• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.397-403
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• 2024

North Korea's rapidly advancing drone development and operational capabilities have become a significant threat to South Korea's security. The drone incursions by North Korea in 2014, 2017, and 2022 demonstrate the technological advancement and provocative potential of North Korean drones. This study aims to closely analyze the military threats posed by North Korean drones and seek effective countermeasures. The research examines the development level of North Korean drone technology, its military applications, the characteristics and patterns of recent drone incursions, the adequacy and limitations of South Korea's current response systems, and future countermeasures. For this purpose, domestic and international research literature and media reports were reviewed, and specific North Korean drone incursion cases were analyzed. The results indicate that North Korea's small drones possess technological features such as small size, low altitude, low-speed flight, long-duration flight, and reconnaissance equipment. These drones pose threats that can be utilized for reconnaissance, surveillance, surprise attacks, and terrorism. Additionally, South Korea's current response systems reveal limitations such as inadequate detection and identification capabilities, low interception success rates, lack of an integrated response system, and insufficient specialized personnel and equipment. Therefore, this study suggests various technical, policy, and international cooperative countermeasures, including the development of drone detection and identification technologies, the utilization of diverse drone neutralization technologies, the establishment of legal and institutional foundations, the construction of a cooperative framework among relevant agencies, and the strengthening of international cooperation. The study particularly emphasizes the importance of raising awareness of the North Korean drone threat across South Korean society and unifying national efforts to respond to these threats.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.405-411
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• 2024

This study aims to address the sustainability of South Korea's conscription system, which is being questioned due to issues like low birth rates and societal changes, and to explore the necessity and implementation strategies for transitioning to an all-volunteer force (AVF). South Korea has long maintained national security through conscription, but it now faces challenges such as a decrease in military resources and the advancement of high-tech military technologies. To address these challenges, the study analyzes domestic and international cases of AVF and assesses the current state and issues of South Korea's military service system. The findings indicate that an AVF can enhance military professionalism and efficiency, respect individual choice, and contribute to reducing gender imbalance and promoting social equity. A phased roadmap for the implementation of the AVF is proposed, along with the need for legal and institutional frameworks and measures to foster public consensus. The study also discusses the potential positive economic impacts and long-term cost savings of the AVF. This research aims to provide concrete strategies and policy recommendations for adopting a Korean-style AVF, thereby proactively responding to changes in the future security environment and establishing a sustainable national defense posture.

• The Journal of Bigdata
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• v.8 no.2
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• pp.1-13
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• 2023

Current analysis of air passengers mainly relies on statistical methods, but there are limitations in analyzing detailed aspects such as travel routes, number of regional passengers and airport access times. However, with the advancement of big data technology and revised three data acts, big data-based transportation analysis has become more active. Mobile communication data, which can precisely track the location of mobile phone terminals, can serve as valuable analytical data for transportation analysis. In this paper, we propose a air passenger Origin/Destination (O/D) extraction algorithm based on mobile communication data that overcomes the limitations of existing air transportation user analysis methods. The algorithm involves setting airport signal detection zones at each airport and extracting air passenger based on their base station connection history within these zones. By analyzing the base station connection data along the passenger's origin-destination paths, we estimate the entire travel route. For this paper, we extracted O/D information for both domestic and international air passengers at all domestic airports from January 2019 to December 2020. To compensate for errors caused by mobile communication service provider market shares, we applied a adjustment to correct the travel volume at a nationwide citizen level. Furthermore correlation analysis was performed on O/D data and aviation statistics data for air traffic users based on mobile communication data to verify the extracted data. Through this, there is a difference in the total amount (4.1 for domestic and 4.6 for international), but the correlation is high at 0.99, which is judged to be useful. The proposed algorithm in this paper enables a comprehensive and detailed analysis of air transportation users' travel behavior, regional/age group ratios, and can be utilized in various fields such as formulating airport-related policies and conducting regional market analysis.

• Journal of Service Research and Studies
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• v.14 no.3
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• pp.206-230
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• 2024

Background: The advancement of information and communication technology acts as a key driver in the implementation of smart cities. Smart Public Facilities leverage this technological progress to innovate urban operations, optimizing various city functions, enhancing the quality of public services, and improving citizens' accessibility and convenience. These Smart Public Facilities are introduced for the sustainable development of cities and the enhancement of citizens' quality of life. Method: This study systematically analyzed the public design policies of local governments and examined the use cases of Smart Public Facilities domestically and internationally to evaluate their functions and roles. Through this, the effectiveness and sustainability of public design policies were comprehensively reviewed, and the impact of Smart Public Facilities on urban operations and citizens' lives was analyzed from multiple perspectives. Results: The introduction of Smart Public Facilities significantly enhances the implementation and efficiency of public design policies, playing a crucial role in sustainable urban development and improving citizens' quality of life. Furthermore, positive impacts were observed in various areas such as energy management, transportation systems, and environmental monitoring. Major challenges included managing technological changes, ensuring data privacy and cybersecurity, and strengthening citizen participation. Conclusion: Smart Public Facilities serve as essential infrastructure for improving urban efficiency, sustainability, and citizens' quality of life. Successful implementation and operation require systematic management and citizen participation. Through this, Smart Public Facilities will support sustainable urban development and play a critical role in responding to environmental changes. To ensure that Smart Public Facilities function effectively as urban infrastructure, it is necessary to comprehensively evaluate their impact on the efficiency of public design policies, sustainability, citizens' quality of life, and the local economy, and to suggest concrete measures for their introduction and operation.

• The Mathematical Education
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• v.63 no.3
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• pp.467-484
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• 2024

The rapid advancement of generative AI has ushered in an era where anyone can create and freely utilize personalized chatbots without the need for programming expertise. This study aimed to develop a customized chatbot based on OpenAI's GPTs for the purpose of pre-service teacher education and to analyze its educational performance in mathematics as assessed by educators guiding pre-service teachers. Responses to identical questions from a general-purpose chatbot (ChatGPT), a customized GPTs-based chatbot, and an elementary mathematics education expert were compared. The expert's responses received an average score of 4.52, while the customized GPTs-based chatbot received an average score of 3.73, indicating that the latter's performance did not reach the expert level. However, the customized GPTs-based chatbot's score, which was close to "adequate" on a 5-point scale, suggests its potential educational utility. On the other hand, the general-purpose chatbot, ChatGPT, received a lower average score of 2.86, with feedback indicating that its responses were not systematic and remained at a general level, making it less suitable for use in mathematics education. Despite the proven educational effectiveness of conventional customized chatbots, the time and cost associated with their development have been significant barriers. However, with the advent of GPTs services, anyone can now easily create chatbots tailored to both educators and learners, with responses that achieve a certain level of mathematics educational validity, thereby offering effective utilization across various aspects of mathematics education.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.58-66
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• 2024

Robotics is a convergence technology with significant ripple effects across various industries, including manufacturing and services. Its importance has been increasingly underscored by advancements in artificial intelligence. As a crucial industry for addressing the challenges posed by a declining and aging production workforce and for enhancing manufacturing competitiveness, the training of robotics experts is now critically important. This paper examines the case of the Robot Job Innovation Center in Gumi City and proposes a strategy for training robotics experts and specialists in robot/AI-based signal processing. A core curriculum was carefully selected and implemented in actual educational settings, with key components necessary for developing a comprehensive educational framework detailed. The convergence of AI-based data signal processing and robotics represents a significant technological advancement poised to impact a wide array of industries. By proposing the comprehensive educational framework outlined in this paper, it is anticipated that related organizations will be able to effectively utilize these foundational elements to train experts in the field.

• Korean Journal of Culture and Social Issue
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• v.30 no.3
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• pp.267-298
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• 2024

Childcare support for working mothers is crucial for women's smooth transition into society, career development, and well-being. Based on interviews with 10 Korean working mothers with children aged 0-2, this paper explores the process of utilizing childcare support services, psychological experiences, and plans for work-life balance using the grounded theory analysis method. The analysis revealed three categories: the decision-making process before using the childcare services (past), experiences during the use of childcare support (present), and future plans for work-life balance (future). The decision-making process before using childcare support services consisted of the following categories: seeking information about childcare support services, having family discussions during the decision-making process, the proposer and decision-maker of the services, and the final decision on childcare support services. Experiences during the use of services included economic burdens, changes in postnatal career paths, disparities between expectations and the reality of pre- and post-childbirth, discrepancies between expectations and reality in work-family balance, factors affecting of quality of life, and the division of household and childcare responsibilities with husbands. Plans for future work-life balance included categories such as the desire for career advancement, the desire to maintain a career, the desire for temporary or reduced career commitment, and uncertainty regarding future career plans. Finally, the study investigated whether there were differences in the past and present service usage processes and experiences based on plans for future work-life balance. This research suggests the need for multidimensional support for working mothers' work-family balance and well-being, and highlights the need to reduce uncertainty about women's future careers.

• Information Systems Review
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• v.26 no.1
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• pp.93-117
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• 2024

In February 2022, the EU announced a draft of the EU Corporate Sustainability Due Diligence Directive requiring due diligence and disclosure of information on environmental and human rights risks in corporate supply chains. This study evaluated the ability of 13 Korean pharmaceutical/bio companies to respond to the EU's demand for due diligence in the supply chain and compared it to 13 globally leading pharmaceutical/bio companies which are considered good in environmental and human rights risk management. For comparative analysis, text mining analysis was performed using R. Basic word frequency and concurrent words were analyzed and topic modeling was performed by applying Latent Dirichlet Allocation. As a result of the analysis, it was found that compared to advanced companies, domestic pharmaceutical and bio companies lack negative issue reporting and identification systems and supply chain due diligence implementation processes, and require advancement of data management for environmental and human rights information disclosure. Accordingly, domestic pharmaceutical and bio companies need to prepare differentiated support measures to systematically identify and reduce risks in the supply chain of small and medium-sized businesses beyond simply providing financial support. It is also desirable for the government to provide policy support by mandating Korea's own supply chain environment and human rights due diligence system, along with support for strengthening the ability to respond to due diligence of domestic pharmaceutical and bio companies, such as expert consulting and financial support.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.631-643
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• 2024

With the rapid advancement of digital technology, unmanned store services are on the rise, yet studies investigating their impact on customer satisfaction are scarce. This study aims to explore how unmanned store services affect customer satisfaction, focusing on the factors of risk and benefit. The methodology involved an online survey conducted from December 20 to December 30, 2023, targeting 260 customers who had used unmanned store self-service at least once, with 252 responses ultimately analyzed. The results reveal that the risk and benefit factors of unmanned store self-services complexly and diversely influence subjective norms and perceived control. Firstly, personal information breaches positively affected subjective norms, while overload and uncertainty had negative impacts. Secondly, while convenience negatively influenced subjective norms, playfulness and usefulness had positive effects. However, personal breaches and overload did not affect perceived control, whereas uncertainty did negatively. The findings of this study provide significant insights into how successful implementation and management of unmanned store self-services can regulate social expectations and control perception of customers, thereby enhancing customer satisfaction.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.5
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• pp.51-65
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• 2024

With the advancement of Unmanned Aerial Vehicles (UAV) technology, aerial spraying has been rapidly increasing in the agricultural field. Drones offer many advantages compared to traditional applicators, but they pose challenges such as spray drift risk and spray uniformity. To address these issues, it is essential to understand the characteristics of complex airflow generated by drones and its consequences for the spray performance. This study aims to identify the air velocity distribution of drone downwash and the resulting spray deposition distribution on the ground, ultimately proposing optimized spraying widths and criteria. Experiments were conducted using two agricultural drones with different propeller arrangements under various flight and measurement conditions. The results showed that during hovering, the downward airflow affected the area within a distance of the radius of the blade (R) from the center of the drone. When the drone was flying, the downward airflow was effective up to a distance of 2R. Droplet deposition was concentrated at the center of the drone during hovering. However, during flying, the droplet deposition was more evenly distributed up to the distance of R. The drone downwash and droplet deposition were significantly different during flying compared to the hovering state. At an effective spray width of 3R, the coefficient of variation (CV) was generally less than 16%, indicating a significant improvement in spray uniformity. These findings help optimize effective spraying techniques in drone-based applications.