• Korean Parent-Child Health Journal
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• v.3 no.1
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• pp.27-34
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• 2000

In recent years, there has been a proliferation of consumer health information available on the internet related to parent-child health. More and more, parents are accessing information about child ca re through the Internet and computer at home. But there is no guarantee that the information is current, unbiased, or accurate. Several researchers have suggested some criteria for evaluating internet sites; source, accuracy, disclosure, currency, accessibility. As more consumer search the World Wide Web for parenting information, nurses have to learn more about this technology. Because nurses can assist parents in identifying how to locate information they can trust. It is also needed to for nurses to document the criteria for information selection on internet and to evaluate outcome of cyberspace intervention of parenting.

• Journal of Korean Library and Information Science Society
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• v.3
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• pp.79-88
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• 1976

In Ecorea Lrynasty, the authority all officers a compulsary obligatic.~ to learn the Nyo-I~.'z~\ulcorneruzngd er the custody of a super1 iscr o; Letters wino -1 a\ulcorner the ~ejponsible officer to train ci~ril senants. The Nyo-Kjli ilg was possible to interpret the pious love of ci I illans to the~re lders as a mutual ethics between the parental ber~ec;~lc nce and the filial piety of inferiors which n-as far superior to the traditional cthic; that was laid on an firm obligation of inieri~rs to tEei:- elders. The filial piety as a lovc for elders mean2 a mutual harrn~n:a~n d show\ulcorner a berieiolent conduct as an influence of a political morality. Thc heaer-o!erLt conduct was developed as a political morality of Confucius originated from the filial piety of Confucius based on a moral policj . Such a kenerolent conduct is to become a main spring to effect a mutual tie betn-een the king and his people as a national system of the Confucian theory. In i*

• Journal of The Korean Association For Science Education
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• v.25 no.6
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• pp.642-649
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• 2005

Argumentative discussion is one of the important components of an educational program, which allows students not only to learn the process of social negotiation through discussions, but also to improve students' overall research abilities. The purpose of this study was to examine a) the changes between inquiry of before-argumentative discussion and inquiry of after-argumentative discussion, and b) the connections between the inquiry changes and online argumentative discussion. This study analysed 726 messages in an online argumentative discussion, as well as in first research reports and second research reports. The results of the study indicate that science-gifted students' research abilities were improved through on-line argumentative discussion that provided them with feedback based on interactive discussions, and encouraged them to re-examine hypotheses and experiment processes. The science-gifted students showed knowledge and abilities for identifying simple errors in research processes and arguing problems in the flow of the whole logic of research.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.325-329
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• 2003

This paper discuss the method of the system's efficient control using a Intelligent hybrid algorithm in nonlinear dynamics systems. Existing neural network and genetic algorithm for the control of non-linear systems work well in static states. but it be not particularly good in changeable states and must re-learn for the control of the system in the changed state. This time spend a lot of time. For the solution of this problem we suggest the intelligent hybrid self-tuning controller. it includes neural network, genetic algorithm and immune system. it is based on neural network, and immune system and genetic algorithm are added against a changed factor. We will call a change factor an antigen. When an antigen broke out, immune system come into action and genetic algorithm search an antibody. So the system is controled more stably and rapidly. Moreover, The Genetic algorithm use the memory address of the immune bank as a genetic factor. So it brings an advantage which the realization of a hardware easy.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.17-24
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• 2019

In this paper, we propose a new model for predicting effective Win/Loss in professional baseball game in Korea using machine learning technique. we used basic baseball data and Sabermetrics data, which are highly correlated with score to predict and we used the deep learning technique to learn based on supervised learning. The Drop-Out algorithm and the ReLu activation function In the trained neural network, the expected odds was calculated using the predictions of the team's expected scores and expected loss. The team with the higher expected rate of victory was predicted as the winning team. In order to verify the effectiveness of the proposed model, we compared the actual percentage of win, pythagorean expectation, and win percentage of the proposed model.

• Journal of Technologic Dentistry
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• v.46 no.3
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• pp.126-132
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• 2024

Purpose: This study aims to examine the impact of instructor-learner interaction on online class satisfaction, perceived academic achievement, and online class preference. Methods: From December 20, 2023, to February 10, 2024, this study surveyed students in the medical and public health departments of K University and D University located in Gangwon-do and Daejeon, respectively. Results: In the online class environment, instructor-learner interaction showed a significant positive correlation with online class satisfaction, academic achievement, and online class preference. On re-examination using regression analysis, it was found that among the subfactors of instructor-learner interaction, instructional support and instructor presence had a significant impact. Conclusion: The findings suggest that in an online learning environment, instructors must make efforts to help learners identify what they need to learn by repeatedly asking whether they understand the learning content and providing appropriate feedback.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.15-23
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• 2017

The person Re-identification is the most challenging part of computer vision due to the significant changes in human pose and background clutter with occlusions. The picture from non-overlapping cameras enhance the difficulty to distinguish some person from the other. To reach a better performance match, most methods use feature selection and distance metrics separately to get discriminative representations and proper distance to describe the similarity between person and kind of ignoring some significant features. This situation has encouraged us to consider a novel method to deal with this problem. In this paper, we proposed an enhanced recurrent neural network with three-tier hierarchical network for person re-identification. Specifically, the proposed recurrent neural network (RNN) model contain an iterative expectation maximum (EM) algorithm and three-tier Hierarchical network to jointly learn both the discriminative features and metrics distance. The iterative EM algorithm can fully use of the feature extraction ability of convolutional neural network (CNN) which is in series before the RNN. By unsupervised learning, the EM framework can change the labels of the patches and train larger datasets. Through the three-tier hierarchical network, the convolutional neural network, recurrent network and pooling layer can jointly be a feature extractor to better train the network. The experimental result shows that comparing with other researchers' approaches in this field, this method also can get a competitive accuracy. The influence of different component of this method will be analyzed and evaluated in the future research.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.1
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• pp.87-97
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• 2005

A secure index search protocol let us search the index of encrypted documents using the trapdoor for a keyword. It enables an untrusted server to learn nothing more than the search result about the documents without revealing the keyword. A lot of secure search protocols have been suggested but they only considered the search between a single-user and a server. In real organizations such as government offices or enterprises where exist many hierarchical departments, the search system for groups is arisen more often. In this paper, we construct secure index search protocols for hierarchical group settings without re-encryption of the old encrypted documents when group keys are re-keyed newly.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.291-298
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• 2022

A generative adversarial network (GAN) is a network in which two internal neural networks (generative network and discriminant network) learn while competing with each other. The generator creates an image close to reality, and the delimiter is programmed to better discriminate the image of the constructor. This technology is being used in various ways to create, transform, and restore the entire image X into another image Y. This paper describes a method that can be forged into another object naturally, after extracting only a partial image from the original image. First, a new image is created through the previously trained DCGAN model, after extracting only a partial image from the original image. The original image goes through a process of naturally combining with, after re-styling it to match the texture and size of the original image using the overall style transfer technique. Through this study, the user can naturally add/transform the desired object image to a specific part of the original image, so it can be used as another field of application for creating fake images.

• The Research Journal of the Costume Culture
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• v.20 no.4
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• pp.535-548
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• 2012

The purpose of this study is to research the achievement motivation of beauty industry professionals. The research method involved one-on-one, in-depth interviews with 7 hair professionals, 7 make-up professionals and 7 skincare professionals. The in-depth interviews were recorded in their entirety, and the recorded content was transcribed and organized. Analysis of the transcribed data involved encoding, deconstructing and re-composing the interview content. Research results revealed 5 factors that were extracted to explain the achievement motivation of beauty industry professionals. Four of the 5 factors were similar to the results of precedent studies, but the remaining factor presented unique characteristics. The 4 common factors were "motive to pursue success", "motive to avoid failure", "motive to meet challenges" and "goal-oriented motive". The factor discovered in this study was "relationship-oriented motive", which is characterized by the tendency to place importance in relationships with superiors, colleagues and customers based on the working characteristics of beauty industry professionals. Based on the results of this study, beauty industry professionals can learn about goals that must be met in various stages in order to establish a system for accomplishing those goals, implement an emotional education program for mental balance, introduce a competitive team system, and carry out a relationship improvement program to increase work efficiency.