volumes and the sub-volumes are rendered using grid computing. When using grid computing, different computers rarely have the same processor speeds. Thus the return order of results rarely matches the sending order. However order is vital when combining results to create a final image. Job-Scheduling is important in grid computing for volume rendering, so we use an obstacle-flag which changes priorities dynamically to manage sub-volume results. Obstacle-Flags manage visibility of each sub-volume when line of sight from the view point is obscured by other subvolumes. The proposed Dynamic Job-Scheduling based on visibility substantially increases efficiency. Our Dynamic Job-Scheduling method was implemented on our university's campus grid and we conducted comparative experiments, which showed that the proposed method provides significant improvements in efficiency for large-scale volume rendering.

• 한국산학기술학회논문지
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• 제18권9호
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• pp.1-8
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• 2017

본 연구의 목적은 물리적 메모리 할당이 어려운 대용량 BIM(Building Information Modeling) 형상 데이터를 처리하기 위한 캐쉬(cache) 구조를 제안한다. 조달청 등 공공기관에서 BIM 발주가 많아짐에 따라 대용량 BIM 형상 데이터를 가시화하고, 계산해야 하는 경우가 많아지고 있다. 규모가 크고 복합적인 시설물의 경우, 렌더링 및 계산해야하는 형상 수가 많아 사용자가 BIM 모델을 검토하고, 단면을 확인하는 데 어려움을 겪는 경우가 있다. 예를 들어, 설계, 검토 협업 시, 대용량 BIM 데이터를 네트워크를 통해 전달받아야 할 경우, 다운로드에 많은 시간이 걸릴 수 있고, 물리적 여유 메모리 한계를 넘어가면, 에러로 가시화나 형상정보 추출이 불가능할 수도 있다. 물리적 메모리가 부족하거나 대역폭이 적은 네트워크 상에서 대용량 BIM 데이터를 활용하기 위해서는, BIM 형상 렌더링 및 계산 시점에 필요한 데이터만 메모리로 캐쉬(cache) 처리하는 것이 유리하다. 이 연구는 물리적 메모리 할당이 어려운 대용량 BIM 형상 데이터를 효과적으로 렌더링하고 계산하기 위한 BIM 형상 캐쉬 구조를 제안한다.

• 지적과 국토정보
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• 제45권1호
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• pp.169-179
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• 2015

최근 IT기술의 발달로 데이터의 양이 급증함에 따라 대용량 데이터를 다루는 빅 데이터 시대가 도래하게 되었다. 다양하고 방대한 빅데이터 를 활용하기 위해서는 대용량 데이터 처리 기술을 필요로 하는데, 이러한 흐름에 따라 공간정보 분야에서도 대용량의 공간정보 데이터 서비스 기술이 요구되고 있다. 따라서 본 연구에서는 국외의 대표적인 공간정보 데이터 서비스 기술을 살펴본 후, 국내의 대표적인 지도 소프트웨어인 브이월드 데스크톱에 적용 가능한 KML 포맷의 대용량 데이터 처리 기술을 개발하였다. 개발된 분할 방법과 도구를 검증하기 위해 대용량의 KML 데이터를 이용하여 테스트를 진행하였고, 인덱스 파일과 분할 파일들이 생성되어 브이월드 데스크톱에서 가시화 되었다.

• 대한의용생체공학회:의공학회지
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• 제21권4호
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• pp.433-439
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• 2000

볼륨 렌더링은 기하학적인 기본 도형으로 모델링하지 않고, 3차원 데이터를 직접 가시화하는 방법이다. 이런 볼륨 렌더링의 특성으로 말미암아 3차원 영상을 도시할 때에, 복잡한 물체의 경우에도 물체의 표면을 상세하게 표현하는데 유리하여 의료 영상을 가시화하는 쪽으로의 적용이 많이 이루어져 왔다. 일반적으로 볼륨 데이터의 크기가 커서 실시간으로 처리하기 쉽지 않기 때문에, 근래에는 이 렌더링 시간을 줄이기 위해서 많은 여러 가지 렌더링 알고리즘이 제안되었다. 본 논문에서는 부호화 되어 있지 않은 볼륨 데이터를 빠르게 렌더링 하기 위해서, 쉬어-왑 분해를 이용하는 블록 기반의 볼륨 렌더링 기법을 제안한다. 이 방법에서는 블록 기반의 데이터와 함께 장기의 영역 분할 데이터를 동시에 이용하여 볼륨 렌더링을 수행하므로써, 부호화되어 있지 않은 데이터에 대해 렌더링 속도를 증가시킨다. 본 논문에서는 3차원 X-ray CT 흉부 영상과 MR 3차원 두부 영상을 렌더링 함으로써 제안한 방법의 성능을 검증하였다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제15권2호
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• pp.184-193
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• 2015

This paper proposes a cost-efficient and automatic method for large data acquisition from a test chip without expensive equipment to characterize random process variation in an integrated circuit. Our method requires only a test chip, a personal computer, a cheap digital-to-analog converter, a controller and multimeters, and thus large volume measurement can be performed on an office desk at low cost. To demonstrate the proposed method, we designed a test chip with a current model logic driver and an array of 128 current mirrors that mimic the random process variation of the driver's tail current mirror. Using our method, we characterized the random process variation of the driver's voltage due to the random process variation on the driver's tail current mirror from large volume measurement data. The statistical characteristics of the driver's output voltage calculated from the measured data are compared with Monte Carlo simulation. The difference between the measured and the simulated averages and standard deviations are less than 20% showing that we can easily characterize the random process variation at low cost by using our cost-efficient automatic large data acquisition method.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2007년도 학술대회 1부
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• pp.982-987
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• 2007

The necessity of data compression scheme for volume data has been increased because of the increase of data capacity and the amount of network uses. Now we have various kinds of compression schemes, and we can choose one of them depending on the data types, application fields, the preferences, etc. However, the capacity of data which is produced by application scientists has been excessively increased, and the format of most scientific data is 3D volume. For 2D image or 3D moving pictures, many kinds of standards are established and widely used, but for 3D volume data, specially time-varying volume data, it is very difficult to find any applicable compression schemes. In this paper, we present a compression scheme for encoding time-varying volume data. This scheme is aimed to encoding time-varying volume data for visualization. This scheme uses MPEG's I- and P-frame concept for raising compression ratio. Also, it transforms volume data using Daubechies D4 filter before encoding, so that the image quality is better than other wavelet-based compression schemes. This encoding scheme encodes time-varying volume data composed of single precision floating-point data. In addition, this scheme provides the random reconstruction accessibility for an unit, and can be used for compressing large time-varying volume data using correlation between frames while preserving image qualities.

• 천문학회보
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• 제45권1호
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• pp.29.3-29.3
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• 2020

Cosmology is a study to understand the origin, fundamental property, and evolution of the universe. Nowadays, many observational data of galaxies have become available, and one needs large-volume numerical simulations with good quality of the spatial distribution for a fair comparison with observation data. On the other hand, since galaxies' evolution is affected by both gravitational and baryonic effects, it is nontrivial to populate galaxies only by N-body simulations. However, full hydrodynamic simulations with large volume are computationally costly. Therefore, alternative galaxy assignment methods to N-body simulations are necessary for successful cosmological studies. In this talk, I would like to introduce the MBP-galaxy abundance matching. This novel galaxy assignment method agrees with the spatial distribution of observed galaxies between 0.1Mpc ~ 100Mpc scales. I also would like to introduce mock galaxy catalogs of the Horizon Run 4 and Multiverse simulations, large-volume cosmological N-body simulations done by the Korean community. Finally, I would like to introduce some recent works with those mock galaxies used to understand our universe better.

• 한국CDE학회논문집
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• 제2권1호
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• pp.11-18
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• 1997

Scientific volume visualization addresses the representation, manipulation, and rendering of volumetric data sets, providing mechanisms for looking closely into structures and understanding their complexity and dynamics. In the past several years, a tremendous amount of research and development has been directed toward algorithms and data modeling methods for a scientific data visualization. But there has been very little work on developing a mathematical volume model that feeds this visualization. Especially, in flow visualization, the volume model has long been required as a guidance to display the very large amounts of data resulting from numerical simulations. In this paper, we focus on the mathematical representation of volumetric data sets and the method of extracting meaningful information from the derived volume model. For this purpose, a B-spline volume is extended to a high dimensional trivariate model which is called as a flow visualization model in this paper. Two three-dimensional examples are presented to demonstrate the capabilities of this model.

• Journal of Nutrition and Health
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• 제27권8호
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• pp.856-863
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• 1994

To develop a optimized method for educing the errors associated with the estimation of portion size of foods, fuzzy-dta processing of portion size was performed. Cooked-rice was chosen as a food item. The experiment was conducted in two parts. First, to study the conceptions of respondents to bowl size(large, medium, small), 11 bowls of different size and shape were used and measured the actual weights of cooked-rice. Second, to study the conceptions of respondents to volume(1, 1/2, 1/3, 1/4), 16 different volumes of cooked-rice in bowls of same size and shape were used. Respondents for this study were 31 graduate students. After collecting the data of respondents to size and volume, fuzzy sets of size and volume were produced. The critical values were calculated by defuzzification(mean of maximum method, center of area method). The differences of the weights of cooked-rice in various bowl size and volume between the critical values and the calculated values by average portion size using in conventional methods were compared. The results hows large inter-subject variation in conception to bowl size, especially in large size. However, conception of respondents to volume is relatively accurate. Conception to bowl size seems to be influenced by bowl shape. Considering that the new fuzzy set was calculated by cartesian product(bowl size and volume), bowl shape should be considered in estimation of bowl size to make more accurate fuzzy set for cooked-rice portion size. The limitations of this study were discussed. If more accurate data for size and volume of many other food items are collected by the increased number of respondents, reducing the errors associated with the estimation of portion size of foods and rapid processing will be possible by constructing computer processing systems.

• 정보처리학회논문지A
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• 제13A권7호
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• pp.639-646
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• 2006

데이터 압축 기술은 대용량의 데이터를 효율적으로 저장하고 전송할 수 있게 해주는 기술로, 요구되는 데이터의 용량이 커지고 네트워크의 트래픽이 증가함에 따라 그 중요도가 점점 더 높아지고 있다. 특히 다양한 응용과학과 공학 분야에서 산출되는 볼륨 데이터는 컴퓨팅 기술의 발전에 힘입어 그 용량이 점점 더 증가하는 추세에 있다. 본 논문에서는 Daubechies 웨이블릿 변환을 적용해서 볼륨 데이터를 압축하는 기법을 제안한다. 구현된 D4 웨이블릿 필터 기반 압축 기법은 3차원 볼륨 데이터에 대한 손실 압축과 블록 단위의 무작위 추출 복원을 지원한다. 본 기법은 기존의 Harr 필터를 이용한 압축 방식에 비해 복원 데이터의 손실율이 낮기 때문에, 정밀한 복원 영상이 중요시되는 대용량 데이터의 압축 및 인터렉티브 가시화 응용에 유용하게 사용될 수 있다.