• Journal of Industrial Convergence
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• v.21 no.5
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• pp.43-50
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• 2023

The South Korean government announced its plan to pursue membership in the CPTPP in 2022, aiming to establish a stable supply chain within the Asia-Pacific region. The CPTPP, led by Japan, was ratified in 2018 by 11 countries with the goal of eliminating tariffs and establishing new trade rules. According to our analysis, since the implementation of the CPTPP, there has been a trade promotion effect among Japan and member countries, with greater effects observed in countries with higher GDP per capita and closer geographical distance. As long as tariff elimination and reduction proceed as planned, the trade promotion effects are expected to expand gradually. However, the expansion of trade between Japan and CPTPP member countries may also indicate a relative contraction in trade with non-member countries, potentially posing a threat to the stable supply chain in the Korean industry within the Asia-Pacific region. As Japan is Korea's fourth-largest trading partner, it is necessary to carefully consider the impact of CPTPP on Japan's future trade with member countries and engage in discussions regarding Korea's participation and negotiation content based on a thorough examination of the matter.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.55-62
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• 2009

This paper proposes a decision method of fuzzy weights by utilizing degrees of contribution in order to classify insect footprint patterns having difficulties to classify species clearly. Insect footprints revealed delicately in the form of scattered spots since they are very small. Therefore it is not easy to define shape of footprints unlike other species, and there are lots of noises in the footprint patterns so that it is difficult to distinguish those from correct data. For these reasons, the extracted feature set has obvious feature values with some uncertain feature values, so we estimate weights according to degrees of contribution. If the one of feature values has distinct difference enough to decide a class among other classes, high weight is assigned to make classification. A calculated weight determines the membership values by fuzzy functions and objects are classified into the class having a superior value.atu present experimental resultseighrontribution. Iinsect footprints with noises by the proposed method.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.247-252
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• 2021

The quality growth of online education triggered by remote education platforms such as Coursera and edX has increased the demand for lifelong education through online platforms. In response, South Korea has also created various lifelong education support systems and sites in government agencies and local governments. Each support system and web sites created its own member information collection system. The systematic collection and utilization of learners' information requires an integrated member management system of each system. Therefore, the current status of member information collection of state-level lifelong education support systems was analyzed. Based on this, it distinguishes between member information that systems collect in common and information that they collect separately. It will help to bridge the items underlying the integrated membership framework.

• Journal of Arbitration Studies
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• v.33 no.2
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• pp.53-83
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• 2023

The investment agreement prepared at the beginning of inter-Korean economic cooperation in 2000 can be evaluated as very ineffective as a product of mutual political and diplomatic compromise rather than an effective protection for our investment assets. South Korean companies suffered a lot of losses due to the freezing of assets in the Geumgang mountain district and the closure of the Kaeseung Industrial Complex, but they did not receive practical damage relief due to institutional vulnerabilities. Currently, North Korea is under international economic sanctions of the UN Security Council, so it is true that the resumption of inter-Korean economic cooperation is far away, but North Korea's human resources and geographical location are still attractive investment destinations for us. Therefore, if strained relations between the two Koreas recover in the future and international economic sanctions on North Korea are eased, Korean companies' investment in North Korea will resume. However, the previous inter-Korean investment agreement system was a fictional systemthat was ineffective. Therefore, if these safety devices are not reorganized when economic cooperation resumes, unfair damage to Korean companies will be repeated again. The core of the improved investment guarantee system is not a bilateral system between the two Koreas, but the establishment of a multilateral system through North Korea's inclusion in the international economy. Specifically, it includes encouraging North Korea to join international agreements for the execution of arbitration decisions, securing subrogation rights through membership of international insurance groups such as MIGA, creating matching funds by international financial organizations. Through this new approach, it will be possible to improve the safety of Korean companies' investment in North Korea, and ultimately, it will be necessary to lay the foundation for mutual development through economic cooperation between the two Koreas.

• The Journal of Bigdata
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• v.7 no.2
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• pp.195-204
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• 2022

The tourism industry is facing a crisis due to the recent COVID-19 pandemic, and it is vital to improving profitability to overcome it. In situations such as COVID-19, it would be more efficient to sell additional products other than guest rooms to customers who have visited to increase the unit price rather than adopting an aggressive sales strategy to increase room occupancy to increase profits. Previous tourism studies have used machine learning techniques for demand forecasting, but there have been few studies on cross-selling forecasting. Also, in a broader sense, a resort is the same accommodation industry as a hotel. However, there is no study specialized in the resort industry, which is operated based on a membership system and has facilities suitable for lodging and cooking. Therefore, in this study, we propose a cross-selling prediction model using various machine learning techniques with an actual resort company's accommodation data. In addition, by applying the explainable artificial intelligence XAI(eXplainable AI) technique, we intend to interpret what factors affect cross-selling and confirm how they affect cross-selling through empirical analysis.

• Journal of the Korea Institute of Building Construction
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• v.23 no.1
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• pp.103-111
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• 2023

Accurate cost estimation in the early stages of a construction project is critical to the successful execution of the project. In this study, an ANFIS model was presented to predict construction costs in the early stages of a construction project. To increase the usability of the model, open construction cost data was used, and a model using limited information in the early stage of the project was presented. We analyzed existing studies related to ANFIS to identify recent trends, and after reviewing the basic structure of ANFIS, presented an ANFIS model for predicting conceptual construction costs. The variation in prediction performance depending on the type and number of membership functions of the ANFIS model was analyzed, the model with the best performance was presented, and the prediction accuracy of representative machine learning models was compared and analyzed. Through comparing the ANFIS model with other machine learning models, it was found to show equal or better performance, and it is concluded that it can be applied to predicting construction costs in the early stage of a project.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.573-580
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• 2006

The Saturation headway is a major parameter in estimating the intersection capacity and setting the signal timing. But Existing algorithms are still far from being robust in dealing with factors related to the variation of saturation headways at signalized intersections. So this study apply the fuzzy inference system using ANFIS. The ANFIS provides a method for the fuzzy modeling procedure to learn information about a data set, in order to compute the membership function parameters that best allow the associated fuzzy inference system to track the given input/output data. The climate conditions and the degree of brightness were chosen as the input variables when the rate of heavy vehicles is 10-25 %. These factors have the uncertain nature in quantification, which is the reason why these are chosen as the fuzzy variables. A neuro-fuzzy inference model to estimate saturation headways at signalized intersections was constructed in this study. Evaluating the model using the statistics of $R^2$, MAE and MSE, it was shown that the explainability of the model was very high, the values of the statistics being 0.993, 0.0289, 0.0173 respectively.

• Plant Breeding and Biotechnology
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• v.7 no.3
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• pp.186-199
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• 2019

We selected 68 Chinese maize inbred lines to understand the genetic diversity, population structure, and marker-trait associations for eight agronomic traits and 50 simple sequence repeats (SSRs) markers. In this study, effective traits, such as days of anthesis (DA), days of silking (DS), ear height (EH), plant to ear height ratio (ER), plant height (PH), and leaf width (LW) were divided into PC1 and PC2 by PCA analysis for maize inbred lines. Genetic diversity analysis revealed a total of 506 alleles at 50 SSR loci. The mean number of alleles per locus was 10.12. The averages of genetic diversity (GD) and polymorphic information content (PIC) values were 0.771 and 0.743, respectively. Based on a membership probability threshold of 0.80, the population structure revealed that the total inbred lines were divided into three major groups with one admixed group. A marker-trait association using Q + K MLM showed that nine SSR markers (bnlg1017, umc2041, umc2400, bnlg105, umc1229, umc1250, umc1066, umc2092, and umc1426) were related with seven agronomic traits. Among these SSR markers, eight SSR markers were associated with only one agronomic trait (DA, DS, ER, LL, LW, PH, and ST), whereas one SSR marker (umc1229) was associated with two agronomic traits (DA and ST). These results will help in optimizing the choice of inbred lines for cross combinations, as well as in selecting markers for further maize breeding programs.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.304-311
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• 2022

Construction inspection is a crucial stage that ensures that all contractual requirements of a construction project are verified. The construction inspection capabilities among state highway agencies have been greatly affected due to budget reduction. As a result, efficient inspection practices such as risk-based inspection are required to optimize the use of limited resources without compromising inspection quality. Automated prioritization of textual requirements according to their criticality would be extremely helpful since contractual requirements are typically presented in an unstructured natural language in voluminous text documents. The current study introduces a novel model for predicting the risk level of requirements using machine learning (ML) algorithms. The ML algorithms tested in this study included naïve Bayes, support vector machines, logistic regression, and random forest. The training data includes sequences of requirement texts which were labeled with risk levels (such as very low, low, medium, high, very high) using the fuzzy logic systems. The fuzzy model treats the three risk factors (severity, probability, detectability) as fuzzy input variables, and implements the fuzzy inference rules to determine the labels of requirements. The performance of the model was examined on labeled dataset created by fuzzy inference rules and three different membership functions. The developed requirement risk prediction model yielded a precision, recall, and f-score of 78.18%, 77.75%, and 75.82%, respectively. The proposed model is expected to provide construction inspectors with a means for the automated prioritization of voluminous requirements by their importance, thus help to maximize the effectiveness of inspection activities under resource constraints.

• Asia Marketing Journal
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• v.15 no.4
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• pp.223-241
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• 2014

In May 2012, the collaboration of Hana Bank, top financial service company, and SK Planet, top telecommunication service provider, introduced a new credit card that was filled with all-in-one benefits into the market. Leveraging strong infrastructure of two companies, each top in its own industries, the awareness and preference of 'Club SK Card' brand rapidly increased to about 25% in less than one year. Moreover, this new card was enthroned in the most sold credit card of year 2012, accounting for a market share of 7.2% in the credit card market and more than 80% in the mobile credit card market. To make these results possible, 'Club SK Card' marketing team developed an effective marketing communication strategy which followed the 6M model. The mission of the marketing communication strategy was simple and clear. It was to deliver the card's inherent strengths on consumer benefits that come from the support of subsidiary and affiliated companies of SK Planet. According to OK Cashbag data, the marketing communication team selected the appropriate target consumers and approached them directly, inducing actual purchase behavior. The target consumers received straightforward messages about 'Club SK Card' and were led to join in the new membership at their most frequently visited supermarket or franchise restaurant. The straightforward communication message embedded in an eye-catching commercial ad with a hook song accompanied with a dance was delivered via public media. The ad became so popular that many other television programs quoted or made parodies of the ad. Courtesy of the commercial ad, the brand name disseminated rapidly and widely among the public. In October 2012, an ingenious planning and persistent implementation of the communication strategy results 'Club SK Card' to be ranked top in brand awareness as well as advertising preference tests.