• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 한국소성가공학회 2006년도 춘계학술대회 논문집
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• pp.234-238
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• 2006

In this research, an analysis of damaged instance and forming fault for disc part in automotive steel wheel was performed. Rolled steel material, which had been used in the manufacturing of the damaged disc part, was prepared for tensile test, quantitative analysis of chemical component and acquirement of scanning electron microscope images. Although the results of mechanical properties and chemical component ratio for the material satisfied the suggested specification, some material inherent problem was found in the scanning electron microscope images. Finally, in an analysis of chemical component for the damaged disc part used in road condition, mismatching of chemical component ratio between the suggested specification and test result was found.

• Bulletin of the Korean Chemical Society
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• 제33권8호
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• pp.2799-2802
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• 2012

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2009년도 춘계학술대회 논문집
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• pp.410-411
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• 2009

The multi-component ceramic proton conductor, $BaZr(Y)O_3-SiO_2-TiO_2-ZrO_2$ (BZY-STZ) and $LaPO_4-SiO_2-TiO_2-ZrO_2$ (LP-STZ), were synthesized by micro-emersion and sol-gel technique. The characterization of proton conductors were carried out using X-ray diffraction(XRD), thermogravimetric analysis(TGA), differential thermal analysis(DTA), impedance analysis. The proton conductors indicate the possibility of application for the intermediate temperature up to $700^{\circ}C$.

• Bulletin of the Korean Chemical Society
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• 제32권7호
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• pp.2332-2338
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• 2011

In this study, we proposed a new promising idea of utilizing moving window principal component analysis (MWPCA) as a sensitive diagnostic tool to detect the presence of peak position shift. In this approach, the moving window is constructed from a small data segment along the wavenumber axis. For each window bound by a narrow wavenumber region, separate PCA analysis was applied. Simulated spectra with complex spectral feature variations were analyzed to explore the possibility of MWPCA technique. This MWPCA-based detection of the peak shift, potentially coupled with 2D correlation analysis to provide additional verification, may offer an attractive solution.

• Proceedings of the Korean Reliability Society Conference
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• 한국신뢰성학회 2000년도 추계학술대회
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• pp.269-277
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• 2000

The component reliability database is required in PSA (Probabilistic Safety Analysis) for NPP (Nuclear Power Plant). We have applied a generic database to the PSA for the Korean NPPs, since there is no specific component reliability database. Therefore we are developing the plant-specific component reliability database for domestic NPPs. We also extend the experience and knowledge of PSA and component reliability database for NPP to chemical industry We collect the raw data like component operation history and maintenance history and then input the required data for the component reliability database through failure analysis. With the database, we can not only perform PSA with real data but also perform maintenance optimization.

• Bulletin of the Korean Chemical Society
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• 제24권9호
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• pp.1345-1350
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• 2003

Principal component analysis based two-dimensional (PCA-2D) correlation analysis is applied to FTIR spectra of polystyrene/methyl ethyl ketone/toluene solution mixture during the solvent evaporation. Substantial amount of artificial noise were added to the experimental data to demonstrate the practical noise-suppressing benefit of PCA-2D technique. 2D correlation analysis of the reconstructed data matrix from PCA loading vectors and scores successfully extracted only the most important features of synchronicity and asynchronicity without interference from noise or insignificant minor components. 2D correlation spectra constructed with only one principal component yield strictly synchronous response with no discernible a asynchronous features, while those involving at least two or more principal components generated meaningful asynchronous 2D correlation spectra. Deliberate manipulation of the rank of the reconstructed data matrix, by choosing the appropriate number and type of PCs, yields potentially more refined 2D correlation spectra.

• Korean Chemical Engineering Research
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• 제46권2호
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• pp.383-388
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• 2008

The safe and efficient operation of the chemical processes has become one of the primary concerns of chemical companies, and a variety of fault diagnosis methods have been developed to diagnose faults when abnormal situations arise. Recently, many research efforts have focused on fault diagnosis methods based on quantitative history data-based methods such as statistical models. However, when the history data-based models trained with the data obtained on an operation mode are applied to another operating condition, the models can make continuous wrong diagnosis, and have limits to be applied to real chemical processes with various operation modes. In order to classify operation modes of chemical processes, this study considers three multivariate models of Euclidean distance, FDA (Fisher's Discriminant Analysis), and PCA (principal component analysis), and integrates them with process dynamics to lead dynamic Euclidean distance, dynamic FDA, and dynamic PCA. A case study of the TE (Tennessee Eastman) process having six operation modes illustrates the conclusion that dynamic PCA model shows the best classification performance.

• Journal of Microbiology and Biotechnology
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• 제27권6호
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• pp.1106-1111
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• 2017

Escherichia coli was engineered to sense methanol by employing a chimeric two-component system (TCS) strategy. A chimeric MxaY/EnvZ (MxaYZ) TCS was constructed by fusing the Paracoccus denitrificans MxaY with the E. coli EnvZ. Real-time quantitative PCR analysis and GFP-based fluorescence analysis showed maximum transcription of ompC and the fluorescence at 0.01% of methanol, respectively. These results suggested that E. coli was successfully engineered to sense methanol by the introduction of chimeric MxaYZ. By using this strategy, various chimeric TCS-based bacterial biosensors can be constructed and used for the development of biochemical-producing recombinant microorganisms.

• Journal of Environmental Health Sciences
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• 제30권5호
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• pp.455-468
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• 2004

The purpose of this paper is to understand the time series and origin of a chemical component and to compare the difference during yellow sand episodes for analysis $PM_{10}$ chemical components in the region of west in Korean Peninsula, 1999-2001. An annual mean concentration of $PM_{10}$ is $29.1\;{\mu}g/m^3$. A monthly mean and standard deviation of $PM_{10}$ concentration are very high in spring but there is no remarkably seasonal variation. Also, water soluble ionic component of $PM_{10}$ be influenced by double more total anion than total cation, be included $NO_{3}^-\;and\;SO_{4}^{2-}$ for the source of acidity and $NH_{4}^+$ to neutralize. Tracer metals of $PM_{10}$ slowly increases caused by emitted for soil and ocean (Fe, Al, Ca, Mg, Na) and Zn, Pb, Cu, Mn for anthropogenic source. According to method of enrichment factor (E.F) and statistics, assuming that the origin of metal component in $PM_{10}$ most of element in the Earth's crust e.g. Mg, Ca, Fe originates soil and Cu, Zn, Cd, Pb derives from anthropogenic sources. The ionic component for $Na^{+}\;Cl^-,\;Mg^{2+}\;and\;Ca^{2+}$ and Mg, Al, Ca, Fe originated by soil component largely increase during yellow sand period and then tracer metal component as Pb, Cd, Zn decrease. According to factor analysis, the first group is ionic component ($Na^+,\;Mg^{2+},\;Ca^{2+}$) and metal component (Na, Fe, Mn and Ni) be influenced by soil. The second group, Mg, Cr also be influenced by soil particle.

• Applied Science and Convergence Technology
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• 제23권6호
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• pp.328-339
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• 2014

In this article, plasma monitoring tools and mulivariate analysis techniques were reviewed. Optical emission spectroscopy was reviewed for a chemical composition analysis tool and RF V-I probe for a physical analysis tool for plasma monitoring. Multivariate analysis techniques are discussed to the sensitivity improvement. Principal component analysis (PCA) is one of the widely adopted multivariate analysis techniques and its application to end-point detection of plasma etching process is discussed.