• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.335-341
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• 2019

In order to provide basic data for uniformization of temperature distribution in heating greenhouses, heating experiments were performed in two greenhouses with a hot water heating system. By analyzing heat transfer characteristics and improving pipes layout, measures to reduce the variation of pipe surface temperature and to improve the uniformity were derived. As a result of analyzing the temperature distributions of two different greenhouses and examining the maximum deviation and uniformity, it was found that the temperature deviation of greenhouses with a large amount of hot water flow and a short heating pipe was small and the uniformity was high. And it was confirmed that the temperature deviation was reduced and the uniformity was improved when the circulating fan was operated. The correlation between the surface temperature of the heating pipe and the indoor air temperature was a positive correlation and statistically significant(p<0.01) in both greenhouses. It was confirmed that the indoor temperature distribution in a hot water heating greenhouse was influenced by the surface temperature distribution of heating pipe, and the uniformity of indoor temperature distribution could be improved by arranging the heating pipe to minimize the temperature deviation. Analysis of the heat transfer characteristics of heating pipe showed that the temperature deviation increased as the pipe length became longer and the temperature deviation became smaller as the flow rate in pipe increased. Therefore, it was considered that the temperature distribution and the uniformity of environment in a greenhouse could be improved by arranging the heating pipe to shorten the length and controlling the flow velocity in pipe. In order to control the temperature deviation of one branch pipe within $3^{\circ}C$ in the tube rail type hot water heating system most used in domestic greenhouses, when the flow velocity in the pipe is 0.2, 0.4, 0.6, 0.8, $1.0m{\cdot}s^{-1}$, the length of a heating pipe should be limited to 40, 80, 120, 160, 200m, respectively.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.2
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• pp.110-123
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• 2021

We investigated geochemical constituents of pore-water and sediment, rates of organic carbon (C_org) oxidation and sulfate reduction (SR), and benthic nutrient flux (BNF) to elucidate characteristic of C_org oxidation and its control in the coastal area near Lake Shihwa. The study sites were selected in the vicinity of Soraepogu (E0), Songdo tidalflat (E1) and Oido dock (E3) and in front of floodgate Shihwa tidal plant (E5). The C_org contents in the sediments and concentrations of ammonium and phosphate in pore water exhibited the highest value at EO, and gradually decreased toward the outer sea (E1, E3, E5). Rates of anaerobic C_org oxidation (260.6 mmol C m^-2 d^-1) and SR (91.4 mmol S m^-2 d^-1) at E0 were 4-9 and 6-54 times higher than at the site of outer sea (E1, E3, E5). Rates of SR at E3 and E5 accounted for 11-23% of anaerobic C_org oxidation, whereas it comprised 47-70% of anaerobic C_org oxidation at E0 and E1. Rates of C_org oxidation and SR showed a highly positive correlation with the concentration of dissolved organic carbon (r² = 0.795 and 0.777, respectively). The BNF at E0, E1, and E3 accounted for 120-510% and 26-178%, respectively, of the N and P required for primary production in the water column. Overall results suggest that the C_org oxidation in the sediment controlled by concentration of dissolved organic carbon in the pore water and the excessive C_org oxidation stimulates the benthic nutrient flux, which may cause a phytoplankton bloom in the water column.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.746-752
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• 2022

Kiribati, a South Pacific island, and its surrounding countries are gradually submerging to rising sea levels. The sea level continues to change according to the degree of thermal expansion of glaciers and seawater that decreases with increase in temperature. Global warming affects both the amount and volume of seawater, thus increasing sea level. Tidal phenomena occur twice a day to the attraction of celestial bodies such as the moon and the sun. The moon changes the angle of orbiting surface with the Earth equator every 18.6 years, and the magnitude of the tidal force changes depending on the distance between the Earth equator and the moon orbital surface. The University of Hawaii Sea Level Center selected Tarawa, Christmas, Kanton of Kiribati,, Lautoka, Suva of Fiji,Funafuti of Tuvalu, Nuk1u'alofa of Tonga, and Port Vila of Vanuatu. When comparing tide levels for each year for 19 years, the focus was on checking the change in sleep to Tide levels, and rising sea levels was the effect of Tide levels. The highest astronomical tides (HAT) and lowest astronomical tides (LAT) were identified as Tarawa 297.0, 50.8 cm, Christmas 123.8, 19.9 cm, Kanton 173.7, 39.9 cm, Lautoka 240.7, 11.3 cm, Funafuti 328.6, 98.4 cm, Nuk1u'alofa 188.8, 15.5 cm, Port Vila 161.5, -0.5cm, respectively. The Sea level rising speed was Tarawa 3.1 mm/year, Christmas -1.0 mm/year, Kanton 1.6 mm/year, Lautoka 3.1 mm/year, Suva 7.4 mm/year, Funafuti 1.4 mm/year, Nuk1u'alofa 4.2 mm/year, and Port Vila -1.2 mm/year, respectively

• Plant Journal
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• v.18 no.4
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• pp.58-65
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• 2023

In this study, to increase the methane content of biogas supplied from Nanji Water Regeneration Center and to purify impurities, a three-stage membrane purification process was designed and installed to demonstrate operation. The methane concentration of biomethane produced in the 2 Nm3/h purification process was set to three cases: 95%, 96.5%, and 98%, and the membrane area ratio of the membrane was 1:1, 1:2, 1:1:1, The optimum conditions for the membrane area of the separator were derived by changing to five of 1:2:1 and 1:2:2. 3 stage separation membrane process of 30 Nm3/h was installed to reflect the optimum condition of 2 Nm3/h, and biomethane production of 98% or more of methane concentration was demonstrated. As a result of the operation of the 2 Nm³/h refining device, the methane recovery rate at the 98% methane concentration was 95.6% when the membrane area ratio was 1:1 as the result of the two-stage operation of the separator, and the recovery rate of methane at 1:2 was increased to 96.8%. The methane recovery rate of the membrane three-stage operation was highest at 96.8% when the membrane area ratio was operated at 1:2:1. The carbon dioxide removal rate was 16.4 to 96.4% and the 2:2 to 95.7% film area ratio in the two-step process. In the three-step process, the film area ratio was 1:2:1 to 95.4%, and the two-step process showed higher results than the three-step process. In the 30 Nm3/h scale biogas purification demonstration operation, the methane concentration after purification was 98%, the recovery rate of methane was 97.1%, the removal rate of carbon dioxide was 95.7%, and hydrogen sulfide, the cause of corrosion, was not detected, and the membrane area ratio was 1:2:1 demonstration operation, biomethane production with a methane concentration of 98% or higher was possible.

• Journal of IKEEE
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• v.27 no.1
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• pp.116-121
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• 2023

In this paper, we develop a deep learning structure for a complex microbial incubator that applies deep learning prediction result information. The proposed complex microbial incubator consists of pre-processing of complex microbial data, conversion of complex microbial data structure, design of deep learning network, learning of the designed deep learning network, and GUI development applied to the prototype. In the complex microbial data preprocessing, one-hot encoding is performed on the amount of molasses, nutrients, plant extract, salt, etc. required for microbial culture, and the maximum-minimum normalization method for the pH concentration measured as a result of the culture and the number of microbial cells to preprocess the data. In the complex microbial data structure conversion, the preprocessed data is converted into a graph structure by connecting the water temperature and the number of microbial cells, and then expressed as an adjacency matrix and attribute information to be used as input data for a deep learning network. In deep learning network design, complex microbial data is learned by designing a graph convolutional network specialized for graph structures. The designed deep learning network uses a cosine loss function to proceed with learning in the direction of minimizing the error that occurs during learning. GUI development applied to the prototype shows the target pH concentration (3.8 or less) and the number of cells (10⁸ or more) of complex microorganisms in an order suitable for culturing according to the water temperature selected by the user. In order to evaluate the performance of the proposed microbial incubator, the results of experiments conducted by authorized testing institutes showed that the average pH was 3.7 and the number of cells of complex microorganisms was 1.7 × 10⁸. Therefore, the effectiveness of the deep learning structure for the complex microbial incubator applying the deep learning prediction result information proposed in this paper was proven.

• Korean Journal of Culture and Social Issue
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• v.9 no.spc
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• pp.107-122
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• 2003

The object of this study is to evaluate the prevailing physical and psychosocial conditions regarding occupational low back injury. This study consists of two parts. In the first part of the study, analytic biomechanical model and NIOSH guidelines are applied to evaluate risk levels of low back injury for automobile assembly jobs. Total of 246 workers are analysed. There are 20 jobs having greater back compressive forces than 300kg at L5/S1. Also, there are 44 jobs over Action Limit with respect to 1981 NIOSH guidelines. The relationship between psychosocial factors and low back injury was examined in the second part of the study. A battery of questionnaires concerning the psychosocial stress based on PWI (Psychosocial Well-being Index) and musculoskeletal pain symptoms at low back was completed by 246 workers at the same plant. Results showed that 207 out 246 workers experienced the symptoms and 27 workers were diagnosed as patients. Two groups(low stressed, high stressed) based on PWI score had no significant relationships with both symptoms and results of diagnosis. The relationships between physical work load and psychosocial stress were also analysed. Specifically, some postural factors(vertical deviation angle of forearm, horizontal deviation angle of upperarm, vertical deviation angle of thigh, etc) were highly correlated with psychosocial stress. The results illustrated that PWI scores were associated with some physical workloads. However, psychosocial stress levels couldn't be well related with the pain symptom as well as the actual incidence of low back injury since pain or discomfort regarding low back injury were more complex than that of other musculoskeletal disorders.

• Korean Journal of Ecology and Environment
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• v.37 no.1 s.106
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• pp.26-35
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• 2004

We investigated the effect of physicochemical environmental factors on the community dynamics of phytoplanktons and bacteria at the Hoeya Dam Reservoir, a drinking water reservoir for Ulsan city. Water samples were collected and analyzed every two to four weeks at three sites along the reservoir from April to October, 2001. During the study period, the Secchi depths were between 0.4 and 3.5 m. At the surface layer of water column, temperature ranged 10.2 ~ $32.0^{\circ}C$, pH 7.3${\sim}$9.6, dissolved oxygen 5.5 ${\sim}$ 12.4 mg $L^{-1}$, $BOD_5$ 0.8 ${\sim}$ 5.0 mg $L^{-1}$, $COD_{Mn}$ 3.7 ${\sim}$ 10.0 mg $L^{-1}$, and Chl-a 8.9 ${\sim}$ 60.9 mg $m^{-3}$. At the bottom layer, temperature varied 7.2 ${\sim}$ $28.9^{\circ}C$, pH 7.1 ${\sim}$ 9.3, dissolved oxygen 0.6 ${\sim}$ 9.7 mg $L^{-1}$, $BOD_5$ 0.8 ${\sim}$ 4.5 mg $L^{-1}$, $COD_{Mn}$ 3.9 ${\sim}$ 10.0 mg $L^{-1}$, and Chl-a 4.3 ${\sim}$ 81.9 mg $m^{-3}$. The numbers of phytoplanktons were 7.4${\pm}10^2{\sim}2.6{\pm}10^5$ cells $mL^{-1}$ at surface and 2.5${\pm}10^2{\sim}2.4{\pm}10^4$ cells $mL^{-1}$ at bottom, and were positively correlated with water temperature and Chl- a concentration. Genus Stephanodiscus and genus Oscillatoria dominated on April and on May, respectively. Cyanobacterial blooms of Aphanizomenon, Microcystis, Anabaena were observed from June to early September, and thereafter Stephanodiscus and Aulacoseiral dominated again. Total microbial counts ranged 1.73${\pm}10^4{\sim}1.68{\pm}10^5$ cells $mL^{-1}$, and were positively correlated with water temperature and phytoplankton counts at surface water. Heterotrophic plate counts (HPCs) ranged 30${\sim}4.1{\pm}10^3$ CFU $mL^{-1}$, and were positively correlated with $BOD_5$ and $NO^3\;^-$-N concentration at bottom water. Unlike the total microbial counts, the numbers of fecal coliforms and fecal streptococci as well as HPCs were higher at the bottom than the surface layer and were highest at the upper a site among the three sampling sites. Since the concentrations of fecal coliforms and streptococci were still high at the bottom of site c, where intake for water treatment plant is located, it appeared that special management of water treatment processes may be needed especially after strong rainfall.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.5
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• pp.853-860
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• 2012

To estimate potential use of fly ash in reducing $CH_4$ and $CO_2$ emission from soil, $CH_4$ and $CO_2$ fluxes from a paddy soil mixed with fly ash at different rate (w/w; 0, 5, and 10%) in the presence and absence of fertilizer N ($(NH_4)_2SO_4$) addition were investigated in a laboratory incubation for 60 days under changing water regime from wetting to drying via transition. The mean $CH_4$ flux during the entire incubation period ranged from 0.59 to $1.68mg\;CH_4\;m^{-2}day^{-1}$ with a lower rate in the soil treated with N fertilizer due to suppression of $CH_4$ production by $SO_4^{2-}$ that acts as an electron acceptor, leading to decreases in electron availability for methanogen. Fly ash application reduced $CH_4$ flux by 37.5 and 33.0% in soils without and with N addition, respectively, probably due to retardation of $CH_4$ diffusion through soil pores by addition of fine-textured fly ash. In addition, as fly ash has a potential for $CO_2$ removal via carbonation (formation of carbonate precipitates) that decreases $CO_2$ availability that is a substrate for $CO_2$ reduction reaction (one of $CH_4$ generation pathways) is likely to be another mechanisms of $CH_4$ flux reduction by fly ash. Meanwhile, the mean $CO_2$ flux during the entire incubation period was between 0.64 and $0.90g\;CO_2\;m^{-2}day^{-1}$, and that of N treated soil was lower than that without N addition. Because N addition is likely to increase soil respiration, it is not straightforward to explain the results. However, it may be possible that our experiment did not account for the substantial amount of $CO_2$ produced by heterotrophs that were activated by N addition in earlier period than the measurement was initiated. Fly ash application also lowered $CO_2$ flux by up to 20% in the soil mixed with fly ash at 10% through $CO_2$ removal by the carbonation. At the whole picture, fly ash application at 10% decreased global warming potential of emitted $CH_4$ and $CO_2$ by about 20%. Therefore, our results suggest that fly ash application can be a soil management practice to reduce green house gas emission from paddy soils. Further studies under field conditions with rice cultivation are necessary to verify our findings.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.28 no.3
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• pp.279-293
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• 1995

The most obvious and easily recognizable sources of potential water pollution are point sources such as domestic and industrial wastes. But recently, the potential effects of nonpoint sources on water quality have been increased apparently. In order to evaluate the characteristics and the effects of nonpoint sources on water quality, this study was performed in Suyeong Bay from May, 1992 to July, 1992. The depth-averaged 2-dimensional numerical model, which consists of the hydrodynamic model and the diffusion model was applied to simulate the water quality in Suyeong Bay. When flowrate was $65.736m^3/s,$ the concentration of pollutants (COD, TSS and VSS) at Oncheon stream (Sebeong bridge) during second flush were very high as much as 121.4mg/l of COD, 1148.0mg/l of TSS and 262.0mg/1 of VSS. When flowrate was 4.686m^3/s, the concentration of pollutants $(TIN,\;NH_4\;^+-\;N,\;NO_2\;^--N\;and\;PO_4\;^{3-}-P)$ during the first flush were very high as much as 20.306mg/1 of TIN, 14.154mg/1 of $NH_4\;^+-N$, 9.571mg/l of $NO_2\;^--N$ and l.785mg/l of $PO_2\;^{3-}-P$ As results of the hydrodynamic model simulation, the computed maximum velocity of tidal currents in Suyeong Bay was 0.3m/s and their direction was clockwise flow for ebb tide and counter clockwise flow for Hood tide. Four different methods were applied for the diffusion simulation in Suyeong Bay. There were the effects for the water quality due to point loads, annual nonpoint loads and nonpoint loads during the wet weather and the investigation period, respectively. The efforts of annual nonpoint loads and nonpoint loads during the wet weather seem to be slightly deteriorated in comparison with the effects of point loads. However, the bay was significantly polluted by the nonpoint loads during the investigation period. In this case, COD and SS concentrations ranged 2.0-30.0mg/l, 7.0- 200.0mg/l in ebb tide, respectively. From these results, it can be emphasized that the large amount of pollutants caused by nonpoint sources during the wet weather were discharged into the bay, and affected significantly to both the water quality and the marine ecosystem. Therefore, it is necessary to consider the loadings of nonpoint pollutants to plan wastewater treatment plant.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.