• The Journal of Engineering Geology
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• v.31 no.1
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• pp.31-42
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• 2021

Database of Cut-slope management system (CSMS) has been constructed based on investigations of all slopes on the roads of the whole country. The investigation data is documented by human, so it is inevitable to avoid human-error such as missing-data and incorrect entering data into computer. The goal of this paper is constructing a prediction model based on several machine-learning algorithms to solve those imperfection problems of the CSMS data. First of all, the character-type data in CSMS data must be transformed to numeric data. After then, two algorithms, i.g., multinomial logistic regression and deep-neural-network (DNN), are performed, and those prediction models from two algorithms are compared. Finally, it is identified that the accuracy of DNN-model is better than logistic model, and the DNN-model will be utilized to improve data-quality.

• Journal of The Korean Association of Information Education
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• v.23 no.3
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• pp.273-282
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• 2019

In this study, we have look through the national progress of computer science education in South Korea and analyzed the main subjects and contents of each period. We suggests the ways to evolve the current computer science education in terms of class hours for computer science education, hierarchical instructions, and the limitation of current national curriculum. In South Korea, it has been leaded the computer science education in the world since the it was promoted in earnest since 1995. Based on the recently revised national curriculum, South Korean government are taking efforts to nurture a leader through computer science education in terms of the students' future skills. However, it should be promoted to strengthen the ability of not only problem-solving ability through programming education, but also balanced computing and digital literacy through enhancing the ICT skills. In order to improve the curriculum of computer science education in elementary school of South Korea, a sufficient class hours of computer science education should be secured first.

• Journal of The Korean Association of Information Education
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• v.23 no.2
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• pp.141-148
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• 2019

We proposed a curriculum that can learn the principle of blockchain by using the gamification which can bring up the interest and concentration of the students by connecting the contents of the class with the game. The proposed method is to educate the blockchain in a game format and to solve the problem that can be easily accessed in everyday life by applying the blockchain. By strengthening the thinking ability of computing, By growing information processing capacity, communication capacity, and community capacity, students can naturally enhance their education capacity. It is expected that the blockchain curriculum using the proposed gamification can be used to improve the information curriculum.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.548-562
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• 2022

This study was conducted to diagnose the issues of AI ethics in global content and to discuss what kind of discourse is needed to strengthen human identity. To this end, the study selected Netflix original content "The Social Dilemma" for analysis and adopted narrative analysis as the research method. The analysis results confirmed that "Social Dilemma" showed the structure of a traditional current affairs documentary and mainly used experts and statistical data to develop the story. It also reinforced core content claims by enumerating domestic and foreign cases such as the 2021 Myanmar massacre and the spread of fake news. In addition, the relationship between the characters clearly revealed the binary opposition between developers and media companies as well as users and advertisers. For the solution to the problem, strong regulations on businesses and the suspension of social media use were reached. However, "The Social Dilemma" merely pointed out the misuse of AI technology and had a narrative that ignored human identity and social relationships. Such results raise the need for creating contents that emphasize the importance of human sociality, relationships, and learning ability in the age of AI.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.703-712
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• 2022

The purpose of this study is to present practical implications for employment of people with developmental disabilities by analyzing the moderating effect of family employment support in the relationship between discrimination experience and employment of people with developmental disabilities. The subjects of the study were 394 people with developmental disabilities who participated in the 2nd wave 4th survey of the 2019 Employment Panel Survey for the Disabled, and a hierarchical binary logistic regression analysis was conducted to verify the hypothesis. As a result of the study, it was found that the experience of discrimination among people with developmental disabilities negative effects employment, and family employment support has a significant moderating effect, strengthening the negative effect of discrimination on employment. Therefore, the importance of improving the working environment reflecting the needs of families with developmental disabilities, the necessity of employment support policies, and strengthening trust with the state and local communities were discussed.

• Journal of Korea Game Society
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• v.21 no.2
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• pp.139-150
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• 2021

This study analyzed the effectiveness by developing an online program to enhance collaborative problem-solving capabilities for college freshmen using gamification. According to the research results, the operational model of the online program for enhancing collaborative problem-solving capabilities using gamification was presented in five stages: 1 preparation, 2 team building, 3 assessment, 4 feedback, and 5 achievement sharing. The results of the "pre-test" and post T-test of creative problem-solving capabilities, the variables related to creative problem-solving skills, academic challenge, creative thinking ability, and convergence value creation have been significantly improved. What should be discussed in the future is the need to experience collaborative problem solving process online, and to develop game design and platform that can discuss and communicate.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.18 no.2
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• pp.203-228
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• 2007

This study was conducted to explore pending issues as an obstacle factor in the library growth and progress through measurement of Korean and Chinese College undergraduates' perception on the library, and suggest its countermeasure to that the study result showed that their perception to the library's social and cultural function was low, so the library's cultural events need to be consolidated to enhance perception, and the Korean student's study zeal was lower than Chinese, and amny students did not go to the library, but an incentive is needed to escalate the strength of course study or the library availability. Also a countermeasure should be established such as a class link project through continuing specialized librarians' training strengthened, users' group education for the satisfaction enhancement and validity of the information service users.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.11
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• pp.1552-1563
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• 2016

To examine the cognitive function of onion (Allium cepa L.) beverages (odourless and fortified), we analyzed in vitro neuronal cell protection against $H_2O_2$-induced cytotoxicity and performed in vivo tests on amyloid beta ($A{\beta}$)-induced cognitive dysfunction. Cellular oxidative stress and cell viability were evaluated by DCF-DA assay and MTT assay. These results show that fortified beverage resulted in better neuronal cell protection than odourless beverage at lower concentration ($0{\sim}100{\mu}g/mL$). Fortified beverage also showed more excellent acetylcholinesterase (AChE) inhibitory activity ($IC_{50}$: 4.20 mg/mL) than odourless beverage. The cognitive functions of odourless beverage and fortified beverage in $A{\beta}$-induced neurotoxicity were assessed by Y-maze, passive avoidance, and Morris water maze tests. The results show improved cognitive function in both groups treated with beverages. After in vivo tests, cholinergic activities were determined based on AChE inhibition and acetylcholine levels, and antioxidant activities were measured as SOD, oxidized glutathione (GSH)/total GSH ratio, and MDA levels in mouse brain tissue. In a Q-TOF UPLC/MS system, main compounds were analyzed as follows: odourless beverage (five types of sugars and three types of phenolics) and fortified beverages (six types of phenolics and two types of steroidal saponins).

• Journal of Gifted/Talented Education
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• v.24 no.5
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• pp.781-806
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• 2014

The purpose of this study is to examine the change in the beliefs of regular classroom teachers after participating in a gifted education lectures and practicum as well as the effectiveness of the lectures and practicum. Each teacher was asked to complete a pre-/ a mid-/ and post-journal, detailing their expected characteristics and then describing what occurred and how their initial expectations were altered. The teachers mentioned high thinking skills, creativity, fast problem solving skills, and a lack of communication skills as intellectual characteristics of gifted students and high motivation and task commitment as social characteristics. They mentioned the characteristics in textbooks on pre- and mid-journals, but presented their observations in post-journals such as lack of communication skills, competitive spirit, and frustrations. The study found that teachers broadened their view of giftedness, recognized the need to adapt instructions for gifted students, realized the necessity of knowing the students to differentiate instruction patterns, and emphasized teaching-learning strategies for the gifted. These results contribute to the promise of having regular classroom teachers engage in a field experience with gifted students to supplement discussions about gifted education lectures.

• Korean Chemical Engineering Research
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• v.58 no.4
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• pp.588-595
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• 2020

Prediction and control of nitrogen oxides (NO_x) emission is of great interest in industry due to stricter environmental regulations. Herein, we propose an artificial intelligence (AI)-based framework for prediction of NO_x emission. The framework includes pre-processing of data for training of neural networks and evaluation of the AI-based models. In this work, Long-Short-Term Memory (LSTM), one of the recurrent neural networks, was adopted to reflect the time series characteristics of NO_x emissions. A decision tree was used to determine a time window of LSTM prior to training of the network. The neural network was trained with operational data from a heating furnace. The optimal model was obtained by optimizing hyper-parameters. The LSTM model provided a reliable prediction of NO_x emission for both training and test data, showing an accuracy of 93% or more. The application of the proposed AI-based framework will provide new opportunities for predicting the emission of various air pollutants with time series characteristics.