• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.7-15
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• 2022

With the aim of an intelligent world in the age of individual customization through decentralization of information and technology, sharing/opening, and connection, we often see a tendency to cross expectations and concerns in the technological discourse and interest in artificial intelligence more than ever. Recently, it is easy to find claims by futurists that AI singularity will appear before and after 2045. Now, as part of preparations to create a paradigm of coexistence that coexists and prosper with AI in the coming age of artificial intelligence, a standard framework for setting up more correct AI ethics and regulations is required. This is because excluding the risk of omission of setting major guidelines and methods for evaluating reasonable and more reasonable guideline items and evaluation standards are increasingly becoming major research issues. In order to solve these research problems and at the same time to develop continuous experiences and learning effects on AI ethics and regulation setting, we collect guideline data on AI ethics and regulation of international organizations / countries / companies, and research and suggest ways to set up a standard framework (SF: Standard Framework) through a setting research model and text mining exploratory analysis. The results of this study can be contributed as basic prior research data for more advanced AI ethics and regulatory guidelines item setting and evaluation methods in the future.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.569-578
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• 2021

Thanks to web development today, we can easily access online news via various media. As much as it is easy to access online news, we often face fake news pretending to be true. As fake news items have become a global problem, fact-checking services are provided domestically, too. However, these are based on expert-based manual detection, and research to provide technologies that automate the detection of fake news is being actively conducted. As for the existing research, detection is made available based on contextual characteristics of an article and the comparison of a title and the main article. However, there is a limit to such an attempt making detection difficult when manipulation precision has become high. Therefore, this study suggests using a verifying article to decide whether a news item is genuine or not to be affected by article manipulation. Also, to improve the precision of fake news detection, the study added a process to summarize a subject article and a verifying article through the summarization model. In order to verify the suggested algorithm, this study conducted verification for summarization method of documents, verification for search method of verification articles, and verification for the precision of fake news detection in the finally suggested algorithm. The algorithm suggested in this study can be helpful to identify the truth of an article before it is applied to media sources and made available online via various media sources.

• Journal of Korea Entertainment Industry Association
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• v.15 no.2
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• pp.123-135
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• 2021

The data processing of this study is focused on keywords related to 'Corona 19 and professional baseball' and 'Corona 19 and professional baseball no spectators', using text mining and social network analysis of textom program to identify problems and view quality. It was used to set the variable of For quantitative analysis, a questionnaire on viewing quality was constructed, and out of 270 survey respondents, 250 questionnaires were used for the final study. As a tool for securing the validity and reliability of the questionnaire, exploratory factor analysis and reliability analysis were conducted, and IPA analysis (importance-satisfaction) was conducted based on the questionnaire that secured validity and reliability, and the results and strategies were presented. As a result of IPA analysis, factors related to the image (image composition, image coloration, image clarity, image enlargement and composition, high-quality image) were found in the first quadrant, and the second quadrant was the game situation (support team game level, support player game level, star). Player discovery, competition with rival teams), game information (match schedule information, player information check, team performance and player performance, game information), interaction (consensus with the supporting team), and some factors appeared. The factors of commentator (baseball-related knowledge, communication ability, pronunciation and voice, use of standard language, introduction of game-related information) and interaction (real-time communication with the front desk, sympathy with viewers, information exchange such as chatting) appeared.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.2
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• pp.137-146
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• 2022

AIS(Automatic Identification System) is a device that automatically transmits and receives ship information and is mounted on the ship. AIS information of ships near the coast can be received on the ground, but when going out to sea more than 50 nautical miles, communication with the ground is cut off. To solve this problem, ship information can be transmitted to the ground through an AIS satellite equipped with an AIS receiver. There is no case of AIS satellite development in Korea yet, and many domestic shipping companies are using overseas AIS services. PNUSAT-1 is a 1U+ CubeSat, developed by Pusan National University, and it is equipped with an AIS receiver for monitoring of ships and transmitting ship information to the ground. Since the mission data of PNUSAT-1 is in text format, the data size is not large. In consideration of this, communication equipment, low-precision sensors, and actuators were selected. In this paper, system preliminary design of PNUSAT-1 was performed, requirements for mission performance, operation scenario and mode design, hardware and software selection, and preliminary design of each subsystem were performed.

• Journal of the Korean Society of Radiology
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• v.16 no.5
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• pp.611-618
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• 2022

The purpose of this study was to confirm the degree of other behaviors among university students in the department of radiology(science) who experienced online classes in the COVID-19 situation and to investigate the effect of self-directed learning ability, flow and academic achievement on other behaviors. The research method was descriptive research. Data were 200 students collected from June 1 to 30 in 2022 using structured questionnaires as students in the Department of Radiology(science). Collected data were analyzed using descriptive statistics, t-test, ANOVA, Cronbach's pearson's correlation, multiple regression analysis with SPSS/WIN 21.0. The result of the study showed that the other behaviors were in the order of 'having s different thought, and 'sending text messages'. other behaviors was 1.75, self-directed learning ability was 3.60, flow was 3.23 and academic achievement was 4.29. There was a significant negative correlation between other behaviors and self-directed learning ability, flow, academic achievement. Factors influencing other behaviors were academic achievement, age, flow, self-directed learning ability in that order. As a result of the above research. it is expected that specific measures and various teaching methods to be flowed in the class are need as the way to lower the other behaviors of university students in the Department of Radiology(science) is to increase academic achievement.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.189-196
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• 2023

This paper analyzes the level of satisfaction of two groups of teachers who were educated about artificial intelligence using App Inventor. The participants were 13 pre-service and 9 in-service elementary school teachers and the data was collected using a questionnaire. As a result of the study, in-service teachers were all more satisfied than pre-service teachers in terms of interest, difficulty, and participation in the education. In addition, the questions investigating whether education helped motivate learning of artificial intelligence and whether there is a willingness to apply it to elementary classes in the future were also more positive for in-service teachers than for pre-service teachers. In general, pre-service teachers had somewhat more negative views than in-service teachers, but they were more positive than in-service teachers in terms of whether the education helped improve their understanding of artificial intelligence and whether they were willing to participate in additional education. Analysis of the Mann-Whitney test to see if there was a significant difference in satisfaction between the two groups showed no significance. This may be because most of the students in the two groups already had block-type or text-type programming experience, so they were able to participate in the education without any special resistance or difficulty with App Inventor, resulting in high levels of satisfaction from both groups. The results of this study can provide basic data for the future development and operation of programs for artificial intelligence education for both pre-service and in-service elementary school teachers.

• Therapeutic Science for Rehabilitation
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• v.11 no.4
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• pp.23-39
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• 2022

Objective : To summarize clinical and demographic variables and machine learning uses for predicting functional outcomes of patients with stroke. Methods : We searched PubMed, CINAHL and Web of Science to identify published articles from 2010 to 2021. The search terms were "machine learning OR data mining AND stroke AND function OR prediction OR/AND rehabilitation". Articles exclusively using brain imaging techniques, deep learning method and articles without available full text were excluded in this study. Results : Nine articles were selected for this study. Support vector machines (19.05%) and random forests (19.05%) were two most frequently used machine learning models. Five articles (55.56%) demonstrated that the impact of patient initial and/or discharge assessment scores such as modified ranking scale (mRS) or functional independence measure (FIM) on stroke patients' functional outcomes was higher than their clinical characteristics. Conclusions : This study showed that patient initial and/or discharge assessment scores such as mRS or FIM could influence their functional outcomes more than their clinical characteristics. Evaluating and reviewing initial and or discharge functional outcomes of patients with stroke might be required to develop the optimal therapeutic interventions to enhance functional outcomes of patients with stroke.

• Therapeutic Science for Rehabilitation
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• v.11 no.3
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• pp.23-36
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• 2022

Objectives : This study aimed to provide basic data on intervention strategies that occupational therapists can access by systematically analyzing the intervention and effectiveness for youth with disabilities. Methods : The RISS, PubMed, and Web of Science databases were used to search for papers published between 2006 and 2021. The keywords were "Disability AND Adolescents OR Young adult AND Transition education OR Transition program". Seven papers were selected for analysis, and the full text was reviewed. The keywords and national relations were analyzed and visualized using the WoS (Web of Science) and VOSviewer programs. Results : The participants were classified into five types (ASD or ADHD, ID, DD, and physical disability). The areas used for the intervention were mixed into three categories: occupation (academic), self-management (time), and interaction (personal relations and communication). Sociality and adaptation, quality of life, and at least one of the three categories of daily life activities showed significant improvement. Conclusions : This study can be used as basic data to expand the area where only OTs can contribute while grasping the research trend of the conversion program and presenting the direction of exchange with various experts by organizing the application and its effects.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.675-681
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• 2021

With the recent growth of the AI speaker market, the demand for speech synthesis technology that enables natural conversation with users is increasing. Therefore, there is a need for a multi-speaker speech synthesis system that can generate voices of various tones. In order to synthesize natural speech, it is required to train with a large-capacity. high-quality speech DB. However, it is very difficult in terms of recording time and cost to collect a high-quality, large-capacity speech database uttered by many speakers. Therefore, it is necessary to train the speech synthesis system using the speech DB of a very large number of speakers with a small amount of training data for each speaker, and a technique for naturally expressing the tone and rhyme of multiple speakers is required. In this paper, we propose a technology for constructing a speaker encoder by applying the deep learning-based x-vector technique used in speaker recognition technology, and synthesizing a new speaker's tone with a small amount of data through the speaker encoder. In the multi-speaker speech synthesis system, the module for synthesizing mel-spectrogram from input text is composed of Tacotron2, and the vocoder generating synthesized speech consists of WaveNet with mixture of logistic distributions applied. The x-vector extracted from the trained speaker embedding neural networks is added to Tacotron2 as an input to express the desired speaker's tone.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.211-223
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• 2022

This study aims to verify the possibility of using the blog mining to collect public opinion in the field of housing policy, thus, it collected blog posts with the keyword 'Happy Housing', extracted the main keywords from them, and analyzed the public's perception through keyword and word cluster analysis. 137,002 blog posts were used as analysis data from May 2013, when social discussion about happy housing spread, to August 2021, and the words derived by dividing the period into three stages in consideration of major housing policies and data collection were analyzed. The results are as follows. In the keyword analysis, overall, the importance of words related to the location, the number, the size, and the conditions for occupancy of Happy Housing is high. In the first stage, government policy implementation, in the second stage, the application process for Happy Housing, and in the third stage, recruitment notices, occupancy qualifications, and rental conditions are found to be highly important. In cluster analysis, project progress, application process, and project area were drawn as main themes at all stages. In particular, policy implementation and implementation plan in the first stage, occupancy qualification and financial support in the second stage, and policy implementation and occupancy qualification in the third stage were drawn as main themes. These results present the possibility of the blog mining as a method of collecting public opinion by sharing policy-related information, reflecting social issues, evaluating whether policies are delivered, and inferring the public's participation in policies.