• Journal of the Korean Home Economics Association
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• v.43 no.5 s.207
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• pp.107-115
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• 2005

The purpose of this research was to compare the harmony of tone on tone coloration according to transformation of color area-ratio in traditional Korean dress. The respondents were asked to evaluate 36 stimuli of the traditional Korean skirt and jacket with different color tone. The subjects were 83 female undergraduate students. The results are as follows. For red colors, combinations of vivid/dull, vivid/dark, and light/dark made a difference in the harmony of coloration according to the transformation of color area-ratio. For yellow colors, combinations of vivid/dark, light/dull, and light/dark made a difference in the harmony of coloration according to the transformation of color area-ratio. For green colors, combinations of vivid/dull, vivid/dark, light/dull, and light/dark made a difference in the harmony of coloration according to the transformation of color area-ratio.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.824-827
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• 1988

Eddy Current Sensor to Measure the ${\gamma}-{\alpha}$/ Transformation Ratio of Metal is Designed and Implemented. Experimental Results Regarding to Impedance Variation due to ${\gamma}-{\alpha}$ Transformation Ratio of Metal Under Room Temperature are Reported. It Was Found That the Impedance of Metal is Increased With Increasing ${\gamma}-{\alpha}$ Ratio.

• Fashion & Textile Research Journal
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• v.9 no.2
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• pp.138-144
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• 2007

The purpose of this research was to compare the harmony of tone on tone coloration according to transformation of color area-ratio in shirt and necktie. The respondents were asked to evaluate 48 stimuli of the shirt and necktie with the coloration of the shirt/necktie, the necktie/shirt was separately compounded to be 4 tones such as vivid, light, dull, dark. The subjects were 288 female undergraduate students. The data was analyzed by using SPSS program. Analysis methods were ANOVA, LSD test and t-test. The results of each can be summerized as follows. As to the red, combination of v-lt made a difference in the harmony of coloration according to the transformation of color area-ratio. As to the blue, combination of v-lt, v-dk, lt-d made a difference in the harmony of coloration according to the transformation of color area-ratio. As to the purple, v-lt, v-d was evaluated as harmonized coloration regardless of area-ratio by both male and female students. As to the green, v-lt, lt-d was evaluated as harmonized coloration regardless of area-ratio by both male and female students.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.5
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• pp.348-354
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• 1989

The metallurgical transformation ratios of metals have been evaluated by the eddy current method. Eddy current probes have been designed and applied to various standard samples. The equivalent impedance estimated from the eddy current measurement is closely related to the variation of transformation ratios in metals. It has been found that the variation of the impedance is relatively large in the samples where the transformation ratios of the samples are small. Both reactance and resistance increase when the transformation ratio is large. Sensitivities of eddy current test is increased with increasing frequencies and by inserting ferrite core the solenoid eddy probe. Our results have shown the implementation of eddy current measurement to the one-line nondestructive testing of metals.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.509-516
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• 2019

In the linear transformation method, the original image is divided into a plurality of range blocks, and a partial transform system for finding an optimal domain block existing in the image for each range block is used to adjust the performance of the compression ratio and the picture quality, The nonlinear transformation method uses only the rotation transformation among eight shuffle transforms. Since the search is performed only in the limited domain block, the coding time is faster than the linear transformation method of searching the domain block for any block in the image, Since the optimal domain block for the range block can not be selected in the image, the performance may be lower than other methods. Therefore, the nonlinear transformation method improves the performance by increasing the approximation degree of the brightness coefficient conversion instead of selecting the optimal domain block, The smaller the size of the block, the higher the PSNR value, The higher the compression ratio is increased groups were quadtree block divided to encode the image at best.

• Journal of applied mathematics & informatics
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• v.22 no.1_2
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• pp.541-547
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• 2006

A procedure for investigating the influence of observations in choosing Box-Cox transformation for multivariate data is suggested. It is effective in spotting influential observations. A numerical example is provided for illustration.

• The Journal of the Acoustical Society of Korea
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• v.24 no.3
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• pp.150-159
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• 2005

This paper addresses a voice personality transformation algorithm which makes one person's voices sound as if another person's voices. In the proposed method, one person's voices are represented by LPC cepstrum, pitch period and speaking rate, the appropriate transformation rules for each Parameter are constructed. The Gaussian Mixture Model (GMM) is used to model one speaker's LPC cepstrums and conditional probability is used to model the relationship between two speaker's LPC cepstrums. To obtain the parameters representing each probabilistic model. a Maximum Likelihood (ML) estimation method is employed. The transformed LPC cepstrums are obtained by using a Minimum Mean Square Error (MMSE) criterion. Pitch period and speaking rate are used as the parameters for prosody transformation, which is implemented by using the ratio of the average values. The proposed method reveals the superior performance to the previous VQ-based method in subjective measures including average cepstrum distance reduction ratio and likelihood increasing ratio. In subjective test. we obtained almost the same correct identification ratio as the previous method and we also confirmed that high qualify transformed speech is obtained, which is due to the smoothly evolving spectral contours over time.

• The Journal of Advanced Prosthodontics
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• v.11 no.2
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• pp.81-87
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• 2019

PURPOSE. The purpose of this study was to evaluate the effects of various protocols and systems for finishing and polishing monolithic zirconia on surface topography, phase transformation, and bacterial adhesion. MATERIALS AND METHODS. Three hundred monolithic zirconia specimens were fabricated and then treated with three finishing and polishing systems (Jota [JO], Meisinger [ME], and Edenta [ED]) using four surface treatment protocols: coarse finishing alone (C); coarse finishing and medium polishing (CM); coarse finishing and fine polishing (CF); and coarse finishing, medium polishing, and fine polishing (CMF). Surface roughness, crystal phase transformation, and bacterial adhesion were evaluated using atomic force microscopy, X-ray diffraction, and streptococcal biofilm formation assay, respectively. One-way and two-way analysis of variance with Tukey post hoc tests were used to analyze the results (${\alpha}=.05$). RESULTS. In this study, the surface treatment protocols and systems had significant effects on the resulting roughness. The CMF protocol produced the lowest roughness values, followed by CM and CF. Use of the JO system produced the lowest roughness values and the smallest biofilm mass, while the ME system produced the smallest partial transformation ratio. The ED group exhibited the highest roughness values, biofilm mass, and partial transformation ratio. CONCLUSION. Stepwise surface treatment of monolithic zirconia, combined with careful polishing system selection, is essential to obtaining optimal microstructural and biological surface results.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.1
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• pp.28-40
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• 1991

Affine transformation was used to analyze the bending, buckling and vibration behaviors of a thick antisymmetric angle-ply rectangular simply supported laminate. Introducing the generalized parameters, the comprehensive solutions are found. The generalized parameters are a generalized rigidity ratio ( $D^*1), a generalized Poisson's ratio (.epsilon.) and a principal rigidity ratio (.alpha.). Hence, the transverse deflection decreases, the uniaxial buckling load and the fundamental frequency increase with increasing $D^*1 and decreasing .alpha., but the effect of .epsilon. is negligible. With decreasing the thickness ratio, the results by the classical plate theory are more erroneous. The transverse deflection is minimum, the uniaxial buckling load and the fundamental frequency are maximum if the fiber angle is 45.deg., and number of plies is more than 4. The time and efforts can be saved to understand the behaviors of composite laminates because these results can be applied to another composite material easily.sily.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.105-127
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• 2024

We propose recurrent neural network (RNN) methods for forecasting realized volatility (RV). The data are RVs of ten major stock price indices, four from the US, and six from the EU. Forecasts are made for relative ratio of adjacent RVs instead of the RV itself in order to avoid the out-of-scale issue. Forecasts of RV ratios distribution are first constructed from which those of RVs are computed which are shown to be better than forecasts constructed directly from RV. The apparent asymmetry of RV ratio is addressed by the Piecewise Min-max (PM) normalization. The serial dependence of the ratio data renders us to consider two architectures, long short-term memory (LSTM) and gated recurrent unit (GRU). The hyperparameters of LSTM and GRU are tuned by the nested cross validation. The RNN forecast with the PM normalization and ratio transformation is shown to outperform other forecasts by other RNN models and by benchmarking models of the AR model, the support vector machine (SVM), the deep neural network (DNN), and the convolutional neural network (CNN).