• Tunnel and Underground Space
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• v.32 no.6
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• pp.491-501
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• 2022

Bentonite has been proposed as a buffer and backfill material for high-level radioactive waste repository. Under such repository environment conditions, bentonite is subjected to combined thermal, hydrological, mechanical, and chemical processes. This study evaluates the feasibility of applying X-ray CT technology on the characterization of bentonite under hydration conditions using a newly developed testing cell. The cylindrical cell is made of platic material, with a removable cap to place the sample, enabling to apply vertical pressure on the sample and to measure swelling pressure. The hydration test was carried out with a sample made of Gyeonju bentonite, with a dry density of 1.4 g/cm³, and a water content of 20%. The sample had a diameter of 27.5 mm and a height of 34 mm. During the test, water was injected at a constant pressure of 0.207 MPa, and lasted for 7 days. After one day of hydration, bentonite swelled and filled out the space inside the cell. Moreover, CT histograms showed how the hydration process induced an initial increase and later progressive decrease on the density of the sample. Detailed profiles of the mean CT value, CT standard deviation, and CT gradient provided more details on the hydration process of the sample and showed how the bottom and top regions exhibited a decrease on density while the middle region showed an increase, especially during the first two days of hydration. Later, the differences in CT values with respect to the initial state decreased, and were small at the end of testing. The formation and later reduction of cracks was also characterized through CT scanning.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.19-26
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• 2023

Humans have adapted and evolved to natural light. However, as humans stay in indoor longer in modern times, the problem of biorhythm disturbance has been induced. To solve this problem, research is being conducted on lighting that reproduces the correlated color temperature(CCT) of natural light that varies from sunrise to sunset. In order to reproduce the CCT of natural light, multiple LED light sources with different CCTs are used to produce lighting, and then a control index DB is constructed by measuring and collecting the light characteristics of the combination of input currents for each light source in hundreds to thousands of steps, and then using it to control the lighting through the light characteristic matching method. The problem with this control method is that the more detailed the steps of the combination of input currents, the more time and economic costs are incurred. In this paper, an LED lighting control method that applies interpolation and combination calculation based on the minimum spectral power distribution information for each light source is proposed to reproduce the CCT of natural light. First, five minimum SPD information for each channel was measured and collected for the LED lighting, which consisted of light source channels with different CCTs and implemented input current control function of a 256-steps for each channel. Interpolation calculation was performed to generate SPD of 256 steps for each channel for the minimum SPD information, and SPD for all control combinations of LED lighting was generated through combination calculation of SPD for each channel. Illuminance and CCT were calculated through the generated SPD, a control index DB was constructed, and the CCT of natural light was reproduced through a matching technique. In the performance evaluation, the CCT for natural light was provided within the range of an average error rate of 0.18% while meeting the recommended indoor illumination standard.

• Korean Journal of Heritage: History & Science
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• v.55 no.4
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• pp.278-294
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• 2022

To date, cultural property education has seen rapid quantitative growth due to national and personal needs. However, qualitative growth is lacking. The objectives of cultural property education have not been established, and therefore, even its identity is not clear. The most pressing issue at present in cultural property education is to first set objectives. This study aimed to analyze the objectives of current cultural property education, identify the problems, and set new objectives to meet significant national and personal needs in terms of education. The problems with the objectives of current cultural property education are that the persons interested in the education do not understand the concept of the education objectives clearly and that the objectives do not contain much actual content of the education. Also, the objectives of the education do not take into account the dynamic competencies and interests of the learners and do not satisfy the changes of the times. To solve these problems, new cultural property education, called 'U.V.E.C.,' was offerred. U.V.E.C. education is aimed at understanding cultural properties, recognizing their value, and enjoying them, and at creating culture. The objectives of U.V.E.C. cultural property education were set such that they can be modified flexibly in a learner-centric way with clear and practical format and contents. Based on this direction, stepwise objectives were set including overall objectives, detailed objectives, and practice objectives, and objective cases of each step were proposed. Considering the generality of the education and the distinct characteristics of the cultural properties, the U.V.E.C. education objectives took into account the diversity of behavioral objectives, clearness in statements, the objectives of problem solving, the initiative of learners and openness for expression outcomes. The U.V.E.C. objectives are clear and specific so that teachers can enhance their pedagogical efficiency and learners are able to develop interesting and diversified competencies. In addition, it is expected that the U.V.E.C. objectives will significantly affect objective setting for education on cultural properties which have not been studied widely. Further systemic and specific studies on the contents and methods of the U.V.E.C. education would help to change the overall education on cultural properties and position the field as a new academic area.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.113-126
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• 2022

The tectonic history of the Chukchi Abyssal Plain in the Amerasia Basin, Arctic Ocean, has not been fully explored due to the harsh conditions of sea ice preventing detailed observation. Existing models of the tectonic history of the region provide contrasting interpretation of the timing of formation of the crust (Mesozoic to Cenozoic), crust type (from hyper-extended continental crust to oceanic crust), and formation process (from parallel/fan-shaped rifting to transformation faulting). To help determine the age of the oceanic crust, the geothermal gradient was measured at three stations in the south of abyssal plain at depth of 2,160-2,250 m below sea level. Heat flow measurement stations were located perpendicular to the spreading axis over a 40 km-long transect. In-situ thermal conductivity measurement, corrected by the laboratory test, gave observed marine heat flows of 55 to 61 mW/m². All measurements were taken during Arctic expeditions in 2018 (ARA09C expedition) and 2021 (ARA12C expedition) by the Korean ice-breaking research vessel (IBRV) Araon. Given the assumption of oceanic crust, the results correspond to formation in the Late Cretaceous (Mesozoic). The inferred age supports the hypothesis of formation activated by the opening of the Makarov Basin during the Late Mesozoic-Cenozoic. This would make it contemporaneous with rifting of the Chukchi Border Land immediately east of the abyssal plain. The heat flow data indicate the base of the gas hydrate stability zone is located 332-367 m below the seafloor, this will help to identify the gas hydrate-related bottom simulating reflector in the future seismic survey, as already identified on the Chukchi Plateau. Further geophysical surveys, including heat flow measurements, are required to increase our understanding of the formation process and thermal mantle structure of the abyssal plain.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.246-262
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• 2023

This study analyzed policy implementation factors focusing on how Donuimun, a demolished cultural heritage, was digitally restored and the policy implementation process of Donuimun Gate restoration. Through this, the characteristics of the implementation process of the digital Donuimun Gate restoration policy promoted by public-private multilateral collaboration were examined and implications were sought for how institutions with different interests solved problems and collaborated in the implementation process. The research method was focused on policy implementation factors including policy executive factors, policy content factors, policy resource factors, and policy environment factors, and the process was analyzed for each detailed component. Along with literature analysis, in-depth interviews were conducted with participants in policy implementation. As a result of the study, first, it was found in the policy executive factor that the quick decision-making leadership of the policy manager and the flexible attitude of the person in charge of the government agency had a positive effect on preventing conflicts between different interest groups. Second, in terms of policy content, establishing a common goal that everyone can accept and moving forward consistently gave trust and created synergy. Third, in the policy implementation resource factor, the importance of the budget was emphasized. Finally, as an environmental factor for policy implementation, the opening of 5G mobile communication for the first time along with the emergence of the Fourth Industrial Revolution at the time of policy implementation acted as a timely factor. The digital Donuimun Gate was the first case of restoring a lost cultural heritage with AR and VR, and received attention and support from the mass media and the public. This also shows that digital restoration can be a model case that can be a solution without conflicts with local residents where cultural heritages are located or conflicts between stakeholders in the preservation and restoration of real objects.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.209-223
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• 2023

This study was conducted to evaluate the effectiveness of a polar literacy education program for elementary and middle school students, and to derive implications for new education to respond to climate change. We developed modular education programs based on the seven principles of polar literacy established by the Polar-ICE team. We divided them into two courses, one emphasizing science concepts and another emphasizing humanities and sociological issues. We then selected and structured detailed programs suitable for the two courses. These two courses were applied to 26 elementary and middle school students for approximately 69 hours in a Saturday science class hosted by the Department of Science Education at a university in Seoul. The 26 students were divided into three groups. Two groups completed the science education program for polar literacy and a humanities and social studies education program for polar literacy, respectively. The third group, the control group, received general science education unrelated to polar literacy. Before and after running the programs, all three groups responded to a polar literacy test and questionnaires that used vocabulary and presented scenes associated with polar regions. The test results were expressed using Wilcoxon signed ranks, which is a non-parametric test method, and improvements made upon completion of the program were analyzed. From a cognitive aspect, all three groups showed improvement after completing the program in the knowledge area; however, the experimental groups showed a greater degree of improvement than the control group, and there was a clear difference in the contents or materials explicitly covered. From an affective aspect, the difference between before and after the program was minor, but the group that focused on humanities and social issues showed a statistically significant improvement. Regarding changes in polar imagery, the two experimental groups tended to diverge from monotonous images to more diverse images compared to the control group. Based on the above results, we suggested methods to increase the effectiveness of polar literacy education programs, the importance of polar literacy as appropriate material for scientific thinking and earth system education, measures to improve attitudes related to the polar region, and the need to link to school curriculums.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4B
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• pp.385-396
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• 2009

Non-household unit water use for each type of business are estimated in this study. The business types are subdivided into forty based on nine categories by the national industrial standard classification, such as office, commerce, public bathing, public water use etc. Correlation analysis and analysis of variance (ANOVA) are applied to obtain statistical characteristics between industrial water use data, surveyed in six cities including Nonsan, Seosan and the National Statistical Bureau and site area, employees number etc. for each detailed business area. As the proposed non-household unit water uses are compared with five surveyed data in USA, it is shown that almost of water uses per unit area are less than those in USA. Non-household unit water uses of 25% cumulative probability water use recommended as efficiency benchmarks among surveyed data in Korea are also less than those in USA. Especially, in the case of water use in school, the average and the range are similar results showing water use range between 0.4 and 6.2 ($l/m^2/day$) as liter per capita day per an unit area, also water use range between 11.9 to 64.0 (l/student/day) as liter per capita day per a person. From the result of correlation analysis with internal and exogenous affecting factors on non-household water use, it can be concluded that a unit area is most appropriate factor as a standard of non-household unit water use. In case of water use in educational business, the number of students including staffs is more correlated than site ares with water use for the settled water consumption tendency. Although the increase and decrease of educational institutes, retail/wholesale store and restaurants are shown remarkable by the temperature as a representative factor, low correlations are shown in water use fluctuation in lodging house and hospital.

• Journal of Food Hygiene and Safety
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• v.38 no.3
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• pp.99-111
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• 2023

The purpose of this study was to provide basic data for setting more detailed standards for baby food and to provide food information that can be used in real-world settings. We purchased 80 snacks and 40 drinks for infants and toddlers from supermarkets and online markets and analyzed tar color, artificial sweeteners, mycotoxins, and nutritional components (e.g., sucrose, sodium, and calcium). Fortunately, it was confirmed that both tar color and sodium saccharin, which do not have detection criteria for labeled foods for infants and toddlers, were not detected. However, acesulfame potassium was detected at 0.07 g/kg in one snack sample. As for myxotoxins, aflatoxin (B1, B2, G1, and G2) and ochratoxin A were not detected. Fumonisin B1, fumonisin B2, and zearalenone were detected in the ranges of 9.78-78.94 ㎍/kg, 5.58-11.73 ㎍/kg, and 2.96-8.83 ㎍/kg, respectively, but only in snacks. Sucrose was detected in 65 of the snacks (0.02-40.94 g/net weight [g]) and in 24 of the drinks (0.12-27.60 g/net weight [g]). Minerals were detected in most of the samples, and in four snacks, the zinc content per net exceeded the tolerable upper intake level for infants. Sixteen snacks exceeded the food standards for sodium content for infants and toddlers, but none of them were labeled as food for infants and toddlers in the product manufacturing report, such that the corresponding standards could not be applied. Therefore, it seems necessary to establish institutional improvements, such as strengthening labeling standards, so that the currently enforced standards can be appropriately applied, and establishing standards for labeled foods for infants and toddlers.