• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.453-469
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• 2022

The study of immune cellular composition has been of great scientific interest in immunology because of the generation of multiple large-scale data. From the statistical point of view, such immune cellular data should be treated as compositional. In compositional data, each element is positive, and all the elements sum to a constant, which can be set to one in general. Standard statistical methods are not directly applicable for the analysis of compositional data because they do not appropriately handle correlations between the compositional elements. In this paper, we review statistical methods for compositional data analysis and illustrate them in the context of immunology. Specifically, we focus on regression analyses using log-ratio transformations and the alternative approach using Dirichlet regression analysis, discuss their theoretical foundations, and illustrate their applications with immune cellular fraction data generated from colorectal cancer patients.

• Journal of Ceramic Processing Research
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• v.13 no.spc2
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• pp.403-406
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• 2012

Effect of thickness on ZnO properties including the compositional ratio and crystallinity has been systematically investigated using a variety of characterization tools of x-ray diffraction, field emission scanning electron microscopy, x-ray fluorescence and x-ray photoelectron spectroscopy. Interestingly, it was observed that ZnO films below 80 nm in thickness were in oxygen deficiency, while the oxygen ratio was increased in the films above the thickness, although the compositional ratio of ZnO film was not linearly varied with increasing film thickness. Also, ZnO crystallinity, which is characterized by (002) diffraction pattern, was clearly improved with increasing film thickness. The properties of ZnO film with different sputtering time and the nature of direct current reactive sputtering process were discussed in terms of compositional ratio, especially oxygen ratio in ZnO film.

• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.349-363
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• 2024

Compositional data refers to data where the sum of the values of the components is a constant, hence the sample space is defined as a simplex making it impossible to apply statistical methods developed in the usual Euclidean vector space. A natural approach to overcome this restriction is to consider an appropriate transformation which moves the sample space onto the Euclidean space, and log-ratio typed transformations, such as the additive log-ratio (ALR), the centered log-ratio (CLR) and the isometric log-ratio (ILR) transformations, have been mostly conducted. However, in scenarios with sparsity, where certain components take on exact zero values, these log-ratio type transformations may not be effective. In this work, we mainly suggest an alternative transformation, that is the square-root transformation which moves the original sample space onto the directional space. We compare the square-root transformation with the log-ratio typed transformation by the simulation study and the real data example. In the real data example, we applied both types of transformations to the USG% data obtained from NBA, and used a density based clustering method, DBSCAN (density-based spatial clustering of applications with noise), to show the result.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.81-85
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• 1996

Microwave dielectric properties of 0.15(B $a_{x}$S $r_{0.05}$)O-0.15(S $m_{2}$(1-y)N $d_{2y}$) $O_{3}$-0.7Ti $o_{2}$(x=o.9~0.1[mol.], y=6[m/o]) ceramics were investigated with BaO compositional ratio. Sintered density and resistivity of specimens were independent on the BaO compositional ratio. In the specimen with x=0.975[mol.], dielectric constant, quality factor and temperature coefficient of resonant frequency had good values of 76.52, 3001(at 3[GHz]) and +0.71[ppm/.ceg. C], respectively. By comparing with the stoichiometric compositions of 78.14, 2938(at 3[GHz])+14.19[ppm/.ceg. C], dielectric constant and quality factor showed similar properties, but the temperature coefficient of resonant frequency was highly improved. (author). refs., figs., tabs.s.s.

• Proceedings of the KIEE Conference
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• 1999.07d
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• pp.1680-1682
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• 1999

In this study, three kinds of Mn-Zn ferrite/Ni-Zn ferrite/$Ni_2Y$ ferroxplana prepared by the coprecipitation method were compounded with the silicon rubber, and the ring-shaped specimens with various compositional ratio were made. The material constant of ferrite/rubber composite absorbers was obtained by the 2-port method. The material constants of the ferrite/rubber composite microwave absorber made of three kinds of ferrite with various compositional ratio were utilized in design the matching conditions (frequency and thickness) on the impedance matching map. We were able to predict the matching condition from the matching map. On all three kinds of ferrite/rubber composite microwave absorber with less than compositional ratio 60[wt.%] of ferroxplana, we have found that the reflection losses were over than 20[dB] at the S-Band $(2\sim4[GHz])$ and C-Band$(4\sim8[GHz])$.

• Korean Journal of Materials Research
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• v.34 no.7
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• pp.363-369
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• 2024

In this study, the magnetocaloric effect and transition temperature of bulk metallic glass, an amorphous material, were predicted through machine learning based on the composition features. From the Python module 'Matminer', 174 compositional features were obtained, and prediction performance was compared while reducing the composition features to prevent overfitting. After optimization using RandomForest, an ensemble model, changes in prediction performance were analyzed according to the number of compositional features. The R2 score was used as a performance metric in the regression prediction, and the best prediction performance was found using only 90 features predicting transition temperature, and 20 features predicting magnetocaloric effects. The most important feature when predicting magnetocaloric effects was the 'Fe' compositional ratio. The feature importance method provided by 'scikit-learn' was applied to sort compositional features. The feature importance method was found to be appropriate by comparing the prediction performance of the Fe-contained dataset with the full dataset.

• Macromolecular Research
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• v.17 no.5
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• pp.296-300
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• 2009

Ethylene-1-butene copolymers were prepared with $SiO_2$-supported $TiCl_4$ catalyst by changing of 1-butene/ethylene molar ratio in feed, and the resulting copolymers were analyzed using temperature rising elution fractionation (TREF) and crystallization fractionation (Crystaf) methods to investigated the influence of $C_4/C_2$ molar ratio in feed on chemical compositional distribution and other parameters such as molecular weight and its distribution. TREF analysis showed that the copolymers had a broad and bimodal chemical compositional distribution (CCD) regardless of the content of 1-butene in the copolymer. The chemical composition was in the range of 5 to 55 branches per 1,000 carbons for all copolymers prepared in the study. Furthermore, the broader CCD was revealed for the copolymers having the higher content of 1-butene. Crystaf analysis did not showed a bimodal CCD for the copolymers having the 1-butene content of less than 5.1 wt%. The lower crytalline part having 1-butene content in Crystaf analysis was less than of TREF analysis.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.69-87
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• 2014

This paper suggests a conditional simulation framework based on multiple data transformations for geostatistical simulation of compositional data. First, log-ratio transformation is applied to original compositional data in order to apply conventional statistical methodologies. As for the next transformations that follow, minimum/maximum autocorrelation factors (MAF) and indicator transformations are sequentially applied. MAF transformation is applied to generate independent new variables and as a result, an independent simulation of individual variables can be applied. Indicator transformation is also applied to non-parametric conditional cumulative distribution function modeling of variables that do not follow multi-Gaussian random function models. Finally, inverse transformations are applied in the reverse order of those transformations that are applied. A case study with surface sediment compositions in tidal flats is carried out to illustrate the applicability of the presented simulation framework. All simulation results satisfied the constraints of compositional data and reproduced well the statistical characteristics of the sample data. Through surface sediment classification based on multiple simulation results of compositions, the probabilistic evaluation of classification results was possible, an evaluation unavailable in a conventional kriging approach. Therefore, it is expected that the presented simulation framework can be effectively applied to geostatistical simulation of various compositional data.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1999.05a
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• pp.247-250
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• 1999

In this study, three kinds of Mn-Zn ferrite/Ni-Zn ferrite/$Ni_2Y$ ferroxplana prepared by the coprecipitation method was compounded with silicon rubber, and thereafter made ring-type specimens with various compositional ratio. The material constant of ferrite/rubber composite absorbers was obtaibed by the 2-port method. The material constants of the ferrite/rubber composite absorber with various compositional ratio of three kinds of ferrite were used to design the matching frequency and thickness with the impedance matching map. We were able to predict the matching condition from the design method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.9
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• pp.4015-4021
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• 2011

The purpose of this study is to investigate the effect of compositional ratio of additives, such as potassium ferrocyanide, aminoacetic acid (=glycine) and 2,2'-dipyridyl, on the physical properties of copper layer deposited by environment-friendly electroless plating reaction. The highest plating rate of copper layer, $9.5mg{\cdot}cm^{-2}{\cdot}hr^{-1}$, was obtained at 20 mg/L of potassium ferrocyanide and 0.01 mol/L of aminoacetic acid, which coincided with the change in the hardness of the copper layer. In the additives used in this study, potassium ferrocyanide was considered to improve the plating rate, aminoacetic acid increased the hardness value of deposited films and 2,2'-dipyridyl enhanced the brightness of copper deposited films.