• Journal of IKEEE
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• v.27 no.4
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• pp.464-471
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• 2023

In this paper, we propose a method to reduce age distortion in facial expression image generation using StyleGAN Encoder. The facial expression image generation process first creates a face image using StyleGAN Encoder, and changes the expression by applying the learned boundary to the latent vector using SVM. However, when learning the boundary of a smiling expression, age distortion occurs due to changes in facial expression. The smile boundary created in SVM learning for smiling expressions includes wrinkles caused by changes in facial expressions as learning elements, and it is determined that age characteristics were also learned. To solve this problem, the proposed method calculates the correlation coefficient between the smile boundary and the age boundary and uses this to introduce a method of adjusting the age boundary at the smile boundary in proportion to the correlation coefficient. To confirm the effectiveness of the proposed method, the results of an experiment using the FFHQ dataset, a publicly available standard face dataset, and measuring the FID score are as follows. In the smile image, compared to the existing method, the FID score of the smile image generated by the ground truth and the proposed method was improved by about 0.46. In addition, compared to the existing method in the smile image, the FID score of the image generated by StyleGAN Encoder and the smile image generated by the proposed method improved by about 1.031. In non-smile images, compared to the existing method, the FID score of the non-smile image generated by the ground truth and the method proposed in this paper was improved by about 2.25. In addition, compared to the existing method in non-smile images, it was confirmed that the FID score of the image generated by StyleGAN Encoder and the non-smile image generated by the proposed method improved by about 1.908. Meanwhile, as a result of estimating the age of each generated facial expression image and measuring the estimated age and MSE of the image generated with StyleGAN Encoder, compared to the existing method, the proposed method has an average age of about 1.5 in smile images and about 1.63 in non-smile images. Performance was improved, proving the effectiveness of the proposed method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.779-793
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• 2023

Intensive and long-term aquaculture activities in Korea have generated considerable amounts of organic matter, deteriorating the sedimentary environment and ecosystem. The Korean government enacted the Fishery Management Act to preserve and manage the environment of fish farms. Based on this, a fisheries environment assessment has been conducted on fish cage farms since 2014, necessitating the development of a scientific and objective evaluation method suitable for the domestic environment. Therefore, a benthic health index (BHI) was developed using the relationship between benthic polychaete communities and organic matter, a major source of pollution in fish farms. In this study, the development process and calculation method of the BHI have been introduced. The BHI was calculated by classifying 225 species of polychaetes appearing in domestic coastal and aquaculture areas into four groups by linking the concentration gradient of the total organic carbon in the sediment and the distributional characteristics of each species and assigning differential weights to each group. Using BHI, the benthic fauna communities were assigned to one of the four ecological classes (Grade 1: Normal, Grade 2: Slightly polluted, Grade 3: Moderately polluted, and Grade 4: Heavily polluted). The application of the developed index in the field enabled effective evaluation of the Korean environment, being relatively more accurate and less affected by the season compared with the existing evaluation methods like the diversity index or AZTI's Marine Biotic Index developed overseas. In addition, using BHI will be useful in the environmental management of fish farms, as the environment can be graded in quantified figures.

• Journal of Nutrition and Health
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• v.56 no.6
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• pp.730-741
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• 2023

Purpose: The 2020 Dietary Reference Intakes for Koreans (KDRIs) serves as a foundation for daily nutrient and energy recommendations aiming to enhance public health and prevent chronic diseases. They act as guidelines for maintaining proper nutrition and overall health. Using KDRIs is crucial for promoting healthier lifestyles and making informed dietary choices. Thus, this study explores the influence of a nutrition education program, based on the 2020 KDRIs, on the nutrition knowledge and dietary habits of undergraduates in Gyeongsangnam-do and Gyeonggi-do. Methods: The nutrition education program, designed with diverse instructional materials, was executed across a wide range of universities. The education group (n = 75) engaged in the program for a 6-week instructional period, while the control group (n = 53) underwent the survey without participating in the education program. Nutrition Quotient (NQ) and knowledge assessments were administered to both groups immediately before and after the instructional period. Results: Within the education group, the nutrition education program positively impacted responses to NQ practice items, including knowledge of nutrition, daily intake, and portion sizes (p < 0.05). In contrast, there were no significant differences between the before and after responses of the control group for most survey items. Post-program evaluations showed significantly higher self-assessment scores and increased satisfaction levels (p < 0.05), with the satisfaction rate for the education program using the 2020 KDRIs reaching 99.2%. Conclusion: This study has demonstrated the positive impact of an effective nutrition education program. However, there is a need for the continuous development and implementation of nutrition education programs to sustain these outcomes and further enhance the nutritional education experience.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.729-744
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• 2023

The value of lithium has significantly increased due to the rising demand for electric cars and batteries. Lithium is primarily found in pegmatites, hydrothermally altered tuffaceous clays, and continental brines. Globally, groundwater-fed salt lakes and oil field brines are attracting attention as major sources of lithium in continental brines, accounting for about 70% of global lithium production. Recently, deep groundwater, especially geothermal water, is also studied for a potential source of lithium. Lithium concentrations in deep groundwater can increase through substantial water-rock reaction and mixing with brines. For the exploration of lithim in deep groundwater, it is important to understand its origin and behavior. Therefore, based on a nationwide preliminary study on the hydrogeochemical characteristics and evolution of thermal groundwater in South Korea, this study aims to investigate the distribution of lithium in the deep groundwater environment and understand the geochemical factors that affect its concentration. A total of 555 thermal groundwater samples were classified into five hydrochemical types showing distinct hydrogeochemical evolution. To investigate the enrichment mechanism, samples (n = 56) with lithium concentrations exceeding the 90th percentile (0.94 mg/L) were studied in detail. Lithium concentrations varied depending upon the type, with Na(Ca)-Cl type being the highest, followed by Ca(Na)-SO₄ type and low-pH Ca(Na)-HCO₃ type. In the Ca(Na)-Cl type, lithium enrichment is due to reverse cation exchange due to seawater intrusion. The enrichment of dissolved lithium in the Ca(Na)-SO₄ type groundwater occurring in Cretaceous volcanic sedimentary basins is related to the occurrence of hydrothermally altered clay minerals and volcanic activities, while enriched lithium in the low-pH Ca(Na)-HCO₃ type groundwater is due to enhanced weathering of basement rocks by ascending deep CO₂. This reconnaissance geochemical study provides valuable insights into hydrogeochemical evolution and economic lithium exploration in deep geologic environments.

• Journal of Life Science
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• v.33 no.10
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• pp.797-807
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• 2023

To improve the functionality of mulberry, samples were fermented with Lactobacillus plantarum JCM 1149 (LP) or Pichia kudriavzevii Atz-EN-01 (PK), and their antioxidant and anti-obesity activities were compared to those of unfermented mulberry. After fermenting for 60 hr, the total polyphenol and flavonoid content of the PK-fermented mulberry (PKFM) and LP-fermented mulberry (LPFM) was 1.5-fold and 2-fold higher, respectively, while the total anthocyanin content was 1.3-fold and 1.5-fold higher in the PKFM and LPFM, respectively. DPPH radical scavenging activity was found to be 16.3% higher (86% vs. 100%) after PK fermentation and 8.1% higher (86% vs. 93%) after LP fermentation. The lipase inhibitory activity of the LPFM and PKFM was 62.9% and 52.5%, respectively. 3T3-L1 preadipocytes were treated with unfermented mulberry, LPFM, or PKFM at 200, 400, or 800 ㎍/ml and stained with oil-red-O. A slight difference in the staining was observed in samples treated with 400 ㎍/ml. However, treatment with 800 ㎍/ml significantly reduced staining compared to the control, and the LPFM exhibited relatively higher adipogenesis inhibitory activity than the PKFM. Blood triglyceride content increased by 9.5% in the high-fat diet group, but decreased by 17.1% in the control group, 37.1% in the LPFM group, and 41.6% in the PKFM group. The blood triglyceride content of the LPFM group decreased by 43.1% and 21.4% compared to the high-fat diet group and the control group, respectively, and that of the PKFM group decreased by 48.6% and 28.9% compared to the same groups. In conclusion, the results indicate that fermented mulberry has increased antioxidant activity, lipase inhibitory activity, and adipogenesis inhibition activity, and decreased blood triglyceride content compared to unfermented mulberry.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.695-713
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• 2023

In coastal waters, phytoplankton,suspended particulate matter, and dissolved organic matter intricately and nonlinearly alter the reflectivity of seawater. Neural network technology, which has been rapidly advancing recently, offers the advantage of effectively representing complex nonlinear relationships. In previous studies, a three-stage neural network was constructed to extract the inherent optical properties of each component. However, this study proposes an algorithm that directly employs a deep neural network. The dataset used in this study consists of synthetic data provided by the International Ocean Color Coordination Group, with the input data comprising above-surface remote-sensing reflectance at nine different wavelengths. We derived inherent optical properties using this dataset based on a deep neural network. To evaluate performance, we compared it with a quasi-analytical algorithm and analyzed the impact of log transformation on the performance of the deep neural network algorithm in relation to data distribution. As a result, we found that the deep neural network algorithm accurately estimated the inherent optical properties except for the absorption coefficient of suspended particulate matter (R² greater than or equal to 0.9) and successfully separated the sum of the absorption coefficient of suspended particulate matter and dissolved organic matter into the absorption coefficient of suspended particulate matter and dissolved organic matter, respectively. We also observed that the algorithm, when directly applied without log transformation of the data, showed little difference in performance. To effectively apply the findings of this study to ocean color data processing, further research is needed to perform learning using field data and additional datasets from various marine regions, compare and analyze empirical and semi-analytical methods, and appropriately assess the strengths and weaknesses of each algorithm.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.111-128
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• 2020

Recently, in the process of globalization of companies, the use of third party logistics providers (3PL) has been strengthened. Therefore, the purpose of this study is to test the effectiveness of the logistics information system provided by 3PL companies. This study is to test the relationship between the effect of the characteristics of the 3PL logistics information system on the shipper's supply chain performance, that is, logistics performance, customer performance, and organizational performance, and the shipper's loyalty to the 3PL company, that is, 3PL corporate performance. In addition, long-term relationship orientation is to test whether there is a moderating effect between the shipper company and the 3PL company. Through this, this study aims to provide strategic implications for improving the competitiveness of 3PL companies. In this study, a total 205 data were collected and used for analysis of shippers companies for hypothesis testing, and analyzed using SPSS 21.0 and AMOS 21.0 statistical programs. The results of the study are summarized as follows. First, it was found that the accuracy, timeliness, and usefulness of the 3PL logistics information system all had a significant positive (+) effect on the performance of the shipper's supply chain. Second, it was found that the accuracy, timeliness, and usefulness of the 3PL logistics information system all had a significant positive (+) effect on 3PL corporate performance. Third, it was found that the performance of the supply chain of the shipper company had a significant positive (+) effect on the performance of the 3PL company. Finally, it was found that long-term relationship orientation had a moderating effect on the relationship between the performance of the shipper company's supply chain and the performance of the 3PL company. The purpose of this study is to provide academic and practical implications for securing competitive advantage through the logistics information system of 3PL logistics companies.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.1-21
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• 2020

Recently, the emergence of new technologies caused by the Fourth Industrial Revolution caused a great change not only in the overall society but also in the retail industry. In the retail industry, unmanned stores based on new technologies have emerged, changing the consumption behavior of consumers. In particular, the global pandemic caused by COVID-19, which appeared in December 2019, raised social risks, and as a result of this, the beginning of the non-face-to-face era, interest in unmanned stores is increasing. In this study, the effects of benefits factors (perceived usefulness, perceived economics, perceived enjoyment, relative advantages) and sacrifice factors (perceived risk, technicality) perceived by unmanned store users on continuous use intention through perceived value. In addition, it is a study to test through empirical analysis what role the social risk from COVID-19 plays in the process of consumption through unmanned stores. The purpose of this study is to provide strategic implications for the activation of unmanned stores in the non-face-to-face era. In this study, a total of 293 copies of data were collected for users of unmanned stores for hypothesis testing. In addition, the collected data was analyzed using SPSS 21.0 and AMOS 21.0 statistical programs. The results of the study are summarized as follows. First, it was found that the perceived benefits (perceived usefulness, perceived economics, perceived playfulness, and relative advantages) of unmanned stores all had a significant positive effect on perceived value. Second, it was found that all perceived sacrifices (perceived risk, technicality) of unmanned stores had a significant negative effect on perceived value. Third, it was found that the perceived value of unmanned stores had a significant positive effect on the intention to continue use. Finally, the social risk from COVID-19 has been shown to play a moderating role when the perceived sacrifice of unmanned stores affects the perceived value.

• Journal of the Daesoon Academy of Sciences
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• v.46
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• pp.1-32
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• 2023

The purpose of this article is to critically reflect on the 2022 national curriculum on religions. The perspective of this reflection is that since the religious curriculum is meant to be a national curriculum, it should be applicable to all high school students, be shareable, and function as a place for meta-reflection regarding the proper use of the category of religion. For this purpose, I reviewed the form and content of the 2022 curriculum on religions in Section 2. The form of the 2022 curriculum on religions looks similar to the previously utilized curriculum. However, the main change is that the subject of religions was arbitrarily placed into the category of 'subjects for choosing a career.' And the 2022 curriculum on religions has two characteristics in terms of content: the orientation of 'making religious people (spiritual formation)' and the reemergence of the concept of 'pseudo-religion.' In Section 3, I delved into the orientation of 'making religious people through religious reflection' among the characteristics of the 2022 curriculum on religions. In this process, I discovered that the concept of 'reflection as a metacognitive technology,' which was the core of the prior curriculum and school education, was transformed into the concept of 'religious reflection,' and the concepts of spirituality and religiosity were also added. In Section 4, I delved into the dichotomy of 'religion and pseudo-religion.' 'Pseudo-religion' is a new focus in the 2022 curriculum on religions. In this process, I revealed that the concept of 'pseudo-religion' is a combination of an outdated administrative term of the Japanese Government-General of Korea during Japan's occupation of Korea, and as such, the term is inherently value-laden and harmful. I also revealed that determining 'pseudo-religion' in school education regenerates the colonial Japanese Government-General's biased attitudes toward Korean religions and forces teachers to 'invent' (detect or personally appraise) modern day pseudo-religions through arbitrary judgements. The 'curriculum to emphasize religious reflection and detect pseudo-religions in order to create religious people' can distort the subject of religion in the national curriculum as into a 'subject for religion (promotion or degradation).' If this distortion continues, the appropriateness of curriculum on religions existing within the national curriculum will eventually become a subject of debate.