• 제목/요약/키워드: Fractal Analysis

검색결과 330건 처리시간 0.027초

보행속도변화에 따른 인지 과제 수행이 보행수 변동성에 미치는 영향 (Effects of Cognitive Task on Stride Rate Variability by Walking Speeds)

  • 최진승;유지혜;김형식;정순철;이정한;이봉수;탁계래
    • 대한의용생체공학회:의공학회지
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    • 제27권6호
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    • pp.323-331
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    • 2006
  • The purpose of this study was to investigate the effect of performing a cognitive task during treadmill walking on the stride rate variability. Ten university students(age $24.0{\pm}0.25$, height $172{\pm}3.1cm$, weight $66{\pm}5.3kg$) were participated in dual task experiments which consist of both walking alone and walking with a cognitive task. Two-back task was selected for the cognitive task since it did not have learning effect during the experimental procedure.3D motion analysis system was used to measure subject's position data by changing walking speed with 4.8, 5.6, 6.4, 6.8, and 7.2 km/hr. Stride rate was calculated by the time between heel contact and heel contact. Accuracy rate of a cognitive task during walking, coefficient of variance, allometric scaling methods and Fano factor were used to estimated the stride rate variability. As the walking speed increased, accuracy rate decreased and the logarithmic value of Fano factor increased which showed the statistical difference. Thus it can be concluded that the gait control mechanism is distracted by the secondary attention focus which is the cognitive task ie. two-back task. Further study is needed to clarify this by increasing the number of subject and experiment time.

강우의 시공간적 멀티프랙탈 특성에 기반을 둔 강우다운스케일링 기법의 한반도 호우사상에 대한 적용성 평가 (Applicability of a Space-time Rainfall Downscaling Algorithm Based on Multifractal Framework in Modeling Heavy Rainfall Events in Korean Peninsula)

  • 이동률;이진수;김동균
    • 한국수자원학회논문집
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    • 제47권9호
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    • pp.839-852
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    • 2014
  • 본 연구에서는 강우의 시공간적 멀티프랙탈 특성에 기반을 둔 다운스케일링 알고리즘(RDSTMF-Rainfall Downscaling in Space-Time Multifractal Framework)을 한반도에 적용하여 그 적용성을 살펴보았다. 이를 위하여 2008년부터 2012년까지 우리나라에 호우주의보를 일으킨 8개의 이벤트에 대한 레이더강우자료를 분석하여 각 이벤트에 대한 멀티프랙탈 지수를 판별하였으며, 이에 근거하여 RDSTMF의 모수들을 산정하고 이 모수들과 시공간강우장의 평균강우량과의 관계를 도출하였다. 이 관계에 근거하여 RDSTMF를 사용하여 가상의 시공간강우장을 생성, 관측 시공간 강우장과 비교하였다. 비교 결과, RDSTMF를 사용하여 생성된 가상의 시공간 강우장은 관측 시공간 강우장의 멀티프랙지수를 3차 모멘트까지 정확히 모사함을 확인하였으며, 누적분포함수 또한 비교적 정확히 모사함을 확인하였다.

Review of Soil Structure Quantification from Soil Images

  • Chun, Hyen-Chung;Gimenez, Daniel;Yoon, Sung-Won;Park, Chan-Won;Moon, Yong-Hee;Sonn, Yeon-Kyu;Hyun, Byung-Keun
    • 한국토양비료학회지
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    • 제44권3호
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    • pp.517-526
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    • 2011
  • Soil structure plays an important role in ecological system, since it controls transport and storage of air, gas, nutrients and solutions. The study of soil structure requires an understanding of the interrelations and interactions between the diverse soil components at various levels of organization. Investigations of the spatial distribution of pore/particle arrangements and the geometry of soil pore space can provide important information regarding ecological or crop system. Because of conveniences in image analyses and accuracy, these investigations have been thrived for a long time. Image analyses from soil sections through impregnated blocks of undisturbed soil (2 dimensional image analyses) or from 3 dimensional scanned soils by computer tomography allow quantitative assessment of the pore space. Image analysis techniques can be used to classify pore types and quantify pore structure without inaccurate or hard labor in laboratory. In this paper, the last 50 years of the soil image analyses have been presented and measurements on various soil scales were introduced, as well. In addition to history of image analyses, a couple of examples for soil image analyses were displayed. The discussion was made on the applications of image analyses and techniques to quantify pore/soil structure.

Wavelet Thresholding Techniques to Support Multi-Scale Decomposition for Financial Forecasting Systems

  • Shin, Taeksoo;Han, Ingoo
    • 한국데이타베이스학회:학술대회논문집
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    • 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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    • pp.175-186
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    • 1999
  • Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

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Wavelet Thresholding Techniques to Support Multi-Scale Decomposition for Financial Forecasting Systems

  • Shin, Taek-Soo;Han, In-Goo
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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    • pp.175-186
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    • 1999
  • Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

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음의 시각화와 그 표현의 경향 (Trend analysis and shapes of the visual expressions of the sounds)

  • 김민호;정성환;강민수
    • 디자인학연구
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    • 제16권3호
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    • pp.101-110
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    • 2003
  • 인간은 자연현상으로 발생되는 소리와 인공적으로 발생되는 소리 속에 살고 있다. 인간의 생물학적 행동을 유발시키는 것 또한 소리이다. 감각기관 즉, 청각으로만 인식할 수 있는 소리의 또 다른 표현은 예술의 형식을 통해서 가능하다. 음악과 미술은 같은 감정을 표현하는 예술호서 표현방법만 다를 뿐 둘 모두 우뇌(右惱, dextrocerebral)를 사용하고 직관력이 필요하다는 공통점을 가지고 있다. 이런 관계로 지금까지 음과 시각예술을 접목하려는 시도가 계속되어 왔으며, 주관적인 해석의 예술적 작품에서 컴퓨터를 이용한 작품에 이르기까지 음의 시각화 실험은 계속 시도되어지고 있다. 본 연구는 음의 시각적 표현 중 디자인 저 표현의 본질과 특성을 규명하며, 기존의 학문적 특성과 연구 범주, 최근의 주요 동향에 대한 고찰을 바탕으로 향후 음의 시각표현의 방법론을 정리하고 재해석하여 이의 디자인에 대한 연구 방향을 제시함을 목적으로 한다. 본 연구를 토대로 향후 한국음악 특히 사물놀이가 가지고있는 음색적 특색 및 각 악기의 상징을 이용한 시각적 표현의 가능성을 모색하는 후속연구를 통해 음의 새로운 시각표현의 기능성을 모색코자 한다.

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집수평면의 신장도에 대한 정량적 평가 (The Quantitative Evaluation of Catchment Plan-Form Elongation)

  • 김주철;이상진;노준우
    • 한국공간정보시스템학회 논문지
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    • 제11권3호
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    • pp.1-8
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    • 2009
  • 본 연구에서는 집수평면의 신장도와 밀집도 그리고 등가타원에 대한 개념을 이론적인 고려와 함께 실제 유역에 적용하여 보았다. GIS를 기반으로 산정된 대상유역들에 대한 집수평면과 등가타원을 상류로부터 하류방향으로 진행하면서 변화 양상을 관찰해 본 결과 현재 논의되고 있는 Hack의 법칙에 대한 두 가설이 무작위적으로 상호작용을 할 경우 나타날 수 있는 유역 형상들에 대한 모집단처럼 보여졌다. 또한 집수평면의 최대 및 최소관성적률의 비 $R_i$가 유로연장과 집수평면에 대한 등적원(等積圓)의 직경 사이의 비 E보다 유역형상의 신장도를 보다 민감하게 평가하는 것으로 나타났다. 집수평면에 대한 밀집도는 정의별로 상이한 양상을 보였다. 이러한 결과는 형상의 정량화가 갖는 난점에 기인하는 것으로 2개 이상의 밀집도들에 대한 복합적 고려를 통한 평가나 프랙탈 이론의 적용 등이 앞으로 수행되어야 할 것으로 보인다.

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한국 농산촌 경관의 구조와 이질성 및 다양성의 최근 변화: 경관의 보전과 복원과의 관계 (Recent Spatio-temporal Changes of Landscape Structure, Heterogeneity and Diversity of Rural Landscape: Implements for Landscape Conservation and Restoration)

  • 홍선기;임용득;;장남기
    • The Korean Journal of Ecology
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    • 제23권5호
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    • pp.359-368
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    • 2000
  • Landscape change is the modification and replacement of landscape elements in accordance with human management and natural disturbance on land mosaics. During landscape change, changes in patterns such as heterogeneity, diversity and shape, and juxtaposition of spatial elements are also accompanied. For the sustainable landscape system, therefore, spatial characteristics of the landscape should be considered in implementation of landscape conservation and restoration planning. Short-term changes of land-use and landscape pattern during the 10 years of 1980s and 1990s were investigated in the agriculture-forestry dominated landscape system through the statistics and the analysis of landscape-vegetation map. Study area is Yangdong-myon, Yangpyung-gun (37°27′30"N, 127°46′50"E), Kyonggi-do, in central Korea. Landscape change of this region was significantly related to the recent industrialization according to socio-economic development. Analyses of landscape pattern show that the area of secondary forest sustained by human activity decreased and it was replaced with large exotic plantations during this period. Area of paddy field was also extended. Fractal dimension of the total landscape increased, but that of paddy field area decreased due to rearrangement for mechanized farming. Moreover, the area of landscape management regimes such as plantation and cultivation increased in land mosaics during this period.

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평균변화율 및 유일성을 통한 진화 프로그래밍에서 레비 돌연변이 연산 분석 (Analysis of the Levy Mutation Operations in the Evolutionary prograamming using Mean Square Displacement and distinctness)

  • 이창용
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제28권11호
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    • pp.833-841
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    • 2001
  • 본 논문에서는 진화프로그래밍에서 레비 확률분포(Levy probability distribution)를 사용한 돌연변이 연산의 유용성을 레비 돌연변이 연산 후의 변수의 평균변화율(mean square displacement) 및 유일성(distinctness) 등을 통하여 분석하였다. 레비 확률분포는 무한의 분산(infinite second moment을 가지는 확률분포로 쪽거리(fractal)와 연계되어 최근 연구가 활발히 진행되고 있는 확률분포이다. 레비 확률분포를 사용한 레비 돌연변이 연산은 변화가 작은 자손(offspring)뿐만 아니라 기존의 정규분포를 사용한 돌연변이 연산에 비하여 상대적으로 변화가 큰 자손을 생성할 수 있다. 이러한 사실에 기초하여 레비 돌연변이 연산은 보다 넓은 탐색 공간을 효율적으로 조사할 수 있음을 평균변화율 및 유일성 등의 조사를 통하여 수학적으로 증명하였다. 이를 통하여 진화 프로그래밍에서 레비 확률분포에 기초한 돌연변이 연산이 정규분포를 사용한 돌연변이 연산보다 다변량 함수의 최적화의 경우 일반적으로 효율적인 연산임을 알 수 있었다.

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알곤 이온빔 입사각에 따른 Polyethylene Naphthalate 필름 표면의 자가나노구조화 분석 (Effect of Argon Ion Beam Incident Angle on Self-Organized Nanostructure on the Surface of Polyethylene Naphthalate Film)

  • 조경환;양준영;변은연;박영배;정성훈;김도근;이승훈
    • 한국표면공학회지
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    • 제53권3호
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    • pp.116-123
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    • 2020
  • Ion beam irradiation induces self-organization of nanostructure on the surface of polymer film. We show that the incident angle of Ar ions on polyethylene naphthalate(PEN) film changes self-organized nanostructure. PEN film was irradiated by argon ion beams with the ion incident angle of 0°, 30°, 45°, 60°, and 80°. Nanostructure was altered from dimple to ripple structure as the angle increases. The ripple structure changed to pillar structure after 60°due to that the shallow incident angle increased the ion energy transfer per depth up to 50 eV/Å, which value could induce excessive surface heating and oligomer formation reacting as a physical mask for anisotropic etching. And quantitative analysis of the nanostructures was adapted by using ABC model and fractal dimension theory.