• Journal of The Korean Association of Information Education
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• v.26 no.6
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• pp.517-532
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• 2022

As a result of the this exploratory study the main results show that the factors affecting the satisfaction of non-face-to-face class learning of graduate students in Education were social presence, perceived easy to use, and information service quality. Secondly, the factors affecting the learning persistence were perceived usefulness and social presence, but perceived usefulness's influence was relatively small. Next, it was found that the subjective satisfaction of graduate students of education did not significantly affect their intention to continue learning persistence. Lastly, learning satisfaction and learning persistence had a positive effect on the intention to recommend to others. Through the this empirical analysitics study it demonstrate the factors such as attitudes, feelings, and friendliness toward non-face-to-face online classes perceived by graduate students in Education.

• Journal of Biomedical Engineering Research
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• v.45 no.2
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• pp.90-94
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• 2024

Diagnosing wounds presents a significant challenge in clinical settings due to its complexity and the subjective assessments by clinicians. Wound deep learning algorithms quantitatively assess wounds, overcoming these challenges. However, a limitation in existing research is reliance on specific datasets. To address this limitation, we created a comprehensive dataset by combining open dataset with self-produced dataset to enhance clinical applicability. In the annotation process, machine learning based on Gradient Vector Flow (GVF) was utilized to improve objectivity and efficiency over time. Furthermore, the deep learning model was equipped U-net with residual blocks. Significant improvements were observed using the input dataset with images cropped to contain only the wound region of interest (ROI), as opposed to original sized dataset. As a result, the Dice score remarkably increased from 0.80 using the original dataset to 0.89 using the wound ROI crop dataset. This study highlights the need for diverse research using comprehensive datasets. In future study, we aim to further enhance and diversify our dataset to encompass different environments and ethnicities.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.1-6
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• 2020

There are various approaches to evaluate a watermelon sweetness. However, there are some limitations to evaluating cost, watermelon damage, and subjective issue. In this study, we developed a novel approach to predict a watermelon sweetness using reflected sound and the machine learning algorithm. It was observed that higher brix watermelon produced higher spectral power is reflected sound. Based on the spectral-temporal features of reflected sound, the machine learning algorithms could accurately predict the sweetness group at a rate of 83.2 and 59.6 % in 2-groups and 3-groups classification, respectively.

• Journal of Korean Academy of Nursing
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• v.36 no.8
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• pp.1308-1314
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• 2006

Purpose. The purposes of this study were to develop a PBL program for continuing nurse education and to evaluate the program after its implementation. Methods. The PBL program was developed in the core cardio-pulmonary nursing concepts through a collaborative approach with a nursing school and a hospital. The PBL packages with simulation on ACLS were implemented to 40 clinical nurses. The entire PBL program consisted of six 3-hour weekly classes and was evaluated by the participants' subjective responses. Results. Two PBL packages in cardio-pulmonary system including clinical cases and tutorial guidelines were developed. The 57.5 % of the participants responded positively about the use of PBL as continuing nurse education in terms of self-motivated and cooperative learning, whereas 20.0% of the participants answered that the PBL method was not suitable for clinical nurses. Some modifications were suggested in grouping participants and program contents for PBL. Conclusion. The PBL method could be utilized to promote nurses' clinical competencies as well as self-learning abilities. Further research is needed in the implementation strategies of PBL-based continuing education in order to improve its effectiveness.

• Journal of the Korean Society for information Management
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• v.34 no.2
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• pp.97-114
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• 2017

This study aims to develop the lesson plan of public library user education for children for the activation of user education. For the development of lesson plan, elementary school 3rd and 4th graders were selected as user education subjects through the literature survey, and orientation were derived as contents of user education. This study developed a lesson plan that applies Jonassen's constructivist learning environments to specifically design the librarian's role as teacher in user education with voluntary and subjective education participation of the children. Lesson plan was evaluated in terms of usefulness and appropriateness.

• Journal of The Korean Association For Science Education
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• v.9 no.2
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• pp.29-45
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• 1989

The purpose of this paper is to study the operational skills of apparatuses in observation and experiments a point of view of the teaching-learning guidance of the middle school science. In order to understand the actual condition of the field learner, the achivment levels of learner have been investigated on the operational skills of apparatuses, observation and experiments through 1120 students of 16 middle schools. The results showed that there were large differences at each item and especially, in animate natural part(physics and chemistry), the handling ability was very low to average 33 percentage. By the result of analyzing the actual condition of the experiment and field science from the question of 114 science teachers who work in 40 middle schools in P distriet. it has been recognized that though the lessons through the experiments stimulate the motivation of learning, it couldn't be mamaged efficently because of all the educational conditions. And it was revealed that the major part of Experiment was performed not by student who is subjective in the course of learning but by teacher through experiments.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.166-175
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• 2019

Grit, a concept conceived in 2007 by Duckworth and others in the United States, is based on positive psychology that focuses on growth and development through individual strengths. Recently, "Grit", which means patience and enthusiasm for long-term goals, has emerged as a key factor of personality strength. In Korea, Joo-hwan Kim (2013) was the first to conceptualize and study the subject of Grit. However, there have been no overview studies that systematically summarize the overall trends and flow in the research of Grit so far. There have been 147 research papers on Grit published so far in Korea. The purpose of this study was to conduct trend analysis on the subject of Grit by analyzing forty-three (43) master's and doctoral dissertations, thus presenting the direction of future research on Grit through careful analysis. In the studies conducted, it was found that Grit is a very significant variable linked to self-efficacy. It is also a subjective belief that can help an individual achieve his/her educational goals, and go through failure resynchronization. In addition, Grit is very significant as a practical core indicator of how fusion talent is fostered for the fourth industrial revolution. Therefore, there is a need for more in-depth research from the viewpoints of workplace learning, experiential learning, or informal learning, as well as research into Grit characteristics.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.693-700
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• 2023

Sentiment analysis, a branch of natural language processing that classifies and identifies subjective opinions and emotions in text documents as positive or negative, can be used for various promotions and services through customer preference analysis. To this end, recent research has been conducted utilizing various techniques in machine learning and deep learning. In this study, we propose an optimal language model by comparing the accuracy of sentiment analysis for movie, product, and game reviews using existing RNN-based models and recent Transformer-based language models. In our experiments, LMKorBERT and GPT3 showed relatively good accuracy among the models pre-trained on the Korean corpus.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.280-282
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• 2021

A particular matter prediction model was designed using a deep learning algorithm to solve the problem of particular matter forecast with subjective judgment applied. RNN and LSTM were used among deep learning algorithms, and it was designed by applying optimal parameters by proceeding with hyperparametric navigation. The predicted performance of the two models was evaluated through RMSE and predicted accuracy. The performance assessment confirmed that there was no significant difference between the RMSE and accuracy, but there was a difference in the detailed forecast accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.438-455
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• 2024

Recently, many unsupervised learning-based models have emerged for Just Noticeable Difference (JND) estimation, demonstrating remarkable improvements in accuracy. However, these models suffer from a significant drawback is that their heavy reliance on handcrafted priors for guidance. This restricts the information for estimating JND simply extracted from regions that are highly related to handcrafted priors, while information from the rest of the regions is disregarded, thus limiting the accuracy of JND estimation. To address such issue, on the one hand, we extract the information for estimating JND in an Adversarial Complementary Learning (ACoL) way and propose an ACoL-JND network to estimate the JND by comprehensively considering the handcrafted priors-related regions and non-related regions. On the other hand, to make the handcrafted priors richer, we take two additional priors that are highly related to JND modeling into account, i.e., Patterned Masking (PM) and Contrast Masking (CM). Experimental results demonstrate that our proposed model outperforms the existing JND models and achieves state-of-the-art performance in both subjective viewing tests and objective metrics assessments.