• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.1
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• pp.70-77
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• 2001

This paper present a fuzzy mxlel of describing reacton features for ozon contactor in advanced water treatn-ent systems. Input and output variables are chosen by considenng the object of ozon processing and several parameters related to management of water quahty. Dissolved organic carbon concentration, $UV_{254}$ absorptIon and $KM_NO_4$ consumption are proposed as common variables in input and outp.lt variables. Furthermore own concentration, raw water's temperature and contact time are suggested as input variables, Membership hmctions for input variables have triangular type share and the grades in each lrembership function are determined by investigating process data gathered at pilot planl The decision parts of fuzzy model have linear combination form of input variables and coefficients included in such linear equations are computedd with process clata in the sense of least square error Also fuzzy trodel suggested in this paper is partitioned by 3 independent fuzzy rnxlels using the characteristics of having no interactions armng output variables. As a result, such fuzzy mxlel has rrerits in computation and comprehension. According to simulatIon results, fuzzy moIel's outputs give almost similar data to process output under same input conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.689-694
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• 2009

In this paper an approach to building fuzzy models for predicting daily and weekly stock prices is presented. Predicting stock prices with traditional time series analysis has proven to be difficult. Fuzzy logic based models have advantage of expressing the input-output relation linguistically, which facilitates the understanding of the system behavior. In building a stock prediction model we bear a burden of selecting most effective indicators for the stock prediction. In this paper information used in traditional candle stick-chart analysis is considered as input variables of our fuzzy models. The fuzzy rules have the premises and the consequents composed of trapezoidal membership functions and nonlinear equations, respectively. DE(Differential Evolution) identifies optimal fuzzy rules through an evolutionary process. The fuzzy models to predict daily and weekly open, high, low, and close prices of KOSPI(KOrea composite Stock Price Index) are built, and their performances are demonstrated.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.736-741
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• 2006

The design of a classification system generally involves data acquisition module, learning module and decision module, considering their functions and it is often an important component of intelligent systems. The learning module provides a priori information and it has been playing a key role for the classification. The conventional learning techniques for classification are based on a winner take all fashion which does not reflect the description of real data where boundarues might be fuzzy Moreover they need all data for the learning of its problem domain. Generally, in many practical applications, it is not possible to prepare them at a time. In this paper, we design an adaptive classification model using incremental training fuzzy neural networks, FNN-I. To have a more useful information, it introduces the representation and membership degree by fuzzy theory. And it provides an incremental learning algorithm for continuously gathered data. We present tie experimental results on computer virus data. They show that the proposed system can learn incrementally and classify new viruses effectively.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.298-305
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• 2018

This paper explored the impact of adaptive efforts for the 4th Industrial Revolution(hereafter, 4IR) on social cohesion at national level. To examine this relationship, Latent Growth Model was applied to thirty one OECD membership countries, 2006-2015. Adaptive efforts for 4IR was measured by the 4IR Relative Readiness(WEF, 2016) and social cohesion was measured by Corruption Perception Index(Transparency International) and trust on politicians(WEF). Results showed that corruption perception significantly decreased by the 4IR Relative Readiness and legal protection(judiciary independency and corporate ethics) and trust on politicians significantly increased by judiciary independency. These results imply that public and corporate efforts for the 4IR does not necessarily have negative impact on social cohesion as long as legal protection such as judiciary independency and corporate ethics are equally pursuit at national level.

• Health Policy and Management
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• v.28 no.4
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• pp.369-377
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• 2018

Background: Catastrophic health expenditure (CHE) occurs when medical expenditure of a household passes over a certain ratio of household income. This research studied the effect of gender on CHE based on Korea Health Panel data. Methods: This study implemented binary logistic regression model to figure out whether gender affects CHE and how different gender groups show pattern of CHE process. With gender, age, marital status, income level, economic activity, membership of private insurance, existence of chronic disease, and self-rated health were included in the model. Results: Results showed that females faced CHE 1.5 times more than males (odds ratio, 1.241). Also, main determinants of CHE in female groups were marital status, while age and economic activity status were significant in male groups. Subgroup analysis displayed that married female under 35 years old are located in intersectionality of CHE including pregnancy and delivery, multiple health risk behaviors, mental stress, and relatively vulnerable social status due to lower income. Meanwhile, both gender above 50 years old faced remarkably high chance of CHE, which seems to be caused by complex health risk behaviors and chronic diseases. Conclusion: Such results implied not only that gender is an important determinant of CHE, but also other determinants of CHE differ according to gender, which suggests a necessity of gender-based CHE support and rescue policy.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.59-68
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• 2020

This study aims to present the direction of fostering creative and innovative future design personnel required by companies according to the trend of the times. Changes in design manpower policy and industry, academia, and government cases are examined through policy case studies. Through analysis of industry-academia project cases, we discovered that a new educational model is needed to experience the process of developing products that can be commercialized. This study is expected to be used as basic data for policy development related to program development to foster creative and innovative talents required in the design industry.

• Journal of Information Technology Services
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• v.21 no.2
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• pp.1-26
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• 2022

This study classified five types of online food subscription economy: replenishment, curation, surprise, membership, and visitation. An online survey was conducted with 314 customers who experienced 5 types of online subscription economy. This study selected the characteristics of the food subscription economy as convenience, perceived personalization, economic utility, and timeliness through previous studies. The effect of the four characteristics on perceived value (utilitarian and emotional) and the relationship between customer engagement and perceived value, which are dependent variables that have never been used in the food subscription economy, were verified through the S-O-R model. In this relationship, we demonstrated how consumers' personal tendencies, such as need for cognitive closure and self-efficacy, mediate between timeliness and perceived value related to online food delivery. The study results are as follows. Perceived personalization, convenience, and timeliness had a positive effect on the utilitarian value in the order. It also had a positive effect on emotional values in the order of perceived personalization and timeliness. On the other hand, economic utility had no significant effect on practical branches. Customer engagement had a positive effect in the order of emotional value and utilitarian value. The lower the need for cognitive closure the more positive the utilitarian value. The lower the self-efficacy, the more positive the emotional value was perceived. Through the above study, companies that want to operate or start an online food subscription economy need a strategic approach rather than unreasonable price discounts in pricing policy. In addition, it is necessary to focus on marketing activities that provide emotional value by focusing on perceived personalization, which is the satisfaction factor of online food subscription.

• Journal of Korea Trade
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• v.27 no.3
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• pp.161-178
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• 2023

Purpose - purpose of this paper is to analyze the effects of the investment facilitation levels of 11 RCEP countries (excluding Myanmar, Brunei, and Laos due to lack of data) on China's outward foreign direct investments(OFDI) using balanced panel data from 2010 to 2019. Design/methodology - First, four investment facilitation measurement indicators (regulatory environment, infrastructure, financial market, ease of doing business) were selected,investment facilitation scores of the 11 countries were obtained using the principal component analysis, an investment gravity model was established with nine explanatory variables (investment facilitation level, market size, population, geographic distance, degree of opening, tax level, natural resources, whether the country is an APEC member or not, and whether a valid bilateral investment treaty with China has been concluded) were used to establish an investment gravity model, and regression analyses were conducted with OLS and system GMM. Findings - The results of the regression analyses showed that investment facilitation levels had the greatest effect on China's OFDI, all four first-level indicators had positive effects on China's OFDI, and among them, the institutional environment had the greatest effect. In addition, it was shown that explanatory variables such as market size, population, geographical distance, degree of openness, natural resources, and whether or not a valid bilateral investment treaty has been concluded would have positive effects on China's OFDI, while tax levels and APEC membership would impede China's OFDI to some extent. Originality/value - Since the Regional Comprehensive Economic Partnership (RCEPT) came into effect not long ago, there are not so many studies on the effects of investment facilitation levels of RCEP member states on China's OFDI, and the investment facilitation measurement index constructed in this paper is relatively systematic and scientific because it includes all the contents of investment facilitation related to the life cycle of company's foreign direct investments.

• 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.

• 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.