• Title/Summary/Keyword: Learning Media

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Analyzing the Trends of Culture Technology using National Research Projects (문화기술(CT) 연구 동향 분석: 국가연구과제를 중심으로)

  • Lee, Beom-Hun;Jeon, Woojin;Geum, Youngjung
    • The Journal of the Korea Contents Association
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    • v.21 no.11
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    • pp.64-76
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    • 2021
  • Culture technology (CT) becomes important in the recent environment where digital technology drives content-based innovations. However, technological trends of CT have not been systematically discussed. Especially, the trends of CT should be analyzed from the national perspective, because CT has grown with the help of government-driven innovation. Therefore, this paper aims to analyze CT trends focusing on national research projects. We collected data on CT from the national science and technology information service (NTIS) database, analyzed the keyword co-occurrence network, and identified the patterns of technological innovation using a clustering analysis. As a result, we found that CT has contributed to the digital content and cultural media, and has been actively developed with the help of machine learning technique. Especially, due to the rise of Covid-19, the non-face-to-face online content is rapidly increasing. This study provides important clues for understanding, analyzing CT trends.

Introduction and Utilization of Time Series Data Integration Framework with Different Characteristics (서로 다른 특성의 시계열 데이터 통합 프레임워크 제안 및 활용)

  • Jisoo, Hwanga;Jaewon, Moon
    • Journal of Broadcast Engineering
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    • v.27 no.6
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    • pp.872-884
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    • 2022
  • With the development of the IoT industry, different types of time series data are being generated in various industries, and it is evolving into research that reproduces and utilizes it through re-integration. In addition, due to data processing speed and issues of the utilization system in the actual industry, there is a growing tendency to compress the size of data when using time series data and integrate it. However, since the guidelines for integrating time series data are not clear and each characteristic such as data description time interval and time section is different, it is difficult to use it after batch integration. In this paper, two integration methods are proposed based on the integration criteria setting method and the problems that arise during integration of time series data. Based on this, integration framework of a heterogeneous time series data was constructed that is considered the characteristics of time series data, and it was confirmed that different heterogeneous time series data compressed can be used for integration and various machine learning.

Efficient Memory Update Module for Video Object Segmentation (동영상 물체 분할을 위한 효율적인 메모리 업데이트 모듈)

  • Jo, Junho;Cho, Nam Ik
    • Journal of Broadcast Engineering
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    • v.27 no.4
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    • pp.561-568
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    • 2022
  • Most deep learning-based video object segmentation methods perform the segmentation with past prediction information stored in external memory. In general, the more past information is stored in the memory, the better results can be obtained by accumulating evidence for various changes in the objects of interest. However, all information cannot be stored in the memory due to hardware limitations, resulting in performance degradation. In this paper, we propose a method of storing new information in the external memory without additional memory allocation. Specifically, after calculating the attention score between the existing memory and the information to be newly stored, new information is added to the corresponding memory according to each score. In this way, the method works robustly because the attention mechanism reflects the object changes well without using additional memory. In addition, the update rate is adaptively determined according to the accumulated number of matches in the memory so that the frequently updated samples store more information to maintain reliable information.

Performance Enhancement of Speech Declipping using Clipping Detector (클리핑 감지기를 이용한 음성 신호 클리핑 제거의 성능 향상)

  • Eunmi Seo;Jeongchan Yu;Yujin Lim;Hochong Park
    • Journal of Broadcast Engineering
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    • v.28 no.1
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    • pp.132-140
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    • 2023
  • In this paper, we propose a method for performance enhancement of speech declipping using clipping detector. Clipping occurs when the input speech level exceeds the dynamic range of microphone, and it significantly degrades the speech quality. Recently, many methods for high-performance speech declipping based on machine learning have been developed. However, they often deteriorate the speech signal because of degradation in signal reconstruction process when the degree of clipping is not high. To solve this problem, we propose a new approach that combines the declipping network and clipping detector, which enables a selective declipping operation depending on the clipping level and provides high-quality speech in all clipping levels. We measured the declipping performance using various metrics and confirmed that the proposed method improves the average performance over all clipping levels, compared with the conventional methods, and greatly improves the performance when the clipping distortion is small.

Block-based Learned Image Compression for Phase Holograms (신경망 기반 블록 단위 위상 홀로그램 이미지 압축)

  • Seung Mi Choi;Su yong Bahk;Hyun Min Ban;Jun Yeong Cha;Hui Yong Kim
    • Journal of Broadcast Engineering
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    • v.28 no.1
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    • pp.42-54
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    • 2023
  • It is an important issue to compress huge holographic data in a digital format. In particular, research on the compression of phase-only holograms for commercialization is noteworthy. Conventional video coding standards optimized for natural images are not suitable for compressing phase signals, and neural network-based compression model that can be optimized for phase signals can achieve high performance, but has a memory issue in learning high-resolution holographic data. In this paper, we show that by applying a block-based learned image compression model that can solve memory problems to phase-only holograms, the proposed method can demonstrate significant performance improvement over standard codecs even under the same conditions as block-based. Block-based learned compression model can provide compatibility with conventional standard codecs, solve memory problems, and can perform significantly better against phase-only hologram compression.

Research on Overseas Trends and Emerging Topics in Field of Library and Information Science (문헌정보학분야 해외 연구 동향 및 유망 주제 분석 연구)

  • Bon Jin Koo;Durk Hyun Chang
    • Journal of the Korean Society for Library and Information Science
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    • v.57 no.3
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    • pp.71-96
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    • 2023
  • This study aimed to investigate key research areas in the field of Library and Information Science (LIS) by analyzing trends and identifying emerging topics. To facilitate the research, a collection of 40,897 author keywords from 11,252 papers published in the past 30 years (1993-2022) in five journals was gathered. In addition, keyword analysis, as well as Principal Component Analysis (PCA) and correlation analysis were conducted, utilizing variables such as the number of articles, number of authors, ratio of co-authored papers, and cited counts. The findings of the study suggest that two topics are likely to develop as promising research areas in LIS in the future: machine learning/algorithm and research impact. Furthermore, it is anticipated that future research will focus on topics such as social media and big data, natural language processing, research trends, and research assessment, as they are expected to emerge as prominent areas of study.

Privacy-preserving Proptech using Domain Adaptation in Metaverse (메타버스 내 원격 부동산 중계 시스템을 위한 부동산 매물 영상 내 민감정보 삭제 기술)

  • Junho Kim;Jinhong Kim;Byeongjun Kang;Jaewon Choi;Jihoon Kim;Dongwoo Kang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.11a
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    • pp.187-190
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    • 2022
  • 본 논문은 메타버스 등 인공지능 연계 증강/가상현실 부동 중계 플랫폼에서 부동산 영상 기반 매물 소개 시스템 구축에서 사생활 및 개인정보가 영상에 담기게 될 수 있는 위험이 존재하기에 부동산 영상 내의 개인정보 및 민감 정보를 인공지능 기술을 기반으로 검출하여 삭제해주고 복원해주는 인공지능 기술 연구개발을 목표로 하였다. 한국형 부동산 내 민감 object 를 정의하고, 최신 인공지능 딥러닝 기술 기반 민감 object detection 알고리즘을 연구 개발하며, 영상에서 삭제된 부분은 인공지능 기술을 기반으로 물체가 없는 실제 공간영상으로 복원해주는 영상복원 기술도 연구 개발하였다. 한국형 부동산 환경 (영상 촬영 조도, 디스플레이 스타일, 주변 가구 배치 등)에 맞는 인공지능 모델 구축을 위하여, 자체적으로 한국 영상 database 구축 및 Transfer learning for target domain adaptation 을 진행하였다. 제안된 알고리즘은 일반적인 환경에서 98%의 정확도와 challenge 환경에서 (occlusion 빛 반사, 저조도 등) 81%의 정확도를 보였다. 본 기술은 Proptech 분야에서 주목받고 있는 메타버스 기반 온라인 중계 서비스 기술을 활성화하기 위하여 기획되었으며, 특히 메타버스 부동산 중계 플랫폼의 활성화를 위하여 사생활 보호 측면에서 필요한 중요 기술을 인공지능 기술을 활용하여 연구 개발하였다.

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Development of Story Recommendation through Character Web Drama Cliché Analysis (캐릭터 웹드라마 클리셰 분석을 통한 스토리 추천 개발)

  • Hyun-Su Lee;Jung-Yi Kim
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.4
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    • pp.17-22
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    • 2023
  • This study analyzed the genres of popular character web dramas and studied the development of story recommendations through the language model GPT. As a result of the study, it was confirmed that similar cliches are repeated in web dramas. In this study, a common story structure (cliché) was analyzed and a typical story structure was standardized and presented so that even unskilled video producers can easily produce character web dramas. For analysis, clichés of web dramas in the school romance genre, which is the most popular genre among teenagers, were listed in order of success. In addition, this study studied the story recommendation mechanism for users by learning the clichés that were analyzed and cataloged in GPT. Through this study, it is expected to accelerate the production of various contents as well as popular popularity through the acceptance of various databases from the standpoint of database consumption theory of web contents.

A Study on Elementary School Teachers' Needs for Access Points for Picture Books (초등학교 교사의 그림책 접근점 요구에 관한 연구)

  • Kim, Hyemi;Kim, Soojung
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.33 no.1
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    • pp.233-258
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    • 2022
  • The purpose of this study is to identify elementary school teachers' needs for access points when searching for picture books to be used as teaching media, and suggest ways to improve DLS(Digital Library System) in school libraries. To achieve this purpose, the study examined the access points provided by OPAC(Online Public Access Catalog) systems in seven domestic and foreign libraries. In addition, it conducted an online survey with elementary school teachers, and a total of 220 responses were finally analyzed. It was found that the most needed access points were topic, grade/age, content, subject/chapter, and cross-curricula learning topics, etc. Based on the results, this study suggests providing the most needed access points in DLS, developing controlled vocabulary tools, and improving system functions or the interface to enhance accessibility to picture books.

A Proposal for the Development of Online Graduate School for Lifelong Education (평생교육을 위한 온라인 대학원 발전방안 제안)

  • Kwon, Arum;Kim, Seung-In
    • Journal of Digital Convergence
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    • v.20 no.3
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    • pp.415-422
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    • 2022
  • This study requires a new paradigm for universities in line with the global pandemic and the 4th industrial revolution. Accordingly, we propose an educational plan for the H university online graduate school in Korea. As a research method, the implications of scholars and experts on future education were synthesized, and the cases of overseas universities using it were analyzed to propose an online graduate school education plan. As a result of the study, online graduate school needs diversity as a venue for providing new opportunities as lifelong education, and to realize this, they use a microcredit. Blockchain technology is introduced so that microcredit can be transparently verified. In addition, to correspond to various convergence major programs and further develop them, problem-solving-oriented teaching methods enhance students' convergent skills as well as active learning and interaction. More detailed curriculum research at online graduate schools is needed in the future, and we hope that you will contribute to the development of online graduate school education based on this study.