• 정보교육학회논문지
• /
• 제26권5호
• /
• pp.397-406
• /
• 2022

본 연구에서는 2020년 정부에서 발표한 "인공지능시대 교육정책방향과 핵심과제"에서 제시한 3대 정책 추진 방향을 확인하고, '20-'22년 발표된 인공지능 교육 관련 정부 정책 자료들로부터 키워드를 추출해 방향과 핵심과제가 정책으로 어떻게 반영되고 있는지 분석하였다. 텍스트 마이닝 빈도 분석 결과 정부가 추진하는 다양한 정책 방향을 확인하였고, 매트릭스 데이터에서 핵심 추진과제로 설정된 교육의 방향을 분석하였다. 토픽 분석 결과 인공지능 분야의 인재 양성을 위한 다양한 형태의 교육활동을 확인하였고, 개정 교육과정이 적용되기 전 다양한 콘텐츠가 개발되고 있는 것도 확인하였다. 최종적으로 정부의 정책 방향은 '25년 개정 교육과정을 본격적으로 적용하는 동시에 인공지능 교육 정책을 고도화, 활성화하고 현장에 자연스럽게 안착하도록 하는 쪽으로 움직일 것이며 교육과정이 적용되는 시기가 점점 다가올수록 현장 안착과 관련된 정책과 과제들이 점점 더 많이 등장할 것으로 예측할 수 있었다.

• 디지털융복합연구
• /
• 제19권1호
• /
• pp.141-149
• /
• 2021

세계적으로 인공지능 기술의 급부상으로 인해 초·중등에서 실시하고 있는 SW(Software 이하 SW) 교육은 AI(Artificial Intelligence 이하 AI) 교육을 포함하여 확대되고 있는 추세이다. 이에 본 연구에서는 4P(Play, Problem Solving, Product Making, Project)기반 만5세 대상 유치원에서부터 고등학교까지 적용할 수 있는 AI 교육체계를 제시하고자 한다. 본 연구에서 제시하는 AI 교육체계는 학령별, 단계별로 적용할 수 있도록 4P기반의 Play(놀이), Problem Solving(문제해결), Product Making(제작), 그리고 Project(프로젝트) 4단계 교육전략을 설계하고, 수준을 AI 소양과 AI 개발이라는 2개의 영역으로 나누어 제시하였다. 개발된 AI 교육체계의 타당도를 검증하기 위하여 SW 교육 또는 AI 교육 경험이 있는 15명의 전문가를 대상으로 델파이 방법을 적용하였다. 검증 결과 도출된 AI 교육체계는 향후 학교급별 AI 교육을 위한 내용 체계를 개발하는데 기여할 수 있을 것이다.

• 한국콘텐츠학회논문지
• /
• 제20권7호
• /
• pp.86-96
• /
• 2020

본 연구는 이미지 인식기술 서비스의 산업 적용 사례를 기반으로 인공지능이 이미지 인식기술에 어떠한 역할을 하고 있는지 살펴보았다. 이미지 인식 기술을 사용하여 위성사진을 인공지능으로 분석해 특정 국가의 원유 저장탱크의 산출 내역을 밝혀내거나, 사용자가 촬영하거나 다운로드한 이미지와 유사한 이미지나 제품을 검색해주기도 하며, 과일의 산출량을 정렬한다거나 식물의 질병을 탐지해 낼 수도 있다. 딥러닝과 신경망 알고리즘을 기반으로 사람의 나이, 성별, 기분까지도 인식할 수 있어 이미지 인식 기술이 다양한 산업에서 적용되고 있음을 확인하였다. 본 연구에서는 국내 및 해외의 이미지 인식 기술의 활용 사례를 살펴보는 것 뿐 아니라, 어떠한 형태로 산업에 적용되고 있는지 확인을 할 수 있다. 또한, 본 연구를 통하여 여러 산업에서 이미지 인식기술을 구현하고 적용하여 발전시킨 여러 성공 사례들을 중심으로 향후 연구의 방향성을 제시했으며, 향후 국내 이미지 인식 기술이 나아가야 할 방향을 고찰해 볼 수 있다.

• Computers and Concrete
• /
• 제21권5호
• /
• pp.513-523
• /
• 2018

Time dependent strain due to creep is a significant factor in structural design. Multi-gene genetic programming (MGGP) and artificial neural network (ANN) are used to develop two models for prediction of creep compliance in concrete. The first model was developed by MGGP technique and the second model by hybridized MGGP-ANN. In the MGGP-ANN, the ANN is working in parallel with MGGP to predict errors in MGGP model. A total of 187 experimental data sets that contain 4242 data points are filtered from the NU-ITI database. These data are used in developing the MGGP and MGGP-ANN models. These models contain six input variables which are: average compressive strength at 28 days, relative humidity, volume to surface ratio, cement type, age at start of loading and age at the creep measurement. Practical equation based on MGGP was developed. A parametric study carried out with a group of hypothetical data generated among the range of data used to check the generalization ability of MGGP and MGGP-ANN models. To confirm validity of MGGP and MGGP-ANN models; two creep prediction code models (ACI209 and CEB), two empirical models (B3 and GL 2000) are used to compare their results with NU-ITI database.

• 인터넷정보학회논문지
• /
• 제24권5호
• /
• pp.67-73
• /
• 2023

The Digital Age calls for improvement of information literacy particularly among children and youth who are vulnerable to cybergrooming. Taking an interdisciplinary approach by leveraging our team's expertise including child and adolescent development, data analytics, and cybersecurity, this study proposes an interactive artificial intelligence (AI)-based preventive simulation program that raises youth knowledge and awareness about the risk of cybergrooming as well as increases resilient self-efficacy in their cybersecurity-relevant skills. The primary purpose of this project is to evaluate the effectiveness of the simulation program on preventing cybergrooming. More specifically, this study is designed to examine developmental changes in self-efficacy of cybersecurity-relevant skills among youth participants as a function of the preventive simulation program. Further, this study will identify risk and protective factors that explain interindividual differences in the ability of children and youth either to fall victim to advances from a cyber predator or to recognize and deter such threats. The preliminary data will help improve the effectiveness of the preventive simulation program as well as the methods of implementation to large groups of youth. The findings from the proposed study will contribute to making specific recommendations to parents, educators, practitioners, and policy makers for the prevention of cybergrooming.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제16권9호
• /
• pp.2867-2881
• /
• 2022

This study investigates fashion Artificial Intelligence (AI) curation services to expand sustainable consumption. We analyzed the factors that affect the AI fashion curation service experience of women in their 20s and 30s using their clothes. An online survey was conducted from March 29, 2021, to June 4, 2021, for women of the previously mentioned age groups residing in the metropolitan area. Before answering the questionnaire, they installed the "Style Bot" application on their phone, took five or more photos of their clothes according to the manual provided by the application, stored them in a virtual wardrobe on the application, and then responded to the questionnaire using the AI recommended coordinating function. The effect of the properties of fashion AI curation service application on the use of clothes was investigated. Among the attributes of the fashion AI curation service application, convenience, speed, and usefulness were found to have a positive effect on the use of clothes, and promptness had no effect. Second, regarding the impact of clothing utilization on environmental sustainability, clothing utilization was found to have a positive effect on environmental sustainability. Third, environmental sustainability was found to have a positive effect on satisfaction. Fourth, clothing utilization had a positive effect on satisfaction. Thus, fashion AI curation service would help promote service development so that clothes could be used actively through an in-depth understanding of the properties of these services. Finally, the results of this study would contribute to promoting environmental sustainability.

• International Journal of Internet, Broadcasting and Communication
• /
• 제15권2호
• /
• pp.227-239
• /
• 2023

Online marketing is a rapidly growing industry that heavily depends on digital technologies and data analysis to effectively reach and engage consumers. For that, artificial intelligence (AI) has emerged as a crucial tool for online marketers, enabling marketers to analyze extensive consumer data and automate decision-making processes. The purpose of this study was to investigate the ethical implications of using AI in online marketing, focusing on its impact on consumer privacy and decision-making. AI has created new possibilities for personalized marketing but raises concerns about the collection and use of consumer data, transparency and accountability of decision-making, and the impact on consumer autonomy and privacy. In this study, we reviewed the relevant literature and case studies to assess the potential risks and make recommendations for improving consumer protection. The findings provide insights into ethical considerations and offer a roadmap for balancing the advantages of AI in online marketing with the protection of consumer rights. Companies should consider these ethical issues when implementing AI in their marketing strategies. In this study, we explored the concerns and provided insights into the challenges posed by AI in online marketing, such as the collection and use of consumer data, transparency, and accountability of decision-making, and the impact on consumer autonomy and privacy.

• 한국방사선학회논문지
• /
• 제13권5호
• /
• pp.785-790
• /
• 2019

인공지능, 빅데이터, 사물인터넷 등 기술간 융합과 고도화가 지역주력산업에도 큰 영향을 미치고 있다. 모든 기술분야가 기술간-산업간 연결이 되어 융합된 기술로 활용되고 있다. 최근 기술동향을 파악하기 위해 특허정보를 이용한 키워드검색을 통해 기술동향 조사 및 분석으로 쉽게 파악이 가능하게 되었다. 본 연구는 방사선 기술발전에서 4차 산업혁명시대 융합기술을 적용한 특허동향을 파악하고 방사선 관련 산업기술경쟁력 강화 및 활용방안을 위한 특허동향 및 분석을 제시하여 수요기술 발굴과 미래 유망기술 예측에 활용하고자 한다.

• 한국인공지능학회지
• /
• 제10권2호
• /
• pp.1-6
• /
• 2022

In this paper, the research and development aim to strengthen the digital accessibility of the elderly by developing a kiosk incorporating AI voice recognition technology that can replace the promotional signage currently being installed and spread in the elderly and social welfare centers most frequently used by the digital underprivileged. It was intended to develop a converged system for the use of bulletin board functions, educational functions, and welfare center facilities, and to seek ways to increase the user's digital device experience through direct experience and education. Through interviews and surveys of senior citizens and social welfare centers, it was intended to collect problems and pain Points that the elderly currently experience in the process of using kiosks and apply them to the development process, and improve problems through pilot services. Through this study, it was confirmed that voice recognition technology is 2 to 6 times faster than keyboard input, so it is helpful for the elderly who are not familiar with device operation. However, it is necessary to improve the problem that there is a difference in the accuracy of the recognition rate according to the surrounding environment with noise. Through small efforts such as this study, we hope that the elderly will be a little free from digital alienation.

• 한국인공지능학회지
• /
• 제10권1호
• /
• pp.15-19
• /
• 2022

This study is to understand the relationship between turnover and various conditions. Turnover refers to workers moving from one company to another, which exists in various ways and forms. Currently, a large number of workers are considering many turnover rates to satisfy their income levels, distance between work and residence, and age. In addition, they consider changing jobs a lot depending on the type of work, the decision-making ability of workers, and the level of education. The company needs to accept the conditions required by workers so that competent workers can work for a long time and predict what measures should be taken to convert them into long-term workers. The study was conducted because it was necessary to predict what conditions workers must meet in order to become long-term workers by comparing various conditions and turnover using regression and decision trees. It used Microsoft Azure machines to produce results, and it found that among the various conditions, it looked for different items for long-term work. Various methods were attempted in conducting the research, and among them, suitable algorithms adopted algorithms that classify various kinds of algorithms and derive results, and among them, two decision tree algorithms were used to derive results.