• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.4
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• pp.393-400
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• 2012

In recent years, nano-structured thin film systems are often applied in industries such as MEMS/NEMS device, optical coating, semiconductor or like this. Thin films are used for many and varied purpose to provide resistance to abrasion, erosion, corrosion, or high temperature oxidation and also to provide special magnetic or dielectric properties. Quite a number of articles to evaluate the characterization of thin film structure such as film density, film grain size, film elastic properties, and film/substrate interface condition were reported. Among them, the evaluation of film adhesive to substrate has been of great interest. In this study, we fabricated the polymeric thin film system with different adhesive conditions to evaluate the adhesive condition of the thin film. The nano-structured thin film system was fabricated by spin coating method. And then V(z) curve technique was applied to evaluate adhesive condition of the interface by measuring the surface acoustic wave(SAW) velocity by scanning acoustic microscope(SAM). Furthermore, a nano-scratch technique was applied to the systems to obtain correlations between the velocity of the SAW propagating within the system including the interface and the shear adhesive force. The results show a good correlation between the SAW velocities measured by acoustic spectroscope and the critical load measured by the nano-scratch test. Consequently, V(z) curve method showed potentials for characterizing the adhesive conditions at the interface by acoustic microscope.

• Journal of The Korean Astronomical Society
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• v.51 no.1
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• pp.17-25
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• 2018

Detecting exoplanets around giant stars sheds light on the later-stage evolution of planetary systems. We observed the M giant HD 18438 and the K giant HD 158996 as part of a Search for Exoplanets around Northern circumpolar Stars (SENS) and obtained 38 and 24 spectra from 2010 to 2017 using the high-resolution Bohyunsan Observatory Echelle Spectrograph (BOES) at the 1.8m telescope of Bohyunsan Optical Astronomy Observatory in Korea. We obtained precise RV measurements from the spectra and found long-period radial velocity (RV) variations with period 719.0 days for HD 18438 and 820.2 days for HD 158996. We checked the chromospheric activities using Ca $\text\tiny{II}$ H and $H{\alpha}$ lines, HIPPARCOS photometry and line bisectors to identify the origin of the observed RV variations. In the case of HD 18438, we conclude that the observed RV variations with period 719.0 days are likely to be caused by the pulsations because the periods of HIPPARCOS photometric and $H{\alpha}$ EW variations for HD 18438 are similar to that of RV variations in Lomb-Scargle periodogram, and there are no correlations between bisectors and RV measurements. In the case of HD 158996, on the other hand, we did not find any similarity in the respective periodograms nor any correlation between RV variations and line bisector variations. In addition, the probability that the real rotational period can be as longer than the RV period for HD 158996 is only about 4.3%. Thus we conclude that observed RV variations with a period of 820.2 days of HD 158996 are caused by a planetary companion, which has the minimum mass of 14.0 $M_{Jup}$, the semi-major axis of 2.1 AU, and eccentricity of 0.13 assuming the stellar mass of $1.8 M_{\odot}$. HD 158996 is so far one of the brightest and largest stars to harbor an exoplanet candidate.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.34.2-35
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• 2018

Galaxy transition from star-forming to quiescent, accompanied with morphology transformation, is one of the key unresolved issues in extragalactic astronomy. Although several environmental mechanisms have been proposed, a deeper understanding of the impact of environment on galaxy transition still requires much exploration. My Ph.D. thesis focuses on which environmental mechanisms are primarily responsible for galaxy transition in different environments and looks at what happens during the transition phase using multi-wavelength photometric/spectroscopic data, from UV to mid-infrared (MIR), derived from several large surveys (GALEX, SDSS, and WISE) and our GMOS-North IFU observations. Our multi-wavelength approach provides new insights into the *late* stages of galaxy transition with a definition of the MIR green valley different from the optical green valley. I will present highlights from three areas in my thesis. First, through an in-depth study of environmental dependence of various properties of galaxies in a nearby supercluster A2199 (Lee et al. 2015), we found that the star formation of galaxies is quenched before the galaxies enter the MIR green valley, which is driven mainly by strangulation. Then, the morphological transformation from late- to early-type galaxies occurs in the MIR green valley. The main environmental mechanisms for the morphological transformation are galaxy-galaxy mergers and interactions that are likely to happen in high-density regions such as galaxy groups/clusters. After the transformation, early-type MIR green valley galaxies keep the memory of their last star formation for several Gyr until they move on to the next stage for completely quiescent galaxies. Second, compact groups (CGs) of galaxies are the most favorable environments for galaxy interactions. We studied MIR properties of galaxies in CGs and their environmental dependence (Lee et al. 2017), using a sample of 670 CGs identified using a friends-of-friends algorithms. We found that MIR [3.4]-[12] colors of CG galaxies are, on average, bluer than those of cluster galaxies. As CGs are located in denser regions, they tend to have larger early-type galaxy fractions and bluer MIR color galaxies. These trends can also be seen for neighboring galaxies around CGs. However, CG members always have larger early-type fractions and bluer MIR colors than their neighboring galaxies. These results suggest that galaxy evolution is faster in CGs than in other environments and that CGs are likely to be the best place for pre-processing. Third, post-starburst galaxies (PSBs) are an ideal laboratory to investigate the details of the transition phase. Their spectra reveal a phase of vigorous star formation activity, which is abruptly ended within the last 1 Gyr. Numerical simulations predict that the starburst, and thus the current A-type stellar population, should be localized within the galaxy's center (< kpc). Yet our GMOS IFU observations show otherwise; all five PSBs in our sample have Hdelta absorption line profiles that extend well beyond the central kpc. Most interestingly, we found a negative correlation between the Hdelta gradient slopes and the fractions of the stellar mass produced during the starburst, suggesting that stronger starbursts are more centrally-concentrated. I will discuss the results in relation with the origin of PSBs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.69-74
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• 2017

In this study, cholesteryl 4-n-alkoxybenzoates (Chol-n), with alkyl groups used for controlling the temperature of transition to the liquid crystal phase, were synthesized, and the effects of the length of the alkyl groups on the physical properties of the liquid crystal compounds were investigated. The chemical structures and thermal and liquid crystalline properties of the synthesized compounds were investigated by Fourier transform infrared spectroscopy (FT-IR), proton nuclear magnetic resonance spectroscopy ($^1H$-NMR), differential scanning calorimetry (DSC), and polarizing optical microscopy (POM). The synthesized compounds showed melting transition temperatures ($T_m$) in the range of $103^{\circ}C$ to $143^{\circ}C$ and all of the compounds except Chol-6 exhibited a wide liquid crystal phase temperature range of about $60^{\circ}C$ to $100^{\circ}C$. No correlation between the number of carbon atoms in the molecule and the thermal properties of the compounds was found. All of the synthesized compounds showed an enantiotropic cholesteric phase, which was accompanied by a chiral smectic phase in the compounds Chol-6, Chol-8, Chol-9, and Chol-10. All of the compounds exhibited thermochromism in the liquid crystal state, and their color changed from red to blue as the temperature was increased.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.3
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• pp.113-124
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• 2009

This study has attempted to calculate the intensity of illumination for the optimal growth environment of indoor plants after analyzing both damage to plant species and growth conditions as impacted by light conditions for the Kyobo Life Insurance greenhouse. The optical intensity of illumination has been estimated after investigating the problems of growth conditions based on an analysis of illumination by light condition, dead tree replacement cycle(weeks) and rate of damage of plant species. According to the investigation of illumination, the lowest difference was observed between the shaded spot in the south(531lux) and the sunny spot(602lux) while the largest difference(nearly 500lux) was detected between the shaded spot in the central area(210lux) and the sunny spot(782lux). According to an analysis of dead trees from 1990 to 2004, in terms of dead tree replacement cycle, Viburnum awabuki was the highest(161weeks), followed by Phyllostachys spp.(84weeks), Camellia japonica and Ternstroemia japonica(40weeks). Regardless of plant species, damage rate of plant were lower in the shaded spot and higher in the sunny spot. According to correlation and regression analyses with the intensity of illumination as an independent variable and the damage rate of plant species as a dependent variable, the damage rate of plant species increased as the intensity of illumination decreased. A dramatic decline in the rate of damage was observed at $500{\sim}600lux$. At 700lux, it reached the lowest level.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.4
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• pp.292-297
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• 2019

In this study, whole crop rice samples were used to develop near-infrared reflectance (NIR) equations to estimate six forage quality parameters: Moisture, crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), Ash and relative feed value (RFV). A population of 564 whole crop rice representing a wide range in chemical parameters was used in this study. Undried finely chopped whole crop rice samples were scanned at 1 nm intervals over the wavelength range 680-2500 nm and the optical data recorded as log 1/Reflectance (log 1/R). NIRS calibrations were developed by means of partial least-squares (PLS) regression. The correlation coefficients of cross-validation (R²_cv) and standard error of cross-validation (SECV) for whole crop rice calibration were 0.98 (SECV 1.81%) for moisture, 0.89 (SECV 0.50%) for CP, 0.86 (SECV 1.79%) for NDF, 0.89 (SECV 0.86%) for ash, and 0.84 (SECV 5.21%) for RFV on a dry matter (%), respectively. The NIRS calibration equations developed in this study will be useful in predicting whole crop rice quality for these six quality parameters.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.24 no.1
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• pp.65-73
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• 2014

Objectives: The purposes of this study are to investigate workers' exposures to respirable particles generated in taconite mines and to compare two metric methods for mass concentrations using direct-reading instruments. Methods: Air monitorings were conducted at six mines where subjects have been exposed primarily to particulate matters in crushing, concentrating, and pelletizing processes. Air samples were collected during 4 hours of the entire work shift for similarly exposure groups(SEGs) of nine jobs(N=37). Following instruments were employed to evaluate the workplace: a nanoparticle aerosol monitor(particle size range; 10-1000 nm, unit: ${\mu}m^2/cc$, Model 9000, TSI Inc.); DustTrak air monitors($PM_{10}$, $PM_{2.5}$, unit: $mg/m^3$, Model 8520, TSI Inc.); a condensation particle counter(size range; 20-1000 nm, unit: #/cc, P-Trak 8525, TSI Inc.); and an optical particle counter(particle number by size range $0.3-25{\mu}m$, unit: #/cc, Aerotrak 9306, TSI Inc.). Results: The highest airborne concentration among SEGs was for furnace operator followed by pelletizing maintenance workers in number of particle and surface area, but not in mass concentrations. The geometric means of $PM_{2.5}$ by the DustTrak and the Ptrak/Aerotrak were $0.04{\mu}m$(GSD 2.52) and $0.07{\mu}m$(GSD 2.60), respectively. Also, the geometric means of RPM by the DustTrak and the Ptrak/Aerotrak were $0.16{\mu}m$(GSD 2.24) and $0.32{\mu}m$(GSD 3.24), respectively. The Pearson correlation coefficient for DustTrak $PM_{2.5}$ and Ptrak/Aerotrak $PM_{2.5}$ was 0.56, and that of DustTrak RPM and Ptrak/Aerotrak RPM was 0.65, indicating a moderate positive association between the two sampling methods. Surface area and number concentration were highly correlated($R^2$ = 0.80), while $PM_{2.5}$ and RPM were also statistically correlated each other($R^2$ = 0.79). Conclusions: The results suggest that it is possible to measure airborne particulates by mass concentrations or particle number concentrations using real-time instruments instead of using the DustTrak Aerosol monitor that monitor mass concentrations only.

• Journal of The Korean Society of Grassland and Forage Science
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• v.35 no.3
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• pp.257-263
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• 2015

This study was conducted to assess the potential of using NIRS to accurately determine the chemical composition and fermentation parameters in fresh coarse sorghum and sudangrass silage. Near Infrared Spectroscopy (NIRS) has been increasingly used as a rapid and accurate method to analyze the quality of cereals and dried animal forage. However, silage analysis by NIRS has a limitation in analyzing dried and ground samples in farm-scale applications because the fermentative products are lost during the drying process. Fresh coarse silage samples were scanned at 1 nm intervals over the wavelength range of 680~2500 nm, and the optical data were obtained as log 1/Reflectance (log 1/R). The spectral data were regressed, using partial least squares (PLS) multivariate analysis in conjunction with first and second order derivatization, with a scatter correction procedure (standard normal variate and detrend (SNV&D)) to reduce the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation (SECV). The results of this study showed that NIRS predicted the chemical constituents with a high degree of accuracy (i.e. the correlation coefficient of cross validation ($R^2{_{cv}}$) ranged from 0.86~0.96), except for crude ash which had an $R^2{_{cv}}$ of 0.68. Comparison of the mathematical treatments for raw spectra showed that the second-order derivatization procedure produced the best result for all the treatments, except for neutral detergent fiber (NDF). The best mathematical treatment for moisture, acid detergent fiber (ADF), crude protein (CP) and pH was 2,16,16 respectively while the best mathematical treatment for crude ash, lactic acid and total acid was 2,8,8 respectively. The calibrations of fermentation products produced poorer calibrations (RPD < 2.5) with acetic and butyric acid. The pH, lactic acid and total acids were predicted with considerable accuracy at $R^2{_{cv}}$ 0.72~0.77. This study indicated that NIRS calibrations based on fresh coarse sorghum and sudangrass silage spectra have the capability of assessing the forage quality control

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.4
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.2
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• pp.119-126
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• 1999

A numerical model using soil surface energy balance and soil heat flow equations to estimate mulched soil temperature was developed. The required inputs data include weather data, such as global solar radiation, air temperature, wind speed, atmospheric water vapor pressure, the optical properties of mulching material, and soil physical properties. The observed average soil temperature at 50 cm depth was used as the initial value of soil temperature at each depth. Soil temperature was simulated starting at 0 hour at an interval of 10 minutes. The model reliably described the variation of soil temperature with time progress and soil depth. The correlation between the estimated and measured temperature yielded coefficient values of 0.961, 0.966 for 5cm and 10cm depth of the bare soil, respectively, 0.969, 0.965 for the paper mulched soil, and 0.915, 0.938 for the black polyethylene film mulched soil. The percentages of absolute differences less than 2$^{\circ}$C between soil temperatures measured and simulated at 10 minute interval were 97.4% and 98.5% for 5 cm and 10cm for the bare soil, respectively, and 95.8% and 97.4% for the paper mulched soil, and 70.1% and 92.5% for the polyethylene film mulched soil. The results indicated that the model was able to predict the soil temperature fairly well under mulched condition. However, in the night time, the model performance was a little poor as compared with day time due to the difficulty of accurate determination of the atmospheric long wave radiation.