• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.599-608
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• 2020

This study aims to investigate the performance and satisfaction of occupational therapists at the Dementia Relief Center for health care of the elderly in local communities, and to provide basic data necessary for role establishment by checking occupational therapists' tasks according to the priority. The subjects of this study were occupational therapists in dementia care centers in the Honam area and Gwangju Metropolitan City, who were surveyed via mail and e-mail. The survey had a total of 54 items covering the general characteristics of the therapists and current state of the centers (n=8), performance and satisfaction with the service areas and task content of the centers (n=45), and tasks that were considered important (one short-answer question). It was found that occupational therapists at the Dementia Relief Center were mainly carrying out the "Dementia Prevention Management Projects", which provided the programs for the patients, and they showed the highest satisfaction. Although the 'MMSE-DS' is occupational therapists' own area with high performance and satisfaction, it was not assigned to the occupational therapists at the Dementia Relief Center, indicating that the role was insufficient. The tasks related "administrative works and strengthening community capacities" showed low performance and satisfaction, but they are essential for the operation of the Dementia Relief Center and the management of the patients, so the plans to increase the occupational therapists' performance should be established. The categories of projects that occupational therapists consider important were also consistent with those they had to perform. It means the occupational therapists at the Dementia Relief Center recognized their unique roles. In this context, to establish the role of occupational therapist at the Dementia Relief Center, it is necessary to amend the operating guidelines based on the performance, satisfaction, and priorities of the projects, and to develop the curriculums and programs that can improve the tasks with insufficient performance and low satisfaction.

• 지역과문화
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• v.7 no.2
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• pp.173-202
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• 2020

This study aims to enhance the family-friendliness of the region by examining the relationship between family relations and the community environment, and objectively comparing the local environment surrounding the family. To this end, we reviewed the areas of socio-cultural and economic sectors that affect the family relationship satisfaction, and in particular, analyzed the trend of changes in regional index by utilizing the Korean Family Happiness Composite Index (KFHCI) developed as a community indicators. This index utilizes community indicators published in the National Statistical Portal's "e-Region indicators," and these variables are related to family relationship satisfaction. Therefore, this study compared the seven areas of the Family Happiness Composite Index (Population Family, Health Culture, Education, Income Consumption, Employment Labor, Housing Transportation, Environment and Social Integration) by region, and examined the trends for 10 years. According to the study, the average score of KFHCI's entire region was rising from 2008 to 2018. Overall, the community environment that affects family relationship satisfaction is also improving. The regions belonging to the upper level were Jeonnam, Gangwon, Chungnam, Jeonbuk, and Gyeongbuk. Areas belonging to the lower level are Seoul, Busan, Daegu, Incheon, and Gwangju. In almost sectors, the lower-level regions did not have sufficient physical infrastructure compared to population density and over-density, and improved little by little, but not enough to reflect the needs of local people and improve the quality of life. In the future, we should develop more regular and complementary indicators to develop customized policies for each region that can improve the quality of family relationships. It will also be necessary to study the impact of each index field when a socioeconomic crisis occurs due to social disasters, and try to change indicators

• The Journal of Engineering Geology
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• v.32 no.4
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• pp.697-723
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• 2022

Data-driven models to predict groundwater levels 30 days in advance were developed for 12 groundwater monitoring stations in the middle-Jeju watershed, Jeju Island. Stacked long short-term memory (stacked-LSTM), a deep learning technique suitable for time series forecasting, was used for model development. Daily time series data from 2001 to 2022 for precipitation, groundwater usage amount, and groundwater level were considered. Various models were proposed that used different combinations of the input data types and varying lengths of previous time series data for each input variable. A general procedure for deep-learning-based model development is suggested based on consideration of the comparative validation results of the tested models. A model using precipitation, groundwater usage amount, and previous groundwater level data as input variables outperformed any model neglecting one or more of these data categories. Using extended sequences of these past data improved the predictions, possibly owing to the long delay time between precipitation and groundwater recharge, which results from the deep groundwater level in Jeju Island. However, limiting the range of considered groundwater usage data that significantly affected the groundwater level fluctuation (rather than using all the groundwater usage data) improved the performance of the predictive model. The developed models can predict the future groundwater level based on the current amount of precipitation and groundwater use. Therefore, the models provide information on the soundness of the aquifer system, which will help to prepare management plans to maintain appropriate groundwater quantities.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.251-273
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• 2022

Recently, research on applying text analysis to deep learning has steadily continued. In particular, researches have been actively conducted to understand the meaning of words and perform tasks such as summarization and sentiment classification through a pre-trained language model that learns large datasets. However, existing pre-trained language models show limitations in that they do not understand specific domains well. Therefore, in recent years, the flow of research has shifted toward creating a language model specialized for a particular domain. Domain-specific pre-trained language models allow the model to understand the knowledge of a particular domain better and reveal performance improvements on various tasks in the field. However, domain-specific further pre-training is expensive to acquire corpus data of the target domain. Furthermore, many cases have reported that performance improvement after further pre-training is insignificant in some domains. As such, it is difficult to decide to develop a domain-specific pre-trained language model, while it is not clear whether the performance will be improved dramatically. In this paper, we present a way to proactively check the expected performance improvement by further pre-training in a domain before actually performing further pre-training. Specifically, after selecting three domains, we measured the increase in classification accuracy through further pre-training in each domain. We also developed and presented new indicators to estimate the specificity of the domain based on the normalized frequency of the keywords used in each domain. Finally, we conducted classification using a pre-trained language model and a domain-specific pre-trained language model of three domains. As a result, we confirmed that the higher the domain specificity index, the higher the performance improvement through further pre-training.

• Journal of Korean Home Economics Education Association
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• v.34 no.1
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• pp.131-149
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• 2022

The purpose of this study is to explore what value home economics education should pursue to be established as an essential subject in the 'with-/post Covid-19 era', and to suggest directions for the development of the future. To this end, first of all, changes in the future society symbolized by the with-/post- Covid-19 era were diagnosed through literature review. Moreover, the 'OECD Education 2030' project and Korea's 'Educational Vision 2045', which identified the purpose of education in response to changes in the future, were considered. Furthermore, the teleology of education of John White, a British educational philosopher, was contemplated. As a result, the purpose of education for the future society is considered to be changing toward the well-being of society and individuals, and efforts such as the development of a well-being subject are being made in various countries for this purpose. While several a number of strategies are possible for the implementation of well-being education in Korea, this study argues that the easiest way is to strengthen home economics education that already exists as a subject. In addition, the main value of home economics education as an essential subject in the with-/post-Covid-19 era is evaluated to lie in the fact that this subject helped society and individuals cultivate diverse competencies necessary to pursue well-being. Finally, this study suggests a conceptual framework necessary to develop a discourse on home economics education as 'happiness and well-being education.' Additionally, a conceptual framework describing the unique thinking and execution process that learners will represent in the course of learning of home economics that implements well-being education is suggested. In the follow-up studies, it is expected that the discourse on well-being education in home economics education will be verified by empirical studies.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.361-381
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• 2023

Research on corporate bankruptcy prediction has been focused on financial information. Since the company's financial information is updated quarterly, there is a problem that timeliness is insufficient in predicting the possibility of a company's business closure in real time. Evaluated companies that want to improve this need a method of judging the soundness of a company that uses information other than financial information to judge the soundness of a target company. To this end, as information technology has made it easier to collect non-financial information about companies, research has been conducted to apply additional variables and various methodologies other than financial information to predict corporate bankruptcy. It has become an important research task to determine whether it has an effect. In this study, we examined the impact of electronic payment-related information, which constitutes non-financial information, when predicting the closure of business operators using electronic payment service and examined the difference in closure prediction accuracy according to the combination of financial and non-financial information. Specifically, three research models consisting of a financial information model, a non-financial information model, and a combined model were designed, and the closure prediction accuracy was confirmed with six algorithms including the Multi Layer Perceptron (MLP) algorithm. The model combining financial and non-financial information showed the highest prediction accuracy, followed by the non-financial information model and the financial information model in order. As for the prediction accuracy of business closure by algorithm, XGBoost showed the highest prediction accuracy among the six algorithms. As a result of examining the relative importance of a total of 87 variables used to predict business closure, it was confirmed that more than 70% of the top 20 variables that had a significant impact on the prediction of business closure were non-financial information. Through this, it was confirmed that electronic payment-related information of non-financial information is an important variable in predicting business closure, and the possibility of using non-financial information as an alternative to financial information was also examined. Based on this study, the importance of collecting and utilizing non-financial information as information that can predict business closure is recognized, and a plan to utilize it for corporate decision-making is also proposed.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.302-318
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• 2023

The purpose of this study was to study to the effect of presenting SBF questions on the level of conceptual achievement and eye movement of elementary students in seasonal constellation learning that requires systems thinking. In this study, the effectiveness of SBF questions was divided into experimental groups and comparison groups, and scientific texts with different question types were presented to analyze the level of conceptual achievement and differences in eye movement of sixth-grade elementary students. Data analysis quantitatively analyzed the pre- and post-test results of the developed concept test paper and the eye movement data when learning scientific texts related to seasonal constellations. As a result of the study, first, the SBF question was a valid learning strategy for learning seasonal constellations. The SBF question showed a statistically significant difference (p<0.05) in the pre- and post-test between groups, and a statistically significant difference (p<0.001) in the pre- and post-test within the group. Second, SBF questions had a positive effect on students' learning by inducing learners with low preconceptions to area of interest that help them achieve concepts. In other words, when presenting SBF questions with visual data from a space-based perspective, it was confirmed based on the results of eye movement analysis that there was a significant difference in total fixation count (p<0.01) of learners. On the other hand, for learners with high scientific preconceptions, the effect of exploration was not significant because the preconceptions of the learners themselves acted as a hard core rather than the effect of SBF questions. This study is different from existing seasonal constellation learning studies in that it provides quantitative data through pre- and post-test and eye movement analysis in the seasonal constellation learning process, and can help elementary students learn seasonal constellations.

• Korea Science and Art Forum
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• v.21
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• pp.105-116
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• 2015

This study intended to give helps in planning a specialized exhibition by carrying out a survey objecting to KOREA PACK 2015 attendees including visitors who possessed mobile coupons after finishing advance registration through on-line, and then investigating, analyzing satisfactions of attendees together with effects of the specialized exhibition using IT technology. As a lot of relevant preceeding researches have been made by focussing on exhibition organizer and exhibitors, the viewpoints of attendees at the specialized exhibition using IT conversing technology such as mobile and etc. were to be investigated and analyzed. Thus, this research tried to do an empirical identification on effects of the exhibition by analyzing relations between its watching forms and satisfactions including a survey on the on-line PR route utility of IT technology in addition to visiting motives of attendees who watched the exhibition. A summarization of the current study is followed: First, in case of attending in the exhibition for specific purposes, they searched related information positively, and were shown as doing information gathering behaviors and also high possibility on purchases was confirmed. Second, it was confirmed that positive attendees had decision-making on purchases. This finding means that attendees who watch the specialized exhibition have authority and responsibility of being able to purchase in many cases, so methods of improving sales by effectively doing PR on own products and technical competitiveness in the exhibition are necessary to exhibitors. Third, attendees who have specific purposes showed higher satisfactions on the exhibition than general visitors, but satisfactions on consultation, staff attitudes, and facility were turn out to be higher than providing related information on products or technology. Accordingly, the necessity of improving this outcome was confirmed. Therefore, exhibitors have to endeavor in providing more advanced services to attendees of the exhibition by grasping technical trends in advance as well as cultivating professional staff who can promote products well.

• Resources Recycling
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• v.32 no.1
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• pp.50-59
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• 2023

The amount of dust generated during the dissolution of scrap in an electric arc furnace is approximately 1.5% of the scrap metal input, and it is primarily collected in a bag filter. Electric arc furnace dust primarily consists of zinc and ion. The processing of zinc starts with its conversion into pellet form by the addition of a carbon-based reducing agent(coke, anthracite) and limestone (C/S control). These pellets then undergo reduction, volatilization, and re-oxidation in rotary kiln or RHF reactor to recover crude zinc oxide (60%w/w). Next, iron is discharged from the electric arc furnace dust as a solid called Fe clinker (secondary by-product of the Fe-base). Several methods are then used to treat the Fe clinker, which vary depending on the country, including landfilling and recycling (e.g., subbase course material, aggregate for concrete, Fe-source for cement manufacturing). However, landfilling has several drawbacks, including environmental pollution due to leaching, high landfill costs, and wastage of iron resources. To improve Fe recovery in the clinker, we pulverized it into optimal -sized particles and employed specific gravity and magnetic force selection methods to isolate this metal. A carbon-based reducing agent and a binding material were added to the separated coarse powder (>10㎛) to prepare briquette clinker. A small amount (1-3%w/w) of the briquette clinker was charged with the scrap in an electric arc furnace to evaluate its feasibility as an additives (carbonaceous material, heat-generating material, and Fe source).

• Sleep Medicine and Psychophysiology
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• v.29 no.1
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• pp.21-28
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• 2022

Objectives: Our study aimed to investigate the relationship between the anxiety at first year and chronotype and sleep quality at third year in medical students. We also investigated the association between sleep quality, chronotype, depression and resilience at third year. Methods: Fifty two medical students (36 males, 69%, aged 21 ± 0.93) in first year, and forty four medical students (31 males, 70.5%, aged 23.05 ± 0.99) at third year answered Beck Depression Inventory 2, Beck anxiety inventory, Insomnia severity index-K, Composite scale of morningness and Conner-Davidson Resilience scale-10. Multiple linear regression analysises were performed to identify predictors of chronotype, sleep quality and resilience. Results: Higher anxiety (β = -0.434, p = 0.006) at first year was significant predictor of eveningness at third year, while lower anxiety score (β = 0.606, p < 0.001) at first year was significant predictor of sleep quality at third year. Lower sleep quality (β = -0.314, p = 0.042) and eveningness (β = 0.315, p = 0.041) were associated with low resilience at third year. Also, Lesser depression (β = -0.717, p < 0.001) was associated with higher resilience at third year. Conclusion: Our study showed that higher anxiety in first year had significantly related with eveningness and poor sleep quality at third year. In addition, higher sleep quality, morningness and less depression had significantly associated with better resilience at third year.