• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.179-193
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• 2022

Amid the explosive growth of various metaverse platforms, there is no unified indicator to measure, analyze, and evaluate based on customer experience. Therefore, the usability evaluation factors in metaverse were identified through a heuristic methodology and literature review, to evaluate the metaverse, a two-to three-dimensional virtual world platform. A measurable system was established by subdividing 20 items in 5 fields, including user control, information structure, design and content, and usage environment, derived through Delphi technique. Based on this, after experiencing the actual contents of major metaverse platforms such as Roblox and Zepeto, usability was evaluated and comparative verification was conducted. As a result, it was estimated that metaverse user experience could be improved as its utility was derived relatively high in terms of user control and content. This study constitutes a theoretical contribution by extending the usability evaluation system, which has been widely used in the field of service design, to the fields of extended reality and mixed reality. At the same time, it has practical key findings of providing basic judgment standards to stakeholders in the metaverse field, as well as policy implications for digital capability enhancement and industry revitalization.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.157-166
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• 2022

Structural supervision on the construction site has been performed based on visual inspection, which is highly labor-intensive and subjective. In this study, the remote technique was developed to improve the efficiency of the measurements on rebar spacing using a 360° camera and reconstructed 3D models. The proposed method was verified by measuring the spacings in reinforced concrete structure, where the twelve locations in the construction site (265 m²) were scanned within 20 seconds per location and a total of 15 minutes was taken. SLAM, consisting of SIFT, RANSAC, and General framework graph optimization algorithms, produces RGB-based 3D and 3D point cloud models, respectively. The minimum resolution of the 3D point cloud was 0.1mm while that of the RGB-based 3D model was 10 mm. Based on the results from both 3D models, the measurement error was from 10.8% to 0.3% in the 3D point cloud and from 28.4% to 3.1% in the RGB-based 3D model. The results demonstrate that the proposed method has great potential for remote structural supervision with respect to its accuracy and objectivity.

• The Journal of the Acoustical Society of Korea
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• v.40 no.6
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• pp.593-606
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• 2021

The present study investigated the sounds at 13 points in the four districts in Cheongju including commercial district, historic district, urban walking district and university campus in order to realize the soundscape of the city. In order to this, questionnaire survey was conducted to 65 citizens and 5 acoustic experts on sites to find both sound loudness and annoyance of each district. At the same time, information about loud, unpleasant, preferred and representative sound of each district were acquired by selecting three from 35 sounds which consist of natural, artificial and machinery sounds. As a result, it was found that there is a very close correlation between sound loudness and annoyance. Through the analysis of sounds at each district, it was revealed that machinery sounds dominate in commercial area as figure sound, It was also shown that artificial and natural sounds dominate in historic area, artificial sounds in both urban area and university campus respectively. Laboratory listening tests were undertaken to 20 people using recorded sounds and video captured on site. The results denote that machinery and artificial sounds are regarded as most loud, machinery sounds as most unpleasant, natural and artificial sounds as most pleasant which shows similar tendency of on-site evaluation.

• Journal of Korean Home Economics Education Association
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• v.34 no.1
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• pp.151-165
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• 2022

The aim of this study is to examine the effectiveness of non-face-to-face classes conducted due to the COVID-19 crisis. In order to achieve this goal, a non-face-to-face class with flipped learning was applied in one subject of clothing major held at 'S' University in Cheongju, Korea. In addition, this study tried to analyze the differences between pre- and post-non-face-to-face classes in problem analysis ability, resource/information/technology literacy, convergent thinking ability as core competencies, and overall learning satisfaction. As a result, after participating in the non-face-to-face class in which the flipped learning was applied, the students recognized that their abilities improved in the three problem-solving competency sub-areas, and their overall learning satisfaction also increased. The effectiveness of non-face-to-face classes in the field of clothing and fashion has been mainly measured in fashion design and clothing construction courses. However, based on the results of this study, it can be suggested that non-face-to-face classes in a theory-oriented lecture-type class can be effective methods for improving students' core competencies such as problem-solving skills if teaching-learning methods such as flipped learning are applied. Therefore, the results of this study will be useful data for designing differentiated non-face-to-face class strategies in a theory-oriented lecture-type class to improve the core competencies of college students.

• Journal of agricultural medicine and community health
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• v.47 no.2
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• pp.78-89
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• 2022

목적: 이 연구는 2019학년도 역학조사관 입문교육 과정에 참여한 29명의 수습과정생에게 참여형 자기주도 학습 역학조사관 연수 프로그램(FETP)의 효과와 만족도 등 역량 변화를 분석해 그 결과를 향후 과정 개발의 참고 자료로 활용하고자 하였다. 방법: 교육 프로그램의 만족도와 교육 후 모듈에 대한 역량 변화를 평가하는 연구가 수행되었다. 만족도와 역량의 차이 비교는 크루스칼 왈리스 검정(Kruskal-Wallis test)를 실시하였고, 역량의 차이는 윌콕슨 부호순위검정(Wilcoxon signed rank test)에 의해 이루어 졌다. 결과: 2019년 FETP에 참여한 역학조사관 중 여성은 48.3% 였으며, 40세 미만은 9.4% 였다. 역학조사관 입문교육과정 모듈(역학조사, 보건통계 및 정보통계, 감염병 국가 체계, 감염병 질환 감시 체계, 진단 및 실험실 검사, 생물 안전 및 관리, 주요 감염성질환 관리와 조사, 커뮤니케이션, 협동과 리더십, 일반과정)별 만족도는 실무적 도움, 전문성, 기능, 태도 등에서 4점(5점 만점)을 초과하였고, 전체 4.2±0.21(5점 만점)점으로 높은 수준이였다, 모듈의 교육훈련 전후 평균 점수는 2.25±0.91, 3.68±0.63점 등으로 유의한 향상이 있었으며, 모든 모듈 및 하위 주제들도 유의한 향상이 있었다(p<0.001). 그 중에서 현장역학조사 경험이 가장 높은 변화가 있었고, 표본 수집과 실무가 가장 낮은 역량 변화가 있었다. 결론: 2019년 진행된 입문교육 과정은 수료 후 학생들의 역량은 개선되었고, 만족도는 높은 편이었다. 참여형 자기주도학습의 촉진은 역량을 향상시킬 뿐만 아니라 보건 종사자들의 자신감을 높일 수 있었다.

• Korean Journal of Culture and Social Issue
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• v.27 no.4
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• pp.629-659
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• 2021

This study compared the influences of Korean psycho-social experiences on emotional-distress(stress, depression, anxiety, anger) of Koreans between two-periods during COVID-19. First, an online survey was conducted among 600 participants between April 13, 2020 and 21, while WHO had declared the pandemic, and Daegu-Gyungbuk were declared as a special-disaster area. Second, an online survey was conducted among 482 participants out of 600 study participants from the first study during August 21 to September 2, while COVID-19 re-spreaded around the world, and total confirmed cases were over 1,000 for a week in Seoul-Gyeonggi province. Hierarchical-regression analysis was used to determine the influence of personal characteristics, fear and social constraints, relationship conflict and income-decreasing factors on stress, depression, anxiety, anger in the two-time points. Results suggest that gender, quality-of-life, 'frequent information-checking about COVID-19', 'fear of unpredictability' and 'difficulties on hospital treatment access' predicted distress(stress, depression, anxiety, anger) at both Time1 and 2. 'Difficulties with official schedule' predicted distress at Time 1, and age, vulnerability to infection and difficulties with personal schedules predicted distress(stress, depression, anxiety, anger) at Time 2. Based on the reseults, implications and recommendations were presented.

• Korean Journal of Ecology and Environment
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• v.55 no.4
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• pp.352-359
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• 2022

Recently, with the development of genetic technology, interest in environmental DNA (eDNA) to study biodiversity according to molecular biological approaches is increasing. Environmental DNA has many advantages over traditional research methods for biological communities distributed in the environment but highly depends on the established base sequence database. This study conducted a comprehensive analysis of the habitat status and classification at the genus level, which is mainly used in eDNA (12S rRNA, 16S rRNA, 18S rRNA, COI, and CYTB), focusing on Korean registration taxon groups (phytoplankton, zooplankton, macroinvertebrates, and fish). As a result, phytoplankton and zooplankton showed the highest taxa proportion in 18S rRNA, and macroinvertebrates observed the highest ratio in the nucleotide sequence database in COI. In fish, all genes except 18S rRNA showed a high taxon ratio. Based on the Korean registration taxon group, the gene construction of the top 20 genera according to bio density observed that most of the phytoplankton were registered in 18S rRNA, and the most significant number of COI nucleotide sequences were established in macroinvertebrates. In addition, it was confirmed that there is a nucleotide sequence for the top 20 genera in 12S rRNA, 16S rRNA, and CYTB in fish. These results provided comprehensive information on the genes suitable for eDNA research for each taxon group.

• Journal of International Area Studies (JIAS)
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• v.18 no.3
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• pp.145-168
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• 2014

Given the distance from Mt. Baekdu, volcanic ash will have the direct impact on South Korea in case Mt. Baekdu erupts. Ash fall deposits or particulate matters(PM10) in the air will cause damages in various sectors. In particular, the PM10 impact on the manufacturing sector when the ash disperses in Korea is needed to be assessed since South Korea's manufacturing sector accounts for more than 30% of GDP. Meanwhile the economic impacts of PM10, including Asian dust, have been researched in Korea as the events become frequent, and losses in the manufacturing have been also reported. This study is to identify vulnerable sectors to volcanic ash in the korean industry, and to assess economic losses in case of a Mt. Baekdu eruption scenario, based on the historical loss experience with particulate matters. Study results show that airline, precision such as electronics and semiconductors, distribution, shipbuilding, car, leisure, glass, dairy farming are vulnerable to volcanic ash, or PM10. The economic losses in both car and shipbuilding industry is estimated to 46.49 billion Korean won due to shutdown for 6 hours in case of a Mt. Baekdu eruption scenario.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.194-199
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• 2022

Preprocessing for high-quality data is required for high accuracy and usability in various and complex image data-based industries. However, when a contaminated hostile example that combines noise with existing image or video data is introduced, which can pose a great risk to the company, it is necessary to restore the previous damage to ensure the company's reliability, security, and complete results. As a countermeasure for this, restoration was previously performed using Defense-GAN, but there were disadvantages such as long learning time and low quality of the restoration. In order to improve this, this paper proposes a method using adversarial examples created through FGSM according to image segmentation in addition to using the VQ-VAE model. First, the generated examples are classified as a general classifier. Next, the unsegmented data is put into the pre-trained VQ-VAE model, restored, and then classified with a classifier. Finally, the data divided into quadrants is put into the 4-split-VQ-VAE model, the reconstructed fragments are combined, and then put into the classifier. Finally, after comparing the restored results and accuracy, the performance is analyzed according to the order of combining the two models according to whether or not they are split.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.1
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• pp.24-35
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• 2023

Rapid industrialization and urbanization have led to severe marine pollution. A Water Quality Index (WQI) has been developed to allow the effective management of marine pollution. However, the WQI suffers from problems with loss of information due to the complex calculations involved, changes in standards, calculation errors by practitioners, and statistical errors. Consequently, research on the use of artificial intelligence techniques to predict the marine and coastal WQI is being conducted both locally and internationally. In this study, six techniques (RF, XGBoost, KNN, Ext, SVM, and LR) were studied using marine environmental measurement data (2000-2020) to determine the most appropriate artificial intelligence technique to estimate the WOI of five ecoregions in the Korean seas. Our results show that the random forest method offers the best performance as compared to the other methods studied. The residual analysis of the WQI predicted score and actual score using the random forest method shows that the temporal and spatial prediction performance was exceptional for all ecoregions. In conclusion, the RF model of WQI prediction developed in this study is considered to be applicable to Korean seas with high accuracy.