• Title/Summary/Keyword: AI Importance

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Efficacy analysis for the Radar-based Artificial Intelligence (AI) Scientific Guard System based on AHP (AHP를 활용한 레이더 기반 AI 과학화 경계시스템 효과 분석)

  • Minam Moon;Kyuyong Shin;Hochan Lee;Seunghyun Gwak
    • Convergence Security Journal
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    • v.22 no.5
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    • pp.135-143
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    • 2022
  • The defense environment is rapidly changing, such as nuclear and missile threats of North Korea, changes in war patterns, and a decrease in military service resources due to low birth rate. In order to actively respond to these changes, the Korean military is promoting Defense Innovation 4.0 and is trying to foster an army armed with high technology such as artificial intelligence (AI), big data analysis, etc. In this regard, we analyze the effectiveness of the radar-based AI scientific guard system applied by high technology for guard operations using Analytic Hierarchy Process (AHP). We first select evaluation factors that can assess the effectiveness of the scientific guard system, and analyze its relative importance. Each evaluation factor was selected by deriving a significant concept from operating principle and how they work, and by consulting experts on the correlation between each factor and effectiveness of the scientific guard system. We examine the relative effects of the radar-based AI scientific guard system and existing scientific guard system based on the importance of the evaluation factors.

Application of Artificial Intelligence for the Management of Oral Diseases

  • Lee, Yeon-Hee
    • Journal of Oral Medicine and Pain
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    • v.47 no.2
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    • pp.107-108
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    • 2022
  • Artificial intelligence (AI) refers to the use of machines to mimic intelligent human behavior. It involves interactions with humans in clinical settings, and augmented intelligence is considered as a cognitive extension of AI. The importance of AI in healthcare and medicine has been emphasized in recent studies. Machine learning models, such as genetic algorithms, artificial neural networks (ANNs), and fuzzy logic, can learn and examine data to execute various functions. Among them, ANN is the most popular model for diagnosis based on image data. AI is rapidly becoming an adjunct to healthcare professionals and is expected to be human-independent in the near future. The introduction of AI to the diagnosis and treatment of oral diseases worldwide remains in the preliminary stage. AI-based or assisted diagnosis and decision-making will increase the accuracy of the diagnosis and render treatment more precise and personalized. Therefore, dental professionals must actively initiate and lead the development of AI, even if they are unfamiliar with it.

Criteria for implementing artificial intelligence systems in reproductive medicine

  • Enric Guell
    • Clinical and Experimental Reproductive Medicine
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    • v.51 no.1
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    • pp.1-12
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    • 2024
  • This review article discusses the integration of artificial intelligence (AI) in assisted reproductive technology and provides key concepts to consider when introducing AI systems into reproductive medicine practices. The article highlights the various applications of AI in reproductive medicine and discusses whether to use commercial or in-house AI systems. This review also provides criteria for implementing new AI systems in the laboratory and discusses the factors that should be considered when introducing AI in the laboratory, including the user interface, scalability, training, support, follow-up, cost, ethics, and data quality. The article emphasises the importance of ethical considerations, data quality, and continuous algorithm updates to ensure the accuracy and safety of AI systems.

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.

A Study on the Importance of Software Quality-in-use for Educational Chatbot: Using the AHP Method (학습용 챗봇 소프트웨어 사용 품질 특성의 중요도 연구: AHP기법을 활용하여)

  • Yunjeung Min;Jaekyoung Ahn
    • Journal of Information Technology Services
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    • v.23 no.5
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    • pp.59-72
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    • 2024
  • Recent advancements in IT technology and infrastructure have led to the widespread application of AI chatbots across various fields, including education, where they have shown effectiveness in improving classroom focus and achievement [1][2]. This study analyzes the importance of quality-in-use for AI chatbots in elementary Korean language learning based on ISO/IEC 25000 Quality-in-use standards, aiming to provide quality evaluation criteria for future educational chatbot development. The research methodology involved a two-tier hierarchy of 5 main characteristics and 13 sub-characteristics of quality-in-use, with surveys conducted among industry professionals and instructors after preliminary investigations. Results showed that situational adaptability, effectiveness, and efficiency were prioritized in the main characteristics. In sub-characteristics, situational completeness, learning accuracy, and flexibility were top-ranked. Instructors emphasized the importance of risk mitigation, reflecting their concern for reducing private education costs and improving learning environments. Industry professionals prioritized completeness in chatbot outputs. These findings suggest that prioritizing instructor-valued features in subject-based learning chatbots can enhance their utility and effectiveness in educational settings. The study also highlights the potential for leveraging differences in quality evaluation priorities between industry professionals and instructors in developing learning chatbots

Security Threats to Enterprise Generative AI Systems and Countermeasures (기업 내 생성형 AI 시스템의 보안 위협과 대응 방안)

  • Jong-woan Choi
    • Convergence Security Journal
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    • v.24 no.2
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    • pp.9-17
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    • 2024
  • This paper examines the security threats to enterprise Generative Artificial Intelligence systems and proposes countermeasures. As AI systems handle vast amounts of data to gain a competitive edge, security threats targeting AI systems are rapidly increasing. Since AI security threats have distinct characteristics compared to traditional human-oriented cybersecurity threats, establishing an AI-specific response system is urgent. This study analyzes the importance of AI system security, identifies key threat factors, and suggests technical and managerial countermeasures. Firstly, it proposes strengthening the security of IT infrastructure where AI systems operate and enhancing AI model robustness by utilizing defensive techniques such as adversarial learning and model quantization. Additionally, it presents an AI security system design that detects anomalies in AI query-response processes to identify insider threats. Furthermore, it emphasizes the establishment of change control and audit frameworks to prevent AI model leakage by adopting the cyber kill chain concept. As AI technology evolves rapidly, by focusing on AI model and data security, insider threat detection, and professional workforce development, companies can improve their digital competitiveness through secure and reliable AI utilization.

Impact of Artificial Intelligence on the Development of Art Projects: Opportunities and Limitations

  • Zheng, Xiang;Xiong, Jinghao;Cao, Xiaoming;Nazarov, Y.V.
    • International Journal of Computer Science & Network Security
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    • v.22 no.9
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    • pp.343-347
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    • 2022
  • To date, the use of artificial intelligence has already brought certain results in such areas of art as poetry, painting, and music. The development of AI and its application in the creative process opens up new perspectives, expanding the capabilities of authors and attracting a new audience. The purpose of the article is to analyze the essential, artistic, and technological limitations of AI art. The article discusses the methods of attracting AI to artistic practices, carried out a comparative analysis of the methods of using AI in visual art and in the process of writing music, identified typical features in the creative interaction of the author of a work of art with AI. The basic principles of working with AI have been determined based on the analysis of ways of using AI in visual art and music. The importance of neurobiology mechanisms in the course of working with AI has been determined. The authors conclude that art remains an area in which AI still cannot replace humans, but AI contributes to the further formation of methods for modifying and rethinking the data obtained into innovative art projects.

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.

Natural Selection in Artificial Intelligence: Exploring Consequences and the Imperative for Safety Regulations

  • Seokki Cha
    • Asian Journal of Innovation and Policy
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    • v.12 no.2
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    • pp.261-267
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    • 2023
  • In the paper of 'Natural Selection Favors AIs over Humans,' Dan Hendrycks applies principles of Darwinian evolution to forecast potential trajectories of AI development. He proposes that competitive pressures within corporate and military realms could lead to AI replacing human roles and exhibiting self-interested behaviors. However, such claims carry the risk of oversimplifying the complex issues of competition and natural selection without clear criteria for judging whether AI is selfish or altruistic, necessitating a more in-depth analysis and critique. Other studies, such as ''The Threat of AI and Our Response: The AI Charter of Ethics in South Korea,' offer diverse opinions on the natural selection of artificial intelligence, examining major threats that may arise from AI, including AI's value judgment and malicious use, and emphasizing the need for immediate discussions on social solutions. Such contemplation is not merely a technical issue but also significant from an ethical standpoint, requiring thoughtful consideration of how the development of AI harmonizes with human welfare and values. It is also essential to emphasize the importance of cooperation between artificial intelligence and humans. Hendrycks's work, while speculative, is supported by historical observations of inevitable evolution given the right conditions, and it prompts deep contemplation of these issues, setting the stage for future research focused on AI safety, regulation, and ethical considerations.

Enablers and Inhibitors of Generative AI Usage Intentions in Work Environments (업무 환경에서 생성형 AI 사용 의도에 영향을 미치는 촉진 요인과 저해 요인 분석)

  • Park, JunSung;Park, Heejun
    • Journal of Korean Society for Quality Management
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    • v.52 no.3
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    • pp.509-527
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    • 2024
  • Purpose: This study aims to investigate the factors influencing the adoption of Generative AI in the workplace, focusing on both enablers and inhibitors. By employing the dual factor theory, this research examines how knowledge support, customization, entertainment, perceived risk, realistic threat, and identity threat impact the intention to adopt Generative AI technologies such as ChatGPT. Methods: Data were collected from 192 participants via MTurk, all of whom had experience using Generative AI. The survey was conducted in June 2024, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to ensure the validity and reliability of the measurement model. Attention-check questions were used to ensure data quality, and participants provided demographic information at the end of the survey. Results: : The findings reveal that knowledge support and entertainment significantly enhance the intention to adopt Generative AI, whereas realistic threat poses a substantial barrier. Customization, perceived risk, and identity threat did not significantly affect adoption intentions. Conclusion: This study contributes to the literature by addressing the gap in understanding the adoption mechanisms of Generative AI in professional settings. It highlights the importance of promoting AI's knowledge support and entertainment capabilities while addressing employees' concerns about job security. Organizations should emphasize these benefits and proactively mitigate perceived threats to foster a positive reception of Generative AI technologies. The findings offer practical implications for enhancing user acceptance and provide a foundation for future research in this area.