• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 1995.11a
• /
• pp.167-170
• /
• 1995

LiCoO$_2$is a electrode material of Li ion Cell which is expected as the cell with a very high electric charge density. The recent study is mainly to focused on a high power secondary cell. If very thin Li ion Cell can be made in the scale of IC substrate it can be a electric souse in IC chip , micro machine or very thin electrical display etc. LiCoO$_2$thin film can be made by CVD, Laser ablation, E-Beam, ton Beam process, sputtering etc. But to make the material with a high quality for a cell is difficult as the electrode in cell have the fitable ratio in components and a lattice structure of bulk etc. In this study, LiCoO$_2$is made by R.F magnetron sputtering with the variance of substrate temperature and oxygen partial pressure etc. In the substrate temperature of 600$^{\circ}C$ and the oxygen rate of 10%, we can acquire the good thin film LiCoO$_2$compared wish a bulk material.

• Journal of the korean society of oceanography
• /
• v.32 no.3
• /
• pp.112-119
• /
• 1997

Coastal sediments collected near the Youngkwang Nuclear Power Plant were analysed for major(Al$_2$O$^_3$, Fe$^_2$O$^_3$, MgO, CaO, Na$^_2$O, K$^_2$O, TiO$^_2$, MnO), trace (Ba, Sr, V, Co, Cr, Cu, Ni, Zn, Pb) metal, and P$^_2$O$^_5$ contents. The composition of bulk metals from most stations fits within the range as those in the average crustal and sedimentary rocks, suggesting that the anthropogenic perturbation of these components is insignificant. The abundance and distribution of total contents for the majority of metals in the surface sediment could be explained by the grain size and were associated with mud (<63 ${\mu}$m) contents. However, distributions of Ca, K, Sr and Ba did not have any significant association with the sediment grain size. This may be due to the geochemical coherence among these metals in certain minerals abundant in coarse grained fractions. The distribution of Pb appears to be partly affected by the contribution from aerosol fallout. Using the R'-mode factor analysis, we show that the variance of the metal contents could be explained by four factors which account for 93.7% of the total variance. It appears that texturally controlled and/or sorting factors influenced by fine fraction are the most dominant factors which determine the relative abundance and distribution of metals in the study area.

• Journal of the Korean Recycled Construction Resources Institute
• /
• v.11 no.4
• /
• pp.535-541
• /
• 2023

Friction material, an integral constituent of bearing supports, facilitates frictional interactions between two components. Polytetrafluoroethylene (PTFE), a commonly employed friction material in bearing supports, has assessed resultant friction equilibrium. Nonetheless, protracted utilization diminishes frictional performance as the lubricating agent is progressively depleted. Friction materials can affect the entire structural system. Hence, this study applied ceramic material as a friction material due to its high strength, low friction, and low deformation. The frictional behavior was investigated using a cyclic friction test, considering various friction materials as the primary design variables and examining their covariance in cyclic frictional movements. The results substantiated that the ceramic friction material yielded a low variance and friction coefficients in cyclic frictional movements.

• Nuclear Engineering and Technology
• /
• v.52 no.9
• /
• pp.2119-2129
• /
• 2020

Flow-accelerated corrosion (FAC), liquid droplet impingement erosion (LDIE), cavitation and flashing can cause continuous wall-thinning in nuclear secondary pipes. In order to prevent pipe rupture events resulting from the wall-thinning, most NPPs (nuclear power plants) implement their management programs, which include periodic thickness inspection using UT (ultrasonic test). Meanwhile, it is well known in field experiences that the thickness measurement errors (or deviations) are often comparable with the amount of thickness reduction. Because of these errors, it is difficult to estimate wall-thinning exactly whether the significant thinning has occurred in the inspected components or not. In the previous study, the authors presented an approximate estimation procedure as the first step for thickness measurement deviations at each inspected component and the statistical & quantitative characteristics of the measurement deviations using plant experience data. In this study, statistical significance was quantified for the current methods used for wall-thinning determination. Also, the authors proposed new estimation procedures for determining local wall-thinning to overcome the weakness of the current methods, in which the proposed procedure is based on analysis of variance (ANOVA) method using subgrouping of measured thinning values at all measurement grids. The new procedures were also quantified for their statistical significance. As the results, it is confirmed that the new methods have better estimation confidence than the methods having used until now.

• Journal of Biosystems Engineering
• /
• v.34 no.2
• /
• pp.114-119
• /
• 2009

Field test was conducted to investigate primary factors reducing rapeseed harvesting using a reciprocating cutter-bar of combine. The results showed that the correlation between crop moisture content and yield loss had a U-type, which indicated that the yield reduction increased at too high and too low crop moisture contents. The proper ranges of crop moisture contents were 27${\sim}$35%, 21${\sim}$56%, and 62${\sim}$73% in case of grain, pod and stem, respectively. Crop moisture content was negatively correlated with header loss, but positively correlated with threshing loss. In contrary, stem moisture content showed positive correlations with total loss, threshing loss and separation loss. Working speed was positively correlated with header loss. Total flow rate, pod flow rate and stem flow rate were highly correlated with threshing loss and separation loss. However, grain flow rate did not show any correlation with total loss. According to the principal component analysis, two principal components were derived as components with eigenvalues greater than 1.0. The contribution rates of the first and the second components were 52.7% and 38.9%, which accounted for 91.6% of total variance. As a contributive factor influencing total loss of rapeseed mechanical harvesting, a crop moisture content factor was greater than a crop flow rate factor. The stepwise multiple regression analysis for total loss was conducted using crop moisture content factor, crop flow rate factor and coefficient. However, the model did not show any correlation among independent and dependent factors ($R^2$=0.060).

• Journal of Environmental Health Sciences
• /
• v.31 no.2 s.83
• /
• pp.134-146
• /
• 2005

Environmental monitoring system has been adopted and supplemented as inspection measures for the quantitative and qualitative changes of environmental impact assessment (EIA). This study compares the results of environmental impact assessment with the results of post-environmental investigation using a correction and principal component analysis (PCA) in the housing development project. Correlation analysis showed that most of air quality variables including TSP, $PM_{10},\;NO_2$, CO were linearly correlated with each other in the environmental impact assessment and the post-environmental investigation. In the water quality, pH and BOD were well correlated with the DO and SS, respectively. As a result of correlation analysis in the noise and vibration, noise in day and night and vibration in day and night were related to each other between EIA and the post-environmental investigation. From the results of analysis of soil, Cu with Cd, Cu with Pb, and Cd with Pb were related to each other in EIA. Principal component analysis (PCA) showed a powerful pattern recognition that had attempted to explain the variance of a large dataset of inter-correlated variable with a smaller set of independent variables (principal components). Principal component (PC1) and principal component (PC2) were obtained with eigenvalues> 1 summing almost $90\%$ of the total variance in the all of the items(air, water, noise, vibration and soil) in EIA and post-environmental investigation.

• Journal of Environmental Science International
• /
• v.26 no.11
• /
• pp.1297-1306
• /
• 2017

This study identified physical characteristics and aerosol particle sources of $PM_{10}$ and $PM_{2.5}$ in the industrial complex of Busan Metropolitan City, Korea. Samples of $PM_{10}$, $PM_{2.5}$ and also soil, were collected in several areas during the year of 2012 to investigate elemental composition. A URG cyclone sampler was used for collection. The samples were collected according to each experimental condition, and the analysis method of SEM-EDX was used to determine the concentration of each metallic element. The comparative analysis indicated that their mass concentration ranged from 1% to 3%. The elements in the industrial region that were above 10% were Si, Al, Fe, and Ca. Those below 5% were Na, Mg, and S. The remaining elements (1% of total mass) consisted of elements such as Ni, Co, Br and Pb. Finally, a statistical tool was applied to the elemental results to identify each source for the industrial region. From a principal components analysis (SPSS, Ver 20.0) performed to analyze the possible sources of $PM_{10}$ in the industrial region, five main factors were determined. Factor 1 (Si, Al), which accounted for 15.8% of the total variance, was mostly affected by soil and dust from manufacturing facilities nearby, Factors 2 (Cu, Ni), 3 (Zn, Pb), and 4 (Mn, Fe), which also accounted for some of variance, were mainly related to iron, non-ferrous metals, and other industrial manufacturing sources. Also, five factors determined to access possible sources of $PM_{2.5}$, Factor 1 (Na, S), accounted for 13.5% of the total variance and was affected by sea-salt particles and fuel incineration sources, and Factors 2 (Ti, Mn), 3 (Pb, Cl), 4 (K, Al) also explained significant proportions of the variance. Theses factors mean that the $PM_{2.5}$ emission sources may be considered as sources of incineration, and metals, and non-ferrous manufacturing industries.

• Bulletin of the Korean Chemical Society
• /
• v.30 no.5
• /
• pp.1121-1126
• /
• 2009

This paper describes a pattern recognition method of Magnoliae flos based on a gas chromatographic/mass spectrometric (GC/MS) analysis of the essential oil components. The botanical drug is mainly comprised of the four magnolia species (M. denudata, M. biondii, M. kobus, and M. liliflora) in Korea, although some other species are also being dealt with the drug. The GC/MS separation of the volatile components, which was extracted by the simultaneous distillation and extraction (SDE), was performed on a carbowax column (supelcowax 10; 30 m{\time}0.25 mm{\time}0.25{\mu}m$) using temperature programming. Variance in the retention times for all peaks of interests was within RSD 2% for repeated analyses (n = 9). Of the 74 essential oil components identified from the magnolia species, approximately 10 major components, which is $\alpha$-pinene, $\beta$-pinene, sabinene, myrcene, d-limonene, eucarlyptol (1,8-cineol), $\gamma$-terpinene, p-cymene, linalool, $\alpha$-terpineol, were commonly present in the four species. For statistical analysis, the original dataset was reduced to the 13 variables by Fisher criterion and factor analysis (FA). The essential oil patterns were processed by means of the multivariate statistical analysis including hierarchical cluster analysis (HCA), principal component analysis (PCA) and discriminant analysis (DA). All samples were divided into four groups with three principal components by PCA and according to the plant origins by HCA. Thirty-three samples (23 training sets and 10 test samples to be assessed) were correctly classified into the four groups predicted by PCA. This method would provide a practical strategy for assessing the authenticity or quality of the well-known herbal drug, Magnoliae flos.

• Journal of Animal Science and Technology
• /
• v.55 no.1
• /
• pp.7-11
• /
• 2013

The purpose of this study was to estimate (co) variance components of three milk production traits for genetic evaluation using a multiple lactation model. Each of the first five lactations was treated as different traits. For the parameter estimation study, a data set was set up including lactations from cows calved from 2001 to 2009. The total number of raw lactation records in first to fifth parities reached 1,416,589. At least 10 cows were required for each contemporary group, herd-year-season effect. Sires with fewer than 10 daughters were discarded. Lactations with 305d milk yield exceeding 15,000 kg were removed. In total, 1,456 sires of cows were remained after all the selection steps. A complete pedigree consisting of 292,382 records was used for the study. A sire model containing herd-year-season, caving age, and sire additive genetic effects was applied to the selected lactation data and pedigree for estimating (co) variance components via VCE. Heritabilities and genetic or residual correlations were then derived from the (co) variance estimates using R package. Genetic correlations between lactations ranged from 0.76 to 0.98 for milk yield, 0.79~1.00 for fat yield, 0.75~1.00 for protein yield. On individual lactation basis, relatively low heritability values were obtained 0.14~0.23, 0.13~0.20 and 0.14~0.19 for milk, fat, and protein yields, respectively. For the combined lactation heritability values were 0.29, 0.28, and 0.26 for milk, fat, and protein yields. The estimated parameters will be used in national genetic evaluations for production traits.

• Animal Bioscience
• /
• v.35 no.7
• /
• pp.955-963
• /
• 2022

Objective: The aim of this study was to estimate genetic parameters for 305-day cumulative milk yield and components, growth, and reproductive traits in Guzerá cattle. Methods: The evaluated traits were 305-day first-lactation cumulative yields (kg) of milk (MY305), fat (FY305), protein (PY305), lactose (LY305), and total solids (SY305); age at first calving (AFC) in days; adjusted scrotal perimeter (cm) at the ages of 365 (SP365) and 450 (SP450) days; and adjusted body weight (kg) at the ages of 210 (W210), 365 (W365), and 450 (W450) days. The (co)variance components were estimated using the restricted maximum likelihood method for single-trait, bi-trait and tri-trait analyses. Contemporary groups and additive genetic effects were included in the general mixed model. Maternal genetic and permanent environmental effects were also included for W210. Results: The direct heritability estimates ranged from 0.16 (W210) to 0.32 (MY305). The maternal heritability estimate for W210 was 0.03. Genetic correlation estimates among milk production traits and growth traits ranged from 0.92 to 0.99 and from 0.92 to 0.99, respectively. For milk production and growth traits, the genetic correlations ranged from 0.33 to 0.56. The genetic correlations among AFC and all other traits were negative (-0.43 to -0.27). Scrotal perimeter traits and body weights showed genetic correlations ranging from 0.41 to 0.46, and scrotal perimeter and milk production traits showed genetic correlations ranging from 0.11 to 0.30. The phenotypic correlations were similar in direction (same sign) and lower than the corresponding genetic correlations. Conclusion: These results suggest the viability and potential of joint selection for dairy and beef traits in Guzerá cattle, taking into account reproductive traits.