• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.532-540
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• 2019

PET microfibers with various diameters (0.5, 0.2, 0.06, and 0.01 dpf) were dyed with a dispersed dye (C.I. Disperse Blue 56) at various temperatures. The dyeing process was conducted under infinite dyebath conditions at constant temperatures. The effects of the dyeing temperature and diameter on the partition coefficient, affinity, and diffusion coefficient of disperse dyes were studied. The curve of isotherms was fitted well to Nernst-type model in a large range of initial dye concentrations. At the same temperature, the partition coefficient and affinity decreased with increasing sample diameter due to the increase in surface area. At all deniers, the partition coefficient and affinity decreased with increasing temperature because the dyeing process is an exothermic reaction. In addition, the decrease in radius of the sample gives rise to a decrease in the heat of dyeing. The fine diameter of the sample resulted in an increased surface area but decreased space between the microfibers. Consequently, decreasing the diameter of the microfibers leads to a decrease in the diffusion coefficient. At the same diameter, the diffusion coefficient increased with increasing temperature because of rapid dye movement and the large free volume of the sample inside. In addition, thermal dependence of the diffusion coefficient increased when the diameter of the sample increased.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.04a
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• pp.62-62
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• 2019

Bacterial leaf blight(BLB), caused by X. oryzae pv. oryzae(Xoo), is one of the most destructive diseases of rice due to its high epidemic potential. Understanding BLB resistance at a genetic level is important to further improve the rice breeding that provides one of the best approaches to control BLB disease. In the present investigation, a collection of 192 accessions was used in the genome-wide association study (GWAS) for BLB resistance loci against four Korean races of Xoo that were represented by the prevailing BLB isolates under Xoo differential system. A total of 192 accessions of rice germplasm were selected on the basis of the bioassay using four isolated races of Xoo such as K1 and K2. The selected accessions was used to prepare 384-plex genotyping by sequencing (GBS) libraries and Illumina HiSeq 2000 pairedend read was used for GBS sequencing. GWAS was conducted using TASSEL 5.0. The TASSEL program uses a mixed linear model (MLM). The results of the bioassay using a selected set of 192 accessions showed that a large number of accessions (93.75%) were resistant to K1 race and K2 resistant germplasm proportion remained between 66.67. The genotypic data produced SNP matrix for a total of 293,379 SNPs. After imputation the missing data was removed, which exhibited 34,724 SNPs for association analysis. GWAS results showed strong signals of association at a threshold of [-log10(P-value)] more than 5 (K1 and K2) for nine of the 39 SNPs, which are plausible candidate loci of resistance genes. These SNP loci were positioned on rice chromosome 2, 9, and 11 for K1 and K2 races. The significant loci detected have also been illustrated and make the CPAS markers for NBS-LRR type disease resistance protein, SNARE domain containing protein, Histone deacetylase 19, NADP-dependent oxidoreductase, and other expressed and unknown proteins. Our results provide a better understanding of the distribution of genetic variation of BLB resistance to Korean pathogen races and breeding of resistant rice.

• (The)Study of the Eastern Classic
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• no.41
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• pp.477-516
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• 2010

The Korean art history academia has lately been carrying out active research on the Korean art market and art collectors. This area of research is significant in that it attempts to overcome the limitations of previous research trends focused on tracing back and analyzing preeminent masters, their schools and their influence, and approach new subject matters such as art and society, circulation and consumption of art works, which were unapproachable with previous research methods. This paper examines the life, artwork and art collection activities of Songeun(松隱) Yi Byeong-jik(李秉直: 1896-1973), an outstanding painter, calligrapher and art collector during the Japanese colonial period. The primary purpose of this paper is to advance the research project the author has recently initiated on modern Korean art collectors by reconstructing parts of this major art collector's individual lifestyle and to generally identify the art collection activities and the art works that he kept. Yi Byeong-jik, one of the preeminent art collectors during the colonial period, disposed his voluminous collection through two auctions in 1937 and 1941, and then held another auction two weeks before the onset of the Korean War on June 25, 1950 to sell off the remaining works. It seems that the reason why Yi had auctioned off his collections was for the purpose of investing in education. The tale that Yi safely kept 'Sam-guk-yu-sa(三國遺事),' which is considered a national treasure, even through the time of turbulence is evidence of his exemplary behavior as a model art collector. He may be one of the best examples of what an art collector should be in terms of giving back to the society and preserving things of beauty and value. However, one factor that limited and defined Yi's life was that he was a eunuch. This aspect of his life could be pointed out as the biggest factor that stopped him from becoming a mainstream participant in the art world despite his influence as a great painter, calligrapher, significant art collector, and discerning connoisseur.

• Korean Journal of Metals and Materials
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• v.49 no.8
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• pp.628-634
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• 2011

SA508 Gr.4N Ni-Cr-Mo low alloy steel, in which Ni and Cr contents are higher than in commercial SA508 Gr.3 Mn-Mo-Ni low alloy steels, may be a candidate reactor pressure vessel (RPV) material with higher strength and toughness from its tempered martensitic microstructure. The inner surface of the RPV is weld-cladded with stainless steels to prevent corrosion. The goal of this study is to evaluate the microstructural properties of the clad interface between Ni-Cr-Mo low alloy steel and stainless weldment, and the effects of post weld heat treatment (PWHT) on the properties. The properties of the clad interface were compared with those of commercial Mn-Mo-Ni low alloy steel. Multi-layer welding of model alloys with ER308L and ER309L stainless steel by the SAW method was performed, and then PWHT was conducted at $610^{\circ}C$ for 30 h. The microstructural changes of the clad interface were analyzed using OM, SEM and TEM, and micro-Vickers hardness tests were performed. Before PWHT, the heat affected zone (HAZ) showed higher hardness than base and weld metals due to formation of martensite after welding in both steels. In addition, the hardness of the HAZ in Ni-Cr-Mo low alloy steel was higher than that in Mn-Mo-Ni low alloy steel due to a comparatively high martensite fraction. The hardness of the HAZ decreased after PWHT in both steels, but the dark region was formed near the fusion line in which the hardness was locally high. In the case of Mn-Mo-Ni low alloy steel, formation of fine Cr-carbides in the weld region near the fusion line by diffusion of C from the base metal resulted in locally high hardness in the dark region. However, the precipitates of the region in the Ni-Cr-Mo low alloy steel were similar to that in the base metal, and the hardness in the region was not greatly different from that in the base metal.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.133-140
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• 2022

We investigate the performance of deep learning-based Korean language models on a task of predicting the score range of Korean essays written by foreign students. We construct a data set containing a total of 304 essays, which include essays discussing the criteria for choosing a job ('job'), conditions of a happy life ('happ'), relationship between money and happiness ('econ'), and definition of success ('succ'). These essays were labeled according to four letter grades (A, B, C, and D), and a total of eleven essay score range prediction experiments were conducted (i.e., five for predicting the score range of 'job' essays, five for predicting the score range of 'happiness' essays, and one for predicting the score range of mixed topic essays). Three deep learning-based Korean language models, KoBERT, KcBERT, and KR-BERT, were fine-tuned using various training data. Moreover, two traditional probabilistic machine learning classifiers, naive Bayes and logistic regression, were also evaluated. Experiment results show that deep learning-based Korean language models performed better than the two traditional classifiers, with KR-BERT performing the best with 55.83% overall average prediction accuracy. A close second was KcBERT (55.77%) followed by KoBERT (54.91%). The performances of naive Bayes and logistic regression classifiers were 52.52% and 50.28% respectively. Due to the scarcity of training data and the imbalance in class distribution, the overall prediction performance was not high for all classifiers. Moreover, the classifiers' vocabulary did not explicitly capture the error features that were helpful in correctly grading the Korean essay. By overcoming these two limitations, we expect the score range prediction performance to improve.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.309-328
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• 2022

This study empirically analyzed a Korean pre-trained language models (PLMs) designed for natural language generation. The performance of two PLMs - BART and GPT - at the task of abstractive text summarization was compared. To investigate how performance depends on the characteristics of the inference data, ten different document types, containing six types of informational content and creation content, were considered. It was found that BART (which can both generate and understand natural language) performed better than GPT (which can only generate). Upon more detailed examination of the effect of inference data characteristics, the performance of GPT was found to be proportional to the length of the input text. However, even for the longest documents (with optimal GPT performance), BART still out-performed GPT, suggesting that the greatest influence on downstream performance is not the size of the training data or PLMs parameters but the structural suitability of the PLMs for the applied downstream task. The performance of different PLMs was also compared through analyzing parts of speech (POS) shares. BART's performance was inversely related to the proportion of prefixes, adjectives, adverbs and verbs but positively related to that of nouns. This result emphasizes the importance of taking the inference data's characteristics into account when fine-tuning a PLMs for its intended downstream task.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.35-43
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• 2021

Recently, there has been a growing interest in zero-shot cross-lingual transfer, which leverages cross-lingual language models (CLLMs) to perform downstream tasks that are not trained in a specific language. In this paper, we point out the limitations of the data-centric aspect of quality estimation (QE), and perform zero-shot cross-lingual transfer even in environments where it is difficult to construct QE data. Few studies have dealt with zero-shots in QE, and after fine-tuning the English-German QE dataset, we perform zero-shot transfer leveraging CLLMs. We conduct comparative analysis between various CLLMs. We also perform zero-shot transfer on language pairs with different sized resources and analyze results based on the linguistic characteristics of each language. Experimental results showed the highest performance in multilingual BART and multillingual BERT, and we induced QE to be performed even when QE learning for a specific language pair was not performed at all.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.553-562
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• 2023

The Gobiobotia naktongensis is a species endemic to Korea, and it has recently been designated as a class I endangered species of freshwater fish. Naeseong Stream, one of the tributaries of the Nakdong River, where the Gobiobotia naktongensis was first discovered, provided an optimal habitat for the Gobiobotia naktongensis in the past with fine sand beds and riffle. Currently, due to the construction of Yeongju Dam and the excessive dredging of river channels by the local government, the riverbed armoring in the downstream area of the dam is undergoing rapid changes, and as a result, the habitat environment of the Gobiobotia naktongensis is deteriorating. In this study, the variations of the habitat suitability of the Gobiobotia naktongensis due to the change in the riverbed grain size of the Naeseong Stream were analyzed based on the WUA (weight usable area) using the physical habitat model, River2D. The study domain is the reach from Seoktap Bridge to Hoeryong Bridge downstream of Yeongju Dam. The change in riverbed grain size was analyzed using D50 acquired in 2010 and 2020, respectively. The substrate grain size of Naeseong Stream in 2020 was thicker than that in 2010, and the riverbed coarsening phenomenon was evident overall. As a result of the River2D analysis, the area in which the Gobiobotia naktongensis could inhabit was only about 0.75% in 2010 compared to the entire area of the flow, and even this decreased to 0.55% in 2020 due to riverbed armoring.

• Journal of Dental Rehabilitation and Applied Science
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• v.38 no.4
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• pp.196-203
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• 2022

Purpose: This study aimed to evaluate the accuracy and clinical usability of an identification model using deep learning for 79 dental implant types. Materials and Methods: A total of 45396 implant fixture images were collected through panoramic radiographs of patients who received implant treatment from 2001 to 2020 at 30 dental clinics. The collected implant images were 79 types from 18 manufacturers. EfficientNet and Meta Pseudo Labels algorithms were used. For EfficientNet, EfficientNet-B0 and EfficientNet-B4 were used as submodels. For Meta Pseudo Labels, two models were applied according to the widen factor. Top 1 accuracy was measured for EfficientNet and top 1 and top 5 accuracy for Meta Pseudo Labels were measured. Results: EfficientNet-B0 and EfficientNet-B4 showed top 1 accuracy of 89.4. Meta Pseudo Labels 1 showed top 1 accuracy of 87.96, and Meta pseudo labels 2 with increased widen factor showed 88.35. In Top5 Accuracy, the score of Meta Pseudo Labels 1 was 97.90, which was 0.11% higher than 97.79 of Meta Pseudo Labels 2. Conclusion: All four deep learning algorithms used for implant identification in this study showed close to 90% accuracy. In order to increase the clinical applicability of deep learning for implant identification, it will be necessary to collect a wider amount of data and develop a fine-tuned algorithm for implant identification.

• Journal of the Korean Geotechnical Society
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• v.22 no.9
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• pp.61-68
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• 2006

Recently the large scale civil engineering projects are being implemented by reclaiming the sea or utilizing seashore and river embankment areas. The reclaimed land and utilized seashore are mostly soft ground that doesn't have sufficient bearing capacity. This soft ground consists of fine-grained soil such as clayey and silty soils or large void soil like peat or loose sand. It has high ground water table and it may cause the failure and crock of building foundation by uplift pressure and ground water leakage. In this study, the permittivity and the transmissivity were evaluated with the applied normal pressure in the laboratory. The laboratory model tests were conducted by utilizing geocomposite drainage system for draining the water out to release the uplift pressure. The soil used in the laboratory drainage test was dredged soil from the reclaimed land where uplift pressure problems can arise in soil condition. Geocomposite drainage system was installed at the bottom of apparatus and dredged soil was layered with compaction. Subsequently the water pressure was supplied from the top of specimen and the quantities of drainage and the pore water pressure were measured at each step water pressure. The results of laboratory measurements were compared with theoretical values. For the evaluation of propriety of laboratory drainage test, 2-D finite elements analysis that can analyze the distribution and the transferring of pore water pressure was conducted and compared with laboratory test results.