• Title/Summary/Keyword: AI knowledge

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Implementation of Autonomous IoT Integrated Development Environment based on AI Component Abstract Model (AI 컴포넌트 추상화 모델 기반 자율형 IoT 통합개발환경 구현)

  • Kim, Seoyeon;Yun, Young-Sun;Eun, Seong-Bae;Cha, Sin;Jung, Jinman
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.5
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    • pp.71-77
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    • 2021
  • Recently, there is a demand for efficient program development of an IoT application support frameworks considering heterogeneous hardware characteristics. In addition, the scope of hardware support is expanding with the development of neuromorphic architecture that mimics the human brain to learn on their own and enables autonomous computing. However, most existing IoT IDE(Integrated Development Environment), it is difficult to support AI(Artificial Intelligence) or to support services combined with various hardware such as neuromorphic architectures. In this paper, we design an AI component abstract model that supports the second-generation ANN(Artificial Neural Network) and the third-generation SNN(Spiking Neural Network), and implemented an autonomous IoT IDE based on the proposed model. IoT developers can automatically create AI components through the proposed technique without knowledge of AI and SNN. The proposed technique is flexible in code conversion according to runtime, so development productivity is high. Through experimentation of the proposed method, it was confirmed that the conversion delay time due to the VCL(Virtual Component Layer) may occur, but the difference is not significant.

Present Status and Future of AI-based Drug Discovery (신약개발에서의 AI 기술 활용 현황과 미래)

  • Jung, Myunghee;Kwon, Wonhyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.12
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    • pp.1797-1808
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    • 2021
  • Artificial intelligence is considered one of the core technologies leading the 4th industrial revolution. It is adopted in various fields bringing about a huge paradigm shift throughout our society. The field of biotechnology is no exception. It is undergoing innovative development by converging with other disciplines such as computers, electricity, electronics, and so on. In drug discovery and development, big data-based AI technology has a great potential of improving the efficiency and quality of drug development, rapidly advancing to overcome the limitations in the existing drug development process. AI technology is to be specialized and developed for the purpose including clinical efficacy and safety-related end points based on the multidisciplinary knowledge such as biology, chemistry, toxicology, pharmacokinetics, etc. In this paper, we review the current status of AI technology applied for drug discovery and consider its limitations and future direction.

Methods for Implementing Environmental Education in Elementary Schools by using AI Programming (초등교육에서 인공지능 프로그래밍을 활용한 환경교육 적용 방법)

  • Lee, Yongbae
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.309-314
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    • 2021
  • Even though environmental education has been getting more attention along with the recent rapid increase of natural disasters such as heat wave, heavy snow and downpour, it is unlikely for elementary schools to provide actual lessons due to the shortage of financial support and educational resources. This study is designed to enhance the recycling judgement of the elementary students to define paper, glass, plastic, PET, metal by using AI programming. The survey from the student participants shows that the learning and practice with AI programming was positively helpful for more than 70% of the participants in knowledge obtaining and understanding of recycling. The participants also gained better understanding on artificial intelligence and got motivated to have more opportunities to learn artificial intelligence programming.

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'Knowing' with AI in construction - An empirical insight

  • Ramalingham, Shobha;Mossman, Alan
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.686-693
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    • 2022
  • Construction is a collaborative endeavor. The complexity in delivering construction projects successfully is impacted by the effective collaboration needs of a multitude of stakeholders throughout the project life-cycle. Technologies such as Building Information Modelling and relational project delivery approaches such as Alliancing and Integrated Project Delivery have developed to address this conundrum. However, with the onset of the pandemic, the digital economy has surged world-wide and advances in technology such as in the areas of machine learning (ML) and Artificial Intelligence (AI) have grown deep roots across specializations and domains to the point of matching its capabilities to the human mind. Several recent studies have both explored the role of AI in the construction process and highlighted its benefits. In contrast, literature in the organization studies field has highlighted the fear that tasks currently done by humans will be done by AI in future. Motivated by these insights and with the understanding that construction is a labour intensive sector where knowledge is both fragmented and predominantly tacit in nature, this paper explores the integration of AI in construction processes across project phases from planning, scheduling, execution and maintenance operations using literary evidence and experiential insights. The findings show that AI can complement human skills rather than provide a substitute for them. This preliminary study is expected to be a stepping stone for further research and implementation in practice.

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Knowledge-Grounded Dialogue Generation Using Prompts Combined with Expertise and Dialog Policy Prediction (전문 지식 및 대화 정책 예측이 결합된 프롬프트를 활용한 지식 기반 대화 생성)

  • Eojin Joo;Chae-Gyun Lim;DoKyung Lee;JunYoung Youn;Joo-Won Sung;Ho-Jin Choi
    • Annual Conference on Human and Language Technology
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    • 2023.10a
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    • pp.409-414
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    • 2023
  • 최근 지식 기반 대화 생성에 많은 연구자가 초점을 맞추고 있다. 특히, 특정 도메인에서의 작업 지향형 대화 시스템을 구축하는 것은 다양한 도전 과제가 있으며, 이 중 하나는 거대 언어 모델이 입력과 관련된 지식을 활용하여 응답을 생성하는 데 있다. 하지만 현재 거대 언어 모델은 작업 지향형 대화에서 단순히 정보를 열거하는 방식으로 응답을 생성하는 경향이 있다. 이 논문에서는 전문 지식과 대화 정책 예측 모델을 결합한 프롬프트를 제시하고 작업 지향형 대화에서 사용자의 최근 입력에 대한 정보 제공 및 일상 대화를 지원하는 가능성을 탐구한다. 이러한 새로운 접근법은 모델 파인튜닝에 비해 비용 측면에서 효율적이며, 향후 대화 생성 분야에서 발전 가능성을 제시한다.

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A Study on Public Library Book Location Guidance System based on AI Vision Sensor

  • Soyoung Kim;Heesun Kim
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.3
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    • pp.253-261
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    • 2024
  • The role of the library is as a public institution that provides academic information to a variety of people, including students, the general public, and researchers. These days, as the importance of lifelong education is emphasized, libraries are evolving beyond simply storing and lending materials to complex cultural spaces that share knowledge and information through various educational programs and cultural events. One of the problems library user's faces is locating books to borrow. This problem occurs because of errors in the location of borrowed books due to delays in updating library databases related to borrowed books, incorrect labeling, and books temporarily located in different locations. The biggest problem is that it takes a long time for users to search for the books they want to borrow. In this paper, we propose a system that visually displays the location of books in real time using an AI vision sensor and LED. The AI vision sensor-based book location guidance system generates a QR code containing the call number of the borrowed book. When the AI vision sensor recognizes this QR code, the exact location of the book is visually displayed through LED to guide users to find it easily. We believe that the AI vision sensor-based book location guidance system dramatically improves book search and management efficiency, and this technology is expected to have great potential for use not only in libraries and bookstores but also in a variety of other fields.

A study on Discount in Prior Experience of AI and Acceptance: Focusing on AI Effect (인공지능 사전경험 무시 현상과 수용에 관한 연구: AI Effect를 중심으로)

  • Lee, JeongSeon
    • Journal of Digital Convergence
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    • v.20 no.3
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    • pp.241-249
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    • 2022
  • Artificial intelligence is applied not only to the daily life of individuals but also to all industries, and it is no wonder that the age of artificial intelligence has arrived. Therefore it is important to understand the factors that influence the acceptance of AI. This study analyzes whether "AI Effect" which recognizes that commercialized or familiar artificial intelligence is no longer artificial intelligence, affects the acceptance of artificial intelligence and proposes an acceptance plan based on the results. Two experiments were conducted. The first experiment was conducted on 105 adults in the result it was found that 32.4% (34 people) had AI Effect, AI Effect existed in 43.6% (24 people) of women and 20% (10 people) of men, that is, the proportion of AI Effect exsitence in women is about twice as high.and AI Effect exists when the level of AI knowledge is low. The second experiment was conducted 240 adults and 85 participants with AI Effect were selected. We found the group that recognized experience of AI accepted AI more actively. Understanding of AI Effect is expected to suggest companies' views in order to enhance AI capabilities and acceptance. In addition, future studies are expected on considering individual differences or related to acceptance attitudes.

Knowledge Based and Object-Oriented Simulation Model for Logistics Analysis (지식기반 객체지향 군수시뮬레이션 모델에 관한 연구 - 초기군수지원성 분석모델을 중심으로 -)

  • 마호명;최상영
    • Journal of the military operations research society of Korea
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    • v.22 no.1
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    • pp.67-80
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    • 1996
  • Artificial Intelligence(AI) techniques and Object-Oriented(OO) techniques contribute to the simulation modeling of the complex systems. AI techniques are suitable to model human reasoning in the simulation. While OO techniques have advantages of re-usability, maintainability and extendability of the software. Thus, in this paper, we design a knowledge-based object-oriented simulation model, particularly for the logistics analysis of military armor vehicles. The simulation model consists of three modules i.e., scenario, simulation mechanism, and inference engine. The model is designed within the OO paradigm and implemented by using the C++ language. An example case of using the model for the logistic analysis is included.

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Special Topic: The Impact of ChatGPT in Society, Business, and Academia

  • Kyoung Jun Lee;Taeho Hong;Hyunchul Ahn;Taekyung Kim;Chulmo Koo
    • Asia pacific journal of information systems
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    • v.33 no.4
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    • pp.957-976
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    • 2023
  • ChatGPT has had a significant impact on society, business, and academia by influencing individuals and organizations through knowledge generation and supporting users in locating conversational inquiries and answers. It can transform how people seek answers by combining human-like conversational skills with AI. By eradicating the cumbersome process of selecting from multiple options, users can conduct preliminary research or create optimized solutions. The purpose of this research is to investigate how consumers use ChatGPT and digital transformation, specifically in terms of knowledge development, searching and recommending, and optimizing accessible possibilities. Using many linked theories, we address the potential implications and insights that can be gained from ChatGPT's early stages and its integration with other applications such as robotics, service automation, and the metaverse. Finally, the application of ChatGPT has practical, theoretical, and phenomenological impacts, in addition to improving users' experiences.

Development of the Contents of AI Convergence Education Method Subjects and Verification of Teaching Efficacy Effectiveness for Elementary and Secondary Teachers

  • Kim, Jeong-Rang
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.3
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    • pp.217-223
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    • 2022
  • In this paper, the needs and environment of the 'AI Convergence Education Method' were analyzed for elementary and secondary teachers, and based on this, teaching efficacy of informatics education was verified. For the research, elementary and secondary teachers who take the subject were selected, and based on the results of analyzing the general characteristics, pre-knowledge level, and needs of the subject, curriculum for 15 weeks was developed. As a result of verifying the teaching efficacy effectiveness of the developed 'AI Convergence Education Method' subject for 15 weeks, the effectiveness of the information education teaching efficacy was verified. Among the factors, there were statistically significant differences in information teaching values and information teaching strategies. In the future, it is necessary to conduct follow-up research to secure teachers' professionalism, such as linking with schools and convergence with other subjects. Various teaching and learning materials and teaching and learning methods such as educational contents and materials, reference literature, and artificial intelligence education platforms need to be prepared.