• 전력전자학회논문지
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• 제27권1호
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• pp.48-55
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• 2022

This paper proposes a battery remaining useful life (RUL) prediction method using a deep learning-based EMD-CNN-LSTM hybrid method. The proposed method pre-processes capacity data by applying empirical mode decomposition (EMD) and predicts the remaining useful life using CNN-LSTM. CNN-LSTM is a hybrid method that combines convolution neural network (CNN), which analyzes spatial features, and long short term memory (LSTM), which is a deep learning technique that processes time series data analysis. The performance of the proposed remaining useful life prediction method is verified using the battery aging experiment data provided by the NASA Ames Prognostics Center of Excellence and shows higher accuracy than does the conventional method.

• 영어어문교육
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• 제6호
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• pp.35-47
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• 2000

This study questions the validity of Crosslinguistic Influence (CLI) in EFL Learning. A ten-minute grammaticality judgement test involving resumptive pronouns in English relative clauses was given to 15 female subjects. The research results, which were analysed in terns of language transfer and universalist arguments, support the existence of a universal process that guides L2 learning, and some common developmental patterns between the two processes of L1 and L2 learning. Hence, the universalist view should be given at least equal Weight as the CLI approach.

• 한국정보시스템학회지:정보시스템연구
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• 제6권2호
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• pp.165-188
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• 1997

This paper describes about the development of the 3 Dimensional interactive physics experiment system using virtual reality technologies. Until now, most of the computer aided education systems have adopted one-sided learning way which only shows or tells. It excludes students during learning processes. To solve the problems of the one-sided learning way and to improve the educational productivity, the 3 Dimensional interactive physics experiment system is developed. The 3 Dimensional interactive physics experiment system introduced in this paper provides a new learning motivation for students and improves their educational effects through the 3 Dimensional graphics, realtime action, and realistic interactive experiment.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.154-157
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• 2015

Construction industry still requires a lot of laborers to perform a project despite of advance in technologies, and improving labor productivity is an important strategy for successful project management. Since repetitive construction works exhibits learning effect, understanding laborers' learning phenomenon therefore allows managers to have improved labor productivity. In this context, previous research efforts quantified individual laborer's learning effect, though numerous construction works are performed in group. In other words, previous research about labor learning assumed that sum of individual's productivity is same as group productivity. Also, managers in construction sites need understanding about group learning behavior for dealing with labor performance problem. To address these issues, the authors investigate what variables affect laborers' group level learning process and develop conceptual model as a basic tool of productivity estimation regarding group learning. Based on the result of this research, it is possible to understand forming mechanism of learning within the group level. Further, this research may contribute to maximizing laborers' productivity in construction sites.

• 간호행정학회지
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• 제13권2호
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• pp.191-198
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• 2007

Purpose: The aim of this study was to find the effect of collaborative learning on problem-solving processes according to the level of metacognition, after adopting collaborative learning to clinical practice of nursing management. Method: Senior college students participated in this study. 90 students who was involveled in high level metacognitive group and another 88 students in low level metacognitive group. The data was collected from 2003 to 2005. The process of collaborative learning was categorised in 4 steps. The data were analyzed using t-test, ANCOVA, paired t-test. Results: 'There will be a distinction between the low and high metacognition groups after application of collaborative learning' was rejected. 'In the high level metacognitive group, the problem-solving ability will also increase after application of collaborative learning than before application' was supported. 'In the low level metacognitive group, the problem-solving ability will increase after application of collaborative learning than before application' was supported. Conclusion: The results showed that with collaborative learning, the problem-solving ability of learners with different levels of metacognition is improved.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.165-165
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• 2023

Streamflow prediction is a critical task in water resources management and essential for planning and decision-making purposes. However, the streamflow prediction is challenging due to the complexity and non-linear nature of hydrological processes. The transfer learning is a powerful technique that enables a model to transfer knowledge from a source domain to a target domain, improving model performance with limited data in the target domain. In this study, we apply the transfer learning using the Informer model, which is a state-of-the-art deep learning model for streamflow prediction. The model was trained on a large-scale hydrological dataset in the source basin and then fine-tuned using a smaller dataset available in the target basin to predict the streamflow in the target basin. The results demonstrate that transfer learning using the Informer model significantly outperforms the traditional machine learning models and even other deep learning models for streamflow prediction, especially when the target domain has limited data. Moreover, the results indicate the effectiveness of streamflow prediction when knowledge transfer is used to improve the generalizability of hydrologic models in data-sparse regions.

• 한국수학교육학회지시리즈A:수학교육
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• 제41권2호
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• pp.189-202
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• 2002

Problem-centered learning reflects learning strategy based on constructivism. In this learning, students should find the solution in a small group discussion, and share their solutions with classmates in whole class discussion. So students participate in mathematics instruction actively and interact with other students about the strategies. We expect students would change their attitudes on mathematics and mathematical learning in these processes. In this study, we analyzed students' attitudes on mathematics and mathematical learning when they participated the problem-centered learning program. We found the change of students' attitudes to mathematics via problem-centered learning.

• ETRI Journal
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• 제28권4호
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• pp.461-474
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• 2006

This project aims to design and develop a prototype for an agent that support online collaborative learning. Online collaborative learning, which has emerged as a new form of education in the knowledge-based society, is regarded as an effective method for improving practical and highly advanced problem-solving abilities. Collaborative learning involves complicated processes, such as organizing teams, setting common goals, performing tasks, and evaluating the outcome of team activities. Thus, a teacher may have difficulty promoting and evaluating the entire process of collaborative learning, and a system may need to be developed to support it. Therefore, to promote interaction among learners in the process of collaborative learning, this study designed an extensible collaborative learning agent (ECOLA) for an online learning environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제2권5호
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• pp.239-252
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• 2008

To facilitate the processes of e-learning resource description, discovery and reuse, e-learning objects should be appropriately described and classified using standard metadata that need to be published in a registry to reduce duplication of effort and enhance semantic interoperability. This paper describes how standard ebXML registries can be used for semantic grid computing for annotating, storing, discovering and retrieving e-learning object metadata. For semantic annotation of e-learning objects, IEEE Learning Object Metadata (LOM) is adopted as the metadata ontology. In order to support the e-learning metadata ontology in interoperable ebXML registries, a mapping scheme between LOM and ebXML Registry Information Model (RIM) is proposed. The usefulness of sharing e-learning object metadata is demonstrated by prototyping a semantic registry based on the scheme.

• 한국비블리아학회지
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• 제29권3호
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• pp.89-109
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• 2018

본 연구는 문헌정보학과 '미디어센터 운영' 과목 수강생을 대상으로 프로젝트 기반 학습이 자기주도적 학습과 문제해결능력에 미치는 영향을 파악하기 위해 수행되었다. 자기주도적 학습능력은 8개 하위영역의 48문항, 문제해결능력은 5단계의 문제해결과정에 근거한 30개 문항으로 측정되었다. 대응표본 T-test를 통해 분석한 결과, 8개 하위영역으로 구성된 자기주도적 학습능력에서 '자기이해' 영역을 제외한 모든 영역에서 통계적으로 유의한 결과를 발견하였다. 또한, 5단계로 구성된 문제해결능력에서 모두 통계적으로 유의한 차이를 보였다. 심층면담이 과목 수강의 어려움, 수업 내용, 과제의 적절성, 평가방법의 타당성, 팀원과의 관계, 과제 수행 후 유익성에 대하여 이루어졌고, 추후연구를 위한 제언이 제시되었다.