• Title/Summary/Keyword: Artificial Intelligence

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Artificial Intelligence In The Modern Educational Space: Problems And Prospects

  • Iasechko, Svitlana;Pereiaslavska, Svitlana;Smahina, Olha;Lupei, Nitsa;Mamchur, Lyudmyla;Tkachova, Oksana
    • International Journal of Computer Science & Network Security
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    • v.22 no.6
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    • pp.25-32
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    • 2022
  • The hypothesis of the study of the article is that the use of elements of artificial intelligence will increase the effectiveness of the educational process of the university if: a set of pedagogical conditions for the construction and use of an expert system with elements of artificial intelligence in the educational process of the university is revealed; a model for preparing a future teacher of vocational training for the use of elements of artificial intelligence has been developed; a special course has been developed that contributes to the implementation of the professional orientation of education. In accordance with this, the following tasks were studied in the article: An analysis of scientific and methodological research in the field of the current state, prospects for the development and use of elements of artificial intelligence in the preparation of a future teacher of vocational training and to determine the dynamics of the introduction of intelligent expert systems in education; A set of pedagogical conditions for the construction and use of an expert system with elements of artificial intelligence in the educational process of a university is revealed; It is substantiated to develop a model for preparing a teacher of vocational training to use elements of artificial intelligence.

The AI Promotion Strategy of Korea Defense for the AI Expansion in Defense Domain (국방분야 인공지능 저변화를 위한 대한민국 국방 인공지능 추진전략)

  • Lee, Seung-Mok;Kim, Young-Gon;An, Kyung-Soo
    • Journal of Software Assessment and Valuation
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    • v.17 no.2
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    • pp.59-73
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    • 2021
  • Recently, artificial intelligence has spread rapidly and popularized and expanded to the voice recognition personal service sector, and major countries have established artificial intelligence promotion strategies, but in the case of South Korea's defense domain, its influence is low with a geopolitical location with North Korea. This paper presents a total of six strategies for promoting South Korea's defense artificial intelligence, including establishing roadmaps, securing manpower, installing the artificial intelligence base, and strengthening cooperation among stakeholders in order to increase the impact of South Korea's defense artificial intelligence and successfully promote artificial intelligence. These suggestions are expected to establish the foundation for expanding the base of artificial intelligence.

The Effect of the Project Learning Method on the Learning Flow and AI Efficacy in the Contactless Artificial Intelligence Based Liberal Arts Class

  • Lee, Ae-ri
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.8
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    • pp.253-261
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    • 2022
  • In this study, the educational effect were sought to be identified after developing and applying project learning for the artificial intelligence based liberal arts education for the non-computer majors. A paired-sample t-test was performed within each group to determine the extent of improvement in the learning flow and artificial intelligence efficacy in the experimental and control groups. After class, an independent sample t-test was performed to examine the statistical effects of pre-test and post-test on the learning flow and artificial intelligence efficacy in the experimental and control groups. The experimental group and control group demonstrated significant improvements in the learning flow and artificial intelligence efficacy before and after class, each respectively. There was no statistically significant difference in the learning flow between the experimental group for which the project learning method was applied and the control group for which only theory and practice were conducted in the artificial intelligence class. It was also confirmed that the experimental group for which the project learning method was applied improved the efficacy of artificial intelligence to a significant level compared to the control group which only proceeded with theory and practice.

The Technological Competitiveness Analysis of Evolving Artificial Intelligence by Using the Patent Information (특허 분석을 통한 인공지능 기술경쟁력 변화 과정에 관한 연구 - 주요 5개국을 중심으로 -)

  • Huang, Minghao;Nam, Eun Young;Park, Se Hoon
    • Journal of the Korean Society of Systems Engineering
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    • v.18 no.1
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    • pp.66-83
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    • 2022
  • Artificial Intelligence (AI) is to assumed to be one of next generation technology which determine technological competitiveness and strategic advantage of a certain country. By using the patent data, this study aims to have a comparative analysis of the technological competitiveness of evolving artificial intelligence at different stages of development among the five largest intellectual property offices in the world (IP5). For the analysis data, all AI technology patent data from 1956 to 2019 were utilized according to the classification system presented in the "WIPO 2019 Technology Trend: Artificial Intelligence" report published by the World Intellectual Property Organization (WIPO) in 2019. The results shows that China has already surpassed the United States in terms of the number of patent applications in the field of artificial intelligence technology. However, in the domains of the United States, Europe, Japan, and Korea, the technology competitiveness of the United States is far ahead of China. Interestingly, the rate of increase of Korea's technology competitiveness is also very fast, and it has been shown that the technology strength is ahead of China in non-Chinese domains. The significance of this study can be found in the fact that the temporal and spatial change process of technological competitiveness of significant countries in the field of artificial intelligence technology artificial intelligence was viewed as a macro-framework using the technology index (TS) the differences were compared.

Systematic Review of Upper Extremity Movement Assessment and Artificial Intelligence Convergence Research in Brain Injured Patients (뇌손상 환자의 상지 움직임 평가와 인공지능 융합연구에 관한 체계적 고찰)

  • Park, Sun Ha;Park, Hae Yean
    • Journal of the Korea Convergence Society
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    • v.13 no.1
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    • pp.109-118
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    • 2022
  • The purpose of this study is to identify trends in the application of artificial intelligence by analyzing upper extremity movement assessment and artificial intelligence convergence research using a systematic literature review method. The research was conducted using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Among the 380 articles searched in three databases, 8 articles were finally selected according to the selection and exclusion criteria. For the evaluation of upper extremity movement, motion performance evaluation, FMA, and ARAT were used. For quantification, data were extracted using various tools, and upper extremity movement classification, recovery prognosis prediction, and evaluation tool score were predicted using artificial intelligence. This study is meaningful in that it systematically reviewed studies that objectively evaluated upper extremity movement using artificial intelligence and identified the direction in which artificial intelligence is being applied. Based on this, the introduction of artificial intelligence technology in the assessment of upper extremity movements is expected to help objectively identify the intervention effect and the patient's recovery.

Development of Artificial Intelligence Instructional Program using Python and Robots (파이썬과 로봇을 활용한 인공지능(AI) 교육 프로그램 개발)

  • Yoo, Inhwan;Jeon, Jaecheon
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.369-376
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    • 2021
  • With the development of artificial intelligence (AI) technology, discussions on the use of artificial intelligence are actively taking place in many fields, and various policies for nurturing artificial intelligence talents are being promoted in the field of education. In this study, we propose a robot programming framework using artificial intelligence technology, and based on this, we use Python, which is used frequently in the machine learning field, and an educational robot that is highly utilized in the field of education to provide artificial intelligence. (AI) education program was proposed. The level of autonomous driving (levels 0-5) suggested by the International Society of Automotive Engineers (SAE) is simplified to four levels, and based on this, the camera attached to the robot recognizes and detects lines (objects). The goal was to make a line detector that can move by itself. The developed program is not a standardized form of solving a given problem by simply using a specific programming language, but has the experience of defining complex and unstructured problems in life autonomously and solving them based on artificial intelligence (AI) technology. It is meaningful.

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Dr. Vegetable: an AI-based Mobile Application for Diagnosis of Plant Diseases and Insect Pests (농작물 병해충 진단을 위한 인공지능 앱, Dr. Vegetable)

  • Soohwan Kim;DaeKy Jeong;SeungJun Lee;SungYeob Jung;DongJae Yang;GeunyEong Jeong;Suk-Hyung Hwang;Sewoong Hwang
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.457-460
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    • 2023
  • 본 연구는 시설작물의 병충해 진단을 위해 딥러닝 모델을 응용한 인공지능 서비스 앱, Dr. Vegetable을 제안하고자 한다. 농업 현장에서 숙련된 농부는 한눈에 농작물의 병충해를 판단할 수 있지만 미숙련된 농부는 병충해 피해를 발견하더라도 그 종류와 해결 방법을 찾아내기가 매우 어렵다. 또한 아무리 숙련된 농부라고 할지라도 육안검사만으로 병충해를 조기에 발견하는 것은 쉽지 않다. 한편 시설작물의 경우 병충해에 의한 연쇄피해가 발생할 우려가 있으므로 병충해의 조기 발견 및 방제가 매우 중요하다. 즉, 농부의 경험에 따른 농작물 병해충 진단은 정확성을 장담할 수 없으며 비용과 시간적인 측면에서 위험성이 높다고 할 수 있다. 본 논문에서는 YOLOv5를 활용하여 상추, 고추, 토마토 등 농작물의 병충해를 진단하는 인공지능 서비스를 제안한다. 특히 한국지능정보사회진흥원이 운영하고 있는 AI 통합 플랫폼인 AI 허브에서 제공하는 노지 작물 질병 및 해충 진단 이미지를 사용하여 딥러닝 모델을 학습하였다. 본 연구를 통해 개발된 모바일 어플리케이션을 이용하여 실제 시설농장에서 병충해 진단 서비스를 적용한 결과 약 86%의 정확도, F1 Score 0.84, 그리고 0.98의 mAP 값을 얻을 수 있었다. 본 연구에서 개발한 병충해 진단 딥러닝 모델을 다양한 조도에서 강인하게 동작하도록 개선한다면 농업 현장에서 널리 활용될 수 있을 것으로 기대한다.

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The association between the social presence and trust of chatbots and the sociodemographic characteristics of artificial intelligence chatbots users in general hospitals : focusing on sex and age (의료기관 인공지능 챗봇 이용자의 인구사회학적 특성과 챗봇의 사회적 실재감 및 신뢰감의 관련성 연구 - 성별과 연령 중심으로)

  • Seung Won Jung;Seo Yeon Hwang;Gi Eun Choi;Eun Young Jo;Jin Wook Lee;Jin Young Nam
    • Korea Journal of Hospital Management
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    • v.28 no.3
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    • pp.27-38
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    • 2023
  • Objectives: This study explores the impact of age groups on social presence and trust among users of medical artificial intelligence chatbots. Furthermore, we investigate the existence of gender differences within these relationships. Method: We collected data through a survey from people who had interacted with general hospital chatbot services, either by making reservations or seeking consultations. Multiple linear regression analysis was conducted to examine the relationship between general characteristics of study population and social presence and trust of artificial intelligence chatbots. Additionally, we conducted stratified analysis to confirm the presence of gender differences within these relationship. Results: Among 300 participants, those aged 50 and older had higher social presence of artificial intelligence chatbots and greater trust of artificial intelligence chatbots (social presence, 𝛽=0.543, p=0.003; trust, 𝛽=0.787, p=0.000). In stratified by sex, women aged 50 and older had higher social presence and trust of artificial intelligence chatbots compared to those in their 30s age group (social presence, 𝛽 = 0.925, p=0.002; trust, 𝛽=0.645, p=:0.007). However, there was no statistically significant relationship between age and chatbot social presence and trust in men. Conclusion: This study demonstrates that advanced age plays a significant roles in users' social presence and trust in medical artificial intelligence chatbots. Futhermore, our findings reveal gender differences with women aged 50 and older showing the most substantial levels of social presence and trust. Therefore, it is expected that this finding can serve as valuable evidence to enhance the satisfaction of medical institution service users, offering crucial insights into the effective utilization of chatbot services.

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GreedyUCB1 based Monte-Carlo Tree Search for General Video Game Playing Artificial Intelligence (일반 비디오 게임 플레이 인공지능을 위한 GreedyUCB1기반 몬테카를로 트리 탐색)

  • Park, Hyunsoo;Kim, HyunTae;Kim, KyungJoong
    • KIISE Transactions on Computing Practices
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    • v.21 no.8
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    • pp.572-577
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    • 2015
  • Generally, the existing Artificial Intelligence (AI) systems were designed for specific purposes and their capabilities handle only specific problems. Alternatively, Artificial General Intelligence can solve new problems as well as those that are already known. Recently, General Video Game Playing the game AI version of General Artificial Intelligence, has garnered a large amount of interest among Game Artificial Intelligence communities. Although video games are the sole concern, the design of a single AI that is capable of playing various video games is not an easy process. In this paper, we propose a GreedyUCB1 algorithm and rollout method that were formulated using the knowledge from a game analysis for the Monte-Carlo Tree Search game AI. An AI that used our method was ranked fourth at the GVG-AI (General Video Game-Artificial Intelligence) competition of the IEEE international conference of CIG (Computational Intelligence in Games) 2014.

Cloud Computing Industry Trends for Artificial Intelligence (인공지능을 위한 클라우드 컴퓨팅 산업 동향)

  • Choi, J.R.;Song, Y.M.;Kim, C.H.;Kim, S.J.
    • Electronics and Telecommunications Trends
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    • v.32 no.5
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    • pp.107-116
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    • 2017
  • Artificial intelligence has recently been regarded as a key engine of future industry, and cloud computing and big data technologies have begun to receive significant attention. Major global vendors such as IBM, Microsoft, Google, and Amazon have been launching cloud-computing services for artificial intelligence. On the other hand, the situation domestically is now at an early stage. This report describes the industry trends both domestically and internationally regarding cloud computing for artificial intelligence. We also describe to significance of cloud computing ecosystem and data competitiveness for artificial intelligence.