• Journal of Korea Society of Industrial Information Systems
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• v.27 no.5
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• pp.1-11
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• 2022

With the development of deep learning technology, various research and development are underway to estimate preference rankings through learning, and it is used in various fields such as web search, gene classification, recommendation system, and image search. Approximation algorithms are used to estimate deep learning-based preference ranking, which builds more than k comparison sets on all comparison targets to ensure proper accuracy, and how to build comparison sets affects learning. In this paper, we propose a k-disjoint comparison set generation algorithm and a k-chain comparison set generation algorithm, a novel algorithm for generating paired comparison sets for crowd-sourcing-based deep learning affinity measurements. In particular, the experiment confirmed that the k-chaining algorithm, like the conventional circular generation algorithm, also has a random nature that can support stable preference evaluation while ensuring connectivity between data.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.69-78
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• 2006

In the field of the bioinformatics, it plays an important role in predicting functional information or structure information to search similar sequence in biological DB. Biolrgical sequences have been increased dramatically since Human Genome Project. At this point, because the searching speed for the similar sequence is highly regarded as the important factor for predicting function or structure, the SMP(Sysmmetric Multi-Processors) computer or cluster is being used in order to improve the performance of searching time. As the method to improve the searching time of BLAST(Basic Local Alighment Search Tool) being used for the similarity sequence search, We suggest the nBLAST algorithm performing on the cluster environment in this paper. As the nBLAST uses the MPI(Message Passing Interface), the parallel library without modifying the existing BLAST source code, to distribute the query to each node and make it performed in parallel, it is possible to easily make BLAST parallel without complicated procedures such as the configuration. In addition, with the experiment performing the nBLAST in the 28 nodes of LINUX cluster, the enhanced performance according to the increase in the number of the nodes has been confirmed.

• Proceedings of the Korean Vacuum Society Conference
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• 1999.07a
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• pp.53-53
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• 1999

전계방출을 이용한 평판 표시장치는 CRT가 가진 장점을 모두 갖는 동시에 얇고 가벼우며 낮은 전력소모로 완벽한 색을 구현할 수 있는 차세대 표시장치로서 이에 대한 여국가 활발히 이루어지고 있다. 여기에 사용되는 음극물질로서 실리콘이나 몰리 등을 팁모양으로 제작하여 사용해 왔다. 하지만 잔류가스에 의한 역스퍼터링이나 화학적 반응에 의해서 전계방출 성능이 점차 저하되는 등의 해결해야할 많은 문제가 있다. 이러한 문제들을 해결하기 위하여 탄소계 재료로서 다이아몬드, 다이아몬드상 카본 등을 이용하려는 노력이 진행되어 왔다. 이중 유리화 비정형 탄소는 다량의 결함을 가지고 있는 유리질의 고상 탄소 재로로서, 전기전도도가 우수하면서 outgassing이 적고 기계적 강도가 뛰어나며 고온에서도 화학적으로 안정하여 전계방출 소자의 음극재료로서 알맞은 것으로 생각된다. 유리화 비정형 탄소가루를 전기영동법으로 기판에 코팅하여 전계방출 소자를 제작하였다. 전기영동 용액으로 이소프로필알코올에 질산마그네슘과 소량의 증류수, 유리화 비정형 탄소분말을 섞어주었고 기판으로는 몰리(Mo)가 증착된 유리를 사용하였다. 균일한 증착을 위해서 증착후 역전압을 걸어 주는 방법과 증착 후 플라즈마 처리를 하는 등의 여러 가지 방법을 사용했다. 전계방출 전류는 1$\times$10-7Torr이사에서 측정하였다. 1회 제작된 용액으로 반복해서 증착한 횟수에 따라 표면의 거치기, 입자의 분포, 전계방출 측정 결과 등의 차이가 관찰되었다. 발광이미지는 전압에 따라 변화하였고, 균일한 발광을 관찰하기 위해서 오랜 시간동안 aging 과정을 거쳐야 했다. 그리고 구 모양의 양극을 사용해서 위치를 변화시키며 시동 전기장을 관찰하여 위치에 따른 전계방출의 차이를 조사하여 발광의 균일성을 알 수 있었다.on microscopy로 분석하였으며 구조 분석은 X-선 회절분석, X-ray photoelectron spectroscopy 그리고Auger electron spectroscope로 하였다. 증착된 산화바나듐 박막의 전기화학적 특성을 분석하기 위하여 리튬 메탈을 anode로 하고 EC:DMC=1:1, 1M LiPF6 액체 전해질을 사용한 Half-Cell를 구성하여 200회 이상의 정전류 충 방전 시험을 행하였다. Half-Cell test 결과 박막의 결정성과 표면상태에 따라 매우 다른 전지 특성을 나타내었다.도상승율을 갖는 경우가 다른 베이킹 시나리오 모델에 비해 효과적이라 생각되며 초대 필요 공급열량은 200kW 정도로 산출되었다. 실질적인 수치를 얻기 위해 보다 고차원 모델로의 해석이 필요하리라 생각된다. 끝으로 장기적인 관점에서 KSTAR 장치의 베이킹 계획도 살펴본다.습파라미터와 더불어, 본 연구에서 새롭게 제시된 주기분할층의 파라미터들이 모형의 학습성과를 높이기 위해 함께 고려된다. 한편, 이러한 학습과정에서 추가적으로 고려해야 할 파라미터 갯수가 증가함에 따라서, 본 모델의 학습성과가 local minimum에 빠지는 문제점이 발생될 수 있다. 즉, 웨이블릿분석과 인공신경망모형을 모두 전역적으로 최적화시켜야 하는 문제가 발생한다. 본 연구에서는 이 문제를 해결하기 위해서, 최근 local minimum의 가능성을 최소화하여 전역적인 학습성과를 높여 주는 인공지능기법으로서 유전자알고리즘기법을 본 연구이 통합모델에 반영하였다. 이에 대한 실증사례 분석결과는 일일 환율예측문제를 적용하였을 경우, 기존의 방법론보다 더 나운 예측성과를 타나내었다.pective" to workflow architectural discussions. The vocabulary suggested

• Weed & Turfgrass Science
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• v.5 no.4
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• pp.196-202
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• 2016

With increasing LM soybean import, the concern about unintentional gene flow from LM soybean to wild soybean and consequential weedy risk has been growing. Therefore, we conducted this study to characterize seed traits including germination of hybrids resulted from gene flow from LM soybean to wild soybean in comparison with their parents, LM soybean and wild soybean. Pollen-donor LM soybean seeds were much greater and heavier (about 15.0 g of 100 seed weight) than F2 hybrid (5.7 g), while pollen-recipient wild soybean and F1 hybrid seeds were smallest and lightest (about 2.5 g). F2 hybrid was brown, intermediate between yellow LM soybean seed and black wild soybean seed. These findings indicate that F1 hybrid seeds show similar characteristics with wild soybean, while F2 hybrid seeds show intermediate color and size between two parents. F2 hybrid seed showed intermediate traits between two parents in germination and dormancy rates, which were 35% and 65%, respectively. LM soybean showed no dormancy, while wild soybean showed greater than 90% dormancy. This finding indicates that F2 hybrid show intermediate characteristics in seed germination with high dormancy trait, suggesting a potential weediness of hybrids resulted from gene flow from LM soybean to wild soybean.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.211-226
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• 2019

Pig CD45, the leukocyte common antigen, is encoded by the PTPRC gene and CD45 is a T cell-type specific tyrosine phosphatase with alternative splicing of its exons. The CD45 is a coordinated regulator of T cell antigen receptor (TCR) signal transduction achieved by dephosphorylating the phosphotyrosine of its substances, including $CD3{\zeta}$ chain of TCR, Lck, Fyn, and Zap-70 kinase. A dysregulation of CD45 is associated with a multitude of immune disease and has been a target for immuno-drug discovery. To characterize its key structural features with the effects of regulating TCR signaling, this study predicted the unknown structure of pig CD45RO (the smallest isoform) and the complex structure bound to the ITAM (REEpYDV) of $CD3{\zeta}$ chain via homology modeling and docking the peptide, based on the known human CD45 structures. These features were integrated into the structural plasticity of extracellular domains and functional KNRY and PTP signature motifs (the role of a narrow entrance into ITAM binding site) of the tyrosine phosphatase domains in a cytoplasmic region from pig CD45RO. This contributes to the selective recognition of phosphotyrosine from its substrates by adjusting the structural stability and binding affinity of the complex. The characterized features of pigCD45RO can be applied in virtual screening of the T-cell specific immunomodulator.

• Journal of Life Science
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• v.33 no.11
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• pp.876-886
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• 2023

In some cases of head and neck cancers (HNC), surgical interventions may result in the loss of organs and/or changes to their functions, thereby significantly affecting the patient's quality of life. As a result, the surgical treatment of HNC patients is often limited to specific cases, and alternative treatment modalities, such as chemotherapy, are considered. However, serious adverse effects caused by chemotherapy, such as severe nausea and vomiting, necessitate the need for the development of adjunctive methods to minimize patient suffering. Chuanxiong, Ligusticum chuanxiong (L. chuanxiong), is a natural herb used in Eastern medicine to treat cerebrovascular disorders and headaches. This study aimed to predict the effect and potential of L. chuanxiong as an auxiliary anticancer drug through network-based pharmacology and molecular docking analysis. The study results showed that 40 out of 41 genes of L. chuanxiong shared common targets of HNC and their proteins could be used to target HNC cells to prevent cancer progression. The results of the functional enrichment analysis confirmed that L. chuanxiong is associated with the neuroactive-ligand metabolism and neurotransmitter pathways, indicating its potential medicinal value as an adjuvant in HNC treatment. Lastly, our findings demonstrated that the active ingredient of L. chuanxiong, (Z)-Ligustilide, has the ATP binding site of heat shock protein 90, a protein known to promote the activation of cancer cells. These results suggest that L. chuanxiong is a promising candidate for developing auxiliary anticancer drugs, and further research could potentially lead to the discovery of newer and safer anti-cancer agents.

• Childhood Kidney Diseases
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• v.4 no.1
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• pp.33-39
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• 2000

Purpose: Our study was designed to investigate the association of MHC Class II (DR, DQ) allele with IgA nephropathy and its significance as a prognostic factor for progression to ESRD Material and Methods: 69 children with IgA nephropathy with normal renal function(serum creatinine $\leq$ 1.5mg/dL) was classified as group A and 70 patients who received renal transplantation due to IgA nephropathy were selected as group B. The HLA-DQB1 and HLA-DRB1 alleles were studied by polymerase chain reaction using sequence specific primers. We have compared the difference in alleles between these two groups and with normal control and also examined any possible effect of the MHC class II genes on the histopathological severity and prognosis of IgAN. Results: Mean age was $8.8{\pm}2.9$ years in group A and $35.0{\pm}15.5$ years in group B. Male to female ratio was 2.8:1 in group A and 2.5:1 in group B. There was a significantly higher frequency of HLA-$DQB1^*03\;and\;DQB1^*05$ in Group B. The frequency of HLA-$DQB1^*0302\;and\;^*05031$ allele had increasing tendency in Group B(P<0.05). HLA-$DRB1^*03\;and\;^*05$ were more common in Group B(P<0.05). HLA-$DRB1^*04$ allele was the most common DR alleles in both group, but there was no statistical significance. There were no significant correlation with MHC class 13 genes on the hjstopathological severity in Group A. Conclusion: In conclusion, $HLA-DQB1^*0302\;and\;HLA-DQB1^*05031 $ allele seemed to be more common in transplanted patients compared to group with normal renal function suggesting that this allele is associated with poor prognosis in IgAN. However larger studies and follow up are required to confirm this due to uncharacterized heterogeneity in etiopathogenesis of IgA nephropathy and possibly one or more than one gene may exert influence in determining susceptibility to the diseases.

• 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 Life Science
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• v.25 no.6
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• pp.680-685
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• 2015

Previously, cellulase and xylanase producing microorganism, Bacillus subtilis NC1, was isolated from soil. Based on the 16S rRNA gene sequence and API 50 CHL test the strain was identified as Bacillus subtilis, and named as B. subtilis NC1. We cloned and sequenced the genes for cellulase and xylanase. Plus, the deduced amino acid sequences from the genes of cellulase and xylanase were determined and were also identified as glycosyl hydrolases family (GH) 5 and 30, respectively. In this study to optimize the medium parameters for cellulase production by B. subtilis NC1 the RSM (response surface methodology) based on CCD (central composite design) model was performed. Three factors, tryptone, yeast extract, and NaCl, for N or C source were investigated. The cellulase activity was measured with a carboxylmethyl cellulose (CMC) plate and the 3,5-dinitrosalicylic acid (DNS) methods. The coefficient of determination (R²) for the model was 0.960, and the probability value (p=0.0001) of the regression model was highly significant. Based on the RSM, the optimum conditions for cellulase production by B. subtilis NC1 were predicted to be tryptone of 2.5%, yeast extract of 0.5%, and NaCl of 1.0%. Through the model verification, cellulase activity of Bacillus subtilis NC1 increased from 0.5 to 0.62 U/ml (24%) compared to the original medium.

• Journal of Life Science
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• v.29 no.9
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• pp.1002-1009
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• 2019

Early life stress (ELS) increases the risk of depression. ELS may be involved in the susceptibility to subsequent stress exposure during adulthood. We investigated whether epigenetic mechanisms of p11 promoter affect the vulnerability to chronic unpredictable stress (CUS) induced by the maternal separation (MS). Mice pups were separated from their dams (3 hr/day from P1-P21). When the pups reached adulthood, we applied CUS (daily for 3 weeks). The levels of hippocampal p11 expression were analyzed by quantitative real-time PCR. The levels of acetylated and methylated histone H3 at p11 promoter were measured by chromatin immunoprecipitation. Depression-like behavior was measured by the forced swimming test (FST). The MS and CUS group exhibited significant decreases in p11 mRNA level and the MS plus CUS group had a greater reduction in this level than the CUS group. The MS plus CUS group also resulted in greater reduction in H3 acetylation than the CUS group. This reduction was associated with an upregulation of histone deacetylase 5. Additionally, the MS plus CUS group showed a greater decrease in H3K4met3 level and a greater increase in H3K27 met3 level than the CUS group. Consistent with the reduction of p11 expression, the MS plus CUS group displayed longer immobility times in the FST compared to the control group. Mice exposed to MS followed by CUS had much greater epigenetic alterations in the hippocampus compared to adult mice that only experienced CUS. ELS can exacerbate the effect of stress exposure during adulthood through histone modification of p11 gene.