• Korean Journal of Plant Resources
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• v.25 no.5
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• pp.624-632
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• 2012

As there have been lately many worldwide resource challenges such as potential exhaustion of fossil fuels, sudden rise of oil price and ever-rising grain pricing due to global food crisis, there have been more interests focused on recycling vegetable oils and fats into clean natural fuel and producing new resources based on waste cooking oil as a part of reusing waste resources. An Experiment was performed by using ratio of 50:50, 75:25 (w/w) mixture of based rapeseed oil, camellia oil, and olive oil. 50:50, 25:75 (w/w) mixture of based palm oil. The result was that the oleic acid ($C_{18:1}$) got the lowest percentage of 42.8%, when we combined the mixture of rapeseed oil and soybean oil. While the highest percentage of 72.1% was when the mixture of camellia oil and rapeseed oil were combined at 50:50 ratio. In 75:25 (w/w) case, mixture of rapeseed oil and soybean oil got the lowest. The highest ratio was the mixture of camellia oil and olive oil. Based on the component of palm oil, the total saturated fatty acid was decreased. It is expected that stabilizing oxidation through controlling of fatty acid after mixture and that liquidity at a low temperature. The acid value indicated that stabilizing oxidation got a range of highest to lowest. Camellia oil ranked as the highest, followed by olive oil, and the oil seeds as the lowest in rank. Controlling iodine value through mixture and improvement of stabilizing oxidation will provide a good quality. The quality of color has no significant change about mixture in ratio and maintenance. The reduction of the cost of refining process is expected by controling of mixture ratio at biodiesel production in the future.

• Journal of Climate Change Research
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• v.3 no.1
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• pp.71-88
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• 2012

The global warming is probably the most significant issue of concern all over the world and according to the report published by the Intergovernmental Panel on Climate Change (IPCC), the average temperature and extent of global warming around the globe have been on the rise and so have the uncertainty for the future. Such effects of global warming have adverse effects on basic foundation of the mankind in numerous ways and water resource is no exception. The researches on water resources assessment for climate change are significant enough to be used as the preliminary data for researches in other fields. In this research, a total of 124 peer-reviewed publications and 57 reports on the subject of research on climate change related to water resources, that has been carried out so far in Korea has been reviewed. The research on climate change in Korea (inclusive of the peer-reviewed articles and reports) has mainly focused on the future projection and assessment. In the fields of hydrometeorology tendency and projection, the analysis has been carried out with focus on surface water, flood, etc. for hydrological variables and precipitation, temperature, etc. for meteorological variables. This can be attributed to the large, seasonal deviation in the amount of rainfall and the difficulty of water resources management, which is why, the analysis and research have been carried out with focus on those variables such as precipitation, temperature, surface water, flood, etc. which are directly related to water resources. The future projection of water resources in Korea may differ from region to region; however, variables such as precipitation, temperature, surface water, etc. have shown a tendency for increase; especially, it has been shown that whereas the number of casualties due to flood or drought decreases, property damage has been shown to increase. Despite the fact that the intensity of rainfall, temperature, and discharge amount are anticipated to rise, appropriate measures to address such vulnerabilities in water resources or management of drainage area of future water resources have not been implemented as yet. Moreover, it has been found that the research results on climate change that have been carried out by different bodies in Korea diverge significantly, which goes to show that many inherent uncertainties exist in the various stage of researches. Regarding the strategy in response to climate change, the voluntary response by an individual or a corporate entity has been found to be inadequate owing to the low level of awareness by the citizens and the weak social infrastructure for responding to climate change. Further, legal or systematic measures such as the governmental campaign on the awareness of climate change or the policy to offer incentives for voluntary reduction of greenhouse gas emissions have been found to be insufficient. Lastly, there has been no case of any research whatsoever on the anticipated effects on the economy brought about by climate change, however, there are a few cases of on-going researches. In order to establish the strategy to prepare for and respond to the anticipated lack of water resources resulting from climate change, there is no doubt that a standardized analysis on the effects on the economy should be carried out first and foremost.

• Journal of Plant Biotechnology
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• v.46 no.3
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• pp.236-245
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• 2019

Fruit ripening is a genetically programmed process involving a number of biochemical and physiological processes assisted by variations in gene expression and enzyme activities. This process generally affects the phytochemical profile and the bioactive principles in fruits and vegetables. To appraise the variation in bioactive principles of fruits from Rosa rugosa during its ripening process, we analyzed the changes in antioxidant and anti-elastase activities and polyphenolic compounds during the four ripening stages of fruits. Overall, an extract of unripe fruits contained the highest levels of total phenolic and flavonoid contents, radical scavenging activity, reducing power, oxygen radical antioxidant capacity, and elastase inhibitory activity, compared with the extracts of fruits at other stages of ripening. Additionally, we found that the reduction of flavonoid content occurs because of decreased transcriptional levels of genes involved in flavonoid biosynthesis pathway during the ripening process. Based on HPLC analysis, we found that the extract of unripe fruits contained the highest amount of myricetin, caffeic acid, chlorogenic acid, syringic acid, and p-coumaric acid and suggested that the antioxidant and anti-elastase activities of the extract obtained from stage 1, should be mediated by the presence of these compounds. Additionally, we analyzed the interaction sites and patterns between these compounds and elastase using the structure-based molecular docking approach, and suggested that chlorogenic acid strongly interacted with elastase. Together, these findings suggest that the maturity of fruits has profound effects on the pharmaceutical value of R. rugosa.

• Journal of Life Science
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• v.29 no.2
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• pp.173-180
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• 2019

Amyloid ${\beta}$-protein ($A{\beta}$) is the principal component of senile plaques characteristic of Alzheimer's disease (AD) and elicits a toxic effect on neurons in vitro and in vivo. Many environmental factors, including antioxidants and proteoglycans, modify $A{\beta}$ toxicity. It is worthwhile to isolate novel natural compounds that could prove therapeutic for patients with AD without causing detrimental side effects. In this study, we investigated the in vitro neuroprotective effects of the ethyl acetate fraction of methanol extract of Ophiophogon japonicas (OJEA fraction). We used an MTT reduction assay to detect protective effects of the OJEA fraction on $A{\beta}_{25-35}$-induced cytotoxicity to PC12 cells. We also used a cell-based ${\beta}$-secretase assay system to investigate the inhibitory effect of the OJEA fraction on ${\beta}$-secretase activity. In addition, we performed an in vitro lipid peroxidation assay to evaluate the protective effect of the OJEA fraction against oxidative stress induced by $A{\beta}_{25-35}$ in PC12 cells. The OJEA fraction had strong protective effects against $A{\beta}_{25-35}$-induced cytotoxicity to PC12 cells and was strongly inhibitory to ${\beta}$-secretase activity, which resulted in the attenuation of $A{\beta}$ generation. In addition, the OJEA fraction significantly decreased malondialdehyde (MDA) content, which is induced by the exposure of PC12 cells to $A{\beta}_{25-35}$. Our results suggested that the OJEA fraction contained active compounds exhibiting a neuroprotective effect on $A{\beta}$ toxicity.

• Journal of Plant Biotechnology
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• v.49 no.3
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• pp.240-249
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• 2022

Measuring chlorophyll fluorescence (CF) is a useful tool for assessing a plant's ability to tolerate abiotic stresses such as drought, waterlogging and high temperature. Korean ginseng is highly sensitive to water stress in paddy fields. To evaluate the possibility of non-destructively diagnosing waterlogging stress using chlorophyll fluorescence (CF) imaging techniques, we screened 57 ginseng accessions for waterlogging tolerance. To evaluate waterlogging tolerance among the 2-year-old Korean ginseng accessions, we treated ginseng plants with water stress for 25 days. The physiological disorder rate was characterized through visual assessment (an assigned score of 0-5). The physiological disorder rates of Geumjin, Geumsun and GS00-58 were lower than that of other accessions. In contrast, lines GS97-62, GS97-69 and GS98-1-5 were deemed susceptible. Root traits, chlorophyll content and the reduction rates decreased in most ginseng accessions. Further, these metrics were significantly lower in susceptible genotypes compared to resistant ones. All CF parameters showed a positive or negative response to waterlogging stress, and this response continuously increased over the treatment time among the genotypes. The CF parameter Fv/Fm was used to screen the 57 accessions, and the results showed clear differences in Fv/Fm between the susceptible and resistant genotypes. Susceptible genotypes had an especially low Fv/Fm value of less than 0.8, reflecting damage to the reaction center of photosystem II. It is concluded that Fv/Fm can be used as a CF parameter index for screening waterlogging stress tolerance in ginseng genotypes.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.136-143
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• 2021

Pacific island countries, including Kiribati, are suffering from a shortage of essential resources as well as a reduction in their living space due to sea level rise and coastal erosion from climate change, groundwater pollution and vegetation changes. Global activities to solve these problems are being progressed by the UN's efforts to implement SDGs. Pacific island countries can adapt to climate change by using abundant marine resources. In other words, seawater plants can assist in achieving SDGs #2, #6 and #7 based on SDGs #14 in these Pacific island countries. Under the auspice of Korea International Cooperation Agency (KOICA), Korea Research Institute of Ships and Ocean Engineering (KRISO) established the Sustainable Seawater Utilization Academy (SSUA) in 2016, and its 30 graduates formed the SSUA Kiribati Association in 2017. The Ministry of Oceans and Fisheries (MOF) of the Republic of Korea awarded ODA fund to the Association. By taking advantage of seawater resource and related plants, it was able to provide drinking water and vegetables to the local community from 2018 to 2020. Among the various fields of education and practice provided by SSUA, the Association hope to realize hydroponic cultivation and seawater desalination as a self-support project through a pilot project. To this end, more than 140 households are benefiting from 3-stage hydroponics, and a seawater desalination system in connection with solar power generation was installed for operation. The Association grows and supplies vegetable seedlings from the provided seedling cultivation equipment, and is preparing to convert to self-support business from next year. The satisfaction survey shows that Tarawa residents have a high degree of satisfaction with the technical support and its benefits. In the future, it is hoped that SSUA and regional associations will be distributed to neighboring island countries to support their SDGs implementations.

• Resources Recycling
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• v.32 no.1
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• pp.50-59
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• 2023

The amount of dust generated during the dissolution of scrap in an electric arc furnace is approximately 1.5% of the scrap metal input, and it is primarily collected in a bag filter. Electric arc furnace dust primarily consists of zinc and ion. The processing of zinc starts with its conversion into pellet form by the addition of a carbon-based reducing agent(coke, anthracite) and limestone (C/S control). These pellets then undergo reduction, volatilization, and re-oxidation in rotary kiln or RHF reactor to recover crude zinc oxide (60%w/w). Next, iron is discharged from the electric arc furnace dust as a solid called Fe clinker (secondary by-product of the Fe-base). Several methods are then used to treat the Fe clinker, which vary depending on the country, including landfilling and recycling (e.g., subbase course material, aggregate for concrete, Fe-source for cement manufacturing). However, landfilling has several drawbacks, including environmental pollution due to leaching, high landfill costs, and wastage of iron resources. To improve Fe recovery in the clinker, we pulverized it into optimal -sized particles and employed specific gravity and magnetic force selection methods to isolate this metal. A carbon-based reducing agent and a binding material were added to the separated coarse powder (>10㎛) to prepare briquette clinker. A small amount (1-3%w/w) of the briquette clinker was charged with the scrap in an electric arc furnace to evaluate its feasibility as an additives (carbonaceous material, heat-generating material, and Fe source).

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.61-118
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• 2008

The purpose of this research is to construct research framework for international franchising based on existing literature and to identify research components in the framework. Franchise can be defined as management styles that allow franchisee use various management assets of franchisor in order to make or sell product or service. It can be divided into product distribution franchise that is designed to sell products and business format franchise that is designed for running it as business whatever its form is. International franchising can be defined as a way of internationalization of franchisor to foreign country by providing its business format or package to franchisee of host country. International franchising is growing fast for last four decades but academic research on this is quite limited. Especially in Korea, research about international franchising is carried out on by case study format with single case or empirical study format with survey based on domestic franchise theory. Therefore, this paper tries to review existing literature on international franchising research, providing research framework, and then stimulating new research on this field. International franchising research components include motives and environmental factors for decision of expanding to international franchising, entrance modes and development plan for international franchising, contracts and management strategy of international franchising, and various performance measures from different perspectives. First, motives of international franchising are fee collection from franchisee. Also it provides easier way to expanding to foreign country. The other motives including increase total sales volume, occupying better strategic position, getting quality resources, and improving efficiency. Environmental factors that facilitating international franchising encompasses economic condition, trend, and legal or political factors in host and/or home countries. In addition, control power and risk management capability of franchisor plays critical role in successful franchising contract. Final decision to enter foreign country via franchising is determined by numerous factors like history, size, growth, competitiveness, management system, bonding capability, industry characteristics of franchisor. After deciding to enter into foreign country, franchisor needs to set entrance modes of international franchising. Within contractual mode, there are master franchising and area developing franchising, licensing, direct franchising, and joint venture. Theories about entrance mode selection contain concepts of efficiency, knowledge-based approach, competence-based approach, agent theory, and governance cost. The next step after entrance decision is operation strategy. Operation strategy starts with selecting a target city and a target country for franchising. In order to finding, screening targets, franchisor needs to collect information about candidates. Critical information includes brand patent, commercial laws, regulations, market conditions, country risk, and industry analysis. After selecting a target city in target country, franchisor needs to select franchisee, in other word, partner. The first important criteria for selecting partners are financial credibility and capability, possession of real estate. And cultural similarity and knowledge about franchisor and/or home country are also recognized as critical criteria. The most important element in operating strategy is legal document between franchisor and franchisee with home and host countries. Terms and conditions in legal documents give objective information about characteristics of franchising agreement for academic research. Legal documents have definitions of terminology, territory and exclusivity, agreement of term, initial fee, continuing fees, clearing currency, and rights about sub-franchising. Also, legal documents could have terms about softer elements like training program and operation manual. And harder elements like law competent court and terms of expiration. Next element in operating strategy is about product and service. Especially for business format franchising, product/service deliverable, benefit communicators, system identifiers (architectural features), and format facilitators are listed for product/service strategic elements. Another important decision on product/service is standardization vs. customization. The rationale behind standardization is cost reduction, efficiency, consistency, image congruence, brand awareness, and competitiveness on price. Also standardization enables large scale R&D and innovative change in management style. Another element in operating strategy is control management. The simple way to control franchise contract is relying on legal terms, contractual control system. There are other control systems, administrative control system and ethical control system. Contractual control system is a coercive source of power, but franchisor usually doesn't want to use legal power since it doesn't help to build up positive relationship. Instead, self-regulation is widely used. Administrative control system uses control mechanism from ordinary work relationship. Its main component is supporting activities to franchisee and communication method. For example, franchisor provides advertising, training, manual, and delivery, then franchisee follows franchisor's direction. Another component is building franchisor's brand power. The last research element is performance factor of international franchising. Performance elements can be divided into franchisor's performance and franchisee's performance. The conceptual performance measures of franchisor are simple but not easy to obtain objectively. They are profit, sale, cost, experience, and brand power. The performance measures of franchisee are mostly about benefits of host country. They contain small business development, promotion of employment, introduction of new business model, and level up technology status. There are indirect benefits, like increase of tax, refinement of corporate citizenship, regional economic clustering, and improvement of international balance. In addition to those, host country gets socio-cultural change other than economic effects. It includes demographic change, social trend, customer value change, social communication, and social globalization. Sometimes it is called as westernization or McDonaldization of society. In addition, the paper reviews on theories that have been frequently applied to international franchising research, such as agent theory, resource-based view, transaction cost theory, organizational learning theory, and international expansion theories. Resource based theory is used in strategic decision based on resources, like decision about entrance and cooperation depending on resources of franchisee and franchisor. Transaction cost theory can be applied in determination of mutual trust or satisfaction of franchising players. Agent theory tries to explain strategic decision for reducing problem caused by utilizing agent, for example research on control system in franchising agreements. Organizational Learning theory is relatively new in franchising research. It assumes organization tries to maximize performance and learning of organization. In addition, Internalization theory advocates strategic decision of direct investment for removing inefficiency of market transaction and is applied in research on terms of contract. And oligopolistic competition theory is used to explain various entry modes for international expansion. Competency theory support strategic decision of utilizing key competitive advantage. Furthermore, research methodologies including qualitative and quantitative methodologies are suggested for more rigorous international franchising research. Quantitative research needs more real data other than survey data which is usually respondent's judgment. In order to verify theory more rigorously, research based on real data is essential. However, real quantitative data is quite hard to get. The qualitative research other than single case study is also highly recommended. Since international franchising has limited number of applications, scientific research based on grounded theory and ethnography study can be used. Scientific case study is differentiated with single case study on its data collection method and analysis method. The key concept is triangulation in measurement, logical coding and comparison. Finally, it provides overall research direction for international franchising after summarizing research trend in Korea. International franchising research in Korea has two different types, one is for studying Korean franchisor going overseas and the other is for Korean franchisee of foreign franchisor. Among research on Korean franchisor, two common patterns are observed. First of all, they usually deal with success story of one franchisor. The other common pattern is that they focus on same industry and country. Therefore, international franchise research needs to extend their focus to broader subjects with scientific research methodology as well as development of new theory.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.