• Electronics and Telecommunications Trends
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• v.34 no.3
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• pp.34-42
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• 2019

This study introduces artificial intelligence (AI) techniques for video generation. For an effective illustration, techniques for video generation are classified as either semi-automatic or automatic. First, we discuss some recent achievements in semi-automatic video generation, and explain which types of AI techniques can be applied to produce films and improve film quality. Additionally, we provide an example of video content that has been generated by using AI techniques. Then, two automatic video-generation techniques are introduced with technical details. As there is currently no feasible automatic video-generation technique that can generate commercial videos, in this study, we explain their technical details, and suggest the future direction for researchers. Finally, we discuss several considerations for more practical automatic video-generation techniques.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.219-222
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• 2016

블록형 구조물의 구축은 완구의 목적으로 널리 사용되고 있으며 이외에도 제품 디자인을 위한 래피드 프로토타이핑 및 창의학습을 위한 도구로도 활용되고 있다. 본 논문은 블록형 구조물을 적은 비용으로 손쉽게 설계하고 구축하기 위하여 블록형 구조물 자동 생성 기능 및 편집 기능을 제공하는 소프트웨어 시스템을 개발하였다. 본 시스템을 이용하여 가상공간에서 자유롭게 블록형 구조물을 생성 및 편집할 수 있고, 실제 구조물의 조립을 위한 매뉴얼로 활용할 수 있다.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.287-293
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• 2023

With the rapid development of domestic and international over-the-top markets, a large amount of video content is being created. As the volume of video content increases, consumers tend to increasingly check data concerning the videos before watching them. To address this demand, video summaries in the form of plot descriptions, thumbnails, posters, and other formats are provided to consumers. This study proposes an approach that automatically generates posters to effectively convey video content while reducing the cost of video summarization. In the automatic generation of posters, face recognition and clustering are used to gather and classify character data, and keyframes from the video are extracted to learn the overall atmosphere of the video. This study used the facial data of the characters and keyframes as training data and employed technologies such as DreamBooth, a text-to-image generation model, to automatically generate video posters. This process significantly reduces the time and cost of video-poster production.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.736-743
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• 2021

Due to COVID-19, the non-face-to-face content market is growing rapidly. However, most of the non-face-to-face content such as webtoons and web novels are produced based on the traditional culture of other countries, not Korean traditional culture. The biggest cause of this situation is the lack of reference materials for creating based on Korean traditional culture. Therefore, the need for materials on traditional Korean culture that can be used for content creation is emerging. In this paper, we propose a generation model of source data based on traditional folk paintings through the fusion of traditional Korean folk paintings and AI technology. The proposed model secures basic data based on folk tales, analyzes the style and characteristics of folk tales, and converts historical backgrounds and various stories related to folk tales into data. In addition, using the built data, various new stories are created based on AI technology. The proposed model is highly utilized in that it provides a foundation for new creation based on Korean traditional folk painting and AI technology.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.288-294
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• 2022

The media content market has been growing, as various types of content are being mass-produced owing to the recent proliferation of the Internet and digital media. In addition, platforms that provide personalized services for content consumption are emerging and competing with each other to recommend personalized content. Existing platforms use a method in which a user directly inputs video metadata. Consequently, significant amounts of time and cost are consumed in processing large amounts of data. In this study, keyframes and audio spectra based on the YCbCr color model of a movie trailer were extracted for the automatic generation of metadata. The extracted audio spectra and image keyframes were used as learning data for genre recognition in deep learning. Deep learning was implemented to determine genres among the video metadata, and suggestions for utilization were proposed. A system that can automatically generate metadata established through the results of this study will be helpful for studying recommendation systems for media super-personalization.

• The Mathematical Education
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• v.61 no.4
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• pp.581-595
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• 2022

The purpose of this study is to specify the procedure for making item models based on ontology models using automatic item generation in the mathematics subject through the CAFA system, and to explore the generated item instances. As an illustration for this, an item model was designed as a part of formative assessment based on the content characteristics, including concepts and calculations, and process characteristics, including application, using the representative values and the measures of dispersion in Mathematics of the 9th grade based on the evaluation criteria achievement standards. The item types generated in one item model were a best answer type, a correct answer type, a combined-response type, an incomplete statement type, a negative type, a true-false type, and a matching type. It was found that HTML, Google Charts, TTS, figures, videos and so on can be used as media. The implications of the use of digital evaluation based on automatic item generation were suggested in the aspects of students, pre-service teachers, general teachers, and special education, and the limitations of this study and future research directions were presented.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.39-45
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• 2020

Despite the increasing interest in cyber security in recent years, the emergence of new technologies has led to a shortage of professional personnel to efficiently perform the cyber security. Although various methods such as cyber rage are being used to cultivate cyber security experts, there are problems of limitation of virtual training system, scenario-based practice content development and operation, unit content-oriented development, and lack of consideration of learner level. In this paper, we develop a fuzzy rule-based user-customized training scenario automatic generation system for improving user's ability to respond to infringement. The proposed system creates and provides scenarios based on advanced persistent threats according to fuzzy rules. Thus, the proposed system can improve the trainee's ability to respond to the bed through the generated scenario.

• Journal of Science Education
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• v.47 no.2
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• pp.211-224
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• 2023

The purpose of this study is to suggest how to investigate the reliability of the assessment, which consists of items generated by automatic item generation using empirical example data. To achieve this, we analyzed the illustrative assessment data by applying the multivariate generalizability theory, which can reflect the design of responding to different items for each student and multiple error sources in the assessment score. The result of the G-study showed that, in most designs, the student effect corresponding to the true score of the classical test theory was relatively large after residual effects. In addition, in the design where the content domain was fixed, the ranking of students did not change depending on the item types or items. Similarly, in the design where the item format was fixed, the difficulty showed little variation depending on the content domains. The result of the D-study indicated that the original assessment data achieved a sufficient level of reliability. It was also found that higher reliability than the original assessment data could be obtained by reducing the number of items in the content domains of operation, geometry, and probability and statistics, or by assigning higher weights to the domains of letters and formulas, and function. The efficient measurement conditions presented in this study are limited to the illustrative assessment data. However, the method applied in this study can be utilized to determine the reliability and to find efficient measurement conditions for the various assessment situations using automatic item generation based on measurement traits.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.4
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• pp.569-579
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• 1994

A 5.9kW phosphoric acid fuel cell(PAFC) power generation system that consists of a reformer, a stack, heat exchangers, an automatic data acquisition and control system was designed, fabricated and analyzed. This system which was firstly fabricated in Korea has been operated for 140 hours with an electricity generation of 684kWh. The PAFC generate electricity in the range of 38-52V and 50-160A and has a typical I-V characteristics of a fuel cell. Using the reformed fuel, the system performance is decreased in some degree due to CO content, compared to using the simulated fuel. At steady state operation condition, the total efficency of this system was 45.2%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.246-249
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• 2005

본 논문에서는 4세대 이동통신을 위한 적응부호화 하이브리드 ARQ 시스템 모델을 제안하고, 제안 시스템의 성능을 분석 검토 하였다. 또한 적응 하이브리드 시스템의 프레임 효율도 분석하였다. 결과로부터 제안 시스템이 성능이나 효율에서 우수함을 확인 할 수 있었다.