• Food Science and Preservation
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• v.21 no.5
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• pp.618-626
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• 2014

The physicochemical characteristics and consumer perceptions of two Fuji cultivars (Fuji and Royal Fuji) with six different size groups (3D: 30~39, 4D: 40~49, 5D: 50~59, 6D: 60~69, 7D: 70~79, and 8D: 80~89 apples/15 kg) were investigated to identify the ideal size and the drivers of consumer acceptability of apples. For the physicochemical characteristics, the weight, volume, specific volume, L, a, and b colors, hardness, pH, acidity, and brix of apples were measured. A total of 100 consumers were asked to mark the intensity of the characteristics (size, redness, glossiness, surface roughness, apple odor, apple flavor, sweetness, sourness, hardness, crunchiness, and toughness) to determine the ideal characteristics of apples before they were asked to taste the apple products. The consumers evaluated the apple samples in terms of their appearance, odor, flavor, texture, and overall acceptability; the consumers' intent to purchase such apples and willingness to pay for them; and the intensity of the aforementioned characteristics. Compared to the ideal characteristics of apples, the actual apple samples were rated low in their apple odor, apple flavor, acidity, sweetness, hardness, and crispness. The ideal size of the apples was between 4D and 5D. Their overall acceptability was highly affected by their flavor, followed by their texture, odor, and appearance. The acceptability of the appearance was highly correlated with the glossiness (r = 0.80), volume, weight, redness (r = 0.73), and size (r = 0.72). The consumer acceptability of the apples increased with the decreased pH and the increased Brix, hardness, and color b values of the peeled apples. The apple flavor, sweetness, hardness, crispiness, juiciness, and toughness during mastication were noted as sensory drivers of consumer acceptability.

• Journal of the Korean Vacuum Society
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• v.17 no.6
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• pp.528-537
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• 2008

60 nm and 20 nm thick hydrogenated amorphous silicon(a-Si:H) layers were deposited on 200 nm $SiO_2$/single-Si substrates by inductively coupled plasma chemical vapor deposition(ICP-CVD). Subsequently, 30 nm-Ni layers were deposited by an e-beam evaporator. Finally, 30 nm-Ni/(60 nm and 20 nm) a-Si:H/200 nm-$SiO_2$/single-Si structures were prepared. The prepared samples were annealed by rapid thermal annealing(RTA) from $200^{\circ}C$ to $500^{\circ}C$ in $50^{\circ}C$ increments for 40 sec. A four-point tester, high resolution X-ray diffraction(HRXRD), field emission scanning electron microscopy(FE-SEM), transmission electron microscopy(TEM), and scanning probe microscopy(SPM) were used to examine the sheet resistance, phase transformation, in-plane microstructure, cross-sectional microstructure, and surface roughness, respectively. The nickel silicide from the 60 nm a-Si:H substrate showed low sheet resistance from $400^{\circ}C$ which is compatible for low temperature processing. The nickel silicide from 20 nm a-Si:H substrate showed low resistance from $300^{\circ}C$. Through HRXRD analysis, the phase transformation occurred with silicidation temperature without a-Si:H layer thickness dependence. With the result of FE-SEM and TEM, the nickel silicides from 60 nm a-Si:H substrate showed the microstructure of 60 nm-thick silicide layers with the residual silicon regime, while the ones from 20 nm a-Si:H formed 20 nm-thick uniform silicide layers. In case of SPM, the RMS value of nickel silicide layers increased as the silicidation temperature increased. Especially, the nickel silicide from 20 nm a-Si:H substrate showed the lowest RMS value of 0.75 at $300^{\circ}C$.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.3
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• pp.82-93
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• 2008

In order to ensure a standardized data analysis of the eddy covariance measurements, Hong and Kim's quality control program has been updated and used to process eddy covariance data measured at two levels on the main flux tower at Gwangneung site from January to May in 2005. The updated program was allowed to remove outliers automatically for $CO_2$ and latent heat fluxes. The flag system consists of four quality groups(G, D, B and M). During the study period, the missing data were about 25% of the total records. About 60% of the good quality data were obtained after the quality control. The number of record in G group was larger at 40m than at 20m. It is due that the level of 20m was within the roughness sublayer where the presence of the canopy influences directly on the character of the turbulence. About 60% of the bad data were due to low wind speed. Energy balance closure at this site was about 40% during the study period. Large imbalance is attributed partly to the combined effects of the neglected heat storage terms, inaccuracy of ground heat flux and advection due to local wind system near the surface. The analysis of wind direction indicates that the frequent occurrence of positive momentum flux was closely associated with mountain valley wind system at this site. The negative $CO_2$ flux at night was examined in terms of averaging time. The results show that when averaging time is larger than 10min, the magnitude of calculated $CO_2$ fluxes increases rapidly, suggesting that the 30min $CO_2$ flux is influenced severely by the mesoscale motion or nonstationarity. A proper choice of averaging time needs to be considered to get accurate turbulent fluxes during nighttime.

• Journal of Sericultural and Entomological Science
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• v.45 no.1
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• pp.34-45
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• 2003

Silk was treated with calcium hydroxide for degumming at different treatment times, temperatures and Ca(OH)$_2$ concentration to optimize degumming conditions in this thesis. After degumming, soluble and insoluble sericin were seperated and then the soluble sericin was characterized by measuring the average degree of polymerization (D.P.), lysinoalanine (LAL) content, DSC, and by amino acid analysis. And degummed silk fibroin was characterized by measuring tenacity and SEM. Degumming loss was increased by increasing the treatment time and temperature until about 30 minutes. After then, a slight difference was found along with treatment times at the Ca(OH)$_2$ concentrations of 0.07% and 0.1% solutions. After degumming, insoluble sericin ratio on degumming solution was increased by increasing treatment temperature at Ca(OH)$_2$ 0.04% solution. At the concentration Ca(OH)$_2$ of 0.07%, a soluble ratio was almost 100% regardless of treatment time and temperature. At the beginning of treatment, insoluble ratio was high at Ca(OH)$_2$ 0.1% solution but it was decreased by increasing treatment time. At the Ca(OH)$_2$ concentration of 0.04%, D.P. of soluble sericin was maintained as a constant value of 10 at 100$^{\circ}C$ although treatment time was increased. However, at 80$^{\circ}C$ and 90$^{\circ}C$, it was hard to prepare a soluble sericin having a constant D.P. by increasing treatment time. At the Ca(OH)$_2$ concentration of 0.07%, D.P. was almost 10 irrespective of treatment temperature and time. Soluble sericins with high D.P. of 20∼30 were obtained at 0.1% and 100$^{\circ}C$. LAL was not detected in soluble sericin. As the results of amino acid analysis, it showed that Ca(OH)$_2$ degumming reduced the contents of hydroxy amino acids like Ser., Thr. and Tyr. In DSC analysis of soluble sericin, endothermic peak by thermal deformation and pyrolysis showed at 189$^{\circ}C$ and at 299$^{\circ}C$, respectively. The tenacities of degummed silk were 15∼30% lower than that of raw silk. And it was decreased with increasing treatment time. From the morphological study, the thickness of degummed silk fibroin became thinner by increasing degumming loss. The roughness of a silk fibroin surface was appeared as treatment concentration was increased.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.28 no.2
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• pp.183-193
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• 1995

Assuming that fishing nets are porous structures to suck water into their mouth and then filtrate water out of them, the flow resistance N of nets with wall area S under the velicity v was taken by $R=kSv^2$, and the coefficient k was derived as $$k=c\;Re^{-m}(\frac{S_n}{S_m})n(\frac{S_n}{S})$$ where $R_e$ is the Reynolds' number, $S_m$ the area of net mouth, $S_n$ the total area of net projected to the plane perpendicular to the water flow. Then, the propriety of the above equation and the values of c, m and n were investigated by the experimental results on plane nettings carried out hitherto. The value of c and m were fixed respectively by $240(kg\cdot sec^2/m^4)$ and 0.1 when the representative size on $R_e$ was taken by the ratio k of the volume of bars to the area of meshes, i. e., $$\lambda={\frac{\pi\;d^2}{21\;sin\;2\varphi}$$ where d is the diameter of bars, 21 the mesh size, and 2n the angle between two adjacent bars. The value of n was larger than 1.0 as 1.2 because the wakes occurring at the knots and bars increased the resistance by obstructing the filtration of water through the meshes. In case in which the influence of $R_e$ was negligible, the value of $cR_e\;^{-m}$ became a constant distinguished by the regions of the attack angle $ \theta$ of nettings to the water flow, i. e., 100$(kg\cdot sec^2/m^4)\;in\;45^{\circ}<\theta \leq90^{\circ}\;and\;100(S_m/S)^{0.6}\;(kg\cdot sec^2/m^4)\;in\;0^{\circ}<\theta \leq45^{\circ}$. Thus, the coefficient $k(kg\cdot sec^2/m^4)$ of plane nettings could be obtained by utilizing the above values with $S_m\;and\;S_n$ given respectively by $$S_m=S\;sin\theta$$ and $$S_n=\frac{d}{I}\;\cdot\;\frac{\sqrt{1-cos^2\varphi cos^2\theta}} {sin\varphi\;cos\varphi} \cdot S$$ But, on the occasion of $\theta=0^{\circ}$ k was decided by the roughness of netting surface and so expressed as $$k=9(\frac{d}{I\;cos\varphi})^{0.8}$$ In these results, however, the values of c and m were regarded to be not sufficiently exact because they were obtained from insufficient data and the actual nets had no use for k at $\theta=0^{\circ}$. Therefore, the exact expression of $k(kg\cdotsec^2/m^4)$, for actual nets could De made in the case of no influence of $R_e$ as follows; $$k=100(\frac{S_n}{S_m})^{1.2}\;(\frac{S_m}{S})\;.\;for\;45^{\circ}<\theta \leq90^{\circ}$$, $$k=100(\frac{S_n}{S_m})^{1.2}\;(\frac{S_m}{S})^{1.6}\;.\;for\;0^{\circ}<\theta \leq45^{\circ}$$