• Korean Journal of Plant Resources
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• v.35 no.4
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• pp.471-501
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• 2022

This study was carried out on 455 forest wetlands of south Korea for which an inventory was established through value evaluation and grade. Correlation analysis was conducted to find out the correlation between the types and grades of forest wetlands and 23 evaluation factors in four categories: vegetation and landscape, material circulation and hydraulics·hydrology, humanities and social landscape, and disturbance level. Through the improvement of types and grades of forest wetlands, it is possible to secure basic data that can be used in setting up conservation measures by preparing standards necessary for future forest wetland conservation and restoration, and to found a systematic monitoring system. First, between the type of forest wetland and size and accessibility showed a positive correlation, but the remaining items were analyzed to have negative or no correlation. In particular, it was found that there was no negative correlation or no correlation with the grades of forest wetland. Moreover, it was found that there was a very strong negative correlation with the weighted four category items. Thus, it is judged that improvement is necessary because there is an error in the weight or adjust the evaluation criteria of the value evaluation item, add an item that can increase objectivity. Especially, in the case of forest wetlands, the ecosystem service function due to biodiversity is the largest, so evaluation items should be improved in consideration of this. Therefore, it can be divided into five categories: uniqueness and rarity (15%), wildlife habitat (15%), vegetation and landscape (35%), material cycle·hydraulic hydrology (30%), and humanities and social landscape (5%). It will be possible to propose weights that can increase effectiveness.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3543-3548
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• 2023

Shutdown chemistry evolution is performed in nuclear power plants at each refueling outage (RFO) to establish safe conditions to open system and minimize inventory of corrosion products in the reactor coolant system (RCS). After hydrogen peroxide is added to RCS during shutdown chemistry evolution, corrosion products are released and are removed by filters and ion exchange resins in the chemical volume control system (CVCS). Shutdown chemistry evolution including RCS clean-up time to remove released corrosion products impacts the critical path schedule during RFOs. The estimation of clean-up time prior to RFO can provide more reliable actions for RCS clean-up operations and transients to operators during shutdown chemistry. Electric Power Research Institute (EPRI) shutdown calculator (SDC) enables to provide clean-up time by Co-58 peak activity through operational data from nuclear power plants (NPPs). In this study, we have investigated the results of EPRI SDC by shutdown chemistry data of Co-58 activity using NPP data from previous cycles and modeled the estimated clean-up time by EPRI SDC using average Co-58 activity of the NPP. We selected two RFO data from the NPP to evaluate EPRI SDC results using the purification time to reach to 1.3 mCi/cc of Co-58 after hydrogen peroxide addition. Comparing two RFO data, the similar purification time between actual and computed data by EPRI SDC, 0.92 and 1.74 h respectively, was observed with the deviation of 3.7-7.2%. As the modeling the estimated clean-up time, we calculated average Co-58 peak concentration for normal cycles after cycle 10 and applied two-sigma (2σ, 95.4%) for predicted Co-58 peak concentration as upper and lower values compared to the average data. For the verification of modeling, shutdown chemistry data for RFO 17 was used. Predicted RCS clean-up time with lower and upper values was between 21.05 and 27.58 h, and clean-up time for RFO 17 was 24.75 h, within the predicted time band. Therefore, our calculated modeling band was validated. This approach can be identified that the advantage of the modeling for clean-up time with SDC is that the primary prediction of shutdown chemistry plans can be performed more reliably during shutdown chemistry. This research can contribute to improving the efficiency and safety of shutdown chemistry evolution in nuclear power plants.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.6
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• pp.1157-1163
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• 2012

This study was performed a comparative life cycle assessment (LCA) among three rice production systems in order to analyze the difference of greenhouse gases (GHGs) emissions and environment impacts. Its life cycle inventory (LCI) database (DB) was established using data obtained from interview with conventional, without agricultural chemical and organic farming at Gunsan and Iksan, Jeonbuk province in 2011. According to the result of LCI analysis, $CO_2$ was mostly emitted from fertilizer production process and rice cropping phase. $CH_4$ and $N_2O$ were almost emitted from rice cultivation phase. The value of carbon footprint to produce 1 kg rice (unhulled) on conventional rice production system was 1.01E+00 kg $CO_2$-eq. $kg^{-1}$ and it was the highest value among three rice production systems. The value of carbon footprints on without agricultural chemical and organic rice production systems were 5.37E-01 $CO_2$-eq. $kg^{-1}$ and 6.58E-01 $CO_2$-eq. $kg^{-1}$, respectively. Without agricultural chemical rice production system whose input amount was the smallest had the lowest value of carbon footprint. Although the yield of rice from organic farming was the lowest, its value of carbon footprint less than that of conventional farming. Because there is no compound fertilizer inputs in organic farming. Compound fertilizer production and methane emission during rice cultivation were the main factor to GHGs emission in conventional and without agricultural chemical rice production systems. In organic rice production system, the main factors to GHGs emission were using fossil fuel on machine operation and methane emission from rice paddy field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.87-95
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• 2016

This study examined the characteristics of the hourly demand of city gas in Korea and proposed multiple regression models to obtain precise estimates of the hourly demand of city gas. Forecasting the hourly demand of city gas with accuracy is essential in terms of safety and cost. If underestimated, the pipeline pressure needs to be increased sharply to meet the demand, when safety matters. In the opposite case, unnecessary inventory and operation costs are incurred. Data analysis showed that the hourly demand of city gas has a very high autocorrelation and that the 24-hour demand pattern of a day follows the previous 24-hour demand pattern of the same day. That is, there is a weekly cycle pattern. In addition, some conditions that temperature affects the hourly demand level were found. That is, the absolute value of the correlation coefficient between the hourly demand and temperature is about 0.853 on average, while the absolute value of the correlation coefficient on a specific day improves to 0.861 at worst and 0.965 at best. Based on this analysis, this paper proposes a multiple regression model incorporating the hourly demand ahead of 24 hours and the hourly demand ahead of 168 hours, and another multiple regression model with temperature as an additional independent variable. To show the performance of the proposed models, computational experiments were carried out using real data of the domestic city gas demand from 2009 to 2013. The test results showed that the first regression model exhibits a forecasting accuracy of MAPE (Mean Absolute Percentage Error) around 4.5% over the past five years from 2009 to 2013, while the second regression model exhibits 5.13% of MAPE for the same period.

• Sleep Medicine and Psychophysiology
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• v.6 no.1
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• pp.76-84
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• 1999

Objectives: A number of studies have shown that sleep deprivation results in reduced vigilance and increased negative affects such as tension, depression and anger. However there are few studies about effects of sleep deprivation on anxiety. The purpose of this study was to investigate the effects of 40 hour sleep deprivation on state anxiety, affects, sleepiness and fatigue. The authors also intended to study the effect of trait-anxiety on these psychological variables after sleep deprivation. Methods: Twenty nine subjects(22 men, 7 women, $24.59{\pm}1.35$ years of age) participated in this study. Subjects had no past history of psychiatric disorders and physical illnesses, and had normal sleep-waking cycle without current sleep disturbances. All of the subjects completed sleep dairy for two weeks to exclude some who suffered from chronic sleep deprivation or sleep disturbances. Subjects were instructed to get a normal sleep as usual at night before the study. After awakening, subjects remained awake for 40 hours under continuous surveillance. They completed State-Trait Anxiety Inventory, Index of General Affect, Stanford Sleepiness Scale and Fatigue Questionnaire every three hours, therefore they completed the scales 14 times totally. Subjects were dictated not to take caffeine, alcohol, or any medications on the day of the study. Heavy exercises and naps were restricted too. Results: Sleep deprivation resulted in increased state anxiety, negative general affects, and increased sleepiness and fatigue(p<.001). Dividing into high trait-anxiety group and low trait-anxiety group, there was significant sleep deprivation x traitanxiety interaction effect on general affect(p<.05). But, there was no significant sleep deprivation x trait-anxiety interaction effect on state-anxiety, sleepiness and fatigue. During sleep deprivation, the highest ratings of scales on anxiety, negative affect, sleepiness and fatigue occurred between 4 : 00AM and 7 : 00AM. Conclusions: These results show that sleep deprivation results in increased anxiety, mood state disturbance and increment of sleepiness and fatigue. These findings also suggest that trait-anxiety is a factor that influences the degree of worsening in general affect caused by sleep deprivation. During sleep deprivation, the rating curves of anxiety, affect, sleepiness and fatigue show rhythmicity that may be related to circadian rhythm.

• Journal of Distribution Science
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• v.9 no.3
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• pp.83-94
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• 2011

Most domestic companies, with the exclusion of major firms, are reluctant to implement a supply chain management (SCM) network into their operations. Most small- and medium-sized enterprises are not even aware of SCM. Due to the inherent total-systems efficiency of SCM, it coordinates domestic manufacturers, subcontractors, distributors, and physical distributors and cuts down on cost of inventory control, as well as demand management. Furthermore, a lack of SCM causes a decrease in competitiveness for domestic companies. The reason lies in the fundamentality of SCM, which is the characteristic of information sharing, process innovation throughout SCM, and the vast range of problems the SCM management tool is able to address. This study suggests the contemplation and reformation of the current SCM situation by analyzing the SCM strategic plan, discourses and logical discussions on the topic, and a successful case for adapting SCM; hence, the study plans to productively "process" SCM. First, it is necessary to contemplate the theoretical background of SCM before discussing how to successfully process SCM. I will describe the concept and background of SCM in Chapter 2, with a definition of SCM, types of SCM promotional activities, fields of SCM, necessity of applying SCM, and the effects of SCM. All of the defects in currently processing SCM will be introduced in Chapter 3. Discussion items include the following: the Bullwhip Effect; the breakdown in supply chain and sales networks due to e-business; the issue that even though the key to a successful SCM is cooperation between the production and distribution company, during the process of SCM, the companies, many times, put their profits first, resulting in a possible defect in demands estimation. Furthermore, the problems of processing SCM in a domestic distribution-production company concern Information Technology; for example, the new system introduced to the company is not compatible with the pre-existing document architecture. Second, for effective management, distribution and production companies should cooperate and enhance their partnership in the aspect of the corporation; however, in reality, this seldom occurs. Third, in the aspect of the work process, introducing SCM could provoke corporations during the integration of the distribution-production process. Fourth, to increase the achievement of the SCM strategy process, they need to set up a cross-functional team; however, many times, business partners lack the cooperation and business-information sharing tools necessary to effect the transition to SCM. Chapter 4 will address an SCM strategic plan and a case study of LG Electronics. The purpose of the strategic plan, strategic plans for types of business, adopting SCM in a distribution company, and the global supply chain process of LG Electronics will be introduced. The conclusion of the study is located in Chapter 5, which addresses the issue of the fierce competition that companies currently face in the global market environment and their increased investment in SCM, in order to better cope with short product life cycle and high customer expectations. The SCM management system has evolved through the adaptation of improved information, communication, and transportation technologies; now, it demands the utilization of various strategic resources. The introduction of SCM provides benefits to the management of a network of interconnected businesses by securing customer loyalty with cost and time savings, derived through the consolidation of many distribution systems; additionally, SCM helps enterprises form a wide range of marketing strategies. Thus, we could conclude that not only the distributors but all types of businesses should adopt the systems approach to supply chain strategies. SCM deals with the basic stream of distribution and increases the value of a company by replacing physical distribution with information. By the company obtaining and sharing ready information, it is able to create customer satisfaction at the end point of delivery to the consumer.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1195-1206
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• 2011

This study was conducted to apply LCA (Life cycle assessment) methodology to lettuce (Lactuca sativa L.) production systems in Namyang-ju as a case study. Five lettuce growing farms with three different farming systems (two farms with organic farming system, one farm with a system without agricultural chemicals and two farms with conventional farming system) were selected at Namyangju city of Gyeonggi-province in Korea. The input data for LCA were collected by interviewing with the farmers. The system boundary was set at a cropping season without heating and cooling system for reducing uncertainties in data collection and calculation. Sensitivity analysis was carried out to find out the effect of type and amount of fertilizer and energy use on GHG (Greenhouse Gas) emission. The results of establishing GTG (Gate-to-Gate) inventory revealed that the quantity of fertilizer and energy input had the largest value in producing 1 kg lettuce, the amount of pesticide input the smallest. The amount of electricity input was the largest in all farms except farm 1 which purchased seedlings from outside. The quantity of direct field emission of $CO_2$, $CH_4$ and $N_2O$ from farm 1 to farm 5 were 6.79E-03 (farm 1), 8.10E-03 (farm 2), 1.82E-02 (farm 3), 7.51E-02 (farm 4) and 1.61E-02 (farm 5) kg $kg^{-1}$ lettuce, respectively. According to the result of LCI analysis focused on GHG, it was observed that $CO_2$ emission was 2.92E-01 (farm 1), 3.76E-01 (farm 2), 4.11E-01 (farm 3), 9.40E-01 (farm 4) and $5.37E-01kg\;CO_2\;kg^{-1}\;lettuce$ (farm 5), respectively. Carbon dioxide contribute to the most GHG emission. Carbon dioxide was mainly emitted in the process of energy production, which occupied 67~91% of $CO_2$ emission from every production process from 5 farms. Due to higher proportion of $CO_2$ emission from production of compound fertilizer in conventional crop system, conventional crop system had lower proportion of $CO_2$ emission from energy production than organic crop system did. With increasing inorganic fertilizer input, the process of lettuce cultivation covered higher proportion in $N_2O$ emission. Therefore, farms 1 and 2 covered 87% of total $N_2O$ emission; and farm 3 covered 64%. The carbon footprints from farm 1 to farm 5 were 3.40E-01 (farm 1), 4.31E-01 (farm 2), 5.32E-01 (farm 3), 1.08E+00 (farm 4) and 6.14E-01 (farm 5) kg $CO_2$-eq. $kg^{-1}$ lettuce, respectively. Results of sensitivity analysis revealed the soybean meal was the most sensitive among 4 types of fertilizer. The value of compound fertilizer was the least sensitive among every fertilizer imput. Electricity showed the largest sensitivity on $CO_2$ emission. However, the value of $N_2O$ variation was almost zero.