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학교수학 교수.학습에서 기술공학의 활용 연구 (A Study on the Use of Technology in Teaching-learning School Mathematics)

  • 이정례
    • 한국수학교육학회지시리즈E:수학교육논문집
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    • 제24권1호
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    • pp.29-48
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    • 2010
  • 본 연구의 목적은 학교수학 교수 학습에서 성공적인 기술공학의 활용을 위하여 기술공학 활용의 현황을 분석하고 효과적인 활용 방안을 제시하는 것이다. 본 연구에서는 기술공학 활용의 필요성에 대한 이론적 배경과 활용 가능한 기술공학적 도구들을 소개하고, 고등학교 수학교과서를 중심으로 기술공학 활용의 현황과 문제점을 분석하여 그 해결 방안을 제시한다. 또한 학교수학 교수 학습에서 기술공학의 활용 방안을 수학의 영역별로 살펴보고, 기술공학을 활용한 모델들을 소개한다.

하브루타(Havruta) 수업이 전문대학교 물리치료과 학생들의 학습 태도와 수업 만족도에 미치는 영향 (The effect of Havruta class on learning attitude and class satisfaction in a class of college physical therapy students)

  • 정은정
    • 대한물리치료과학회지
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    • 제28권1호
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    • pp.62-75
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    • 2021
  • Background: The world has entered the age of biotechnology and artificial intelligence, and encouraging students to test the value of information and knowledge ie to become information fluent, is becoming more important. The education system is also changing in order to adapt to the times. As a part of this, the cultivation of creative talent is a core goal of many nation states, and Israel's Jewish education methods are attracting attention; havruta (or chavrusa) is one such method. This study aims to effects of havruta class on learning attitudes and class satisfaction in a class of college physical therapy students. Design: Pretest-posttest design. Methods: The subjects were 95 students in College A. The learning attitudes questionnaire were used by the Korea Educational Development Institute, and the class satisfaction questionnaire before and after intervention. Results: The results showed significant differences in learning habits about physical therapy of learning attitudes (p<.05) and class methods and contents attention and understanding (p<.05), class interest of class satisfaction (p<.05). Conclusion: These results suggest that havruta class improves learning attitudes and class satisfaction. Therefore, follow-up study is needed to apply the havruta class in various students and teaching methods.

The effects of the online team project-based learning on problem solving ability, cooperative self efficacy and cooperative self regulation in students of department of physical therapy

  • Kim, Jung Hee;Lee, Woo Hyung
    • 대한물리치료과학회지
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    • 제28권3호
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    • pp.1-10
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    • 2021
  • Background: The purpose of this study is to investigate the effect of the online team project based learning on problem-solving, cooperative self-efficacy, and cooperative self-regulation of college students. Design: Single group pre-post design. Methods: The online team project based learning was conducted for a total of 92 college students for 8 weeks. A survey was conducted on problem-solving ability, cooperative self-efficacy, and cooperative self-regulation. In the online team project-based class, two projects were performed. It consists of video lectures and real-time video conferencing. Through the real-time video conference, the project was carried out based on discussion among learners and feedback was provided. Results: There was a significant difference in the change in problem-solving ability compared to before learning (p<0.05). As a result of the evaluation of cooperative self-efficacy, there was a significant difference (p<0.05). There was a significant differences in cooperative self-regulation compared to before learning (p<0.05). Conclusion: The online team project-based learning are effective in improving learners' problem-solving ability, cooperative self-efficacy, and cooperative self-regulation.

대학 교수자의 수업전문성 향상을 목적으로 하는 e-티칭 포트폴리오의 구성요소 탐색 (An Exploration on Elements of e-Teaching Portfolio for Enhancing Teaching Expertise in Higher Education)

  • 이은화
    • 수산해양교육연구
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    • 제20권2호
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    • pp.236-248
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    • 2008
  • This study has explored the elements of e-teaching portfolio for enhancing teaching expertise in higher education. This study is carried out through the literature review and expert's focus group interview. As the result of this study, seven elements of e-teaching portfolio for enhancing teaching expertise in higher education have been found. First, 'personal background' include curriculum vitae, course responsibility, and other educational activities. Second, 'teaching philosophy' include the principals on teaching and learning, statements of teaching philosophy. Third, 'learning environment' include the characteristics of students, the previous learning contents, and physical environment. Forth, 'course contents and methods' include teaching strategies and instructional materials, Fifth, 'instructional evaluation' includes the principals of evaluation and the examples of learning outcomes. Sixth, 'endeavor for improvement of instruction' include evidence of activity for teaching improvement and instruction feedback from peer and students. And e-teaching portfolio also includes research career and awards history element.

사교육문제 해소를 위한 U-learning대안에 관한 고찰 (Will U-learning Replace Any private Lesson\ulcorner)

  • Kim, Jae-Won
    • 한국산업정보학회:학술대회논문집
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    • 한국산업정보학회 2003년도 추계공동학술대회
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    • pp.227-237
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    • 2003
  • U-learning stresses the ubiquitous networking environment where different sizes of U-devices, let alone the dominant PCs, comprise a background infrastructure to enhance knowledge and performance. This paper suggests a U-learning system that will provide an alternative for the hectic private lessons, particularly English training among grade-school students. Several points are suggested of the U-system to be a cost-effective alternative. Besides the corresponding advancement of U-networking, the production of a profitable business model harnessing the emerging technology is most urgent. The Government authorities should recognize the potential U-social system solutions, and take an initiative to develop them. The latest technology seems to throw a light to the upcoming social systems applied in various fields of social needs.

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Robust appearance feature learning using pixel-wise discrimination for visual tracking

  • Kim, Minji;Kim, Sungchan
    • ETRI Journal
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    • 제41권4호
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    • pp.483-493
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    • 2019
  • Considering the high dimensions of video sequences, it is often challenging to acquire a sufficient dataset to train the tracking models. From this perspective, we propose to revisit the idea of hand-crafted feature learning to avoid such a requirement from a dataset. The proposed tracking approach is composed of two phases, detection and tracking, according to how severely the appearance of a target changes. The detection phase addresses severe and rapid variations by learning a new appearance model that classifies the pixels into foreground (or target) and background. We further combine the raw pixel features of the color intensity and spatial location with convolutional feature activations for robust target representation. The tracking phase tracks a target by searching for frame regions where the best pixel-level agreement to the model learned from the detection phase is achieved. Our two-phase approach results in efficient and accurate tracking, outperforming recent methods in various challenging cases of target appearance changes.

딥러닝 기반 드론 검출 및 분류 (Deep Learning Based Drone Detection and Classification)

  • 이건영;경덕환;서기성
    • 전기학회논문지
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    • 제68권2호
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    • pp.359-363
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    • 2019
  • As commercial drones have been widely used, concerns for collision accidents with people and invading secured properties are emerging. The detection of drone is a challenging problem. The deep learning based object detection techniques for detecting drones have been applied, but limited to the specific cases such as detection of drones from bird and/or background. We have tried not only detection of drones, but classification of different drones with an end-to-end model. YOLOv2 is used as an object detection model. In order to supplement insufficient data by shooting drones, data augmentation from collected images is executed. Also transfer learning from ImageNet for YOLOv2 darknet framework is performed. The experimental results for drone detection with average IoU and recall are compared and analysed.

심층 전이 학습을 이용한 이미지 검색의 문화적 특성 분석 (Analysis of Cultural Context of Image Search with Deep Transfer Learning)

  • Kim, Hyeon-sik;Jeong, Jin-Woo
    • 한국정보통신학회논문지
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    • 제24권5호
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    • pp.674-677
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    • 2020
  • The cultural background of users utilizing image search engines has a significant impact on the satisfaction of the search results. Therefore, it is important to analyze and understand the cultural context of images for more accurate image search. In this paper, we investigate how the cultural context of images can affect the performance of image classification. To this end, we first collected various types of images (e.g,. food, temple, etc.) with various cultural contexts (e.g., Korea, Japan, etc.) from web search engines. Afterwards, a deep transfer learning approach using VGG19 and MobileNetV2 pre-trained with ImageNet was adopted to learn the cultural features of the collected images. Through various experiments we show the performance of image classification can be differently affected according to the cultural context of images.

Radiomics and Deep Learning in Brain Metastases: Current Trends and Roadmap to Future Applications

  • Park, Yae Won;Lee, Narae;Ahn, Sung Soo;Chang, Jong Hee;Lee, Seung-Koo
    • Investigative Magnetic Resonance Imaging
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    • 제25권4호
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    • pp.266-280
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    • 2021
  • Advances in radiomics and deep learning (DL) hold great potential to be at the forefront of precision medicine for the treatment of patients with brain metastases. Radiomics and DL can aid clinical decision-making by enabling accurate diagnosis, facilitating the identification of molecular markers, providing accurate prognoses, and monitoring treatment response. In this review, we summarize the clinical background, unmet needs, and current state of research of radiomics and DL for the treatment of brain metastases. The promises, pitfalls, and future roadmap of radiomics and DL in brain metastases are addressed as well.

강건한 얼굴인식을 위한 배경학습에 관한 연구 (A Study on Background Learning for Robust Face Recognition)

  • 박동희;설증보;나상동;배철수
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2004년도 춘계종합학술대회
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    • pp.608-611
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    • 2004
  • 본 논문에서는 고유얼굴 특성에 기반한 강건한 얼굴 인식 기술을 제안한다. 전형적인 고유얼굴 인식방법은 학습영역에서 고유얼굴을 생성시키고, 모든 학습영상을 이 얼굴공간에 투영시켜 각각의 사람마다 저장된 성분들을 비교하거나 상관시켜 특징들을 추출합니다. 복잡한 배경에 있는 얼굴들을 인식할 때 EFR방법은 얼굴인식에는 강하지만, 얼굴과 배경들 사이의 구분을 실패하게 된다 배경에서 강건한 얼굴인식을 위해서 배경패턴을 학습하며, 배경영역은 배경패턴으로부터 생성되어 얼굴영역과 함께 얼굴 인식을 위하여 사용된다. 본 논문에서 제안한 방법이 EFR방법보다 성능과 복잡한 배경하에서 매우 좋은 결과를 나타냄을 확인할 수 있었다.

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