• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.501-513
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• 2019

In this study, which is based on the findings of the preceding studies, the researchers determined social support and Career Decision Self-efficacy as the key influencing variables for the successful Career Preparation Activities, to analyze the relationship between Career Preparation Activities and these variables, while identifying the mediating effect of Career Decision Self-efficacy in the relationship between social support and Career Preparation Activities. In addition, there is an objective to provide effective career counseling materials. For this study, a total of 174 North Korean adolescent defectors, who were in their middle and high schools, were interviewed and the resultant data were analyzed the data based on the questionnaire data of 204 copies from March 12 to 19, 2019. For the analysis of the data, SPSS and AMOS statistical suites were used to verify the hypothesis. The result of the analysis showed that, first, in the relationship between the social support, Career Decision Self-efficacy, and Career Preparation Activities of the North Korean adolescent defectors social support, Career Decision Self-efficacy, and Career Preparation Activities were all positively related. Especially, Career Decision Self-efficacy has been identified as the variable that is highly related to Career Preparation Activities. Second, rather than social support(${\beta}=.107$), Career Decision Self-efficacy(${\beta}=.388$) turned out to have more profound direct influence on Career Preparation Activities. Third, social support did not influence Career Preparation Activities directly(${\beta}=.107$, p>.05) but completely intermediated Career Decision Self-efficacy to influence Career Preparation Activities(Indirect effect=.307, p<.05, Z-value=2.924, p<.01). The findings of this study show that, in order to enhance the Career Preparation Activities of the North Korean adolescent defectors, it is necessary to examine how they perceive the emotional, informational, material, and evaluative supports from the surrounding environment are perceived and identify the abilities, values, and career desires of themselves through a behavioral planning that can establish a professional and value system in accordance with them.

• Korean Journal of Heritage: History & Science
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• v.54 no.2
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• pp.240-253
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• 2021

Various decipherment technologies, including manual rubbing, have been continuously applied to the Goguryeo Stele in Chungju. However, an official document for advanced decipherment is required as there remain characters to be deciphered. This study focuses on interdisciplinary digital decipherment using digital visualization results based on reflectance transformation imaging and three-dimensional scanning. On that basis, the joint decipherment document in 2019 is classified into eight types according to character changes from 1979 to 2000, and decipherment achievements are discussed. Important outcomes of the joint decipherment document include a new interpretation of four existing characters and the identification of 28 new characters. Additionally, 68 characters on the front face and 20 on the left face, which are listed differently in previous decipherment documents, are determined to be a single character through a consensus process. Compared to the previous decipherment document, the "decision" character is increased by a total of 89 characters (22.6%), and the "different opinion" character is decreased by 126 characters (32.0%). Thus, this digital decipherment greatly contributes to the reexamination of the Goguryeo Stele in Chungju and complements the previous decipherment document through reflectance transformation imaging and three-dimensional scanning. However, continuous research is necessary to enhance decipherment rates, since 123 characters (31.3%) are yet to receive decipherment. In the future, decipherment advancement regarding the Goguryeo Stele in Chungju should be based on convergence research between the humanities and science. Furthermore, it seems that researchers must make constant efforts to apply new imaging analysis technology and to develop customized technology for decipherment.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• The Journal of Korean Academy of Sensory Integration
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• v.19 no.1
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• pp.69-82
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• 2021

Objective : This recent work intended to provide basic information for researchers and practitioners related to occupational therapy about Developmental Coordination Disorder (DCD) in South Korea. The previous research of screening DCD and the effects of intervention programs were reviewed. Methods : Peer-reviewed papers relating to DCD and published in Korea from January 1990 to December 2020 were systematically reviewed. The search terms "developmental coordination disorder," "development coordination," and "developmental coordination" were used to identify previous Korean research in this area from three representation database, the Research Information Sharing Service, Korean Studies Information Service System, and Google Scholar. We found a total of 4,878 articles identified through the three search engines and selected seventeen articles for analysis after removing those that corresponded to the overlapping or exclusion criteria. We adopted "the conceptual model" to analyze the selected articles about DCD assessment and intervention. Results : We found that twelve of the 17 studies showed the qualitative level of Level 2 using non-randomized approach between the two groups. The Movement Assessment Battery for Children and its second edition were the most frequently used tools in assessing children for DCD. Among the intervention studies, the eight articles (47%) were adopted a dynamic systems approach; a normative functional skill framework and cognitive neuroscience were each used in 18% of the pieces; and 11% of the articles were applied neurodevelopmental theory. Only one article was used a combination approach of normative functional skill and general abilities. These papers were mainly focused on the movement characteristics of children with DCD and the intervention effect of exercise or sports programs. Conclusion : Most of the reviewed studies investigated the movement characteristics of DCD or explore the effectiveness of particular intervention programs. In the future, it would be useful to investigate the feasibility of different assessment tools and to establish the effectiveness of various interventions used in rehabilitation for better motor performance in children with DCD.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.60-76
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• 2022

This study presents a software full setup and the following test execution times in a Linux cluster for the United Kingdom Earth System Model (UKESM) and then compares the model results from control and experimental simulations of the UKESM relative to various observations. Despite its low resolution, the latest version of the UKESM can simulate tropospheric chemistry-aerosol processes and the stratospheric ozone chemistry using the United Kingdom Chemistry and Aerosol (UKCA) module. The UKESM with UKCA (UKESM-UKCA) can treat atmospheric chemistryaerosol-cloud-radiation interactions throughout the whole atmosphere. In addition to the control UKESM run with the default CMIP5 SO₂ emission dataset, an experimental run was conducted to evaluate the aerosol effects on meteorology by changing atmospheric SO₂ loading with the newest REAS data over East Asia. The simulation period of the two model runs was 28 years, from January 1, 1982 to December 31, 2009. Spatial distributions of monthly mean aerosol optical depth, 2-m temperature, and precipitation intensity from model simulations and observations over East Asia were compared. The spatial patterns of surface temperature and precipitation from the two model simulations were generally in reasonable agreement with the observations. The simulated ozone concentration and total column ozone also agreed reasonably with the ERA5 reanalyzed one. Comparisons of spatial patterns and linear trends led to the conclusion that the model simulation with the newest SO₂ emission dataset over East Asia showed better temporal changes in temperature and precipitation over the western Pacific and inland China. Our results are in line with previous finding that SO₂ emissions over East Asia are an important factor for the atmospheric environment and climate change. This study confirms that the UKESM can be installed and operated in a Linux cluster-computing environment. Thus, researchers in various fields would have better access to the UKESM, which can handle the carbon cycle and atmospheric environment on Earth with interactions between the atmosphere, ocean, sea ice, and land.

• 한국노년학
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• v.41 no.4
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• pp.547-566
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• 2021

The purpose of this study is to analyze the effect of social activities on healthy life expectancy (HLE) by gender difference. HLE implies an estimate of how long an individual can expect to live in full health or without disease and/or disability. Morbidity, mortality, and functional health status usually have been known as key variables. Many researchers have tried to investigate factors affecting HLE in countries level by performing comparative analyses. In micro level, there have been some studies about social factors affecting HLE in individual level. However, few studies are found focusing on the relationship between HLE and social activities. This study anlayzes 4,029 over 65 years of age from the first wave (2006) to the seventh wave (2018) of the Korean Longitudinal Study of Ageing (KLoSA), which is a national panel data collected by Korea Employment Information Service. The data has been collected as a part of social and economic policies planning for Korean government. HLE was measured by life period without disease or disability. One of findings is that male older adults (76.9 yrs) show higher HLE in comparing to female group (75.3 yrs). Female group appeared to be more likely to have higher incidence rate and disorders. Another finding indicates that age, number of chronic diseases, and subjective health status affect HLE of both groups. Finally, regarding social activities, religion affiliated activities appear to significantly affect HLE of both groups. In case of male older adults, alumni or hometown gathering also appeared another activities affecting HLE. This study indicates that the effect of social activities types on HLE among older adults appears differently by gender. Further, unlikely of longer life expectancy among female older adults as known, HLE shows a reverse estimate, longer healthy life expectancy among male older adults. This finding may imply that later life of female older adults shows lower quality of life in comparing to that of male group, even if female life expectancy has been higher. This study encourages to develop more social activity programs for older adults in community level. Specifically, more attention is required to planning for programs targeting female older adults.

• Journal of the Korean Chemical Society
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• v.67 no.5
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• pp.378-392
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• 2023

The purpose of this study is to analyze the pre-service chemistry teachers' cognition of the nature of model in process of designing and developing models using technology. For this purpose, 19 pre-service chemistry teachers' in the 3rd grade of a education college located in the central region observe experimental phenomena related to Boyle's law presented in the 7th grade science textbook and researchers required the design and development of a model related to the observed experimental results using technology. Based on previous studies, the nature of model were classified into two aspect: 'Representational aspect' and 'Explanatory aspect'. The 'Representational aspect' was classified into 'Representation', 'Abstraction', and 'Simplification', and the 'Explanatory aspect' was classified into 'Analysis', 'Interpretation', 'Reasoning', 'Explanation', and 'Quantification'. The pre-service chemistry teachers' cognition were analyzed by the classification. As a result of the study, the 'Representation' of the 'expressive aspect' was uniformized in the form of space that changes in volume, and the pressure was expressed as the Brightness inside the cylinder or frequency of color change of particles for 'Abstraction'. In the case of 'Simplification', the particle collision was expressed as a perfectly elastic collision, but there was a group that could not simply indicate the type of particle. In the 'Explanatory aspect', in the case of 'Analysis', volume was classified as a manipulated variable, and in the case of 'Interpretation', most groups analyzed the change in pressure through the collision of gas particles. However, the cognition involved in 'Reasoning' was not observed much. In the case of 'Explanation', there were groups that did not succeed in explanation because the area where the particles collided was not set or incorrectly set, and in the case of 'Quantification', there was a group that formulated the number of collisions per unit time, and on the contrary, there was a group that could not quantify the number of collisions because they could not be expressed in numbers.

• Korean Journal of School Psychology
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• v.9 no.3
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• pp.485-503
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• 2012

Academic engagement has been known as a strong predictor of students' cognitive and affective outcomes in an educational context. Despite increasing interest and theoretical usefulness of this construct, a few researchers seem to be interested in the validation of instruments to measure academic engagement for Korean students. Thus, this study would like to introduce one of academic scales widely used, UWES-S(Utrecht Work Engagement Scale-Student) (Schaufeli et al., 2002a: 2002b) and to validate the UWES-S for Korean college students. To validate the Korean version of the UWES-S, 651 college students (285 for Field Trial, 366 for Main Study) were used. The procedure is as follows. First, we used an integrated adaptation procedure to produce a Korean version of the UWES-S. Second, EFA(exploratory factor analyses) was applied to explore the factor structure of the UWES-S on the field trial data. Third, the psychometric properties of the UWES-S items were examined by graded response model(GRM). Also CFA(confirmatory factor analysis) was used to examine its internal construct validity for the data from the main study. Finally, the external validity of the UWES-S was scrutinized with the related variables such as academic motivation and satisfaction. As a result, the Korean version of the UWES-S with 13 items was accepted that the four items were excluded from its original version. Second, the internal validity was supported that the 3 factor CFA model(vigor, dedication, absorption) fit the data well. Third, we supported the partial mediation model that academic engagement played as a mediating variable between academic motivation(internal/external) and academic satisfaction. Finally, the differences between a validation of UWES-S for Korean college and high school students, the necessity of construct equivalence testing, and direction for future research of scale validating were discussed.

• Korean Journal of Culture and Social Issue
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• v.23 no.2
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• pp.131-157
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• 2017

Loving-kindness & compassion meditation (LCM) is one of the popular intervention on clinical setting to cultivate loving-kindness & compassion for self and other. Shame is known for unconscious and implicit emotion including negative self-concept. Some researchers suggest that people with high shame have difficulty in cultivating loving-kindness & compassion toward oneself because of shame including the negative self-critic. In this research, it is explored the influence of shame for the object of LCM. There are 2 experiments to find out the answer to this question. In experiment 1, participants (N = 108) are randomly assigned to two conditions. The one condition is loving-kindness meditation for self, and the other is loving-kindness meditation for positive others. Dislike and engagement from participants about loving-kindness meditation instruction are measured after meditation for 8 minutes. From the experiment 2, loving-kindness meditation is replaced with compassion meditation from the design of experiment 1. This experiment is conducted because of psychological differences between loving-kindness and compassion. Participants (N = 116) are randomly assigned to two conditions, compassion meditation for self and positive others, respectively. The results of experiment 1 show that dislike of loving-kindness meditation for self seems to high when people have high shame, but shame does not have an influence on engagement. For loving-kindness meditation for positive others, shame seems to not affect on dislike and engagement about loving-kindness meditation instruction. The results of experiment 2 show that dislike is higher for self than for positive others about compassion meditation for people with high shame, but shame does not affect on engagement. For discussion, it is suggested that shame has special features of emotion. For the future, we discuss the therapeutic strategy for people with negative self-concept.

• Korean Journal of Culture and Social Issue
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• v.11 no.3
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• pp.91-119
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• 2005

This study examines the perception and trust of Korean society and people among students and adults using the indigenous psychological analysis. A matched sample of 1,107 participants, consisting of 369 students, their mothers and their fathers completed a questionnaire developed by the present researchers. The results indicate that parents more likely than adolescents to hold negative views of Korean society. Adults are more likely than adolescents to view Korean society as showing high ingroup favoritism, to be insecure, to be conservative, to be corrupt, and to have social inequities. Both groups agree that Korean society is not rational nor democratic, but believe that it has the potential for progress. Second, parents are more likely to hold negative views about Korean people. Adults are more likely than adolescents of viewing Korean people as overly conscious about social face, emotional, selfish, exclusionary, and conceited. Both adolescents and their parents agree that Koreans are cooperative, full of jung (deep affection and attachment), and sincere. Third, adults are less likely to trust Korean institutions than adolescents. Adults are less likely than adolescents to trust National Assembly, political parties, and unions. Adolescents are more likely than their parents to trust family members, school friends, teachers, and government employees. These results indicate that adolescents have higher trust of Korean society and people than their parents. Fifth, the overall results indicate that both group perceive Korean society as showing high ingroup favoritism and corruption. In terms of Korean people, respondents had a more balanced view of perceiving them as highly sensitive to social face and being emotional, while also perceiving them as cooperative and full of jung. The trust of Korean institutions were generally low, especially the National Assembly and political parties. However, the trust of family was very high, followed by trust of school friends and teachers. The trust of government employees was low and this was especially the case for politicians.