• Journal of Service Research and Studies
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• v.11 no.3
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• pp.75-97
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• 2021

This study was conducted to derive a society and education system model that will improve the happiness and sustainability of human society. An ideological model for making human society a happy society was derived, and a society and education system structure and operation model based on this was presented. A fair society, a justice society, a mutually considerate society, and a society where individuals are happy are the conditions for a sustainable society. After analyzing the current situation of freedom and equality pursued by capitalism and democracy, which are currently adopted by most societies, an improvement model was derived from the perspective of a sustainable society. The cost of freedom and equality were analyzed and a new alternative system was discussed. The social solidarity and class mobility issues were discussed together and servicism was derived as an alternative solution. It is a system in which two opposing opponents of individual freedom and social norms form a symmetrical balance, and material and spiritual values are balanced. Servicism is a dynamic balance model. That is, the dimensions of time and space are involved. It is a model that maintains a thorough balance through a dialectical process as time and space change, and one value can dominate the other at a specific time or space. The service-oriented society and education system is a system that simultaneously pursues the goals of individual happiness and sustainable development of the social community.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.21-29
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• 2023

In this paper, we propose an AI-based system for automatically classifying industry and occupation codes in the population census. The accurate classification of industry and occupation codes is crucial for informing policy decisions, allocating resources, and conducting research. However, this task has traditionally been performed by human coders, which is time-consuming, resource-intensive, and prone to errors. Our system represents a significant improvement over the existing rule-based system used by the statistics agency, which relies on user-entered data for code classification. In this paper, we trained and evaluated several models, and developed an ensemble model that achieved an 86.76% match accuracy in industry and 81.84% in occupation, outperforming the best individual model. Additionally, we propose process improvement work based on the classification probability results of the model. Our proposed method utilizes an ensemble model that combines transfer learning techniques with pre-trained models. In this paper, we demonstrate the potential for AI-based systems to improve the accuracy and efficiency of population census data classification. By automating this process with AI, we can achieve more accurate and consistent results while reducing the workload on agency staff.

• Journal of Korea Entertainment Industry Association
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• v.13 no.7
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• pp.25-38
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• 2019

For many years, emotions have been regarded as dangerous as well as obstructive to reason and rationality. Even in the history of dramatic genres based on human behavior, emotions are often portrayed as errors or flaws that lead to the collapse of characters, even though they are presented as powerful motives to evoke the characters' actions. Based on the development of the cognitive science field today, it is revealed how emotion is important for human thinking, judgment and action, and how closely reason and emotion are combined. This study examines emotions dealt with in drama genres on the basis of the sociality of emotions. Emotions also play a crucial role in the change and judgment of the audience of drama. This study examines the sociality of emotions and looks at the social aspect of individual emotions through the movie as a text. Just as horror movies attempt to communicate using and expanding feelings of fear, the movie uses the emotions of 'Sad' and 'Losing' to try to expand and share it. And I look into the mechanism in which the emotions of the characters in drama are transmitted to the audience in the form of empathy.

• 한국노년학
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• v.29 no.2
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• pp.657-667
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• 2009

The aim of the present study was to investigate the effects of swimming exercise on growth-related telomere length and expression of TRF 2 in different tissues of SD rats. The telomere lengths of all the tissues analyzed were longer in the standard group than either in aged-control group or in two aged-exercise groups, suggesting growth-induced attrition of telomere lengths. On the other hand, it was also found that swimming exercise could attenuate this growth-related telomere attrition in the heart tissue of the long-term group only, with no significant attenuating effects of aerobic exercise on either liver telomere length or soleus muscle telomere length. Also, in the heart, TRF 2 expression was significantly lower in control group compare to standard group. But, there was significantly higher in long term exercise group compare to control group. There was positive correlation between telomere length and expression of TRF 2 in heart tissue. This study implies that the swimming exercise performed for longer periods of time can contribute to growth process of heart by regulation of telomere length and TRF 2 expression. In the growth process, the regular swimming exercise will provide a meaningful advantage for various physiological processes.

• Journal of the Korean Electrochemical Society
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• v.26 no.4
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• pp.43-55
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• 2023

Mass transport through nanoporous structures such as nanopores or nanochannels has fundamental electrochemical implications and many potential applications as well. These structures can be particularly useful for water treatment, energy conversion, biosensing, and controlled delivery of substances. Earlier research focused on creating nanopores with diameters ranging from tens to hundreds of nanometers that can selectively transport cationic or anionic charged species. However, recent studies have shown that nanopores with diameters of a few nanometers or even less can achieve more complex and versatile transport control. For example, nanopores that mimic biological channels can be functionalized with specific receptors to detect viruses, small molecules, and even ions, or can be made hydrophobic and responsive to external stimuli, such as light and electric field, to act as efficient valves. This review summarizes the latest developments in nanopore-based systems that can control mass transport based on the size of the nanopores (e.g., length, diameter, and shape) and the physical/chemical properties of their inner surfaces. It also provides some examples of practical applications of these systems.

• Resources Recycling
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• v.32 no.6
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• pp.54-66
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• 2023

Titanium's importance as a mineral resource is increasing, but the Korean industry depends on imports. Ilmenite is the principal titanium ore. However, research and development from raw materials have not been investigated yet in detail. Hence, measures to secure a stable titanium supply chain are urgently needed. Accordingly, through beneficiation technology, we evaluated the possibility of technological application for the efficient recovery of valuable minerals. As a result of the experiments, we confirmed that mineral particles existed as fine particles due to weathering, making recovery through classification difficult. Consequently, applying beneficiation technologies, i.e., specific gravity separation, magnetic separation, and flotation, makes it possible to recover valuable minerals such as hematite and rutile. However, there are limitations in increasing the quality and yield of TiO₂ due to the mineralogical characteristic of the hematite and rutile contained in titanium ore. Hametite is combined with rutile even at fine particles. Therefore, it is essential to develop mineral processing routes, to recover iron, vanadium, and rare earth elements as resources. On that account, we used grinding technology that improves group separation between constituent minerals and magnetic separation technology that utilizes the difference in magnetic sensitivity between fine mineral particles. The development of beneficiation technology that can secure the economic feasibility of valuable materials after reforming iron oxide and titanium oxide components is necessary.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.29-42
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• 2023

In this paper, we propose a method to enhance the prediction accuracy of solar irradiance for three major South Korean cities: Seoul, Busan, and Incheon. Our method entails the development of five generative models-vanilla GAN, CTGAN, Copula GAN, WGANGP, and TVAE-to generate independent variables that mimic the patterns of existing training data. To mitigate the bias in model training, we derive values for the dependent variables using random forests and deep neural networks, enriching the training datasets. These datasets are integrated with existing data to form comprehensive solar irradiance prediction models. The experimentation revealed that the augmented datasets led to significantly improved model performance compared to those trained solely on the original data. Specifically, CTGAN showed outstanding results due to its sophisticated mechanism for handling the intricacies of multivariate data relationships, ensuring that the generated data are diverse and closely aligned with the real-world variability of solar irradiance. The proposed method is expected to address the issue of data scarcity by augmenting the training data with high-quality synthetic data, thereby contributing to the operation of solar power systems for sustainable development.

• Korean Journal of Environmental Agriculture
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• v.42 no.4
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• pp.331-337
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• 2023

Physiological disorders in pear fruit are mainly caused by problems during the growing season, such as lack of calcium in the soil, poor drainage, low porosity, vigorous pruning, and excessive fruiting. In this study, soil physicochemical properties and leaf characteristics were analyzed in pear orchards in four regions of Korea where chlorosis symptoms occurred to determine the causes of chlorosis. The color of chlorotic leaves was diagnosed using the naked eye or SPAD and Hunter values. The soil of the chlorotic orchard had a significantly higher soil pH than that of the regular orchard. Although adequate soil depth was not significantly associated with chlorosis, combined with over-fertilization of the soil with lime, it could potentially impair plant iron uptake. Chlorotic leaves had significantly lower iron and calcium contents and significantly higher magnesium contents than those of regular leaves. Therefore, the intensive occurrence of chlorosis during secondary shoot development around June and July when it is hot and humid may be due to impaired iron and calcium absorption, leading to physiological disorders. To solve this problem, avoiding the over-application of lime and applying foliar fertilizers containing chelated iron is recommended.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.159-174
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• 2023

In this paper, we proposed a methodology to effectively determine the selection and prioritization of new business and innovation projects using AI technology. AI technology is a technology that can upgrade the business of companies in various industries and increase the added value of the entire industry. However, there are various constraints and difficulties in the decision-making process of selecting and implementing AI projects in the enterprise. In this paper, we propose a new methodology for prioritizing AI projects using Morphology, AHP, and TOPSIS. The proposed methodology helps prioritize AI projects by simultaneously considering the technical feasibility of AI technology and real-world user requirements. In this study, we applied the proposal methodology to a real enterprise that wanted to prioritize multiple AI projects in the HR field and evaluated the results. The results confirm the practical applicability of the methodology and suggest ways to use it to help companies make decisions about AI projects. The significance of the methodology proposed in this study is that it is a framework for prioritizing multiple AI projects considered by a company in the most reasonable way by considering both business and technical factors at the same time.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.119-138
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• 2024

Text indicators are increasingly valuable in economic forecasting, but are often hindered by noise and high dimensionality. This study aims to explore post-processing techniques, specifically noise filtering and dimensionality reduction, to normalize text indicators and enhance their utility through empirical analysis. Predictive target variables for the empirical analysis include monthly leading index cyclical variations, BSI (business survey index) All industry sales performance, BSI All industry sales outlook, as well as quarterly real GDP SA (seasonally adjusted) growth rate and real GDP YoY (year-on-year) growth rate. This study explores the Hodrick and Prescott filter, which is widely used in econometrics for noise filtering, and employs sufficient dimension reduction, a nonparametric dimensionality reduction methodology, in conjunction with unstructured text data. The analysis results reveal that noise filtering of text indicators significantly improves predictive accuracy for both monthly and quarterly variables, particularly when the dataset is large. Moreover, this study demonstrated that applying dimensionality reduction further enhances predictive performance. These findings imply that post-processing techniques, such as noise filtering and dimensionality reduction, are crucial for enhancing the utility of text indicators and can contribute to improving the accuracy of economic forecasts.