• Title/Summary/Keyword: Fractal model

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Design Principles of Fractal Geometry as Complex System (복잡계 구조로서 프랙탈 기하학의 조형원리)

  • Lim, Eun-Young
    • Proceedings of the Korean Institute of Interior Design Conference
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    • 2004.11a
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    • pp.195-196
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    • 2004
  • Fractal geometry based upon the latest complex theory shows different features of design pattern quite different from the past. It is not yet sure which kind of effects it would bring about in the future, we think that it would help to create various spaces and organic design vision. Therefore we will look into the significances and adaptabilities in space design by studying fractal design principles of today's new model in space design

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Simulation Uleung Island By The Statistical Fractals (프랙탈 기법에 의한 울릉도 형상화 사례 연구)

  • 노용덕
    • Journal of the Korea Society for Simulation
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    • v.4 no.1
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    • pp.113-119
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    • 1995
  • In 3D computer graphics, fractal techniques have been applied to terrain models. Even though fractal models have become popular for recreating a wide variety of the shapes found in nature, a specific 3D terrain model such as Uleung Island could not be formulated by statistical fractals easily owing to the random effects. However, by locating the midpoints on the edges and the surface of a specific terrain such as Uleung Island, a similar shape of the terrain model can be simulated. This paper shows the way of simulating 3D Uleung Island terrain model by the statistical fractals wherein the subdivision algorithm is used.

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Fractal Analysis of Tidal Channel using High Resolution Satellite Image (고해상도 위성 영상을 이용한 조류로의 프랙털 분석)

  • Eom, Jin-Ah;Lee, Yoon-Kyung;Ryu, Joo-Hyung;Won, Joong-Sun
    • Korean Journal of Remote Sensing
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    • v.23 no.6
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    • pp.567-573
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    • 2007
  • Tidal channel development is influenced by sediment type, grain size, composition and tidal current. Tidal channels are usually characterized by channel formation, density and shape. Quantitative analysis of tidal channels using remotely sensed data have rarely been studied. The objective of this study is to quantify tidal channels in terms of fractal dimension and compare different inter-tidal channel patterns and compare with DEM (Digital Elevation Model). For the fractal analysis, we used box counting method which had been successfully applied to streams, coastlines and others linear features. For a study, the southern part of Ganghwado tidal flats was selected which know for high dynamics of tidal currents and vast tidal flats. This area has different widths and lengths of tidal channels. IKONOS was used for extracting tidal channels, and the box counting method was applied to obtain fractal dimensions (D) for each tidal channel. Yeochari area where channels showed less dense development and low DEM had low fractal dimenwion near $1.00{\sim}1.20$. Area (near Donggumdo and Yeongjongdo) of dendritic channel pattern and high DEM resulted in high fractal dimension near $1.20{\sim}1.35$. The difference of fractal dimensions according to channel development in tidal flats is relatively large enough to use as an index for tidal channel classification. Therefore we could conclude that fractal dimension, channel development and DEM in tidal channel has high correlation. Using fractal dimension, channel development and DEM, it would be possible to quantify the tidal channel development in association with surface characteristics.

Analysis of Electromagnetic Wave Scattering From a Perfectly Conducting One Dimensional Fractal Surface Using the Monte-Carlo Moment Method (몬테칼로 모멘트 방법을 이용한 1차원 프랙탈 완전도체 표면에서의 전자파 산란 해석)

  • 최동묵;김채영
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.39 no.12
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    • pp.566-574
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    • 2002
  • In this paper, the scattered field from a perfectly conducting fractal surface by the Monte-Carlo moment method was computed. An one-dimensional fractal surface was generated by using the fractional Brownian motion model. Back scattering coefficients are calculated with different values of the spectral parameter(S$\_$0/), and fractal dimension(D) which determine characteristics of the fractal surface. The number of surface realization for the computed field, the point number, and the width of surface realization are set to be 80, 2048, and 64L, respectively. In order to verify the computed results these results are compared with those of small perturbation methods, which show good agreement between them.

Elevation Restoration of Natural Terrains Using the Fractal Technique (프랙탈 기법을 이용한 자연지형의 고도 복원)

  • Jin, Gang-Gyoo;Kim, Hyun-Jun
    • Journal of Navigation and Port Research
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    • v.35 no.1
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    • pp.51-56
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    • 2011
  • In this paper, we presents an algorithm which restores lost data or increases resolution of a DTM(Digital terrain model) using fractal theory. Terrain information(fractal dimension and standard deviation) around the patch to be restored is extracted and then with this information and original data, the elevations of cells are interpolated using the random midpoint displacement method. The results of the proposed algorithm are compared with those of the bilinear and bicubic methods on a fractal terrain map.

Fractal-Based Interpolation of Sea Floor Terrains (프랙탈에 기초한 해저지형의 보간)

  • Lee, Hyun-Shik;Park, Dong-Jin;Jin, Gang-Gyoo
    • Journal of Navigation and Port Research
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    • v.33 no.6
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    • pp.451-456
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    • 2009
  • In this paper, we presents an algorithm which generates its high-resolution DTM using a low-resolution DTM of the sea floor terrain and fractal theory. The fractal dimension of each patch region divided from the DTM is extracted and then with this information and original data, each cell region in the patch is interpolated using the midpoint displacement method and a median filter is incorporated to generate natural and smooth sea floor surface. The effectiveness of the proposed algorithm is tested on a fractal terrain map.

Spatial Estimation of soil roughness and moisture from Sentinel-1 backscatter over Yanco sites: Artificial Neural Network, and Fractal

  • Lee, Ju Hyoung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.125-125
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    • 2020
  • European Space Agency's Sentinel-1 has an improved spatial and temporal resolution, as compared to previous satellite data such as Envisat Advanced SAR (ASAR) or Advanced Scatterometer (ASCAT). Thus, the assumption used for low-resolution retrieval algorithms used by ENVISAT ASAR or ASCAT is not applicable to Sentinel-1, because a higher degree of land surface heterogeneity should be considered for retrieval. The assumption of homogeneity over land surface is not valid any more. In this study, considering that soil roughness is one of the key parameters sensitive to soil moisture retrievals, various approaches are discussed. First, soil roughness is spatially inverted from Sentinel-1 backscattering over Yanco sites in Australia. Based upon this, Artificial Neural Networks data (feedforward multiplayer perception, MLP, Levenberg-Marquadt algorithm) are compared with Fractal approach (brownian fractal, Hurst exponent of 0.5). When using ANNs, training data are achieved from theoretical forward scattering models, Integral Equation Model (IEM). and Sentinel-1 measurements. The network is trained by 20 neurons and one hidden layer, and one input layer. On the other hand, fractal surface roughness is generated by fitting 1D power spectrum model with roughness spectra. Fractal roughness profile is produced by a stochastic process describing probability between two points, and Hurst exponent, as well as rms heights (a standard deviation of surface height). Main interest of this study is to estimate a spatial variability of roughness without the need of local measurements. This non-local approach is significant, because we operationally have to be independent from local stations, due to its few spatial coverage at the global level. More fundamentally, SAR roughness is much different from local measurements, Remote sensing data are influenced by incidence angle, large scale topography, or a mixing regime of sensors, although probe deployed in the field indicate point data. Finally, demerit and merit of these approaches will be discussed.

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Compressive behavior of concrete under high strain rates after freeze-thaw cycles

  • Chen, Xudong;Chen, Chen;Liu, Zhiheng;Lu, Jun;Fan, Xiangqian
    • Computers and Concrete
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    • v.21 no.2
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    • pp.209-217
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    • 2018
  • The dynamic compressive behavior of concrete after freezing and thawing tests are investigated by using the split Hopkinson pressure bar (SHPB) technique. The stress-strain curves of concrete under dynamic loading are measured and analyzed. The setting numbers of freeze-thaw cycles are 0, 25, 50, and 75 cycles. Test results show that the dynamic strength decreases and peak strain increases with the increasing of freeze-thaw cycles. Based on the Weibull distribution model, statistical damage constitutive model for dynamic stress-strain response of concrete after freeze-thaw cycles was proposed. At last, the fragmentation test of concrete subjected to dynamic loading and freeze-thaw cycles is carried out using sieving statistics. The distributions of the fragment sizes are analyzed based on fractal theory. The fractal dimensions of concrete increase with the increasing of both freeze-thaw cycle and strain rate. The relations among the fractal dimension, strain rates and freeze-thawing cycles are developed.

A Study on Design of Dynamic weaving Framework using Mixin class in Fractal component model (FCM환경에서 혼합클래스를 이용한 동적 위빙 프레임워크 설계에 관한 연구)

  • Park Jea-Youn;Song Young-Jae
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07b
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    • pp.397-399
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    • 2005
  • 기존의 컴포넌트 모델에서는 컴포넌트 사용과 설정의 분리가 용이하지 않아 개발자가 제약사항(처리시간과 메모리)간의 트레이드 오프(trade-off)를 고려할 수 없을 뿐만 아니라 AOP를 적용하기 힘들다. 본 논문에서는 제어인터페이스를 임의적으로 추가할 수 있는 FCM(fractal component model)을 사용하여 aspect을 적용하였고, 런타임시 비기능적인 속성을 효율적으로 재구성하는 동적 위빙(dynamic weaving)을 지원하기 위해서, fractal component의 제어기능을 담당하는 membrane에 있는 구성요소 중 제어 객체(control object)와 인터셉터 객체(interceptor object)를 간단하게 선택하고 구성하기 위해 혼합클래스를 사용하는 프레임워크를 제안한다. 또한 aspect의 재사용성을 높이기 위해, AspectDataBase를 프레임워크에 설계하였다.

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Goal Regulation Mechanism through Reinforcement Learning in a Fractal Manufacturing System (FrMS) (프랙탈 생산시스템에서의 강화학습을 통한 골 보정 방법)

  • Sin Mun-Su;Jeong Mu-Yeong
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.05a
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    • pp.1235-1239
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    • 2006
  • Fractal manufacturing system (FrMS) distinguishes itself from other manufacturing systems by the fact that there is a fractal repeated at every scale. A fractal is a volatile organization which consists of goal-oriented agents referred to as AIR-units (autonomous and intelligent resource units). AIR-units unrestrictedly reconfigure fractals in accordance with their own goals. Their goals can be dynamically changed along with the environmental status. Since goals of AIR-units are represented as fuzzy models, an AIR-unit itself is a fuzzy logic controller. This paper presents a goal regulation mechanism in the FrMS. In particular, a reinforcement learning method is adopted as a regulating mechanism of the fuzzy goal model, which uses only weak reinforcement signal. Goal regulation is achieved by building a feedforward neural network to estimate compatibility level of current goals, which can then adaptively improve compatibility by using the gradient descent method. Goal-oriented features of AIR-units are also presented.

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