• Proceedings of the Korea Concrete Institute Conference
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• 2001.05a
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• pp.333-338
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• 2001

Fractal geometry is a non-Euclidean geometry which has been developed to quantitative analysis irregular or fractional shapes. Fractal dimension of irregular surface has fractal values ranging from 2 to 3 and of irregular line profile has fractal values ranging from 1 to 2. In this paper, quantitative analysis of crack growth patterns during the fracture processing of fiber-reinforced cement composites based on fractal geometry. The fracture behaviors of fiber reinforced mortar beams subjected to three-point loading in flexure. The beams all had a single notch depth, but varing volume fractions of polypropylene, cellulose fibers. The crack growth behaviors, as observed through the image processing system, and the box counting method was used to determine the fractal dimension, Df. The results showed that the linear correlation exists between fractal dimension and fracture energy of the fiber reinforced cement mortar.

• Geomechanics and Engineering
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• v.4 no.3
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• pp.219-227
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• 2012

Pavement management systems require systematic monitoring of pavement surfaces to determine preventive and corrective maintenance. The process involves the accumulation of large amounts of visual data, typically obtained from site visitation. The pavement surface condition is then correlated to a pavement distress index that is based on a scoring system previously established by state or federal agencies. The scoring system determines if the pavement section requires maintenance, overlay or reconstruction. One of the surface distresses forming part of the overall pavement distress index is the Alligator Crack Index (AC Index). The AC Index involves the visual evaluation of the crack severity of a section of a pavement as being low, medium, or high. This evaluation is then integrated into a formula in order to obtain the AC Index. In this study a quantification of the visual evaluation of the severity of alligator cracking is carried out using photographs and the fractal dimension concept from fractal theory. Pavements with low levels of cracking were found to have a fractal dimension equal to 1.051. Pavements with moderate levels of cracking had a fractal dimension equal to 1.1754. Pavements with high degrees of cracking had a fractal dimension that varied between 1.5037 (high) and 1.7111 (very high). Pavements with a level of cracking equal to 1.8976 represented pavements that disintegrated and developed potholes. Thus, the visual evaluation of the state of cracking of a pavement (the AC Index) could be enhanced with the use of the fractal dimension concept from fractal theory.

• 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.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.28 no.1
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• pp.17-26
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• 1998

The purpose of this study was to investigate whether a radiographic estimate of osseous fractal dimension is useful in the characterization of structural changes in bone. Ten specimens of bone were progressively decalcified in fresh 50 ml solutions of 0.1 N hydrochloric acid solution at cummulative timed periods of 5, 10, 20, 30, 60 and 90 minutes, and radiographed from 0 degree projection angle controlled by intraoral parelleling device. The test set of 70 radiographs was digitized and digitally filtered to reduce film -grain noise. I performed one-dimensional variance and fractal analysis of bony profiles or scan lines. Correlation analysis quantified the relationship between variance and fractal dimension. The obtained results were as follow. 1. After the first stage of decalcification variance and fractal dimension of scan line pixel intensities generally decreased with a range of 57.94 to 12.64 and 1.59 to 1.36. 2. Correlation coefficient(r) relating variances to fractal dimensions was consistantly excellent(range r=0.90 to 0.98). 3. Variance and fractal dimension were much alike in ability to discriminate, at leat on a group basis, between control and decalcified specimens.

• Imaging Science in Dentistry
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• v.52 no.1
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• pp.33-41
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• 2022

Purpose: This study aimed to evaluate the structural complexity of craniofacial trabecular bone in multiple myeloma by fractal analysis of panoramic and lateral skull radiography, and to compare the fractal dimension values of healthy patients (HPs), pre-treatment patients (PTPs), and patients during bisphosphonate treatment (DTPs). Materials and Methods: Pairs of digital panoramic and lateral skull radiographs of 84 PTPs and 72 DTPs were selected. After application of exclusion criteria, 43 panoramic and 84 lateral skull radiographs of PTPs, 56 panoramic and 72 lateral skull radiographs of DTPs, and 99 panoramic radiographs of age- and sex-matched HPs were selected. The fractal dimension values from panoramic radiographs were compared among HPs, PTPs, and DTPs and between anatomical locations within patient groups using analysis of variance with the Tukey test. Fractal dimension values from lateral skull radiographs were compared between PTPs and DTPs using the Student t-test. Pearson correlation coefficients were used to assess the relationship between the mandible from panoramic radiographs and the skull from lateral skull radiographs. Intra-examiner agreement was assessed using intraclass correlation coefficients (α=0.05). Results: The fractal dimension values were not significantly different among HPs, PTPs, and DTPs on panoramic radiographs or between PTPs and DTPs on lateral skull radiographs (P>0.05). The mandibular body presented the highest fractal dimension values (P≤0.05). The fractal dimension values of the mandible and skull in PTPs and DTPs were not correlated. Conclusion: Fractal analysis was not sensitive for distinguishing craniofacial trabecular bone complexity in multiple myeloma patients using panoramic and lateral skull radiography.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2005.10a
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• pp.387-392
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• 2005

The research was performed to predict the potential landslide with roughness index. It was known that fractal dimension and surface area index can be represented the topography, specially when the natural slopes were rough or rugged. A test site was selected and fractal dimension and surface area index were calculated from the irregular triangle network. Fractal dimension were ranged between $2.016{\sim}2.046$ and surface area index $1.56E+07{\sim}2.59E+07$. Surface area index increased as fractal dimension increased. Slope stability was calculated by infinite slope stability analysis model and was compared to slope stability by fractal and surface area index. In the result, unsafe zones where slope stability is under 1.1 were $5.11{\sim}6.25%$ for the test site. It can be said that fractal dimension and surface area index are a good index to evaluate the slope stability because when fractal dimension and surface area index are greater, then stability of the site is more unsafe.

• Economic and Environmental Geology
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• v.27 no.1
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• pp.81-91
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• 1994

There has been considerable research dealing with the influence of surface roughness along surfaces of rock discontinuities in relation to the peak shear strength of rock masses. Concepts accepted recently for measuring such strength include estimation of a roughness coefficient such as developed by Barton's studies. The method for estimation the Joint Roughness Coefficient (JRC) value of a measured roughness profile is subjective. The aim of this research is to estimate the JRC value of the roughness of a surface profile in a rock mass system using an objective method. The study of roughness of surfaces has included measurement of fractal geometric characteristics. Once the irregularity of the surface has been described by the fractal dimension, the spatial variation of the surface irregularities can be described using variogram and drift analysis. An empirical relationships between the roughness profiles of selected JRC ranges and their fractal dimension with variogram and drift were derived. The application of analyses of fractal dimension, variogram and drift was novel for the analysis of roughness profiles. Also, an empirical equation was applied to experimental data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.655-658
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• 2009

Fractal dimension has been used for texture analysis as it is highly correlated with human perception of surface roughness and applied to quantifying the structures of wide range of objects in biology and medicine. On the other hand, the evaluation of the human skin state is based solely on the subjective assessment of clinicians; this assessment may vary from moment to moment and from rater to rater. Therefore we attempt to analysis of skin texture image using fractal dimension and discuss its application to evaluating human skin state. It can be helpful for extracting human features and also can be useful for detection of many human skin diseases. This paper presents a method to calculate fractal dimension of skin with use of camera lens magnification. We take multiple pictures frequently from skin with different camera lens magnification as a magnification factor of fractal set, and counting the number of objects (cells) in each picture as a number of self similar pieces of fractal set.

• Journal of the Korean association of regional geographers
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• v.11 no.6
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• pp.530-542
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• 2005

In this study, GIS method has been used to get fractal characteristics. Using the projected area and surface area, 2 dimensional fractal characteristic of terrain was found out. Correlation of fractal dimension and mean slope were also checked over. Results are as below. 1) To get a fractal dimension, the method which is using the surface area is also directly proportional to complexity of the terrain as other fractal dimension. 2) Fractal dimensions using the surface area, that is proposed in this thesis are carried out as below : Uiseong : $2.02{\sim}2.15$ Yeongcheon : $2.10{\sim}2.24$. These values are in a range of fractal $2.10{\sim}2.20$ dimensions which has known. 3) Correlation of mean slope and fractal dimension is diminished about 30% in a region which is more than $25^{\circ}$ of mean slope. So, in this region using the fractal dimension method is better than using the mean slope. From this study, on formula using the projected area and surface area is still good to get a fractal dimension that has been found. But to confirm this method the region of research should be wider and be set up the correlation of mean slope, surface area and fractal dimension. It can be applicable to restoration of terrain and traffic flow analysis in the future research.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.145-149
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• 2023

High-resolution images of surfaces provide detailed information on pores or shapes with specific sizes ranging from nano sizes to micrometers. However, it is not yet clear to determine an efficient association for pores or shapes from high-resolution images of surfaces. For the efficient association of pores and shapes, the surface characteristics of the device were considered as fractal dimensions by taking SEM photographs and binarizing the images. The fractal program was directly coded for surface analysis of the device. The device surface characteristics and electrical characteristics are thought to be related to the fractal dimension. The fractal dimension decreased with an increase in internal pores. The density and grain boundary of particles, which are structural characteristics of the device surface, were related to the fractal dimension. The particle size decreased with an increase in the fractal dimension and was uniformly formed. When the particles were uniformly formed, fewer pores were present and the fractal dimension increased.