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평생교육과 연계한 공공도서관의 정보활용 교육 적용 방안에 관한 연구 (A Study on Application of Information Literacy Education of Public Library Connected Lifelong Education)

  • 조미아
    • 한국도서관정보학회지
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    • 제38권4호
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    • pp.187-213
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    • 2007
  • 본 연구는 평생교육과 연계한 공공도서관의 정보활용 교육 방안을 제시하기 위하여 지방평생교육센터로 지정된 공공도서관에서 수행하고 있는 평생교육 프로그램을 조사하여 e-learning과 오프라인 프로그램으로 나누어 분석하였으며 정보활용교육이 활발한 공공도서 관의 정보활용교육의 실제 사례를 수집하여 분석하였다.

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XML-based Retrieval System for E-Learning Contents using mobile device PDA

  • Park Yong-Bin;Yang Hae-Sool
    • 한국산업정보학회:학술대회논문집
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    • 한국산업정보학회 2006년도 춘계 국제학술대회 논문집
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    • pp.241-248
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    • 2006
  • Web is greatly contributing in providing a variety of information. Especially, as media for the purpose of development and education of human resources, the role of web is important. Furthermore, E-Learning through web plays an important role for each enterprise and an educational institution. Also, above all, fast and various searches are required in order to manage and search a great number of educational contents in web. Therefore, most of present information is composed in HTML, so there are lots of restrictions. As a solution to such restriction, XML a standard of Web document, and its various search functions is being extended and studied variously. This paper proposes a search system able to search XML in E-Learning or var ious contents of non-XML using mobile device PDA.

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비선형 시스템 식별기로서의 자율분산 신경망 (Self-Organized Ditributed Networks as Identifier of Nonlinear Systems)

  • 최종수;김형석;김성중;최창호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 하계학술대회 논문집 B
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    • pp.804-806
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    • 1995
  • This paper discusses Self-organized Distributed Networks(SODN) as identifier of nonlinear dynamical systems. The structure of system identification employs series-parallel model. The identification procedure is based on a discrete-time formulation. The learning with the proposed SODN is fast and precise. Such properties arc caused from the local learning mechanism. Each local networks learns only data in a subregion. Large number of memory requirements and low generalization capability for the untrained region, which are drawbacks of conventional local network learning, are overcomed in the SODN. Through extensive simulation, SODN is shown to be effective for identification of nonlinear dynamical systems.

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Application of Artificial Intelligence in Capsule Endoscopy: Where Are We Now?

  • Hwang, Youngbae;Park, Junseok;Lim, Yun Jeong;Chun, Hoon Jai
    • Clinical Endoscopy
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    • 제51권6호
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    • pp.547-551
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    • 2018
  • Unlike wired endoscopy, capsule endoscopy requires additional time for a clinical specialist to review the operation and examine the lesions. To reduce the tedious review time and increase the accuracy of medical examinations, various approaches have been reported based on artificial intelligence for computer-aided diagnosis. Recently, deep learning-based approaches have been applied to many possible areas, showing greatly improved performance, especially for image-based recognition and classification. By reviewing recent deep learning-based approaches for clinical applications, we present the current status and future direction of artificial intelligence for capsule endoscopy.

유동인구 예측을 위한 Global - Local 구조 기반의 시계열 Deep Learning 모델에 관한 연구 (A Study on Deep Learning Model Based on Global-Local Structure for Crowd Flow Prediction)

  • 고현모;박상현
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2021년도 추계학술발표대회
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    • pp.458-461
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    • 2021
  • 유동인구 예측은 상권의 특성에 따른 점포의 입지 선정 및 고객 맞춤형 마케팅 등 민간 분야에서부터 교통망 등 사회 간접 자본 설계를 위한 공공 분야에 이르기까지 다양한 목적으로 연구되어 왔으며, 최근에는 Covid-19 의 확산에 따라 그 중요도가 더욱 높아지고 있다. 보다 정교한 예측을 위해서는 전체적인 유동 인구 뿐만 아니라 특성 별로 세분화된 하위 그룹에 대해서도 정확한 예측이 요구되나, 기존의 예측 모델들은 이러한 데이터의 계층 구조를 고려하지 않았다. 본 연구에서는 세분화된 하위 그룹 별 유동인구의 예측 정확도를 높이기 위해 전체 유동인구의 패턴을 동시에 활용하는 Global-Local 구조 기반의 Deep Learning 유동인구 분석 모델을 제안한다. 실험 결과 단일 시계열 데이터만을 사용하는 경우 대비 5.4%~52.6%의 예측 오류 감소 효과가 있음을 확인하였다.

Methodology for Apartment Space Arrangement Based on Deep Reinforcement Learning

  • Cheng Yun Chi;Se Won Lee
    • Architectural research
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    • 제26권1호
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    • pp.1-12
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    • 2024
  • This study introduces a deep reinforcement learning (DRL)-based methodology for optimizing apartment space arrangements, addressing the limitations of human capability in evaluating all potential spatial configurations. Leveraging computational power, the methodology facilitates the autonomous exploration and evaluation of innovative layout options, considering architectural principles, legal standards, and client re-quirements. Through comprehensive simulation tests across various apartment types, the research demonstrates the DRL approach's effec-tiveness in generating efficient spatial arrangements that align with current design trends and meet predefined performance objectives. The comparative analysis of AI-generated layouts with those designed by professionals validates the methodology's applicability and potential in enhancing architectural design practices by offering novel, optimized spatial configuration solutions.

Effect of Acupuncture at ST36 on Ischemia-induced Learning and Memory Deficits in Gerbils

  • Chung, Jin-Yong;Park, Hyun-Jung;Shim, Hyun-Soo;Hahm, Dae-Hyun;Kim, Hee-Young;Lee, Hye-Jung;Kim, Kyung-Soo;Shim, In-Sop
    • 동의생리병리학회지
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    • 제25권2호
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    • pp.300-305
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    • 2011
  • The present study was investigated the neuroprotective effects of acupuncture at ST36 on learning and memory deficits after transient cerebral ischemia in a gerbil model. The animals were randomly divided into three groups (n=7 in each group): the sham operation group (SHAM), ischemia-induced and ST36 acupuncture group (ISC + ST36), and the ischemia-induced and Tail-acupuncture group (ISC + TAIL). For the acupuncture stimulation, stainless steel needles, 0.3 mm in diameter, were inserted bilaterally into the ST36 locus or the tail and stimulated for 1 min/day for 14 days. Using the Morris water maze test, the animals were tested on spatial learning and memory. In addition, the effects of acupuncture on memory storage and the choline acetyltransferase (ChAT) activity, in the hippocampal CA1 area, were investigated by ChAT immunohistochemistry. Transient cerebral ischemia produced impaired performance on the MWM test (DAY 5: p<0.01 and retention test: p<0.05) and severely decreased ChAT immunoreactivity in the CA1 hippocampal area compared to the SHAM group (p<0.05). However, improved learning and memory were observed (DAY 5: p<0.05 and retention test: p<0.01) as well as a significantly reduced loss of ChAT immunoactivity in the hippocampal CA1 region (p<0.001) after acupuncture stimulation at ST36 were observed. These results show that acupuncture at ST36 ameliorated the learning and memory deficits at least in part through the cholinergic system. The findings of this study provide potential data that acupuncture is useful for the treatment of some of the behavioral impairs of transient cerebral ischemia.

웹 기반 간호 교육을 위한 튜터의 운영 전략 개발 및 효과 검증 연구 (A Study of Development and Evaluation of Tutorial Management Strategy for Web-based Nursing Education)

  • 최지은;김분한
    • 성인간호학회지
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    • 제17권4호
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    • pp.635-645
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    • 2005
  • Purpose: This study was attempted and completed in order to settle down and qualitatively improve web-based nursing education by evaluating effect and managing strategy of tutor. Method: The development of tutor's managing strategy was based on "The Self-regulated Learning" and "The supportive Learning", then it was applied to 79 learners in one of the cyber-learning centers. After applying the tutor's managing strategy, self-regulated learning scale, attitude for school, preference for computer and academic achievement were evaluated. The development of tutor's managing strategy for web-based nursing education are consisted of participation promotion, psychological support and motivation, recognition and promotion strategy of learning activity, management strategy of evaluating stage. Result: The levels of learner's self-regulated learning, recognition, behavior, attitude on the school and learning achievement were meaningfully increased in statistics after applying for the managing strategy of tutor. The motivation level and learning participation kept high scores from the beginning with no significant statistical changes. Conclusion: It is required to develop an educational program for cultivating well-educated tutors in order to help the effective learning process of nurses based on understanding characteristics of learners.

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4개 전공/학습내용별 교수법에 따른 학습반응 분석 (Analysis of Learning Responses According to Teaching Methods for Four Major/Learning Contents)

  • 이재경;안준수
    • 공학교육연구
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    • 제20권2호
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    • pp.31-38
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    • 2017
  • In this study, specific teaching methods of lecturing and improved discussion methods (combining discussion and problem-based learning) were selected and applied for each major subject and learning content area in the fields of engineering, language, and social sciences. Then, the selected teaching methods were examined to determine the most effective learning contents. Finally, in order to determine the most effective teaching methods, a survey on student satisfaction was analyzed statistically. The results showed that students preferred teaching methods that combine lectures and improved discussion methods to the traditional method of only lectures. Therefore, this research proposes the combined teaching method for each major subject and learning content area.

Multi-dimensional Interactivity for Learners' Satisfaction with e-Learning

  • Lee, Ji-Eun;Shin, Min-Soo
    • Journal of Information Technology Applications and Management
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    • 제17권3호
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    • pp.135-150
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    • 2010
  • Interactivity has been referred to as an important element promoting students' active participation in virtual classes. Assuming that interactivity cannot be defined by a single dimension, this study proposes multi-dimensional interactivity. Multi-dimensional interactivity includes all types of interactivity in e-learning. This study explored multi-dimensional interactivity which affects learners' satisfaction with e-learning. Data were collected from 132 students who had attended e-learning courses and the relationship between multi-dimensional interactivity and learners' satisfaction levels were tested through regression analysis. The result of this study showed that mechanical, reactive, and creative interactivity were positively related to learners' satisfaction. However, social interactivity seemed not to be related to learners' satisfaction. This study provides new insights on interactivity and verifies the importance of the multi-dimensional interactivity. The result of this study is expected to provide practical implications for interactivity strategies in e-learning.

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