• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.497-502
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• 2022

Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.

• Journal of Korea Entertainment Industry Association
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• v.13 no.2
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• pp.37-45
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• 2019

The This study aimed at clarifying that the cognitive interpretation code is essential for college students to read the correct culture while discussing the producer's story production system for creative advertising content and the process of interpreting the meaning of advertisers and the formation of principles and beliefs. The production of advertising content aimed at persuasion should first identify anachronistic reason system based on the target audience's perception principle. A concise analysis of the experiment found key clues that confirmed that a sample of the producer's intended story would be inconsistent with the clues of information that a college student could remember. I have tried to organize a semantic analysis tool that combines these key clues and as a tool for reading culture of the right time for college students. As a result, university student inmates were able to identify one side of positive communication: reading a new cognitive symbol culture based on their subjective experience and beliefs, rather than analyzing cross-sectional analysis of the primary language and non-verbal expressions of their advertising contents. In the future, if an advertising content story producer works to identify such a process in advance, it will help persuade inmates.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.323-338
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• 2023

TV advertising with deep analysis of watching pattern of audiences is important to set-top box audience targeting. Applying session-based recommendation model(SBR) to internet commercial, or recommendation based on searching history of user showed its effectiveness in previous studies, but applying SBR to the TV advertising was difficult in South Korea due to data unavailabilities. Also, traditional SBR has limitations for dealing with user preferences, especially in data with user identification information. To tackle with these problems, we first obtain set-top box data from three major broadcasting companies in South Korea(SKB, KT, LGU+) through collaboration with Korea Broadcast Advertising Corporation(KOBACO), and this data contains of watching sequence of 4,847 anonymized users for 6 month respectively. Second, we develop personalized session-based recommendation model to deal with hierarchical data of user-session-item. Experiments conducted on set-top box audience dataset and two other public dataset for validation. In result, our proposed model outperformed baseline model in some criteria.

• The Mathematical Education
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• v.62 no.1
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• pp.57-78
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• 2023

Students' engagement in lessons not only determines the direction and result of the lessons, but also affects academic achievement and continuity of follow-up learning. In order to provide implications related to teaching strategies for encouraging students' engagement in elementary mathematics lessons, this study implemented lessons for middle-low achieving fifth graders using open-ended tasks and analyzed characteristics of students' engagement in the light of the framework descripors developed based on previous research. As a result of the analysis, the students showed behavioral engagement in voluntarily answering teacher's questions or enduring difficulties and performing tasks until the end, emotional engagement in actively expressing their pleasure by clapping, standing up and the feelings with regard to the topics of lessons and the tasks, cognitive engagement in using real-life examples or their prior knowledge to solve the tasks, and social engagement in helping friends, telling their ideas to others and asking for friends' opinions to create collaborative ideas. This result suggested that lessons using open-ended tasks could encourage elementary students' engagement. In addition, this research presented the potential significance of teacher's support and positive feedback to students' responses, teaching methods of group activities and discussions, strategies of presenting tasks such as the board game while implementing the lessons using open-ended tasks.

• Communications of Mathematical Education
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• v.37 no.1
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• pp.85-104
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• 2023

The purpose of this study is to analyze the types of mathematics journals of elementary school students and to understand how they change in mathematics journals as the grade goes up, and to obtain implications in mathematics education. To this end, 170 of the 222 parish mathematics data submitted to the "Math Journal Contest" were analyzed with the consent of both minors and their parents. As for the framework for analyzing math journal types, 12 types were derived through independent analysis between three researchers. The research results showed that first, the type of math journal written by elementary school students is a variety of journals, such as observation, problem making, concept organization, and review. In addition, as a learning area, it was found that math journal showed a noticeable increase in experimental observation, problem making, and concept journal as the grades progressed, while a small number of idea journal and explanatory journals appeared. However, game (winning) strategy building and types declined. It can be seen that this is evolving from a type that requires activity-oriented or simple descriptions to a type that actively applies mathematical concepts. As such, there are 12-type of math journals, but it is necessary to actively use the teaching materials in writing that can be freely expressed in the school setting.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.357-366
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• 2023

In the purpose of this study, the college textbooks of self-narrative writing and examples of classroom practice are analyzed to find a way to educate it. The self- narrative writing subject with a learning of recognization, expression, and communication with oneself, emphasizes the necessity when they become college students through entrance exam-oriented education. The research methods are as follows. Firstly, three university textbooks which include a section on self-narrative writing were compared and analyzed. The analysis highlights the needs for a textbook covering self-narrative writing more extensively and comprehensively as what is offered by the existing textbooks is limited in facilitating students to fully develop the ability of self-reflection, which should be dealt as a long-term goal. Secondly, the current discussion on self-narrative writing and examples of real classroom practice were analyzed. It shows that a step-by-step approach is required to encourage the practice of deep self-reflection to be incorporated into writing. In addition, during the writing process, various correction and feedback activities should be carried out on a macro level and gradually while the communication and feedback should take place not only between a teacher and students, but also among students. As a result, it is expected that this study will help establish a teaching model of self-narrative writing by seeking complementary points and educational directions for self-narrative writing.

• Journal of the Korean Applied Science and Technology
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• v.39 no.2
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• pp.246-260
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• 2022

This study was conducted to analyze the creativity education contents of dance activities in physical education textbooks for the 3rd and 4th grades of elementary school. For this purpose, 16 types of textbooks and auxiliary data for physical education in the 3rd and 4th grades of elementary school were collected and analyzed using the creative education content analysis frame of the physical education textbook based on the 4P model. In order to secure the integrity of the research, expert consultation was operated. The results of this study are as follows. First, from the viewpoint of creative person, 'inquiry' was the most common in creative mind, and the rest of the elements appeared relatively evenly. As for the subject of activity, 'individual' and 'colleague (team)' showed similar frequencies. Second, from the viewpoint of the creative process, all activity areas appeared as 'learning', and most of the elements of the activity purpose appeared evenly, and the creative process was explored. Third, from the viewpoint of creative output, physical activity performance was the most common activity method, and two or three activity methods were used together. In the creativity factor, all factors appeared evenly, and sensitivity and sophistication were the most common with 4 factors. Fourth, from the viewpoint of the creative environment, most of the activity spaces were no restrictions, and the activity media consisted of many educational contents using the body. Through this study, it was requested that creativity education in dance activities should be expanded quantitatively and intensified in quality, and the necessity of spreading creativity education contents of dance activities to other areas was explored.

• Journal of Korean Elementary Science Education
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• v.42 no.4
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• pp.591-604
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• 2023

This study investigated the impact of elementary science classes using metaverse on the academic achievement, positive experience in science, and digital literacy of elementary school students. In addition, we examined their perceptions. The respondents were derived from two classes in the sixth grade at an elementary school in Gyeonggi-do, who were selected designated as the experimental (n=29 students) and comparative (n=29) groups, respectively. Across five lessons under the "Plant Structure and Function" unit, the experimental group conducted science classes using the metaverse, whereas the comparative group conducted general textbook-based classes. To investigate instructional effects, the study performed ANCOVA using the pre-test score as a covariate, a survey on the perception of students about science classes using metaverse, and conducted interviews with a number of subjects. The result demonstrated that science classes using metaverse exerted no significant effect on scientific academic achievement and digital literacy. However, the study observed a statistically significant effect on science learning emotion which is a sub-element of positive experiences in science. The students were positively aware of science classes using metaverse in terms of interesting and diverse activities, and free expression of inquiry results and perceived the instability of smart devices and network connections as regrettable. Finally, the study posed the implications of the use of metaverse in science classes.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.31-49
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• 2023

With the growth of the food-catering industry, consumer preferences and the number of dine-in restaurants are gradually increasing. Thus, personalized recommendation services are required to select a restaurant suitable for consumer preferences. Previous studies have used questionnaires and star-rating approaches, which do not effectively depict consumer preferences. Online reviews are the most essential sources of information in this regard. However, previous studies have aggregated online reviews into long documents, and traditional machine-learning methods have been applied to these to extract semantic representations; however, such approaches fail to consider the surrounding word or context. Therefore, this study proposes a novel review textual-based restaurant recommendation model (RT-RRM) that uses deep learning to effectively extract consumer preferences from online reviews. The proposed model concatenates consumer-restaurant interactions with the extracted high-level semantic representations and predicts consumer preferences accurately and effectively. Experiments on real-world datasets show that the proposed model exhibits excellent recommendation performance compared with several baseline models.