• Journal of Digital Convergence
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• v.20 no.1
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• pp.335-341
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• 2022

This is a descriptive research study to confirm the relationship between communication types, emotional labor, and job stress of nurses in small and medium-sized hospitals and to identify factors affecting job stress. The study was conducted on 192 nurses randomly selected from small and medium-sized hospitals located in G Metropolitan City. A structured questionnaire was used as a research tool for measuring communication types, emotional labor, and job stress, and the data were collected from August 20 to September 10, 2019. The results of the study are as follows. The subject's communication type averaged 3.55±0.31 points, emotional labor 3.21±0.59 points, and job stress 3.44±0.52 points. Job stress showed a statistically significant negative correlation with friendly communication among the types of communication, and a statistically significant positive correlation with emotional labor. Factors affecting job stress included gender, total clinical experience, and emotional labor, showing an explanatory power of 28.0%. It is considered that an efficient management strategy for emotional labor is needed to reduce the job stress of nurses in the future.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.459-469
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• 2022

This study aims to provide basic data for the development of teaching methods to improve the performance confidence of performing core basic nursing skills in nursing students while availing of online education owing to COVID-19. Data were collected from 146 students in the Department of Nursing at N University located in C city. The collected data was analyzed using descriptive statistics, difference, correlation analysis, and multiple regression by using SPSS 23.0 program.. The subjects' performance confidence of core basic nursing skills was dependent on self-directed learning readiness (r=.368, p<.001), intrinsic goal motivation (r=.232, p=.005), extrinsic goal motivation (r=.344, p<.001), task value (r=.237, p=<.001), control of learning beliefs (r=.262, p=<.001), and self-efficacy for learning and performance (r=.443), p<.001) with a significant positive correlation. The results indicate that the factors influencing the subjects' performance confidence of core basic nursing skills were the 4th grade (β=0.413, p<.001), extrinsic goal motivation (β=0.307, p<.001), and self-efficacy for learning and performance (β=0.316, p=.005), and the explanatory power was 35.8% (F=8.354, p<.001). The research results showed that it is necessary to develop and apply various online-centered teaching and learning methods to increase the extrinsic goal motivation and self-efficacy for learning and performance of nursing students to enhance their performance confidence of core basic nursing skills. This will serve as a basis for preparing effective online centered nursing education strategies to improve performance confidence of core basic nursing skills.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.391-398
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• 2022

The aim of this study was to identify the factors affecting the mental health of high school students. The participants comprised 216 students in general high school. Data collection was conducted from May 1, 2020 to May 20, 2020. The data were analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient and a multiple regression analysis. The average score for self-esteem was 3.75±0.64(1-5), perceived stress was 2.86±0.58(1-5), emotional regulation ability was 3.43±0.65(1-5) and mental health was 1.91±0.71(1-5). Mental health had a statistically significant relationship with self-esteem(r=-.64, p<.001), emotional regulation ability(r=-.61, p<.001) and perceived stress(r=.54, p<.001). The factors affecting mental health were self-esteem(β=.46, p<.001), emotional regulation ability(β=-.37, p<.001), negative perceived stress(β=.17, p=.001) ; the explanatory power of the model was 60.0%. Therefore, it will be necessary to develop a program that can help high school students improve their self-esteem and control their negative emotions in order to promote their mental health.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.35-43
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• 2023

This study tried to find out the applicability and effectiveness of the AI-based adaptive learning system in university classes by operating an AI-based adaptive learning system on a pilot basis. To this end, an AI-based adaptive learning system was applied to analyze the operation results of 42 learners who participated in basic mathematics classes, and a survey and in-depth interviews were conducted with students and professors. As a result of the study, the use of an AI-based customized learning system improved students' academic achievement. Both instructors and learners seem to contribute to improving learning performance in basic concept learning, and through this, the AI-based adaptive learning system is expected to be an effective way to enhance self-directed learning and strengthen knowledge through concept learning. It is expected to be used as basic data related to the introduction and application of basic science subjects for AI-based adaptive learning systems. In the future, we suggest a strategy study on how to use the analyzed data and to verify the effect of linking the learning process and analyzed data provided to students in AI-based customized learning to face-to-face classes.

• Journal of Life Science
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• v.33 no.7
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• pp.538-548
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• 2023

The research has been conducted on the isolation of antimicrobial compounds from plant natural extracts and their potential application in oral health care products. This study aimed to investigate the antimicrobial mechanism by analyzing the changes in gene expression of Streptococcus mutans, a major oral pathogen, in response to complex compounds extracted from Aralia continentalis and Arctii Semen using organic solvents. Transcriptome analysis (RNA-seq) revealed that both natural extracts commonly upregulated or downregulated the expression of various genes associated with different metabolic and physiological activities. Three genes (SMU_1584c, SMU_2133c, SMU_921), particularly SMU_921 (rcrR), known as a transcription activator of two sugar phosphotransferase systems (PTS) involved in sugar transport and biofilm formation, exhibited consistent high expression levels. Additionally, component analysis of the A. continentalis extract was performed to compare its effects on gene expression changes with the A. Semen extract, and two active compounds were identified through gas chromatography-mass spectrometry (GC-MS) analysis of the active fraction. The n-hexane fraction (ACEH) from the A. continentalis extract exhibited antibacterial specificity against S. mutans, leading to a significant reduction in the viable cell counts of Streptococcus sanguinis and Streptococcus gordonii among the tested multi-species bacterial communities. These findings suggest the broad-spectrum antibacterial activity of the A. continentalis extract and provide essential foundational data for the development of customized antimicrobial materials by elucidating the antibacterial mechanism of the identified active compounds.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.839-848
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• 2006

Korea has become the 5th country to own and operate the high speed railroad in 2004. However, there were many difficulties until Koreans enjoy the first bullet train service with the average hourly speed of 300km. The high speed railroad requires elevated quality standards differently from the traditional railways. In addition to the technical difficulties, the construction project itself was an unpleasant case with huge delays and cost overruns mainly due to the lack of experiences, deficiency of owner$^{\circ}{\O}$s role, and increase of public resistances triggered by environmental concerns. This paper analyzes the reasons for delays on this mega-project. With respect to the characteristics of the whole project level, it is very complicated/linear project, whose total length is around 412 km with the composition of various sections in the route of the railway which have basically different conditions. For that reason, the analysis is performed in both macro and micro level. First, macroscopic analysis is performed to find critical subdivisions in the railway route that induces the significant delay in the opening due date. Then, microscopic analysis is followed to quantify the causes and effects of delays focused on these critical subdivisions in more detailed way. Finally, this paper provides lessons learned from this project to avoid the decisive delays in performing the similar large-scaled projects.

• Membrane Journal
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• v.33 no.6
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• pp.325-343
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• 2023

Direct methanol fuel cells (DMFCs) have been attracting attention as energy conversion devices that can directly supply methanol liquid fuel without a fuel reforming process. The commercial polymer electrolyte membranes (PEMs) currently applied to DMFC are perfluorosulfonic acid ionomer-based PEMs, which exhibit high proton conductivity and physicochemical stability during the operation. However, problems such as high methanol permeability and environmental pollutants generated during decomposition require the development of PEMs for DMFCs using novel ionomers. Recently, studies have been reported to develop PEMs using hydrocarbon-based ionomers that exhibit low fuel permeability and high physicochemical stability. This review introduces the following studies on hydrocarbon-based PEMs for DMFC applications: 1) synthesis of grafting copolymers that exhibit distinct hydrophilic/hydrophobic phase-separated structure to improve both proton conductivity and methanol selectivity, 2) introduction of cross-linked structure during PEM fabrication to reduce the methanol permeability and improve dimensional stability, and 3) incorporation of organic/inorganic composites or reinforcing substrates to develop reinforced composite membranes showing improved PEM performances and durability.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.27-35
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• 2023

In this paper, we propose a process of increasing productivity by applying a deep learning-based defect detection and classification system to the prepreg fiber manufacturing process, which is in high demand in the field of producing composite materials. In order to apply it to toe prepreg manufacturing equipment that requires a solution due to the occurrence of a large amount of defects in various conditions, the optimal environment was first established by selecting cameras and lights necessary for defect detection and classification model production. In addition, data necessary for the production of multiple classification models were collected and labeled according to normal and defective conditions. The multi-classification model is made based on CNN and applies pre-learning models such as VGGNet, MobileNet, ResNet, etc. to compare performance and identify improvement directions with accuracy and loss graphs. Data augmentation and dropout techniques were applied to identify and improve overfitting problems as major problems. In order to evaluate the performance of the model, a performance evaluation was conducted using the confusion matrix as a performance indicator, and the performance of more than 99% was confirmed. In addition, it checks the classification results for images acquired in real time by applying them to the actual process to check whether the discrimination values are accurately derived.

• Journal of the Microelectronics and Packaging Society
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• v.29 no.4
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• pp.63-69
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• 2022

Vanadium dioxide shows a unique and interesting property of metal-insulator transition, which has attracted great attention from the viewpoints of fundamental materials science and industrial applications. In this study, the effect of Mg and W addition on the metal-insulator transition of VO₂ were investigated for the bulk materials that are prepared by spark plasma sintering. The X-ray diffraction analysis of the sintered specimens revealed that the lattice parameters barely change, and the secondary phases are present. The transition temperature of MIT appears in the range of 64.2-64.6℃, regardless of the impurity element and content. On the other hand, the addition of Mg and W alters the electrical conductivity, i.e., the electrical conductivity increases by a factor of up to 2.4 or decrease by a factor of up to 57.4 depending on the impurity type and its content. The thermal conductivity showed the values of 1.8~2.5 W/m·K below the transition temperature, and the values of 1.9~2.8 W/m·K above the transition temperature. These changes in electrical and thermal conductivities can be attributed to the combination of the change in charge carrier density, the impurities as scattering centers, and the change in microstructures.

• Korean Chemical Engineering Research
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• v.62 no.1
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• pp.19-26
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• 2024

In this study, the electrochemical properties of SiOx@C composite materials were prepared to alleviate volume expansion and cycle stability of silicon and to increase the capacity of anode material for LIBs. SiO₂ particles of 100, 200, and 500 nm were synthesized by the Stӧber method, and reduced to SiOx (0≤x≤2) through the magnesiothermic reduction method. Then, SiOx@C anode materials were synthesized by carbonization of PVC on SiOx. The physical properties of prepared SiOx and SiOx@C anode materials were analyzed by XRD, SEM, TGA, Raman spectroscopy, XPS and BET. The electrochemical properties were investigated by cycling performance, rate performance, CV and EIS test. As a result, the SiOx@C-7030 manufactured by coating carbon at SiOx : C = 70 : 30 on a 100 nm SiOx with the smallest particle size showed the best electrochemical properties with a discharge capacity of 1055 mAh/g and a capacity retention rate of 81.9% at 100 cycles. It was confirmed that cycle stability was impoved by reducing particle size and carbon coating.