• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.205-215
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• 2021

Sufficient dimension reduction is useful dimension reduction tool in regression, and sliced inverse regression (Li, 1991) is one of the most popular sufficient dimension reduction methodologies. In spite of its popularity, it is known to be sensitive to the number of slices. To overcome this shortcoming, the so-called fused sliced inverse regression is proposed by Cook and Zhang (2014). Unfortunately, the two existing methods do not have the direction application to large p-small n regression, in which the dimension reduction is desperately needed. In this paper, we newly propose seeded sliced inverse regression and seeded fused sliced inverse regression to overcome this deficit by adopting iterative projection approach (Cook et al., 2007). Numerical studies are presented to study their asymptotic estimation behaviors, and real data analysis confirms their practical usefulness in high-dimensional data analysis.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.513-521
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• 2018

The goal of sufficient dimension reduction (SDR) is to replace original p-dimensional predictors with a lower-dimensional linearly transformed predictor. The sliced inverse regression (SIR) (Li, Journal of the American Statistical Association, 86, 316-342, 1991) is one of the most popular SDR methods because of its applicability and simple implementation in practice. However, SIR may yield different dimension reduction results for different numbers of slices and despite its popularity, is a clear deficit for SIR. To overcome this, a fused sliced inverse regression was recently proposed. The study shows that the dimension-reduced predictors is robust to the numbers of the slices, but it does not investigate how robust its dimension determination is. This paper suggests a permutation dimension determination for the fused sliced inverse regression that is compared with SIR to investigate the robustness to the numbers of slices in the dimension determination. Numerical studies confirm this and a real data example is presented.

• Communications for Statistical Applications and Methods
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• v.28 no.3
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• pp.267-279
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• 2021

A regression with multi-dimensional responses is quite common nowadays in the so-called big data era. In such regression, to relieve the curse of dimension due to high-dimension of responses, the dimension reduction of predictors is essential in analysis. Sufficient dimension reduction provides effective tools for the reduction, but there are few sufficient dimension reduction methodologies for multivariate regression. To fill this gap, we newly propose two fused slice-based inverse regression methods. The proposed approaches are robust to the numbers of clusters or slices and improve the estimation results over existing methods by fusing many kernel matrices. Numerical studies are presented and are compared with existing methods. Real data analysis confirms practical usefulness of the proposed methods.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.533-541
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• 2017

Sufficient dimension reduction (SDR) replaces original p-dimensional predictors to a lower-dimensional linearly transformed predictor. The sliced inverse regression (SIR) has the longest and most popular history of SDR methodologies. The critical weakness of SIR is its known sensitive to the numbers of slices. Recently, a fused sliced inverse regression is developed to overcome this deficit, which combines SIR kernel matrices constructed from various choices of the number of slices. In this paper, the fused sliced inverse regression and SIR are compared to show that the former has a practical advantage in survival regression over the latter. Numerical studies confirm this and real data example is presented.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.546-547
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• 2007

Magnesium is widely used as a lightweight alloy for car engine components and case of cellular phone. Extraction technologies of magnesium are divided to fused salt electrolysis process and thermal reduction process. In this study, electrolysis magnesium is prepared by fused salt electrolysis process with magnesium chloride. We compared two kinds of mixed salt at 7V. As a result, 47% of current efficiency was obtained by electrolyzing KCl/NaCl/$MgCl_2$ mixed salt bath at $760^{\circ}C$, and purity of the prepared magnesium was over 98%. With this study, we can scale up fused salt electrolysis device and accumulate basic data which will be needed for designing an electrolysis cell.

• Resources Recycling
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• v.26 no.3
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• pp.69-78
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• 2017

Magnesium has been used as parts of vehicles, case materials of notebook PC and mobile phone, and its demand has been increasing recently. Its extraction technologies were classified according to the two major reduction methods: the fused salt electrolysis and the thermal reduction method. A research on the extraction of magnesium from magnesite which has been being carried out at KIGAM was briefly introduced here. Magnesium was prepared using a fused salt electrolysis method through preparation of anhydrous magnesium chloride with lab scale experiments.

• Korean Journal of Organic Agriculture
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• v.8 no.2
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• pp.89-96
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• 2000

To reduce loss of nitrogen and generation of ammonia gas during composting, poultry manure and sawdust were mixed at the equivalent ratio and calcium chloride, fused superphosphate and vermiculite were added. Ammonia and sulfurous gas during composting, and NH4-N and NO3-N contents of composts were periodically measured. With the treatments of 0.5∼3% calcium chloride and 3% fused superphosphate, ammonia and sulfurous gas during composting significantly decreased, and especially generation of gases sharply reduced and a increase of calcium chlorde. Extractable NH4-N content in composts treasted with calcium chloride and fused superphosphate were high but extractable NO3-N markedly decreased. In conclusion, the results suggest that it is necessary the additon of 1∼3% calcium chloride or 3% fused superphosphate to reduce loss of nirogen and generation of offensive odor during composting of poultry manure mixed with sawdust.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.835-842
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• 2018

The so-called sliced average variance estimation (SAVE) is a popular methodology in sufficient dimension reduction literature. SAVE is sensitive to the number of slices in practice. To overcome this, a fused SAVE (FSAVE) is recently proposed by combining the kernel matrices obtained from various numbers of slices. In the paper, we consider practical applications of FSAVE to large p-small n data. For this, near-infrared spectroscopy of biscuit dough data is analyzed. In this case study, the usefulness of FSAVE in high-dimensional data analysis is confirmed by showing that the result by FASVE is superior to existing analysis results.

• Resources Recycling
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• v.16 no.2 s.76
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• pp.3-11
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• 2007

It is to review the current status of magnesium smelting. Raw materials for magnesium source, worldwide production and producers of metallic magnesium, Korean magnesium markets and some important extraction technologies were reviewed. The magnesium extraction technologies were described according to the two major reduction methods: the fused salt electrolysis and the thermal reduction method. Also, the research on the extraction of magnesium from magnesite which has been being carried out at KIGAM was briefly introduced with discussing the related topics on the recycling of the chlorine and the hydrogen chloride gas used in the process.

• Journal of the Korean Ceramic Society
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• v.44 no.6 s.301
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• pp.331-337
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• 2007

High temperature reaction behaviors of various oxide materials (such as bauxite, pyrophyllite, mullite and fused silica powders) used in the refractory materials for tap-hole plugging of blast furnace were investigated with varying temperature in the carbon surrounding. Kinetics of carbothermal reduction of $SiO_2$ for forming SiC with high corrosion resistance were strongly dependent on it's crystalline phase. SiC generation yield increased with increasing catalyst amount in oxide regardless of generated SiO gas amount at temperature of $<1500^{\circ}C$. However, in case of fused silica over $1500^{\circ}C$, SiC generation yield was dominantly influenced by SiO amount without catalyst effect. Bauxite showed the most effective carbothermal reduction reaction, since bauxite have a large amount of catalyst and well-dispersed $SiO_2$ phase in oxide matrix.