• The Journal of Bigdata
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• v.3 no.2
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• pp.19-33
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• 2018

Owing to the increase of FTA, food trade, and versatile preferences of consumers, food import has increased at tremendous rate every year. While the inspection check of imported food accounts for about 20% of the total food import, the budget and manpower necessary for the government's import inspection control is reaching its limit. The sudden import food accidents can cause enormous social and economic losses. Therefore, predictive system to forecast the compliance of food import with its preemptive measures will greatly improve the efficiency and effectiveness of import safety control management. There has already been a huge data accumulated from the past. The processed foods account for 75% of the total food import in the import food sector. The analysis of big data and the application of analytical techniques are also used to extract meaningful information from a large amount of data. Unfortunately, not many studies have been done regarding analyzing the import food and its implication with understanding the big data of food import. In this context, this study applied a variety of classification algorithms in the field of machine learning and suggested a data preprocessing method through the generation of new derivative variables to improve the accuracy of the model. In addition, the present study compared the performance of the predictive classification algorithms with the general base classifier. The Gaussian Naïve Bayes prediction model among various base classifiers showed the best performance to detect and predict the nonconformity of imported food. In the future, it is expected that the application of the abnormality detection model using the Gaussian Naïve Bayes. The predictive model will reduce the burdens of the inspection of import food and increase the non-conformity rate, which will have a great effect on the efficiency of the food import safety control and the speed of import customs clearance.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.1
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• pp.68-75
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• 2019

This study aims to look at the application methods of landscape architecture in response to the 4th Industrial Revolution. The results of the analysis of trends in the 4th Industrial Revolution and the subsequent search for application methods to the field of landscape architecture are as follows. First, the 4th Industrial Revolution means innovative change based on digital technology and seeks to create value based on intelligent information technology, and continuous growth is being made through innovation. This requires expertise to collect large amounts of information and creatively rework it, and a strategy to flexibly cope with changes in the times. Second, the status of technological use in response to the 4th Industrial Revolution in the field of landscape architecture is generalizing the establishment of precise analysis results such as survey technology and global mapping using drones, three-dimensional design simulation, and VR. In the field of traditional landscape architecture, efforts are made to obtain accurate fact-finding data on landscape site components. Third, the application methods in the field of landscape science according to the 4th Industrial Revolution in the future are required to supply precision technology and supply programs in the technology sector, and to provide a shared platform. In addition, a systemically standardized process will need to be established for this. In addition, educational efforts should be continued to professional manpower training and provide economic support for the development of technologies.

• Journal of Korea Trade
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• v.25 no.5
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• pp.39-57
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• 2021

Purpose - This research uses ocean marine insurance (OMI) statistics, international emails, focus-group interviews, and surveys to fill the gap between the theory of behavioral insurance, particularly status quo bias (SQB), and the practice of OMI in Korea. The contractual forms of OMI, the oldest and most globalized form of commercial insurance, were developed in the UK as the Institute Cargo Clauses in 1906 and revised in 1963, 1982, and 2009. SQB has been academically explored, mostly in health insurance and the financial services sector, but never in OMI. Thanks to the availability of OMI statistics in Korea, we can conduct SQB research here for the first time in this field. Design/methodology - We show the existence of SQB in the OMI of Korea through Korean statistics between 2009 and 2018, email correspondence with experts in the UK, Germany, and Japan, focus-group interviews with Korean OMI underwriters, an in-depth interview with one underwriter, and a survey of 15 OMI insureds (company representatives). Findings - We find that Korean foreign traders rely on the old-type OMI contracts developed in 1963, whereas other industrialized countries use the newest type of OMI contract developed in 2009. With a simple loss ratio analysis during 2009-2018, we show that the behavior of insurers has little to do with rational profit maximization and is instead driven by irrational bias, as they forgo the more profitable contracts provided by the new clauses by keeping the old clauses. The consistent addiction to old types of contracts in the OMI market suggests strong SQB among Korean exporters, importers, bankers, or insurers, which we confirmed in our interviews and survey. Originality/value - This research has significant originality and academic value because it reports new findings with crucial implications for the development of efficient trade practices and policy. First, this research is based on actual statistics that have not been used in previous Korean research on OMI. Second, this research shows that all-risk OMI policies provide more value to insureds, in terms of coverage given premium, than partial coverage policies, which differs from arguments previously made in Korea. Third, this research reveals strong SQB in Korea, where foreign trade plays a pivotal role in economic growth. That bias could be attributable to uninformed traders, informed but idle insurers, or conservative bankers. Fourth, to further develop foreign trade, policy initiatives are needed to review the current practices of OMI contracts and move forward with the new contract forms. All of these findings and arguments are both new and important.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.603-613
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• 2021

As a core policy for achieving the goal of reducing greenhouse gas emissions in the building sector, Korea has enforced the mandatory certification of zero energy buildings for new public buildings from 2020. This study suggests energy-saving technologies and economic factors that building officials can refer to for decision-making on the implementation of zero energy buildings. For this study, the construction cost for the energy item of a building was analyzed by collecting the building energy efficiency level certification data and detailed construction cost statement data from public institutions for the last three years. Based on the building energy efficiency certification data, each energy item of the baseline building was derived, and the energy performance of the zero energy building was derived through repetitive simulations by gradually increasing the energy performance value of the baseline building. By applying the analyzed construction cost, the construction cost for each energy item of the baseline and zero energy buildings was derived. As a result, the lighting equipment contributed up to 10.5% energy savings, and the increase in construction cost of the cooling and heating system was at least 9.1%.

• Journal of the Korean Institute of Gas
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• v.24 no.6
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• pp.34-46
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• 2020

In order to supply stable natural gas in the future, it is necessary to forecast the demand in advance and secure the quantity of supply. In this paper, we propose a method of estimating the demand function of industrial natural gas, which is the core of the increase of domestic natural gas demand in the future. The cross-sectional data of 304 domestic industries were used to estimate the demand function of the industrial natural gas, and the effect of industry specific characteristics such as capital investment, manufacturing cost. Finally, the least absolute deviation estimation method which is robust to outliers and does not assume the homogeneity of the error term and the normality, And the results were derived. In addition, the economic value of industrial city gas was estimated using the price elasticity of industrial city gas. Therefore, it can be seen that the continuous expansion and supply of city gas to the industrial sector is beneficial at the national level, and the government needs to promote expansion through the industrial city gas support policy.

• Clean Technology
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• v.28 no.1
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• pp.9-17
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• 2022

Electrochemical carbon dioxide (CO₂) reduction technology, one of the promising solutions for climate change, can convert CO₂, a representative greenhouse gas (GHG), into valuable base chemicals using electric energy. In particular, carbon monoxide (CO), among various candidate products, is attracting much attention from both academia and industry because of its high Faraday efficiency, promising economic feasibility, and relatively large market size. Although numerous previous studies have recently analyzed the GHG reduction potential of this technology, the assumptions made and inventory data used are neither consistent nor transparent. In this study, a comparative life cycle assessment was carried out to analyze the potential for reducing GHG emissions in the electrochemical CO production process in a more transparent way. By defining three different system boundaries, the global warming impact was compared with that of a fossil fuel-based CO production process. The results confirmed that the emission factor of electric energy supplied to CO₂-electrolyzers should be much lower than that of the current national power generation sector in order to mitigate GHG emissions by replacing conventional CO production with electrochemical CO production. Also, it is important to disclose transparently inventory data of the conventional CO production process for a more reliable analysis of GHG reduction potential.

• Analyses & Alternatives
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• v.5 no.2
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• pp.77-105
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• 2021

Natural gas consumption in Asia is growing at fast tempo because of various factors such as economic growth in the region, urbanization, coal-to-gas switch at power and industry sector. Due to geographical characteristics and lack of international pipeline connections between countries in the continent, majority of natural gas exported to Asian consumers is transported by tankers on the sea in the form of liquefied natural gas. As Asian market is the most lucrative market with the fastest demand growth, the competitions between LNG sellers for market share in Asian market are strengthening. The competitions accelerated, especially after the introduction of large volume of incremental supply into the market by new exporters from the U.S., Australia, and Russia. Cheniere Energy, the first exporter of liquefied natural gas (LNG) in the lower 48 states of U.S. has not adopted the traditional price formation mechanism and business model. Traditionally, prices of long-term LNG contracts have been indexed to the price of competing fuels, such as crude oil. The company adopted a pricing mechanism and business model based on a cost-plus system. Cheniere Energy opted for the safer and the risk-free pricing system, that annually guarantees a fixed amount of revenue to the seller. The company earns the same amount of money, regardless of natural gas price dynamics in the domestic and international market, but possibly with less revenue. However, by introducing and successfully implementing the safer and risk- free business model, Cheniere Energy, a company of a relatively smaller size in comparison with major oil and gas companies, became an example to other smaller-sized companies in the U.S. The company's business model demonstrated how to enter and operate LNG business amid increasing competitions among sellers in the U.S. and international market.

• Journal of the Korean Wood Science and Technology
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• v.49 no.3
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• pp.234-253
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• 2021

The Quercus mongolica has a high utilization value in industrial economic sector. The species is distributed throughout Korea, however, the damage caused by deterioration such as discoloration and decay is severe. For this reason, the deterioration of Q. mongolica is an obstacle to its use as wood, but research on deterioration factors is insufficient. In this study, we focused on fungi as a factor influencing the deterioration of Q. mongolica, and isolated and identified the fungi from the deteriorated Q. mongolica. In additions, in order to confirm whether the identified fungi actually affects wood deterioration, enzyme activities of the identified fungi were evaluated and related mass loss of wood treated with the fungi was measured by wood decay test. As a result of sequencing analysis using the ITS region of the genomic DNA of the fungi isolated from Q. mongolica, Mucor circinelloides, Cunninghamella elegans, and Umbelopsis isabellina 3 species belonging to Mucoromycota phylum, and Ophiostoma piceae and Aureobasidium melanogenum 2 species belonging to Ascomycota phylum were identified. These five fungi had enzyme (i.e. cellulase, laccase) activities related to wood decay and reduced the mass of heartwood and sapwood of Q. mongolica in practice. In particular, O. piceae and A. melanogenum, which have both cellulase and laccase activities, showed 6.9% and 1.5% mass loss, respectively. These results indicated that five fungi identified in this study influence the deterioration of Q. mongolica and are wood decaying fungi for Q. mongolica potentially.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.71-82
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• 2023

As an alternative to solving social problems, social economic actors are attracting attention as an important alternative. SPC is a private program that pays incentives according to the social performance measured by monetary value. This study measured efficiency by applying DEA to social enterprises that participated in the SPC program and analyzed the factors affecting efficiency through tobit regression. As a result of DEA analysis, it was found that 21% of social enterprises participating in SPC were efficient, but 66% needed to improve their efficiency. In the Tobit regression analysis, the efficiency was relatively low in the case of manufacturing sector, and when the square term of sales is included, the efficiency decreases as sales increase. Through this, it was estimated that external support is needed at a low level sales before crossing the critical point, and that the efficiency of social value creation increases when it grows above a certain level. Moreover, it is significant in that it combines the variables used in the analysis of traditional industrial efficiency while conducting efficiency analysis focusing on the social performance by monetary value, which is considered the most important achievement of social enterprises. It is believed that it will contribute to research related to the environment creation and the requirements of each field in creating social values for social enterprises in the future.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.587-602
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• 2023

Due to climate change, population growth, and economic development, the demand for water in the urban water system (UWS) and the energy required for water use constantly increase. Therefore, beyond the traditional method of considering only the water sector, the Nexus approach, which considers synergies and trade-offs between the water and energy sectors, has begun to draw attention. In previous researches, the Nexus methodology was used to demonstrate that the UWS is an energy-intensive system, analyze the water-energy efficiency relationship surrogated by energy intensity, and identify climate (long-term climate change, drought, type), geographic characteristics (topography, flat ratio, location), system characteristics (total supply water amount, population density, pipeline length), and operational management level (water network pressure, leakage rate, water saving) effects on the UWS. Through this, it was possible to suggest the direction of policies and institutions to UWS managers. However, there was a limit to establishing and implementing specific action plans. This study built the energy intensity matrix of the UWS, quantified the impact of city conditions, external influences, and operational management levels on the UWS using the water-energy Nexus model, and introduced water-energy efficiency criteria. With this, UWS managers will be able to derive strategies and action plans for efficient operation management of the UWS and evaluate suitability and validity after implementation.