• Title/Summary/Keyword: AI Generated Technology

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Generative AI as a Virtual Conversation Partner in Language Learning

  • Ji-Young Seo;Seon-Ah, Kim
    • International Journal of Advanced Culture Technology
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    • v.12 no.2
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    • pp.7-15
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    • 2024
  • Despite a recent surge in multifaceted research on AI-integrated language learning, empirical studies in this area remain limited. This study adopts a Human-Generative AI parallel processing model to examine students' perceptions, asking 182 college students to independently construct knowledge and then compare their efforts with the results generated through in-classroom conversations with ChatGPT 3.5. In questionnaire responses, most students indicated that they found these activities useful and expressed a keen interest in learning various ways to utilize generative AI for language learning with instructor guidance. The findings confirm that ChatGPT's potential as a virtual conversation partner. Identifying specific reasons for the perceived usefulness of conversation activities and drawbacks of ChatGPT, this study emphasizes the importance of teachers staying informed about both the latest advances in technology and their limitations. We recommend that teachers endeavor to creatively design various classroom activities using AI technology.

Research on Character's Consistency in AI-Generated Paintings

  • Chenghao Wang;Jeanhun Chung
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.3
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    • pp.199-204
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    • 2024
  • This study aims to explore the issue of character consistency in AI-generated artwork. First, the concept of character consistency is explained, including the consistency of appearance, actions, and lighting, and its importance in continuous creation and storytelling is analyzed. Next, the study examines current mainstream AI drawing tools such as MidJourney and Stable Diffusion-based WebUI and ComfyUI, evaluating their strengths and limitations in maintaining character consistency. Finally, methods to improve AI drawing technology were proposed to enhance character consistency, aiming to achieve a higher level of consistency in AI art creation.

User Perception of Ai Self-Organizing Natural Image Generation Analyzed by Cognitive Paradigm

  • Soo-Jin Lee
    • International Journal of Advanced Culture Technology
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    • v.12 no.3
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    • pp.67-72
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    • 2024
  • The algorithm is applied on the premise that the image generated by AI can be recognized and used smoothly by the user. Other assets are not exposed to the user or discarded because they are unnecessary or unfamiliar. This study aims to expand the scope of the utility of the image generated by AI, which is used as a high-level tool in the design field. To this end, we first examined human information processing and reflection in AI by the cognitive paradigm by examining previous studies and cases, and discussed the value of expansion by focusing on creativity and bottom-up processing of AI's self-organization. Considering the human recogmition process that instinctively grasps an object, the following AI usability was proposed. It is to utilize AI as a high-level tool applied appropriately to human perception, or to utilize the derivative itself by bottom-up self-organization. In addition, it is to set the algorithm to the minimum intervention so that basic elements such as shape, color, size, texture, and movement are composed of figure-ground according to the human perception process that instinctively grasps an object, and to utilize the results. Limiting the use of AI to a tool suitable for human perception and information processing or production by designers or general users is to operate only a part of the convenience and usability of AI. The image creation through AI's self-organization, as seen from the cognitive paradigm, is a step toward opening a new era of design where technical aesthetics meets devices, just as design has been constantly developing in pursuit of novelty and differentiation due to its nature.

Structural analysis and design using generative AI

  • Moonsu Park;Gyeongeun Bong;Jungro Kim;Gihwan Kim
    • Structural Engineering and Mechanics
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    • v.91 no.4
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    • pp.393-401
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    • 2024
  • This study explores the integration of the generative AI, specifically ChatGPT (GPT-4o), into the field of structural analysis and design using the finite element method (FEM). The research is conducted in two main parts: structural analysis and structural design. For structural analysis, two scenarios are examined: one where the FEM source code is provided to ChatGPT and one where it is not. The AI's ability to understand, process, and accurately perform finite element analysis in both scenarios is evaluated. Additionally, the application of ChatGPT in structural design is investigated, including design modifications and parameter sensitivity analysis. The results demonstrate the potential of the generative AI to assist in complex engineering tasks, suggesting a future where AI significantly enhances efficiency and innovation in structural engineering. However, the study also highlights the importance of ensuring the accuracy and reliability of AI-generated results, particularly in safety-critical applications.

Analysis of AI Content Detector Tools

  • Yo-Seob Lee;Phil-Joo Moon
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.154-163
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    • 2023
  • With the rapid development of AI technology, ChatGPT and other AI content creation tools are becoming common, and users are becoming curious and adopting them. These tools, unlike search engines, generate results based on user prompts, which puts them at risk of inaccuracy or plagiarism. This allows unethical users to create inappropriate content and poses greater educational and corporate data security concerns. AI content detection is needed and AI-generated text needs to be identified to address misinformation and trust issues. Along with the positive use of AI tools, monitoring and regulation of their ethical use is essential. When detecting content created by AI with an AI content detection tool, it can be used efficiently by using the appropriate tool depending on the usage environment and purpose. In this paper, we collect data on AI content detection tools and compare and analyze the functions and characteristics of AI content detection tools to help meet these needs.

Analysis of Teen Consumers' Perceptions and Behaviors Regarding AI Profile Photography (AI 프로필 사진에 대한 10대 소비자 인식 및 행동 분석)

  • Dohyup Lee;Yoojin Kim
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.5
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    • pp.699-705
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    • 2024
  • The purpose of this study is to explore the positive application direction of this technology by investigating the perception and use of teenage adolescents about the recently emerged AI profile. The development of AI technology has brought about changes in various industries, and the AI profile service, which started in 2023, has gained great popularity as it is widely used as an SNS profile or personal blog image. However, it has recently become a social controversy as it is used for identification purposes such as social ID cards. However, as a result of a survey of adolescents, they did not use AI profiles for the purpose of issuing ID cards. Satisfaction with the AI profile service was high, but there were also complaints about its unnaturalness and limited style. And female students showed higher awareness and experience in using AI profiles than male students. This study can be used as a reference for developing AI profiles and establishing marketing strategies, and preparing national policies related to AI profiles.

Understanding User Perception of Generative AI and Copyright of AI-Generated Outputs: focusing on differences by user group (생성 AI와 AI 창작물 저작권에 대한 사용자의 인식 연구: 사용자 그룹의 차이를 중심으로)

  • Dahye Choi;Jungyong Kim;Daeun Han;Changhoon Oh
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.1
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    • pp.777-786
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    • 2023
  • Generative AI systems are expected to be more widely utilized. However, relatively little attention has been paid to understanding how users perceive and accept generative AI results. To identify strategies for increasing the future use of generative AI and prepare for potential issues, we organized design workshop for the general user group and the designer group. They created artwork utilizing Novel AI and semi-structured interview was followed to evaluate their attitudes toward generative AI and its copyright. Results indicate that the general public views generative AI positively, while the design-related group views it quite negatively. The participants expressed concerns as to the misuse the system, specifically related to copyright issues. People who are likely to utilize generative AI outcomes have insisted more strongly that copyrights should be their own. Those working in the design field highly evaluated the possibility of using generative AI in their work. Copyright perceptions were not significantly influenced by users' satisfaction or their level of involvement in the creation process. We discuss design implications for interfaces using generative AI based on the findings.

Study on AI-based content reproduction system using movie contents (영화를 이용한 AI 기반 콘텐츠 재생산 시스템 연구)

  • Yang, Seokhwan;Lee, Young-Suk
    • Journal of Korea Multimedia Society
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    • v.24 no.2
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    • pp.336-343
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    • 2021
  • AI technology is spreading not only to industrial fields, but also to culture, art, and content fields. In this paper, we proposed a system based on AI technology that can automate the process of reproducing contents using characters for movie contents. After creating the basic appearance of the character by using the StyleGAN2 model from the video extracted from the movie contents, analyzing the character's personality and propensity using the extracted dialogue data, it was determined from the contemplative appearance based on the yin-yang and five elements to the character's propensity. Accordingly, the external characteristics are reflected in the character. Using the OpenPose model, a character's motion is created, and the finally generated data is integrated to reproduce the content. It is expected that many movie contents can be reproduced through the study of the proposed system.

Management Architecture With Multi-modal Ensemble AI Models for Worker Safety

  • Dongyeop Lee;Daesik, Lim;Jongseok Park;Soojeong Woo;Youngho Moon;Aesol Jung
    • Safety and Health at Work
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    • v.15 no.3
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    • pp.373-378
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    • 2024
  • Introduction: Following the Republic of Korea electric power industry site-specific safety management system, this paper proposes a novel safety autonomous platform (SAP) architecture that can automatically and precisely manage on-site safety through ensemble artificial intelligence (AI) models. The ensemble AI model was generated from video information and worker's biometric information as learning data and the estimation results of this model are based on standard operating procedures of the workplace and safety rules. Methods: The ensemble AI model is designed and implemented by the Hadoop ecosystem with Kafka/NiFi, Spark/Hive, HUE, and ELK (Elasticsearch, Logstash, Kibana). Results: The functional evaluation shows that the main function of this SAP architecture was operated successfully. Discussion: The proposed model is confirmed to work well with safety mobility gateways to provide some safety applications.

Transforming mathematics education with AI: Innovations, implementations, and insights

  • Sheunghyun Yeo;Jewoong Moon;Dong-Joong Kim
    • The Mathematical Education
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    • v.63 no.2
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    • pp.387-392
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    • 2024
  • The use of artificial intelligence (AI) in mathematics education has advanced as a means for promoting understanding of mathematical concepts, academic achievement, computational thinking, and problem-solving. From a total of 13 studies in this special issue, this editorial reveals threads of potential and future directions to advance mathematics education with the integration of AI. We generated five themes as follows: (1) using ChatGPT for learning mathematical content, (2) automated grading systems, (3) statistical literacy and computational thinking, (4) integration of AI and digital technology into mathematics lessons and resources, and (5) teachers' perceptions of AI education. These themes elaborate on the benefits and opportunities of integrating AI in teaching and learning mathematics. In addition, the themes suggest practical implementations of AI for developing students' computational thinking and teachers' expertise.