• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.82-91
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• 2021

The purpose of this study was to explore the prerequisites for securing the convergence validity of qualifications and the development of a lifelong education support system for the disabled. The research method consisted of the procedure of collecting and analyzing previous research literature and conducting expert meetings. The content of this study is based on the limitations and reflection of the current promotion of the qualification system for lifelong education professionals for the disabled, establishing the academic foundation and concept system for lifelong education for the disabled, designing a career development path for the professional competency of developing and operating the lifelong education curriculum for the disabled. Also, Restructuring of related institutions based on the curriculum for lifelong education for the disabled, and enhancement of qualification types for nurturing professionals for lifelong education for the disabled were suggested. As a result of the study, it was analyzed that the value and function of qualifications are very important in the comprehensive category of developing a lifelong education support system for persons with disabilities, and conclusively, the viewpoint of university foundation and the application model for nurturing professionals for lifelong education for persons with disabilities should be reviewed.

• Nutrition Research and Practice
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• v.16 no.2
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• pp.272-283
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• 2022

BACKGROUND/OBJECTIVES: Most child and adolescent food literacy measurement tools focus on nutrition and food safety. However, the importance of aspects related to the food system such as food distribution and food waste and their effects on environmental sustainability is growing. We therefore developed and validated a two-dimensional tool for children (8-12 years old) and adolescents (13-18 years old) that can comprehensively measure food literacy. The association of food literacy with diet quality and self-reported health was assessed. SUBJECTS/METHODS: First, we developed a food literacy conceptual framework that contains food system and literacy dimensions through a literature review, focus group interviews, and expert review. After a face validity study, we conducted the main survey (n = 200) to validate the questionnaire. Construct validity and reliability were assessed using exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and Cronbach's alpha. RESULTS: As a result of the Delphi study, content validity was confirmed for the remaining 30 items after two items were excluded (content validity ratio = 0.86). Eleven items were excluded from the EFA results, while the CFA results indicated appropriate fit indices for the proposed model (comparative fit index = 0.904, root mean square error of approximation = 0.068). The final food literacy questionnaire consisted of 19 questions and comprised 5 factors: production, distribution, selection, preparation and cooking, and intake. Food literacy was positively associated with diet quality, as assessed by the Nutrition Quotient score, in both children and adolescents and with self-reported health in adolescents.

• The Journal of Sustainable Design and Educational Environment Research
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• v.20 no.4
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• pp.1-12
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• 2021

This study aims to propose a planning direction based on the results of domestic case studies and expert advice as a basic research to establish a specific implementation model for kindergarten education space in response to changes in future society and future education by escaping from the issues and facility limitations of existing kindergarten education space. To this end, it is intended to contribute to the positive effect of future education policies by being used as basic data for building specific implementation models through review of the 'Nuri' course, domestic case analysis, and revision of specific standards for kindergarten facility planning. The main research results were case analysis and advisory consultations to derive facility standards and planning directions divided into layout plans, general classrooms, support facilities, public spaces, and external spaces, and a process for identifying and systematizing space-influencing factors based on the facility standards derived in this basic study is needed hereafter.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.4
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• pp.192-199
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• 2022

With the advent of autonomous ships, it is emerging as one of the very important issues not only to operate with a minimum crew or unmanned ships, but also to secure the safety of ships to prevent marine accidents. On-site inspection of the hull is mainly performed by the inspector's visual inspection, and video information is recorded using a small camera if necessary. However, due to the shortage of inspection personnel, time and space constraints, and the pandemic situation, the necessity of introducing an automated inspection system using artificial intelligence and remote inspection is becoming more important. Furthermore, research on hardware and software that enables the automated inspection system to operate normally even under the harsh environmental conditions of a ship is absolutely necessary. For automated inspection systems, it is important to review artificial intelligence technologies and equipment that can perform a variety of hull failure detection and classification. To address this, it is important to classify the hull failure. Based on various guidelines and expert opinions, we divided them into 6 types(Crack, Corrosion, Pitting, Deformation, Indent, Others). It was decided to apply object detection technology to cracks of hull failure. After that, YOLOv5 was decided as an artificial intelligence model suitable for survey and a common hull crack dataset was trained. Based on the performance results, it aims to present the possibility of applying artificial intelligence in the field by determining and testing the equipment required for survey.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.235-245
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• 2021

In the era of the 4th Industrial Revolution, complex problems of the advertising and PR industry ecosystem, which have become more complex than in the past, are raised, and the necessity and importance of convergence education is being demanded. In this study, the usefulness and implementation plan of the team teaching method for revitalization of convergence education were studied by conducting in-depth interviews with experts in academia and practice expert. The results of this study summarized that it is appropriate to introduce a team teaching method in which academia and industry jointly participate in the curriculum of the Department of Advertising and PR. It was found to be a meaningful educational method aimed at nurturing students with problem-solving ability. This study proposed a new industry-academic cooperation model as an exploratory study of advertising and PR department and team teaching education.

• Safety and Health at Work
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• v.13 no.3
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• pp.326-335
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• 2022

Background: One of the important actions for enhancing human reliability in any industry is assessing human error probability (HEP). The HEART technique is a robust tool for calculating HEP in various industries. The traditional HEART has some weaknesses due to expert judgment. For these reasons, a hybrid model is presented in this study to integrate HEART with Best-Worst Method. Materials Method: In this study, the blasting process in an iron ore mine was investigated as a case study. The proposed HEART-BWM was used to increase the sensitivity of APOA calculation. Then the HEP was calculated using conventional HEART formula. A consistency ratio was calculated using BWM. Finally, for verification of the HEART-BWM, HEP calculation was done by traditional HEART and HEART-BWM. Results: In the view of determined HEPs, the results showed that the mean of HEP in the blasting of the iron ore process was 2.57E-01. Checking the full blast of all the holes after the blasting sub-task was the most dangerous task due to the highest HEP value, and it was found 9.646E-01. On the other side, obtaining a permit to receive and transport materials was the most reliable task, and the HEP was 8.54E-04. Conclusion: The results showed a good consistency for the proposed technique. Comparing the two techniques confirmed that the BWM makes the traditional HEART faster and more reliable by performing the basic comparisons.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.235-248
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• 2022

Through the research on the design evaluation index of parent-child interactive game furniture, it is convenient for designers to quantitatively analyze the design advantages and disadvantages of related products, which is of positive help to control and improve the design quality. Combined with AHP and TOPSIS, this study proposes the evaluation model of three design criteria and 26 design indexes. After expert scoring, calculation, and consistency test of each index, the weight value of each design index is obtained, and the index is classified according to the importance of each index. Finally, eight essential indicators, eleven secondary indicators, and seven general indicators are classified. A case study was conducted with TOPSIS, and the design samples of three parent-child climbing game furniture were analyzed. Finally, the three samples' relative proximity was 0.505, 0281, and 0.640, respectively. The research shows that the AHP-TOPSIS method can scientifically and effectively sort and screen the advantages and disadvantages of design schemes and provide a reference for the research and development of related products.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Journal of the Korea Computer Graphics Society
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• v.28 no.2
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• pp.11-19
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• 2022

Recently, various researches on medical image generation have been suggested, and it becomes crucial to accurately evaluate the quality and diversity of the generated medical images. For this purpose, the expert's visual turing test, feature distribution visualization, and quantitative evaluation through IS and FID are evaluated. However, there are few methods for quantitatively evaluating medical images in terms of fidelity and diversity. In this paper, images are generated by learning a chest CT dataset of non-small cell lung cancer patients through DCGAN and PGGAN generative models, and the performance of the two generative models are evaluated in terms of fidelity and diversity. The performance is quantitatively evaluated through IS and FID, which are one-dimensional score-based evaluation methods, and Precision and Recall, Improved Precision and Recall, which are two-dimensional score-based evaluation methods, and the characteristics and limitations of each evaluation method are also analyzed in medical imaging.

• Journal of Hospice and Palliative Care
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• v.25 no.3
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• pp.110-120
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• 2022

Purpose: The purpose of this study was to confirm the factor structure of the McGill Quality of Life Questionnaire-Revised (MQOL-R) in the context of Korean culture and to verify its reliability and validity. Methods: The participants comprised terminal cancer patients aged 25 or older, and data from 164 participants were analyzed. The study was conducted in the following order: translation, expert review, reverse translation, preliminary investigation and interviews, and completion of the final version. Confirmatory factor analysis was applied to evaluate the validity of the instrument, and the Beck Depression Inventory, Korean version (K-BDI) was applied to confirm the criterion validity of the MQOL-R Korean version. The Cronbach's alpha coefficient, representing internal consistency, was measured to evaluate reliability. Results: Cronbach's alpha for all 14 questions was 0.862. The model fit indices for confirmatory factor analysis were within the acceptance criteria. The factor loadings of all four factors were over 0.50, and convergent validity and discriminant validity were confirmed. Regarding criterion validity, a negative correlation was found between the four factors of MQOL-R Korean version and the K-BDI. Conclusion: The MQOL-R Korean version, the reliability and validity of which were verified in this study, is a 15-item tool consisting of 14 items dealing with four physical, psychological, existential, and social factors and a single item evaluating the overall quality of life. The MQOL-R Korean version is an instrument that can more concisely and effectively measure the quality of life of patients with life-threatening diseases.