• Title/Summary/Keyword: AI year

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The Effect of Appreciative Inquiry on Positive Psychological Capital and Organizational Commitment of New Nurses (긍정적 탐구 활동이 신규간호사의 긍정심리자본과 조직몰입에 미치는 효과)

  • Kim, Hyunju;Yi, Young Hee
    • Journal of Korean Critical Care Nursing
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    • v.12 no.3
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    • pp.13-23
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    • 2019
  • Purpose : The purpose of this study was to determine whether appreciative inquiry (AI) is an effective intervention for increasing the positive psychological capital and organizational commitment of new nurses. Method : The study used a nonequivalent control group pretest-posttest design. The participants were 60 new nurses in a tertiary hospital in Seoul. The experimental group received 2 classes of AI education and in-unit AI activities. The control group received the existing education program. Results : There was no statistically significant difference in the positive psychological capital and organizational commitment between the experimental group and the control group over time. Satisfaction with the AI education scored 3.69, which was higher than the average. The reason why the experimental group members were satisfied with the program was that AI education helped them to adapt and the in-unit AI activities made staff more cooperative and the atmosphere of the unit more positive. Conclusion : When applying AI activities to new nurses to promote positive psychological capital and organizational commitment, it is necessary to provide a workshop in which the participants can fully concentrate on education and to extend the period of use to one year in order to maintain the effect of AI activities.

The Effect of AI Development on the Economic Growth: The Case of South Korea (인공지능산업 발전이 경제성장에 미치는 효과 분석)

  • Dong Jin Lee
    • Analyses & Alternatives
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    • v.8 no.1
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    • pp.59-85
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    • 2024
  • This study examines the impact of the development of the artificial intelligence (AI) industry on the economic growth of South Korea. The study uses variables such as the revenue and patent applications of AI-related companies, as well as industry-specific total factor productivity and GDP, to estimate the effects. The results suggest that the growth of the AI industry has a positive effect on the economic growth with a lag of about one year. Specifically, the effect of government AI revenue on GDP growth appears to be greater than that of private companies or consumer-focused AI revenue. This indicates that government policies aimed at promoting the diffusion of the AI industry have had significant effects. The study notes that the period covered by the AI industry survey data is relatively short, and there is a lack of detailed data for the manufacturing sector. I suggest that further improvements and accumulation of data could lead to more robust results.

Empirical Research on the Interaction between Visual Art Creation and Artificial Intelligence Collaboration (시각예술 창작과 인공지능 협업의 상호작용에 관한 실증연구)

  • Hyeonjin Kim;Yeongjo Kim;Donghyeon Yun;Hanjin Lee
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.1
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    • pp.517-524
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    • 2024
  • Generative AI, exemplified by models like ChatGPT, has revolutionized human-machine interactions in the 21st century. As these advancements permeate various sectors, their intersection with the arts is both promising and challenging. Despite the arts' historical resistance to AI replacement, recent developments have sparked active research in AI's role in artistry. This study delves into the potential of AI in visual arts education, highlighting the necessity of swift adaptation amidst the Fourth Industrial Revolution. This research, conducted at a 4-year global higher education institution located in Gyeongbuk, involved 70 participants who took part in a creative convergence module course project. The study aimed to examine the influence of AI collaboration in visual arts, analyzing distinctions across majors, grades, and genders. The results indicate that creative activities with AI positively influence students' creativity and digital media literacy. Based on these findings, there is a need to further develop effective educational strategies and directions that incorporate AI.

Application of Endoscopic Ultrasound-based Artificial Intelligence in Diagnosis of Pancreatic Malignancies (악성 췌장 병변 진단에서 인공지능기술을 이용한 초음파내시경의 응용)

  • Jae Hee Ahn;Hwehoon Chung;Jae Keun Park
    • Journal of Digestive Cancer Research
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    • v.12 no.1
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    • pp.31-37
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    • 2024
  • Pancreatic cancer is a highly fatal malignancy with a 5-year survival rate of < 10%. Endoscopic ultrasound (EUS) is a useful noninvasive tool for differential diagnosis of pancreatic malignancy and treatment decision-making. However, the performance of EUS is suboptimal, and its accuracy for differentiating pancreatic malignancy has increased interest in the application of artificial intelligence (AI). Recent studies have reported that EUS-based AI models can facilitate early and more accurate diagnosis than other preexisting methods. This article provides a review of the literature on EUS-based AI studies of pancreatic malignancies.

Effects of duck farming restriction measures on the incidence of avian influenza

  • Jaesung Cho;Yonggeon Lee;Hyunjoong Kim
    • Korean Journal of Agricultural Science
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    • v.50 no.2
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    • pp.207-218
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    • 2023
  • Duck farming restriction refers to a program in which duck farms suspend their operations for a certain period at times when the risk of avian influenza (AI) is high and receive compensation from the Korean government. This study analyzed the effect of this duck farming restriction on the incidence of AI using data on regional AI incidence rates, the program participation rate, and characteristics of poultry farming in 2016 (before the implementation of the restriction), as well as data from 2020 and 2021 (when new AI outbreaks occurred). In this study, the treatment group was divided into five subgroups according to the policy participation rate and a difference-in-difference (DID) estimation was conducted using certain covariates, in this case the average number of ducks raised, the land area, the number of high-susceptibility farms, the number of low-susceptibility farms, the average number of farms within a 3 km radius, the average distance to the nearest farm, and a year dummy. The results showed that when more than 30% of all duck farms in a region participated in the farming restriction, it had a statistically significant effect on the incidence of AI. Specifically, when more than 30, 40, 50, and 60% of all duck farms participated in the farming restriction, the AI incidence rate decreased by 0.7184, 1.0025, 1.5844, and 1.5843%p, respectively.

Deep Learning-Based, Real-Time, False-Pick Filter for an Onsite Earthquake Early Warning (EEW) System (온사이트 지진조기경보를 위한 딥러닝 기반 실시간 오탐지 제거)

  • Seo, JeongBeom;Lee, JinKoo;Lee, Woodong;Lee, SeokTae;Lee, HoJun;Jeon, Inchan;Park, NamRyoul
    • Journal of the Earthquake Engineering Society of Korea
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    • v.25 no.2
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    • pp.71-81
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    • 2021
  • This paper presents a real-time, false-pick filter based on deep learning to reduce false alarms of an onsite Earthquake Early Warning (EEW) system. Most onsite EEW systems use P-wave to predict S-wave. Therefore, it is essential to properly distinguish P-waves from noises or other seismic phases to avoid false alarms. To reduce false-picks causing false alarms, this study made the EEWNet Part 1 'False-Pick Filter' model based on Convolutional Neural Network (CNN). Specifically, it modified the Pick_FP (Lomax et al.) to generate input data such as the amplitude, velocity, and displacement of three components from 2 seconds ahead and 2 seconds after the P-wave arrival following one-second time steps. This model extracts log-mel power spectrum features from this input data, then classifies P-waves and others using these features. The dataset consisted of 3,189,583 samples: 81,394 samples from event data (727 events in the Korean Peninsula, 103 teleseismic events, and 1,734 events in Taiwan) and 3,108,189 samples from continuous data (recorded by seismic stations in South Korea for 27 months from 2018 to 2020). This model was trained with 1,826,357 samples through balancing, then tested on continuous data samples of the year 2019, filtering more than 99% of strong false-picks that could trigger false alarms. This model was developed as a module for USGS Earthworm and is written in C language to operate with minimal computing resources.

Development and Application of an Artificial Intelligence Convergence Education Program Linked to School Library Reading Activities for Middle School Students (중학생을 위한 학교도서관의 독서활동 연계 인공지능 융합교육 프로그램의 개발과 적용)

  • Yonju No;Ji Won You
    • Journal of the Korean Society for information Management
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    • v.41 no.1
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    • pp.439-463
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    • 2024
  • Recently, there has been a growing demand for school libraries to take on the role of curriculum convergence and content development. This study purposed to develop a program that integrates reading activities and artificial intelligence (AI) education in a middle school library as a platform for convergence education. The program aimed to enhance creative problem-solving skills by integrating an understanding of AI concepts and principles through reading activities related to AI topics. The program, comprising 18 sessions (6 modules), was implemented with 36 first-year students at A Middle School, Gyeonggi-do, in 2022. After implementation, a paired-sample t-test revealed significant improvements in AI learning self-efficacy and creative problem-solving skills. Participants also showed positive attitudes toward class engagement and reading activities. Implications for AI convergence education in connection with school libraries were discussed.

Artificial Insemination and Embryo Transfer Project to Foster Mongolia Dairy Industry

  • Kwon, Tae-Hyeon;Choi, Byeong-Hyun;Cho, Su-Jin;Tsolmon, Munkhbatar;Durevjargal, Naidansuren;Baldan, Tumur;Min, Chan-Sik;Kong, Il-Keun
    • Journal of Embryo Transfer
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    • v.24 no.4
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    • pp.289-292
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    • 2009
  • Mongolia has 80% livestock of total agriculture industry, 170,000 farms are engaged, 2,500,000 of cows that were beef and dairy cows are raised. Despite of Mongolian has great application with milk, there are not clear differences between cow and dairy cattle, and the production of milk is also low. But the milk suppliers are varied (horse, sheep, goat, etc), so that the total milk production is 500 thousand ton per year. It's really considerable to improve the breed of owing to many problems with big differences among milk qualities. For carrying out for first year project, artificial insemination project was operated with 3rd grade Holstein semen that were imported from S. Korea, and initiation and field training were also carried out through appropriate AI technique we developed for Mongolia environment. Local information research and MOU conclusion were done with professor D. Altangerel in May $10^{th}{\sim}13^{th}$, 2009, and development for AI technique and AI equipments were supplied for Mongolia breeding and natural environment in July $10^{th}{\sim}17^{th}$ in 2009. All cows were treated by synchronization for AI. To do this, $PGF_{2\alpha}$ injection were treated for luteal phase cow, if it wouldn't work, try again after 11 days. After confirmation of estrus, AI and AI training were carried out with sperm injection in the uterus or cervix by rectum-vagina method which is common worldwide, the most effective artificial insemination technique. If cows were return to next estrus cycle, second AI was carried out about approximately 21 days after artificial insemination. After 2 months, all cows not showing return estrus should be taken pregnancy test. Every pregnant cow will be cared thoroughly. Total 48 cows administrated by $PGF_{2\alpha}$ for synchronization and after 48 hours 45 cows (93.8%) showing estrus were detected and then artificial inseminate them within who 8 cows (27.8%) showed return estrus. Therefore, Using $PGF_2{\alpha}$ for synchronization is effective to use for Mongolia breeding conditions. There are possibility of base for food production after all, including increase of livestock production in Mongolia by improvement of breeding cow with AI and embryo transfer project.

A Nationwide Web-Based Survey of Neuroradiologists' Perceptions of Artificial Intelligence Software for Neuro-Applications in Korea

  • Hyunsu Choi;Leonard Sunwoo;Se Jin Cho;Sung Hyun Baik;Yun Jung Bae;Byung Se Choi;Cheolkyu Jung;Jae Hyoung Kim
    • Korean Journal of Radiology
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    • v.24 no.5
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    • pp.454-464
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    • 2023
  • Objective: We aimed to investigate current expectations and clinical adoption of artificial intelligence (AI) software among neuroradiologists in Korea. Materials and Methods: In April 2022, a 30-item online survey was conducted by neuroradiologists from the Korean Society of Neuroradiology (KSNR) to assess current user experiences, perceptions, attitudes, and future expectations regarding AI for neuro-applications. Respondents with experience in AI software were further investigated in terms of the number and type of software used, period of use, clinical usefulness, and future scope. Results were compared between respondents with and without experience with AI software through multivariable logistic regression and mediation analyses. Results: The survey was completed by 73 respondents, accounting for 21.9% (73/334) of the KSNR members; 72.6% (53/73) were familiar with AI and 58.9% (43/73) had used AI software, with approximately 86% (37/43) using 1-3 AI software programs and 51.2% (22/43) having up to one year of experience with AI software. Among AI software types, brain volumetry software was the most common (62.8% [27/43]). Although 52.1% (38/73) assumed that AI is currently useful in practice, 86.3% (63/73) expected it to be useful for clinical practice within 10 years. The main expected benefits were reducing the time spent on repetitive tasks (91.8% [67/73]) and improving reading accuracy and reducing errors (72.6% [53/73]). Those who experienced AI software were more familiar with AI (adjusted odds ratio, 7.1 [95% confidence interval, 1.81-27.81]; P = 0.005). More than half of the respondents with AI software experience (55.8% [24/43]) agreed that AI should be included in training curriculums, while almost all (95.3% [41/43]) believed that radiologists should coordinate to improve its performance. Conclusion: A majority of respondents experienced AI software and showed a proactive attitude toward adopting AI in clinical practice, suggesting that AI should be incorporated into training and active participation in AI development should be encouraged.

Exploration of AI Curriculum Development for Graduate School of Education (교육대학원 AI교육과정 개발 탐색)

  • Bae, Youngkwon;Yoo, Inhwan;Jang, Junhyeok;Kim, Daeyu;Yu, Wonjin;Kim, Wooyeol
    • Journal of The Korean Association of Information Education
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    • v.24 no.5
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    • pp.433-441
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    • 2020
  • The advent of the intelligent information society and artificial intelligence education for fostering future talents is attracting the attention of the education community, and the AI graduate course for teachers is also being opened and operated. The curriculum of the AI education graduate school, which was established this year, is self-contained considering the conditions of each university. Are organized. Accordingly, this study seeks to explore the direction of curriculum development so that AI curriculum that can be more effective and enhance educational value in the graduate school of education can be developed in the future. Based on the Backward design, the AI curriculum proposed in this study includes Bloom's digital taxonomy, Bruner's spiral curriculum composition principle, and three elements such as 'content domain', 'level', and 'teacher learning method'. It was intended to consist of. Based on the direction of AI curriculum development suggested in the study, we hope that the AI curriculum of domestic graduate schools of education will be more substantial, and this framework will be revised and supplemented in the future to be used in the composition of the AI curriculum in elementary and secondary schools.