• Journal of Korea Foundry Society
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• v.41 no.2
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• pp.144-152
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• 2021

Based on the analysis of the current state of the world's foundry industry, we looked at the international competitiveness of Korea's foundry industry for the past 20 years. Korea's total foundry production is 2.52 million tons, and the production per company (so-called productivity) is 2,831 tons, which is the eighth largest in the world and down one position for the case of total foundry production, while productivity remains its position compared to three years ago. Korea is the only one of the top 10 foundry to see a decline in production. Similar to the global situation, Korean products consist of 38% of grey csat iron, 31% of ductile cast iron, 15% of aluminum, and 9% of cast steel. In order to obtain statistics on Korea's foundry industry, the survey conducted a service project for approximately nine months from April 2020. Various statistical surveys and sample in-depth surveys by the Korean standard industry class were evaluated for various contents of the domestic casting industry. We also looked at the number of companies, the distribution by region, the number of workers and the percentage of foreigners, and the distribution of each job, as well as the R&D investment status according to the size of the enterprise. Together, sales, exports, sales and various profit ratios were analyzed to measure the earning power of foundry industry. In addition, the classification by grouping the foundry industry according to the process utilized by focusing on each company, and to determine the sales, exports, and yield status for each process was also investigated on the basis. Based on these data, the domestic foundry industry has presented a variety of offers for the following issues for sustainable growth; global ranking, marginal corporate restructuring, training of domestic technical people, differentiated support policies by company size and process.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.457-468
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• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.316-328
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• 2021

In this study, the leaf Na content prediction model for spring potato was established using 400-1000 nm hyperspectral sensor to develop the multispectral sensor for the salinity monitoring in reclaimed land. The irrigation conditions were standard, drought, and salinity (2, 4, 8 dS/m), and the irrigation amount was calculated based on the amount of evaporation. The leaves' Na contents were measured 1st and 2nd weeks after starting irrigation in the vegetative, tuber formative, and tuber growing periods, respectively. The reflectance of the leaves was converted from 5 nm to 10 nm, 25 nm, and 50 nm of FWHM (full width at half maximum) based on the 10 nm wavelength intervals. Using the variance importance in projections of partial least square regression(PLSR-VIP), ten band ratios were selected as the variables to predict salinity damage levels with Na content of spring potato leaves. The MLR(Multiple linear regression) models were estimated by removing the band ratios one by one in the order of the lowest weight among the ten band ratios. The performance of models was compared by not only R2, MAPE but also the number of band ratios, optimal FWHM to develop the compact multispectral sensor. It was an advantage to use 25 nm of FWHM to predict the amount of Na in leaves for spring potatoes during the 1st and 2nd weeks vegetative and tuber formative periods and 2 weeks tuber growing periods. The selected bandpass filters were 15 bands and mainly in red and red-edge regions such as 430/440, 490/500, 500/510, 550/560, 570/580, 590/600, 640/650, 650/660, 670/680, 680/690, 690/700, 700/710, 710/720, 720/730, 730/740 nm.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.251-267
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• 2021

Remotely sensed vegetation indices (VIs) are empirically related with gross primary productivity (GPP) in various spatio-temporal scales. The uncertainties in GPP-VI relationship increase with temporal resolution. Uncertainty also exists in the eddy covariance (EC)-based estimation of GPP, arising from the partitioning of the measured net ecosystem CO2 exchange (NEE) into GPP and ecosystem respiration (RE). For two forests and two agricultural sites, we correlated the EC-derived GPP in various time scales with three different near-surface remotely sensed VIs: (1) normalized difference vegetation index (NDVI), (2) enhanced vegetation index (EVI), and (3) near infrared reflectance from vegetation (NIRv) along with NIRvP (i.e., NIRv multiplied by photosynthetically active radiation, PAR). Among the compared VIs, NIRvP showed highest correlation with half-hourly and monthly GPP at all sites. The NIRvP was used to test the reliability of GPP derived by two different NEE partitioning methods: (1) original KoFlux methods (GPP_Ori) and (2) machine-learning based method (GPP_ANN). GPP_ANN showed higher correlation with NIRvP at half-hourly time scale, but there was no difference at daily time scale. The NIRvP-GPP correlation was lower under clear sky conditions due to co-limitation of GPP by other environmental conditions such as air temperature, vapor pressure deficit and soil moisture. However, under cloudy conditions when photosynthesis is mainly limited by radiation, the use of NIRvP was more promising to test the credibility of NEE partitioning methods. Despite the necessity of further analyses, the results suggest that NIRvP can be used as the proxy of GPP at high temporal-scale. However, for the VIs-based GPP estimation with high temporal resolution to be meaningful, complex systems-based analysis methods (related to systems thinking and self-organization that goes beyond the empirical VIs-GPP relationship) should be developed.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.33 no.2
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• pp.103-111
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• 1988

This study was carried out with two cultivars under two levels of pH and four levels of nitrogen fertilization in a field and nutri-culture experiments to obtain the information about the effects of pH and nitrogen fertilization on the growth and yield of soybean. Acidic condition suppressed the growth of soybean plants, and thus yield and yield components of soybean decreased under acidic condition. But they increased with increased nitrogen fertilization. Especially, these respones were more remarkable under acidic condition and in the variety Jangbaegkong. Grain yield of soybean were highly correlated with the content of allantoin and total nitrogen of soybean plants in the variety Jangbaegkong, but this was not in the variety Danyeobkong. The content of protein and fat of soybean seeds decreased under acidic condition, and more nitrogen fertilization increased the protein content, but decreased the fat content.

• Journal of Food Hygiene and Safety
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• v.38 no.4
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• pp.211-216
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• 2023

A total of 100 commercially available olive oil products were analyzed for 179 pesticide residues using gas chromatography-tandem mass spectrometry (GC/MS/MS). The olive oil samples were mixed with organic solvents, centrifuged and frozen to remove fat, and pesticide residues were analyzed using the "quick, easy, cheap, effective, rugged, and safe" (QuEChERS) method. The determination coefficient (R²) of the analysis method used in this study was ≥0.998. The detection limit of the method ranged 0.004-0.006 mg/kg and its quantitative limit ranged 0.012-0.017 mg/kg. The recovery rate (n=5) measured at the level ranging 0.01-0.02, 0.1, and 0.5 mg/kg ranged 66.8-119.5%. The relative standard deviation (RSD) was determined to be ≤5.7%, confirming that this method was suitable for the "Guidelines for Standard Procedures for Preparing Food Test Methods". The results showed that a total of 151 pesticides (including difenoconazole, deltamethrin, oxyfluorfen, kresoxim-methyl, phosmet, pyrimethanil, tebuconazole, and trifloxystrobin) were detected in 64 of the 100 olive oil products. The detection range of these pesticide residues was 0.01-0.30 mg/kg. The percentage acceptable daily intake (%ADI) of the pesticides calculated using ADI and estimated daily intake (EDI) was 0.0001-0.1346, indicating that the detected pesticides were present at safe levels. This study provides basic data for securing the safety of olive oil products by monitoring pesticide residues in commercially available oilve oil products. Collectively, the analysis method used in this study can be used as a method to analyze residual pesticides in edible oils.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.491-501
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• 2022

Bentonite has been proposed as a buffer and backfill material for high-level radioactive waste repository. Under such repository environment conditions, bentonite is subjected to combined thermal, hydrological, mechanical, and chemical processes. This study evaluates the feasibility of applying X-ray CT technology on the characterization of bentonite under hydration conditions using a newly developed testing cell. The cylindrical cell is made of platic material, with a removable cap to place the sample, enabling to apply vertical pressure on the sample and to measure swelling pressure. The hydration test was carried out with a sample made of Gyeonju bentonite, with a dry density of 1.4 g/cm³, and a water content of 20%. The sample had a diameter of 27.5 mm and a height of 34 mm. During the test, water was injected at a constant pressure of 0.207 MPa, and lasted for 7 days. After one day of hydration, bentonite swelled and filled out the space inside the cell. Moreover, CT histograms showed how the hydration process induced an initial increase and later progressive decrease on the density of the sample. Detailed profiles of the mean CT value, CT standard deviation, and CT gradient provided more details on the hydration process of the sample and showed how the bottom and top regions exhibited a decrease on density while the middle region showed an increase, especially during the first two days of hydration. Later, the differences in CT values with respect to the initial state decreased, and were small at the end of testing. The formation and later reduction of cracks was also characterized through CT scanning.

• Journal of Bio-Environment Control
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• v.32 no.2
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• pp.122-131
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• 2023

This study was aimed to determine the effects of grow media on the mineral contents of the leaves and growth characteristics of strawberry grown under aquaponics system in a plant factory. For aquaculture, 12 fish (Cyprinus carpio) (total weight, 2.0 kg) were raised in an aquaponics tank (W 0.7 m × L 1.5 m × H 0.45 m, 472.5 L) filled with 367.5 L of water at a density of 5.44 kg·m^-3 and total 34 of strawberry seedlings were transplanted in the pots filed with 200 g of orchid stone, hydroball or polyurethane sponge in the growing bed (W 0.7 m × L 1.5 m × H 0.22 m) laid out with holly acrylic sheet (140×60 mm, Ø80) on the top of the system. The pH and EC of the aquaponic solution was ranged from 7.6 to 4.9 and 0.24-0.91 dS·m^-1, respectively. The concentration of NO_3-N was about 28% lower than that of the hydroponic standard solution, and K, Fe and B were 10, 27 and 3.8 times lower, respectively; however, the mineral contents of strawberry leaves were in the appropriate ranges with lower contents in the leaves grown with sponge media. The organic content (OM), nitrogen (N), phosphorus (P), and potassium (K) of the sludge were 61.5, 5.72, 8.92, and 0.24%, respectively. The leaf area, leaf number, and dry and fresh weights of shoot at 81 DAT were significantly higher in the hydroball, and the average number of fruits per plant was significantly higher in both the orchid stone and hydroball. There was no significant difference in the fresh and dry weights of fruits. Integrated all the results suggest that the orchid stone and hydroball media are more effective to utilize nutrients in solid particles of aquaponic solution, compared to the polyurethane sponge.

• Analytical Science and Technology
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• v.20 no.4
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• pp.261-267
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• 2007

The 20 L small chamber test method is to evaluate pollutants such as TVOC, formaldehyde emitted from building materials. This method was only designed to evaluate the surface emission of sample exposed in the chamber. In this method, building materials cut with a fixed standard size are fixed in a sample sealing box. The sample sealing box is put into the 20 L test chamber. This chamber is ventilated at a standard air change rate with purified air for 7 days then the sample from the chamber is collected and analyzed to measure the emission rate of TVOC and formaldehyde. In this method, however, if the sealing box does not guarantee airtightness, accurate evaluation for the building materials can not be achieved due to the pollutants emitted from edge of the sample so called, edge effect. This edge effect can be much greater when evaluating panels such as plywood, flooring due to their surface treatment. In this study, flooring was tested to check airtightness of the sample sealing box with analytic results between 1L and 20 L test chamber. Furniture materials like LPM coated one side surface treatment and MDF coated both sides surface treatment with LPM were tested to identify whether the improvement of the sample sealing box airtightness is possible with the comparison between existing and improved test method that low VOC emission tape was used to seal the sample edge. After 7 days, MDF TVOC emission rate was different according to the existence and nonexistence of tape. The emission rate of the existing test method was $0.009mg/m^2h$ and that of improved test method was $0.003mg/m^2h$. Relative standard deviation for the existing test method was $0.004mg/m^2h$ and relative standard deviation for the improved test method was $0.002mg/m^2h$ when the same sample was analyzed three times. The improved test method in this study using low VOC emission tape was effective and able to reduce the heterogeneous effect of the edge from the sample sealing box.