• Journal of Environmental Health Sciences
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• v.28 no.5
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• pp.13-21
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• 2002

This study analyzed the characteristic of basic river structure, a flood level, the tree planting recommendation and syn thetic design, in order to establish a basic plan for preparing a natural practical area of environmental ecosystem at Bukchun and its surroundings. It was also investigated based on the opinion of citizens, geographical condition and the equipment/utilization examination of Bukchun which were included ecological circumstances, and thus provided a composite item for managing the natural river. This study also considered the development of the river in terms of culture, environment and ecology concept. The results were summarized as followed. Bukchun showed that the speed of a funning fluid is very fast on a period of flood. but very slow in a period of water shortage about 0.02 m/s. To prevent the speed change of a running fluid by a steep slope in a riverbed, there established Dongchun sluice gates under a bridge, including three sluice gates under a bridge, but there occurred extremely a riverbed erosion and corrosion section. The result of comparison between real flood degree and prediction flood data, there should perform a countermeasure the riverbed structure regulation of this area. Also, it was needed an exhaustive flood management in summer. According to the Bukchun and Hyungsangang riverbed investigation, there were needed preparation for natural/practical area and ecology Park development in the future. This study was investigated tree Planting/flower/blossom around the Bukchun and its surroundings. It was recommended willow, Italian poplar, bamboos and cherry blossoms in the Hyungsangang and Bukchun. There exist together historical space, environment space iud have enough possibility both natural learning space and civil rest space. And, it is possible to compose ecology natural learning and experimental area.

• Journal of The Korean Association For Science Education
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• v.17 no.2
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• pp.139-148
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• 1997

This study investigated the influences of the cooperative learning strategies upon students' achievement and their perceptions of learning environments in a middle school physical science course. Prior to instruction, the Group Assessment of Logical Thinking was administered, and its score was used as a blocking variable. Mid-term examination score was used as a covariate. For the treatment group with heterogeneous grouping, cooperative learning instruction (the Learning Together model) was used, which emphasized group reward, individual accountability, and role division. For the control group, traditional instruction was used. After instruction, an achievement test consisting of three subtests (knowledge, understanding, and application), and the perception questionnaire of classroom and laboratory environments, were administered. ANCOVA results revealed that there was a significant interaction between instruction and the level of logical reasoning ability although there were no significant differences in all three subtest scores of the achievement test. For the concrete operational reasoners, the treatment group performed better in the subtests of understanding and application than the control group. For students at the formal and transition levels, however, the treatment group scored lower than the control group. Significant interactions were also found in the perceptions of classroom environment and laboratory environment. For the concrete operational reasoners, the treatment group showed more positive perception than the control group. For the students at the formal and transition levels, the control group had positive perception than the treatment group. Educational implications are discussed.

• The Korean Journal of Pain
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• v.30 no.4
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• pp.258-264
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• 2017

Background: Pulpal pain is one of the most common and severe orofacial pain conditions with considerable adverse effects on physiological processes including learning and memory. Regular exercise is known to be effective on cognitive function as well as pain processing in the central nervous system. Here, the possible effects of regular exercise on pulpal pain response as well as pain-induced changes in learning and memory efficiency in rats were investigated. Methods: Twenty-four male Wistar rats were randomly assigned to the control, capsaicin, exercise, and exercise plus capsaicin groups. Rats in exercise groups were forced to run on a treadmill with a moderate exercise protocol for 4 weeks. Capsaicin was used to induce dental pulp pain. Passive avoidance learning and memory performance was assessed by using a shuttle box apparatus. Results: According to the results, regular exercise could decrease the time course of capsaicin-induced pulpal pain (P < 0.001). Moreover, in capsaicin-treated rats, passive avoidance acquisition was impaired as compared to the control (P < 0.05) and exercise (P < 0.001) groups. Additionally, regular exercise before capsaicin injection could attenuate capsaicin-induced memory impairments (P < 0.05). Conclusions: Taken together, the present data showed that regular exercise has inhibitory effects on capsaicin-induced pulpal pain as well as pain-induced cognitive dysfunction in rats.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.115-136
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• 2014

The game industry has grown steadily and the online game has become one of the most attractive game segments for its remarkable growth. Customer management in the online game industry, however, has received little attention from the academic field. The purpose of this study is to analyze the drivers of customer defection in the online game setting and suggest not only theoretical but also managerial insights into increasing customer retention rates. Prior to empirical analysis, the authors hypothesized that 3 variables of interests (Learning, Playing, Achievement) would explain the customer defection according to preceeding researches. To demonstrate these hypotheses, the authors obtained data from one of the biggest game publishers in Korea, and the empirical analysis model was developed considering context of research settings. The results of analyses provide the following insights. First, the key behavioral variables of Learning, Playing, and Achievement play substantial roles in explaining the customer defection. Next, the effects of these variables vary between customer types: novice and experienced customers. The defection decisions by novice customers are predicted by all key behavioral variables and Playing serves as the most influential indicator of the defection decisions. However, experienced customers are influenced by Playing and Achievement, while Learning has no impact on the defection decisions. Finally, the authors investigated hypothetical customer retention strategies, using the empirical results. The market outcomes indicate that the customer retention strategies work well with novice customers and it is hard-to-impossible to prevent experienced customers from defection using their behavioral data. These findings together deliver several meaningful insights to management as follow. First, the management should support customers to get involved in Learning activities at the very first stage. Second, customer's Achievement and appropriate compensation for it would work as defection barriers. Last, to optimize the outcomes of firm's marketing investments, it is better to focus on retention of novice users not experienced ones.

• Korean Journal of Social Welfare
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• v.45
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• pp.341-373
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• 2001

This study seeks to identify the reform of vocational education plans so as to bring about a seamless transition from school to work. It puts forward a number of suggestions based upon an analysis of vocational education policies in Korean and U.S. schools, concerning the government's role, partnerships between education and industry, the educational system, curriculum and work-based learning. First, not only government initiatives but also close partnerships between education and industry are essential to help vocational education in school the transition to employment. Education and industry should work closely together to standardize certificate related skills and to have these skills reflected in the curriculum. Also the government should strive to provide guidelines for work-based learning and formulate standards for supervision and evaluation. Second, to facilitate the school to work transition, comprehensive schools should be promoted so that students have access to a greater ranger of vocational education. At the same time, an assessment system that certifies a mastering of the basic skills of those who undergo the education should be introduced, and it should be related to earn these certificates. Third, standardized vocational skills should be included in the curriculum so that students can acquire skills that are useful for industry. All the students in vocational and general high schools should have access both to general education, the foundation for lifelong learning and for employ ability, and to basic occupational skills which empower students in dealing with rapid changes of technology. Also a range of specialized vocational curricula should be offered so that students can opt for more specialized occupations; and they can select careers appropriate to their capability. Fourth, so that all students to have the opportunity to take part in work-based education, which is closely related to employment, various work-based learning programs should be offered to meet the needs of students and their educational conditions. Companies should for their part train students thoroughly in accordance with the standards of work-based education. In addition, supervisors should be stationed both in schools and companies in order to administer the students' work-based learning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.27-32
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• 2019

Research that implements the classification process through Deep Learning algorithm, one of the outstanding human abilities, includes a unimodal model, a multi-modal model, and a multi-modal method using music videos. In this study, the results were better by suggesting a system to analyze each song's spectrum into short samples and vote for the results. Among Deep Learning algorithms, CNN showed superior performance in the category of music genre compared to RNN, and improved performance when CNN and RNN were applied together. The system of voting for each CNN result by Deep Learning a short sample of music showed better results than the previous model and the model with Softmax layer added to the model performed best. The need for the explosive growth of digital media and the automatic classification of music genres in numerous streaming services is increasing. Future research will need to reduce the proportion of undifferentiated songs and develop algorithms for the last category classification of undivided songs.

• Asia-Pacific Journal of Business
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• v.13 no.3
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• pp.293-309
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• 2022

Purpose - The purpose of this study is to explore the possibility of predicting the degree of smartphone overdependence based on mobile phone usage patterns. Design/methodology/approach - In this study, a survey conducted by Korea Internet and Security Agency(KISA) called "problematic smartphone use survey" was analyzed. The survey consists of 180 questions, and data were collected from 29,712 participants. Based on the data on the smartphone usage pattern obtained through the questionnaire, the smartphone addiction level was predicted using machine learning techniques. k-NN, gradient boosting, XGBoost, CatBoost, AdaBoost and random forest algorithms were employed. Findings - First, while various factors together influence the smartphone overdependence level, the results show that all machine learning techniques perform well to predict the smartphone overdependence level. Especially, we focus on the features which can be obtained from the smartphone log data (without psychological factors). It means that our results can be a basis for diagnostic programs to detect problematic smartphone use. Second, the results show that information on users' age, marriage and smartphone usage patterns can be used as predictors to determine whether users are addicted to smartphones. Other demographic characteristics such as sex or region did not appear to significantly affect smartphone overdependence levels. Research implications or Originality - While there are some studies that predict smartphone overdependence level using machine learning techniques, but the studies only present algorithm performance based on survey data. In this study, based on the information gain measure, questions that have more influence on the smartphone overdependence level are presented, and the performance of algorithms according to the questions is compared. Through the results of this study, it is shown that smartphone overdependence level can be predicted with less information if questions about smartphone use are given appropriately.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.4
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• pp.691-708
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• 2022

As the technology of machine learning and deep learning became common, it began to be applied to research on anomaly(abnormal) detection of industrial control systems. In Korea, the HAI dataset was developed and published to activate artificial intelligence research for abnormal detection of industrial control systems, and an AI contest for detecting industrial control system security threats is being conducted. Most of the anomaly detection studies have been to create a learning model with improved performance through the ensemble model method, which is applied either by modifying the existing deep learning algorithm or by applying it together with other algorithms. In this study, a study was conducted to improve the performance of anomaly detection with a post-processing method that detects abnormal data and corrects the labeling results, rather than the learning algorithm and data pre-processing process. Results It was confirmed that the results were improved by about 10% or more compared to the anomaly detection performance of the existing model.

• The Journal of Bigdata
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• v.7 no.2
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• pp.11-29
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• 2022

Pre-trained language models are the most important and widely used tools in natural language processing tasks. Since those have been pre-trained for a large amount of corpus, high performance can be expected even with fine-tuning learning using a small number of data. Since the elements necessary for implementation, such as a pre-trained tokenizer and a deep learning model including pre-trained weights, are distributed together, the cost and period of natural language processing has been greatly reduced. Transformer variants are the most representative pre-trained language models that provide these advantages. Those are being actively used in other fields such as computer vision and audio applications. In order to make it easier for researchers to understand the pre-trained language model and apply it to natural language processing tasks, this paper describes the definition of the language model and the pre-learning language model, and discusses the development process of the pre-trained language model and especially representative Transformer variants.

• Research in Community and Public Health Nursing
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• v.32 no.4
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• pp.485-496
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• 2021

Purpose: This study attempted to obtain basic data for developing a global nursing practice education program. Methods: The data collection period was from July 2 to 11, 2020. The study participants were professors with experience in design, operation and management of global nursing practice education or experts with experience in international cooperation projects, and 8 people who agreed to participate in focus group interview (FGI). FGI was conducted twice in total and the directed content analysis method was applied. Results: The categories of 'practice design' are 'growing as a global nursing leader' and 'working together towards one goal'. The categories of 'practice operation' are 'watching, listening, and performing', 'self-directed organizing from preparation to finishing', and 'learning the value of participation rather than grades'. The category of 'practice management' is 'one's own weight to carry'. Conclusion: Global nursing practice education aims one goal - growing as a global nursing leader - and is self-directed course from preparation to an end with watching, listening and performing together. It is about learning the value of participation rather than grades. This can be used as basic data for the design, operation and management of global nursing practice education in the future.