• Title/Summary/Keyword: box-counting

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Studies on Random Fractal and Multifractal Structures in Korean Topography (한국지형에서의 랜덤 프랙탈과 멀티프랙탈구조의 연구)

  • Kim, Kyungsik;Kong, Young Sae
    • 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 ($1{\times}1km^2$, $2{\times}2km^2$, $4{\times}4km^2$).

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A Study on the Fractal Attractor Creation and Analysis of the Printed Korean Characters

  • Shon, Young-Woo
    • Journal of information and communication convergence engineering
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    • v.1 no.1
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    • pp.53-57
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    • 2003
  • Chaos theory is a study researching the irregular, unpredictable behavior of deterministic and non-linear dynamical system. The interpretation using Chaos makes us evaluate characteristic existing in status space of system by tine series, so that the extraction of Chaos characteristic understanding and those characteristics enables us to do high precision interpretation. Therefore, This paper propose the new method which is adopted in extracting character features and recognizing characters using the Chaos Theory. Firstly, it gets features of mesh feature, projection feature and cross distance feature from input character images. And their feature is converted into time series data. Then using the modified Henon system suggested in this paper, it gets last features of character image after calculating Box-counting dimension, Natural Measure, information bit and information dimension which are meant fractal dimension. Finally, character recognition is performed by statistically finding out the each information bit showing the minimum difference against the normalized pattern database. An experimental result shows 99% character classification rates for 2,350 Korean characters (Hangul) using proposed method in this paper.

Fractal Structure of the Stock Markets of Leading Asian Countries

  • Gunay, Samet
    • East Asian Economic Review
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    • v.18 no.4
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    • pp.367-394
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    • 2014
  • In this study, we examined the fractal structure of the Nikkei225, HangSeng, Shanghai Stock Exchange and Straits Times Index of Singapore. Empirical analysis was performed via non-parametric, semi-parametric long memory tests and also fractal dimension calculations. In order to avoid spurious long memory features, besides the Detrended Fluctuations Analysis (DFA), we also used Smith's (2005) modified GPH method. As for fractal dimension calculations, they were conducted via Box-Counting and Variation (p=1) tests. According to the results, while there is no long memory property in log returns of any index, we found evidence for long memory properties in the volatility of the HangSeng, the Shanghai Stock Exchange and the Straits Times Index. However, we could not find any sign of long memory in the volatility of Nikkei225 index using either the DFA or modified GPH test. Fractal dimension analysis also demonstrated that all raw index prices have fractal structure properties except for the Nikkei225 index. These findings showed that the Nikkei225 index has the most efficient market properties among these markets.

Evaluation of the Effect of using Fractal Feature on Machine learning based Pancreatic Tumor Classification (기계학습 기반 췌장 종양 분류에서 프랙탈 특징의 유효성 평가)

  • Oh, Seok;Kim, Young Jae;Kim, Kwang Gi
    • Journal of Korea Multimedia Society
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    • v.24 no.12
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    • pp.1614-1623
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    • 2021
  • In this paper, the purpose is evaluation of the effect of using fractal feature in machine learning based pancreatic tumor classification. We used the data that Pancreas CT series 469 case including 1995 slice of benign and 1772 slice of malignant. Feature selection is implemented from 109 feature to 7 feature by Lasso regularization. In Fractal feature, fractal dimension is obtained by box-counting method, and hurst coefficient is calculated range data of pixel value in ROI. As a result, there were significant differences in both benign and malignancies tumor. Additionally, we compared the classification performance between model without fractal feature and model with fractal feature by using support vector machine. The train model with fractal feature showed statistically significant performance in comparison with train model without fractal feature.

Analysis on Antifungal Activity of Paulownia-Wood Storage Box and Application of Natural Biocide for the Activity Enhancement (오동나무상자의 항균활성 분석 및 활성 증진을 위한 천연 살생물제 적용연구)

  • Chung, Yong-Jae;Kang, So-Yeong;Choi, Yun-A
    • Journal of Conservation Science
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    • v.24
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    • pp.75-83
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    • 2008
  • In order to assess antifungal activity of a wooden storage box, which was made of Paulownia tomentosa and used for keeping ancient documents, antifungal activity of volatile organic compounds emitted from the box was investigated along with qualitative analysis on major substances of the compounds. After collecting floating microorganisms inside air tester, the fungal activity was assessed by counting the number of colonies growing on TSA media. Compared to the control which collected 85 colonies from outdoor, 72 colonies were observed showing reduction rate of 14.82%. Through GC/MS and TDS system analysis, limonene was detected from the volatile organic compounds as characteristic features. When the fungal activity was assessed through fumigation by adding natural biocide BI and BII containing eugenol and anethole as major substances, both biocides showed a strong fungal activity with respectively 92.6%(inside the box) and 99.9%(outdoor) of reduction rate. Although these results didn't clarify antifungal activity of the volatile organic compounds emitted from the Paulownia-wood storage box and their functional components, it was at least confirmed that there is application possibility of natural biocide to use for preservation of ancient documents with increased efficiency in controlling pests of wooden storage boxes.

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The Analysis of Tidal Channel Development Using Fractal (프랙탈 기법을 이용한 조류로 발달 양상의 분석)

  • Eom, Jin-Ah;Lee, Yoon-Kyung;Ryu, Joo-Hyung;Won, Joong-Sun;Choi, Jung-Hyun
    • Korean Journal of Remote Sensing
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    • v.23 no.2
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    • pp.131-135
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    • 2007
  • The tidal channel is influenced by sediment type, grain size, grain composition and tidal currents in tidal flat. The development of tidal channel including density, shape and order can be used to analyze the characteristics of tidal channel. The quantitative investigation to the tidal channel is insufficiency. In this paper, we represented the fractal analysis method according to the quantitatively analysis in tidal channel and compared with the different intertidal channel patterns. The tidal channel was extracted from the IKONOS image of the southern part of the Kanghwa-do. We used the Box-counting method to estimate fractal dimensions for each tidal channel. As a result, the fractal dimension values (D) were 1.31 in the southern Kanghwa-Do. Linear pattern and less dense channel development area had low D values (from 1.0563 to 1.0672). Dendritic pattern and dense channel development area had high D values (from 1.2550 to 1.3016). In other words, fractal dimension values had difference about 0.2 values according to the characteristic of tidal channel development. We concluded that fractal analysis can be able to quantitatively classification in tidal channel.

Feature Extraction from the Strange Attractor for Speaker Recognition (화자인식을 위한 어트랙터로 부터의 음성특징추출)

  • Kim, Tae-Sik
    • The Journal of the Acoustical Society of Korea
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    • v.13 no.2E
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    • pp.26-31
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    • 1994
  • A new feature extraction technique utilizing strange attractor and artificial neural network for speaker recognition is presented. Since many signals change their characteristics over long periods of time, simple time-domain processing techniques should e capable of providing useful information of signal features. In many cases, normal time series can be viewed as a dynamical system with a low-dimensional attractor that can be reconstructed from the time series using time delay. The reconstruction of strange attractor is described. In the technique, the raw signal will be reproduced into a geometric three dimensional attractor. Classification decision for speaker recognition is based upon the processing or sets of feature vectors that are derived from the attractor. Three different methods for feature extraction will be discussed. The methods include box-counting dimension, natural measure with regular hexahedron and plank-type box. An artificial neural network is designed for training the feature data generated by the method. The recognition rates are about 82%-96% depending on the extraction method.

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Changes in the fractal dimension of peri-implant trabecular bone after loading: a retrospective study

  • Mu, Teh-Jing;Lee, Dong-Won;Park, Kwang-Ho;Moon, Ik-Sang
    • Journal of Periodontal and Implant Science
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    • v.43 no.5
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    • pp.209-214
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    • 2013
  • Purpose: To assess bony trabecular changes potentially caused by loading stress around dental implants using fractal dimension analysis. Methods: Fractal dimensions were measured in 48 subjects by comparing radiographs taken immediately after prosthesis delivery with those taken 1 year after functional loading. Regions of interest were isolated, and fractal analysis was performed using the box-counting method with Image J 1.42 software. Wilcoxon signed-rank test was used to analyze the difference in fractal dimension before and after implant loading. Results: The mean fractal dimension before loading ($1.4213{\pm}0.0525$) increased significantly to $1.4329{\pm}0.0479$ at 12 months after loading (P<0.05). Conclusions: Fractal dimension analysis might be helpful in detecting changes in peri-implant alveolar trabecular bone patterns in clinical situations.

The Analysis of Tidal Channel Development Using Fractal (프랙탈 기법을 이용한 조류로 발달 양상의 분석)

  • Choi, Jung-Hyun;Eom, Jin-Ah;Lee, Yoon-Kyung;Ryu, Joo-Hyung;Won, Joong-Sun
    • Proceedings of the KSRS Conference
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    • 2007.03a
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    • pp.262-266
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    • 2007
  • 조간대의 생물상과 조류로는 조간대 내의 모래나 펄을 구성하는 입자의 크기와 조성에 의하여 많은 영향을 받는다. 이런 조류로의 특성을 파악하기 위하여 전통적으로 현장조사를 실시하였으나 이 방법은 짧은 조간대의 노출시간 동안 넓은 조간대 지역을 파악하기 힘든 단점이 있다. 이러한 단점을 극복하기 위하여 최근 국내외적으로 위성자료와 현장조사롤 통해 조간대내의 조류로 발달을 연구하는 노력이 활발히 진행 중 이다. 본 연구에서는 프랙탈 이론을 적용하여 발달양상이 다른 두 지역의 조류로의 발달정도를 정량적인 값으로 나타내었다. 본 연구에서는 강화도 남단 조간대에 대하여 IKONOS 영상에서 조류로를 추출한 뒤, 프랙탈 분석방법 중 2차원 분석에 많이 사용되는 box counting 방법을 적용하여 프랙탈 차원을 구하였다. 분석 결과, 강화도 남단 조간대 전체 지역에 대한 프랙탈 차원 값은 약 1.31 로 나타났다. 조류로의 지선이 단순하며 남북으로 수직방향으로 발달한 지역은 프랙탈 차원 값이 $1.0563{\sim}1.0672$로 나타났으며,조류로의 지선이 발달하고 매우 복잡한 형태를 보이는 곳은 프랙탈 차원 값이 $1.255{\sim}1.3016$로 나타나는 것을 알 수 있었다. 실제 해안선과 같은 곡선의 경우 프랙탈 차원 값이 $1.1{\sim}1.3$ 정도 나타나는데 본 연구에서 얻어진 프랙탈 차원 값을 보면 매우 흡사하게 나온 것을 알 수가 있다. 또한, 양상이 다른 두 지역의 프랙탈 차원 값이 약 0.2 정도 차이를 나타내는 것을 알 수가 있다. 이 결과는 영상에서의 조류로 발달의 복잡성에 대한 구분을 뒷받침 할 수 있을 것으로 생각한다.

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The Remark on the Fractal Dimensions (후랙탈 차원에 관하여)

  • Kim, Yong Sung;Yoo, Heung Sang;Kang, Ji Ho
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.19 no.37
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    • pp.233-240
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    • 1996
  • Julia set, Fatou set와 Mandelbrot set 가 컴퓨터에 의하여 도형화된 후부터 혼돈 역학체계 (chaotic dynamical system)에 대한 연구가 모든 학계에 비상한 관심을 모으고 있으며 특히 수학자들에 의하여 많은 연구가 이루어지고 있다. 또한 혼돈 역학체계를 기초로 하여 컴퓨터 그래픽스를 이용한 후랙탈(fractal)들의 매혹적인 시각적 표현으로 인하여 최근들어 과학자들 뿐 아니라 일반대중의 후랙탈에 대한 관심이 매우 높아지고 있다. 후랙탈이란 말은 라틴어 fractus(부서진 상태를 뜻함)에서 유래되었으며 1975년 Mandelbrot가 수학 및 자연계의 비정규적 패턴들에 대한 체계적 고찰을 담은 자신의 에세이의 표제를 주기 위해서 만들었다(〔6〕). 후랙탈을 기술하는데 있어서 가장 중요한 양은 차원(dimension)으로, 예컨데 Cantor 1/3 집합은 길이 1인 선분으로부터 시작하야 매 단계마다 모든 선분들의 가운데 1/3을 잘라내는 것을 무한히 반복함으로써 얻어지는데 이 집합의 Lebesgue measure는 0이지만 후랙탈 차원은 log2/log3 로 정수차원이 아닌 실수차원을 갖으며 또한 Cantor 1/3집합은 연속이 아니면서 점도 선도 아닌 집합인 것이다. 이 논문에서는 Box counting dimension 과 Hausdorff dimension에 대한 몇 가지 정의를 하고 정리 2.6, 정리2.7 및 정리 3.3을 증명함으로써 어떤 성질을 갖는 후랙탈의 가장 중요한 양인 후랙탈 차원에 대하여 논의 하고자 한다.

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