• Ocean and Polar Research
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• v.21 no.2
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• pp.109-116
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• 1999

Total lipid content, lipid class and fatty acid composition of the Antarctic krill Euphausia superba collected from the water of King George Island, Antarctica during austral summer of 1997-1998, were investigated. The overall lipid content of 5. superba was 72 mg/g dry mass similar to the reported values for most temperate species. The neutral lipid of E. superba was 29% of the total lipid and that of phospholipid was 71%. The majority of neutral lipid was triacylglycerols(31.6% of neutral lipids) while phosphatidyl choline (44% of phospholipid) was the most abundunt in phospholipids. The quantitative composition of the fatty acid in E. superba show consisting mostly of the saturated 16:0 (16.6% -22.1%), along with the polyunsaturated 20:5(n-3) (20.6% -22.1%) and 22:6(n-3) (14.9% -16.9%) acids.

• Journal of the Korean Chemical Society
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• v.55 no.6
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• pp.969-973
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• 2011

The synthesis, as well as spectroscopic and biological studies of a novel class of [3-(4-substitutedphenylamino)-8-azabicyclo [3.2.1] oct-8yl]-phenyl-methanone derivatives are described. All the synthesized compounds were characterized by elemental analysis FTIR, $^1H$-NMR, $^{13}C$ NMR, and Mass spectral data. All the synthesized compounds were exhibit in vitro antibacterial activity.

• Bulletin of the Korean Chemical Society
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• v.28 no.5
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• pp.821-826
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• 2007

Several oxazolidinones, a new class of synthetic antibacterial agents, have shown biological activity against multidrug-resistant gram positive organisms such as staphylococci, streptococci, and enterococci. Previous results of our studies with benzoxazolidinone phosphonate derivatives have demonstrated very low antibacterial activity. In the course of our studies directed towards the discovery of noble antibacterial agents, we have synthesized several new derivatives of oxazolidinone phosphonates prepared efficiently from commercially available amino acids. These compounds are tested for in vitro antibacterial activity and one of the compounds showed promising results allowing us to pursue further studies.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.455-456
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• 2014

본 연구에서는 예비교사가 학교 현장에서 적용할 수 있는 STEAM 수업 프로그램 개발을 위한 역량을 기르기 위한 수업을 개발하였다. 오픈소스와 CT (Computational Thinking)를 활용하여 팀별 프로젝트 (아두이노 및 스크래치 활용)를 진행하는 방식의 STEAM 교육을 통해 학생들의 창의성을 기를 수 있도록 수업내용을 구성하고 시범운영하였다. 이 수업을 통해 예비교사들은 다양한 학문 분야에서의 문제해결능력이 서로 밀접하게 연관되어 있음을 이해하고, 융합인재를 길러나갈 수 있는 역량을 기르게 될 것이다.

• Journal of the Korean Magnetic Resonance Society
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• v.17 no.2
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• pp.76-80
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• 2013

The TCP domain is a DNA-binding domain present in plant transcription factors and has a similar structural feature to the bHTH motif of eukaryotic transcription factors. The imino proton exchange study has been performed for the DNA duplex containing the consensus DNA-binding site for the AtTCP11 transcription factor. The first two base pairs in the consensus 5'-GTGGG-3' sequence are relatively very unstable but lead to greater stabilization of the neighboring two G C base pairs. These unique dynamic features of the five base pairs in the consensus DNA sequence might play crucial roles in the effective DNA binding of the AtTCP11 protein.

• Bulletin of the Korean Chemical Society
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• v.10 no.1
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• pp.15-19
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• 1989

Mass spectral fragmentations of some s-triazine herbicides have been investigated using tandem mass spectrometry. Major pathways driven by the side chains have been confirmed. However, most of the previously proposed pathways which were thought to be characteristic of the ring have been found unlikely. A class of ring cleavage reactions characteristic of s-triazine rings with alkylamino side chains has been found and the mechanism has been proposed. In addition, tandem mass spectrometry has been utilized to differentiate tautomeric structures and to analyze the fragmentation reactions occurring from the mixture of isobaric ions.

• Bulletin of the Korean Chemical Society
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• v.11 no.5
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• pp.450-455
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• 1990

Fifty eight obsidian artifacts and four obsidian source samples have been analyzed by instrumental neutron activation analysis. Artifact samples have been classified into classes by unsupervised learning techniques such as eigenvector projection and nonlinear mapping. The source samples have thereafter been connected to the classes by the supervised learning techniques such as SLDA and SIMCA so as to characterize each class by possible source sites. Some difference attributable to different nonlinear mapping techniques and the elemental effects on the separation between classes have been discussed.

• Journal of the Korean Chemical Society
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• v.67 no.4
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• pp.281-295
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• 2023

The purpose of this study was to investigate the effects of role assignment in a group on collaboration in a mid- dle school science class to which Collaborative Problem Solving for Character Competency (CoProC) model was applied. For this purpose, 4 classes in the second year of a middle school located in a small and medium-sized city were selected, two classes among these were assigned roles, and the other classes were not. The science class with 4 topics using CoProC model was carried out. As a result of the study, in middle school science class to which CoProC was applied, it was effective in increasing the collaboration. As a result of analyzing the discussion process using the analysis framework for collaboration developed in this study, the group without role assignment was statistically significantly higher than the group with role assignment in the total score and the four sub-factors, especially in 'partnership building' and 'consensus building' which is a high level of collaboration.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.88-95
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• 2017

As the safety fields are expanding to a variety of industrial fields, safety technology has been developed by convergence between industrial safety fields such as mechanics, ergonomics, electronics, chemistry, construction, and information science. As the technology convergence is facilitating recently advanced safety technology, it is important to explore the trends of safety technology for understanding which industrial technologies have been integrated thus far. For studying the trends of technology, the patent is considered one of the useful sources that has provided the ample information of new technology. The patent has been also used to identify the patterns of technology convergence through various quantitative methods. In this respect, this study aims to identify the convergence patterns and fields of safety technology using association rule mining(ARM)-based patent co-classification(co-class) analysis. The patent co-class data is especially useful for constructing convergence network between technological fields. Through linkages between technological fields, the core and hub classes of convergence network are explored to provide insight into the fields of safety technology. As the representative method for analyzing patent co-class network, the ARM is used to find the likelihood of co-occurrence of patent classes and the ARM network is presented to visualize the convergence network of safety technology. As a result, we find three major convergence fields of safety technology: working safety, medical safety, and vehicle safety.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1042-1042
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from daily monitoring of two Japanese cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from two cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA md FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference.