• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.48 no.1
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• pp.33-40
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• 2022

Objectives: Prolotherapy is a method that has gained popularity in recent years and has been reported to have positive short-term and long-term clinical results in maxillofacial surgery, especially temporomandibular joint (TMJ) hypermobility. This study aimed to evaluate the changes in the trabecular structure of mandibular condyles in patients who underwent prolotherapy due to TMJ hypermobility using the fractal analysis method. Materials and Methods: Forty-five patients who received dextrose prolotherapy at a concentration of 20% and fifteen control patients were included in the study. All patients had panoramic radiographs just before (T0) and six months after treatment (T1). The patients who received treatment were divided into three groups according to the number of prolotherapy injections. The regions of interest were selected from bone areas close to the articular surfaces of the condyles. The fractal dimension (FD) values were calculated. Results: The main effect of time on the FD value was significant [F (1, 56)=86.176, P<0.001]. This effect was qualified by a significant time×group interaction effect [F (3, 56)=9.023, P<0.001]. The decreases in FD values in all treatment groups between T0 and T1 times were significant (P=0.004). However, changes in FD values were not significant in the control group (P=0.728). Conclusion: Dextrose prolotherapy without the effect of the number of injections caused a decrease in FD values in the mandibular condyles over time.

• The Journal of Korean Academy of Prosthodontics
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• v.54 no.1
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• pp.14-20
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• 2016

Purpose: The aim of this study was to know whether there is significant difference of peri-implant bone density according to the state of antagonist region. Materials and methods: 51 patients who had implant operation in Daejeon Dental Hospital of Wonkwang University participated in this study and total of 51 implants were analyzed. Implants were classified depending on opposing antagonist region, gender, age and location of jaw. The opposing antagonist region was divided into four groups; natural tooth, implant, pontic and edentulous region. Fractal analysis was performed using two periapical radiographs; one after implant placement and the other after 10 weeks following prosthetic restoration. The analysis was done by Image J. The data was statistically analyzed using one-way ANOVA and Tukey multiple comparison test. Results: The mean value of fractal difference was $0.009{\pm}0.048$ with opposing natural tooth, $0.026{\pm}0.080$ with opposing implant, $0.025{\pm}0.068$ with opposing pontic and $0.093{\pm}0.171$ with opposing edentulous area. There was a statistically significant difference in fractal value between opposing implant and opposing edentulous state. And there was no statistically significant difference according to age, gender and location of jaw. Conclusion: There was no statistically significant difference between 3 groups except opposing edentulous region and there was a statistically significant difference between opposing implant and edentulous region. And there was no statistically significant difference according to age, gender and location of jaw.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.125-131
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• 2008

Hyperspectral imaging is used in a wide variety of research since the image is obtained with a wider wavelength range and more bands than multispectral imaging. However, there are limitations, namely that each band has a shorter wavelength range, the computation cost is increased in the case of numerous bands, and a high correlation between each band and noise bands exists. The previous analysis method does not produce ideal results due to these limitations. Therefore, in the case of using the hyperspectral image, image analysis after eliminating noise bands is more accurate and efficient. In this study, noise band elimination of the hyperspectral image preprocessing is highlighted, and we use fractal dimension for noise band elimination. The Triangular Prism Method is used, being the typical fractal dimension method of the curved surface. The fractal dimension of each band is calculated. We then apply the Continuum Removal method to normalize. A total of 35 bands are estimated by noise band with a threshold value that is obtained empirically. The hyperion hyperstpectral image collected on the EO-1 satellite is used in this study. The result delineates that noise bands of the hyperion image are able to be eliminated with the fractal dimension and Continuum Removal method.

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.133-147
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• 1998

Recently, many researchers have been involved in finding deterministic equations which can accurately predict future event, based on chaotic theory, or fractal theory. The theory says that some events which seem very random but internally deterministic can be accurately predicted by fractal equations. In contrast to the conventional methods, such as AR model, MA, model, or ARIMA model, the fractal equation attempts to discover a deterministic order inherent in time series data set. In discovering deterministic order, researchers have found that neural networks are much more effective than the conventional statistical models. Even though prediction accuracy of the network can be different depending on the topological structure and modification of the algorithms, many researchers asserted that the neural network systems outperforms other systems, because of non-linear behaviour of the network models, mechanisms of massive parallel processing, generalization capability based on adaptive learning. However, recent survey shows that prediction accuracy of the forecasting models can be determined by the model structure and data structures. In the experiments based on actual economic data sets, it was found that the prediction accuracy of the neural network model is similar to the performance level of the conventional forecasting model. Especially, for the data set which is deterministically chaotic, the AR model, a conventional statistical model, was not significantly different from the MLP model, a neural network model. This result shows that the forecasting model. This result shows that the forecasting model a, pp.opriate to a prediction task should be selected based on characteristics of the time series data set. Analysis of the characteristics of the data set was performed by fractal analysis, measurement of Hurst index, and measurement of Lyapunov exponents. As a conclusion, a significant difference was not found in forecasting future events for the time series data which is deterministically chaotic, between a conventional forecasting model and a typical neural network model.

• 한국전기화학회:학술대회논문집
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• 2004.04a
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• pp.56-56
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• 2004

• Proceedings of the Korean Nuclear Society Conference
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• 1999.10a
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• pp.139.1-139
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• 1999

• Journal of Korean Society of Environmental Engineers
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• v.28 no.3
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• pp.337-344
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• 2006

Characteristics of flocculent aggregates have great effects on membrane fouling. Floc from kaolin particles gave higher permeate throughputs than floc from natural particles at the same conditions. Therefore, the objectives of this study are to thoroughly analyze characteristics of flocculated aggregates and to investigate effects of flocculated aggregates on membrane fouling. Image analysis, specific rake resistance and cake compressibility were used for characterization of flocs. Different flocculent aggregates formed with natural and kaolin particles were employed in this study. The fractal dimensions from the image analysis were $D_2=1.79{\pm}0.07$ for floc from natural particles and $D_2=1.84{\pm}0.06$ for floc from kaolin particles. The lower fractal dimension($D_2$) of floc from natural particles indicated that the aggregates were more porous and less compact than floe from kaolin particles. In addition, both the specific cake resistances and compressible degrees of flocs from natural particles showed greater values than those of flocs from kaolin particles. The results implied that the porous and loose flocs from natural particles were more easily compressed on membrane surface than the dense and compact flocs from kaolin particles. The compressed flocs yielded the great hydraulic resistances by hindering the water flow through the cake layer.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05b
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• pp.107-110
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• 2002

The optical memory devices of BST thin films to composite $(Ba_{0.7}\;Sr_{0.3})TiO_{3}$ using sol-gel method were fabricated by changing of the depositing layer number on $Pt/Ti/SiO_{2}/Si$ substrate. The structural properties of optical memory devices to be ferroelectric was investigated by fractal analysis and 3-dimension image processing. The thickness of BST thin films at each coating numbers 3, 4 and 5 times was $2500[\AA]$, $3500[\AA]$ and $3800[\AA]$. BST thin films exhibited the most pronounced grain growth. The surface morphology image was roughness with coating numbers. The thin films increasing with coating numbers shows a more textured and complex configuration.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.542-544
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• 1997

The analysis of distribution line faults is essential to the proper protections in the power system. A high impedance fault does not make enough current to cause conventional protective devices. In this paper, Fractal dimensions are estimated for distinction between normal status and fault status in the power system. Application of the concepts of the fractal geometry to analyze chaotic properties of high impedance fault current was described. In addition, to analyze variation of fault current and normal current on phase plane, embedding state variables are reconstructed from 1 dimensional time series.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.817-821
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• 1997

Ever since the nonlinearity of machine tool dynamics was established, researchers attempted to make use of this fact to devise better monitoring, diagnostics and system, which were hitherto based on linear models. Theory of chaos, which explains many nonlinear phenomena comes handy for furthering the analysis using nonlinear model. In this study, measuring system will be constructed using multi-sensor (Tool Dynamometer, Acoustic Emission) in end millingprocess. Then, it will be verified that cutting force is low-dimensional deterministic chaos calculating Lyapunov exponents, Fractal dimension, Embedding dimension. Aen it will be investigated that the relations between characteristic parameter caculated form sensor signal and tool wear.