• Title/Summary/Keyword: Artificial intelligence program

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Verification of the Effectiveness of Artificial Intelligence Education for Cultivating AI Literacy skills in Business major students

  • SoHyun PARK
    • The Journal of Economics, Marketing and Management
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    • v.11 no.6
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    • pp.1-8
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    • 2023
  • Purpose: In the era of the Fourth Industrial Revolution, individuals equipped with fundamental understanding and practical skills in artificial intelligence (AI) are essential. This study aimed to validate the effectiveness of AI education for enhancing AI literacy among business major student. Research design, data and methodology: Data for analyzing the effectiveness of the AI Fundamental Education Program for business major students were collected through surveys conducted at the beginning and end of the semester. Structural equation modeling was employed to perform basic statistical analyses regarding gender, grade, and prior software (SW) education duration. To validate the effectiveness of AI education, seven variables - AI interest, AI perception, data analysis/utilization, AI projects, AI literacy, AI self-efficacy, and AI learning persistence - were defined and derived. Results: All seven operationally defined variables showed statistically significant positive changes. The average differences were observed as follows: 0.47 for AI interest, 0.32 for AI perception, 0.37 for data analysis/utilization, 0.27 for AI projects, 0.25 for AI literacy, 0.39 for AI self-efficacy, and 0.41 for AI learning persistence. Statistically, AI interest exhibited the most substantial average difference. Conclusions: Through this study, the applied AI education was confirmed to enhance learners' overall competencies in AI, proving its utility and effectiveness in AI literacy education for business major students. Future research endeavors should build upon these results, focusing on ongoing studies related to AI education programs tailored to learners from diverse academic backgrounds and conducting continuous efficacy evaluations.

Top-Level Implementation of AI4SE, SE4AI for the AI-SE convergence in the Defense Acquisition (무기체계 획득에서 인공지능-시스템엔지니어링 융화를 위한 최상위 수준의 AI4SE, SE4AI 구현방안)

  • Min Woo Lee
    • Journal of the Korean Society of Systems Engineering
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    • v.19 no.2
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    • pp.135-144
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    • 2023
  • Artificial Intelligence (AI) is a prominent topic in almost every field. In Korea, Systems Engineering (SE) procedures are applied in Defense Acquisition, and it is anticipated that SE procedures will also be applied to systems incorporating AI capabilities. This study explores the applicability of the concepts "AI4SE (AI for SE)" and "SE4AI (SE for AI)," which have been proposed in the United States, to the Korean context. The research examines the feasibility of applying these concepts, identifies necessary tasks, and proposes implementation strategies. For the AI4SE, many attempts and studies applying AI to SE Processes both Requirements & Architectures Define, System implementation & V&V, and Sustainment. It needs Explainability and Security. For the SE4AI, the Functional AI implementation level, Quality & Security of the Data-set, AI Ethics, and Review policies are needed. Furthermore, it provides perspectives on how these two concepts should ultimately converge and suggests future directions for development.

Comparison of the Differences in AI-Generated Images Using Midjourney and Stable Diffusion (Midjourney와 Stable Diffusion을 이용한 AI 생성 이미지의 차이 비교)

  • Linh Bui Duong Hoai;Kang-Hee Lee
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.563-564
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    • 2023
  • Midjourney and Stable Diffusion are two popular AI-generated image programs nowadays. With AI's outstanding image-generation capabilities, everyone can create artistic paintings in just a few minutes. Therefore, "Comparison of differences between AI-generated images using Midjourney and Stable Diffusion" will help see each program's advantages and assist the users in identifying the tool suitable for their needs.

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Comparative Evaluation of 18F-FDG Brain PET/CT AI Images Obtained Using Generative Adversarial Network (생성적 적대 신경망(Generative Adversarial Network)을 이용하여 획득한 18F-FDG Brain PET/CT 인공지능 영상의 비교평가)

  • Kim, Jong-Wan;Kim, Jung-Yul;Lim, Han-sang;Kim, Jae-sam
    • The Korean Journal of Nuclear Medicine Technology
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    • v.24 no.1
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    • pp.15-19
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    • 2020
  • Purpose Generative Adversarial Network(GAN) is one of deep learning technologies. This is a way to create a real fake image after learning the real image. In this study, after acquiring artificial intelligence images through GAN, We were compared and evaluated with real scan time images. We want to see if these technologies are potentially useful. Materials and Methods 30 patients who underwent 18F-FDG Brain PET/CT scanning at Severance Hospital, were acquired in 15-minute List mode and reconstructed into 1,2,3,4,5 and 15minute images, respectively. 25 out of 30 patients were used as learning images for learning of GAN and 5 patients used as verification images for confirming the learning model. The program was implemented using the Python and Tensorflow frameworks. After learning using the Pix2Pix model of GAN technology, this learning model generated artificial intelligence images. The artificial intelligence image generated in this way were evaluated as Mean Square Error(MSE), Peak Signal to Noise Ratio(PSNR), and Structural Similarity Index(SSIM) with real scan time image. Results The trained model was evaluated with the verification image. As a result, The 15-minute image created by the 5-minute image rather than 1-minute after the start of the scan showed a smaller MSE, and the PSNR and SSIM increased. Conclusion Through this study, it was confirmed that AI imaging technology is applicable. In the future, if these artificial intelligence imaging technologies are applied to nuclear medicine imaging, it will be possible to acquire images even with a short scan time, which can be expected to reduce artifacts caused by patient movement and increase the efficiency of the scanning room.

A Study on Analysis of national R&D research trends for Artificial Intelligence using LDA topic modeling (LDA 토픽모델링을 활용한 인공지능 관련 국가R&D 연구동향 분석)

  • Yang, MyungSeok;Lee, SungHee;Park, KeunHee;Choi, KwangNam;Kim, TaeHyun
    • Journal of Internet Computing and Services
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    • v.22 no.5
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    • pp.47-55
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    • 2021
  • Analysis of research trends in specific subject areas is performed by examining related topics and subject changes by using topic modeling techniques through keyword extraction for most of the literature information (paper, patents, etc.). Unlike existing research methods, this paper extracts topics related to the research topic using the LDA topic modeling technique for the project information of national R&D projects provided by the National Science and Technology Knowledge Information Service (NTIS) in the field of artificial intelligence. By analyzing these topics, this study aims to analyze research topics and investment directions for national R&D projects. NTIS provides a vast amount of national R&D information, from information on tasks carried out through national R&D projects to research results (thesis, patents, etc.) generated through research. In this paper, the search results were confirmed by performing artificial intelligence keywords and related classification searches in NTIS integrated search, and basic data was constructed by downloading the latest three-year project information. Using the LDA topic modeling library provided by Python, related topics and keywords were extracted and analyzed for basic data (research goals, research content, expected effects, keywords, etc.) to derive insights on the direction of research investment.

AlphaGo Case Study: On the Social Nature of Artificial Intelligence (알파고 사례 연구: 인공지능의 사회적 성격)

  • Kim, Ji Yeon
    • Journal of Science and Technology Studies
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    • v.17 no.1
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    • pp.5-39
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    • 2017
  • In March 2016, the computer Go program, AlphaGo, defeated Sedol Lee, a Korean professional Go player of 9-dan rank. This victory by AlphaGo shows the rise in popularity of artificial intelligence (AI). Not only was this game a testament to machine performance, it was the type of game that extended the Turing test. When the interrogator cannot differentiate between human being and machine, the machine has passed the test. This article examines the interactions between AI and human beings and studies the social nature of intelligence through the AlphaGo case. Collins insists that knowledge or intelligence is social and embodied, and the interrogators in the Turing test can identify the difference between native members and non-members through their knowledge only. Applying this concept, AlphaGo, as subject A of this test, fulfilled its role of stirring up the classical "truth of human." Meanwhile, Lee as subject B, played to speak the truth by revealing his own qualities. Here, it is also important role that interrogators judge what it is. Many spectators, as interrogators, have intervened to confirm the border between human beings and machines by using their embodied and social knowledge.

Drawing of penetrating lines using personal computer (個人용 컴퓨터를 利용한 相貫線의 圖示)

  • 채희창
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.12 no.1
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    • pp.173-182
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    • 1988
  • A program for drawing of penetrating lines was developed in personal computer. PROLOG, a language of Artificial Intelligence, was used and a data structure using relational data base was designed. An algorithm for finding the penetrating lines in the real space was developed. The program can be applied at any types of penetrating problems like curve-surface, surface-surface, curve-object, surface-object, object-object, etc. In developing the program, the following results were obtained. (1) Relational data base built in PROLOG and the function of backtracking are helpful in Computer Graphics. (2) In spite of increasing the number of edges, assigning direction to the edges makes it possible to represent the polygon meshes as the non ordered sets of directional half edges. (3) Topologicaly the penetrating lines of a polygon can be represented as the edge-pairs in the edge list of the polygon,

A Primitive Model of An Expert Training Model

  • 유영동
    • The Journal of Information Systems
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    • v.1
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    • pp.149-178
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    • 1992
  • The field of Artificial Intelligence (AI) is growing, and many firms are investing in expert system, one of AI's subfields. An expert system is defined as a computer program designed to replicate some aspect of the decision making of one or more experts and to be used by nonexperts. The kernel of an expert system is the knowledge base, which consists of the facts and rules that represent the expert's knowledge. Firms need expert systems for training employees to provide competitive advantage. This paper describes the model of an instructional expert training system which interfaces to external programs, such as an ASCII file, a work-sheet program, and a database program. A model for such an expert training system, and its prototype have been developed to demonstrate its functionality. A modular knowledge base has been developed and implemented in support of this study. The modularized knowledge base offers the user an easy and quick maintenance of facts and rules, which are frequently required to change in future.

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Analysis of Toxic Heavy Meatals using Hybrid Neural Network in Glow Discharge Atomic Emission Spectroscoy (글로우 방전 원자방출에서의 Hybrid Neural Network를 이용한 유해 중금속 분석)

  • Lee, J.S.;Lee, S.C.;Choi, K.S.;Kim, Y.S.;So, S.H.;Ha, K.J.;Ryu, D.H.;Cho, T.H.;Jung, M.S.
    • Analytical Science and Technology
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    • v.15 no.5
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    • pp.399-409
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    • 2002
  • A system software on-line spectral analysis of atomic emission spectrometer. The system program consisted of a control part for the optical instruments and the spectrum analysis part the artificial intelligence method to reduce nonlinear error of the wavelengths. McPHERSON 207 Monochromator controlled GPIB communication protocol, and the detector signal was measured from PMT by using A/D Amplifier that was made by Photon_Tek. co.. HNN(Hybrid Neural Network) of artificial intelligence technique was applied to the qualitative analysis of P, Cu, Fe, Cr, and that was accurately applied to the quantitative analysis of Cd with 10 ppb level better than the conventional methods.

Effects of maker education for high-school students on attitude toward software education, creative problem solving, computational thinking (고등학생 대상 메이커 교육이 소프트웨어 교육에 대한 태도, 창의적 문제해결력, 컴퓨팅 사고에 미치는 영향)

  • Hong, Wonjoon;Choi, Jae-Sung;Lee, Hyun
    • Journal of The Korean Association of Information Education
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    • v.24 no.6
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    • pp.585-596
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    • 2020
  • The purpose of this study is to examine effects of maker education for high-school students on attitude toward software education, creative problem solving, and computational thinking. The program was designed to develop an artificial intelligence robot using mBlock and Arduino and implemented at a maker space. We analyzed 19 students among 20 who participated in the program, the result of paired t-test indicated significant increase in all variables. Also, we performed a multiple regression analysis to investigate predictors of perceived achievement and satisfaction. The finding demonstrated an initial attitude toward software education was found to be the significant predictor of perceived achievement and satisfaction. With the results, we confirmed maker education enhances attitude toward software education, creative problem solving, and computational thinking. Lastly, we discussed the implications and limitations and suggested the direction for future research.