• The Journal of Korean Society for School & Community Health Education
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• v.25 no.1
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• pp.1-15
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• 2024

Objectives: This study aims to examine the general characteristics and physical activity characteristics of young and middle-aged individuals with hypertension, with the goal of identifying key influencing factors and providing public health policy recommendations. Methods: Participants in this study used data from the 2021 Community Health Survey. The study participants include 5,511 individuals diagnosed with hypertension in the young and middle-aged group (aged 19 to 49). The collected data were analyzed using SPSS 26.0. Results: Model 1 is the influencing factors of young and middle-aged hypertensive patients according to general characteristics. The explanatory power is R²= .065. The influencing factors are as follows. Economic activity (𝛽= -.219, p<.001), breakfast per week (𝛽= .117, p<.001), gender (𝛽= .090, p<.001), subjective health status (𝛽= .073, p<.001), and education level (𝛽= .069, p<.001). Model 2 is the influencing factors of young and middle-aged hypertensive patients, including physical activity characteristics. The explanatory power is R²= .076. The influencing factors are as follows. Strength exercises (𝛽= -4.791, p<.001), the walking activity (𝛽= -2.694, p<.01), and the high-intensity physical activity (𝛽= -2.629, p<.01). Conclusion: The active management of young and middle-aged hypertension is essential to prevent progression to serious disease. To prevent hypertension in young and middle-aged people, health education is needed to develop and utilize health promotion programs that take into account general characteristics and physical activity characteristics.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.199-205
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• 2024

Purpose: This study aims to improve the recognition rate of Auto People Counting (APC) in accurately identifying and providing information on remaining evacuees in disaster-vulnerable facilities such as nursing homes to firefighting and other response agencies in the event of a disaster. Methods: In this study, a baseline model was established using CNN (Convolutional Neural Network) models to improve the algorithm for recognizing images of incoming and outgoing individuals through cameras installed in actual disaster-vulnerable facilities operating APC systems. Various algorithms were analyzed, and the top seven candidates were selected. The research was conducted by utilizing transfer learning models to select the optimal algorithm with the best performance. Results: Experiment results confirmed the precision and recall of Densenet201 and Resnet152v2 models, which exhibited the best performance in terms of time and accuracy. It was observed that both models demonstrated 100% accuracy for all labels, with Densenet201 model showing superior performance. Conclusion: The optimal algorithm applicable to APC among various artificial intelligence algorithms was selected. Further research on algorithm analysis and learning is required to accurately identify the incoming and outgoing individuals in disaster-vulnerable facilities in various disaster situations such as emergencies in the future.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.47-59
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• 2024

Purpose: This study aims to propose measures for the prevention of fire and explosion accidents within manufacturing facilities by improving the existing classification criteria for hazardous locations based on the leakage patterns of flammable liquids. The objective is to suggest ways to safely manage ignition sources and combustible materials. Method: The hazardous locations were calculated using "KS C IEC 60079-10-1," and the calculated explosion hazard distances were visualized in 3D. Additionally, the formula for the atmospheric dispersion of flammable vapors, as outlined in "P-91-2023," was utilized to calculate the dispersion rates within the hazardous locations represented in 3D. Result: Visualization of hazardous locations in 3D enabled the identification of blind spots in the floor plan, facilitating immediate recognition of ignition sources within these areas. Furthermore, when calculating the time taken for the Lower Explosive Limit (LEL) to reach within the volumetric space of the hazardous locations represented in 3D, it was found that the risk level did not correspond identically with the explosion hazard distances. Conclusion: Considering the atmospheric dispersion of flammable liquids, it was concluded that safety management should be conducted. Therefore, a method for calculating the concentration values requiring detection and alert based on realistically achievable ventilation rates within the facility is proposed.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.69-81
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• 2024

Purpose: Recently, there has been a movement to guarantee the right to watch sports for the disabled. However, the sports stadium is designed without considering the wheelchair users, so the right to move in the stadium is not secured. Restrictions on the movement of the disabled make the evacuation vulnerable in an emergency. This study aims to develop a plan to ensure the safety of movement and evacuation of wheelchair users by conducting simulations targeting indoor sports stadiums. Method: The simulation was performed by constructing a scenario with the shape of the stands as a variable. The effect of the installation of wheelchair seats on evacuation was confirmed. Result: The results according to whether wheelchair seats are installed, the evacuation route of wheelchair movement, and whether wheelchair seats are separately arranged were compared. The impact of wheelchair seat installation on evacuation and its characteristics were derived. As a result, upward and separation seat was the most vulnerable to evacuation. Conclusion: A plan to secure evacuation performance was derived for the top floors of upward and separation seat. It is judged that the content can be use as a way to secure the safety of movement and evacuation of the disabled in sports stadiums.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.93-105
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• 2024

Purpose: This study aims to quantitatively determine the impact on nearby risidents by selecting the amount of chemicals emitted from the workplace among the substances subject to the chemical emission plan and predicting the concentration with the atmospheric diffusion program. Method: The selection of research materials considered half-life, toxicity, and the presence or absence of available monitoring station data. The areas discharged from the materials to be studied were selected as the areas to be studied, and four areas with floating populations were selected to evaluate health risks. Result: AERMOD was executed after conducting terrain and meteorological processing to obtain predicted concentrations. The health hazard assessment results indicated that only dichloromethane exceeded the threshold for children, while tetrachloroethylene and chloroform appeared at levels that cannot be ignored for both children and adults. Conclusion: Currently, in the domestic context, health hazard assessments are conducted based on the regulations outlined in the "Environmental Health Act" where if the hazard index exceeds a certain threshold, it is considered to pose a health risk. The anticipated expansion of the list of substances subject to the chemical discharge plan to 415 types by 2030 suggests the need for efficient management within workplaces. In instances where the hazard index surpasses the threshold in health hazard assessments, it is judged that effective chemical management can be achieved by prioritizing based on considerations of background concentration and predicted concentration through atmospheric dispersion modeling.

• Information Systems Review
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• v.25 no.2
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• pp.77-101
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• 2023

Due to COVID-19, paid virtual live-stream concerts have emerged as an alternative format and a new revenue model for in-person live concerts. Despite the increasing scholarly and practical interest in how participants experience paid virtual live-stream concerts, few studies examined participants' consumption and participation experiences. Thus, this study aims to provide insights into consumers' virtual live-stream concert experience by employing social representations theory (SRT). We explore the features of paid virtual live-stream concerts based on the C-P-N-D (Content-Platform-Network-Device) framework and the consumers' cognitive and affective perception. To this end, an SRT-based core-periphery analysis was conducted based on 239 responses to the open-ended survey questions. The results show that network-and device-level features of virtual live concerts and participants' overall perception are presented as core elements of paid virtual live-stream concerts, whereas content- and platform-level features are peripheral elements. This finding provides an in-depth understanding of the emergence of paid virtual live-stream concerts as an alternative concert format, thereby providing an invaluable understanding of a virtual live concert experience and theoretical and practical insights.

• Knowledge Management Research
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• v.25 no.1
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• pp.89-109
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• 2024

The development of digital technology has given rise to a new service model: self-service. This model introduces the concept of "digital shadow work", in which consumers conduct unpaid behind-the-scenes digital tasks instead of employees. While consumers are engaging in increasingly more digital shadow work in self-service environments, they are unaware of their unpaid labor. This raises concerns about consumer rights and businesses' long-term sustainability and health. This study aims to reveal the psychological awareness factors that influence consumers' decisions to engage in digital shadow work in self-service environments. This exploratory qualitative study utilizes a grounded theory approach and semi-structured interviews to reveal the psychological awareness factors that contribute to consumers' decision to engage in digital shadow work. By revealing the psychological awareness of decision-making factors, this study enhances consumer's understanding and awareness of digital shadow work, which helps increase their awareness of self-protection in the context of self-service technologies. Additionally, understanding consumers' decision-making psychology is crucial for non-face-to-face self-service technology companies and provides a theoretical basis for sustainable and healthy business development.

• Knowledge Management Research
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• v.25 no.1
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• pp.173-192
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• 2024

This study aims to understand the changes in the beauty industry due to the pandemic from the consumer's perspective based on consumers' opinions about their skin online before and after the pandemic. Furthermore, this study tries to derive strategies for companies and governments to support sustainable growth and innovation in the beauty industry. To this end, posts on social media from 2017 to 2022 that contained the keyword 'skin concerns' are collected, and after data preprocessing, 96,908 posts are used for the structural topic model. To examine whether consumers' interest areas related to skin change according to the pandemic situation, the analysis period is divided into 7 periods, and the variables that distinguish each stage are used as meta-variables for the structural topic model. As a result, it is found that consumers' interests can be divided into 22 topics, which can be categorized into four main categories: beauty manufacturing, beauty services, skin concerns, and other. The results of this study are expected to be utilized in construction of product development and marketing strategies of related companies and the establishment of economic support policies by the government in response to changes in demand in the beauty industry due to the pandemic.

• Knowledge Management Research
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• v.25 no.1
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• pp.193-215
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• 2024

This study aims to identify the main factors that caused the digital divide during the COVID-19 pandemic. Utilizing data from the 2020 and 2021 Digital Divide Surveys by the National Information Agency, a research model was constructed for analysis using SmartPLS 4, applying PLS-SEM and Multigroup Analysis methods. The results of the study are as follows. First, combining 2020 and 2021, mobile internet usage during COVID-19 is positively associated with digital skills, digital usage, and usage outcomes except for networking. Second, the impact of digital usage was significantly higher during the outbreak than during the beginning of COVID-19, which may be due to the increased demand for digital usage as the outbreak continued, and the corresponding increase in internet usage. Third, we discovered that demographics are not the main factor affecting changes in mobile internet use during the COVID-19 pandemic. Instead, digital literacy affects mobile usage, which is the most important one. The results show the importance of creating programs to teach people how to use technology appropriately. We propose that digital literacy should be central to training programs for people who use digital services.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.1
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• pp.10-20
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• 2024

RNA-sequencing (RNA-seq) is a technique used for providing global patterns of transcriptomes in samples. However, it can only provide the average gene expression across cells and does not address the heterogeneity within the samples. The advances in single-cell RNA sequencing (scRNA-seq) technology have revolutionized our understanding of heterogeneity and the dynamics of gene expression at the single-cell level. For example, scRNA-seq allows us to identify the cell types in complex tissues, which can provide information regarding the alteration of the cell population by perturbations, such as genetic modification. Since its initial introduction, scRNA-seq has rapidly become popular, leading to the development of a huge number of bioinformatic tools. However, the analysis of the big dataset generated from scRNA-seq requires a general understanding of the preprocessing of the dataset and a variety of analytical techniques. Here, we present an overview of the workflow involved in analyzing the scRNA-seq dataset. First, we describe the preprocessing of the dataset, including quality control, normalization, and dimensionality reduction. Then, we introduce the downstream analysis provided with the most commonly used computational packages. This review aims to provide a workflow guideline for new researchers interested in this field.