• Journal of the Mineralogical Society of Korea
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• v.23 no.4
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• pp.367-375
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• 2010

Understanding the interactions between earth materials and fluids is essential for studying the diverse geological processes in the Earth's surface and interior. In order to better understand the interactions between earth materials and fluids, we explore the effect of specific surface area and porosity on structural parameters of pore structures. We obtained 3D pore structures, using random packing simulations of porous media composed of single sized spheres with varying the particle size and porosity, and then we analyzed configurational entropy for 2D cross sections of porous media and cube counting fractal dimension for 3D porous networks. The results of the configurational entropy analysis show that the entropy length decreases from 0.8 to 0.2 with increasing specific surface area from 2.4 to $8.3mm^2/mm^3$, and the maximum configurational entropy increases from 0.94 to 0.99 with increasing porosity from 0.33 to 0.46. On the basis of the strong correlation between the liquid volume fraction (i.e., porosity) and configurational entropy, we suggest that elastic properties and viscosity of mantle melts can be expressed using configurational entropy. The results of the cube counting fractal dimension analysis show that cube counting fractal dimension increases with increasing porosity at constant specific surface area, and increases from 2.65 to 2.98 with increasing specific surface area from 2.4 to $8.3mm^2/mm^3$. On the basis of the strong correlation among cube counting fractal dimension, specific surface area, and porosity, we suggest that seismic wave attenuation and structural disorder in fluid-rock-melt composites can be described using cube counting fractal dimension.

• 한국전기화학회:학술대회논문집
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• 2004.04a
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• pp.75-75
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• 2004

• 한국전기화학회:학술대회논문집
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• 2004.04a
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• pp.57-57
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• 2004

• 한국전기화학회:학술대회논문집
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• 2004.10a
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• pp.23-23
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• 2004

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.79-82
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• 2006

최근 사물에 태그를 부착하여 무선으로 사물과 주변의 정보를 감지하는 RFID 기술이 등장하여 IT시장을 선도할 기술로 주목받고 있다. 그 중 국내에서 아마추어용으로 사용되던 433MHz대역이 컨테이너용 RFID 대역으로 지정되면서 국내에서도 활발히 연구가 이루어지고 있으며, 부산항에서 시범 운영하고 있으며 향후 확대 운영할 계획에 있다. 이에 본 논문에서는 프랙탈 이론을 적용하여 433MHz대역의 RFID 태그 안테나를 설계 및 제작하였다. 프랙탈 이론 중 민코스키 곡선을 응용하였고, 중심에 미앤더를 둔 구조로 설계하였다. 또한 접지면을 안테나와 같은 면에 구조로 최종 설계하였다.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.30-38
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• 2007

In this paper, UHF band RFID reader antenna using filbert curve fractal structure and adding the partially grounded plane at the bottom of antenna, which has a resonant frequency at 910MHz, is proposed. Input impedance of antenna is matched with the feed line of 50ohm by varying the length and width of line segment making up the antenna, and by moving the position of via hole. The gain and directivity of antenna is enhanced as varying the dimension of the partially grounded plane and adding the line segment. The size of fabricated antenna is $68mm\times68mm$. The impedance band width(VSWR<2) is $882\sim942MHz$. The return loss and the gain of fabricated antenna are -18.2dB, 5.3dBi at 910MHz.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.538-540
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• 2000

프랙탈 이미지 압축을 적용하는 경우 많은 시간을 필요로 하는 블록의 비교과정에서 블록 정보의 효율적인 처리를 위하여 선형으로 연결된 기존의 블록 정보 저장을 tree 구조의 형태로 저장하는 방법을 제안한다. Tree의 형태로 저장된 블록의 정보는 BFS 탐색을 이용하여 참조, 사용되며 이를 tree의 각 node에 분류된 domain 블록의 개수로 표현하여 기존의 전체 탐색과 비교 분석하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.708-714
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• 2000

In this paper, an one-dimensional VLSI array for high speed processing of fractal image compression algorithm based the quad-tree partitioning method is proposed. First of all, the single assignment code algorithm is derived from the sequential Fisher's algorithm, and then the data dependence graph(DG) is obtained. The two-dimension array is designed by projecting this DG along the optimal direction and the one-dimensional VLSI array is designed by transforming the obtained two-dimensional array. The number of Input/Output pins in the designed one-dimensional array can be reduced and the architecture of process elements(PEs) can he simplified by sharing the input pins of range and domain blocks and internal arithmetic units of PEs. Also, the utilization of PEs can be increased by reusing PEs for operations to the each block-size. For fractal image compression of 512X512gray-scale image, the proposed array can be processed fastly about 67 times more than sequential algorithm. The operations of the proposed one-dimensional VLSI array are verified by the computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5A
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• pp.702-708
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• 2000

In this paper, we designed one-dimensional VLSI array with optimal pipeline period for high speed processing fractal image compression. The algorithm is derived which is suitable for VLSI array from axed block partition algorithm. Also the algorithm satisfies high quality of image and high compression-ratio. The designed VLSI array has optimal pipeline relied because the required processing time of PEs is distributed as same as possible. As this result, we can improve the processing speed up to about 3 times. The number of input/output pins can be reduced by sharing the input/output and arithmetic unit of the domain blocks and the range blocks.

• Economic and Environmental Geology
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• v.29 no.4
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• pp.523-528
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• 1996

In Korean topography the behaviors of random fractals and multifractality are analytically and numerically studied on the mountain heights shown between $128{\sim}129^{\circ}E$ and $37{\sim}38^{\circ}N$. The phase transitions on the fractal structure are approximately found at the critical length $N_c=2000m$ from the values of standard deviations that it varies with both the longitudinal and latitudinal lengths. In the multifractal structure we assume that the mountain heights divided by the intervals of 20 m are located on the horizontal plane in two dimensional square lattice, and estimate the values of the generalized dimension and the scaling exponents by using the the box counting method for the three cases of square area ($1{\times}1km^2$, $2{\times}2km^2$, $4{\times}4km^2$).