• Journal of Environmental Health Sciences
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• v.49 no.5
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• pp.262-274
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• 2023

Background: Exposure levels for heavy metals such as lead (Pb), mercury (Hg), and cadmium (Cd) have increased due to human activities. They are known to be a public health concern. Objectives: This study aimed to determine the exposure levels to heavy metals in the blood and urine of South Korean adults and to present the contribution rate of exposure pathways using an exposure algorithm for men aged 19~64, women aged 19~64, and all seniors aged 65 or older. Methods: We analyzed data from the Korean National Environmental Health Survey (KoNEHS) Cycle 4 (2018~2020). A total of 2,646 participants aged ≥19 years were included. Multiple regression analysis was performed to determine the factors affecting heavy metal concentrations. The contribution rate was calculated by applying three exposure algorithms for ingestion, inhalation, and dermal exposure. Results: Factors that commonly affect heavy metal concentrations in blood and urine were gender and age. The main influencing factors for Pb and Cd were education level and smoking status, while frequency of fish consumption and of alcohol consumption were indicated to be the main influencing factors for mercury. The contribution rates of lead and cadmium from food ingestion were 78.03~79.62% and 88.39~92.89%, respectively. Additionally, the highest contribution for mercury was accounted for by food at 81.69~85.77%. As a result of the risk assessment, cadmium was found to pose a potential health risk a with total cancer risk (TCR) of more than 1×10^-6. Conclusions: The KoNEHS could be an important study for determining the level of exposure to heavy metals and their influencing factors. Integrated exposure to heavy metals could assess the main exposure pathways, and this methodology could be applied to exposure management of heavy metals.

• Korea Trade Review
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• v.48 no.3
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• pp.1-22
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• 2023

Many major country have struggled to build a block of the secondary battery industry supply chain by considering their interests first. And their supply chain due diligence agreement mandates due diligence on human rights and environmental risks that may occur throughout the supply chain. So the integrated approach called supply chain ESG is needed. But there isn't to be a global standard for ESG yet. And the disclosure standards for each country are different, adding to companies' confusion. In this perspective, to present guidelines for establishing a supply chain ESG management strategy accompanied by Korean SMEs, this study presents environmental evaluation indicators of global secondary battery supply chain ESG customized for Korean SMEs and then performs weight analysis using AHP methodology. Through this, this study aims to suggest implications for accepting sustainability within the supply chain of Korean SMEs by presenting indicators to be considered first among environmental evaluation indicators in preparation for ESG due diligence of the global secondary battery supply chain.

• Journal of Korea Trade
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• v.27 no.5
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• pp.1-22
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• 2023

Purpose - Southeast Asia has been the focus of Korea's foreign investment. Korea has been helping developing countries in Southeast Asia achieve economic growth and win-win cooperation through capital exports. FDI is an important channel for technology diffusion. However, the impact of FDI on the bias of technological progress in the host country is dependent on the host country's own endowment structure and capital-labor factor substitution elasticity. Therefore, the central issue of this paper is to accurately evaluate the impact of Korea's FDI to the four Southeast Asian countries in various industries on their bias of technological progress. Design/methodology - The paper uses macroeconomic data for Korea and four East Asian countries to estimate capital-labor factor elasticities of substitution using nonlinear, seemingly uncorrelated regressions (NLSUR). Then, the biased technological change index (BTCI) is calculated for each country. Finally, panel data analysis is used to explore the impact of Korean FDI in various industries in the four Southeast Asian countries on their own directed technological progress, and a robustness test is conducted. Findings - There is a substitution relationship between capital and labor factors based on their elasticity in Korea, Singapore and the Philippines. There is a complementary relationship between capital and labor factors in Indonesia and Malaysia. According to the BTCI, there is a trend toward labor-biased technological progress in all countries. Korean investments in manufacturing, wholesale and retail trade in the host country trigger capital-biased technological change in the host country; investments in the finance, insurance and information and communication sectors trigger labor-biased technological change. In addition, this paper also confirms that directed technological progress can enable cross-country transmission. Originality/value - The innovation of this paper lies in three aspects. First, we estimate the BTCI for five countries and explore the trend and situation of directed technological progress in each country from each country's own perspective. Second, we explore the impact of Korean FDI in the host country on the bias to its technological progress at the industry level. Second, we explore the impact of Korean FDI in various industries in the four Southeast Asian countries on the four countries' own directed technological progress from a national perspective. Finally, we propose corresponding countermeasures for technological progress from the perspective of inverse factor endowment. These innovative points not only expand the understanding of technological progress and cross-country technology transfer in East Asia but also provide practical references for policy-makers and business operators.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1497-1503
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• 2023

To address challenges in classifying clouds and snow cover when calculating ground reflectance in Near-UltraViolet (UV) wavelengths, this study introduces a methodology that combines cloud data from the Geostationary Environmental Monitoring Spectrometer (GEMS) and the Advanced Meteorological Imager (AMI)satellites for snow cover analysis. The proposed approach aims to enhance the quality of surface reflectance calculations, and combined cloud data were generated by integrating GEMS cloud data with AMI cloud detection data. When applied to compute GEMS surface reflectance, this fusion approach significantly mitigated underestimation issues compared to using only GEMS cloud data in snow-covered regions, resulting in an approximately 17% improvement across the entire observational area. The findings of this study highlight the potential to address persistent underestimation challenges in snow areas by employing fused cloud data, consequently enhancing the accuracy of other Level-2 products based on improved surface reflectivity.

• Korea Trade Review
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• v.48 no.4
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• pp.23-45
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• 2023

This study aims to investigate the relationship between institutional distance and FDI and focuses on China's outward FDI. The institutional distance between China and the host country is measured using the institutional quality published by the World Bank. This study collects panel data from 50 countries in which China invested from 2008 to 2019 and use the panel GLS methodology to examine the factors affecting outward FDI through three models. First, this study examines the impact of the absolute value of institutional distance on China's OFDI across all countries in which China invests. Second, this study divides countries with positive and negative institutional distance to China into two groups and examine the relationship between institutional distance and OFDI in each group. Finally, this study examines the non-linear relationship between institutional distance and OFDI from China. To test this, this study adds the squared term of institutional distance to the model. The results of the analysis are as follows Institutional distance is positively related to China's OFDI. The relationship between institutional distance and OFDI is inverted U-shaped in the group of host countries with relatively higher institutional quality than China, but positive in the group of low-quality host countries. In addition, China's OFDI is affected by a combination of institutional and economic factors. The results of this study have implications not only for FDI host countries but also for MNCs' choice of FDI destinations.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.325-345
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• 2023

In the rapidly evolving domain of e-commerce, our study presents a cohesive approach to enhance customer satisfaction prediction from online reviews, aligning methodological innovation with practical insights. We integrate the RFE-SHAP feature selection with LDA topic modeling to streamline predictive analytics in e-commerce. This integration facilitates the identification of key features-specifically, narrowing down from an initial set of 28 to an optimal subset of 14 features for the Random Forest algorithm. Our approach strategically mitigates the common issue of overfitting in models with an excess of features, leading to an improved accuracy rate of 84% in our Random Forest model. Central to our analysis is the understanding that certain aspects in review content, such as quality, fit, and durability, play a pivotal role in influencing customer satisfaction, especially in the clothing sector. We delve into explaining how each of these selected features impacts customer satisfaction, providing a comprehensive view of the elements most appreciated by customers. Our research makes significant contributions in two key areas. First, it enhances predictive modeling within the realm of e-commerce analytics by introducing a streamlined, feature-centric approach. This refinement in methodology not only bolsters the accuracy of customer satisfaction predictions but also sets a new standard for handling feature selection in predictive models. Second, the study provides actionable insights for e-commerce platforms, especially those in the clothing sector. By highlighting which aspects of customer reviews-like quality, fit, and durability-most influence satisfaction, we offer a strategic direction for businesses to tailor their products and services.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.187-203
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• 2022

As the economic, social, and environmental problems of the local community reach a serious level, our society is realizing the need to foster young talents who discover opportunities in local issues through entrepreneurship education and create social values through creative challenges. However, entrepreneurship education programs are generally focused on commerciality, so customized education programs to solve regional problems are insufficient. Therefore, this study aimed to develop a community problem-solving entrepreneurship curriculum. In this study, a competency based curriculum model was applied to develop the curriculum, and regional problem-solving entrepreneurship competencies were derived through expert advice from a total of 10 people. In the process, the Delphi methodology was additionally used to reduce the possibility of errors in the competency model. As a result of the study, a total of 23 regional problem-solving entrepreneurship competencies were confirmed, and knowledge(K) - skill(S) - attitude(A) by competency consisted of 5, 9, and 9, respectively. By applying this to Dunham's problem-solving six-step model, modular learning support measures were developed in the order of phase 1(problem discovery), phase 2(problem analysis), phase 3(plan), phase 4(measure), and phase 5(evaluation). This study is meaningful in that it integrated theory and practice by developing specific entrepreneurship curriculum and learning support measures based on the theoretical model devised in social welfare. In addition, it has implications in that it developed a regional problem-solving entrepreneurship competency model based on expert advice and proposed a specific curriculum based on this.

• Korean Association of Arts Management
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• no.50
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• pp.65-100
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• 2019

The purpose of this study is to examine the patterns of deviation in urban music festival through the theories and a case study. A deviation help contemporary people in the routine of daily life to give a lot of energy. Such a deviation is strongly experienced from the festival. So it is important to study the patterns of deviation in urban festival. For this purpose, the relation between deviation and festival is examined first. And then the patterns of deviation in festival are drawn from the preceding research and case studies. The patterns of deviation in festival are identified as spatio-temporal deviation, active deviation, and situational deviation. Spatio-temporal deviation is divided into non-dailiness, space separation, and space appropriation. Active deviation is divided into make-over and expression. Situational deviation is divided into overturning and new meeting. This patterns of deviation applies to case study of ACC world music festival held in Gwangju metropolitan city with a content analysis methodology. The research finding is that Spatio-temporal deviation is most evident in ACC world music festival, on the other hand active deviation and situational deviation are weak or no evident. It is expected that various deviant elements presented in this study will be used strategically in festival planning to help strengthen the festivity of modern urban festivals.

• Information Systems Review
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• v.23 no.1
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• pp.155-172
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• 2021

With the recent increase in online product purchases, a recommender system that recommends products considering users' preferences has still been studied. The recommender system provides personalized product recommendation services to users. Collaborative Filtering (CF) using user ratings on products is one of the most widely used recommendation algorithms. During CF, the item-based method identifies the user's product by using ratings left on the product purchased by the user and obtains the similarity between the purchased product and the unpurchased product. CF takes a lot of time to calculate the similarity between products. In particular, it takes more time when using text-based big data such as review data of Amazon store. This paper suggests a hybrid recommendation system using a 2-phase methodology and text data mining to calculate the similarity between products easily and quickly. To this end, we collected about 980,000 online consumer ratings and review data from the online commerce store, Amazon Kinder Store. As a result of several experiments, it was confirmed that the suggested hybrid recommendation system reflecting the user's rating and review data has resulted in similar recommendation time, but higher accuracy compared to the CF-based benchmark recommender systems. Therefore, the suggested system is expected to increase the user's satisfaction and increase its sales.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.55-58
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• 2024

최근 각 기업의 AI 면접시스템 도입이 증가하고 있으며, AI 면접에 대한 실효성 논란 또한 많은 상황이다. 본 논문에서는 AI 면접 과정에서 지원자를 평가하는 방식을 시각, 음성, 자연어처리 3영역에서 구현함으로써, 면접 지원자를 다방면으로 분석 방법론의 적절성에 대해 평가하고자 한다. 첫째, 시각적 측면에서, 면접 지원자의 감정을 인식하기 위해, 합성곱 신경망(CNN) 기법을 활용해, 지원자 얼굴에서 6가지 감정을 인식했으며, 지원자가 카메라를 응시하고 있는지를 시계열로 도출하였다. 이를 통해 지원자가 면접에 임하는 태도와 특히 얼굴에서 드러나는 감정을 분석하는 데 주력했다. 둘째, 시각적 효과만으로 면접자의 태도를 파악하는 데 한계가 있기 때문에, 지원자 음성을 주파수로 환산해 특성을 추출하고, Bidirectional LSTM을 활용해 훈련해 지원자 음성에 따른 6가지 감정을 추출했다. 셋째, 지원자의 발언 내용과 관련해 맥락적 의미를 파악해 지원자의 상태를 파악하기 위해, 음성을 STT(Speech-to-Text) 기법을 이용하여 텍스트로 변환하고, 사용 단어의 빈도를 분석하여 지원자의 언어 습관을 파악했다. 이와 함께, 지원자의 발언 내용에 대한 감정 분석을 위해 KoBERT 모델을 적용했으며, 지원자의 성격, 태도, 직무에 대한 이해도를 파악하기 위해 객관적인 평가지표를 제작하여 적용했다. 논문의 분석 결과 AI 면접의 다면적 평가시스템의 적절성과 관련해, 시각화 부분에서는 상당 부분 정확도가 객관적으로 입증되었다고 판단된다. 음성에서 감정분석 분야는 면접자가 제한된 시간에 모든 유형의 감정을 드러내지 않고, 또 유사한 톤의 말이 진행되다 보니 특정 감정을 나타내는 주파수가 다소 집중되는 현상이 나타났다. 마지막으로 자연어처리 영역은 면접자의 발언에서 나오는 말투, 특정 단어의 빈도수를 넘어, 전체적인 맥락과 느낌을 이해할 수 있는 자연어처리 분석모델의 필요성이 더욱 커졌음을 판단했다.