• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.3-3
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• 2017

The question of how to establish sustainable agricultural systems has become as prominent as questions related to water, energy and climate change. High input/high output agriculture has brought with it many adverse effects; the massive deterioration of soil and water in both quantity and quality, increased greenhouse gas emissions and an increased prevalence of unsafe foods. Additionally, urbanization and climate change has worsened the shortage of farmland and reduced the supply of agricultural water. Given these challenges, maintaining, conserving and efficiently using agri-environmental resources, through fostering of sustainable agriculture, have emerged as key tasks in solving these problems. What is needed therefore is research, based on systematic and comprehensive empirical analyses, that can propose plans and methods for establishing an appropriate sustainable agricultural system. The empirical analysis of sustainable agricultural system is approached separately from economic, environmental and social aspects. An analysis of environment effect reveals that the available phosphate level is 1.3~2.1 times greater than the optimal amount in rice paddies, upland fields and orchards. Further examination has revealed that the excess nutrient is polluting both ground water and surface water. Analytical results for economic feasibility show that factors of production have been invested heavily in the rice crop. Under these conditions, sustainable agriculture, including low-input agriculture, appears to be a possible alternative that will facilitate simultaneous improvements in both economic feasibility and environment effects. Analysis results for sociality reveal that social factors include the value of producer, association and interior networks. Social conditions are comprised of leadership, consumers' awareness, education and conflict solutions. In addition, analysis as to the degree investments contribute to improving agricultural value added has revealed that the direct payment program is the most effective instrument. Experts confirm that economic feasibility can be improved by scientific and well-reasoned nutrient management on the basis of soil testing. Farmers pointed to 'economic factors' as being the largest obstacle to switching to the practice of sustainable agriculture. They also indicate 'uncertainty with regards to sustainable agriculture technology' as an impediment to practicing sustainable agriculture. Even so, farmers who believe environmental and regional issues to be the most pressing problems have expanded their practice of sustainable agriculture. The keys to establishing sustainable agriculture system are classified into the following four aspects. Firstly, from an economic aspect, the research indicates that agricultural policy needs to be integrated with environmental policy and that the function of market making based on the value chain needs to be revitalized. Secondly, from an environmental aspect, there is a need for an optimal resource management system to be established in the agricultural sector. In addition, sustainable agriculture practice will need to be extended with attendant environmentally-friendly and sustainable intensive technology also requiring further development. Thirdly, from a social aspect, green agriculture management needs to be fostered, technology and education extended, and social conflict mediated. Lastly, from a governance aspect, it will be necessary to strengthen good governance, assign and share suitable roles and responsibilities, build a cooperation system and utilize community supported agriculture.

• Journal of Energy Engineering
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• v.23 no.4
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• pp.256-262
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• 2014

Cycle length of domestic nuclear power plants is determined by the demand-supply plan of utility company. The target cycle length is achieved by adjusting the number of feed fuel assembly and fuel enrichment. Traditionally, utility company first select the number of feed fuel assembly and then find out the fuel enrichment to achieve the special cycle length. But it is difficult to find out if this method is most economical than any other combinations of the enrichment and batch size satisfying the same cycle length. In this paper, core depletion calculation is performed to find out the optimum combination of the enrichment and batch size for given target cycle length in terms of fuel cycle cost using commercial core design code; CASMO/MASTER code. To minimize the uncertainty resulting from transition core analysis, levelized fuel cycle cost analysis was applied to the equilibrium cycle core in order to determine the optimum combination. The sensitivity study of discount rate was also carried out to analyze the levelized fuel cycle cost applicable to countries with different discount rates. From the levelized fuel cycle cost analysis results, the combination with smaller batch size and higher fuel enrichment becomes more economical as the discount rate becomes lower. On the other hand, the combination with higher batch size and lower fuel enrichment becomes more economical as the discount rate becomes higher.

• The Journal of Engineering Geology
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• v.26 no.2
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• pp.223-233
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• 2016

This study establishes a commercialization strategy for technology that can monitor and detect landslides in real time. An effective commercialization strategy was sought through both qualitative and quantitative analyses. The qualitative analysis considered the business environment in detail, while the quantitative analysis examined technologically strong and weak areas by visualizing the links between IPC (International Patent Classification) code structure and patent applicants. The results from both analyses are considered together, with particular attention paid to the business environment. The resulting integrated analysis comprehensively explores the degree of technological development and the current state of real-time monitoring and detection technology for landslides. The integrated analysis identified complementary assets in the business environment, as there is strong development and many research entities in this area. This suggests positive reinforcement for commercialization with two sub-strategies: (1) exploring demand with complementary assets, and (2) providing technology information for explored demand, which should facilitate successful commercialization. Exploiting this positive reinforcement for technology commercialization could reduce the high uncertainty of the technology and the market, and thus increase the probability of successful commercialization. It is also expected to contribute to long-term success by strengthening collaboration between the supply and demand sides.

• Land and Housing Review
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• v.4 no.1
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• pp.43-54
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• 2013

This This paper investigates the variation of the factors to determinate housing price in Seoul metropolitan area after sub-prime financial crisis, in Korea, using a VAR model. The model includes housing price and housing rent (Jeonse) in Seoul metropolitan area from 1999 to 2011, and uses interest rate, real GDP, KOSPI, Producer Price Index and practices to impulse response and variance decomposition analysis to grasp the dynamic relation between a variable of macro economy and and a variable of housing price. Data is classified to 2 groups before and after the 3rd quater of 2008, when sub-prime crisis occurred; one is from the 1st quater of 1999 to the 3rd quater of 2008, and the other is from the 2nd quater of 1999 and the 4th quater of 2011. As a result, comparing before and after sub-prime crisis, housing price is more influenced by its own variation or Jeonse price's variation instead of interest rate and KOSPI. Both before and after sub-prime financial crisis, Jeonse price is also influenced by its own variation and housing price. While after sub-prime financial crisis, influences of Producer Price Index, KOSPI and interest rate were weakened, influence of real GDP is expanded. As housing price and housing rent are more influenced by real economy factors such as GDP, its own variation than before sub-prime financial crisis, the recent trend that the house prices is declined is difficult to be converted, considering domestic economic recession and uncertainty, continued by Europe financial crisis. In the future to activate the housing business, it ia necessary to promote purchasing power rather than relaxation of financial and supply regulation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.167-178
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• 2020

The purpose of this study is to examine the relationship between internal corporate, supplier, and customer integrations for domestic SMEs on non-financial and financial performance through SCM performance such as flexibility and reduction of uncertainties. To this end, data was collected on 286 SMEs in Korea, and the structural relationships between SCM integration level, SCM performances, and management performance were analyzed. As a result of the analysis, first, it was found that the SCM integration level had a significant positive effect on the flexibility and reduction of uncertainties, which are SCM performances. Second, the flexibility and reduction of uncertainties showed significantly positive effects on the non-financial performance of the companies, but did not directly affect the financial performance positively. Third, the non-financial performance was found to have a positive effect on the financial performance. In addition, the SCM integration level did not have a direct effect on the financial and non-financial performance, but it was found that it affected management performance by mediating the flexibility and reduction of uncertainties, which are SCM performances. That is, although the SCM integration level did not directly affect financial and non-financial performance, it was confirmed that it affects management performance by mediating SCM performances, flexibility and uncertainty reduction. In other words, it was confirmed that the SCM integration level directly or indirectly affects SCM performances and overall management performance. These results imply the necessity to focus on competency in the supply chain management area according to the SCM performance expected by SMEs, and the step by step approaches to the expected effects. In a situation where prior SCM related studies have not been able to present SCM performances and management performance of SMEs that are relatively lacking in their capital and SCM construction capabilities, the findings of this study could suggest the importance of SCM integration from the perspective of SMEs. In addition, from the viewpoint of SMEs, this study suggested that a sequential approach for performance measurement is required (SCM performance → management performance) in relation to the performance factors to be established through SCM.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.14-14
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• 2011

Groundwater in the Waikatoregion is a valuable resource for agriculture, water supply, forestry and industries. The 434,000 ha study area comprises the upper Waikato River catchment from the outflow of Lake Taupo (New Zealand's largest lake) through to Lake Karapiro (a man-made hydro lake with high recreational value) (Figure 1). Water quality in the area is naturally high. However, there are indications that this quality is deteriorating as a result of land use intensification and deforestation. Compounding this concern for decision makers is the lag time between land use changes and the realisation of effects on groundwater and surface water quality. It is expected that the effects of land use changes have not yet fully manifested, and additional intensification may take decadesto fully develop, further compounding the deterioration. Consequently, Environment Waikato (EW) have proposed a programme of work to develop a groundwater model to assist managing water quality and appropriate policy development within the catchment. One of the most important and critical decisions of any modelling exercise is the choice of the modelling platform to be used. It must not inhibit future decision making and scenario exploration and needs to allow as accurate representation of reality as feasible. With this in mind, EW requested that two modelling platforms, MODFLOW/MT3DMS and FEFLOW, be assessed for their ability to deliver the long-term modelling objectives for this project. The two platforms were compared alongside various selection criteria including complexity of model set-up and development, computational burden, ease and accuracy of representing surface water-groundwater interactions, precision in predictive scenarios and ease with which the model input and output files could be interrogated. This latter criteria is essential for the thorough assessment of predictive uncertainty with third-party software, such as PEST. This paper will focus on the attributes of each modelling platform and the comparison of the two approaches against the key criteria in the selection process. Primarily due to the ease of handling and developing input files and interrogating output files, MODFLOW/MT3DMS was selected as the preferred platform. Other advantages and disadvantages of the two modelling platforms were somewhat balanced. A preliminary regional groundwater numerical model of the study area was subsequently constructed. The model simulates steady state groundwater and surface water flows using MODFLOW and transient contaminant transport with MT3DMS, focussing on nitrate nitrogen (as a conservative solute). Geological information for this project was provided by GNS Science. Professional peer review was completed by Dr. Vince Bidwell (of Lincoln Environmental).

• Journal of Climate Change Research
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• v.9 no.1
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• pp.13-29
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• 2018

This study presented evaluation procedure for selecting appropriate GCMs and downscaling method by focusing on the climate extreme indices suitable for climate change adaptation. The procedure includes six stages of processes as follows: 1) exclusion of unsuitable GCM through raw GCM analysis before bias correction; 2) calculation of the climate extreme indices and selection of downscaling method by evaluating reproducibility for the past and distortion rate for the future period; 3) selection of downscaling method based on evaluation of reproducibility of spatial correlation among weather stations; and 4) MME calculation using weight factors and evaluation of uncertainty range depending on number of GCMs. The presented procedure was applied to 60 weather stations where there are observed data for the past 30 year period on Korea Peninsula. First, 22 GCMs were selected through the evaluation of the spatio-temporal reproducibility of 29 GCMs. Between Simple Quantile Mapping (SQM) and Spatial Disaggregation Quantile Delta Mapping (SDQDM) methods, SQM was selected based on the reproducibility of 27 climate extreme indices for the past and reproducibility evaluation of spatial correlation in precipitation and temperature. Total precipitation (prcptot) and annual 1-day maximum precipitation (rx1day), which is respectively related to water supply and floods, were selected and MME-based future projections were estimated for near-future (2010-2039), the mid-future (2040-2069), and the far-future (2070-2099) based on the weight factors by GCM. The prcptot and rx1day increased as time goes farther from the near-future to the far-future and RCP 8.5 showed a higher rate of increase in both indices compared to RCP 4.5 scenario. It was also found that use of 20 GCM out of 22 explains 80% of the overall variation in all combinations of RCP scenarios and future periods. The result of this study is an example of an application in Korea Peninsula and APCC Integrated Modeling Solution (AIMS) can be utilized in various areas and fields if users want to apply the proposed procedure directly to a target area.

• Journal of Korea Water Resources Association
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• v.54 no.2
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• pp.105-119
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• 2021

An increase in the frequency and intensity of both floods and droughts has been recently observed due to an increase in climate variability. Especially, land-use change associated with industrial structure and urbanization has led to an imbalance between water supply and demand, acting as a constraint in water resource management. Accurate rainfall-runoff analysis plays a critical role in evaluating water availability in the water budget analysis. This study aimed to explore various continuous rainfall-runoff models over the Soyanggang dam watershed. Moreover, the ensemble modeling framework combining multiple models was introduced to present scenarios on streamflow considering uncertainties. In the ensemble modeling framework, rainfall-runoff models with fewer parameters are generally preferred for effective regionalization. In this study, more than 40 continuous rainfall-runoff models were applied to the Soyanggang dam watershed, and nine rainfall-runoff models were primarily selected using different goodness-of-fit measures. This study confirmed that the ensemble model showed better performance than the individual model over different flow regimes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.128-130
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• 2021

This study aims to implement a Regression Analysis system for predicting the appropriate production of flatfish. Due to Korea's signing of FTAs with countries around the world and accelerating market opening, Korean flatfish farming businesses are experiencing many difficulties due to the specificity and uncertainty of the environment. In addition, there is a need for a solution to problems such as sluggish consumption and price drop due to the recent surge in imported seafood such as salmon and yellowtail and changes in people's dietary habits. in this study, Using the python module, xlwings, it was used to obtain for the production amount of flatfish and to predict the amount of flatfish to be produced later. was used to predict the amount of flatfish to be produced in the future. Therefore, based on the analysis results of this prediction of flatfish production, the flatfish aquaculture industry will be able to come up with a plan to achieve an appropriate production volume and control supply and demand, which will reduce unnecessary economic loss and promote new value creation based on data. In addition, through the data approach attempted in this study, various analysis techniques such as artificial neural networks and multiple regression analysis can be used in future research in various fields, which will become the foundation of basic data that can effectively analyze and utilize big data in various industries.

• Knowledge Management Research
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• v.24 no.3
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• pp.217-237
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• 2023

Recently, in the face of successive and unexpected global economic risks, ESG(Environmental, Social, and Governance) management has risen as an essential survival strategy for businesses. Particularly, the supply chain disruptions due to the COVID-19 pandemic have added to the uncertainty of risks, heightening the importance of ESG management in the distribution industry. In this context, the role of blockchain technology in strengthening and managing the connection between the distribution industry and ESG management has become increasingly significant. While there have been extensive proposals for business models that integrate blockchain technology into distribution, few studies have specifically focused on the feasibility and effectiveness of applying blockchain to ESG management in this field. Therefore, this study analyzed the relationship between blockchain and ESG management in the distribution industry by employing association analysis, a text mining technique, on Korean academic research. Through this, the study confirmed the possibility of implementing blockchain in the distribution industry's ESG management and presented keywords to guide future research directions. The findings obtained from this study are expected to be utilized as foundational research for future studies in constructing blockchain-based business models for ESG management in the distribution industry.