• Title/Summary/Keyword: AI (artificial intelligence)

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Design of a Multi-Platform Omok Program for Artificial Intelligence Education (인공지능 교육을 위한 멀티 플랫폼 오목 프로그램 설계)

  • Cha, Joo Hyoung;Woo, Young Woon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.530-532
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    • 2021
  • This paper deals with AI education service that enables developers who have completed basic programming education to program in C/C++ language in order to learn big data and artificial intelligence. In addition, a customized development environment configuration system according to the development environment and how the user implements and tests artificial intelligence are explained. And also it has a function to check the effect on artificial intelligence through manipulation of various internal parameters. It is expected that it will be possible to develop artificial intelligence education services without language restrictions through networks in the future.

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A study on Improving the Performance of Anti - Drone Systems using AI (인공지능(AI)을 활용한 드론방어체계 성능향상 방안에 관한 연구)

  • Hae Chul Ma;Jong Chan Moon;Jae Yong Park;Su Han Lee;Hyuk Jin Kwon
    • Journal of the Korean Society of Systems Engineering
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    • v.19 no.2
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    • pp.126-134
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    • 2023
  • Drones are emerging as a new security threat, and the world is working to reduce them. Detection and identification are the most difficult and important parts of the anti-drone systems. Existing detection and identification methods each have their strengths and weaknesses, so complementary operations are required. Detection and identification performance in anti-drone systems can be improved through the use of artificial intelligence. This is because artificial intelligence can quickly analyze differences smaller than humans. There are three ways to utilize artificial intelligence. Through reinforcement learning-based physical control, noise and blur generated when the optical camera tracks the drone may be reduced, and tracking stability may be improved. The latest NeRF algorithm can be used to solve the problem of lack of enemy drone data. It is necessary to build a data network to utilize artificial intelligence. Through this, data can be efficiently collected and managed. In addition, model performance can be improved by regularly generating artificial intelligence learning data.

Policy Analysis on AI SW Human Resources Development Using Cognitive Map Analysis (인지지도분석을 활용한 AI SW 인력양성 정책분석)

  • Lee, Jung Mann
    • Journal of Information Technology Applications and Management
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    • v.28 no.3
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    • pp.109-125
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    • 2021
  • For the government of president Moon's AI SW HRD policy, he proclaimed AI democracy that anyone can utilize artificial intelligence technology to spread AI education for the people of the country. Through cognitive map analysis, this study presents expected policy outcomes due to the input of policy factors to overcome crisis factors and utilize opportunity factors. According to the cognitive guidance analysis, first, the opportunity factor is recognized as accelerating the digital transformation to Covid 19 if AI SW HRD is well nurtured. Second, the crisis factor refers to the rapid paradigm shift caused by the intelligence information society, resulting in job losses in the manufacturing sector and deepening imbalance in manpower supply and demand, especially in the artificial intelligence sector. Third, the comprehensive cognitive map shows a circular process for creating an AI SW ecosystem in response to threats caused by untact caused by Corona and a circular process for securing AI talent in response to threats caused by deepening imbalance in manpower supply and demand in the AI sector. Fourth, in order to accelerate the digital circulation that has been accelerated by Corona, we found a circular process to succeed in the Korean version of digital new deal by strengthening national and corporate competitiveness through AI-utilized capacity and industrial and regional AI education. Finally, the AI utilization empowerment strengthening rotation process is the most dominant of the four mechanisms, and we also found a relatively controllable feedback loop to obtain policy outputs.

Design and Application of Artificial Intelligence Experience Education Class for Non-Majors (비전공자 대상 인공지능 체험교육 수업 설계 및 적용)

  • Su-Young Pi
    • Journal of Practical Engineering Education
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    • v.15 no.2
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    • pp.529-538
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    • 2023
  • At the present time when the need for universal artificial intelligence education is expanding and job changes are being made, research and discussion on artificial intelligence liberal arts education for non-majors in universities who experience artificial intelligence as part of their job is insufficient. Although artificial intelligence education courses for non-majors are being operated, they are mainly operated as theory-oriented education on the concepts and principles of artificial intelligence. In order to understand the general concept of artificial intelligence for non-majors, it is necessary to proceed with experiential learning in parallel. Therefore, this study designs artificial intelligence experiential education learning contents of difficulty that can reduce the burden of artificial intelligence classes with interest in learning by considering the characteristics of non-majors. After, we will examine the learning effect of experiential education using App Inventor and the Orange artificial intelligence platform. As a result of analysis based on the learning-related data and survey data collected through the creation of AI-related projects by teams, positive changes in the perception of the need for AI education were found, and AI literacy skills improved. It is expected that it will serve as an opportunity for instructors to lay the groundwork for designing a learning model for artificial intelligence experiential education learning.

Analysis of User Experience and Usage Behavior of Consumers Using Artificial Intelligence(AI) Devices (인공지능(AI) 디바이스 이용 소비자의 사용행태 및 사용자 경험 분석)

  • Kim, Joon-Hwan
    • Journal of Digital Convergence
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    • v.19 no.6
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    • pp.1-9
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    • 2021
  • Artificial intelligence (AI) devices are rapidly emerging as a core platform of next-generation information and communication technology (ICT), this study investigated consumer usage behavior and user experience through AI devices that are widely applied to consumers' daily lives. To this end, data was collected from 600 consumers with experience in using AI devices were derived to recognize the attributes and behavior of AI devices. The analysis results are as follows. First, music listening was the most used among various attributes and it was found that simple functions such as providing weather information were usefully recognized. Second, the main devices used by AI device users were identified as AI speakers, smartphone, PC and laptops. Third, associative images of AI devices appeared in the order of fun, useful, novel, smart, innovative, and friendly. Therefore, practical implications are suggested to contribute to provision of user services using AI devices in the future by analyzing usage behaviors that reflect the characteristics of AI devices.

A TabNet - Based System for Water Quality Prediction in Aquaculture

  • Nguyen, Trong–Nghia;Kim, Soo Hyung;Do, Nhu-Tai;Hong, Thai-Thi Ngoc;Yang, Hyung Jeong;Lee, Guee Sang
    • Smart Media Journal
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    • v.11 no.2
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    • pp.39-52
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    • 2022
  • In the context of the evolution of automation and intelligence, deep learning and machine learning algorithms have been widely applied in aquaculture in recent years, providing new opportunities for the digital realization of aquaculture. Especially, water quality management deserves attention thanks to its importance to food organisms. In this study, we proposed an end-to-end deep learning-based TabNet model for water quality prediction. From major indexes of water quality assessment, we applied novel deep learning techniques and machine learning algorithms in innovative fish aquaculture to predict the number of water cells counting. Furthermore, the application of deep learning in aquaculture is outlined, and the obtained results are analyzed. The experiment on in-house data showed an optimistic impact on the application of artificial intelligence in aquaculture, helping to reduce costs and time and increase efficiency in the farming process.

Development of Evaluation Framework for Adopting of a Cloud-based Artificial Intelligence Platform (클라우드 기반 인공지능 플랫폼 도입 평가 프레임워크 개발)

  • Kwang-Kyu Seo
    • Journal of the Semiconductor & Display Technology
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    • v.22 no.3
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    • pp.136-141
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    • 2023
  • Artificial intelligence is becoming a global hot topic and is being actively applied in various industrial fields. Not only is artificial intelligence being applied to industrial sites in an on-premises method, but cloud-based artificial intelligence platforms are expanding into "as a service" type. The purpose of this study is to develop and verify a measurement tool for an evaluation framework for the adoption of a cloud-based artificial intelligence platform and test the interrelationships of evaluation variables. To achieve this purpose, empirical testing was conducted to verify the hypothesis using an expanded technology acceptance model, and factors affecting the intention to adopt a cloud-based artificial intelligence platform were analyzed. The results of this study are intended to increase user awareness of cloud-based artificial intelligence platforms and help various industries adopt them through the evaluation framework.

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A Comparative Analysis of Contents Related to Artificial Intelligence in National and International K-12 Curriculum (국내외 초·중등학교 인공지능 교육과정 분석)

  • Lee, Eunkyoung
    • The Journal of Korean Association of Computer Education
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    • v.23 no.1
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    • pp.37-44
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    • 2020
  • As the importance of artificial intelligence(AI) education is emphasized recently, policies and researches are being promoted to develop the AI curriculum or courses for K-12 students in worldwide. In this study, researcher analysed a synthesis of contents and standards on AI education curriculum to present implications for AI education in the elementary and secondary schools. As a result, Korea and the United States are proposing national curriculum standards to provide the basis for AI curriculum establishment in school sites and to provide guidelines for various related policies such as teacher training programs. The EU's AI education is characterized by its curriculum and online courses to ensure that all citizens of the EU have AI literacy, rather than designating students or subjects at specific school levels. In terms of educational contents and levels, Korea, United States, and EU's curriculum or standards includes basics and applications related to machine learning and neural network based on the fundamental concepts and principles of artificial intelligence.

Design of Artificial Intelligence Textbooks for Kindergarten to Develop Computational Thinking based on Pattern Recognition. (패턴인식에 기반한 컴퓨팅사고력 계발을 위한 유치원 AI교재 설계)

  • Kim, Sohee;Jeong, Youngsik
    • Journal of The Korean Association of Information Education
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    • v.25 no.6
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    • pp.927-934
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    • 2021
  • AI(Artificial intelligence) is gradually taking up a large part of our lives, and the pace of AI development is accelerating. It is called ACT that develop students' computational thinking in the way artificial intelligence learns. Among ACTs, pattern recognition is an essential factor in efficiently solving problems. Pattern analysis is part of the pattern recognition process. In fact, Netflix's personalized movie recommendation service and what it named Covid-19 after repeated symptoms are all the results of pattern analysis. While the importance of ACT, including pattern recognition, is highlighted, software education for kindergarten and elementary school lower grades is much insufficient compared to foreign countries. Therefore, this study aims to design and develop textbooks for the development of artificial intelligence-based computational thinking through pattern analysis for kindergarten students.

Preservice teacher's understanding of the intention to use the artificial intelligence program 'Knock-Knock! Mathematics Expedition' in mathematics lesson: Focusing on self-efficacy, artificial intelligence anxiety, and technology acceptance model (수학 수업에서 예비교사의 인공지능 프로그램 '똑똑! 수학 탐험대' 사용 의도 이해: 자기효능감과 인공지능 불안, 기술수용모델을 중심으로)

  • Son, Taekwon
    • The Mathematical Education
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    • v.62 no.3
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    • pp.401-416
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    • 2023
  • This study systematically examined the influence of preservice teachers' self-efficacy and AI anxiety, on the intention to use AI programs 'knock-knock! mathematics expedition' in mathematics lessons based on a technology acceptance model. The research model was established with variables including self-efficacy, AI anxiety, perceived ease of use, perceived usefulness, and intention of use from 254 pre-service teachers. The structural relationships and direct and indirect effects between these variables were examined through structural equation modeling. The results indicated that self-efficacy significantly affected perceived ease of use, perceived usefulness, and intention to use. In contrast, AI anxiety did not significantly influence perceived ease of use and perceived usefulness. Perceived ease of use significantly affected perceived usefulness and intention to use and perceived usefulness significantly affected intention to use. The findings offer insights and strategies for encouraging the use of 'knock-knock! mathematics expedition' by preservice teachers in mathematics lessons.