• The Journal of Engineering Geology
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• v.4 no.3
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• pp.311-319
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• 1994

This paper presents a sensitivity analysis to obtain best fit of hydraulic parameters of leaky fractal aquifer. The sensitivity analysis uses the least squares method. The hydraulic parameters (generalized transmissivity and generalized storage coefficient) can be easily determined by the sensitivity analysis for various flow dimensions and different values of the leakage factor. Furthermore, the sensitivity analysis was applied to variable-rate pump tast at several abstraction wells, A computer program was developed to evaluate the hydraulic parameters by the sensitivity analysis.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.14-21
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• 2001

To estimate crack growth rate and cycle ratio uniquely, many investigators have developed various kinds of mechanical parameters and theories. But, thes have produced local solution space through single parameter. Neural Networks can perform patten classification using several input and output parameters. Fatigue damage model by neural networks was used to recognize the relation between da/dN/N/N(sub)f, and half-value breadth ratio B/Bo, fractal dimension D(sub)f, and fracture mechanical parameters in 2024-T3 aluminium alloy. Learned neural networks has ability to predict both crack growth rate da/dN and cycly ratio /N/N(sub)f within engineering estimated mean error(5%).

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.10a
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• pp.295-300
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• 1996

In this study, the dynamic instabilities of a nonlinear elastic system subjected to follower force are investigated. The two-degree-of-freedom double pendulum model with nonlinear geometry, cubic spring, and linear viscous damping is used for the study. The constant and periodic follower forces are considered. The chaotic nature of the system is identified using the standard methods, such as time histories, phase portraits, and Poincare maps, etc.. The responses are chaotic and unpredictable due to the sensitivity to initial conditions. The sensitivities to parameters, such as geometric initial imperfections, magnitude of follower force, and viscous damping, etc. is analysed. The strange attractors in Poincare map have the self-similar fractal geometry. Dynamic buckling loads are computed for various parameters, where the loads are changed drastically for the small change of parameters.

• Journal of Biomedical Engineering Research
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• v.17 no.1
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• pp.121-128
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• 1996

This paper presents the ECG data compression method referred the adaptive fractal interpolation algorithm. In the previous piecewise fractal interpolation(PFI) algorithm, the size of range is fixed So, the reconstruction error of the PFI algorithm is nonuniformly distributed in the part of the original ECG signal. In order to improve this problem, the adaptive fractal interpolation(AEI) algorithm uses the variable range. If the predetermined tolerance was not satisfied, the range would be subdivided into two equal size blocks. large ranges are used for encoding the smooth waveform to yield high compression efficiency, and the smaller ranges are U for encoding rapidly varying parts of the signal to preserve the signal quality. The suggested algorithm was evaluated using MIT/BIH arrhythmia database. The AEI algorithm was found to yield a relatively low reconstruction error for a given compression ratio than the PFI algorithm. In applications where a PRD of about 7.13% was acceptable, the ASI algorithm yielded compression ratio as high as 10.51, without any entropy coding of the parameters of the fractal code.

• The Journal of Engineering Geology
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• v.4 no.3
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• pp.283-295
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• 1994

A new nonstationary dual-porosity fractal model is presented which simulates a nonsteady state block-to-fissure flow with or without fracture skin between the block and the fissure in a fractal aquifer. The model includes weilbore storage and well loss effects on the production well. Type curves for different flow dimensions with different values of hydraulic parameters are created. The application of the model to experimental data in fractured aquifer is described.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.2
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• pp.175-182
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• 1999

Scanning electron microscopy (SEM) has played an important role in receptor modeling area because it is a powerful tool for characterizing individual particles. The purpose of the study was to classify individual diesel particles base on statistical analysis and image analysis by SEM/EDX (energy dispersive x-ray analyser). The diesel particles were sampled by both a modified CVS 75 mode and a high speed mode with a chassis dynamometer. The SEM/EDX system provides various physical parameters including particle's particle diameter and chemical information. Thus density and mass of the diesel particle were estimated cased on its chemical composition and further fractal dimensions of the diesel particle were obtained by the Hurst exponent method. The fractal dimension in the sample of modified CVS 75 mode was higher than the high speed mode. Finally, mass fractions for a diesel vehicle as a source profile were estimated cased on a particle class concept.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.3
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• pp.35-41
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• 2002

There are many image segmentation methods having been published as the results of research so far, but it is difficult to be partitioned to each similar range that should be extracted into the accurate parameters of image information on the images with noises. Also if it is used to fractal coding, according to amount of noise in image, the image segmentation leads to decreasing of the compression ratio. In this paper, we propose the new quad-tree image segmentation using the box-counting dimension which can estimate the effective image information parameters against the noise properties and apply this method to fractal image coding. As the result of simulation, we confirm that the image segmentation is improved to 31.10% for parameter detection of image information and compression ratio is enhanced to 38.93% for fractal image coding when tested on 10% Gaussian white noise image by the proposed quad-tree method compared with method using existing quad-tree. 

• Journal of Periodontal and Implant Science
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• v.40 no.1
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• pp.19-24
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• 2010

Purpose: It has been suggested that primary implant stability plays an essential role in successful osseointegration. Resonance frequency analysis (RFA) is widely used to measure the initial stability of implants because it provides superior reproducibility and non-invasiveness. The purpose of this study is to investigate whether the fractal dimension from the panoramic radiograph is related to the primary stability of the implant as represented by RFA. Methods: This study included 22 patients who underwent dental implant installation at the Department of Periodontology of Seoul National University Dental Hospital. Morphometric analysis and fractal analysis of the bone trabecular pattern were performed using panoramic radiographs, and the implant stability quotient (ISQ) values were measured after implant installation using RFA. The radiographs of 52 implant sites were analyzed, and the ISQ values were compared with the results from the morphometric analysis and fractal analysis. Results: The Pearson correlation showed a linear correlation between the ISQ values of RFA and the parameters of morphometric analysis but not of statistical significance. The fractal dimension had a linear correlation that was statistically significant. The correlation was more pronounced in the mandible. Conclusions: In conclusion, we suggest that the fractal dimension acquired from the panoramic radiograph may be a useful predictor of the initial stability of dental implants.

• Journal of Broadcast Engineering
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• v.4 no.1
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• pp.76-85
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• 1999

The degradation of image quality by block loss is more serious in fractal coded images with the error propagation due to mapping from the lost blocks than in DCT coded images. Therefore. a new algorithm is presented for recovering the blocks lost in the transmission through the lossy network as A TM network of the images coded by Jacquins fractal coding. Jacquins fractal code is divided into two layers of header code and main code according to its importance. The key technique of the proposed BLRA (block loss recovery algorithm) is a fractal extrapolation that estimates the lost pixels by using the contractive mapping parameters of the neighboring range blocks whose characteristics are similar to a lost block. The proposed BLRA is applied to the lost blocks in the iteration of decoding. Some experimental results show the proposed BLRA yields excellent performance in PSNR as well as subjective quality.

• 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.