• Journal of Life Science
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• v.5 no.2
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• pp.20-20
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• 1995

The aroma components of commercial green teas picked inAugust were collected and identified. The extract of aroma compounds in green tea were accoimplished by a modified rotary evaporation. The concentrated wxtracts were analyzed and identified by GC and GC-MS. In GC analysis, T$_{R}$ value of GC represented bt KI value which standardized. The most abundant components of green teas picked in August were 1-Penten-3-ol, trans, trans-2, 4-heptadienal, linalool, $\beta$-ionone and nerolidol.

• Journal of Life Science
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• v.5 no.2
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• pp.76-80
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• 1995

The aroma components of commercial green teas picked inAugust were collected and identified. The extract of aroma compounds in green tea were accoimplished by a modified rotary evaporation. The concentrated wxtracts were analyzed and identified by GC and GC-MS. In GC analysis, T$_{R}$ value of GC represented bt KI value which standardized. The most abundant components of green teas picked in August were 1-Penten-3-ol, trans, trans-2, 4-heptadienal, linalool, $\beta$-ionone and nerolidol.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1079-1082
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• 1999

This paper presents a denoising algorithm that can suppress additive noise components while preserving signal components in the wavelet domain. The algorithm uses the local statistics of wavelet coefficients to attenuate noise components adaptively. Then threshohding operation is followed to reject the residuary noise components in the wavelet coefficients. Simulations are carried out over 1-D signals corrupted by Gaussian noise and the experimental results show the effectiveness of the proposed algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.907-911
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• 2000

In this study, a modified model for prediction of cutting force components in down end milling process is presented. Using this cutting force components of 4-tooth endmills with various helix angles have been predicted. Predicted values of cutting force components are well coincide with the measured ones. As helix angle increases overlapping effects of the active cutting edges increase and as a result the amplitudes of cutting force components decrease.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.75-78
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• 2003

Those who are interested in making inferences concerning linear combination of variance components in a simple linear regression model with unbalanced nested error structure can use the confidence intervals proposed in this paper. Two approximate confidence intervals for the sum of two variance components in the model are proposed. Simulation study is peformed to compare the methods.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.3-7
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• 2000

In this study, a modified model for prediction of cutting force components in up end milling process is presented. Using this cutting force components of 4-tooth endmils with various helix angles have been predicted. Predicted value of cutting force components are well coincide with the measured ones. As helix angle increases overlapping effects of the active cutting edges increase and as a result the amplitudes of cutting force components decrease and the specific cutting energy consumed also decreases

• Proceedings of the Korean Ceranic Society Conference
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• 2002.10a
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• pp.32.1-32
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• 2002

• Journal of the Korean Society of Tobacco Science
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• v.16 no.1
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• pp.20-25
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• 1994

The volatile components were extracted from root of Cnidium officinale M. by SDE(Simultaneous steam distillation and extraction) apparatus and analyzed by GC/M.5 and GC retention index matching. The experimental results revealed the presence of over 22 volatile components. Major components were cnidilide (35.1%), neocnidilids (13.4%), ligustilide (23.2%). The essential oils were separated by silica gel column chromatography(Merck 70-230mesh), and 4 fractions among 12 fractions separated had a, good aroma character.

• Korean Journal of Applied Biomechanics
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• v.25 no.2
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• pp.157-165
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• 2015

Object : The goals of this research were to make Performance Enhanced Model(PE) taken the largest performance index (PI) through artificial variation of principle components calculated by principle component analysis for trial data, and to verify the effect through comparing kinematic factors between trial data (Raw) and PE. Method : Ten subjects (5 men, 5 women) were recruited and 80% of their maximal record was considered. The PI is a regression equation. In order to develop PE, we extracted Principle components from trial position data (by Principle Components Analysis (PCA)). Before PCA, we made 17 position data to 3 row matrix according to components. We calculated 3 eigen value (principle components) through PCA. And except Y (medial-lateral direction) component (because motion of Y component is small), principle components of X (anterior-posterior direction) and Z (vertical direction) components were changed as following. Changed principle components = principle components + principle components ${\times}$ k. After changing the each principle component, we reconstructed position data using the changed principle components and calculated performance index (PI). A Paired t-test was used to compare Raw data and Performance Enhanced Model data. The level of statistical significance was set at $p{\leq}0.05$. Result : The PI was significantly increased about 12.9kg at PE ($101.92{\pm}6.25$) when compared to the Raw data ($91.29{\pm}7.10$). It means that performance can be increased by optimizing 3D positions. The difference of kinematic factors as follows : the movement distance of the bar from start to lock out was significantly larger (about 1cm) for PE, the width of anterior-posterior bar position in full phase was significantly wider (about 1.3cm) for PE and the horizontal displacement toward the weightlifter after beginning of descent from maximal height was significantly greater (about 0.4cm) for PE. Additionally, the minimum knee angle in the 2-pull phase was significantly smaller (approximately 2.7cm) for the PE compared to that of the Raw. PE was decided at proximal position from the Raw (origin point (0,0)) of PC variation). Conclusion : PI was decided at proximal position from the Raw (origin point (0,0)) of PC variation). This means that Performance Enhanced Model was decided by similar motion to the Raw without a great change. Therefore, weightlifters could be accept Performance Enhanced Model easily, comfortably and without large stress. The Performance Enhance Model can provide training direction for athletes to improve their weightlifting records.

• The Korean Journal of Food And Nutrition
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• v.10 no.1
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• pp.25-30
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• 1997

Volatile components of green tea were isolated by purge and trap headspace method and were analyzed by GC and GC/MSD. And ten headspace volatiles were compared with volatiles isolated by simultaneous distillation-extraction(SDE) method. A total of 99 components were identified in the green tea volatile components, from which 88 components were identified in the headspace volatiles, contained 20 alcohols, 30 hydrocarbons, 21 aldehydes, 10 ketones, 2 acids and 5 miscellaneous components. The major components were low boiling components, such as methyl butanal(3.1%), 1-penten-3-ol(5.48%), 2-penten-1-ol(2.89%), hexanal(5.77%), heptanal(1.90%), and ere 2,4-eptadienal(4.28%), linalool(2.27%), 2,6-dimethyl cyclohexanol(2.57%), $\alpha$-pinene(1.52%), caryophyllene(1.70%), and carbonyl compounds, such as $\alpha$-ionone(2.62%), $\beta$-ionone(2.98%), $\beta$-cyclocitral(2.0%). On the other hand SDE volatiles, from which 64 components were identified, contained 16 alcohols, 16 ydrocarbons, 15 aldehydes, 10 ketones, 3 acids and 4 miscellaneous components. The major components were alcohols, such as, benzyl alcohol(3.79%), linalool(9.52%), terpineol(2.16%), geraniol(2.75%), nerolidol(6.50%), ketones, such as $\alpha$-ionone(1.77%), $\beta$-ionone(4.80%), geranyl acetone(1.82%) and acids, such as hexanoic acid(1.45%), nonanoic acid(1.11%).