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A Study on the Document viewer optimized for VR environment (VR 환경에 최적화 된 문서 뷰어에 관한 연구)

  • Joo, Yong-Ho;Kim, Sang-Mok;Cho, Ok-Hue
    • Journal of the Korea Convergence Society
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    • v.12 no.5
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    • pp.139-145
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    • 2021
  • Through this study, we intend to study user satisfaction in order to verify whether there is a need for full-scale research, development and commercialization of document viewers in a VR environment. VR content consists of realistic 3D graphics and 360-degree video, and provides a synesthesia experience and immersion. We developed and tested a VR document viewer prototype that can utilize this concept as a document viewing system. It can act as a viewer that provides an interactive viewing environment according to the user's body interaction and the direction of the field of view, and it can be said that the feature of VR document viewer is that it can draw the user's high level of immersion and concentration when using the viewer. The developed prototype was tested in a test group consisting of 100 VR experiences and device owners for about 1 hour and 3 days a day, and then a questionnaire survey in the form of a fixed selection question was conducted. This study is a prototype study of a document viewer suitable for a virtual reality environment, and can lead to a sense of immersion when reading a document, and suggest a new document viewer direction that is effective for visual fatigue and visual perception of the document.

A Study on Geospatial Information Role in Digital Twin (디지털트윈에서 공간정보 역할에 관한 연구)

  • Lee, In-Su
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.3
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    • pp.268-278
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    • 2021
  • Technologies that are leading the fourth industrial revolution, such as the Internet of Things (IoT), big data, artificial intelligence (AI), and cyber-physical systems (CPS) are developing and generalizing. The demand to improve productivity, economy, safety, etc., is spreading in various industrial fields by applying these technologies. Digital twins are attracting attention as an important technology trend to meet demands and is one of the top 10 tasks of the Korean version of the New Deal. In this study, papers, magazines, reports, and other literature were searched using Google. In order to investigate the contribution or role of geospatial information in the digital twin application, the definition of a digital twin, we investigated technology trends of domestic and foreign companies; the components of digital twins required in manufacturing, plants, and smart cities; and the core techniques for driving a digital twin. In addition, the contributing contents of geospatial information were summarized by searching for a sentence or word linked between geospatial-related keywords (i.e., Geospatial Information, Geospatial data, Location, Map, and Geodata and Digital Twin). As a result of the survey, Geospatial information is not only providing a role as a medium connecting objects, things, people, processes, data, and products, but also providing reliable decision-making support, linkage fusion, location information provision, and frameworks. It was found that it can contribute to maximizing the value of utilization of digital twins.

Analysis System of School Life Records Based on Data Mining for College Entrance (데이터 마이닝 기반 대학입시를 위한 학교생활기록부 분석시스템)

  • Yang, Jinwoo;Kim, Donghyun;Lim, Jongtae;Yoo, Jaesoo
    • The Journal of the Korea Contents Association
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    • v.21 no.2
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    • pp.49-58
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    • 2021
  • The Korean curriculum and admission system have evolved through numerous changes. Currently, the nation's college entrance rate stands at nearly 70 percent, and it is the highest among OECD members. Amid this environment, the importance of school life records is increasing among students who are interested in going to college and who have the highest percentage in the nation's education system. Happiness is not the order of grades, but I can find my future and happiness at the same time through active school life. Through the analysis system of school life records, you can find interests and career paths suitable for yourself, and analyze and supplement factors suitable for the university and department you want to go to, so that you can take a step further in successful advancement. Each item in the school records is divided into three categories to analyze the necessary and unnecessary words. By visualizing and numericalizing the analyzed data, an analysis system is established that can be supplemented in school life. An analysis system through data mining can be utilized by concisely summarizing sentences of different elements and extracting words by applying the multi-topic minutes summary system using word frequency and similarity analysis as an existing prior study.

Research Trends on Emotional Labor in Korea using text mining (텍스트마이닝을 활용한 감정노동 연구 동향 분석)

  • Cho, Kyoung-Won;Han, Na-Young
    • Journal of Korea Society of Industrial Information Systems
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    • v.26 no.6
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    • pp.119-133
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    • 2021
  • Research has been conducted in many fields to identify research trends using text mining, but in the field of emotional labor, no research has been conducted using text mining to identify research trends. This study uses text mining to deeply analyze 1,465 papers at the Korea Citation Index (KCI) from 2004 to 2019 containing the subject word 'emotional labor' to understand the trend of emotional labor researches. Topics were extracted by LDA analysis, and IDM analysis was performed to confirm the proportion and similarity of the topics. Through these methods, an integrated analysis of topics was conducted considering the usefulness of topics with high similarity. The research topics are divided into 11 categories in descending order: stress of emotional labor (12.2%), emotional labor and social support (12.0%), customer service workers' emotional labor (10.9%), emotional labor and resilience (10.2%), emotional labor strategy (9.2%), call center counselor's emotional labor (9.1%), results of emotional labor (9.0%), emotional labor and job exhaustion (7.9%), emotional intelligence (7.1%), preliminary care service workers' emotional labor (6.6%), emotional labor and organizational culture (5.9%). Through topic modeling and trend analysis, the research trend of emotional labor and the academic progress are analyzed to present the direction of emotional labor research, and it is expected that a practical strategy for emotional labor can be established.

The Effectiveness of the Living Lab-based Elementary School Data Science Program (리빙랩 기반 초등학교 데이터 과학 프로그램의 효과성 분석)

  • Son, Jungmyoung;Kim, Taeyoung
    • Journal of The Korean Association of Information Education
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    • v.26 no.2
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    • pp.105-120
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    • 2022
  • In addition to the rapid changes in the times caused by the pandemic, the revision of the new curriculum coincides with the change in the proportion of the three elements of learners, society, and subjects that make up the curriculum. In particular, along with the proportion of 'social' in the curriculum, the scope of the word 'educational community' has increased, and the allowable range of curriculum restructuring centered on it has expanded. In order for the intended direction of education to be properly established in the new curriculum, various educational method studies are needed to cultivate newly emerged competencies and literacy. In this study, after selecting the contents and goals of the convergence curriculum based on various criteria for subject selection, the data science program was designed by reconstructing Living Lab's PDIE methodology. As an evaluation factor for this, we tried to analyze the effectiveness of 'creativity', 'problem-solving ability', 'communication ability', 'collaboration ability' among future competencies emphasized in the curriculum. As a result of the study, it was effective in improving creative and communication skills, and this study focuses on verifying the effectiveness of School Living Lab, suggesting the necessity of post-research that expands the application space of research and diversifies the role of educational community subjects.

Using Service Design Tools in Community Nutrition Research: A Case Study in Developing Dietary Guidelines for Young Adults (서비스 디자인 도구의 지역사회영양학 분야 활용: 청년 식생활 가이드 개발 사례)

  • Jo, Eunbin;Shim, Jae Eun;Ryou, Hyun Joo;Kim, Kirang;Song, Su Jin;Kim, Hyun Ja;Ahn, Jeong Sun;Kwon, Kwang-il;Lee, Hye Young;Park, Sohyun
    • Korean Journal of Community Nutrition
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    • v.27 no.3
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    • pp.177-191
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    • 2022
  • Objectives: Recent epidemiological data reported that young adults in their 20 ~ 30s are a vulnerable population with unhealthy dietary practices and a few signs of deteriorated health indicators. However, there are no dietary guidelines that are specifically developed for the young adult population. This study introduces some data collection tools that are mostly used in the service design field, and demonstrates how these tools can be used in nutrition research for developing dietary guidelines for specific target groups. Methods: To understand the context of food choices among young people, 39 people were enrolled to complete a probes booklet. Thematic analysis and word cloud were performed to capture the main themes from the probes and a persona was developed based on the findings. Results: Data from the probes enabled us to grasp the various contextual meanings of eating practices among young people. Most participants understand what a healthy diet is and often have a willingness to practice it. However, there were very few participants who were following the practices. We created four types of persona for developing dietary guidelines: healthy eating, emotional eating, convenient eating, and trendy eating. Conclusions: Probes and persona were used in order to understand the lives of young adults and develop targeted messages. We hope that this introduction will be helpful to researchers who are looking for new ways of understanding their target population in the field of community nutrition.

Investigation of the listening environment for lower grade students in elementary school using subjective tests (주관적 평가법을 이용한 초등학교 저학년 교실의 청취환경 조사)

  • Park, Chan-Jae;Haan, Chan-Hoon
    • The Journal of the Acoustical Society of Korea
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    • v.40 no.3
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    • pp.201-212
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    • 2021
  • The present study was conducted as a pilot investigation to suggest the standards of acoustic performance for classrooms suitable for incomplete hearing people such as children under 9 years of age. Subjective evaluations such as questionnaire and speech intelligibility test were conducted to 264 students at two elementary schools in Cheong-ju in order to analyze the characteristics of the listening environment in the classrooms of the lower grades in elementary school. The survey was undertaken with a total of 264 students at two elementary schools in Cheong-ju, and investigated their satisfaction with the classroom listening environment. As a result, students responded that the most helpful information type for understanding class content is the voice of teacher. In addition, the volume of the current teacher's voice is normal, and the level of clarity is highly satisfactory. As for the acoustic performance of the classroom, the opinion that the noise was normal and the reverberation was very short was found to be dominant in overall satisfaction with the listening environment. Meanwhile, as a result of speech intelligibility test using the word list selected for the lower grade students of elementary school, it could be inferred that the longitudinal axis distance from the sound source in the case of 8-year-olds is a factor that affects speech recognition.

Analysis of Research Trends in Elder Abuse Using Text Mining : Academic Papers from 2004 to 2021. (텍스트 마이닝 분석을 통한 노인학대 관련 연구 동향 분석 : 2004년~2021년까지 발행된 국내 학술논문을 중심으로)

  • Youn, Ki-Hyok
    • Journal of Internet of Things and Convergence
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    • v.8 no.4
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    • pp.25-40
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    • 2022
  • This study aimed to understand the increasing number of elder abuses in South Korea, where entry into the super-aged society is imminent, by implementing text mining analysis. Korean Academic journals were obtained from 2004, the establishment year of the senior care agency, to 2021. We performed natural language processing of the titles, keywords, and abstracts and divided them into three segments of periods to identify latent meanings in the data. The results illustrated that the first section included 81 papers, the second 64, and the third 104 respectively, averaging 13.8 annually, which increased its numbers from 2014 until the decrease below the annual average in 2020. Word frequency demonstrated that the common keywords of the entire segments were 'elder abuse,' 'elders,' 'influences,' 'factors,' 'recognition,' 'family,' 'society,' 'prevention plans,' 'experiences,' 'abused elders,' 'abuse prevention,' 'depression,' etc., in consecutive order. TF-IDF indicated that 'influences,' 'recognition,' 'society,' 'prevention plans,' 'abuse prevention,' 'experiences,' 'depression,' etc., were the common keywords of all divisions. Network text analysis displayed that the commonly represented keywords were 'elder abuse,' 'elders,' 'influences,' 'factors,' 'characteristics,' 'recognition,' 'family,' 'prevention plans,' 'society,' 'abuse prevention,' and 'experiences' in the entire sections. concor analysis presented that the first segment consisted of 5 groups, the second 7, and the third 6. We suggest future directions for elder abuse research based on the results.

Trends in the Use of Artificial Intelligence in Medical Image Analysis (의료영상 분석에서 인공지능 이용 동향)

  • Lee, Gil-Jae;Lee, Tae-Soo
    • Journal of the Korean Society of Radiology
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    • v.16 no.4
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    • pp.453-462
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    • 2022
  • In this paper, the artificial intelligence (AI) technology used in the medical image analysis field was analyzed through a literature review. Literature searches were conducted on PubMed, ResearchGate, Google and Cochrane Review using the key word. Through literature search, 114 abstracts were searched, and 98 abstracts were reviewed, excluding 16 duplicates. In the reviewed literature, AI is applied in classification, localization, disease detection, disease segmentation, and fit degree of registration images. In machine learning (ML), prior feature extraction and inputting the extracted feature values into the neural network have disappeared. Instead, it appears that the neural network is changing to a deep learning (DL) method with multiple hidden layers. The reason is thought to be that feature extraction is processed in the DL process due to the increase in the amount of memory of the computer, the improvement of the calculation speed, and the construction of big data. In order to apply the analysis of medical images using AI to medical care, the role of physicians is important. Physicians must be able to interpret and analyze the predictions of AI algorithms. Additional medical education and professional development for existing physicians is needed to understand AI. Also, it seems that a revised curriculum for learners in medical school is needed.

A Study on the Application of Machine Learning in Literary Texts - Focusing on Rule Selection for Speaker Directive Analysis - (문학 텍스트의 머신러닝 활용방안 연구 - 화자 지시어 분석을 위한 규칙 선별을 중심으로 -)

  • Kwon, Kyoungah;Ko, Ilju;Lee, Insung
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.4
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    • pp.313-323
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    • 2021
  • The purpose of this study is to propose rules that can identify the speaker referred by the speaker directive in the text for the realization of a machine learning-based virtual character using a literary text. Through previous studies, we found that when applying literary texts to machine learning, the machine did not properly discriminate the speaker without any specific rules for the analysis of speaker directives such as other names, nicknames, pronouns, and so on. As a way to solve this problem, this study proposes 'nine rules for finding a speaker indicated by speaker directives (including pronouns)': location, distance, pronouns, preparatory subject/preparatory object, quotations, number of speakers, non-characters directives, word compound form, dispersion of speaker names. In order to utilize characters within a literary text as virtual ones, the learning text must be presented in a machine-comprehensible way. We expect that the rules suggested in this study will reduce trial and error that may occur when using literary texts for machine learning, and enable smooth learning to produce qualitatively excellent learning results.