• Title/Summary/Keyword: 기술적 학습

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A Corpus-based Analysis on Primary English Education Research for the Past 20 Years (초등영어교육 연구 논문의 변천: 코퍼스 기반 분석)

  • Choi, Wonkyung
    • The Journal of the Korea Contents Association
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    • v.19 no.2
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    • pp.11-21
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    • 2019
  • It has been about 20 years since the English subject was formally taught in public elementary schools in Korea. The present research aims to analyze the studies regarding 'primary English' implemented in Korea during the time period. I have investigated 6,467 theses or research papers in total that were published in Korea with the help of the corpus programs Utagger and WordSmith Tools. The results show that for the last 20 years the number of overall studies appears to have increased since the year 1997, although the recent trend seems to be in recession. The research scope ranges from 'teaching-learning interaction' to 'curriculum' and 'assessment', which have been steadily investigated for 20 years. Furthermore, researchers sometimes appear to have followed the English education policy by conducting particular investigations like 'immersion program' or 'native English speaking teachers' in a certain time period. Recently, researchers started to have interest in the cutting-edge ICT. In conclusion, the academic field of 'primary English' in Korea has grown in quantity, and the spectrum of research areas has been expanded for the past 20 years. It is hoped that the results of this research will help set a new direction for future research.

Solitary Work Detection of Heavy Equipment Using Computer Vision (컴퓨터비전을 활용한 건설현장 중장비의 단독작업 자동 인식 모델 개발)

  • Jeong, Insoo;Kim, Jinwoo;Chi, Seokho;Roh, Myungil;Biggs, Herbert
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.41 no.4
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    • pp.441-447
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    • 2021
  • Construction sites are complex and dangerous because heavy equipment and workers perform various operations simultaneously within limited working areas. Solitary works of heavy equipment in complex job sites can cause fatal accidents, and thus they should interact with spotters and obtain information about surrounding environments during operations. Recently, many computer vision technologies have been developed to automatically monitor construction equipment and detect their interactions with other resources. However, previous methods did not take into account the interactions between equipment and spotters, which is crucial for identifying solitary works of heavy equipment. To address the drawback, this research develops a computer vision-based solitary work detection model that considers interactive operations between heavy equipment and spotters. To validate the proposed model, the research team performed experiments using image data collected from actual construction sites. The results showed that the model was able to detect workers and equipment with 83.4 % accuracy, classify workers and spotters with 84.2 % accuracy, and analyze the equipment-to-spotter interactions with 95.1 % accuracy. The findings of this study can be used to automate manual operation monitoring of heavy equipment and reduce the time and costs required for on-site safety management.

A Study on the Classification of Unstructured Data through Morpheme Analysis

  • Kim, SungJin;Choi, NakJin;Lee, JunDong
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.4
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    • pp.105-112
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    • 2021
  • In the era of big data, interest in data is exploding. In particular, the development of the Internet and social media has led to the creation of new data, enabling the realization of the era of big data and artificial intelligence and opening a new chapter in convergence technology. Also, in the past, there are many demands for analysis of data that could not be handled by programs. In this paper, an analysis model was designed and verified for classification of unstructured data, which is often required in the era of big data. Data crawled DBPia's thesis summary, main words, and sub-keyword, and created a database using KoNLP's data dictionary, and tokenized words through morpheme analysis. In addition, nouns were extracted using KAIST's 9 part-of-speech classification system, TF-IDF values were generated, and an analysis dataset was created by combining training data and Y values. Finally, The adequacy of classification was measured by applying three analysis algorithms(random forest, SVM, decision tree) to the generated analysis dataset. The classification model technique proposed in this paper can be usefully used in various fields such as civil complaint classification analysis and text-related analysis in addition to thesis classification.

A Study on Model for Drivable Area Segmentation based on Deep Learning (딥러닝 기반의 주행가능 영역 추출 모델에 관한 연구)

  • Jeon, Hyo-jin;Cho, Soo-sun
    • Journal of Internet Computing and Services
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    • v.20 no.5
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    • pp.105-111
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    • 2019
  • Core technologies that lead the Fourth Industrial Revolution era, such as artificial intelligence, big data, and autonomous driving, are implemented and serviced through the rapid development of computing power and hyper-connected networks based on the Internet of Things. In this paper, we implement two different models for drivable area segmentation in various environment, and propose a better model by comparing the results. The models for drivable area segmentation are using DeepLab V3+ and Mask R-CNN, which have great performances in the field of image segmentation and are used in many studies in autonomous driving technology. For driving information in various environment, we use BDD dataset which provides driving videos and images in various weather conditions and day&night time. The result of two different models shows that Mask R-CNN has higher performance with 68.33% IoU than DeepLab V3+ with 48.97% IoU. In addition, the result of visual inspection of drivable area segmentation on driving image, the accuracy of Mask R-CNN is 83% and DeepLab V3+ is 69%. It indicates Mask R-CNN is more efficient than DeepLab V3+ in drivable area segmentation.

A Study on the Evaluation of Librarian's Competency Value (도서관 사서의 역량가치 평가 연구)

  • Cha, Sung-Jong;Kim, Jinmook;Park, Heejin
    • Journal of the Korean Society for Library and Information Science
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    • v.55 no.1
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    • pp.107-133
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    • 2021
  • This study was performed in order to provide suggestions on how to strengthen librarian competency by evaluating and analyzing the competency value of librarians as information professions. First, the study divided the common competency value of librarians as human capital of libraries into skills, knowledge, behavior and attitude, and analyzed each area of competency value for librarians of the A-library. As a result, the average of the 'librarian's behavior and attitude' area was the highest, followed by the 'librarian's skill' area and the 'librarian's knowledge' area. Second, in terms of 'librarian's skill', A-library librarians' competence values were high in the order of 'communication', 'leadership', 'technology' and in the terms of 'librarian's knowledge' ones were high in the order of 'law and policy', 'marketing', 'learning and growth' and 'finance and accounting'. In addition, in areas of 'librarian's behavior and attitude', the factors were high in the order of 'ethics and values', 'interpersonal relationships' and 'customer service'. Third, the analysis of whether the average difference exists depending on the characteristics of A-library librarians on their evaluation of the competency value shows that only the 'working period' factor in the total competency value and the two factors 'age' and 'working period' were statistically significant in the 'librarian's knowledge' area. Forth, as a result of a regression analysis to identify the characteristics of A-library librarians and their impact on competency value, only the 'final education' factor was statistically significant for the competency value of the 'librarian's skill' area. Fifth, in the survey on problems and desirable improvement measures in increasing the competency value of librarians, the proportion of presenting problems and improvement plan in systemic aspects such as the 'librarian qualification system' and 'librarian training system' was high.

An Analysis of the Users' Demands of Public Library Services in Busan (부산지역 공공도서관 서비스에 대한 이용자 수요 분석)

  • Jung, Youngmi;Lee, Eun-Ju
    • Journal of Korean Library and Information Science Society
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    • v.52 no.4
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    • pp.229-253
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    • 2021
  • The service strategy of the public library needs to be established based on the users who are the actual beneficiaries of the services, including the perspective of changes in the social environment. This study investigated and analyzed the users' perceptions of the library functions and services currently provided and the demand for future services, targeting public library users in the Busan area. The data were collected through a questionnaire, and the respondents were 733 public library users in Busan. The main result is that first, the role and function of the public library that Busan users consider most important was still in material collection and provision. Second, in the information service type, the demand for cultural/lifelong learning program service was the highest, and in the service program, the demand for new IT technology experience and education was the highest. Third, as a result of ISA analysis of information service type, material provision service and information literacy education service were types to be maintained, and reading related service was type to be managed intensively. Fourth, in the analysis of service demand by age, those aged 41 to 50 years old were the generation with the highest demand in all types except for the information literacy education service type, and the demand for information literacy education was the highest among the elderly generation over 61 years old. And the user group in the western part of Busan was higher than the user group in other regions in demand for almost all service types. The results of this study can be used as basic data when establishing strategies to optimize community public library services for users.

Development of a Building Safety Grade Calculation DNN Model based on Exterior Inspection Status Evaluation Data (건축물 안전등급 산출을 위한 외관 조사 상태 평가 데이터 기반 DNN 모델 구축)

  • Lee, Jae-Min;Kim, Sangyong;Kim, Seungho
    • Journal of the Korea Institute of Building Construction
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    • v.21 no.6
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    • pp.665-676
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    • 2021
  • As the number of deteriorated buildings increases, the importance of safety diagnosis and maintenance of buildings has been rising. Existing visual investigations and building safety diagnosis objectivity and reliability are poor due to their reliance on the subjective judgment of the examiner. Therefore, this study presented the limitations of the previously conducted appearance investigation and proposed 3D Point Cloud data to increase the accuracy of existing detailed inspection data. In addition, this study conducted a calculation of an objective building safety grade using a Deep-Neural Network(DNN) structure. The DNN structure is generated using the existing detailed inspection data and precise safety diagnosis data, and the safety grade is calculated after applying the state evaluation data obtained using a 3D Point Cloud model. This proposed process was applied to 10 deteriorated buildings through the case study, and achieved a time reduction of about 50% compared to a conventional manual safety diagnosis based on the same building area. Subsequently, in this study, the accuracy of the safety grade calculation process was verified by comparing the safety grade result value with the existing value, and a DNN with a high accuracy of about 90% was constructed. This is expected to improve economic feasibility in the future by increasing the reliability of calculated safety ratings of old buildings, saving money and time compared to existing technologies.

Cloud Detection from Sentinel-2 Images Using DeepLabV3+ and Swin Transformer Models (DeepLabV3+와 Swin Transformer 모델을 이용한 Sentinel-2 영상의 구름탐지)

  • Kang, Jonggu;Park, Ganghyun;Kim, Geunah;Youn, Youjeong;Choi, Soyeon;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.38 no.6_2
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    • pp.1743-1747
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    • 2022
  • Sentinel-2 can be used as proxy data for the Korean Compact Advanced Satellite 500-4 (CAS500-4), also known as Agriculture and Forestry Satellite, in terms of spectral wavelengths and spatial resolution. This letter examined cloud detection for later use in the CAS500-4 based on deep learning technologies. DeepLabV3+, a traditional Convolutional Neural Network (CNN) model, and Shifted Windows (Swin) Transformer, a state-of-the-art (SOTA) Transformer model, were compared using 22,728 images provided by Radiant Earth Foundation (REF). Swin Transformer showed a better performance with a precision of 0.886 and a recall of 0.875, which is a balanced result, unbiased between over- and under-estimation. Deep learning-based cloud detection is expected to be a future operational module for CAS500-4 through optimization for the Korean Peninsula.

A Study about Building a Community of Practice of Experts for Sharing and Using Research Data (연구데이터 공유 및 활용을 위한 전문가 실천공동체 구축에 관한 연구)

  • Na-eun, Han
    • Journal of the Korean Society for Library and Information Science
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    • v.56 no.4
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    • pp.181-203
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    • 2022
  • This study analyzed domestic and foreign literature and examined cases of foreign Community of Practice(CoP) of experts to find out what benefits researchers can gain from participating in their CoP, how the CoP was established, and how data is shared within the CoP. In addition, this study discussed on how to establish a CoP of experts in Korea for sharing and using research data. By participating in the CoP of experts, members can be provided with the opportunity to build an experts' network and have a chance to meet with various experts, to acquire and share their expertise and information, to receive help from other experts, to learn about their expertise, and to have opportunities for professional experiences. In addition, this study discussed 4 factors such as operation method and management system, memberships and number of members, activities, and management of data and repository for establishing a CoP of experts for sharing and using research data. This study provides a knowledge base for building a CoP of experts in Korea.

Study On the Development of Convenience Evaluation Tool for Mobile VR Device (모바일 VR 디바이스의 사용편의성 평가도구 개발에 관한 연구)

  • Seo, Ji-Young;Jang, Joong-Sik
    • Journal of the Korea Convergence Society
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    • v.12 no.11
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    • pp.221-228
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    • 2021
  • This study was conducted to improve the convenience of design of mobile VR devices use in a way binds smart phones. Research on traditional mobile VR devices is insufficient. So the first survey was conducted on users 100 to understand the current status and status of mobile VR devices. As a result, it was found that the satisfaction with the convenience of use was significantly lowered, and countermeasures were needed. Then, a second survey of 30 Heavy Users was conducted to find out specific usability and problems of mobile VR devices. Through this, problems, ease of use, and other opinions of mobile VR devices were found. The survey results were analyzed through the Descriptive Statistics Act, and it was found that improvement was urgent due to low satisfaction with wearing and network. In-depth interviews were conducted with the same respondents. As with the problems derived first, problems such as wearing satisfaction, excessive head weight for long-term use, and lack of content could be found. Based on the previous studies, the focus group interview consisting of 6 experts derived the ease of use evaluation element. It consists of elements that can satisfy the convenience of use of mobile VR devices for creation, wearing satisfaction, network, morphology, learning, and spatiality, and has a total of 26. Using this evaluation elements, it is intended to provide better ease of use to users who will use the mobile VR device.