• Journal of Convergence for Information Technology
• /
• v.9 no.8
• /
• pp.9-19
• /
• 2019

The effects of artificial intelligence technology is social science research as research on the impact on industry and changes in daily life, etc. This means that developing 'emotion AI' will prepare 'next-generation 3D-vector-sensitive AI'. This suggests the main keywords of the tertiary AI decision-making power. Particularly important results will be achieved because of the importance of current unethical learning and the implementation of decision-making systems that reflect ethical value judgments. This is a data based simulation, and required (1)Available data, (2)the technology for the goal of simulation. This takes into account the general content of the intended simulation based research. Currently, existing researches focus on meaningful research motivation, but this study presents the direction of technology. So, empirical analysis is consistent with the decision-making power of each country vs. new technology firms for AI on ehtic responsibility. As a result, there is a need for a concrete contribution and interpretation that can be achieved for the ethic Responsibility, on the technical side of AI / ML. In AI decision making, analytic power of human empathy should be included tech own trust.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.6
• /
• pp.15-20
• /
• 2020

Recently, the real estate is of high interest. This is because real estate, which was considered only a residential environment in the past, is recognized as a stable investment target due to the ever-growing demand on it. In particular, in the case of the domestic market, despite the decrease in the number of people, the number of single-person households and the influx of people to large cities are accelerating, and real estate prices are rising sharply around the metropolitan area. Therefore, accurately predicting the prospects of the future real estate market becomes a very important issue not only for individual asset management but also for government policy establishment. In this paper, we developed a program to predict future real estate market prices by learning past real estate sales data using machine learning techniques. The data on the market price of real estate provided by the Korea Appraisal Board and the Ministry of Land, Infrastructure and Transport were used, and the average sales price forecast for 2022 by region is presented. The developed program is publicly available so that it could be used in various forms.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.1
• /
• pp.1-7
• /
• 2021

Investor mood from social media is gaining increasing attention for leading a price movement in stock market. Based on the behavioral finance theory, this study argues that sentiment extracted from social media using big data technique can predict a real-time (short-run) price momentum in Chinese stock market. Collecting Sina Weibo posts that related to COVID-19 using keyword method, a daily influential weighted sentiment factors is extracted from the sizable raw data of over 2 millions of posts. We examine one supervised and 4 unsupervised sentiment analysis model, and use the best performed word-frequency and BiLSTM mdoel. The test result shows a similar movement between stock price change and sentiment factor. It indicates that public mood extracted from social media can in some extent represent the investors' sentiment and make a difference in stock market fluctuation when people are concentrating on a special events that can cause effect on the stock market.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.3
• /
• pp.355-360
• /
• 2021

Recently Youtube has been more popular. As many studies show the comparative deprivation of the Social Medeia, this study looks into whether the comparative deprivation is expressed on the YouTube comments. It focuses on the Luxury Haul contents, videos about huge amounts of luxurious products, of which Youtubers'economic feature are demonstrative. The comments of the videos are analyzed with LDA TF-IDF and Word2Vec. Additionally, the comments were classified into positive and negative groups by the LSTM model as well. As a result of the study, even though many comments turned out positive, the negative keywords were indicated related to comparative deprivation. Also it was found that the viewers compared themselves with Youtubers. In particular, some YouTubers are more criticized if they are younger or does not seem to afford the luxurious products themselves. This study suggests that the users express the comparative deprivation on YouTube as well like on the other Social Media.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.4
• /
• pp.281-289
• /
• 2021

Adolescence is a period when ego resilience, the ability to overcome stress, is important because self-identity is not established. Culture and arts education has various effects on the ego resilience of adolescents, so school culture arts education and social culture arts education use teaching and learning methods appropriate to the situation of adolescents. Self-understanding of the effects of culture and arts education has a significant effect on emotional control, vitality, interpersonal relationships, optimism, and curiosity of adolescent ego resilience, On the other hand, it was found that emotional stability among the effects of culture and arts education did not have a significant effect on all factors of adolescent ego resilience. Therefore, it is necessary to prepare a plan to provide opportunities for career exploration as a more practical program for adolescence to understand themselves and develop themselves. In addition, Culture and arts education should be conducted with convergence research that enables youths to maintain good relationships with others, have high self-confidence, and play a role in a wide range of stable and mature lives.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.518-520
• /
• 2021

In this paper, we propose a hand gesture recognition method by modifying the textNAS used for text classification so that it can be applied to multivariate time series data. It can be applied to various fields such as behavior recognition, emotion recognition, and hand gesture recognition through multivariate time series data classification. In addition, it automatically finds a deep learning model suitable for classification through training, thereby reducing the burden on users and obtaining high-performance class classification accuracy. By applying the proposed method to the DHG-14/28 and Shrec'17 datasets, which are hand gesture recognition datasets, it was possible to obtain higher class classification accuracy than the existing models. The classification accuracy was 98.72% and 98.16% for DHG-14/28, and 97.82% and 98.39% for Shrec'17 14 class/28 class.

• Journal of Advanced Navigation Technology
• /
• v.25 no.6
• /
• pp.557-561
• /
• 2021

A meatadata has become an essential element in order to recommend video content to users. However, it is passively generated by video content providers. In the paper, a method for automatically generating metadata was studied in the existing manual metadata input method. In addition to the method of extracting emotion tags in the previous study, a study was conducted on a method for automatically generating metadata for genre and country of production through movie audio. The genre was extracted from the audio spectrogram using the ResNet34 artificial neural network model, a transfer learning model, and the language of the speaker in the movie was detected through speech recognition. Through this, it was possible to confirm the possibility of automatically generating metadata through artificial intelligence.

• Journal of The Korean Association For Science Education
• /
• v.34 no.5
• /
• pp.469-478
• /
• 2014

To provide students an alternative image of science and scientist, we developed five lesson plans that include scientists' joy, anger, sorrow, and pleasure in their life. Through the 10 hour lessons with the five topics, we investigated the effect of our program on students' image change toward scientists, their science learning, and their career development in science field. Twenty high school students participated in our program and five of them were analyzed. The qualitative data included opinionnaire survey before and after the program, field note, video recording, students' worksheets, and interview. The science episode lessons that reflect the human side of scientists were designed in five steps. The first step is the one about imaging of scientists, the second step is the one about reading scientists' episode in their life, the third step is the one about investigating human side of scientists, the fourth step is the one about feeling sympathy in scientists' context, and the last step is the one about judging human side of scientists. Students participated in this program got to feel familiarity in scientists as well as confidence in science. By obtaining the alternative image of scientists after the class, it is expected that students will play roles of well-prepared supporters with scientific literacy.

• Communications of Mathematical Education
• /
• v.27 no.4
• /
• pp.547-566
• /
• 2013

Education, Science and Technology Department in January 2012, announced the advancement of mathematics education scheme. Select a textbook of storytelling method in policy by this, it is easy to understand the math, and that you can learn happily, was fabricated and spread. In this study, we selected three of the textbook that describes the set to its characteristics the application of storytelling in a textbook of mathematics 13 different middle school that will be used from March 2013. And of research that the textbook is to analyze the reflected reality of storytelling that is part of the advancement scheme of mathematics education content and direction and basic curriculum of current. View by presenting instead I is an object of the present invention. Six components of storytelling in the teaching and learning context that is proposed in the Park's study (2012) are used to analyze. Those are 'Persona', 'empathy', 'analogy', 'aesthetic experience ', 'plot' and 'time'. The data were analyzed storytelling was used to introduce the nature and mathematical concepts in math textbook based on these elements 6. That is looking at the ratio of the presence or absence of reflecting elements of storytelling on teaching and learning context that the data storytelling meets much the elements of storytelling to investigate the characteristics of each textbook. It is expected to provide the information and resources needed to develop methods and materials that can be studied to be interested in conjunction with real life mathematics as a result of this study.

• Journal of The Korean Association For Science Education
• /
• v.38 no.5
• /
• pp.739-751
• /
• 2018

The purpose of this study is to identify the differences of argumentation discourses for Socio-Scientific Issues in the types of decision-making and personality traits of pre-service biology teachers. For this study, SSI discussion topics were selected according to four types of decision making: logical reasoning, suggestion of complement, emotional base, and internal conflict. Three groups were constructed based on personality traits such as extroversion, acceptability, and integrity. Each three group used the workbook specially developed and freely used the smart device for discussion. A recorder and a camcorder were used to record each group, their behavior was recorded and the written materials during the discussion were collected for the results. Using Walton's analysis framework, the collected data analyzed in terms of the source of utterance, the process of dialogue shift, and the critical movements that can judge the reasoning of utterance. As a result of the study, it was confirmed that the decision-making type of SSI topics and learners' personalities were influential in the decision-making process of SSI small group discussions. This research shows that there is a need to develop instructional materials considering decision-making types and learners' personality types of students as well as pre-service teachers for SSI discussion.