• IMMUNE NETWORK
• /
• v.22 no.5
• /
• pp.40.1-40.24
• /
• 2022

Mesenchymal stem cells (MSCs) are attractive alternatives to conventional anti-asthmatic drugs for severe asthma. Mechanisms underlying the anti-asthmatic effects of MSCs have not yet been elucidated. This study evaluated the anti-asthmatic effects of intravenously administered MSCs, focusing on macrophages and monocytes. Seven-week-old transgenic (Tg) mice with lung-specific overexpression of IL-13 were used to simulate chronic asthma. MSCs were intravenously administered four days before sampling. We examined changes in immune cell subpopulations, gene expression, and histological phenotypes. IL-13 Tg mice exhibited diverse features of chronic asthma, including severe type 2 inflammation, airway fibrosis, and mucus metaplasia. Intravenous administration of MSCs attenuated these asthmatic features just four days after a single treatment. MSC treatment significantly reduced SiglecF^-CD11c^-CD11b⁺ monocyte-derived macrophages (MoMs) and inhibited the polarization of MoMs into M2 macrophages, especially M2a and M2c. Furthermore, MSCs downregulated the excessive accumulation of Ly6c^- monocytes in the lungs. While an intravenous adoptive transfer of Ly6c^- monocytes promoted the infiltration of MoM and Th2 inflammation, that of MSC-exposed Ly6c^- monocytes did not. Ex vivo Ly6c^- MoMs upregulated M2-related genes, which were reduced by MSC treatment. Molecules secreted by Ly6c^- MoMs from IL-13 Tg mice lungs upregulated the expression of fibrosis-related genes in fibroblasts, which were also suppressed by MSC treatment. In conclusion, intravenously administered MSCs attenuate asthma phenotypes of chronic asthma by modulating macrophages. Identifying M2 macrophage subtypes revealed that exposure to MSCs transforms the phenotype and function of macrophages. We suggest that Ly6c^- monocytes could be a therapeutic target for asthma management.

• Journal of Navigation and Port Research
• /
• v.47 no.6
• /
• pp.410-418
• /
• 2023

Recently, advancements and commercialization in the field of maritime autonomous surface ships (MASS) has rapidly progressed. Concurrently, studies are also underway to develop methods for automatically surveying the condition of various on-board equipment remotely to ensure the navigational safety of MASS. One key issue that has gained prominence is the method to obtain values from analog gauges installed in various equipment through image processing. This approach has the advantage of enabling the non-contact detection of gauge values without modifying or changing already installed or planned equipment, eliminating the need for type approval changes from shipping classifications. The objective of this study was to identify a dynamically changing indicator needle within noisy images of analog gauges. The needle object must be identified because its position significantly affects the accurate reading of gauge values. An analog pressure gauge attached to an emergency fire pump model was used for image capture to identify the needle object. The acquired images were pre-processed through Gaussian filtering, thresholding, and morphological operations. The needle object was then identified through Hough Transform. The experimental results confirmed that the center and object of the indicator needle could be identified in images of noisy analog gauges. The findings suggest that the image processing method applied in this study can be utilized for shape identification in analog gauges installed on ships. This study is expected to be applicable as an image processing method for the automatic remote survey of MASS.

• Information Systems Review
• /
• v.19 no.4
• /
• pp.87-110
• /
• 2017

Analyzing and finding the risk factors in information technology (IT) projects have been discussed because risk management is an important issue in IT project management. This study obtained the risk factor checklists with priorities, analyzed the causal relationship of risk factors, and determined their influences on IT project management. However, only few studies systematically classified IT project risk factors in terms of risk exposure. These studies considered both the probability of occurrence and the degree of risk simultaneously. The present study determined 53 IT project risk factors on the basis of literature and expert group discussions. Additionally, this study presented clustering analysis based on the data of 140 project managers. The IT project risk factor classification framework was divided into four areas (HIHF, HILF, LIHF, and LILF). The present results can be used to help IT project managers establish effective risk management strategies and reduce IT project failures. This study also provides academic implication because it considers both the probability of occurrence and the degree of influence of risk factors.

• Journal of the Society of Disaster Information
• /
• v.20 no.1
• /
• pp.222-231
• /
• 2024

Purpose: The purpose of this study is to study how to activate the use of public transportation by identifying the main factors that reduce the use of public transportation due to external influences such as COVID-19 infectious diseases. Method: This study analyzed the connection between the traffic behavior and the characteristics of public transportation use in the metropolitan area changed by COVID-19 with COVID-19 indicators, and analyzed social and environmental factors affecting traffic. Results: It was analyzed that the traffic behavior in the metropolitan area moves from commercial areas to tourist resort areas, the number of COVID-19 deaths affects the use of public transportation, and the lower the deviation between population density, agricultural and forestry areas, and gender ratios due to social and environmental factors, the more significant differences are shown. Conclusion: In the future, it will be able to be activated as a basic analysis model for revitalizing the city's transportation system, regional bases, and various social and economic indicators, such as quarantine of public transportation and social distancing, and can be used as basic data for establishing public transport policy directions according to major influencing factors.

• Therapeutic Science for Rehabilitation
• /
• v.13 no.2
• /
• pp.69-84
• /
• 2024

Objective : This study aimed to categorize the lifestyles of older adults into two types - healthy and unhealthy, and use machine learning to identify the personal values that influence these lifestyles. Methods : This cross-sectional study targeting middle-aged and older adults (55 years and above) living in local communities in South Korea. Data were collected from 300 participants through online surveys. Lifestyle types were dichotomized by the Yonsei Lifestyle Profile (YLP)-Active, Balanced, Connected, and Diverse (ABCD) responses using latent profile analysis. Personal value information was collected using YLP-Values (YLP-V) and analyzed using machine learning to identify the relative importance of personal values on lifestyle types. Results : The lifestyle of older adults was categorized into healthy (48.87%) and unhealthy (51.13%). These two types showed the most significant difference in social relationship characteristics. Among the machine learning models used in this study, the support vector machine showed the highest classification performance, achieving 96% accuracy and 95% area under the receiver operating characteristic (ROC) curve. The model indicated that individuals who prioritized a healthy diet, sought health information, and engaged in hobbies or cultural activities were more likely to have a healthy lifestyle. Conclusion : This study suggests the need to encourage the expansion of social networks among older adults. Furthermore, it highlights the necessity to comprehensively intervene in individuals' perceptions and values that primarily influence lifestyle adherence.

• Communications of Mathematical Education
• /
• v.38 no.2
• /
• pp.93-120
• /
• 2024

On-line education in mathematics education changed in various aspects before and after COVID-19. This study conducted a systematic literature review of 98 academic papers on on-line education published from 2017 to 2023 in the field of mathematics education before and after COVID19. In particular, this study conducted content analysis to organize on the definitions of various similar terms related to online education. In addition, this study explored research trends on year, research subject, research method, on-line education type, and research topic by the pre-COVID-19, COVID-19, and post-COVID-19 era. Also, a comparative analysis was conducted on literatures on the effects of online education. As a result, first, it was confirmed that there is a need to organize the definitions of terms similar to online education. Also, the implications of identifying the differences and hierarchies between each term can be found. Second, it was confirmed that teachers' expertise for on-line mathematics education was emphasized based on the result of the rapid increase in the number of on-line education studies on teachers since COVID-19. Third, it was confirmed that the number of studies on blended and flipped learning was high in pre-COVID-19, but decreased in the COVID-19 era. Instead, in the COVID-19 era, studies on real-time interactive classes were rapidly active, and even in the post-COVID-19 era, studies on real-time interactive classes still occupied a large proportion. Finally, it was confirmed that the effectiveness of on-line education varies depending on the research background and model. Accordingly, the need to be cautious in interpreting the results of each study on the effectiveness of on-line education was confirmed. Based on these findings, this study presented implications for future research on on-line education in mathematics education.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.17 no.3
• /
• pp.121-129
• /
• 2024

The rapid advancement of digital technology and the COVID-19 pandemic have significantly accelerated the growth of online commerce, highlighting the need for support mechanisms that enable small business owners to effectively respond to these market changes. In response, this paper presents a foundational technology leveraging the Online to Offline (O2O) strategy to automatically capture products displayed on retail shelves and utilize these images to create virtual stores. The essence of this research lies in precisely identifying and recognizing the location and names of displayed products, for which a single-class-targeted, lightweight model based on YOLOv8, named ESD-YOLOv8, is proposed. The detected products are identified by their names through feature-point-based technology, equipped with the capability to swiftly update the system by simply adding photos of new products. Through experiments, product name recognition demonstrated an accuracy of 74.0%, and position detection achieved a performance with an F2-Score of 92.8% using only 0.3M parameters. These results confirm that the proposed method possesses high performance and optimized efficiency.

• Journal of Christian Education in Korea
• /
• v.77
• /
• pp.251-276
• /
• 2024

This study aimed to enhance the educational competencies of instructors and improve the quality of higher education by identifying instructing types, developing an assessment diagnostic tool, and designing a customized faculty training curriculum for each type. To achieve this, a literature review and Delphi research were conducted. The results are summarized as follows: First, instructing types such as 'Star Lecturer', 'Learning Mentor', and 'Designer' were identified through the analysis of previous studies. Second, a diagnostic tool for determining an instructor's type was developed by modifying and enhancing Grasha's Teaching Style Inventory, which is widely used both domestically and internationally. This tool comprises 24 questions, with 8 questions for each type. Third, a curriculum was designed for each instructing type, consisting of common courses necessary for all types and specialized courses tailored to the characteristics of each type. The common courses cover essentials for lesson design, implementation, and evaluation, while the specialized courses cater to the unique needs of each instructing type. Fourth, the developed model, tools, and curriculum underwent validation. A Delphi method was employed with a group of 10 experts, leading to revisions and finalizations based on their feedback. This study has laid the groundwork for instructors to identify their own teaching styles and receive customized training, thereby enhancing their teaching effectiveness and overall educational quality. However, further research is necessary to develop systems and mechanisms for the operationalization of these findings, including incentives for instructors and strategies for disseminating information among participants.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.19 no.4
• /
• pp.87-101
• /
• 2024

This study aims to provide insights for the efficient utilization of resources by analyzing the entrepreneurship support efficiency of Korean universities. To identify the factors influencing the number of entrepreneurs, which is the primary goal of university entrepreneurship support, a multiple regression analysis was conducted, identifying five effective independent variables. Using these five identified independent variables as input variables and the number of entrepreneurs as the output variable, the DEA method was used to analyze the efficiency of entrepreneurship support for each university as of 2023. The analysis of 150 four-year universities in Korea showed that nine universities exhibited complete efficiency in both CCR and BCC models. Among the remaining 141 universities that showed inefficiency, the cause was scale for five universities, technology for two universities, and both scale and technology for 134 universities. Regarding the returns to scale, nine universities exhibited CRS, 79 exhibited IRS, and 62 exhibited DRS. Additionally, reference groups that could serve as benchmarks for improving the efficiency of inefficient universities were identified, and target values(projections) for each variable to achieve efficiency were also presented. Despite the limitations of the DEA model, this study helps each university identify the causes of inefficiency in their entrepreneurship support and derive specific improvements to enhance efficiency. This facilitates more efficient resource management and can positively impact the ultimate goals of university entrepreneurship support, such as regional economic development and job creation.

• 대한공업교육학회지
• /
• v.40 no.1
• /
• pp.142-162
• /
• 2015

The purpose of this study are to provide the basic data materials and implementations for successful performance of electric-work field representatives of South Korean firms by identifying their roles and competency and examining their educational need. For this research purposes, three phased analysis was followed on: (1) the roles of electric-work field representatives, (2) competency of electric-work field representatives and (3) educational need for their competency. This research method was to conduct a focus group interview for 10 expert field representatives along with survey. The collected data materials were processed by MS Excel and SPSS 21.0 for statistical analysis including average, standard deviation and other basic statistics; the gap in awareness of field representatives; and need values. For the needs analysis, the difference between significance of field representatives' competency and current status was examined by t test. And the awareness gap between competency importance and current status was identified based on the Borich equation. The Locus for Focus model was employed herein to identify the kinds of competency with high importance and high inconsistency to prioritize. As a result, this research has found as follows: first, the roles of field representatives were found to be in 13 different kinds of roles. Second, electric-work field representatives were found to need to have 16 different skills. Third, regarding the 16 abilities, the gap between current status and significance was analyzed herein. The results showed statistically significant differences in all cases. The Borich needs analysis found the first required ability was communication ability followed by power of execution, conflict management ability, analytical thinking and time management ability. Also, the results of Locus for Focus model analysis displayed that the first quadrant(HH) included 7 highly-demanded abilities of communication ability, analytical thinking, decision making ability, specialty, time management ability, power of execution and drive for work implementation. The top-priority group was found to have 5 items of communication ability, analytical thinking, time management ability, power of execution and drive for work implementation which were commonly seen in the Locus for Focus model outcomes. Based on these findings, this research could identify the roles and competency of electric-work field representatives and provide the basic data materials applicable to future personal management of electricity companies including recruitment, division of work, job description, evaluation, etc. Also this research offered guidelines on demanded abilities in the field and where to place priority. The kinds of abilities with high educational demand as found in this research must be considered in designing educational programs for the competency building of field representatives. This research is expected to provide useful information in developing such educational programs for field representatives.