• 한국의학물리학회지:의학물리
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• 제30권2호
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• pp.39-48
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• 2019

Deep learning has been applied to various medical data. In particular, current deep learning models exhibit remarkable performance at specific tasks, sometimes offering higher accuracy than that of experts for discriminating specific diseases from medical images. The current status of deep learning applications to molecular imaging can be divided into a few subtypes in terms of their purposes: differential diagnostic classification, enhancement of image acquisition, and image-based quantification. As functional and pathophysiologic information is key to molecular imaging, this review will emphasize the need for accurate biomarker acquisition by deep learning in molecular imaging. Furthermore, this review addresses practical issues that include clinical validation, data distribution, labeling issues, and harmonization to achieve clinically feasible deep learning models. Eventually, deep learning will enhance the role of theranostics, which aims at precision targeting of pathophysiology by maximizing molecular imaging functional information.

• International Journal of Advanced Culture Technology
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• 제10권4호
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• pp.420-426
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• 2022

Developing a machine learning model and putting it into production goes through a number of steps. Automated Machine Learning(AutoML) appeared to increase productivity and efficiency by automating inefficient tasks that occur while repeating this process whenever machine learning is applied. The high degree of automation of AutoML models allows non-experts to use machine learning models and techniques without the need to become machine learning experts. Automating the process of applying machine learning end-to-end with AutoML models has the added benefit of creating simpler solutions, generating these solutions faster, and often generating models that outperform hand-designed models. In this paper, the AutoML data is collected and AutoML's Color Petri net model is created and analyzed based on it.

• East Asian mathematical journal
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• 제38권4호
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• pp.497-516
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• 2022

In this study, we tried to devise a method to activate meta-affect in the aspect of supporting mathematics teaching and learning according to the need to find specific strategies and teaching and learning methods to activate learners' meta-affect in mathematics subjects, which are highly influenced by psychological factors. To this end, the definitional and conceptual elements of meta-affect which are the basis of this study, were identified from previous studies. Reflecting these factors, a teaching and learning model that activates meta-affect was devised, and a meta-affect activation strategy applied in the model was constructed. The mathematics teaching and learning model that activates meta-affect developed in this study was refined by verifying its suitability and convenience in the field through expert advice and application of actual mathematics classes. The developed model is meaningful in that it proposed a variety of practical teaching and learning methods that activate the meta-affect of learners in a mathematical learning situation.

• 무역학회지
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• 제46권2호
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• pp.281-299
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• 2021

This paper analyzes the feasibility of using machine learning methods to forecast the employment. The machine learning methods, such as decision tree, artificial neural network, and ensemble models such as random forest and gradient boosting regression tree were used to forecast the employment in Busan regional economy. The following were the main findings of the comparison of their predictive abilities. First, the forecasting power of machine learning methods can predict the employment well. Second, the forecasting values for the employment by decision tree models appeared somewhat differently according to the depth of decision trees. Third, the predictive power of artificial neural network model, however, does not show the high predictive power. Fourth, the ensemble models such as random forest and gradient boosting regression tree model show the higher predictive power. Thus, since the machine learning method can accurately predict the employment, we need to improve the accuracy of forecasting employment with the use of machine learning methods.

• 대한간호학회지
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• 제4권1호
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• pp.38-49
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• 1974

Presently, the performance level of the college student has received a great deal of attention, particularly in the area of professional education. The problem of under achievement, especially in areas dealing with science and technology, has gone through considerable investigation by numerous Psychologists and Educators. Thus for, however, they have not been successful in determining conclusively the non-intellectual factors involved. The maladjustment problem of these students has been a thorn in the side of nursing education for some time. This topic has been discussed among nursing educators without any tangible results. Furthermore, the fact that the number of students who withdraw from nursing education programs before graduation has increased. This represents a major problem for nursing education. This problem area had increased attention drawn to it on October 1957, when Russia successfully launched to first satellite "Sputnik" into space. Various studies seem to indicate that factors related to over achievement and under.achievement can be found in the motivation of the students. This study is aimed at testing 3 hypotheses which hopefully will lead to a better understanding of the learning activities of nursing students and to determine some of their nonintellectually personality traits. Hypothesis I: learning activities in nursing students and persona1ity are correlated, there will be significant differences in personality need structures between 4 classes of nursing collegiate students. Sub-hypothesis: There will also be significant differences in the degree of student satisfaction in her major subject. Hypothesis I: If there is a special personality need structure which is required for the clinical learning activity in general, then there will be significant differences between the personality need structures of under-achievers and overachiever. Hypothesis II : If each clinical nursing subject requires different personality need structures, then there will be differences in personality need structure between the different clinical groups Methodology: 1. Tool: A Korean translation and correction of the Edwards Personal Preference Schedule of U.S.A. was used. 2. Subject and Test Method: Subjects were nursing students at Yonsei University, who enrolled for Fall semester of 1971. The Researcher herself executed the test for the test for the class as a group, and the absent students were tested indidually. Out of 307 students, 293 students (95.4%) were reported. 3. Statistical treatment: The mean and standard deviation for each of the 15 personality need variables were computed and the value of T-test was obtained to determine the differences in the personality need structures between each group. Results: 1, For the first hypothesis, the personality need structures between each of the 4 classes and the reported degree of satisfaction in major subject showed significant differences. Therefore the hypothesis I was accepted. 2. The comparison of personality need structure of under-achievers and over-achievers in clinical fields showed significant differences. Thus hypothesis II was accepted. 3. Personality need structure between clinical subject groups showed significant differences therefore the 3rd hypothesis was accepted.

• 근관절건강학회지
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• 제29권3호
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• pp.185-193
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• 2022

Purpose: This study aims to provide basic data for future nursing education by identifying the effects of flipped learning-type project-based learning on nursing college students' self-directed learning ability, self-leadership, and academic self-efficacy. Methods: It is a pre-experimental study designed before and after a single group to verify the effect of flipped learning project-based learning on nursing students' self-directed learning ability, self-leadership, and academic self-efficacy in 81 third-grade nursing students. Results: No statistically significant difference in self-efficacy (t=-0.80, p=.545) but self-directed learning ability (t=-3.85, p<.001) and self-leadership (t=-5.18, p<.001) were found to have a statistically significant difference before and after. Conclusion: Flipped learning-type project-based learning was confirmed effective in improving nursing college students' self-directed learning ability and self-leadership. Therefore, instructors will need to develop and apply teaching methods that provide learners with opportunities for pre-learning and carry out learner-centered projects to improve nursing college students' self-directed learning ability and self-leadership.

• 한국산학기술학회논문지
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• 제18권1호
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• pp.269-281
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• 2017

최근 들어 초기 청소년기인 중학생 시기부터 진로준비를 적극적으로 해나가야 환경적 요구가 증가하면서 적극적인 진로준비행동을 촉진하는 환경적, 심리내적 변인에 대한 연구의 필요성이 증가하고 있다. 본 연구는 이러한 필요성에 근거하여 중학생을 대상으로 모의 학습관여가 진로준비행동에 미치는 영향을 희망이 매개하는지 알아보기 위해 실시되었다. 이를 위해 강원도 W시의 중학생 320명을 대상으로 모의 학습관여, 진로준비행동, 희망에 대한 설문을 실시하였고, 그 결과를 Baron과 Kenny(1986)의 매개효과 검증절차에 따라서 검증하였다. 그 결과 첫째, 모의 학습관여의 학업정보제공/조언, 학습방법존중은 희망 및 진로준비행동과 유의한 정적상관을 보였다. 반면 모의 부정적 학습관여인 학습성과 압력은 진로준비행동, 희망과 유의미한 상관을 보이지 않았다. 둘째, 희망은 모의 긍정적 학습관여인 학업정보제공/조언과 진로준비행동 간의 관계에서 부분매개효과가 있는 것으로 나타났고, 학습방법존중과 진로준비행동 간의 관계에서 완전매개효과가 있는 것으로 나타났다. 반면 희망은 모의 부정적 학습관여인 학습성과 압력과 진로준비행동 간의 관계에서 매개효과를 나타내지 않았다. 이러한 결과는 중학생의 진로준비행동의 수준을 높이기 위해 적절한 학업정보와 조언을 제공하고, 학업정보제공/조언과 학습방법존중을 통해 희망을 고취하는 것이 중요함을 시사한다.

• 대한화학회지
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• 제57권1호
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• pp.147-158
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• 2013

본 연구는 화학교육의 동기전략에 영향을 끼치는 학습관련 변인들의 인과관계에 대한 최적 모형을 찾고자 한다. 이를 위하여 광주광역시 소재 G와 I 고등학교에서 화학교육에 참여한 487명을 대상으로 하였다. 동기전략에 영향을 주는 학습관련 변인들의 경로모형을 탐색하기 위해, '자기효능감, 성취욕구, 지능신념'이 목표지향성을 매개로 하여 동기전략인 자기핸디캡경향과 학습전략으로 가는 모형을 Model I로 설정했다. 그리고 목표지향성을 근본 동기변인으로 하고 '자기효능감, 성취욕구, 지능신념'을 매개로 하여 '자기핸디캡경향과 학습전략'에 이르는 모형을 Model II로 설정했다. 이들 기본모형들을 기반으로 하여, 목표지향성(숙달목표, 수행접근목표 및 수행회피목표), 자기효능감, 성취욕구, 지능신념, 자기핸디캡경향 및 학습전략 간에 경로모형을 알기위해 통계분석을 통해 단계적으로 살펴보았다. 그 결과 Model I과 Model II 중에서 Model II가 선택되었고, 이 모형의 주요한 통계적 적합도 지수들을 확인하고 분석하면서 경로의 추가 및 삭제를 했고, 5차 수정한 결과, Model II-5의 경로모형이 본 연구의 최적 모형으로 채택되었다. 이 최적 모형을 분석한 결과, ${\chi}^2$의 p값도 0.267를 보임으로써 Model II-5가 측정자료와 아주 잘 일치한 모형임을 알 수 있었다. 본 연구에서는 15개의 경로들이 통계적으로 p <.05에서 유의미하게 학습전략에 영향을 주고 있음을 알 수 있다.

• 수산해양교육연구
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• 제27권1호
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• pp.18-28
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• 2015

This study aims to understand the meaning that learning of the old age has, through old age learners who augustly live after retirement-life so called successful silver years. Qualitative research methods is used for analyzing the contents of articles about 15 old age learners and the results are follows below. First, the retirement has dual meaning for the old learners. One is they experienced psychological and emotional insecurity after retirement and the other is it is a turning point for them to realize their longtime dream. Second, the old age learners showed enthusiasm about learning and they voluntarily found the way of success in their silver years. Finally, the old age learners working in new career with provocative and enthusiastic attitude work as a role model of successful old age life and show how they progress. This study argued that we need to consider the old as active agents and the old age as the time when productive and continuous learning can be done. In addition, this study strongly insisted that we need to realize the importance of 'education by the elderly' and social and other relevant conditions are needed to be established immediately.

• 공학교육연구
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• 제20권3호
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• pp.32-41
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• 2017

The $4^{th}$ industrial revolution refers to an era where machines capable of outperforming humans are created. In light of the 4th industrial revolution, university students are demanded problem solving abilities, critical thinking abilities, and problem discovering abilities as general and basic abilities. The need for changes in the university level communication education for engineering students remains imperative in this constantly changing social environment. The era where education is conducted only in classrooms is over. This paper discusses the need for diversified education such as the integration of online and offline education, the reinforcement of learning outside of the classroom as well as an education model that transcends formal and informal education such as games and activities that induce self-learning, both intentional and non-intentional learning, and the utilization of mass media and social networking systems. Through providing an education model that assesses and utilizes the data gained from the learning process provided above, this paper widens the perception of future education methods in the 4th industrial revolution.