• Journal of Oral Medicine and Pain
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• 제47권2호
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• pp.107-108
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• 2022

Artificial intelligence (AI) refers to the use of machines to mimic intelligent human behavior. It involves interactions with humans in clinical settings, and augmented intelligence is considered as a cognitive extension of AI. The importance of AI in healthcare and medicine has been emphasized in recent studies. Machine learning models, such as genetic algorithms, artificial neural networks (ANNs), and fuzzy logic, can learn and examine data to execute various functions. Among them, ANN is the most popular model for diagnosis based on image data. AI is rapidly becoming an adjunct to healthcare professionals and is expected to be human-independent in the near future. The introduction of AI to the diagnosis and treatment of oral diseases worldwide remains in the preliminary stage. AI-based or assisted diagnosis and decision-making will increase the accuracy of the diagnosis and render treatment more precise and personalized. Therefore, dental professionals must actively initiate and lead the development of AI, even if they are unfamiliar with it.

• Clinical and Experimental Reproductive Medicine
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• 제51권1호
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• pp.1-12
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• 2024

This review article discusses the integration of artificial intelligence (AI) in assisted reproductive technology and provides key concepts to consider when introducing AI systems into reproductive medicine practices. The article highlights the various applications of AI in reproductive medicine and discusses whether to use commercial or in-house AI systems. This review also provides criteria for implementing new AI systems in the laboratory and discusses the factors that should be considered when introducing AI in the laboratory, including the user interface, scalability, training, support, follow-up, cost, ethics, and data quality. The article emphasises the importance of ethical considerations, data quality, and continuous algorithm updates to ensure the accuracy and safety of AI systems.

• ETRI Journal
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• 제46권1호
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• pp.48-58
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• 2024

This paper presents the development of language tutoring systems for nonnative speakers by leveraging advanced end-to-end automatic speech recognition (ASR) and proficiency evaluation. Given the frequent errors in non-native speech, high-performance spontaneous speech recognition must be applied. Our systems accurately evaluate pronunciation and speaking fluency and provide feedback on errors by relying on precise transcriptions. End-to-end ASR is implemented and enhanced by using diverse non-native speaker speech data for model training. For performance enhancement, we combine semisupervised and transfer learning techniques using labeled and unlabeled speech data. Automatic proficiency evaluation is performed by a model trained to maximize the statistical correlation between the fluency score manually determined by a human expert and a calculated fluency score. We developed an English tutoring system for Korean elementary students called EBS AI Peng-Talk and a Korean tutoring system for foreigners called KSI Korean AI Tutor. Both systems were deployed by South Korean government agencies.

• 한국과학교육학회지
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• 제22권3호
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• pp.508-516
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• 2002

이 연구에서는 소집단 구성 방법에 따른 협동적 CAI의 효과를 개념 이해도, 개념 응용력, 과학 학습 동기, 수업 참여도에 대한 인식 측면에서 조사하였다. 서울시의 한 남녀공학 중학교에서 1학년 97명을 선정하고 '분자의 운동'에 대하여 5차시 동안 수업을 실시하였다. 두 처치 집단에서는 사전 과학 청취도를 기준으로 이질적 소집단과 동질적 소집단을 구성하여 협동적 CAI를 실시하였고, 비교 집단에는 전통적인 수업을 실시하였다. 이원 공변량 분석 결과, 처치 집단들의 개념 검사 점수가 비교 집단에 비하여 유의미하게 높았다. 그러나 집단 구성 방법에 따른 차이는 유의미하지 않았다. 개념 응용력 검사와 과학 학습 동기 검사 점수에서는 세 집단 간에 유의미한 차이가 없었다. 그러나 협동적 CAI 집단의 수업 참여도에 대한 인식이 비교 집단에 비하여 더 긍정적이었다.

• 간호행정학회지
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• 제12권1호
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• pp.41-51
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• 2006

Purpose: The purposed of this study was to develop and evaluate a Web-based for medical terminology educational program. Method: For the development of this program, the NBISD model was applied as a basic model and WBI ID Process Action model was applied. It was executed for 15 weeks along with off-line lectures. After the operation of this program to 210 nursing students, learners' responses were analyzed twice(at 5th week and 15th week). Result: The satisfaction with this program was slightly above the center point. But the structure of system and composition of design were high score. The results of the final evaluation were more positive than those of the interim one. This program have the advantage of easy accessibility and easy understandability with picture and testing. Conclusions: This study proved the importance of the suitability of learning contents and learning form in developing WBI programs and showed possibility for applying WBI to medical terminology. In order to enhance the effects of Web-based medical terminology educational program for, it is necessary to perform analytic comparison with the effect of WBI based on self-directed learning.

• 한국기계가공학회지
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• 제19권9호
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• pp.47-52
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• 2020

With the 4th industrial revolution, condition monitoring using machine learning techniques has become popular among researchers. An overload due to complex operations causes several irregularities in MOSFETs. This study investigated the acquired voltage to analyze the overcurrent effects on MOSFETs using a failure mode effect analysis (FMEA). The results indicated that the voltage pattern changes greatly when the current is beyond the threshold value. Several features were extracted from the collected voltage signals that indicate the health state of a switched-mode power supply (SMPS). Then, the data were reduced to a smaller sample space by using a principal component analysis (PCA). A robust machine learning algorithm, the support vector machine (SVM), was used to classify different health states of an SMPS, and the classification results are presented for different parameters. An SVM approach assisted by a PCA algorithm provides a strong fault diagnosis framework for an SMPS.

• 컴퓨터교육학회논문지
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• 제13권1호
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• pp.37-44
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• 2010

최근 효율적인 외국어 학습 및 진단을 위해 외국어학습의 뇌공학적 접근이 활발하게 이루어지고 있다. 본 논문은 기존의 지필고사를 대체할 수 있는 뇌공학적 외국어 능숙도 진단 도구를 개발하는 것을 목표로 이를 위해 기존 언어심리학 과제에서 주로 사용되었던 테스트들을 기반으로 외국어 능숙도 진단을 위한 도구를 개발 하였다. 본 논문에서 제안한 도구들은 학습자의 기억능력, 이해능력, 산출능력을 5가지 테스트를 통하여 대뇌의 정보처리 양상을 간접적으로 측정한다.

• 디지털산업정보학회논문지
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• 제10권3호
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• pp.207-221
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• 2014

Education environment of modern society is rapidly changing along the usage of various device and development of contents. Learners of diverse age groups and genders are exposed in smart education environment. Thus in order to investigate effective smart education contents production, this study classified interactive types that affect learning satisfaction into CAI (Computer Assisted Instruction) based , NCS (Network Communication System) based , and NTS (New Technology System) based . Then we investigated how each interactive types affect immersion, utility, self-efficacy, practicality, and stimulation. The effects were measured according to the learner's gender and age. As the result, interactive types do affect smart education, where male had higher learning satisfaction for CAI based, game type, and wiki type while female had higher satisfaction for relationship establishment type and experience type. Also, for age group, the 10s preferred NTS based, 20~30s NCS based, and 40s and over CAI based interactive type. Thus, if satisfaction levels according to gender and age are considered when producing smart education contents, it may be possible to create educative contents that meet the dispositions of the learners.

• 성인간호학회지
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• 제15권1호
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• pp.105-115
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• 2003

Purpose: The research purposes analyzed the study participation and lecture evaluation of applicants in the cyber hospice specialist education course to find problems of nurse education application on the web. Method: Study participants were 125 nurses for participation and 68nurses for lecture evaluation. The data was analysed by descriptive statistics. Result: The results obtained from this study were as follows 1) The residence distribution of study participants was spread out across the nation. Equal distribution of education was accomplished without a difference among provinces. 2) The average study duration in the study participation was about one hour and a quarter minutes a week, and number of access to lecture notes was 65.8 times. But in a discussion room and a cooperative room, the system using rate was very low, so we considered the idea to come up with a more effective application way. 3) The participant's lecture evaluation of cyber education were generally satisfied about the quality of lecture, time, contents etc. Conclusion: This study shows the possible implication for nursing fields using a web-based learning program for reeducation in a variety of fields, so nursing cyber application can be considered to come up with this more effective method.

• 한국가정과교육학회지
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• 제5권1호
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• pp.143-152
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• 1993

The purposes of this study were to compare the learning effects of CAI and traditional instruction method in the Home Economics class of middle school and to examine the difference of learning effect between CAI group and traditional instruction group according to ability level. The research findings are as follows: 1.$\circled1$As a result of the post test, CAI group showed significantly higher scores on academic achievement than those of traditional instruction group(p<.05). $\circled2$As a result of the retention test, CAI group showed higher scores than those of traditional instruction group, but statistically the difference is not so significant. 2. $\circled1$Higher group in pre-test score of CAI group showed higher scores in post-test and retention test than those of traditional instruction group, but statistically the difference is not so significant. $\circled2$Lower group in pretest score of CAI group showed significantly higher academic achievements than those of traditional instruction group(p<.05). $\circled3$Higher group in IQ test score of CAI group did not show significantly higher academic achievements than those of traditional instruction group. $\circled4$Lower group in IQ test score of CAI group showed significantly higher academic achievements than those of traditional instruction group(p<.05)