• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.141-147
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• 2024

Progressive photon mapping is a widely adopted rendering technique that conducts a kernel-density estimation on photons progressively generated from lights. Its hyperparameter, which controls the reduction rate of the density estimation, highly affects the quality of its rendering image due to the bias-variance tradeoff of pixel estimates in photon-mapped results. We can minimize the errors of rendered pixel estimates in progressive photon mapping by estimating the optimal parameters based on gradient-based optimization techniques. To this end, we derived the gradients of pixel estimates with respect to the parameters when performing progressive photon mapping and compared our estimated gradients with finite differences to verify estimated gradients. The gradient estimated in this paper can be applied in an online learning algorithm that simultaneously performs progressive photon mapping and parameter optimization in future work.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.1-10
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• 2007

Most of natural images have a special property, what is called self-similarity, which is the basis of fractal image coding. Even though an image has local stationarity in several homogeneous regions, it is generally non-stationarysignal, especially in edge region. This is the main reason that poor results are induced in linear techniques. In order to overcome the difficulty we propose a non-linear technique using self-similarity in the image. In our work, an image is classified into stationary and non-stationary region with respect to sample variance. In case of stationary region, do-noising is performed as simply averaging of its neighborhoods. However, if the region is non-stationary region, stationalization is conducted as make a set of center pixels by similarity matching with respect to bMSE(block Mean Square Error). And then do-nosing is performed by Gaussian weighted averaging of center pixels of similar blocks, because the set of center pixels of similar blocks can be regarded as nearly stationary. The true image value is estimated by weighted average of the elements of the set. The experimental results show that our method has better performance and smaller variance than other methods as estimator.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.983-993
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• 2021

Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.9-20
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• 2010

In order to visualize participating media in 3D space, they usually calculate the incoming radiance by subdividing the ray path into small subintervals, and accumulating their respective light energy due to direct illumination, scattering, absorption, and emission. Among these light phenomena, scattering behaves in very complicated manner in 3D space, often requiring a great deal of simulation efforts. To effectively simulate the light scattering effect, several approximation techniques have been proposed. Volume photon mapping takes a simple approach where the light scattering phenomenon is represented in volume photon map through a stochastic simulation, and the stored information is explored in the rendering stage. While effective, this method has a problem that the number of necessary photons increases very fast when a higher variance reduction is needed. In an attempt to resolve such problem, we propose a different approach for rendering particle-based volume data where kernel smoothing, one of several density estimation methods, is explored to represent and reconstruct the light in-scattering effect. The effectiveness of the presented technique is demonstrated with several examples of volume data.

• Journal of Radiation Industry
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• v.10 no.1
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• pp.29-35
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• 2016

Radiation generating devices must be properly shielded for their safe application. Although institutes such as US National Bureau of Standards and National Council on Radiation Protection and Measurements (NCRP) have provided guidelines for shielding X-ray tube of various purposes, industry people tend to rely on 'Half Value Layer (HVL) method' which requires relatively simple calculation compared to the case of those guidelines. The method is based on the fact that the intensity, dose, and air kerma of narrow beam incident on shielding wall decreases by about half as the beam penetrates the HVL thickness of the wall. One can adjust shielding wall thickness to satisfy outside wall dose or air kerma requirements with this calculation. However, this may not always be the case because 1) The strict definition of HVL deals with only Intensity, 2) The situation is different when the beam is not 'narrow'; the beam quality inside the wall is distorted and related changes on outside wall dose or air kerma such as buildup effect occurs. Therefore, sometimes more careful research should be done in order to verify the effect of shielding specific radiation generating device. High energy X-ray tubes which is operated at the voltage above 400 kV that are used for 'heavy' nondestructive inspection is an example. People have less experience in running and shielding such device than in the case of widely-used low energy X-ray tubes operated at the voltage below 300 kV. In this study, Air Kerma value per week, outside concrete shielding wall of various thickness surrounding 450 kVp X-ray tube were calculated using MCNP simulation with the aid of Geometry Splitting method which is a famous Variance Reduction technique. The comparison between simulated result, HVL method result, and NCRP Report 147 safety goal $0.02mGy\;wk^{-1}$ on Air Kerma for the place where the public are free to pass showed that concrete wall of thickness 80 cm is needed to achieve the safety goal. Essentially same result was obtained from the application of HVL method except that it suggest the need of additional 5 cm concrete wall thickness. Therefore, employing the result from HVL method calculation as an conservative upper limit of concrete shielding wall thickness was found to be useful; It would be easy, economic, and reasonable way to set shielding wall thickness.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.

• Journal of Biosystems Engineering
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• v.1 no.1
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• pp.1-6
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• 1976

This paper is the third one of the study on balanced type oscillating mole-drainer, the first one was presented in No 9. Gyeongsang College Report and the second one in Vol. 17, No.4 of the KSAE. In the first part of this study, the characteristics of traction forces between the nonoscillating earth working equipments and oscillating ones was compared. A model of the balanced type oscillating mole-drainer, which composed of a mechanism that may reduce the machine vibration, was designed following the dimensional analysis and similitude technique. The model test was carried out to clarify the balancing mechanism of the oscillating parts and other parts of the machine. In the light of the results from the model tests, a prototype machine was made for experimental purpose. Results from the field test by a reported in the near future. In the second report, the model tests were carried out under the same soil conditions, i.e, . oscillating frequency, running velocity, and oscillating amplitude, etc. It was clear that use of balanced type oscillating model could substantially reduce the vibration of the whole system of the machine, when compared with the nonoscillating type model. In this paper(the third report), results of investigation on the traction force, power requirement, and moment. etc, is presented. Analysis of variance technique was used for analyzing the effect of the frequency, amplitude, and running velocity on the draft force, torque, power requirements, and moments. The results obtained from the model tests are as follows, 1) By practicing a balanced-type oscillating mole-drainer, it was possible to reduce the traction resistance by 55.1-61. 2 percent of traction resistance, however, was 1.75 - 1.95 times greater than the value of resistance which was induced by use of a mole-drainer with single bullet. The resistance of rear shank against soil was considered as a main causing factor of the above results. 2) As the oscillation frequency was increased, the traction resistance was decreased. Considering on the effect of oscillation the greater the amplitude, and the slower the running velocity was, the greater the reduction ratio of traction resistance was. 3) The ratio of the traction resistance of oscillating mole-drainer to that of non-oscillating one could be represented as a function of dimensionless variable (V/$Af$). The results from the tests were well agreed with the reported results from the experim ents on oscillation plow or hoe. 4) By taking a lower value of (V/$Af$), reducing the traction resistance was possible. This fact meant, however, that the efficiency of mole drain practice would be lower. 5) It was experimentally confirmed under the same condition of soil that the variable (R/$rD1^3$) could be represented as a function of a variable($V^2/gD$) when a non\ulcornerocillating mole-drainer was used. 6) When a oscillating mole-drainer was used, the variable(R/$rD_1^{3}$) could be represented as a function of two variables ($v^2/gD_1$) and (V^2/gD_1$). 7) The torque was not affected by a change of frequency. However, a relation of proportionality existed between torque and amplitude, running velocity, and ratio of bullet diameter. When a balanced type oscillating mole-drainer with two bullets was used, torque was increased by 52.8-78. 4 percent and total power requirement was also increased. 8) Total power requirement was increased linearly in accordance with the increasing frequency, 41.96 percent of total power was used for oscillating action. The magnitude of total power requirement was 1. 8-9. 4 times greater than that of a non-oscillating mechanism. In the view point of power requirement, it was not advisable to increase the frequency, amplitude, running velocity, and ratio of bullet diameter at the same time. 9) Only the positive moment occured in the rear shank. Change of the diameter of a rear bullet, could not affect the balancing against the soil resistance. It was necessary for rear bullet to have a large resistance against soil only when the rear bullet was in backward motion. 10) Within an extent of the experimental base, optimum limits for several design factors were A=0.5cm, $f$=22.5Hz, V=O. 05m/sec, and $\lambda$=1.0 By adapting these values traction resistance was reduced by 40 percent and vibration acceleration wa s reduced by 60 percent. Even though the total , power requirements for operating a balanced type oscillation mechanism was greater ~than that of non-oscillating one, using a oscillating mechanism would be more effective. Because a balanced type oscillating mechanism is used, tractive resistance will be reduced and then the lighter . tractive equipment could be used.

• Journal of Dental Rehabilitation and Applied Science
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• v.23 no.3
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• pp.249-257
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• 2007

State of problem : The use of zirconium oxide all-ceramic material provides several advantages, including a high flexural strength(>1000MPa) and desirable optical properties, such as shading adaptation to the basic shades and a reduction in the layer thickness. Along with the strength of the materials, the cementation technique is also important to the clinical success of a restoration. Nevertheless, little information is available on the effect of different surface treatments on the bonding of zirconium high-crystalline ceramics and resin luting agents. Purpose : The aim of this study was to test the effects of surface treatments of zirconium on shear bond strengths between bovine teeth and a zirconia ceramic and evaluate differences among cements Material and methods : 54 sound bovine teeth extracted within a 1 months, were used. They were frozen in distilled water. These were rinsed by tap water to confirm that no granulation tissues have left. These were kept refrigerated at $4^{\circ}C$ until tested. Each tooth was placed horizontally at a plastic cylinder (diameter 20mm), and embedded in epoxy resin. Teeth were sectioned with diamond burs to expose dentin and grinded with #600 silicon carbide paper. To make sure there was no enamel left, each was observed under an optical microscope. 54 prefabricated zirconium oxide ceramic copings(Lava, 3M ESPE, USA) were assigned into 3 groups ; control, airborne-abraded with $110{\mu}m$ $Al_2O_3$ and scratched with diamond burs at 4 directions. They were cemented with a seating force of 10 ㎏ per tooth, using resin luting cement(Panavia $F^{(R)}$), resin cement(Superbond $C&B^{(R)}$), and resin modified GI cement(Rely X $Luting^{(R)}$). Those were thermocycled at $5^{\circ}C$ and $55^{\circ}C$ for 5000 cycles with a 30 second dwell time, and then shear bond strength was determined in a universal test machine(Model 4200, Instron Co., Canton, USA). The crosshead speed was 1 mm/min. The result was analyzed with one-way analysis of variance(ANOVA) and the Tukey test at a significance level of P<0.05. Results : Superbond $C&B^{(R)}$ at scratching with diamond burs showed the highest shear bond strength than others (p<.05). For Panavia $F^{(R)}$, groups of scratching and sandblasting showed significantly higher shear bond strength than control group(p<.05). For Rely X $Luting^{(R)}$, only between scratching & control group, significantly different shear bond strength was observed(p<.05). Conclusion : Within the limitation of this study, Superbond $C&B^{(R)}$ showed clinically acceptable shear bond between bovine teeth & zirconia ceramics regardless of surface treatments. For the surface treatment, scratching increased shear bond strength. Increase of shear bond strength by sandblasting with $110{\mu}m$ $Al_2O_3$ was not statistically different.