• Asia pacific journal of information systems
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• v.30 no.1
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• pp.167-187
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• 2020

College students experience more cyber bullying than youth and cyber bullying on college students may be more harmful than youth. But many studies of cyber bullying have been conducted in youth, but little has been studied for college students. Therefore, this study investigated the negative effects of college students' cyber bullying experience on cognitive processing ability and emotional states. The social support of friends has a buffering effect that prevents stress and reduces the influence on external damage in stressful situations. But the impact of parental social support is controversial. Traditionally, the social support of parents has been claimed to mitigate the negative effects of external damage. Recently, however, it has been argued that parental social support, without considering the independence and autonomy needs of college students, does not alleviate the negative effects. Therefore, this study examined how the social support of friends and parents moderate the negative impact of cyber bullying. The results show that the more college students experience cyber bullying, the lower their cognitive processing ability and emotional states. And, the higher the social support of friends, the lower the harmful impacts of cyber bullying on cognitive processing ability and emotional states. But, the higher the social support of parents, the higher the harmful impacts of cyber bullying on cognitive processing ability and emotional states.

• The Journal of Information Systems
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• v.33 no.2
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• pp.1-25
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• 2024

Purpose Live commerce, a real-time product promotion method using portable hardware, is experiencing significant growth. This approach involves product experts or celebrities endorsing products, providing consumers with valuable information to mitigate uncertainty. This research underscores the significance of the seller's authenticity and their value similarity with consumers in live commerce. The study's first objective enhance the seller's authenticity and elucidate the mechanism that influences purchase intention. The second objective is to demonstrate the interactive effect of value similarity and the seller's authenticity on positively influencing purchase intention. Design/methodology/approach This research utilized previous studies to develop models and hypotheses, focusing on adults experienced in live commerce product purchasing. The study tested the research hypothesis using 330 samples. The study analyzed the path from seller authenticity to purchase intention via structural equation modeling (AMOS 22.0), and also explored the interaction between value similarity and seller authenticity using the Process 3.1 macro. Findings The research validates that the seller's channel activities and external perception amplify the seller's authenticity, influencing purchase intentions. It also affirms that value similarity fosters seller authenticity and interactive effects, thereby boosting purchase intentions. These findings provide insights for devising seller management strategies on live commerce platforms.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.269-279
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• 2024

The study explores the evolving landscape of overseas expansion strategies by Korean corporations, focusing on recent geopolitical tensions, the COVID-19 pandemic, and disruptions in global supply chains. It emphasizes the challenges faced by industries producing high-value products and delves into the concept of "Friend-Shoring" policies in the United States, leading major Korean companies to invest in local semiconductor, battery, and automotive factories. Recognizing the potential fragmentation of Korea's manufacturing sector, the paper introduces the "Mother Factory" strategy as a policy initiative, inspired by Japan's model, to establish core production facilities domestically. The discussion unfolds by examining the cases of major companies in Japan and the United States, highlighting the need for Korea to adopt a mother factory strategy to mitigate risks associated with friend-shoring policies. Inspired by Intel's "Copy Exactly" approach, the paper proposes a Korean mother factory model integrating smart factory technology and digital twin systems. This strategic shift aims to enhance responsiveness to geopolitical challenges and fortify the competitiveness of Korean high-tech industries. Finally, the paper proposes a Korean Mother Factory based on smart factory concepts. The suggested model integrates smart factory technology and digital twin frameworks to enhance responsiveness and fortify competitiveness. In conclusion, the paper advocates for the adoption of a comprehensive Korean Mother Factory model to address contemporary challenges, foster advanced manufacturing, and ensure the sustainability and competitiveness of Korean high-tech industries in the global landscape. The proposed strategy aligns with the evolving dynamics of the manufacturing sector and emphasizes technological advancements, collaboration, and strategic realignment.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.61-68
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• 2024

In the quest for advancing diabetes diagnosis, this study introduces a novel two-step machine learning approach that synergizes the probabilistic predictions of Logistic Regression with the classification prowess of Random Forest. Diabetes, a pervasive chronic disease impacting millions globally, necessitates precise and early detection to mitigate long-term complications. Traditional diagnostic methods, while effective, often entail invasive testing and may not fully leverage the patterns hidden in patient data. Addressing this gap, our research harnesses the predictive capability of Logistic Regression to estimate the likelihood of diabetes presence, followed by employing Random Forest to classify individuals into diabetic, pre-diabetic or nondiabetic categories based on the computed probabilities. This methodology not only capitalizes on the strengths of both algorithms-Logistic Regression's proficiency in estimating nuanced probabilities and Random Forest's robustness in classification-but also introduces a refined mechanism to enhance diagnostic accuracy. Through the application of this model to a comprehensive diabetes dataset, we demonstrate a marked improvement in diagnostic precision, as evidenced by superior performance metrics when compared to other machine learning approaches. Our findings underscore the potential of integrating diverse machine learning models to improve clinical decision-making processes, offering a promising avenue for the early and accurate diagnosis of diabetes and potentially other complex diseases.

• Korean Journal of Radiology
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• v.24 no.10
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• pp.952-959
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• 2023

Large language models (LLMs) such as ChatGPT have garnered considerable interest for their potential to aid non-native English-speaking researchers. These models can function as personal, round-the-clock English tutors, akin to how Prometheus in Greek mythology bestowed fire upon humans for their advancement. LLMs can be particularly helpful for non-native researchers in writing the Introduction and Discussion sections of manuscripts, where they often encounter challenges. However, using LLMs to generate text for research manuscripts entails concerns such as hallucination, plagiarism, and privacy issues; to mitigate these risks, authors should verify the accuracy of generated content, employ text similarity detectors, and avoid inputting sensitive information into their prompts. Consequently, it may be more prudent to utilize LLMs for editing and refining text rather than generating large portions of text. Journal policies concerning the use of LLMs vary, but transparency in disclosing artificial intelligence tool usage is emphasized. This paper aims to summarize how LLMs can lower the barrier to academic writing in English, enabling researchers to concentrate on domain-specific research, provided they are used responsibly and cautiously.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.644-654
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• 2024

After the Tohoku earthquake and tsunami (Japan, 2011), regulatory efforts to mitigate external hazards have increased both the safety requirements and the total capital cost of nuclear power plants (NPPs). In these circumstances, identifying not only disaster robustness but also cost-effective capacity setting of NPPs has become one of the most important tasks for the nuclear power industry. A few studies have been performed to relocate the seismic capacity of NPPs, yet the effects of multiple hazards have not been accounted for in NPP capacity optimization. The major challenges in extending this problem to the multihazard dimension are (1) the high computational costs for both multihazard risk quantification and system-level optimization and (2) the lack of capital cost databases of NPPs. To resolve these issues, this paper proposes an effective method that identifies the optimal multihazard capacity of NPPs using a multi-objective genetic algorithm and the two-stage direct quantification of fault trees using Monte Carlo simulation method, called the two-stage DQFM. Also, a capacity-based indirect capital cost measure is proposed. Such a proposed method enables NPP to achieve safety and cost-effectiveness against multi-hazard simultaneously within the computationally efficient platform. The proposed multihazard capacity optimization framework is demonstrated and tested with an earthquake-tsunami example.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1234-1243
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• 2024

The pressing need to mitigate greenhouse gas emissions has stimulated a renewed interest in nuclear energy worldwide. However, while numerous countries have shown interest in nuclear power over the course of history, many of them have not continued their pursuit and chosen to defer or abandon their peaceful nuclear power projects. Scrapping a national nuclear power program after making initial efforts implies significant challenges in such a course or a waste of national resources. Therefore, this study aims to identify the crucial factors that influence a country's decision to terminate or hold off its peaceful nuclear power programs. Our empirical analyses demonstrate that major nuclear accidents and leadership changes are significant factors that lead countries to terminate or defer their nuclear power programs. Additionally, we highlight that domestic politics (democracy), lack of military alliance with major nuclear suppliers, low electricity demand, and national energy security environments (energy import, crude oil price) can hamper a country's possibility of regaining interest in a nuclear power program after it has been scrapped, suspended, or deferred. The findings of this study have significant implications for policymakers and stakeholders in the energy sector as they strive to balance the competing demands of energy security, and environmental sustainability.

• Journal of the Korean Society of Safety
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• v.39 no.2
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• pp.9-21
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• 2024

Static-electricity-induced fires and explosions persistently occur every year, averaging approximately 80 and 20 cases annually according to fire statistics provided by the National Fire Agency and industrial accident statistics provided by the Ministry of Employment and Labor, respectively. Despite the relatively low probabilities of these accidents, their potential risks are high. Consequently, effective risk assessment methodologies and accident investigation strategies are essential for efficiently managing static-electricity hazards in fire- and explosion-prone areas. Accordingly, this study aimed to identify the causal variables essential for accident investigations, thereby facilitating risk assessments and the implementation of effective recurrence prevention measures to mitigate static-electricity hazards in fire-and explosion-prone regions. To this end, industrial accident statistics recorded over the past decade (2012 to 2021) by the Ministry of Employment and Labor were analyzed to identify major fire and explosion incidents and related industrial accidents wherein static electricity was identified as a potential ignition source. Subsequently, relevant investigation reports (63 cases) were thoroughly analyzed. Based on the results of this analysis, existing electrostatic fire and explosion risk assessment techniques were refined and augmented. Moreover, factors essential for investigating electrostatic fire and explosion disasters were delineated, and the primary causal variables necessary for effective risk assessments and scientific investigations were derived.

• Journal of Korean Society of Water and Wastewater
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• v.38 no.2
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• pp.61-68
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• 2024

In the context of the Ministry of Environment's 2022 Climate Change Adaptation Plan for Public Institutions, public sewage treatment plants are one of the important targets for climate change response aimed at sustainable water management. In this study, it is applied a modified methodology to four water regeneration centers (public sewage treatment facilities) in charge of sewage treatment in Seoul to analyze the impacts and risks of climate change and discuss priorities for adaptation measures. The results of the study showed that heavy rains, heat waves, and droughts will be the key impacts of climate change, and highlighted the need for measures to mitigate these risks, especially for facility managers.

• Journal of Distribution Science
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• v.22 no.7
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• pp.83-94
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• 2024

Purpose: This article aims to investigate the influence of pricing and distribution on the level of satisfaction and purchase decisions among consumers of pharmaceutical products in Kazakhstan. Research design, data, and methodology: A mixed-methods research design was utilized, incorporating primary and secondary data. Primary data were collected through a survey administered to customers across various pharmacy types, with 100 valid responses analyzed. Secondary data involved an extensive review of existing literature and analysis of national statistics concerning the pharmaceutical market trends from 2008 to 2022. Results: The results reveal a complex relationship between price perceptions and customer satisfaction. A significant segment of the population views current drug prices as high, which affects their satisfaction levels and purchase decisions. The study also highlights the importance of service quality in enhancing customer satisfaction, suggesting that service improvements could mitigate some of the negative perceptions of pricing. Conclusions: This research contributes to the limited but growing body of knowledge on the impact of pricing strategies on consumer satisfaction in the pharmaceutical sectors of developing countries like Kazakhstan. Focusing on economic and behavioral aspects, this study provides a more holistic understanding of the factors driving consumer satisfaction and purchase behaviors in this critical sector.