• Korean Journal of Heritage: History & Science
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• v.51 no.2
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• pp.78-91
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• 2018

Sangjogam, located in Goseong, Gyeongsangnam-do, was designated as Natural Monument #411, because of its diverse geological heritage, such as fossils, ripple marks, dykes, and columnar joints. In the area, Byeongpungbawi, with its beautiful columnar joints vertical to the bedding plane of the underlying sedimentary rocks and spectacular coastal view, was named after its overall shape reminiscent of a huge folding screen. The purpose of this study was to investigate the formation process of the columnar joints using the anisotropy of magnetic susceptibility (AMS) method. AMS measurements showed that the k1 and k3 values representative of directions of the long and short axes of a magnetic particle at each point strongly clustered, and the oblate magnetic foliation structure in Byeongpungbawi developed during sill-type intrusion rather than lava flow. In summary, Byeongpungbawi was produced by sill-type intrusion along the bedding plane of the underlying sedimentary layer, and the subsequent formation of columnar joints was accompanied by the cooling and contraction of intruding rhyolite magma. This study potentially provides a basic research tool in understanding the formation mechanism of columnar joints which are widely distributed in southern Korea.

• Journal of Mushroom
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• v.18 no.4
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• pp.398-402
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• 2020

This study was conducted to set up a proper replacement cycle of High Efficiency Particulate Air (HEPA) filters by observing the microbial populations in the air of the cultivation house of Pleurotus eryngii, before and after HEPA filter replacement at different periods. The density of bacteria and fungi in the air during each cultivation stage was measured using a sampler before the replacement of the HEPA filter. The results showed that airborne microorganisms had the highest density in the mushroom medium preparation room, with 169.7 CFU/㎥ of bacteria and 570 CFU/㎥ of fungi, and the removed old spaun had 126.3 CFU/㎥ of bacteria and 560 CFU/㎥ of fungi. The density of bacteria and fungi in the air at each cultivation stage before the replacement of the HEPA filter was 169.7 CFU/㎥ and 570 CFU/㎥, and 126.3 CFU/㎥ and 560 CFU/㎥, during the medium production and harvesting processes, respectively. After the replacement of the HEPA filter, the bacterial density was the lowest in the incubation room and the fungal density was the lowest in the cooling room. The microbial populations isolated at each period consisted of seven genera and seven species before the replacement, including Cladosporium sp., six genera and six species after 1 month of replacement, including Penicillium sp., 5 genera and 7 species after 3 months of replacement, including Mucor plumbeus, and 5 genera and 12 species, 5 genera and 10 species, and 5 genera and 10 species, 4, 5, and 6 months after the replacement, respectively, including Penicillium brevicompactum. During the period after replacement, the species were diversified and their number increased. The density of airborne microorganisms decreased drastically after the replacement of the HEPA filter. Its lowest value was recorded after 2 months of replacement, and it increased gradually afterwards, reaching a level similar to or higher than that of the pre-replacement period. Therefore, it was concluded that replacing the HEPA filter every 6 months is effective for reducing contamination.

• Economic and Environmental Geology
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• v.56 no.1
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• pp.55-63
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• 2023

Variations in geochemical and mineralogical properties of the ferromanganese(Fe-Mn) crust reflect environmental changes. In the present study, geochemical and mineralogical analyses, including micro X-ray fluorescence and X-ray diffraction, were utilized to reconstruct the paleo-ocean environment of western Pacific Magellan seamount cluster. Samples of the Fe-Mn crust were collected using an epibenthic sledge from the open seamount XX (151° 51.12' 7.2" E and 16° 8.16' 9.6" N, 1557 meters below sea level) in the Western Pacific Magellan Seamount. According to the structure and phosphating status, the Fe-Mn crust of the OSM-XX can be divided into the following: phosphatizated (L4-L5), massive non-phosphatizated (L3), and porous non-phosphatizated (L1-L2) portions. All ferromanganese layers contain vernadite, and owing to the presence of carbonate fluorapatite (CFA), the phosphatizated portion (L4-L5) is rich in Ca and P. The massive non-phosphatizated section (L3) contains high Mn, Ni, and Co, whereas the porous non-phosphatizated portion (L1-L2), which comprises detrital quartz and feldspar, is rich in Fe. Variations in properties of the Fe-Mn crust from the OSM-XX reflect changes in the nearby marine environment. The formation of this crust started at approximately 51.87 Ma, and precipitation of the CFA during the global phosphatization event that occurred at approximately 36-32 Ma highlights an elevated sea level and low temperature during the associated period. The high Mn, Ni, and Co concentrations and elevated Mn/Fe ratios of samples from the massive phosphatizated portion indicate that the oxygen minimum zone (OMZ) was enhanced, and reducing conditions prevailed during the crust formation. The high Fe and low Mn/Fe ratios in the porous portion indicate a weak OMZ and dominantly oxidizing conditions. These data reflect environmental changes following the end of the Mi-1 glacial period in the Miocene-Oligocene boundary. Subsequently, Mn/Fe and Co/Mn ratios increased slightly in the outermost part of Fe-Mn crust because of the enhanced bottom current and OMZ associated with the continued cooling from approximately 9 Ma. However, the reduced carbonate dissolution rate in the Pacific Ocean from approximately 6 Ma decreased the growth rate of the Fe-Mn crust.

• Journal of Bio-Environment Control
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• v.32 no.2
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• pp.89-96
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• 2023

This study was conducted to apply with an air duct for the cooling and a utilizing cultivating method that uses the fruiting node and the defoliation to the high-temperature vertical and hydroponic cultivation of the oriental melon. The lower fruiting node (LF) was to remove all third vines generated from 5 nodes of a secondary vine. The higher fruiting node (HF) was fruiting on the third vine generated from a first node of the third vine. The direction of the stem string; upward (UW), downward (DW). Four treatment conditions were applied with the LF-UW, LF-DW, HF-UW (control), and HF-DW. The leaf age of melon leaves was measured for photosynthesis at 3 days intervals, and the fruit characteristic was conducted on 79 fruits in each treatment. The photosynthesis rate steadily increased after leaf development, reaching 20.8 μmol CO₂·m^-2·s^-1 on the 10 days, gradually increasing to 21.3 μmol CO₂·m^-2·s^-1 on the 19 days, and reaching 23.4 μmol CO₂·m^-2·s^-1 on the 32 days. After that, it lowered to 16.8 μmol CO₂·m^-2·s^-1 on the 38 days and dropped significantly to 7.6 μmol CO₂·m^-2·s^-1 on the 47 days. As a result of the fruit characteristics by fruiting nodes, the treatments of the fruit length was 12.6-13.4 cm, respectively, which was significant, and the fruit width was 7.9- 8.6 cm, respectively, was not significant. The soluble content ranged from 12.9 to 15.7°Brix, and the significance of all treatments, and higher than of LF-DW and HF-UW. The photosynthesis rate of melon leaves was good until 32 days after leaf development, but after that, the rate decreased. As for fruit quality, it was conformed that melons can be cultivated at the LF because the fruit enlargement and soluble content dose not decrease even when set at the LF. Results indicated that those can be used for LF and defoliation in the development of vertical and hydroponic cultivation method in high-temperature season.

• Journal of the Korean Institute of Gas
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• v.27 no.3
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• pp.52-58
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• 2023

With the increasing awareness of the importance of carbon neutrality in response to global climate change, the utilization of hydrogen as a carbon-free fuel source is also growing. Hydrogen is commonly used in fuel cells (FC), but it can also be utilized in internal combustion engines (ICE) that are based on combustion. Particularly, ICEs that already have established infrastructure for production and supply can greatly contribute to the expansion of hydrogen energy utilization when it becomes difficult to rely solely on fuel cells or expand their infrastructure. However, a disadvantage of utilizing hydrogen through combustion is the potential generation of nitrogen oxides (NOx), which are harmful emissions formed when nitrogen in the air reacts with oxygen at high temperatures. In particular, for the EURO-7 exhaust regulation, which includes cold start operation, efforts to reduce exhaust emissions during the warm-up process are required. Therefore, in this study, the characteristics of nitrogen oxides and fuel consumption were investigated during the warm-up process of cooling water from room temperature to 88℃ using a 2-liter direct injection spark ignition (SI) engine fueled with hydrogen. One advantage of hydrogen, compared to conventional fuels like gasoline, natural gas, and liquefied petroleum gas (LPG), is its wide flammable range, which allows for sparser control of the excessive air ratio. In this study, the excessive air ratio was varied as 1.6/1.8/2.0 during the warm-up process, and the results were analyzed. The experimental results show that as the excessive air ratio becomes sparser during warm-up, the emission of nitrogen oxides per unit time decreases, and the thermal efficiency relatively increases. However, as the time required to reach the final temperature becomes longer, the cumulative emissions and fuel consumption may worsen.

• The Korean Journal of Quaternary Research
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• v.20 no.1 s.26
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• pp.51-66
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• 2006

The climate of the last glacial maximum (LGM) in northeast Asia is simulated with an atmospheric general circulation model of NCAR CCM3 at spectral truncation of T170, corresponding to a grid cell size of roughly 75 km. Modern climate is simulated by a prescribed sea surface temperature and sea ice provided from NCAR, and contemporary atmospheric CO2, topography, and orbital parameters, while LGM simulation was forced with the reconstructed CLIMAP sea surface temperatures, sea ice distribution, ice sheet topography, reduced $CO_2$, and orbital parameters. Under LGM conditions, surface temperature is markedly reduced in winter by more than $18^{\circ}C$ in the Korean west sea and continental margin of the Korean east sea, where the ocean exposed to land in the LGM, whereas in these areas surface temperature is warmer than present in summer by up to $2^{\circ}C$. This is due to the difference in heat capacity between ocean and land. Overall, in the LGM surface is cooled by $4{\sim}6^{\circ}C$ in northeast Asia land and by $7.1^{\circ}C$ in the entire area. An analysis of surface heat fluxes show that the surface cooling is due to the increase in outgoing longwave radiation associated with the reduced $CO_2$ concentration. The reduction in surface temperature leads to a weakening of the hydrological cycle. In winter, precipitation decreases largely in the southeastern part of Asia by about $1{\sim}4\;mm/day$, while in summer a larger reduction is found over China. Overall, annual-mean precipitation decreases by about 50% in the LGM. In northeast Asia, evaporation is also overall reduced in the LGM, but the reduction of precipitation is larger, eventually leading to a drier climate. The drier LGM climate simulated in this study is consistent with proxy evidence compiled in other areas. Overall, the high-resolution model captures the climate features reasonably well under global domain.

• Korean Journal of Agricultural Science
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• v.16 no.1
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• pp.84-101
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• 1989

An accurate measurement of size, surface area and volume of agricultural products is essential in many engineering operations such as handling and sorting, and in heat transfer studies on heating and cooling processes. Little information is available on these properties due to their irregular shape, and moreover very little information on the rough rice, soybean, barley, and wheat has been published. Physical dimensions of grain, such as length, width, thickness, surface area, and volume vary according to the variety, environmental conditions, temperature, and moisture content. Especially, recent research has emphasized on the variation of these properties with the important factors such as moisture content. The objectives of this study were to determine physical dimensions such as length, width and thickness, surface area and volume of the rough rice, soybean, barley, and wheat as a function of moisture content, to investigate the effect of moisture content on the properties, and to develop exponential equations to predict the surface area and the volume of the grains as a function of physical dimensions. The varieties of the rough rice used in this study were Akibare, Milyang 15, Seomjin, Samkang, Chilseong, and Yongmun, as a soybean sample Jangyeobkong and Hwangkeumkong, as a barley sample Olbori and Salbori, and as a wheat sample Eunpa and Guru were selected, respectively. The physical properties of the grain samples were determined at four levels of moisture content and ten or fifteen replications were run at each moisture content level and each variety. The results of this study are summarized as follows; 1. In comparison of the surface area and the volume of the 0.0375m diameter-sphere measured in this study with the calculated values by the formula the percent error between them showed least values of 0.65% and 0.77% at the rotational degree interval of 15 degree respectively. 2. The statistical test(t-test) results of the physical properties between the types of rough rice, and between the varieties of soybean and wheat indicated that there were significant difference at the 5% level between them. 3. The physical dimensions varied linearly with the moisture content, and the ratios of length to thickness (L/T) and of width to thickness (W/T) in rough rice decreased with increase of moisture content, while increased in soybean, but uniform tendency of the ratios in barley and wheat was not shown. In all of the sample grains except Olbori, sphericity decreased with increase of moisture content. 4. Over the experimental moisture levels, the surface area and the volume were in the ranges of about $45{\sim}51{\times}10^{-6}m^2$, $25{\sim}30{\times}10^{-9}m^3$ for Japonica-type rough rice, about $42{\sim}47{\times}10^{-6}m^2$, $21{\sim}26{\times}10^{-9}m^3$ for Indica${\times}$Japonica type rough rice, about $188{\sim}200{\times}10^{-6}m^2$, $277{\sim}300{\times}10^{-9}m^3$ for Jangyeobkong, about $180{\sim}201{\times}10^{-6}m^2$, $190{\sim}253{\times}10^{-9}m^3$ for Hwangkeumkong, about $60{\sim}69{\times}10^{-6}m^2$, $36{\sim}45{\times}10^{-9}m^3$ for Covered barley, about $47{\sim}60{\times}10^{-6}m^2$, $22{\sim}28{\times}10^{-9}m^3$ for Naked barley, about $51{\sim}20{\times}10^{-6}m^2$, $23{\sim}31{\times}10^{-9}m^3$ for Eunpamill, and about $57{\sim}69{\times}10^{-6}m^2$, $27{\sim}34{\times}10^{-9}m^3$ for Gurumill, respectively. 5. The increasing rate of surface area and volume with increase of moisture content was higher in soybean than other sample grains, and that of Japonica-type was slightly higher than Indica${\times}$Japonica type in rough rice. 6. The regression equations of physical dimensions, surface area and volume were developed as a function of moisture content, the exponential equations of surface area and volume were also developed as a function of physical dimensions, and the regression equations of surface area were also developed as a function of volume in all grain samples.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.