• Title/Summary/Keyword: Learning management

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A Ship-Wake Joint Detection Using Sentinel-2 Imagery

  • Woojin, Jeon;Donghyun, Jin;Noh-hun, Seong;Daeseong, Jung;Suyoung, Sim;Jongho, Woo;Yugyeong, Byeon;Nayeon, Kim;Kyung-Soo, Han
    • Korean Journal of Remote Sensing
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    • v.39 no.1
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    • pp.77-86
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    • 2023
  • Ship detection is widely used in areas such as maritime security, maritime traffic, fisheries management, illegal fishing, and border control, and ship detection is important for rapid response and damage minimization as ship accident rates increase due to recent increases in international maritime traffic. Currently, according to a number of global and national regulations, ships must be equipped with automatic identification system (AIS), which provide information such as the location and speed of the ship periodically at regular intervals. However, most small vessels (less than 300 tons) are not obligated to install the transponder and may not be transmitted intentionally or accidentally. There is even a case of misuse of the ship'slocation information. Therefore, in this study, ship detection was performed using high-resolution optical satellite images that can periodically remotely detect a wide range and detectsmallships. However, optical images can cause false-alarm due to noise on the surface of the sea, such as waves, or factors indicating ship-like brightness, such as clouds and wakes. So, it is important to remove these factors to improve the accuracy of ship detection. In this study, false alarm wasreduced, and the accuracy ofship detection wasimproved by removing wake.As a ship detection method, ship detection was performed using machine learning-based random forest (RF), and convolutional neural network (CNN) techniquesthat have been widely used in object detection fieldsrecently, and ship detection results by the model were compared and analyzed. In addition, in this study, the results of RF and CNN were combined to improve the phenomenon of ship disconnection and the phenomenon of small detection. The ship detection results of thisstudy are significant in that they improved the limitations of each model while maintaining accuracy. In addition, if satellite images with improved spatial resolution are utilized in the future, it is expected that ship and wake simultaneous detection with higher accuracy will be performed.

Prospect of future water resources in the basins of Chungju Dam and Soyang-gang Dam using a physics-based distributed hydrological model and a deep-learning-based LSTM model (물리기반 분포형 수문 모형과 딥러닝 기반 LSTM 모형을 활용한 충주댐 및 소양강댐 유역의 미래 수자원 전망)

  • Kim, Yongchan;Kim, Youngran;Hwang, Seonghwan;Kim, Dongkyun
    • Journal of Korea Water Resources Association
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    • v.55 no.12
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    • pp.1115-1124
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    • 2022
  • The impact of climate change on water resources was evaluated for Chungju Dam and Soyang-gang Dam basins by constructing an integrated modeling framework consisting of a dam inflow prediction model based on the Variable Infiltration Capacity (VIC) model, a distributed hydrologic model, and an LSTM based dam outflow prediction model. Considering the uncertainty of future climate data, four models of CMIP6 GCM were used as input data of VIC model for future period (2021-2100). As a result of applying future climate data, the average inflow for period increased as the future progressed, and the inflow in the far future (2070-2100) increased by up to 22% compared to that of the observation period (1986-2020). The minimum value of dam discharge lasting 4~50 days was significantly lower than the observed value. This indicates that droughts may occur over a longer period than observed in the past, meaning that citizens of Seoul metropolitan areas may experience severe water shortages due to future droughts. In addition, compared to the near and middle futures, the change in water storage has occurred rapidly in the far future, suggesting that the difficulties of water resource management may increase.

A Study on the Gap Analysis of Public Libraries in Gyeongbuk Region (경북지역 공공도서관 격차분석 연구)

  • Yoon, Hee-Yoon
    • Journal of the Korean Society for Library and Information Science
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    • v.56 no.1
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    • pp.5-25
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    • 2022
  • In most countries, public libraries are knowledge information centers, complex cultural spaces, lifelong learning facilities, and third places for local residents. The social homage spoken on the premise of this identity and socio-cultural role is the knowledge and information agora, cultural infrastructure, living room in the city, and the university of the people. However, if there is a significant gap between public libraries regardless of country or region, it will inevitably lead to information gaps, regional gaps, and cultural inequality and cultural welfare gaps among local residents. This study is regarded as the essence of regional cultural facilities and premised that the regional gap in public libraries is a factor of regional cultural gaps. Based on this premise, the gap between the location quotient, input indicators, and output indicators of public libraries of regional governments in Korea and basic local governments in the Gyeongbuk region was analyzed. And this study derived core elements through correlation and regression analysis of input and output indicators of all public libraries nationwide, developed a management model for each indicator, and suggested a plan to resolve the relative gap for public libraries by city and county in Gyeongbuk.

The Study on Needs of Health college students on Extracurricular Programs (보건계열 대학생의 비교과 교육프로그램 요구도 조사)

  • Kim, Hee-Kyoung;Kim, Myung-Eun
    • Journal of Industrial Convergence
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    • v.20 no.5
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    • pp.125-134
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    • 2022
  • This study was conducted to improve the direction of extracurriculular education for health students and to establish and systematic extracurricular education and operation system. The needs and priorities of extracurricular education programs were investigated through a survey of health students. The data were analyzed by Borich's needs and The Locus for Focus Model. As a result of priorities of extracurriculular programs according to Borich's needs, the top 10 programs included 'certification', 'career exploration', 'overseas service', 'second language', 'employment education', 'talent donation', 'English', 'computer utilization', and 'major convergence learning'. As a result of priorities by applying The Locus for Focus Model, 'certification', 'career exploration', 'employment education', 'foreign service', 'English', 'domestic service', 'second foreign language', 'talent donation', and 'computer utilization' was included. A total of nine programs were derived by combining Borich and The Locus for Focus Model, and priorities were 'certification', 'career exploration', 'overseas service', 'second foreign language', 'employment education', 'talent donation', 'English', 'computer utilization', and 'domestic service'. As a result of this study, health students had a high needs for comparison programs for employment and volunteer programs, so universities should reflect this and establish a comparison program operation system for health students.

Trustworthy AI Framework for Malware Response (악성코드 대응을 위한 신뢰할 수 있는 AI 프레임워크)

  • Shin, Kyounga;Lee, Yunho;Bae, ByeongJu;Lee, Soohang;Hong, Heeju;Choi, Youngjin;Lee, Sangjin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.5
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    • pp.1019-1034
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    • 2022
  • Malware attacks become more prevalent in the hyper-connected society of the 4th industrial revolution. To respond to such malware, automation of malware detection using artificial intelligence technology is attracting attention as a new alternative. However, using artificial intelligence without collateral for its reliability poses greater risks and side effects. The EU and the United States are seeking ways to secure the reliability of artificial intelligence, and the government announced a reliable strategy for realizing artificial intelligence in 2021. The government's AI reliability has five attributes: Safety, Explainability, Transparency, Robustness and Fairness. We develop four elements of safety, explainable, transparent, and fairness, excluding robustness in the malware detection model. In particular, we demonstrated stable generalization performance, which is model accuracy, through the verification of external agencies, and developed focusing on explainability including transparency. The artificial intelligence model, of which learning is determined by changing data, requires life cycle management. As a result, demand for the MLops framework is increasing, which integrates data, model development, and service operations. EXE-executable malware and documented malware response services become data collector as well as service operation at the same time, and connect with data pipelines which obtain information for labeling and purification through external APIs. We have facilitated other security service associations or infrastructure scaling using cloud SaaS and standard APIs.

Study on Water Quality Predictability through Machine Learning Techniques in Non-point Pollutant Management Area (비점오염원관리지역의 머신러닝 기법을 통한 수질 예측 가능성 연구)

  • Yeong Na Yu;Min Hwan Shin;Dong Hyuk Kum;Kyoung Jae Lim;Jong Gun Kim
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.467-467
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    • 2023
  • 강우에 의해 발생하는 비점오염물질의 수질 데이터가 충분하지 않아 비점오염원이 문제가 되고 있는 유역의 수질개선을 위한 대책마련이 어려운 실정이다. 기존에 환경부에서 운영하고 있는 자동측정망은 1시간 간격으로 데이터를 축적하고 있으나, 비점오염원이 문제가 되는 유역에 설치되어 있지 않거나 수온, DO, pH 등 현장항목만을 측정하고 있어 하천의 수질오염을 대표할 수 있는 T-P나 SS 등의 수질분석 항목의 부재하다. 이로인해 유역의 수질개선 대책을 수립하기 위한 오염원의 현황을 파악하기 어려운 실정이다. 따라서, 본 연구에서는 비점오염원관리지역 중 골지천 유역을 대상으로 수질항목별 상관성을 분석하고, 실측자료를 기반으로 DT, MLP, SVM, RF, GB, XGB 등의 머신러닝 기법을 통해 수질 예측 가능성을 연구하였다. 상관관계 분석결과 입력변수인 탁도 항목이 예측 수질과 뚜렷한 상관관계를 보이는 것으로 나타났으나, 그 외 항목에서는 약한 상관관계를 보이거나 상관관계가 없는 것으로 나타났다. 머신러닝 기법을 활용한 수질 예측 분석 결과, 검무교와 태봉2교, 제1여량교는 RF 기법에서 결정계수(R2) 0.57~0.86, RMSE 16.49~175.60으로 예측성이 우수한 것으로 나타났다. 관말교는 SVM 기법에서 R2 0.65, RMSE 57.69로, 송계교는 XGB 기법에서 R2 0.74, RMSE 282.86으로 가장 예측성이 우수한 것으로 나타났다. 분석결과와 같이 머신러닝 기법을 활용한 수질 예측은 가능하나, 예측성이 우수한 머신러닝 기법의 R2 비교 결과, 유역면적이 큰 제1여량교와 작은 관말교에서 0.57과 0.65로 다른 지점에 비해 낮은 것으로 나타났다. RMSE 비교 결과, 상류 산간지역에 발생한 국지성 호우의 영향으로 흙탕물이 가장 자주 발생하는 태봉2교 지점과 우선관리지역이 합류되는 송계교 지점에서 175.60과 282.86으로 예측값과 실측값의 오차가 큰 것으로 나타났다. 연구결과와 같이 하천 수질을 예측하기 위해서는 유역면적 혹은 유역특성과 관련한 기초자료를 추가로 적용하여 머신러닝 기법을 적용 해야할 것으로 판단된다. 또한, 본 연구에서 예측한 수질 항목 이외에 입력변수를 추가로 확보하여 수질의 예측 가능성을 검토해야 할 것으로 보여진다.

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Development and Application of Tunnel Design Automation Technology Using 3D Spatial Information : BIM-Based Design for Namhae Seomyeon - Yeosu Shindeok National Highway Construction (3D 공간정보를 활용한 터널 설계 자동화 기술 개발 및 적용 사례 : 남해 서면-여수 신덕 국도 건설공사 BIM기반 설계를 중심으로)

  • Eunji Jo;Woojin Kim;Kwangyeom Kim;Jaeho Jung;Sanghyuk Bang
    • Tunnel and Underground Space
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    • v.33 no.4
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    • pp.209-227
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    • 2023
  • The government continues to announce measures to revitalize smart construction technology based on BIM for productivity innovation in the construction industry. In the design phase, the goal is design automation and optimization by converging BIM Data and other advanced technologies. Accordingly, in the basic design of the Namhae Seomyeon-Yeosu Sindeok National Road Construction Project, a domestic undersea tunnel project, BIM-based design was carried out by developing tunnel design automation technology using 3D spatial information according to the tunnel design process. In order to derive the optimal alignment, more than 10,000 alignment cases were generated in 36hr using the generative design technique and a quantitative evaluation of the objective functions defined by the designer was performed. AI-based ground classification and 3D Geo Model were established to evaluate the economic feasibility and stability of the optimal alignment. AI-based ground classification has improved its precision by performing about 30 types of ground classification per borehole, and in the case of the 3D Geo Model, its utilization can be expected in that it can accumulate ground data added during construction. In the case of 3D blasting design, the optimal charge weight was derived in 5 minutes by reviewing all security objects on the project range on Dynamo, and the design result was visualized in 3D space for intuitive and convenient construction management so that it could be used directly during construction.

Pedagogical Characteristics Supporting Gifted Science Students' Agentic Participation in the Scientist-led Research and Education (R&E) Program: Focusing on the Positioning of Instructors and Students (전문가 사사 R&E에서 과학영재의 행위주체적 연구 참여를 지원하는 교수적 특성 -교수자와 학생의 위치짓기를 중심으로-)

  • Minjoo Lee;Heesoo Ha
    • Journal of The Korean Association For Science Education
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    • v.43 no.4
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    • pp.351-368
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    • 2023
  • The scientist-led Research and Education (R&E) program aims to strengthen gifted science students' research capabilities under the guidance of scientists. Students' actual research experiences in scientist-led R&E activities range from understanding how scientists conduct research to actively participating in research. To develop R&E that promotes student agency, i.e., student participation, this study aimed to identify the pedagogical characteristics that supported gifted science students' agentic participation in the scientist-led R&E program. We conducted interviews with learners and scientists in three teams undertaking R&E activities every three months. The interview covered their perceptions of R&E activities, student participation, and scientists' support for the activities. The recordings and transcripts of the interviews were used as primary data sources for the analysis. The trajectory of each team's activities, as well as the learners' and scientists' dynamic positioning were identified. Based on this analysis, we inductively identified the pedagogical characteristics that emerged from classes in which the scientists supported the students' learning and engagement in research. Regarding agency, three types of student participation were identified: 1) the sustained exercise of agency, 2) the initial exercise and subsequent discouragement of agency, and 3) the continuous non-exercise of agency. Two pedagogical characteristics that supported the learners' agentic participation were identified: 1) opportunities for students to take part in research management and 2) scientist-student interactions encouraging learners to present expert-level ideas. This study contributes to developing pedagogies that foster gifted science students' agentic participation in scientist-led R&E activities.

Analysis of Eco-Citizenship Contents Elements in Home Economics Textbooks for the Introduction of Ecological Transformation Education (생태전환교육 도입을 위한 가정과 교과서의 생태시민성 내용 요소 분석)

  • Cho, Sung Mi;Park, Mi Jeong
    • Journal of Korean Home Economics Education Association
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    • v.35 no.2
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    • pp.1-20
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    • 2023
  • The purpose of this study is to extract and analyze ecological citizenship elements in the middle school home economics textbook used in the 2015 national curriculum for the introduction of ecological transformation education in the 2022 national curriculum. As a result of the analysis, the content analysis of the ecological citizenship factor was validated by six experts who are incumbent middle school home economics teachers, and the S-CVI value was 0.97, ensuring the validity of the ecological citizenship factor analysis. The results of analyzing 242 ecological citizenship factors extracted from home economics textbooks are as follows. According to the content area of the 2015 national home economics curriculum, the 'human development and family' area had the highest presence of ecological citizenship factors followed by the 'resource management and self-reliance' area and the 'home life and safety' area. Among the categories of ecological citizenship factors, 'value⋅attitude' was the most frequent, followed by 'process⋅function' and 'knowledge⋅understanding'. For each textbook composition system, ecological citizenship elements were extracted in the order of pictures, text, activities, and supplementary materials. There was a significant variation in the number of ecological citizenship factors among publishers, indicating the importance of the textbook writers' perception, interpretation, and direction of writing. Based on these analysis results, ecological citizenship teaching and learning activities applicable to home economics education were presented. This study highlights the potential for practicing ecological citizenship education in line with the new orientation of the curriculum on ecological transformation education through home economics education. Furthermore, it provides valuable baseline data for the development and implementation of textbooks for the 2022 national curriculum.

Developing an Occupants Count Methodology in Buildings Using Virtual Lines of Interest in a Multi-Camera Network (다중 카메라 네트워크 가상의 관심선(Line of Interest)을 활용한 건물 내 재실자 인원 계수 방법론 개발)

  • Chun, Hwikyung;Park, Chanhyuk;Chi, Seokho;Roh, Myungil;Susilawati, Connie
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.5
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    • pp.667-674
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    • 2023
  • In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.