• Title/Summary/Keyword: Artificial Intelligence

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Disapproval Judgment System of Research Fund Execution Details Based on Artificial Intelligence

  • Kim, Yongkuk;Juan, Tan;Jung, Hoekyung
    • Journal of information and communication convergence engineering
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    • v.19 no.3
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    • pp.142-147
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    • 2021
  • In this paper, we propose an intelligent research fund management system that applies artificial intelligence technology to an integrated research fund management system. By defining research fund management rules as work rules, a detection model learned using deep learning is designed, through which the disapproval status is presented for each research fund usage history. The disapproval detection system of the RCMS implemented in this study predicts whether the newly registered usage details are recognized or disapproved using an artificial intelligence model designed based on the use of an 8.87 million research fund registered in the RCMS. In addition, the item-detail recommendation system described herein presents the usage details according to the usage history item newly registered by the artificial intelligence model through a correlation between the research cost usage details and the item itself. The accuracy of the recommendation was shown to be 97.21%.

A Study On Parameter Measurement for Artificial Intelligence Object Recognition (인공지능 객체인식에 관한 파라미터 측정 연구)

  • Choi, Byung Kwan
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.15 no.3
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    • pp.15-28
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    • 2019
  • Artificial intelligence is evolving rapidly in the ICT field, smart convergence media system and content industry through the fourth industrial revolution, and it is evolving very rapidly through Big Data. In this paper, we propose a face recognition method based on object recognition based on object recognition through artificial intelligence. In this method, Were experimented and studied through the object recognition technique of artificial intelligence. In the conventional 3D image field, general research on object recognition has been carried out variously, and researches have been conducted on the side effects of visual fatigue and dizziness through 3D image. However, in this study, we tried to solve the problem caused by the quantitative difference between object recognition and object recognition for human factor algorithm that measure visual fatigue through cognitive function, morphological analysis and object recognition. Especially, The new method of computer interaction is presented and the results are shown through experiments.

Standardization Trends on Artificial Intelligence in Medicine (의료 인공지능 표준화 동향)

  • Jeon, J.H.;Lee, K.C.
    • Electronics and Telecommunications Trends
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    • v.34 no.5
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    • pp.113-126
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    • 2019
  • Based on the accumulation of medical big data, advances in medical artificial intelligence technology facilitate the timely treatment of disease through the reading the medical images and the increase of prediction speed and accuracy of diagnoses. In addition, these advances are expected to spark significant innovations in reducing medical costs and improving care quality. There are already approximately 40 FDA approved products in the US, and more than 10 products with K-FDA approval in Korea. Medical applications and services based on artificial intelligence are expected to spread rapidly in the future. Furthermore, the evolution of medical artificial intelligence technology is expanding the boundaries or limits of various related issues such as reference standards and specifications, ethical and clinical validation issues, and the harmonization of international regulatory systems.

Online-Offline Connectivity and Artificial Intelligence : Car Navigation App (온라인-오프라인의 연결 그리고 인공지능 : 자동차 모바일 네비게이션 앱 활용 맥락)

  • Kim, Taekyung
    • Journal of Information Technology Services
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    • v.18 no.1
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    • pp.201-217
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    • 2019
  • Cars have become a necessity in modern life. It is widely used to transport people or products to a destination conveniently. However, the addition of a navigation service that provides route information and more makes driving more convenient and safer. Recent developments in the mobile app ecosystem encourages people to adopt not only an installation-type car navigation, but also a mobile app navigation, supporting connected car concepts. It should be noted that mobile apps with mobile Internet can be a significant linkage between information acquired online and offline business. This study demonstrates the impact of the app use experience for a driver in the context of applying artificial intelligence service. As a result, the introduction of artificial intelligence services has a statistically significant moderating effect on the use of mobile navigation apps. This seminal research is valuable as it evaluates the role of artificial intelligence applied to mobile navigation apps.

Theoretical And Technological Aspects Of Intelligent Systems: Problems Of Artificial Intelligence

  • Frolov, Denys;Radziewicz, Wojciech;Saienko, Volodymyr;Kuchuk, Nina;Mozhaiev, Mykhailo;Gnusov, Yurii;Onishchenko, Yurii
    • International Journal of Computer Science & Network Security
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    • v.21 no.5
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    • pp.35-38
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    • 2021
  • The article discusses approaches to the definition and understanding of artificial intelligence, research directions in the field of artificial intelligence; artificial intelligence in the anthropological dimension; the importance of the systems approach as a methodological basis for the design of intelligent systems; structural and functional components of intelligent systems; intelligent systems in the technological aspect; problems and prospects of relations in the system "man - intellectual system".

Comparative Analysis of Diagnostic Prediction Algorithm Performance for Blood Cancer Factor Validation and Classification (혈액암 인자 유효성 검증과 분류를 위한 진단 예측 알고리즘 성능 비교 분석)

  • Jeong, Jae-Seung;Ju, Hyunsu;Cho, Chi-Hyun
    • Journal of Korea Multimedia Society
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    • v.25 no.10
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    • pp.1512-1523
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    • 2022
  • Artificial intelligence application in digital health care has been increasing with its development of artificial intelligence. The convergence of the healthcare industry and information and communication technology makes the diagnosis of diseases more simple and comprehensible. From the perspective of medical services, its practice as an initial test and a reference indicator may become widely applicable. Therefore, analyzing the factors that are the basis for existing diagnosis protocols also helps suggest directions using artificial intelligence beyond previous regression and statistical analyses. This paper conducts essential diagnostic prediction learning based on the analysis of blood cancer factors reported previously. Blood cancer diagnosis predictions based on artificial intelligence contribute to successfully achieve more than 90% accuracy and validation of blood cancer factors as an alternative auxiliary approach.

Crew Resource Management in Industry 4.0: Focusing on Human-Autonomy Teaming (4차 산업혁명 시대의 CRM: 인간과 자율 시스템의 협업 관점에서)

  • Yun, Sunny;Woo, Simon
    • Korean journal of aerospace and environmental medicine
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    • v.31 no.2
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    • pp.33-37
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    • 2021
  • In the era of the 4th industrial revolution, the aviation industry is also growing remarkably with the development of artificial intelligence and networks, so it is necessary to study a new concept of crew resource management (CRM), which is required in the process of operating state-of-the-art equipment. The automation system, which has been treated only as a tool, is changing its role as a decision-making agent with the development of artificial intelligence, and it is necessary to set clear standards for the role and responsibility in the safety-critical field. We present a new perspective on the automation system in the CRM program through the understanding of the autonomous system. In the future, autonomous system will develop as an agent for human pilots to cooperate, and accordingly, changes in role division and reorganization of regulations are required.

Development of a case-based nursing education program using generative artificial intelligence (생성형 인공지능을 활용한 사례 기반 간호 교육 프로그램 개발)

  • Ahn, Jeonghee;Park, Hye Ok
    • The Journal of Korean Academic Society of Nursing Education
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    • v.29 no.3
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    • pp.234-246
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    • 2023
  • Purpose: This study aimed to develop a case-based nursing education program using generative artificial intelligence and to assess its usability and applicability in nursing curriculums. Methods: The program was developed by following the five steps of the ADDIE model: analysis, design, development, implementation, and evaluation. A panel of five nursing professors served as experts to implement and evaluate the program. Results: Utilizing ChatGPT, six program modules were designed and developed based on experiential learning theory. The experts' evaluations confirmed that the program was suitable for case-based learning, highly usable, and applicable to nursing education. Conclusion: Generative artificial intelligence was identified as a valuable tool for enhancing the effectiveness of case-based learning. This study provides insights and future directions for integrating generative artificial intelligence into nursing education. Further research should be attempted to implement and evaluate this program with nursing students.

KE-T5-Based Text Emotion Classification in Korean Conversations (KE-T5 기반 한국어 대화 문장 감정 분류)

  • Lim, Yeongbeom;Kim, San;Jang, Jin Yea;Shin, Saim;Jung, Minyoung
    • Annual Conference on Human and Language Technology
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    • 2021.10a
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    • pp.496-497
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    • 2021
  • 감정 분류는 사람의 사고방식이나 행동양식을 구분하기 위한 중요한 열쇠로, 지난 수십 년간 감정 분석과 관련된 다양한 연구가 진행되었다. 감정 분류의 품질과 정확도를 높이기 위한 방법 중 하나로 단일 레이블링 대신 다중 레이블링된 데이터 세트를 감정 분석에 활용하는 연구가 제안되었고, 본 논문에서는 T5 모델을 한국어와 영어 코퍼스로 학습한 KE-T5 모델을 기반으로 한국어 발화 데이터를 단일 레이블링한 경우와 다중 레이블링한 경우의 감정 분류 성능을 비교한 결과 다중 레이블 데이터 세트가 단일 레이블 데이터 세트보다 23.3% 더 높은 정확도를 보임을 확인했다.

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A Study on Effective Learning Methods Using Artificial Intelligence (인공지능을 활용한 효율적인 학습 방법에 대한 연구)

  • Lee, Haeun;Ju, Hanbin;Bae, Junhyeong;Yoon, Hyunyoung;Kang, Seongkyeong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.170-171
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    • 2022
  • Recently, artificial intelligence has been widely used in various fields. Traditionally, students have studied in cramming methods rather than self-directed learning through schools and numerous extracurricular activities. In order to alleviate the problem of injection-type education, students can be expected to improve their self-directed learning skills by considering the level of students through the artificial intelligence English word app. In this paper, we will propose ways to utilize artificial intelligence for efficient learning.

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