• 대한예방한의학회지
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• 제28권1호
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• pp.43-57
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• 2024

Objectives : The aim of this study was to identify the effect of Medical humanities curriculum on students of Korean medical school in terms of cognitive, affective, and psychomotor level of humanities skill. Methods : The course was taught to second- and third-year Korean medicine students. The classes were held eight times a semester for second-year students and 9 times for third-year students, and each class was held once a week for 2 hours. Formative and summative assessments, group and individual assignments, and peer assessments were conducted to evaluate educational effectiveness, as well as basic lecture evaluations and satisfaction surveys. Results : Most of the students who took Medical humanities showed a performance rate of more than 60-70% in the cognitive aspect, and the total score was 14.48 with a standard deviation of 2.70 in the knowledge application stage. In terms of class satisfaction, students in Medical humanities I were more satisfied with the evaluation criteria and class management expertise, while students in Medical humanities II were most satisfied with the class organization, with an average score of 4.86/5. Conclusions : It was confirmed that students' humanities improved in cognitive, affective, and psychological aspects after medical humanities courses, and future research should be conducted on the long-term educational effects of medical humanities, effective teaching methods, and evaluation methods.

• Journal of Medicine and Life Science
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• 제21권2호
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• pp.31-39
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• 2024

This study was conducted to determine whether level-1 emergency medical technicians (EMTs) can adequately recognize ST-segment elevation myocardial infarction (STEMI) in the emergency department (ED) and whether their ability to do so differs from that of emergency medicine physicians (EMP). From December 2022 to November 2023, patients aged 20 years or older visiting the ED with chief complaints suggesting acute coronary syndrome (ACS) were enrolled. As soon as the patient arrived at the ED, a level-1 EMT conducted a 12-lead electrocardiogram (ECG) to assess STEMI; an EMP subsequently assessed whether to activate the percutaneous coronary intervention team. Demographic characteristics, test results, and final diagnoses were collected from the medical records. Among the 723 patients with case report forms, 720 were included in the analysis. These were categorized as follows: 117 (16.3%) with STEMI, 159 (22.1%) with non-ST-segment elevation ACS, and 444 (61.7%) with other conditions. STEMI was correctly recognized in 100 patients (91.7%) by level-1 EMTs and in 104 patients (95.4%) by EMPs (kappa=0.646). EMTs with less than 1 year of ED work experience correctly recognized 60 out of 67 STEMI patients (89.6%), which was comparable with the EMPs who recognized 65 out of 67 STEMI patients (97.0%, kappa=0.614). EMTs with more than 1 year of ED work correctly recognized 40 out of 42 STEMI patients (95.2%), and therefore performed better than EMPs, who recognized 39 out of 42 STEMI patients (92.9%, kappa=0.727). The level-1 EMTs adequately recognized STEMI using a 12-lead ECG and were in substantial agreement with the evaluations of the EMPs.

• Steel and Composite Structures
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• 제51권1호
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• pp.25-41
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• 2024

The measurement of pile bearing capacity is crucial for the design of pile foundations, where in-situ tests could be costly and time needed. The primary objective of this research was to investigate the potential use of fuzzy-based techniques to anticipate the maximum weight that concrete driven piles might bear. Despite the existence of several suggested designs, there is a scarcity of specialized studies on the exploration of adaptive neuro-fuzzy inference systems (ANFIS) for the estimation of pile bearing capacity. This paper presents the introduction and validation of a novel technique that integrates the fire hawk optimizer (FHO) and equilibrium optimizer (EO) with the ANFIS, referred to as ANFIS_FHO and ANFIS_EO, respectively. A comprehensive compilation of 472 static load test results for driven piles was located within the database. The recommended framework was built, validated, and tested using the training set (70%), validation set (15%), and testing set (15%) of the dataset, accordingly. Moreover, the sensitivity analysis is performed in order to determine the impact of each input on the output. The results show that ANFIS_FHO and ANFIS_EO both have amazing potential for precisely calculating pile bearing capacity. The R² values obtained for ANFIS_FHO were 0.9817, 0.9753, and 0.9823 for the training, validating, and testing phases. The findings of the examination of uncertainty showed that the ANFIS_FHO system had less uncertainty than the ANFIS_EO model. The research found that the ANFIS_FHO model provides a more satisfactory estimation of the bearing capacity of concrete driven piles when considering various performance evaluations and comparing it with existing literature.

• 한국건축시공학회지
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• 제24권1호
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• pp.23-34
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• 2024

본 연구의 목적은 RC 구조물의 균열 보수용 폴리머 시멘트 복합체의 휨접착성능을 평가하기 위함이다. 시멘트 모르타르에 다양한 크기의 균열을 만들어 PCCs를 충전한 후, 소정의 양생을 거쳐 휨접착강도와 휨강도 개선 정도를 파악하였다. 연구결과, 균열보수용 PCCs의 휨접착강도는 시멘트의 종류, 폴리머 종류 및 폴리머 결합재비에 따라 영향을 받으며 실리카퓸을 혼입한 초조강시멘트를 사용한 경우가 보통시멘트를 사용한 경우에 비해 최대 19.0%의 휨접착강도 개선효과가 나타났다. PCCs로 충전된 시멘트 모르타르의 휨강도 개선 정도는 균열폭의 영향보다는 균열깊이에 따라 큰 차이를 보였으며 균열에 충전된 PCCs가 단순히 보수재료로서 기능뿐만 아니라 어느 정도 휨강도를 개선시키는 보강재료로서도 역할을 하였다. 본 연구결과, 초조강시멘트, 3종류의 폴리머 디스퍼전과 실리카퓸, 60%~80%의 높은 폴리머 결합재비로 제작한 PCCs가 균열을 충전하는 보수재료로서 현장에서 충분히 사용될 수 있을 것이다.

• 한국컴퓨터정보학회논문지
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• 제29권5호
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• pp.93-100
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• 2024

4차 산업혁명의 도래와 함께 인공지능, 빅데이터, 사물인터넷, 클라우드 컴퓨팅 등의 첨단 정보 기술이 다양한 산업 분야에서 혁신을 이끌고 있다. 이 기술들은 방대한 양의 데이터를 생성하고 있으며, 많은 기업들이 이를 활용하고 있다. 그러나 개인 데이터 수집 시 발생할 수 있는 프라이버시 침해 위험으로 인해 사용자들은 민감한 정보 제공을 망설이고 있다. 특히 의료 분야에서는 환자의 병명과 같은 민감한 정보 수집이 큰 도전이 되고 있으며, 프라이버시 문제가 데이터 수집과 분석의 장애가 되고 있다. 본 연구는 프라이버시 보호를 유지하면서도 통계적 정보를 효과적으로 추출할 수 있는 의료 데이터 수집 및 분석 기법을 제안한다. 제안 기법은 기존의 단순한 데이터 수집을 넘어서, 프라이버시를 보장하면서 수집된 데이터에서 통계적 정보를 효과적으로 추출하는 방법을 포함한다. 실제 데이터를 이용한 성능 평가에서는 제안된 기법이 기존 방법보다 더 효과적으로 프라이버시를 보존하며 통계적 정보를 도출할 수 있음을 입증한다.

• Journal of Ginseng Research
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• 제48권4호
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• pp.373-383
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• 2024

Background: Network pharmacology has emerged as a powerful tool to understand the therapeutic effects and mechanisms of natural products. However, there is a lack of comprehensive evaluations of network-based approaches for natural products on identifying therapeutic effects and key mechanisms. Purpose: We systematically explore the capabilities of network-based approaches on natural products, using Panax ginseng as a case study. P. ginseng is a widely used herb with a variety of therapeutic benefits, but its active ingredients and mechanisms of action on chronic diseases are not yet fully understood. Methods: Our study compiled and constructed a network focusing on P. ginseng by collecting and integrating data on ingredients, protein targets, and known indications. We then evaluated the performance of different network-based methods for summarizing known and unknown disease associations. The predicted results were validated in the hepatic stellate cell model. Results: We find that our multiscale interaction-based approach achieved an AUROC of 0.697 and an AUPR of 0.026, which outperforms other network-based approaches. As a case study, we further tested the ability of multiscale interactome-based approaches to identify active ingredients and their plausible mechanisms for breast cancer and liver cirrhosis. We also validated the beneficial effects of unreported and top-predicted ingredients, in cases of liver cirrhosis and gastrointestinal neoplasms. Conclusion: our study provides a promising framework to systematically explore the therapeutic effects and key mechanisms of natural products, and highlights the potential of network-based approaches in natural product research.

• 복식문화연구
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• 제32권2호
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• pp.232-246
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• 2024

This study examines options to revitalize a B2B textile trading platform, exploring user satisfaction and perceptions of the importance of several website features. Between June 8 and June 21, 2023, fashion studies majors and domestic fashion brand product planners were asked to use the website of an open B2B textile platform for 30 minutes and then evaluate its features by responding to a survey. The final sample for analysis wad comprised of 150 questionnaires. To analyze the key textile website features, a paired t-test, Importance-Performance Analysis (IPA), and multiple regression analysis were utilized. The analysis classified the key textile website features related to user importance and satisfaction into the following categories: convenience, appearance, product information, and uniqueness. An analysis investigation of the differences in importance and satisfaction for each website evaluation attribute found significant differences in 12 attributes. The IPA analysis revealed that attributes such as product reliability, quality, a convenient search function, and convenient page movement are highly important to users and garner high user satisfaction; these findings demonstrate the importance of maintaining these elements. Images on the main screen, the latest trend information, and product prominence attributes also garner high importance ratings, but result in low user satisfaction, which signifies extensive revision is required. Finally, user evaluation of the convenience, appearance, and product information of the website was found to affect user recommendation intention.

• 복식문화연구
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• 제32권2호
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• pp.247-259
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• 2024

This study assessed the effectiveness of brand image communication on consumer perceptions of cruelty-free fashion brands. Brand messaging data were gathered from postings on the official Instagram accounts of three cruelty-free fashion brands and consumer perception data were gathered from Tweets containing keywords related to each brand. Web crawling and natural language processing were performed using Python and sentiment analysis was conducted using the BERT model. By analyzing Instagram content from Stella McCartney, Patagonia, and Freitag from their inception until 2021, this study found these brands all emphasize environmental aspects but with differing focuses: Stella McCartney on ecological conservation, Patagonia on an active outdoor image, and Freitag on upcycled products. Keyword analysis further indicated consumers perceive these brands in line with their brand messaging: Stella McCartney as high-end and eco-friendly, Patagonia as active and environmentally conscious, and Freitag as centered on recycling. Results based on the assessment of the alignment between brand-driven images and consumer-perceived images and the sentiment evaluation of the brand confirmed the outcomes of brand communication performance. The study revealed a correlation between brand image and positive consumer evaluations, indicating that higher alignment of ethical values leads to more positive consumer assessments. Given that consumers tend to prioritize search keywords over brand concepts, it's important for brands to focus on using visual imagery and promotions to effectively convey brand communication information. These findings highlight the importance of brand communication by emphasizing the connection between ethical brand images and consumer perceptions.

• 복식문화연구
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• 제32권3호
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• pp.334-344
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• 2024

This study aimed to develop a new convergence course applying project-based learning (PBL) and collaborative teaching methods and identify its educational effects. The course development proceeded as follows: First, three instructors collaborated to define course goals, plan objectives, content, and methods, and create a syllabus for a PBL-based fashion studio course. Roles were divided to maximize expertise: one instructor focused on fashion design, another on three-dimensional cutting, and the third on flat cutting, and digital techniques. Second, the classes were conducted and feedback on student progress was shared, enhancing class quality and engagement. Third, teaching effectiveness was assessed through learner evaluation questionnaires, reflection journals, and performance assessments. Lastly, based on the results from these evaluations, positive aspects of the course were reviewed, and ways to modify it and enhance course quality for continuous improvement were explored. The results showed high satisfaction with the learning effects on major competencies, indicating that students not only effectively learned major skills but also improved their communication and teamwork. The students perceived the teaching methods positively allowing them to be more active in class. Instructors noted that the course produced higher-quality design and production outcomes compared to previous courses. Overall, the course applying PBL and collaborative teaching methods was found to improve educational quality and effectiveness, making it a valuable approach for learner-centered education.

• 아시아태평양코퍼스연구
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• 제5권1호
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• pp.23-36
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• 2024

This research centers on the Taiwan Eye-Movement Corpus of Spanish (TECS), a specially created corpus comprising eye-tracking data from Chinese-speaking learners of Spanish as a third language in Taiwan. Its primary purpose is to explore the broad utility of TECS in understanding language learning processes, particularly the initial stages of language learning. Constructing this corpus involves gathering data on eye-tracking, reading comprehension, and language proficiency to develop a machine-learning model that predicts learner behaviors, and subsequently undergoes a predictability test for validation. The focus is on examining attention in input processing and their relationship to language learning outcomes. The TECS eye-tracking data consists of indicators derived from eye movement recordings while reading Spanish sentences with temporal references. These indicators are obtained from eye movement experiments focusing on tense verbal inflections and temporal adverbs. Chinese expresses tense using aspect markers, lexical references, and contextual cues, differing significantly from inflectional languages like Spanish. Chinese-speaking learners of Spanish face particular challenges in learning verbal morphology and tenses. The data from eye movement experiments were structured into feature vectors, with learner behaviors serving as class labels. After categorizing the collected data, we used two types of machine learning methods for classification and regression: Random Forests and the k-nearest neighbors algorithm (KNN). By leveraging these algorithms, we predicted learner behaviors and conducted performance evaluations to enhance our understanding of the nexus between learner behaviors and language learning process. Future research may further enrich TECS by gathering data from subsequent eye-movement experiments, specifically targeting various Spanish tenses and temporal lexical references during text reading. These endeavors promise to broaden and refine the corpus, advancing our understanding of language processing.