• Journal of Digital Convergence
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• v.16 no.3
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• pp.353-362
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• 2018

The purpose of this study was to investigate the effect of character strength and self-efficacy on subjective happiness of adult learners of distance nursing education. The subjects were 261 adult learners of Bachelor Science in nursing course for Registered Nurse of a national open university. The mean score of subjective happiness of subjects was a little lower. 'Transcendence and Humanity' among Character Strength was the highest and 'Justice' was the lowest. Multiple regressions showed that positive integrity, hardiness, and perceived health status explained 38.0% of subjective happiness and positive integrity was the main influencing factor. The learning supporting strategies focusing on reinforcing these factors are needed to improve the subjective happiness of nurses who are continuing their learning through distance education.

• Journal of Information Technology Services
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• v.12 no.2
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• pp.1-12
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• 2013

A new form of software piracy known as digital piracy has taken the spotlight. Lost revenues due to digital piracy could reach 2,500 billion won in year 2010 alone. This paper examines the causal relationships among the attitude toward digital piracy, subjective norm, economic gain, political efficacy, school policy, etc, in a university setting. Results from survey responses indicate that the social norm and economic gain affect the attitude toward digital piracy, and that school policy influences the subjective norm as well as political efficacy. But, contrary to our expectation, political efficacy has been found to have no impact on the social norm and economic gain. Prior learning experiences have been shown to affect economic gain, but not the subjective norm. As a conclusion, the academic and practical implications of these findings are discussed.

• ETRI Journal
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• v.45 no.1
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• pp.75-92
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• 2023

Level 3 autonomous vehicles require conditional autonomous driving in which autonomous and manual driving are alternately performed; whether the driver can resume manual driving within a limited time should be examined. This study investigates whether the demographics and subjective driving tendencies of drivers affect the take-over performance. We measured and analyzed the reengagement and stabilization time after a take-over request from the autonomous driving system to manual driving using a vehicle simulator that supports the driver's take-over mechanism. We discovered that the driver's reengagement and stabilization time correlated with the speeding and wild driving tendency as well as driving workload questionnaires. To verify the efficiency of subjective questionnaire information, we tested whether the driver with slow or fast reengagement and stabilization time can be detected based on machine learning techniques and obtained results. We expect to apply these results to training programs for autonomous vehicles' users and personalized human-vehicle interfaces for future autonomous vehicles.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.1059-1065
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• 2020

In hospitals, nurses are subjectively determining the urine status to check the kidneys and circulatory system of patients whose statuses are related to patients with kidney disease, critically ill patients, and nursing homes before and after surgery. To improve this problem, this paper proposes a urine spectrum analysis system which clusters urine test results based on a hybrid machine learning model consists of unsupervised learning and supervised learning. The proposed system clusters the spectral data using unsupervised learning in the first part, and classifies them using supervised learning in the second part. The results of the proposed urine spectrum analysis system using a mixed model are evaluated with the results of pure supervised learning. This paper is expected to provide better services than existing medical services to patients by solving the shortage of nurses, shortening of examination time, and subjective evaluation in hospitals.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.69-74
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• 2005

In this paper, we suggested user assistant soft computing method for 3D effect optimization. In order to maximize 3D effect of image, intervals among cameras have to be set up properly according to distance between cameras and an object. Two data such as interval and distance was obtained to use in neural network as the data for learning. However, if the data for learning was obtained by only human's subjective views, it could be that the obtained data was not optimal for learning because the data had an accidental ewer To obtain optimal data lot learning, we added candidature data to obtained data through data analysis, and then selected the most proper data between the candidature data and the obtained data for learning in neural network. Usually, 3D effect of image was affected by both distance from an object to cameras and an object size. Therefore, we suggested fuzzy inference model which was able to represent two factors like distance and size. Candidature data was added by fuzzy model. In the simulation result, we verified that the mote the obtained data was affected by human's subjective views, the more effective the suggested system was.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.1069-1078
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• 2013

The paper is about teaching culture in a language learning. There are many teachers who are afraid of teaching foreign language with culture. They are delighted to teach politics, economics, history, art and literature as objective culture. But they are hesitant to teach subjective culture which is connected with a communication competency. The paper suggests three stages to instruct culture in a schoolroom. The first stage, it is growing out of the self-centered view. The second step, be developing self-consciousness through comparing mother culture with target culture. The last stage, it has to response to appropriately target culture. The teaching materials for the model suggested are two movies. Because the cultural aspects in the moves are subjective culture, so it has something in common with target cultural situations in a language learning. This method which is teaching culture in a the language learning has the advantage of being easy to teachers and learners. Most students like to watch a movie. The teaching material is The Chronicles of Narnia : The Lion, the Witch and The Wardrobe와 Guess Who?. I hope that this suggestion for cultural teaching is helpful for understanding each other.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.139-146
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• 2022

The purpose of this study was to confirm the relationship between the subjective symptoms of smartphone addiction and visual display terminal syndrome in nursing college students and learning flow in the COVID-19 pandemic. For the collection of materials, the materials of the final 134 people were analyzed by collecting the students at the nursing colleges located in S city and M city for convenience. The collected materials were subjected to descriptive statistics, t-test, ANOVA, and Pearson's correlation coefficients using the SPSS / WIN 26 program. As a result of this study, the learning flow of nursing college students was negative correlated to the tendency of smartphone addiction and the subjective symptoms of visual display terminal syndrome. Therefore, to improve the learning flow of nursing college students, it is necessary to reduce the symptoms of smartphone addictive use and visual display terminal syndrome. The need for intervention and development of various effective programs for smart phone addiction management and display terminal syndrome management was suggested.

• Journal of the Korean Society of School Health
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• v.36 no.3
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• pp.113-125
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• 2023

Purpose: The purpose of this study is to develop a model for predicting mental health risk among adolescents based on health behavior information by employing a hybrid machine learning method. Methods: The study analyzed data of 51,850 domestic middle and high school students from 2022 Youth Health Behavior Survey conducted by the Korea Disease Control and Prevention Agency. Firstly, mental health risk levels (stress perception, suicidal thoughts, suicide attempts, suicide plans, experiences of sadness and despair, loneliness, and generalized anxiety disorder) were classified using the k-mean unsupervised learning technique. Secondly, demographic factors (family economic status, gender, age), academic performance, physical health (body mass index, moderate-intensity exercise, subjective health perception, oral health perception), daily life habits (sleep time, wake-up time, smartphone use time, difficulty recovering from fatigue), eating habits (consumption of high-caffeine drinks, sweet drinks, late-night snacks), violence victimization, and deviance (drinking, smoking experience) data were input to develop a random forest model predicting mental health risk, using logistic and XGBoosting. The model and its prediction performance were compared. Results: First, the subjects were classified into two mental health groups using k-mean unsupervised learning, with the high mental health risk group constituting 26.45% of the total sample (13,712 adolescents). This mental health risk group included most of the adolescents who had made suicide plans (95.1%) or attempted suicide (96.7%). Second, the predictive performance of the random forest model for classifying mental health risk groups significantly outperformed that of the reference model (AUC=.94). Predictors of high importance were 'difficulty recovering from daytime fatigue' and 'subjective health perception'. Conclusion: Based on an understanding of adolescent health behavior information, it is possible to predict the mental health risk levels of adolescents and make interventions in advance.

• Journal of the Korean Society of School Health
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• v.32 no.2
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• pp.125-134
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• 2019

Purpose: The purpose of this study was to investigate the effects of sedentary behavior on subjective health in Korean adolescents. Methods: This study is designed as a cross-sectional study. The study sample comprised of 60,040 middle and high school students primarily at the age of 12 to 17. Using data from the 14th (2018) Korea Youth Risk Behavior Web-based Survey, multiple logistic regression analysis was conducted. Results: The rate of engaging in sedentary behavior for less than 2 hours was 28.4% and for more than 4 hours was 28.2% in Korean adolescents. In the result from the logistic regression analysis, compared to engaging in sedentary behavior for 2 hours or less, the adjusted odds ratio was 1.15 for over 4 hours, with other factors controlled. Conclusion: It is necessary to actively develop and promote active leisure activities and limit excessive media exposure and supplementary learning for adolescents.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.44-51
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• 2003

Knowledge acquisition is a bottleneck in knowledge-based system implementation. Decision tree induction is a useful machine learning approach for extracting classification knowledge from a set of training examples. Many real-world data contain fuzziness due to observation error, uncertainty, subjective judgement, and so on. To cope with this problem of real-world data, there have been some works on fuzzy classification rule learning. This paper makes a survey for the kinds of fuzzy classification rules. In addition, it presents a fuzzy classification rule learning method based on decision tree induction, and shows some experiment results for the method.