• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.44-52
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• 2022

With recent scientific advances and growing interest in AI technologies, AI-based chatbots have been viewed as a practical learning aid for English language development. The purpose of this study is to examine preservice teachers' perceptions on the potential benefits of employing AI chatbots in English instruction and its pedagogical aspects. 28 preservice teachers majoring in English education were asked to use Kuki chatbots for a week with a guidance of a researcher and then report on their perceptions of AI chatbots in terms of perceived usefulness after use, applicability, and educational benefits and drawbacks. Emerging codes and themes were identified and evaluated using Thematic Analysis(TA) based on qualitative data from surveys and interviews. The findings show that six emerging themes were identified, encompassing perspectives on teacher, learner, communication, linguistic, affective, and assessment. The overall findings of this study revealed that AI-based chatbots can play a significant role as learning tools for stimulating interactive communication in a target language. Most preservice primary teachers acknowledge that AI chatbots can be useful as teaching and learning aids for both teachers and students. Furthermore, when applying various learner data to chatbot technology, such as learner assessment and diagnosis, a guided approach is necessary to perform a conversation appropriate for the learner's level and characteristics. Finally, as chatbots have a variety of benefits in terms of affective aspects, they may improve EFL learners' confidence in speaking English and learning motivation.

• Journal of Veterinary Science
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• v.24 no.1
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• pp.5.1-5.16
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• 2023

The H9N2 avian influenza (AI) has become endemic in poultry in many countries since the 1990s, which has caused considerable economic losses in the poultry industry. Considering the long history of the low pathogenicity H9N2 AI in many countries, once H9N2 AI is introduced, it is more difficult to eradicate than high pathogenicity AI. Various preventive measures and strategies, including vaccination and active national surveillance, have been used to control the Y439 lineage of H9N2 AI in South Korea, but it took a long time for the H9N2 virus to disappear from the fields. By contrast, the novel Y280 lineage of H9N2 AI was introduced in June 2020 and has spread nationwide. This study reviews the history, genetic and pathogenic characteristics, and control strategies for Korean H9N2 AI. This review may provide some clues for establishing control strategies for endemic AIV and a newly introduced Y280 lineage of H9N2 AI in South Korea.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.589-595
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• 2023

Artificial intelligence(AI) is spurring advancements in EdTech, the merger of technology and education. This includes the creation of effective learning materials and personalized student experiences. Our study focuses on developing a programming education software that employs state-of-the-art generative AI. Our software also includes prompts optimized for programming code analysis, which are based on the well-known ChatGPT API. Furthermore, the necessary functions for acquiring programming skills were created with a user interface and developed as a question-and-answer template function based on an AI chatbot. The objective of this study is to guide the development of educational programmes that make use of generative AI.

• Neonatal Medicine
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• v.18 no.2
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• pp.211-220
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• 2011

Purpose: Late-onset hypotension in preterm infants is not a rare condition. Late circulatory collapse due to adrenal insufficiency (AI) is one of the major causes of late-onset hypotension. We assessed the incidence and causes of late-onset hypotension. We also compared the clinical findings according to the presence of AI. Methods: In total, 244 preterm infants with a gestational age ${\leq}$32 weeks and who were admitted to the neonatal intensive care unit (NICU) of Seoul National University Boramae Hospital and Seoul National University Hospital from January 2009 to April 2011 were included. Clinical findings were analyzed retrospectively. Results: Forty-four infants (18%) suffered from late-onset hypotension. Hydrocortisone was administered to 30 infants (68.2%) and AI occurred in 16 infants (36.4%). Cesarean section, sepsis before hypotension, and gastrointestinal surgery were independently associated with late-onset hypotension. Intrauterine growth retardation (IUGR) was less frequent in the hydrocortisonetreated group than in infants not treated with hydrocortisone. The AI group had fewer IUGR infants, and the duration of hospitalization was shorter in the AI group than in infants who were not administered hydrocortisone. Blood pressure tended to normalize more quickly in the AI group, however, the difference was not significant. Conclusion: AI was a major cause of late-onset hypotension, and the use of hydrocortisone shortened the length of hospitalization.

• Korean Journal of Materials Research
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• v.8 no.7
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• pp.596-600
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• 1998

Reaction bonded $AI_2O_3$(RBAO)-SiC ceramics were prepared from the Al/$AI_2O_3$/SiC powder mixture. The calcined alumina and fused alumina were used as the raw $AI_2O_3$ powder. The same sized (3mm) and differently sized (3mm + Smm) $Zr0_2$ balls were used in attrition milling of starting powders. The effect of $AI_2O_3$ powder shapes on the milling efficiency and reaction sintering was investigated. After attrition milling, isopressed compacts were preheated to 1l00$^{\circ}$C with a heating rate l.5$^{\circ}C$/min and then sintered at the temperature range 1500 to 1$600^{\circ}C$ for S hours with a heating rate 5$^{\circ}C$/min. The powder mixture with fused alumina was effectively comminuted than the mixtures with calcined alumina. And the same sized balls milled more effctive than the differently sized balls. The reaction sintering behavior differed not depending on the shapes of $AI_2O_3$ powder.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.428-434
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• 2020

Recently, due to the development of ICT technology, changes to the convergence service platform of information systems are accelerating. Convergence services expanded to cyber systems with 5G communication, IoT, AI, and cloud are being reflected in the real world. However, the field of cybersecurity audit for responding to cyber attacks and security threats and strengthening security technology is insufficient. In this paper, we analyze the international standard analysis of information security management system, security audit analysis and security of related systems according to the expansion of 5G communication, IoT, AI, Cloud based information system security. In addition, we design and study cybersecurity audit checklists and contents for expanding security according to cyber attack and security threat of information system. This study will be used as the basic data for audit methods and audit contents for coping with cyber attacks and security threats by expanding convergence services of 5G, IoT, AI, and Cloud based systems.

• The Journal of Korean Medicine
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• v.44 no.4
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• pp.72-86
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• 2023

Objectives: The medical field is rapidly evolving with AI and digital technologies like AI-based X-ray analysis and digital therapeutics gaining approval. Telemedicine is becoming prominent, and medical schools are adapting by integrating AI education. Pusan National University leads a talent training project for AI in health. Korean Medicine is incorporating AI with diagnostic systems and chatbots. However, there's a lack of research on education awareness in Korean Medicine Colleges. The study aims to assess opinions on integrating AI, digital therapeutics, and DNA test into the Korean medicine college curriculum for improved education. Methods: We selected appropriate four specific areas: artificial intelligence in medicine, digital therapeutics, DNA test, and telemedicine. The questionnaire developed for this study underwent expert evaluation and was subsequently administered to registered KMDs of the Association of Korean Medicine, as well as students from 12 Korean Medicine universities. The survey was designed to analyze the awareness and perceived importance of the 4 areas. Results: Both KMDs and Korean medicine students exhibited comparable awareness levels across the four objectives. Notably, both groups identified a high educational necessity and importance of artificial intelligence in medicine for clinical settings. Statistically significant differences were observed between KMDs and students in their perspectives on the importance of telemedicine and DNA test in the Korean medicine field, the educational necessity of DNA test within Korean medicine universities, and the need for comprehension of regulations related to digital therapeutics. Conclusion: The survey of Korean medicine professionals and students underscores a strong understanding of key areas such as Telemedicine, medical AI, DNA test, and digital therapeutics. Medical AI is identified as crucial for future education. There's a consensus on the need for curriculum changes in Korean medicine schools, particularly in adapting to evolving healthcare trends. The focus should be on practical clinical application, with a call for additional research to better integrate student and practitioner perspectives in future curriculum reform discussions.

• Korean Journal of Agricultural Science
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• v.42 no.1
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• pp.15-22
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• 2015

This study was conducted to evaluate the phytotoxicity of imazosulfuron+fentrazamide mixture in rice field. It is recommended that safe herbicide application was obtained at 3 cm of transplanting depth and in sandy loam or loam soil type. In the direct water seeding of rice, imazosulfuron+fentrazamide SC should be applied at least 10 days before sowing land ower than 25+100 g ai/ha. In case of imazosulfuron+fentrazamide SC application after sowing, If we use the herbicide 15 days after sowing, no herbicide symptoms will be detected even though the amounts of the herbicide increase. In the rice transplanting, it is recommended that imazosulfuron+fentrazamide GR is applied 5 days after transplanting. In case of sequential herbicide application, the imazosulfuron+fentrazamide SC application at 75+300 g ai/ha 15 or 20 days after transplanting after the application at 25+100 g ai/ha or 50+200 g ai/ha 3 days before sowing increases weed control efficacy and gives no phytotoxicity in the rice growth.

• Korean Journal of Radiology
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• v.23 no.5
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• pp.505-516
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• 2022

Objective: To evaluate whether artificial intelligence (AI) for detecting breast cancer on mammography can improve the performance and time efficiency of radiologists reading mammograms. Materials and Methods: A commercial deep learning-based software for mammography was validated using external data collected from 200 patients, 100 each with and without breast cancer (40 with benign lesions and 60 without lesions) from one hospital. Ten readers, including five breast specialist radiologists (BSRs) and five general radiologists (GRs), assessed all mammography images using a seven-point scale to rate the likelihood of malignancy in two sessions, with and without the aid of the AI-based software, and the reading time was automatically recorded using a web-based reporting system. Two reading sessions were conducted with a two-month washout period in between. Differences in the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and reading time between reading with and without AI were analyzed, accounting for data clustering by readers when indicated. Results: The AUROC of the AI alone, BSR (average across five readers), and GR (average across five readers) groups was 0.915 (95% confidence interval, 0.876-0.954), 0.813 (0.756-0.870), and 0.684 (0.616-0.752), respectively. With AI assistance, the AUROC significantly increased to 0.884 (0.840-0.928) and 0.833 (0.779-0.887) in the BSR and GR groups, respectively (p = 0.007 and p < 0.001, respectively). Sensitivity was improved by AI assistance in both groups (74.6% vs. 88.6% in BSR, p < 0.001; 52.1% vs. 79.4% in GR, p < 0.001), but the specificity did not differ significantly (66.6% vs. 66.4% in BSR, p = 0.238; 70.8% vs. 70.0% in GR, p = 0.689). The average reading time pooled across readers was significantly decreased by AI assistance for BSRs (82.73 vs. 73.04 seconds, p < 0.001) but increased in GRs (35.44 vs. 42.52 seconds, p < 0.001). Conclusion: AI-based software improved the performance of radiologists regardless of their experience and affected the reading time.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.232-237
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• 2020

Given the recent pace of development and expansion of Artificial Intelligence (AI) technology, the influence and ripple effects of AI technology on the whole of our lives will be very large and spread rapidly. The National Artificial Intelligence R&D Strategy, published in 2019, emphasizes the importance of artificial intelligence education for K-12 students. It also mentions STEM education, AI convergence curriculum, and budget for supporting the development of teaching materials and tools. However, it is necessary to create a new type of curriculum at a time when artificial intelligence curriculum has never existed before. With many attempts and discussions going very fast in all countries on almost the same starting line. Also, there is no suitable professor for K-12 students, and it is difficult to make K-12 students understand the concept of AI. In particular, it is difficult to teach elementary school students through professional programming in AI education. It is also difficult to learn tools that can teach AI concepts. In this paper, we propose an educational model for elementary school students to improve their understanding of AI through play or experience. This an experiential education model that combineds exploratory learning and discovery learning using multi-intelligence and the PLAY teaching-learning model to undertand the importance of data training or data required for AI education. This educational model is designed to learn how a computer that knows only binary numbers through UA recognizes images. Through code.org, students were trained to learn AI robots and configured to understand data bias like play. In addition, by learning images directly on a computer through TeachableMachine, a tool capable of supervised learning, to understand the concept of dataset, learning process, and accuracy, and proposed the process of AI inference.