• Geomechanics and Engineering
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• v.31 no.4
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• pp.339-352
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• 2022

Studying slope stability is an important branch of civil engineering. In this way, engineers have employed machine learning models, due to their high efficiency in complex calculations. This paper examines the robustness of various novel optimization schemes, namely equilibrium optimizer (EO), Harris hawks optimization (HHO), water cycle algorithm (WCA), biogeography-based optimization (BBO), dragonfly algorithm (DA), grey wolf optimization (GWO), and teaching learning-based optimization (TLBO) for enhancing the performance of adaptive neuro-fuzzy inference system (ANFIS) in slope stability prediction. The hybrid models estimate the factor of safety (F_S) of a cohesive soil-footing system. The role of these algorithms lies in finding the optimal parameters of the membership function in the fuzzy system. By examining the convergence proceeding of the proposed hybrids, the best population sizes are selected, and the corresponding results are compared to the typical ANFIS. Accuracy assessments via root mean square error, mean absolute error, mean absolute percentage error, and Pearson correlation coefficient showed that all models can reliably understand and reproduce the F_S behavior. Moreover, applying the WCA, EO, GWO, and TLBO resulted in reducing both learning and prediction error of the ANFIS. Also, an efficiency comparison demonstrated the WCA-ANFIS as the most accurate hybrid, while the GWO-ANFIS was the fastest promising model. Overall, the findings of this research professed the suitability of improved intelligent models for practical slope stability evaluations.

• Journal of the Korean Geosynthetics Society
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• v.22 no.4
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• pp.1-8
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• 2023

Space exploration is at the forefront of human scientific endeavors, and planetary exploration rovers play a critical role in studying planetary surfaces. Rover performance is especially vital for safely navigating steep terrain and delicate landscapes found on planets like Mars and the Moon. This paper offers a comprehensive overview of a landing testbed designed to simulate challenging extraterrestrial terrain and loose regolith. The paper briefly outlines lunar crater region topographical features and highlights the importance of these simulations in rover testing. It then explores previous landing testbed developments and describes the design process for a landing testbed to be installed in the dirty thermal vacuum chamber at the Korea Institute of Civil Engineering and Building Technology. Once realized, this proposed landing testbed will enable precise evaluations of rover mobility and exploration capabilities under lunar-like conditions, including high vacuum and extreme temperatures.

• Knowledge Management Research
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• v.24 no.3
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• pp.127-148
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• 2023

Traditional Business Intelligence environment is limited to support the rapidly changing businesses and the exponential growth of data in both volume and complexity of data. Companies should shift their business intelligence environment into Self-Service Business Intelligence (SSBI) environment in order to make smarter and faster decisions. However, firms seem to face various challenges in implementing and leveraging the effective business intelligence system, and academics do not provide sufficient studies related including the success factors of SSBI. This study analyzes the three cases of Korean companies in depth, their development process and the assessment of business intelligence, based on the theoretical model on the key success factors of business intelligence systems. The comparative analysis of the three cases including project managers' interviews and performance evaluations provide rich implications for the successful adoption and the use of business intelligence systems of firms. The study is expected to provide useful references for firms to fully leverage the effects of business intelligence systems and upgrade towards self-service business intelligence systems.

• Journal of the Korean institute of surface engineering
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• v.56 no.6
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• pp.437-442
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• 2023

This research aims to enhance the efficiency of Pt/C catalysts due to the limited availability and high cost of platinum in contemporary fuel cell catalysts. Nano-sized platinum particles were distributed onto a carbon-based support via the polyol process, utilizing the metal precursor H₂PtCl₆·6H₂O. Key parameters such as pH, temperature, and RPM were carefully regulated. The findings revealed variations in the particle size, distribution, and dispersion of nano-sized Pt particles, influenced by temperature and pH. Following sodium hydroxide treatment, heat treatment procedures were systematically executed at diverse temperatures, specifically 120, 140, and 160 ℃. Notably, the thermal treatment at 140 ℃ facilitated the production of Pt/C catalysts characterized by the smallest platinum particle size, measuring at 1.49 nm. Comparative evaluations between the commercially available Pt/C catalysts and those synthesized in this study were meticulously conducted through cyclic voltammetry, X-ray diffraction (XRD), and field-emission scanning electron microscopy-energy dispersive X-ray spectroscopy (FE-SEM EDS) methodologies. The catalyst synthesized at 160 ℃ demonstrated superior electrochemical performance; however, it is imperative to underscore the necessity for further optimization studies to refine its efficacy.

• Steel and Composite Structures
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• v.51 no.1
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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.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.23-34
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• 2024

This research aims to assess the flexural bonding efficacy of polymer-cement composites(PCCs) in mending cracks within reinforced concrete(RC) structures. The study involved infilling PCCs into cement mortar cracks of varying dimensions, followed by evaluations of enhancements in flexural adhesion and strength. The findings indicate that the flexural bond performance of PCCs in crack repair is influenced by the cement type, polymer dispersion, and the polymer-to-binder ratio. Specifically, the use of ultra-high early strength cement combined with silica fume resulted in an up to 19.0% improvement in flexural bond strength compared to the application of ordinary Portland cement with silica fume. It was observed that the augmentation in flexural strength of cement mortar filled with PCCs was significantly more dependent on the depth of the crack rather than the width. Furthermore, PCCs not only acted as repair agents but also as reinforcement materials, enhancing the flexural strength to a certain extent. Consequently, this study concludes that PCCs formulated with ultra-high early strength cement, various polymer dispersions, silica fume, and a high polymer-to-binder ratio ranging from 60% to 80% are highly effective as maintenance materials for crack filling in practical settings.

• Journal of Society of Preventive Korean Medicine
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• v.28 no.1
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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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• v.21 no.2
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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.

• The Research Journal of the Costume Culture
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• v.32 no.2
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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.

• The Research Journal of the Costume Culture
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• v.32 no.2
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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.