• 제목/요약/키워드: complementary learning

검색결과 123건 처리시간 0.033초

'지층과 암석'에 대한 초등 예비 교사의 지식 이해와 교수유형 (Pre-service Elementary Teacher' Knowledge understanding and Teaching-learning type about 'stratum and rock')

  • 이용섭;김순식;이하룡
    • 대한지구과학교육학회지
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    • 제6권1호
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    • pp.69-77
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    • 2013
  • The study aims to figure out pre-service elementary teachers' knowledge understanding on 'stratum and rock' as well as teaching-learning types on the same topic. A total of 65 seniors in an advanced science education course at B University of Education joined the research to fulfill the purpose above. With PCK classification framework, the study examined pre-service teachers' knowledge understanding on 'stratum and rock' while it analyzed how the teachers would teach the given topic to students. The results of the study are presented as follows. First, it was observed that the pre-service elementary teachers have a great understanding on 'stratum and rock' that would be taught via a science textbook for elementary fourth graders. However, regarding terms in 'shale and limestone', they appeared to have a relatively short understanding. Second, PCK elements of the pre-service teachers related to 'stratum and rock' were analyzed and according to the results, the teachers would be interested in teaching model selecting in the teaching-learning strategy field while they would be well aware of how important it is for them to perform an experiment in a teaching process. The teachers also appeared to understand that the teacher question can be mutual complementary during class. However, it turned out that the teachers would have a very much low understanding on learners' prior knowledge as they particularly believe that learning could be significantly affected by the learners' perception level as well as their learning interest and motive. Third, the pre-service elementary teachers were told to design teaching plans on 'stratum and rock' so that the study could find out what learning-teaching methods the teachers would adopt to teach the topic. It was learned that the teachers would proceed with the class basically by giving the learners a descriptive explanation on the topic and also by using pictures and drawings to enhance the learners' understanding during the class.

머신러닝 기법을 활용한 낙동강 하구 염분농도 예측 (Nakdong River Estuary Salinity Prediction Using Machine Learning Methods)

  • 이호준;조민규;천세진;한정규
    • 스마트미디어저널
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    • 제11권2호
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    • pp.31-38
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    • 2022
  • 하천의 염분 변화를 신속히 예측하는 것은 염분 침투로 인한 농업, 생태계의 피해를 예측하고 재해 방지 대책을 수립하기 위해서 중요한 작업이다. 머신러닝 기법은 물리 기반 수리 모델에 비해 계산량이 훨씬 적기 때문에, 비교적 짧은 시간에 염분농도를 예측 가능하여 물리 기반 수리 모델의 보완 기법으로 연구되고 있다. 해외에서는 머신러닝 기법 기반 염분 예측 연구들이 활발히 연구되고 있으나, 대한민국의 공공데이터에 머신러닝 기법을 적용한 연구는 충분치 않다. 낙동강 하구의 환경 정보에 관한 공공데이터와 함께, 본 연구는 여러 종류의 머신러닝 기법의 염분농도에 대한 예측 성능을 측정하였다. 실험 결과에서, 결정 트리 기반의 LightGBM 알고리즘은 평균 RMSE 0.37의 예측 정확도와 타 알고리즘 대비 2-20배 빠른 학습 속도를 보여주었다. 따라서 국내 하천의 염분농도 예측에도 머신러닝 기법을 적용할 수 있다고 판단된다.

한의과대학 학부생을 위한 보완대체의학 교육과정 개발 연구 (Development of Complementary and Alternative Medicine Curriculum for Undergraduate Students at College of Oriental Medicine)

  • 이수진;박수잔;신상우;채한
    • 대한한의학회지
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    • 제29권1호
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    • pp.25-38
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    • 2008
  • Objectives : Integrative medicine in Korea is the 21st century-style medical practice of two orthodox medical doctrines, traditional Korean medicine and western conventional medicine, as well as complementary and alternative medicine (CAM). CAM with scientific evidence should be incorporated in undergraduate curricula for the purpose of Korean integrative medicine. Methods : Items of detailed objectives, syllabi, textbooks, instructor's experiences, and effectiveness and reason for difficulty of the CAM curriculum for undergraduate students were analyzed and the preference of CAM therapies and others were also evaluated. Results and Discussion : The effectiveness of this CAM class curriculum was high (8.0$\pm$1.4) enough to be used in other Oriental medical colleges. Development of ability for self-study was rated as 7.0$\pm$1.7 and the helpfulness for clinical use was marked as 6.8$\pm$1.9. Students preferred placebo, Ayurveda, aromatherapy, yoga, functional food, bio-feedback and homeopathy. The difficulty degree was 7.2$\pm$1.6, and the amount of content was suggested as the major reason for it. We also found that this curriculum can be a model for self-oriented study and problem-based learning. Discussions were made for the improvement of the implemented CAM curriculum, which was shown to be very effective for the achievement of Korean integrative medicine. Conclusion : We have successfully installed a CAM curriculum for undergraduate students at the College of Oriental Medicine, and it can be used in others.

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Congested Market Equilibrium Analysis

  • Oh, Hyung-Sik
    • 대한산업공학회지
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    • 제13권2호
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    • pp.65-77
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    • 1987
  • Congestion occurs whenever users interfere with each other, while competing for scarce resources. In a congested market, such as a telecommunication service market, users of telecommunication services incur costs in using the service in addition to the price. The user's own time costs involved in learning to use the service, waiting for the service, and making use of the service are typically greater than the price of telecommunication services. A market equilibrium analysis is performed in which a method for user demand aggregation is developed. The effects of price changes on user demands and market demands for congested services are examined. It is found that total market demands may increase as the price for less-congested services increase under certain demand conditions. This suggests that a nonuniform pricing scheme for a congested service may improve the utilization of the congested system. The sign of price cross-elasticity for congested services is show to vary with demand conditions. A possible complementary property of congested services is found and the implication of such a property is discussed. It is argued that such a complementary property may lead to a cross subsidy in a market with congestion. Finally, comparisons between uniform pricing and nonuniform pricing policies are made. A specific numerical example is given to show that a nonuniform pricing policy may be Pareto superior to a uniform pricing policy.

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간호 학생의 전인간호 태도에 대한 이해 : 융합적 연구 (Convergence Study for Understanding Nursing Students' Holistic Nursing Attitudes)

  • 이영신
    • 한국융합학회논문지
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    • 제10권1호
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    • pp.361-370
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    • 2019
  • 본 연구는 간호 학생을 대상으로 일반적 특성, 전인간호 태도와 문화역량을 확인하여 전인간호 태도 향상을 돕기 위한 기초자료를 마련하기 위하여 실시한 서술적 조사 연구이다. 연구 결과 전인간호 태도는 전공만족도, 학과 성적 등의 일반적 특성과 관련이 있었다. 비과학적 중재라도 대상자가 원하면 제공하겠다고 응답한 경우와 학부교육과정에서 보완대체요법을 배우는 것에 긍정적으로 응답한 경우 전인간호 태도 점수가 높았다. 전인간호 태도와 문화역량은 양의 상관관계를 보였다. 일반적 특성을 통제한 상태에서 문화역량은 전인간호 태도 증가에 영향을 주었다. 간호학생의 전인간호 태도에 대한 확인은 중요하며 그 수준에 따라 맞추어진 교육이 제공 되어야 할 것으로 생각된다.

상보적 수업을 활용한 읽기전략 훈련이 독해력, 초인지, 자기효능감에 미치는 효과 (The effect of reading strategies developing through reciprocal teaching on reading comprehension, metacognition, self efficacy)

  • 김미정;은혁기
    • 초등상담연구
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    • 제11권2호
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    • pp.299-320
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    • 2012
  • 본 연구는 상보적 수업을 활용한 읽기전략 학습상담프로그램이 초등학생의 독해력, 초인지 및 자기효능감에 미치는 효과를 알아보는데 그 목적이 있다. 이를 위해 중소도시 초등학교 5학년 2개 학급을 각각 실험집단과 통제집단으로 선정하고, 실험집단에 5주 동안 총 10회기의 상보적 수업을 활용한 읽기전략 학습상담프로그램을 실시하였다. 연구의 결과는 다음과 같다. 첫째, 상보적 수업을 활용한 읽기전략 학습상담프로그램은 초등학생들의 독해력과 그 하위 요인인 사실적 이해와 감상적 이해 영역에서 유의한 효과가 있었다. 둘째, 상보적 수업을 활용한 읽기전략 학습상담프로그램은 초인지의 하위요인인 조정 영역에서 유의한 효과가 있었다. 셋째, 상보적 수업을 활용한 읽기전략 학습상담프로그램은 자기효능감에서 유의한 효과가 있었다. 새로운 읽기전략에 대한 경험과 또래집단 구성원간에 주고받는 도움과 성공 경험이 자기효능감에 긍정적인 영향을 준 것으로 볼 수 있다. 넷째, 학생의 활동보고서 및 연구자의 관찰결과와 함께 프로그램에 대한 만족도 평가를 실시한 결과에서 초등학생들이 협동학습을 통해 학습 집단에서 공동 목표를 설정하고 그 목표를 달성하기 위해서 함께 노력하여 다른 구성원에게 도움을 주고받으며 즐겁게 참여하는 것이 긍정적인 프로그램 효과에 기여하였음을 확인할 수 있었다. 이상과 같은 연구 결과를 통해 상보적 수업을 활용한 읽기전략 학습상담프로그램이 초등학생들의 독해력, 초인지, 자기효능감을 향상시키는데 긍정적인 효과가 있었다.

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다중 도메인 학습을 이용한 화면 촬영 영상 내 모아레 무늬 제거 기법 (Screen-shot Image Demorieing Using Multiple Domain Learning)

  • 박현국;비엔지아안;이철
    • 방송공학회논문지
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    • 제26권1호
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    • pp.3-13
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    • 2021
  • 본 논문은 다중 도메인 학습을 이용하여 화면 촬영 영상 내 모아레 무늬를 효과적으로 제거하는 기법을 제안한다. 제안하는 기법은 먼저 화소값 영역과 주파수 영역에서 입력 영상의 모아레 무늬를 각각 제거한다. 다음으로 모아레 영상에서 clean edge map을 추정하고, 추정된 clean edge map을 가이드 정보로 사용하여 화소값 영역과 주파수 영역에서 얻은 결과 영상의 품질을 향상시킨다. 마지막으로, 독립적으로 향상된 두 결과 영상을 적응적으로 결합하며 모아레 무늬가 제거된 최종 결과 영상을 생성한다. 컴퓨터 모의 실험결과를 통해 제안하는 기법이 기존의 알고리즘보다 모아레 무늬를 더욱 효과적으로 제거할 수 있음을 확인한다.

An Empirical Analysis of Trade Support System and Export Performance in Korean SMEs

  • KIM, Byoung-Goo
    • 융합경영연구
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    • 제8권1호
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    • pp.36-49
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    • 2020
  • Purpose - This study investigates factors that affected the utilization of trade support policies and further analyzed how the utilization of trade support policies affected export performance. Research design, data, and methodology - With a sample of 223 small and medium-sized export firms from South Korea, this study examines the determinants of the utilization level of trade support system such as export market orientation, learning orientation, network capability and environmental uncertainty by regression analysis. Results - Export market orientation have a positive effect on the utilization of the trade support system and there is positive relationship between learning orientation and the utilization of trade support system. And network capabilities have had a positive impact on the utilization of the trade support system but there is no relationship between environmental uncertainty and the utilization of trade support system. The utilization of the trade support system had a positive effect on export performance. Conclusions - The internal and external factors of the organization have affected small and medium-sized export firms use of trade support systems. The utilization of trade support system can enhance positive export performance by providing valuable information and resource to external knowledge and also to complementary resources from the external partners.

Image Translation of SDO/AIA Multi-Channel Solar UV Images into Another Single-Channel Image by Deep Learning

  • Lim, Daye;Moon, Yong-Jae;Park, Eunsu;Lee, Jin-Yi
    • 천문학회보
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    • 제44권2호
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    • pp.42.3-42.3
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    • 2019
  • We translate Solar Dynamics Observatory/Atmospheric Imaging Assembly (AIA) ultraviolet (UV) multi-channel images into another UV single-channel image using a deep learning algorithm based on conditional generative adversarial networks (cGANs). The base input channel, which has the highest correlation coefficient (CC) between UV channels of AIA, is 193 Å. To complement this channel, we choose two channels, 1600 and 304 Å, which represent upper photosphere and chromosphere, respectively. Input channels for three models are single (193 Å), dual (193+1600 Å), and triple (193+1600+304 Å), respectively. Quantitative comparisons are made for test data sets. Main results from this study are as follows. First, the single model successfully produce other coronal channel images but less successful for chromospheric channel (304 Å) and much less successful for two photospheric channels (1600 and 1700 Å). Second, the dual model shows a noticeable improvement of the CC between the model outputs and Ground truths for 1700 Å. Third, the triple model can generate all other channel images with relatively high CCs larger than 0.89. Our results show a possibility that if three channels from photosphere, chromosphere, and corona are selected, other multi-channel images could be generated by deep learning. We expect that this investigation will be a complementary tool to choose a few UV channels for future solar small and/or deep space missions.

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Surface-Engineered Graphene surface-enhanced Raman scattering Platform with Machine-learning Enabled Classification of Mixed Analytes

  • Jae Hee Cho;Garam Bae;Ki-Seok An
    • 센서학회지
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    • 제33권3호
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    • pp.139-146
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    • 2024
  • Surface-enhanced Raman scattering (SERS) enables the detection of various types of π-conjugated biological and chemical molecules owing to its exceptional sensitivity in obtaining unique spectra, offering nondestructive classification capabilities for target analytes. Herein, we demonstrate an innovative strategy that provides significant machine learning (ML)-enabled predictive SERS platforms through surface-engineered graphene via complementary hybridization with Au nanoparticles (NPs). The hybridized Au NPs/graphene SERS platforms showed exceptional sensitivity (10-7 M) due to the collaborative strong correlation between the localized electromagnetic effect and the enhanced chemical bonding reactivity. The chemical and physical properties of the demonstrated SERS platform were systematically investigated using microscopy and spectroscopic analysis. Furthermore, an innovative strategy employing ML is proposed to predict various analytes based on a featured Raman spectral database. Using a customized data-preprocessing algorithm, the feature data for ML were extracted from the Raman peak characteristic information, such as intensity, position, and width, from the SERS spectrum data. Additionally, sophisticated evaluations of various types of ML classification models were conducted using k-fold cross-validation (k = 5), showing 99% prediction accuracy.