• Journal of Korea Port Economic Association
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• v.32 no.4
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• pp.1-13
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• 2016

This study attempts to establish a precise forecast model for the container inventory demand of shipping companies through forecasts based on equipment type/size, ports, and weekly system dynamics. The forecast subjects were Shanghai and Yantian Ports. Only dry containers (20, 40) and high cubes (40) were used as the subject container inventory in this study due to their large demand and valid data computation. The simulation period was from 2011 to 2017 and weekly data were used, applying the actual data frequency among shipping companies. The results of the model accuracy test obtained through an application of Mean Absolute Percentage Error (MAPE) verified that the forecast model for dry 40' demand, dry 40' high cube demand, dry 20' supply, dry 40' supply, and dry 40' high cube supply in Shanghai Port provided an accurate prediction, with $0%{\leq}MAPE{\leq}10%$. The forecast model for supply and demand in Shanghai Port was otherwise verified to have relatively high prediction power, with $10%{\leq}MAPE{\leq}20%$. The forecast model for dry 40' high cube demand and dry 20' supply in Yantian Port was accurate, with $0%{\leq}MAPE{\leq}10%$. The forecast model for supply and demand in Yantian Port was generally verified to have relatively high prediction power, with $10%{\leq}MAPE{\leq}20%$. The forecast model in this study also had relatively high accuracy when compared with the actueal data managed in shipping companies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.246-263
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• 2023

The stabilization time of take-over refers to the time it takes for driving to stabilize after the take-over. Following a take-over request from an automated driving system, the driver must become aware of the road driving environment and perform manual driving, making it crucial to clearly understand the relationship between the driving environment and stabilization time of take-over. However, previous studies specifically focusing on stabilization time after take-over are rare, and research considering the driving environment is also lacking. To address this, our study conducted experiments using a driving simulator to observe take-over transitions. The results were analyzed using a liner mixed model to quantitatively identify the driving environment factors affecting the stabilization time of take-over. Additionally, coefficients for stabilization time based on each influencing factor were derived.

• The Journal of Korean Academy of Prosthodontics
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• v.49 no.1
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• pp.73-79
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• 2011

Purpose: The aim of this study was to evaluate the effect of repeated firings on the color of zirconia restoration with different shading method. Materials and methods: Three different types of zirconia frameworks (adding metallic pigments to the initial zirconia powder before sintering (Group NM), dipping the milled frameworks in dissolved coloring agents (Group KI), or application of liner material to the sintered white frameworks (Group KW) were used to support A3 shade dentin porcelain. Repeated firings (3, 5, or 7) were performed, color differences among ceramic specimens were measured using a colorimeter. Repeated measurements analysis of variance (ANOVA) was used to analyze the data for significant difference. The Tukey Honestly Significant Different (HSD) test was used to perform multiple comparisons (${\alpha}$ = .05). Results: 1. $L^*a^*b^*$ values of the ceramic systems were affected by the number of firings (1, 3, 5 or 7 firings) (P < .001) and shading methods (P < .001). 2. As the number of firings increased, the $L^*$ (for all groups) and $a^*$ value (for KW and NM groups) decreased and the $b^*$ value(for all groups) increased. 3. The mean color differences caused by repeated firings were perceptible (${\Delta}E$ > 1) for group KW and KI fired after 3 times, except for group NM fired after 7 times. 4. In order of decreasing ${\Delta}E$ value fired after 7 times, the values were group KI(${\Delta}E$ = 2.26) > group KW (${\Delta}E$ = 1.47) > group NM (${\Delta}E$ = 1.08) (P < .001). Conclusion: Repeated firings influenced the color of the zirconium-oxide all-ceramic specimens with different shading methods.

• Applied Chemistry for Engineering
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• v.16 no.5
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• pp.620-627
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• 2005

In this study, life cycle assessment (LCA) on one of corrugated cardboard box as functional unit was carried out. System boundary of this study divided according to raw material acquisition, corrugated cardboard manufacture and corrugated cardboard box manufacture stage. And environmental impacts are evaluated on each stage and sub-process. The impact categories are classified into eight categories of abiotic resource depletion, global warming stratospheric ozone depletion, photochemical oxidant creation, air acidification, eutrophication, ecotoxicity and human toxicity. From the results, it is found that environment impacts at raw material acquisition stage is the highest as about 92% of whole stage due to liner board manufacture stage. The highest environmental impacts at sub-process of corrugated cardboard and box manufacture stage is a single facer and D/W backer process that included as main process in corrugated cardboard manufacture, and is caused by used energies like electricity, B-C oil, and etc. And then diagnosis for clean production process system of package is carried out. Through diagnosis, on loss rate is reduced and inner pressure intensity of box is improved. After improvement, environmental impact was decreased about 3.8% compared with before improvement.

• Korean Journal of Food Science and Technology
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• v.29 no.1
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• pp.32-37
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• 1997

The rate constants and activation energies for formation of two chemical markers, M-1 and M-2 at sterilization temperatures were determined in a meatball system. Destruction rates for bacterial spores were also determined. The rate constants for M-1 and M-2 formation at $121^{\circ}C$ were 0.03 and 0.28 Abs/min, respectively. The activation energies for M-1 and M-2 were 27.9 and 24.6 Cal/mol. M-2 was formed faster than M-1 and reached a maximum and decreased. M-1 formation continued up to 30 min at $121^{\circ}C$ and 10 min at $131^{\circ}C$, which makes M-1 a more useful chemical marker for high $F_0$ values. The D-values for spores (B. stearothermophilus ATCC 12980) at 111, 114.4, 117.7 and $121^{\circ}C$ were 7.5, 4.5, 1.9 and 0.58 respectively. At temperatures between 111 and $121^{\circ}C$, there was a liner correlation between destruction of the spores and the M-1 formation. It was difficult to get accurate D-value at $126^{\circ}C\;and\;131^{\circ}C$, because almost all spores were dead before temperature at the center of the meatball reached $126^{\circ}C$. These data suggest that the chemical marker should be used to evaluate overprocessing as well as microbial lethality in aseptic processing.

• Asian Journal of Turfgrass Science
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• v.23 no.1
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• pp.77-90
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• 2009

Near Infrared Reflectance Spectroscopy(NIRS) is a quick, accurate, and non-destructive method to measure multiple nutrient components in plant leaves. This study was to acquire a liner regression equation by evaluating the nutrient contents of 'CY2' creeping bentgrass rapidly and accurately using NIRS. In particular, nitrogen fertility is a primary element to keep maintaining good quality of turfgrass. Nitrogen, moisture, carbohydrate, and starch were assessed and analyzed from 'CY2' creeping bentgrass clippings. A linear regression equation was obtained from accessing NIRS values from NIR spectrophotometer(NIR system, Model XDS, XM-1100 series, FOSS, Sweden) programmed with WinISI III project manager v1.50e and ISIscan(R) (Infrasoft International) and calibrated with laboratory values via chemical analysis from an authorized institute. The equation was formulated as MPLS(modified partial least squares) analyzing laboratory values and mathematically pre-treated spectra. The accuracy of the acquired equation was confirmed with SEP(standard error of prediction), which indicated as correlation coefficient($r^2$) and prediction error of sample unacquainted, followed by the verification of model equation of real values and these monitoring results. As results of monitoring, $r^2$ of nitrogen, moisture, and carbohydrate in 'CY2' creeping bentgrass was 0.840, 0.904, and 0.944, respectively. SEP was 0.066, 1.868, and 0.601, respectively. After outlier treatment, $r^2$ was 0.892, 0.925, and 0.971, while SEP was 0.052, 1.577, and 0.394, respectively, which totally showed a high correlation. However, $r^2$ of starch was 0.464, which appeared a low correlation. Thereof, the verified equation appearing higher $r^2$ of nitrogen, moisture, and carbohydrate showed its higher accuracy of prediction model, which finally could be put into practical use for turf management system.

• Journal of Energy Engineering
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• v.25 no.4
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• pp.13-29
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• 2016

In this study, we analyzed the causes of major faults in the biogas plant through the case of gas engine failure when cogenerating electricity and heat using biogas as a fuel in the actual sewage treatment plant and suggested countermeasures. Hydrogen sulfide in the biogas entering the biogas engine and water caused by intermittent malfunction of the water removal system caused intercooler corrosion in the biogas engine. In addition, the siloxane in the biogas forms a silicate compound with silicon dioxide, which causes scratches and wear of the piston surface and the inner wall of the cylinder liner. The substances attached to the combustion chamber and the exhaust system were analyzed to be combined with hydrogen sulfide and other impurities. It is believed that hydrogen sulfide was supplied to the desulfurization plant for a long period of time because of the high content of hydrogen sulfide (more than 50ppm) in the biogas and the hydrogen sulfide was introduced into the engine due to the decrease of the removal efficiency due to the breakthrough point of the activated carbon in the desulfurization plant. In addition, the hydrogen sulfide degrades the function of the activated carbon for siloxane removal of the adsorption column, which is considered to be caused by the introduction of unremoved siloxane waste into the engine, resulting in various types of engine failure. Therefore, hydrogen sulfide, siloxane, and water can be regarded as the main causes of the failure of the biogas engine. Among them, hydrogen sulfide reacts with other materials causing failure and can be regarded as a substance having a great influence on the pretreatment process. As a result, optimization of $H_2S$ removal method seems to be an essential measure for stable operation of the biogas engine.

• Journal of Life Science
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• v.8 no.4
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• pp.437-442
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• 1998

Seed and leaf size is the important morphological traits considered by plant breeder and is the important yield components in soybean. The objective of this research was to know the relationship between seed size and leaf size in 66 $F_2$ populations derived from half diallel mating system with 12 soybean strains, representing distinct seed and leaf size. The range of seed size for 12 parents used was 6.7 to 43.8 g/100 seed. Leaf width leaf length ranged 5.7 to 8.6 cm and 9.4 to 12.9 cm, respectively. Leaf width was highly correlated with leaf length with an R square of 0.754 in the $F_2$ generation. The $F_2$ regression` coefficient indicated that leaves were, on average 1.4 times greater length than in width . Leaf size (width) was highly correlated (r.0.91) with seed size (g/100 seed) in the $F_2$ generation with an R square of 0.833. Our results indicate postive correlation within seed and leaf size is common in $F_2$ segregating populations derived from crossing with soybean. The strong liner relationship we observed between leaf size and seed size in $F_2$ segragating population is useful in that in that indirect selection for a secondary character may be superior to direct selection for the primary character.

• Journal of the Korean Society for Marine Environment & Energy
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• v.12 no.3
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• pp.143-150
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• 2009

Fuel oil mostly used for a ship is made from crude oil by refining process. In order to produce plenty of high-quality fuel oil, the Fluid catalytic cracking(FCC) method is widely adopted to many refinery factories during the decomposition process from high molecule into lower molecule. The major constituents in spent FCC catalysts are Si, Al, Fe, Ti, alkali metals and some others. The spent catalyst is also composed small amounts of rare metals such as Ce, Nd, Ni and V. The big problem in FCC oil is mixing the catalyst in the oil. This reason is unstable separation of FCC catalyst in separator. Such a FCC catalyst will become a reason of heavy wear down in moving parts of engine. The impurity in oil is ash and deposit compound, such as Al, Si, Ni, Fe and V, which will accelerate the wear down on fuel pump, fuel injection valve cylinder liner and piston ring. It is important to find a basic reason of an engine trouble for preventing similar troubles anymore. Insurance compensation will be different according to the reason of an engine trouble which might be natural abrasion or other external causes. In this study, types and reasons of engine troubles related to fuel oil will be covered.

• Analytical Science and Technology
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• v.17 no.4
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• pp.355-362
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• 2004

Fission products and Inter reaction layer of $U_3Si-Al$ dispersion fuel, irradiated in HANARO research reactor with 121 kW/m of maximum liner power and 63 at% of average burn-up, was characterization by EPMA (Electron Probe Micro Analyzer). The fuel punching system developed by Irradiated Materials Examination Facility (IMEF) has used to make these samples for the EPMA. With this system a very small and thin specimen which is 1.57 mm in diameter and 2 mm in thickness respectively has been fabricated to protect the EPMA operator from high radioactive fuel and to mini-mize the equivalent dose rate less than 150 mSv/h. EPMA was performed to observe layers of sectional, Inter-reaction and oxide with specimens of cutting and polished. Stoichiometry in the Inter-reaction layer with $16{\mu}m$ of thickness was $U_{2.84}$ Si $Al_{14}$ with calibration of $UO_2$ and $U_{3.24}$ Si $Al_{14.1}$ with calibration of standard specimen. metallic precipitates in this layer were not observed using fission products examination.