• Title/Summary/Keyword: AI Solutions

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A Case Study on Quality Improvement of Electric Vehicle Hairpin Winding Motor Using Deep Learning AI Solution (딥러닝 AI 솔루션을 활용한 전기자동차 헤어핀 권선 모터의 용접 품질향상에 관한 사례연구)

  • Lee, Seungzoon;Sim, Jinsup;Choi, Jeongil
    • Journal of Korean Society for Quality Management
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    • v.51 no.2
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    • pp.283-296
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    • 2023
  • Purpose: The purpose of this study is to actually implement and verify whether welding defects can be detected in real time by utilizing deep learning AI solutions in the welding process of electric vehicle hairpin winding motors. Methods: AI's function and technological elements using synthetic neural network were applied to existing electric vehicle hairpin winding motor laser welding process by making special hardware for detecting electric vehicle hairpin motor laser welding defect. Results: As a result of the test applied to the welding process of the electric vehicle hairpin winding motor, it was confirmed that defects in the welding part were detected in real time. The accuracy of detection of welds was achieved at 0.99 based on mAP@95, and the accuracy of detection of defective parts was 1.18 based on FB-Score 1.5, which fell short of the target, so it will be supplemented by introducing additional lighting and camera settings and enhancement techniques in the future. Conclusion: This study is significant in that it improves the welding quality of hairpin winding motors of electric vehicles by applying domestic artificial intelligence solutions to laser welding operations of hairpin winding motors of electric vehicles. Defects of a manufacturing line can be corrected immediately through automatic welding inspection after laser welding of an electric vehicle hairpin winding motor, thus reducing waste throughput caused by welding failure in the final stage, reducing input costs and increasing product production.

ON GENERALIZED FLOQUET SYSTEMS II

  • EI-Owaidy, H.;Zagrout, A.A.
    • Kyungpook Mathematical Journal
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    • v.27 no.1
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    • pp.35-41
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    • 1987
  • Consider the system (i) x'=Ax. Let ${\Phi}$ be its fundamental matrix solution. If there is w>0 such that A(t+w)-A(t) commutes with ${\Phi}$ for all t, then we call this system a "generalized" Floquet system or a "G. F. system". We show that $A(t+w)-A(t)=B_1$=constant if and only if $A(t)=C+B_1t/w+Q(t)$, Q is periodic of period w>0. For this A(t) We prove that if all eigenvalues of $B_1$ have negative real parts, then the origin is asumptotically stable. We find a growth condition for a continuous D(t) which guarantees that all solutions of z'=[A(t)+D(t)]z are bounded if all solutions of the G. F. system (i) are bounded. Combining the foregoing results yield a class of perturbed G. F. operators all of whose solutions are bounded.

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Verification of the effectiveness of AI education for Non-majors through PJBL-based data analysis (PJBL기반 데이터 분석을 통한 비전공자의 AI 교육 효과성 검증)

  • Baek, Su-Jin;Park, So-Hyun
    • Journal of Digital Convergence
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    • v.19 no.9
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    • pp.201-207
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    • 2021
  • As artificial intelligence gradually expands into jobs, iIt is necessary to nurture talents with AI literacy capabilities required for non-majors. Therefore, in this study, based on the necessity and current status of AI education, AI literacy competency improvement education was conducted for non-majors so that AI learning could be sustainable in relation to future majors. For non-majors at University D, problem-solving solutions through project-based data analysis and visualization were applied over 15 weeks, and the AI ability improvement and effectiveness of learners before and after education were analyzed and verified. As a result, it was possible to confirm a statistically significant level of positive change in the learners' data analysis and utilization ability, AI literacy ability, and AI self-efficacy. In particular, it not only improved the learners' ability to directly utilize public data to analyze and visualize it, but also improved their self-efficacy to solve problems by linking this with the use of AI.

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.

Odd solutions to perturbed conservation laws

  • Jerome A. Goldstein;Park, Mi-Ai
    • Bulletin of the Korean Mathematical Society
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    • v.33 no.4
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    • pp.521-530
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    • 1996
  • This paper treats the existence of odd solutions of the Cauchy problem for a perturbation of a conservation law.

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Predicting User Acceptance of Strong AI using Extension of Theory of Planned Behavior: Focused on the Age Group of 20s (확장된 계획적 행동이론을 통해 본 강한 인공지능 제품에 대한 이용자의 수용의도: 20대 연령층을 중심으로)

  • Rhee, Chang Seop;Rhee, Hyunjung
    • The Journal of the Korea Contents Association
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    • v.20 no.10
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    • pp.284-293
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    • 2020
  • The rapid progress of AI technology gives us the expectation to solutions to various problems in our society, and at the same time, it gives us anxiety about the side effects that can occur if AI develops beyond human control. This study was conducted in the early 20s with less objection to advanced devices. We attempted to provide clues to understand thoughts and attitudes of the targets about the future environment that will be brought by AI through the process of finding intent the acceptance of strong AI technology. For this, we applied the Theory of Planned Behavior, and further expanded this research model to identify factors affecting the attitude toward AI. As a result, the attitude toward AI and perceived behavioral control had a significant effect on the intention to use to strong AI. In addition, we found that the expectation of the benefit of improving task performance and the anxiety on the threat of relationship disturbance had a significant effect on the attitude toward AI. This study suggests implications for AI-related companies establishing the direction of technology development and for government setting a policy direction for AI adoption.

Generative AI Technology Trends and Development Prospects for Digital Asset Creation (디지털 에셋 창작을 위한 생성형 AI 기술 동향 및 발전 전망)

  • K.S. Lee;S.W. Lee;M.S. Yoon;J.J. Yu;A.R. Oh;I.M. Choi;D.W. Kim
    • Electronics and Telecommunications Trends
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    • v.39 no.2
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    • pp.33-42
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    • 2024
  • With the recent rapid development of artificial intelligence (AI) technology, its use is gradually expanding to include creative areas and building new content using generative AI solutions, reaching beyond existing data analysis and reasoning applications. Content creation using generative AI faces challenges owing to technical limitations and other aspects such as copyright compliance. Nevertheless, generative AI may increase the productivity of experts and overcome barriers to creative work by allowing users to easily express their ideas as digital content. Thus, various types of applications will continue to emerge. As images and videos can be created using text input on a prompt, generative AI allows to create and edit digital assets quickly. We present trends in generative AI technology for images, videos, three-dimensional (3D) assets and scenes, digital humans, interactive content, and interfaces. In addition, the prospects for future technological development in this field are discussed.

A Study on the Image Search System using Mobile Internet (사례 기반 추론법을 이용한 오델로 게임 개발에 관한 연구)

  • Song, Eun-Jee
    • Journal of Digital Contents Society
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    • v.12 no.2
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    • pp.217-223
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    • 2011
  • AI(Artificial Intelligence) refers to the area of computer engineering and IT technology that focuses on the methodology and creation of intelligent agents. The Othello game is often produced with AI, since it is played with relatively simple rules on a board and on a limited space of 8 rows and 8 columns. Previous algorithms take longer time than desirable and often fail to face new circumstances, as they search for all the possible cases and rules. In order to solve this crucial weakness, we propose that a CBR algorithm be applied to Orthello. Case-Based Reasoning(CBR), is the process of solving new problems based on the solutions of the past similar problems. We can apply this process to Othello and expedite the process of computer reasoning for a solution to new cases based on the data from accumulated past cases. Then, these new solutions are dynamically added to the set of past cases so that it becomes harder for players(users) to be able to read the pattern. The proposed system in which a CBR algorithm is applied to the Othello game makes the computation process faster and the game harder to play.

Analysis of Perceptions and Differences between Groups regarding Generative AI (생성형 AI에 관한 인식 및 집단간 차이 분석)

  • Kyoo-Sung Noh
    • Journal of Digital Convergence
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    • v.22 no.1
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    • pp.15-21
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    • 2024
  • The purpose of this study is to analyze the use of generative AI and the perception of differences between user groups. This study explored the perceptions of different user groups regarding generative AI, aiming to derive implications for enhancing AI utilization capabilities for each group. Upon analysis, it was found that there were no significant differences in perceptions across age groups. However, notable differences were observed between professional backgrounds, particularly in the areas of generative AI application and ethical perspectives. Consequently, this study suggests the need for diversified AI solutions tailored to specific fields of expertise. It underscores the importance of customized education and training programs, as well as specialized education focused on ethical considerations. Additionally, this research contributes academically by proposing varied AI usage strategies for different age and professional groups. It also highlights the role of text mining techniques in developing and improving AI utilization skills.