• Economic and Environmental Geology
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• v.42 no.3
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• pp.261-272
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• 2009

An experimental study of the accelerated weathering was performed to investigate the variations of physicomechanical properties of deteriorated rocks due to freeze-thaw weathering for the Jurassic granite specimens from Wonju, Gangwon-do. Each complete cycle of freeze and thaw was lasted 24 hours, comprising 2 hours saturating in vacuum chamber, 8 hours freezing at -20$\pm1^{\circ}C$ and 14 hours thawing at room temperature. Freeze-thaw cycles were implemented with measuring the index physical properties as well as geometries of microfractures. The seismic velocity was found to decrease with increasing freeze-thaw cycles. On the other hand, absorption tends to increase with freeze-thaw cycles. In the end, it was concluded that variations of the index properties of deteriorated specimen depend on its initial properties and flaws in rock. The size and density of the traces of the microfracture on slab specimen were changed continuously with increasing freeze-thaw weathering. The results obtained in this study show that the box fractal dimension($D_B$) has the strong capability of quantifying the combined effect of size and density of the microfractures.

• Tunnel and Underground Space
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• v.19 no.2
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• pp.146-157
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• 2009

An experimental study of accelerated weathering on mudstone sample specimens from Haman, Gyeongnam was performed to investigate the variations of physico-mechanical properties of deteriorated rocks due to freeze-thaw weathering. Each complete cycle of freeze and thaw lasted 24 hours, comprising 2 hours of saturating in vacuum chamber, 8 hours of freezing at $-16{\pm}1^{\circ}C$ and 14 hours of thawing at room temperature. Total of 55 cycles of freeze-thaw were completed with measuring the index properties as well as geometries of microfractures. The measured specific gravity and P-wave velocity found to decrease with increasing freeze-thaw cycles. On the other hand, absorption ratio and effective porosity were continuously increased with increasing freeze-thaw cycles. It was found that the index properties of deteriorated sample specimen depend on its initial properties and flaws in rock. The size and density of the traces of the microfracture on slab specimen exhibited abrupt changes after 30 cycles of freeze-thaw weathering. The results obtained in this study show that the box fractal dimension($D_B$) given in this paper has the strong capability of quantifying the size and density of the microfracture.

• Journal of Physiology & Pathology in Korean Medicine
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• v.21 no.2
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• pp.379-386
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• 2007

Hado(河圖) and Laks${\u{\lrcorner}}$(書洛) are the diagrams composed of the symbols of numbers from one to ten. And the eight-trigrams, P'al-gwoe divide into two types one is a priori eight-trigrams (先夭八卦) or the Bok-Hui's eight trigrams(伏羲八卦); and the other is a posterior eight trigrams (後夭八卦) or the king Mun's eight trigrams (文王八卦). Relating these two diagrams of Hado and Laks${\u{\lrcorner}}$ with the two types of eight trigrams, they are said to be a term of Ha-Lak-Hui-Mun (HLHM). Each of HLHM represents the process of creating and changing of 'heaven and Earth' and every beingby the symbols of numbers and trigrams. In other words, each of HLHM symbolizes the origin and the structure of the universe as well as the birth of every life represented in the diagram of theosophany (福智學) or Kabbalah. HLHM are also regarded as the origin of l-ching or Book of Change. Hado produces Laks${\u{\lrcorner}}$ through the principle of yin-yang(陰陽). Laks${\u{\lrcorner}}$ produces a priori eight trigrams through the zigzag shapes which means Heaven and Earth are mutually responding. And a priori eight trigrams produce a posteriori eight trigrams through the triangle principle of connecting Heaven and Earth. In this process, Hado and a priori eight trigrams are respectively prior to Laks${\u{\lrcorner}}$ and a posteriori eight trigrams. HLHM represent fractal shape resembling the symbol of five on the center of Hado, or Hado itself. In the dynamic process of HLHM, a diagram of Circle, Quadrangle, and Triangle (CQT) is produced as follows: Circle, the symbol of 'infinify' or Heaven, represents the origin of life or birth. Hadois the symbol of creation. Quadrangle, the symbol of Earth, represents that Laks${\u{\lrcorner}}$is scattered into four directions of front, back, left, and rifht. Quadrangle, which is immovable, represents materiality. Triangle, being described from the eight trigrams, means the movements of the process of 'mutual inclusion' of Circle and Quadrangle. Triangle also means the process of harmonizing human beings with natural law.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.18 no.3
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• pp.122-130
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• 2013

To examine floc characteristics of cohesive bed sediment of the Yeongsan River estuary, a floc camera system has been developed and utilized to observe flocs under varying conditions. In order to validate the floc camera system, sand particles were passed through 88-125 and $63-88{\mu}m$ sieves and observed within the laboratory. Mean grain size and settling velocities were found to be 102 and $56.2{\mu}m$ and 6.7 and 5.9 mm/s, respectively. Artifacts of particles estimated outside of the sieve range are attributed to being imaged out of the depth of focus. However, as mean grain size and settling velocity of each size class were within the confidence interval, the floc camera system was confidently used to examine cohesive bed sediments of Yeongsan River estuary. The bed sediment sample was prepared with a concentration of 0.1 g/L in 0 psu deionized water. The mean grain size, settling velocity and fractal dimension of flocs were $40.6{\pm}0.66{\mu}m$, 14 mm/s, and 2.86, respectively. Experiments were also conducted using different salinities (10 and 34 psu) and sediment concentrations (0.1 and 0.3 g/L). Despite changing these parameters, the mean observed grain size and settling velocities were found to be the same within the error range of the system. The relatively higher values of settling velocity and fractal dimension are considered a result of the sediment containing relatively small concentrations of organic matter. Moreover, consistent floc size over various grain sizes and concentrations may be the result of insufficient turbulence to aggregate flocs.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.29 no.3
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• pp.101-113
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• 2018

Objectives: The purpose of this study was to investigate whether the neural activity of autism spectrum disorder (ASD) patients is different from that of normal individuals when performing aesthetic judgments. Methods: We recruited typical ASD patients without savant skills (ASD group, n=17) and healthy controls (HC group, n=19) for an functional magnetic resonance imaging study. All subjects were scanned while performing aesthetic judgment tasks on two kinds of artwork (magnificent landscape images and fractal images). Differences in brain activation between the two groups were assessed by contrasting neural activity during the tasks. Results: The aesthetic judgment score for all images was significantly lower in the ASD group than in the HC group. During the aesthetic judgment tasks, the ASD group showed less activation than the HC group in the anterior region of the superior frontal gyrus, and more activation in the temporoparietal area and insula, regardless of the type of images being judged. In addition, during the aesthetic judgment task for the fractal images, the ASD group exhibited greater neural activity in the amygdala and the posterior region of the middle/inferior temporal gyrus (Brodmann area 37) than the HC group. Conclusion: The results of this study suggest that the brain activation patterns associated with aesthetic experiences in ASD patients may differ from those of normal individuals.

• Proceedings of the Korean Vacuum Society Conference
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• 1999.07a
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• pp.190-190
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• 1999

박막 표면에 대한 경원소 분석법인 탄성 되튐 반도법을 개발하여 수소, 탄소, 질소등 분석에 이용하고 있다. 이때 입사 입자로 Cl 9.6MeV를 이용하였는데, 표적 표면에 탄소막이 흡착되는 현상을 발견하였다. cold trap 및 cold finger를 사용하여 진공도를 개선하므로서, 탄소막 흡착의 한 원인으로 알려져 잇는 chamber 주변의 진공도 변화를 시켜보았다. 하지만 전혀 탄소막이 생기지 않는 10-10torr 이하 진공을 만드는 것은 많은 비용과 장비를 필요로 하는 상당히 힘든 작업이어서, 이차적으로 탄소막이 표적 표면에 달라 붙게 하는 원인으로 추정되는 이차 전자의 발생을 고에너지 이온빔으로 조사하였다. 일반적으로 이차전자의 발생은 이온빔과 표적과의 충돌에 의한 고체 표면으로부터의 전자방출 현상으로 오래전부터 연구되어져 왔다. 여기에는 두가지 다른 구조가 존재하는 것으로 알려져 있다. 그 중 하나는 입사 입자의 전하와 표적 표면사이 작용하는 potential 에너지가 표적 표면의 일함수(재가 function) 보다 클 때에 일어나는 potential emission이다. 즉 표적 궤도에 존재하는 전자와 입사 이온빔 사이의 potential 이 표적의 전자를 들뜨게 만들고, 이 potential의 크기가표적의 표면 장벽 potential 보다 충분히 클 뜸 전자가 방출하는 현상을 말한다. 다른 또 하나의 방출구조로는 입사 이온이 표적 표면의 원자와의 충돌에 의해 직접저인 에너지 전달을 통한 전자 방출을 말하는데, 이를 kienetic emission(이하 KE)이라 한다. 본 연구에서는 Tandem Van de graaff 가속기로 고에너지 이온빔을 만들어 Au에 충돌시키므로서 kinetic emission을 통하여 Au에서 발생한는 이차전자의 방출 수율 및 에너지를 측정하였다.장구조로 전체 성장 양식을 예견할 수 있다. 일반적인 경향은 Ep가 커질수록 fractal 성장형태가 되며, Ed가 적을수록 cluster 밀도가 작아지나, 같은 Ed+Ep에 대해서는 동일한 크기의 팔 넓이(수평 수직 방향 cluster 두께)를 가진다. 따라서 실험으로부터 얻은 cluster의 팔 넓이로부터 Ed+Ep 값을 결정할 수 있고, cluster 밀도와 fractal 차원으로부터 각각 Ed와 Ep값을 분리하여 얻을 수 있다. 또한 다층 성장에 대한 거칠기(roughness) 값으로부터 Es값도 구할 수 있다. 양방향 대칭성을 갖지 않은 fcc(110) 표면과 같은 경우, 형태는 다양하지만 동일한 방법으로 추정이 가능하다. (110) 표면의 경우 nearest neighbor 원자가 한 축으로 형성되고 따라서 이 축과 이것과 수직인 축에 대한 상호작용이나 분산 장벽 모두가 비대칭적이다. 따라서 분산 장벽도 x-축, y-축 방향에 따라 분리하여 Edx, E요, Epx, Epy 등과 같이 방향에 따라 다르게 고려해야 한다. 이러한 비대칭적인 분산 장벽을 고려하여 KMC 시뮬레이션을 수행하면 수평축과 수직축의 분산 장벽의 비에 따라 cluster의 두께비가 달라지는 성장을 볼 수 있었고, 한 축 방향으로의 팔 넓이는 fcc(100) 표면의 경우 동일한 Ed+Ep값에 대응하는 팔 넓이와 거의 동일한 결과가 나타나는 것을 볼 수 있다. 따라서 이러한 비대칭적인 모양을 가지는 성장의 경우도 cluster 밀도, cluster 모양, cluster의 양 축 방향 길이 비, 양 축 방향의 평균 팔 넓이로부터 각 축 방향의 분산 장벽을 얻어낼 수 있을 것으로 보인다. 기대할 수 있는 여러 장점들을 보고하고자 한다.성이 우수한 시편일수록 grain의 크기가 큰 것으로 나타났고 결정성이 우수한 시편의 경우에서는 XR

• Journal of the Korean GEO-environmental Society
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• v.12 no.12
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• pp.79-88
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• 2011

Adfreeze bond strength develops upon freezing of pore water within soil and at foundation surface. It has been reported that various factors like temperature, soil type, and pile surface roughness affect adfreeze bond strength. Especially, pile surface roughness has been considered as a primary factor to design pile foundation in frozen ground. It has usually been estimated with fixed correction factors for pile materials. However, even if the pile foundation material is the same, the surface roughness could vary depending on the production circumstances. In this study, laboratory test was carried out to quantitatively analyze the effects of surface roughness on the adfreeze bond strength, and fractal dimension was used as a measure for surface roughness. Test results showed that adfreeze bond strength increased with decreasing temperature, increasing vertical stress and surface roughness. The adfreeze bond strength varies sensitively with surface roughness in the early freezing section of $-2^{\circ}C$, but its sensitivity decreased in the temperature ranging between $-2^{\circ}C$ to $-5^{\circ}C$. The results conclude that the roughness highly affects the frictional resistance of pile surface in frozen ground; however, the roughness does not affect considerably when the temperature drops below about $-2^{\circ}C$.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.341-353
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• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.3A
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• pp.317-324
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• 2000

In this paper, we propose an interpolation technique to rain attenuation data which represents dynamic characteristics by time variations. By using this technique, it is possible to sample the rain attenuation data at an arbitrary time interval, and thus it would play an important role in developing adaptive transmission scheme for countermeasuring rain attenuation. We propose the interpolation technique which can synthesizes rain attenuation data by extracting the most proper parameters required to emulate the dynamic characteristics of rain attenuation. Interpolation results to measured data of I minute time interval will be demonstrated, and it is shown that more exact performance evaluation of adaptive transmission scheme to countermeasure rain attenuation can be achieved.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.365-373
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• 1999

Recently, numerous studies have demonstrated that artificial intelligence such as neural networks can be an alternative methodology for classification problems to which traditional statistical methods have long been applied. In building neural network model, the selection of independent and dependent variables should be approached with great care and should be treated as a model construction process. Irrespective of the efficiency of a learning procedure in terms of convergence, generalization and stability, the ultimate performance of the estimator will depend on the relevance of the selected input variables and the quality of the data used. Approaches developed in statistical methods such as correlation analysis and stepwise selection method are often very useful. These methods, however, may not be the optimal ones for the development of neural network models. In this paper, we propose a genetic algorithms approach to find an optimal or near optimal input variables for neural network modeling. The proposed approach is demonstrated by applications to bankruptcy prediction modeling. Our experimental results show that this approach increases overall classification accuracy rate significantly.