• Korean Journal of Health Education and Promotion
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• v.26 no.2
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• pp.63-73
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• 2009

Objectives: The purpose of this study was to identify the degree of internet addiction and factors affecting internet addiction in elementary school students. Methods: A cross-sectional survey design was employed in this study. The subjects were 378 students who were recruited from 5th and 6th grade in five elementary schools in J city, Korea. Data were collected through a structured questionnaire. The data were analyzed using the SPSS Win 10.1 program. Results: Of the children, 51.9% reported being average online users, 45.5%, heavy online users, and 2.6%, internet addicted. The level of internet addiction of subjects correlated significantly with the behavioral activation system, behavioral inhibition system, family cohesion, and learned self-concept, but not family adaptability. Significant predictors influencing internet addiction were the behavioral activation system, learned self-concept, and family cohesion. These predictors accounted for 22% of variance in internet addiction. Conclusion: This study found that the behavioral activation system in personality aspects, family cohesion in the family system, and learned self-concept are primary factors that explain internet addiction among elementary students. We suggest these results be used to develop an online addiction prevention or treatment program.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.47-61
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• 1996

We propose a parallel neural network model in which patterns are clustered and patterns in a cluster are studied in a parallel neural network. The learning algorithm used in this paper is based on LVQ algorithm of Kohonen(1990) for clustering and ADALINE(Adaptive Linear Neuron) network of Widrow and Hoff(1990) for parallel learning. The proposed algorithm consists of two parts. First, N patterns to be learned are categorized into C clusters by LVQ clustering algorithm. Second, C patterns that was selected from each cluster of C are learned as input pattern of ADALINE(Adaptive Linear Neuron). Data used in this paper consists of 250 patterns of ASCII characters normalized into $8\times16$ and 1124. The proposed algorithm consists of two parts. First, N patterns to be learned are categorized into C clusters by LVQ clustering algorithm. Second, C patterns that was selected from each cluster of C are learned as input pattern of ADALINE(Adaptive Linear Neuron). Data used in this paper consists 250 patterns of ASCII characters normalized into $8\times16$ and 1124 samples acquired from signals generated from 9 car models that passed Inductive Loop Detector(ILD) at 10 points. In ASCII character experiment, 191(179) out of 250 patterns are recognized with 3%(5%) noise and with 1124 car model data. 807 car models were recognized showing 71.8% recognition ratio. This result is 10.2% improvement over backpropagation algorithm.

• Journal of Korean Philosophical Society
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• v.105
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• pp.95-126
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• 2008

We are all too aware of the ravages of scientific misconduct in the Korean academic community. Plagiarism and fabricated research have become an important issue after many figures such scientist Hwang Woo-suk, former Education Minister Kim Beong-joon and former Korea University President Lee Phil-sang were involved in research ethics scandals. Recent case of falsified data is the instance of Seoul University investigator Hwnag Woo-suk admittted full responsibility for the fabrication and use of false data in a paper published in 2005. Another important lessons learned by Hwang case were that the need of international accepted standards about research misconduct, the matter of authorship, proper allocation of credit, respect for human subjects in scientific research and conflict of interests. And Education Minister Kim Byong-joon have drawn the attention of the general public to the issue of self-plagiarism. Important lessons learned by Kim case were that the need of clear criteria on what is considered plagiarism and historical application. Most recently, Korea University president Lee Phil-sang plagiarized his pupils' academic work. Important lessons learned by Lee case were that the need of after penalty about research misconduct, research mentoring, and desirable whistleblowing. And I suggested three major lessons learned by synthesized review. The fist is the need of public system and institution, the second is the role of media, and the third is the need and direction of research ethics education. The government, universities and research centers are aware of the matters and lessons learned about reseach ethics of Hwang, Kim and Lee cases. And they suggest to set up education programs, guidelines and institutional measures for research ethics.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.932-937
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• 2003

When oil pressure of damper is lost or relative stiffness of spring drops in vibration system, it can be fatally dangerous situation. A fault diagnosis method for vibration system using Support Vector Machine(SVM)is suggested in the paper. SVM is used to classify input data or applied to function regression. System status can be classified by judging input data based on optimal separable hyperplane obtained using SVM which learns normal and abnormal status. It is learned from the relationship of system state variables in term of spring, mass and damper. Normal and abnormal status are learned using phase plane as in put space, then the learned SVM is used to construct algorithm to predict the system status quantitatively

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.485-486
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• 2019

Simulated driving behavior is an important aspect of realistic simulation systems. To simulate natural driving behavior, this paper proposes an imitation learning method based on active learning that combines demonstration and experience. Driving demonstrations are collected from human drivers in a driving simulator. A driving behavior policy is learned from these demonstrations. The driving demonstration dataset is augmented with new demonstrations that the original demonstrations did not contain, in the form of behaviors from another driving behavior policy learned from experience. The final driving behavior policy is learned from an augmented demonstration dataset.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.173-175
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• 2022

국방 각급 부대는 망연계 자료교환 시스템에 의해 인터넷과 국방망을 연계하여 데이터를 수집하고 있다. 또한, 안전한 국방 데이터수집과 빅데이터 환경조성을 위해 악성코드를 내재한 데이터들을 차단 및 분류하는 데이터 검열을 수행한다. 그러나 수집되는 데이터들이 새로운 악성코드를 내재할 경우, 현재 운용되고 있는 국방 시스템으로 식별하는 것이 불가능하여 외부로부터의 보안위협이 존재한다. 따라서 본 논문에서는 새로운 악성코드 위협에도 대응할 수 있는 Learned MAPE-K 기반 자료교환 시스템을 제안한다.

• The Mathematical Education
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• v.56 no.1
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• pp.1-17
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• 2017

The purpose of this study is to analyze the differences between the cognitive load of mathematics textbooks based on storytelling and traditional mathematics textbooks that are presented to students. In order to verify this, we have selected two 4th grade classes in elementary school that were identified as a homogeneous group through prior testing, and thus were separated into experimental group and comparative group. Then, without the teacher's lessons, the experimental group learned from mathematics textbooks based on storytelling and the comparative group learned from traditional mathematics textbooks. Afterwards, the two groups' cognitive load was measured through a questionnaire, and the following results were obtained: In the 'mental effort' and 'self evaluation' categories, the students that learned from the mathematics textbook based on storytelling showed higher scores than the students that learned from the traditional mathematics textbook. also there was statistically significant difference in some items. However, no statistically significant difference was found in the remaining categories 'task difficulty', 'self evaluation', and 'material design'.

• The Korean Journal of Emergency Medical Services
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• v.27 no.3
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• pp.101-111
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• 2023

Purpose: This study attempted to identify how academic self-efficacy, grit, and learned helplessness influence Academic delay behavior in college students and provide a foundation for reducing Academic delay behavior in college students. Methods: Data was collected from October 12, 2023 to October 30, 2023 using a structured questionnaire from 170 college students at a university in City D. The data was collected using a structured questionnaire. Results: Academic delay behaviors were significantly negatively correlated with academic self-efficacy (r=-.371, p<.001) and grit (r=-.562, p=.012), and significantly positively correlated with learned helplessness (r=.341, p<.001). Conclusion: Finally, In order to reduce academic delay behaviors among college students, it is necessary to actively utilize educational environments that promote academic achievement and grit, academic-related counseling programs, and learning environments that do not suffer from academic helplessness.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.10a
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• pp.3-20
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• 2006

The following lessons have been learned from the application of reliability methods in the practice of geotechnical engineering: 1. Establishing Goals Is Important; 2. Mitigating Consequences Can Be Effective; 3. Performance Depends on Systems; 4. Physical Factors Are Important in Statistical Models; 5. Too Much and Too Little Conservatism Are Both Problems; 6. Value of Information Depends on Decision Making; and 7. Effective Communication Is Essential. While the potential for application of reliability methods in the future is unlimited, there are major needs related to each of these lessons that will have to be addressed in order to realize this potential.

• Speech Sciences
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• v.5 no.2
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• pp.7-16
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• 1999

Starting as a poet, I learned about the sounds of words with David Abercrombie. Then, remembering my background in physics, I moved to studying acoustic phonetics and speech synthesis. From there I learned about psychology and how. to test perceptual theories. A meeting with a physiologist led to work on the use of the respiratory muscles in speech. Later I landed in Africa teaching English phonetics and learning about African languages. When I went to UCLA to set up a lab I was able to find bright students who helped make computer models of the vocal tract and taught me linguistic theory. And I was able to continue wandering around the world, describing the sounds of a wide range of languages.