• Journal of Wetlands Research
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• v.25 no.1
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• pp.64-73
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• 2023

Before 2022, there was a lot of confusion in the process of planning and implementing the projects for ecological restoration of the stream due to dualization the principal agent of stream management. Because the Ministry of Environment took charge of the project in 2022, securing the health of aquatic ecosystem of stream became an essential factor in the project. Therefore, in this study, the streams that require the project for ecological restoration was selected in Han River estuary, where it is essential to secure the health of the stream aquatic ecosystem as blackish water zone and Ramsar wetland are located. Physical, chemical, spatial/humanistic, health of aquatic ecosystems evaluation indexes were calculated based on the detailed facts and figures of the project for ecological restoration of the stream in the beginning. Ranking, re-scaling, z-score, and t-score normalization methods were applied to the calculated evaluation index, and the values were compared and analyzed. After that, the entropy weight method was applied to each evaluation index. Through this process, the streams(Mokgamcheon, Anyangcheon etc.) that require the project for ecological restoration were selected for the purpose of securing the health of the aquatic ecosystem in Han River estuary. The result of this study can be used as basic research data in the process of selecting the priority determination of the projects for ecological restoration of the stream.

• Journal of Korean Home Economics Education Association
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• v.35 no.1
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• pp.125-138
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• 2023

This study was an exploratory study to identify the discomfort of using multicultural terms. The contents of the study included exploration of prior research, analysis of news articles, and in-depth interview with field experts. The results of the study are summarized as follows. First, five multicultural terms such as 'multiculturalism', 'multicultural society', 'multicultural education', '다문화가족' and '다문화가정' were extracted from exploration of prior research. Second, as a result of news analysis, 'multiculturalism' mainly appeared in the early 2000s and has been rapidly decreasing since 2006, and 'multicultural society' and 'multicultural education' have been steadily written. In contrast, '다문화가족' and '다문화가정', which first appeared in 2003 and 2004, have exceeded 80% of multicultural news articles since 2009. Third, regarding multicultural terms, the study participants were well aware of '다문화가족' and '다문화가정', and little knew of 'multiculturalism'. In an interview conducted before learning multicultural terms, '다문화가족' and '다문화가정' were recognized as familiar but uncomfortable and distinguishing terms. And 'multiculturalism', 'multicultural society', and 'multicultural education' were recognized as abstract and unfamiliar terms. In an interview conducted after learning about multicultural terms, the study participants expressed confusion about the mixed use of multicultural terms with different meanings and recognized the need for clarification.

• Journal of Practical Agriculture & Fisheries Research
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• v.15 no.1
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• pp.183-202
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• 2013

The demand of ginseng which has attracted many people for a long time has expanded further with great spotlight ; but it has caused anxiety of some safety-sensitive customers due to unavoidable pesticides and its weakness for disease and insect pest. On the other hand, sluggish studies on effective doses of ginseng and red ginseng which is produced and processed after hardship have worsened confusion of customers. Against this backdrop, this study is about to find out measures for safe ginseng cultivation and effective dose of white or red ginseng which are safely produced and reaches meaningful conclusions as follows ; As for a study to minimize the use of chemical fertilizers and pesticides or to change them into environmentally-friendly products, ginseng cultivation utilizing Lime Sulfur complex might be an alternative. The effects of Lime Sulfur complex are great on ginseng seeding with under 200 times compound KHCO3 and five-year-old ginseng with over 200 times compound using NaHCO3. When using with green materials like Bordeaux mixture, there would be great potential to realize ginseng without pesticide use.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Journal of the Korean Society of Radiology
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• v.15 no.3
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• pp.273-279
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• 2021

Metal material inserted into the body have a large difference in density from human tissues or bones around the Metal during CT scans.. Therefore, the Metal material inserted into the body produces Artifact. Metal Artifact, which occurs around Metals, can degrade the quality of CT images, causing confusion when medical team diagnose lesions. Through this experiment, we confirm that the occurrence of Artifacts decrease by using Dual energy CT and MAR algorithm in Single source Dual energy CT. We also want to present basic data on clinical application methods by comparing and analyzing the characteristics of images obtained by each method. Using GE 750HD CT, artificial implants were scanned using general method and Dual energy. Then we apply the MAR algorithm to each image obtained. And all previously acquired images were compared and analyzed the characteristics of the examination, such as image quality evaluation and dose evaluation. Images with MAR algorithm and Dual Energy confirmed a decrease in Metal Artifact. Images with MAR algorithm have reduced Metal Artifact, but have the disadvantage of distorting the details of artificial joint implants. On the other hand images teseted with Dual Energy have the advantage of being able to implement details than those applied with MAR algorithms, it takes longer to reconstruct the image and the exposure dose was about four times higher than those applied with MAR algorithm. In order to locate Metals, such as the post-operative follow-up period, it is useful to apply MAR algorithm to obtain images. And it is more useful to examine with Dual Energy when micro lesion identification, such as cardiac examination, and surgical planning or when tests are performed in diagnostic way.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.397-411
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• 2023

The number of deteriorated bridges with a service period of more than 30 years has been rapidly increasing in Korea. Accordingly, the importance of advanced maintenance technologies through the predictions of age-induced deterioration degree, condition, and performance of bridges is more and more noticed. The prediction method of the safety grade of bridges was proposed in this study using the classification models of the Decision Tree and the Random Forest based on machine learning. As a result of analyzing these models for the 8,850 bridges located in national roads with various evaluation indexes such as confusion matrix, balanced accuracy, recall, ROC curve, and AUC, the Random Forest largely showed better predictive performance than that of the Decision Tree. In particular, random under-sampling in the Random Forest showed higher predictive performance than that of other sampling techniques for the C and D grade bridges, with the recall of 83.4%, which need more attention to maintenance because of the significant deterioration degree. The proposed model can be usefully applied to rapidly identify the safety grade and to establish an efficient and economical maintenance plan of bridges that have not recently been inspected.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.230-237
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• 2023

Due to the COVID-19 pandemic and climate change, shortages of essential commodities and resources continue to occur globally. To address this problem, trade volume demand suddenly increased, driving up the freight rate of container ships sharply. The size of container vessels progressively increased from 1,500 TEU (twenty-foot equivalent unit) in the 1960s to 24,400 TEU in 2021. As the improvement of container loading capacity is closely related to the enlargement of the lashing bridge structure, it is necessary to design a structure effective for good container securing and safe under the various external loads that occur during voyage. Major classification societies have recently issued structural-analysis-based guidelines to evaluate the structural safety of lashing bridges, but their acceptance criteria and evaluation methods are different, causing confusion among engineers during design. In this study, the strength change characteristics are summarized by variations in the main variables (modeling range, opening consideration, mesh size) likely to affect the results. Based on this result, the authors propose a reasonable structural-analysis-based evaluation that is expected to serve as a reference in the next revision of classification standards.

• Journal of Technology Innovation
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• v.30 no.1
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• pp.1-20
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• 2022

Digital transformation refers to the economic and social effects of digitisation and digitalisation. Although digital transformation acts as a useful tool for economic/social development and enhancing the convenience of life, it can have negative effects (misuse of personal information, ethical problems, deepening social gaps, etc.). The government is actively establishing policies to promote digital transformation to secure competitiveness and technological hegemony, however, understanding of digital transformation-related risk issues and implementing policies to prevent them are relatively slow. Thus, this study systematically identifies risk issues of the future society that can be caused by digital transformation based on quantitative analysis of media articles big data through the Embedded Topic Modeling method. Specifically, first, detailed issues of negative effects of digital transformation in major countries were identified. Then detailed issues of negative effects of artificial intelligence in major countries and Korea were identified. Further, by synthesizing the results, future direction of the government's digital transformation policies for responding the negative effects was proposed. The policy implications are as follows. First, since the negative effects of digital transformation does not only affect technological fields but also affect the overall society, such as national security, social issues, and fairness issues. Therefore, the government should not only promote the positive functions of digital transformation, but also prepare policies to counter the negative functions of digital transformation. Second, the detailed issues of future social risks of digital transformation appear differently depending on contexts, so the government should establish a policy to respond to the negative effects of digital transformation in consideration of the national and social context. Third, the government should set a major direction for responding negative effects of digital transformation to minimize confusion among stakeholders, and prepare effective policy measures.

• Korean Chemical Engineering Research
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• v.61 no.3
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• pp.388-393
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• 2023

The analysis of engineering data using neural network based on supervised learning has been utilized in various engineering fields such as optimization of chemical engineering process, concentration prediction of particulate matter pollution, prediction of thermodynamic phase equilibria, and prediction of physical properties for transport phenomena system. The supervised learning requires training data, and the performance of the supervised learning is affected by the composition and the configurations of the given training data. Among the frequently observed engineering data, the data is given in log-scale such as length of DNA, concentration of analytes, etc. In this study, for widely distributed log-scaled training data of virtual 100×100 images, available loss functions were quantitatively evaluated in terms of (i) confusion matrix, (ii) maximum relative error and (iii) mean relative error. As a result, the loss functions of mean-absolute-percentage-error and mean-squared-logarithmic-error were the optimal functions for the log-scaled training data. Furthermore, we figured out that uniformly selected training data lead to the best prediction performance. The optimal loss functions and method for how to compose training data studied in this work would be applied to engineering problems such as evaluating DNA length, analyzing biomolecules, predicting concentration of colloidal suspension.

• Korean Journal of Heritage: History & Science
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• v.55 no.4
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• pp.38-53
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• 2022

In this article, I have summarized and reviewed the concepts and terms surrounding the stamped construction technique, focusing on earthen walls in the Three Kingdoms period. This is because confusion is caused by defining the nature of the earthen walls by using various concepts and terms for each researcher regarding the substance and construction method of the earthen walls. The stamped earth method is a representative ancient civil engineering or construction technique in which a frame is made of plates to form a fortress wall, a fence, and the base of a building, and then soil or sand is poured into it layer by layer and then stamped with a bat to make it solid. Therefore, in order to prove that the earthen wall was built by the stamped earth method, evidence such as a narrow plate, a column for fixing it, long horizontal and vertical wood pieces to support the narrow plate, and traces of pounding the soil must be detected. However, in Korea, there are very few cases where such evidence has been fully excavated, so it is necessary to agree on how strictly the standards for the stamped earth method will be applied. The terms related to the stamped technique mobilized for the construction of the earthen walls were explained with actual examples by dividing the terms related to the concept into terms related to the principle and unit of the stamped plate, and the specific stamped technology. In particular, in Pungnabtoseong Earthen wall, a variety of typical and diverse methods of building the ancient stamped earthen wall were identified so that decisive data could be secured to understand the principles and techniques of the stamped earthen wall. In the future, a more general understanding of the stamped technique will be possible only when more evidence related to it is found in relics other than Pungnabtoseong Earthen wall.