• Title/Summary/Keyword: 이러닝 시스템

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Selective ATM UI Simplification System Using Deep Learning Image Recognition (딥러닝 모델을 이용한 선택적 ATM UI 간편화 시스템)

  • Hyeok-Min Kwon;Dong-Unk Kim;Seong-Kyoo Kim;Gang-Min Lee;San-Ha Park;Hae-Jun Park;Myung-Chun Ryoo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.263-264
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    • 2023
  • 오늘날 출산율 감소와 의료기술 등의 발달에 따라 고령화 사회 현상이 급부상하고 있으며, 이 비율은 계속 증가할 것이다. 또한 노인 인구가 많아지는 만큼 노안을 가진 사람들도 많아진다. 고령화 사회가 지속되는 만큼 고령층이 이용할 수 있는 디지털 기기 또한 많아져야 하지만 그렇지 않다. 그중에 하나인 ATM은 고령층을 제외한 고객들은 모바일뱅킹과 같은 서비스를 이용하고 고령층이 주로 ATM을 이용한다. 주요 고객인 고령층이 사용하는 ATM이지만 고령층을 배려한 ATM은 찾아보기 힘들다. 이에 본 논문에서는 딥러닝 모델을 이용하여 노안을 갖고 있거나 고령층이라는 것을 나이로 판단하여 고령층과 일반적인 노안을 갖는 연령층이 보다 쉽게 ATM을 이용 할 수 있는 선택적 ATM UI 간편화 시스템을 구축하였다.

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Implementation of Computer Vision and Deep Learning-Based Golfer Pose-Estimation System And Coaching System (컴퓨터 비전과 딥러닝 라이브러리 기반 골퍼 자세 판단 및 코칭 시스템)

  • Byeon, Woo-Jin;Shim, Young-Seon;You, Hye-Seung;Kang, Seokhun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.11a
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    • pp.1040-1043
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    • 2020
  • 본 논문에서는 골퍼의 자세 교정을 위해 레슨 프로 혹은 코치가 수행하는 교육을 담당하는 시스템을 구현한다. 이 시스템은 골프를 배우고자 하는 골퍼와 자세를 교정하고자 하는 골퍼를 대상으로 한다. 프로 골퍼의 스윙자세 영상을 촬영하고 딥러닝 라이브러리로 관절, 클럽의 위치를 디지털로 식별하여 표준 자세 정보를 입수한다. 그리고 사용자의 영상을 촬영하여 표준자세 정보와 비교 후 올바른 자세를 도표 및 시각적으로 제공 할 수 있도록 한다. 사람이 하는 방식 보다 객관적이고, 센서방식 보다 경제적인 시스템으로 골프교육산업의 활성화에 기여 할 수 있을 것이다.

TV Watching Pattern Analysis System based on Multi-Attribute LSTM Model (다중속성 LSTM 모델 기반 TV 시청 패턴 분석 시스템)

  • Lee, Jongwon;Sung, Mikyung;Jung, Hoekyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.4
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    • pp.537-542
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    • 2021
  • Smart TVs provide a variety of services and information compared to existing TVs based on the Internet. In order to provide more personalized services or information, it is necessary to analyze users' viewing patterns and provide customized services or information based on them. The proposed system receives the user's TV viewing pattern, analyzes it, and recommends a TV program or movie as customized information to the user. For this, the system was constructed with a preprocessor and a deep learning model. The preprocessor refines the name of the TV program watched by the user, the date the TV program was watched, and the watched time. Then, the multi-attribute LSTM model trains the refined data and performs prediction.The proposed system is a system that provides customized information to users, and is believed to be a leading technology in digital convergence that combines existing IoT technology and deep learning technology.

Design and Implementation of u-Learning Contents Authoring System based on a Learning Activity (학습활동 중심의 u-러닝 콘텐츠 저작 시스템의 설계 및 구현)

  • Seong, Dong-Ook;Lee, Mi-Sook;Park, Jun-Ho;Park, Hyeong-Soon;Park, Chan;Yoo, Kwan-Hee;Yoo, Jae-Soo
    • The Journal of the Korea Contents Association
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    • v.9 no.1
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    • pp.475-483
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    • 2009
  • With the development of information communication and network technologies, ubiquitous era that supports various services regardless of places and time has been advancing. The development of such technologies have a great influence on educational environments. As a result, e-learning concepts that learners use learning contents in anywhere and anytime have been proposed. The various learning contents authoring systems that consider the e-learning environments have also been developed. However, since most of the existing authoring systems support only PC environments, they is not suitable for various ubiquitous mobile devices. In this paper, we design and implement a contents authoring system based on learning activities for u-learning environments. Our authoring system significantly improves the efficiency for authoring contents and supports various ubiquitous devices as well as PCs.

Design and Development of White-box e-Learning Contents for Science-Engineering Majors using Mathematica (이공계 대학생을 위한 Mathematica 기반의 화이트박스 이러닝 콘텐츠 설계 및 개발)

  • Jun, Youngcook
    • Journal of the Korean School Mathematics Society
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    • v.18 no.2
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    • pp.223-240
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    • 2015
  • This paper deals with how to design and develop white-box based e-learning contents which are equipped with conceptual understanding and step-by-step computational procedures for studying vector calculus for science-engineering majors who might need supplementary mathematics learning. Noting that rewriting rules are often used in school mathematics for students' problem solving, the theoretical aspects of rewriting rules are reviewed for developing supplementary e-learning contents for them. The software design of step-by-step problem solving requires careful arrangement of rewriting rules and pattern matching techniques for white-box procedures using a computer algebra system such as Mathematica. Several modules for step-by-step problem solving as well as producing dynamic display of e-learning contents was coded by Mathematica in order to find the length of a curve in vector calculus after implementing several rules for differentiation and integration. The developed contents are equipped with diagnostic modules and immediate feedback for supplementary learning in terms of a tutorial. At the end, this paper indicates the strengths and features of the developed contents for college students who need to increase math learning capabilities, and suggests future research directions.

Development of flash flood guidance system for rural area based on deep learning (딥러닝 기반 농촌유역 돌발홍수 예경보 시스템 개발)

  • Ryu, Jeong Hoon;Kang, Moon Seong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2018.05a
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    • pp.309-309
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    • 2018
  • 기후변화에 따른 강우의 규모와 발생빈도 증가로 농촌유역의 홍수 피해는 지속적으로 증가하고 있다. 하지만 우리나라의 홍수 피해 저감 대책은 도시지역의 대하천 주변으로 집중되어있으며, 소하천 및 농촌유역의 홍수 피해 저감에 대한 관리와 투자 노력은 부족한 실정이다. 특히, 최근 들어 갑작스런 집중호우 등으로 인한 농촌유역 돌발홍수 피해 사례가 증가하고 있으며, 이에 대응하기 위해서는 홍수 발생 등을 신속하게 파악하기 위한 돌발홍수 예경보 시스템 개발이 필요하다. 한편, 최근 산업의 혁신과 생산성 향상을 위한 새로운 패러다임으로 4차 산업혁명이 대두되고 있으며, 빅데이터와 인공지능 (Artificial Intelligence, AI)을 비롯하여 사물인터넷 (Internet of Things, IoT), 드론, 슈퍼컴퓨팅 등의 이른바 4차 산업혁명 기술을 활용한 연구가 수행되고 있다. 본 연구에서는 기후변화에 따른 농촌유역 홍수 피해를 저감하고 또한 사전에 대비하기 위해 빅데이터와 인공지능 등 4차 산업혁명 기술을 적용한 농촌유역 돌발홍수 예경보 시스템을 개발하고 그 적용성을 평가하고자 한다. 우선, 농촌유역의 홍수와 관련된 빅데이터 (기상 자료, 수문 자료, 기후변화 자료, 농업용 수리구조물 자료 등)를 토대로 정형 빅데이터와 비정형 빅데이터를 구분 추출하고 이를 연계 해석할 수 있는 시스템을 개발하였다. 추출한 정형 및 비정형 빅데이터를 활용하여 딥러닝을 기반으로 농촌유역의 홍수를 예측하고 홍수 예경보 기준에 따른 평가를 수행할 수 있는 시스템을 개발하였다. 과거 강우사상을 홍수 예경보 시스템에 적용하여 홍수 모의 결과를 도출하였으며, 재해연보 등과 비교 분석하여 시스템의 적용성을 분석하였다.

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Predicting Determinants of Seoul-Bike Data Using Optimized Gradient-Boost (최적화된 Gradient-Boost를 사용한 서울 자전거 데이터의 결정 요인 예측)

  • Kim, Chayoung;Kim, Yoon
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.6
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    • pp.861-866
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    • 2022
  • Seoul introduced the shared bicycle system, "Seoul Public Bike" in 2015 to help reduce traffic volume and air pollution. Hence, to solve various problems according to the supply and demand of the shared bicycle system, "Seoul Public Bike," several studies are being conducted. Most of the research is a strategic "Bicycle Rearrangement" in regard to the imbalance between supply and demand. Moreover, most of these studies predict demand by grouping features such as weather or season. In previous studies, demand was predicted by time-series-analysis. However, recently, studies that predict demand using deep learning or machine learning are emerging. In this paper, we can show that demand prediction can be made a little better by discovering new features or ordering the importance of various features based on well-known feature-patterns. In this study, by ordering the selection of new features or the importance of the features, a better coefficient of determination can be obtained even if the well-known deep learning or machine learning or time-series-analysis is exploited as it is. Therefore, we could be a better one for demand prediction.

Communication Manager Design and Implementation of Individual Location Information for Social Learning in N-Screen (N-스크린 환경에서 소셜 러닝을 위한 개인 위치정보 지원 커뮤니케이션 매니저 설계 및 구현)

  • Kim, Kyung-Rog;Byeon, Jae-Hee;Moon, Nam-Mee
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.3
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    • pp.27-35
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    • 2011
  • Social network services are developed which is based on interaction and collaboration between users. This used to teaching-learning and integrate personal experience based on constructivism and social learning has developed into. In order to use which better to support the N-Screen communication model is needed. Communication model is to support the interaction between learner-instructor- the system. However, until now, There are a lot of web-based communications research. In this study, Social Learning Services environment to extended to N-Screen. For seamless service, Location information of individuals to use to learning activities. To support this, the communication manager is to design and implement. Communications manager for the N-Screen services draw students use cases and define the required functions. Based on this, Communication function is designed. In addition, Considering the characteristics of each device, personal location information to be reflected.

Development and Effect Verification of U-learning based Leveled Reading Education Support System (U-러닝 기반 수준별 독서교육지원 시스템 개발 및 효과검증)

  • Kim, Jeong-Rang;Ma, DaI-Sung;Cheon, Kyung-Rok;Choi, Hyun-Ho;Ko, Yoon-Mi
    • Journal of The Korean Association of Information Education
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    • v.13 no.1
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    • pp.41-49
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    • 2009
  • It's going to be ubiquitous environment which is able to use web pages independent of time and a place by recent development of mobile techniques. On this, we improved the leveled reading supporting system according to U-learning environment and make student to read on both Off-line and On-line through connecting to E-book service. So we developed the reading supporting system which can improve the interests in reading and reading skill and proved the effects. U-learning based leveled reading education support system could be helped develop the reading ability by raising the interest in the activities reading and after reading.

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Deep Learning Image Processing Technology for Vehicle Occupancy Detection (차량탑승인원 탐지를 위한 딥러닝 영상처리 기술 연구)

  • Jang, SungJin;Jang, JongWook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.8
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    • pp.1026-1031
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    • 2021
  • With the development of global automotive technology and the expansion of market size, demand for vehicles is increasing, which is leading to a decrease in the number of passengers on the road and an increase in the number of vehicles on the road. This causes traffic jams, and in order to solve these problems, the number of illegal vehicles continues to increase. Various technologies are being studied to crack down on these illegal activities. Previously developed systems use trigger equipment to recognize vehicles and photograph vehicles using infrared cameras to detect the number of passengers on board. In this paper, we propose a vehicle occupant detection system with deep learning model techniques without exploiting existing system-applied trigger equipment. The proposed technique proposes a system to detect vehicles by establishing triggers within images and to apply deep learning object recognition models to detect real-time boarding personnel.