• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.41-57
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• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.28-41
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• 2022

A road system with CV(Connected Vehicle)s, which is often referred to as a cooperative intelligent transportation system (C-ITS), provides various road information to drivers using an in-vehicle warning system. Road environments with CVs induce drivers to reduce their speed or change lanes to avoid potential risks downstream. Such avoidance maneuvers can be considered to improve driving behaviors from a traffic safety point of view. Thus, empirically evaluating how a given in-vehicle warning information affects driving behaviors, and monitoring of the correlation between them are essential tasks for traffic operators. To quantitatively evaluate the effect of in-vehicle warning information, this study develops a method to calculate compliance rate of drivers where two groups of speed profile before and after road information is provided are compared. In addition, conventional indexes (e.g., jerk and acceleration noise) to measure comfort of passengers are examined. Empirical tests are conducted by using PVD (Probe Vehicle Data) and DTG (Digital Tacho Graph) data to verify the individual effects of warning information based on C-ITS constructed in Seoul metropolitan area in South Korea. The results in this study shows that drivers tend to decelerate their speed as a response to the in-vehicle warning information. Meanwhile, the in-vehicle warning information helps drivers to improve the safety and comport of passengers.

• Knowledge Management Research
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• v.24 no.3
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• pp.173-193
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• 2023

Digital transformation and the COVID-19 pandemic have facilitated the rapid development and dissemination of non-face-to-face technologies such as self-service technologies (SSTs). This research investigates how motivation factors affect consumers' negative responses to digital shadow work (DSW) in SSTs which decreases their continuous use intention of SSTs. Also, we examine whether the grafication delay ability moderates the relationship between consumers' negative responses to DSW and their continuous use intention of SSTs. By an analysis of usable 450 user respondents via SmartPLS 4.0, perceived benefits was found to significantly influence consumers' negative responses to DSW. Also, consumers' negative responses to DSW can significantly decrease their intention to continue using SSTs. Further, the effect of negative responses to DSW on continuous use intention of SSTs is stronger in case of consumers with low gratification delay ability than in case of consumers with high gratification delay ability. The study findings contribute to providing some strategies for companies operating SSTs by examining the effects of consumer's responses to DSW and gratification delay ability on the continuous usage intention of SSTs.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.837-842
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• 2023

This study analyzed the awareness and actual condition on metaverse utilization in education for design major students. An online survey was conducted for 14 days from May 10 to 23, 2023, targeting 120 students majoring in design at D University. The evaluation method of the questionnaire was a nominal scale and a 5-point scale, and the questionnaire results were analyzed through SPSS 29.0. First, it is necessary to sufficiently share the advantages of metaverse utilization in education with students, and to provide basic literacy programs utilizing the characteristics of metaverse and supporting class activities. Second, students' response will be higher in studio classes where practical training is conducted rather than information delivery or understanding-oriented lectures. Third, in order for the metaverse to become a means of education in the digital transformation era rather than just a temporarily medium in COVID-19 era, specific and systematic design education programs reflecting the characteristics of the metaverse need to be continuously developed. In addition, it is important for instructors to actively review the use of the metaverse and search for various ways to utilize it.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.843-856
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• 2023

The global surge in maritime traffic has resulted in an increased number of ship collisions, leading to significant economic, environmental, physical, and human damage. The causes of these maritime accidents are multifaceted, often arising from a combination of crew judgment errors, negligence, complexity of navigation routes, weather conditions, and technical deficiencies in the vessels. Given the intricate nuances and contextual information inherent in each incident, a methodology capable of deeply understanding the semantics and context of sentences is imperative. Accordingly, this study utilized the SentenceBERT model to analyze maritime safety tribunal decisions over the last 20 years in the Busan Sea area, which encapsulated data on ship collision incidents. The analysis revealed important keywords potentially responsible for these incidents. Cluster analysis based on the frequency of specific keyword appearances was conducted and visualized. This information can serve as foundational data for the preemptive identification of accident causes and the development of strategies for collision prevention and response.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.224-239
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• 2023

C-ITS (Cooperative-Intelligent Transportation System) refers to user safety-oriented technology and systems that provide forward traffic situation information based on a two-way wireless communication technology between vehicles or between vehicles and infrastructure. Since the Daejeon-Sejong pilot project in 2016, the C-ITS infrastructure has been installed at various locations to provide C-ITS safety services through highway and local government demonstration projects. In this study, a methodology was developed to verify the effectiveness of the warning information using individual vehicle data collected through the Gwangju Metropolitan City C-ITS demonstration project. The analysis of the effectiveness was largely divided into driving behavior impact analysis and environmental analysis. Compliance analysis and driving safety evaluation were performed for the driving impact analysis. In addition, to supplement the inadequate collection of Probe Vehicle Data (PVD) collected during the C-ITS demonstration project, Digital Tacho Graph ( DTG ) data was additionally collected and used for effect analysis. The results of the compliance analysis showed that drivers displayed reduced driving behavior in response to warning information based on a sufficient number of valid samples. Also, the results of calculating and analyzing driving safety indicators, such as jerk and acceleration noise, revealed that driving safety was improved due to the provision of warning information.

• The Korean Journal of Quaternary Research
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• v.34 no.1
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• pp.41-51
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• 2024

The Sincheon wetland shows a remarkable diversity of fluvial landforms, such as river islands, anastomosing channels, braided channels, and sand-gravel bars, which contribute to its rich ecological habitat. The wetland area is characterized by a ecological diversity of herbaceous and woody plants. Significant changes in land cover within the wetlands were observed from 2008 to 2020. Notably, there was a rapid decrease in agricultural area from 18% to 0.04%, while the vegetation area expanded from 45% to 54%. Concurrently, the water area also experienced a notable increase from 34% to 41%. The surface sediment composition in the studied area displays sandy loam characteristics and exhibits acidic soil properties. Sediment acidity tends to increase downstream and in the central part of channels. Variations in acidity are also observed at nearby collection sites due to the tributaries and local discharge. The presence of dense vegetation in river islands and bars has led to a significant transformation of sediments into soil, with this change being more pronounced downstream, particularly near the weirs. The installation of a weir in Sincheon wetland is believed to have a significant impact on altering flow velocities between upstream and downstream sections, as well as influencing erosion and sediment deposition patterns. However, given the formation of landforms in response to weirs, effective administration and management are essential to address potential risks of catastrophic environmental disruptions, such as the removal of weirs and/or the maintenance of river channels.

• Knowledge Management Research
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• v.25 no.1
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• pp.135-154
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• 2024

As the digital transformation accelerates, the demand for professionals with competencies in various digital technologies such as artificial intelligence, big data is increasing in the industry. In response, the government is developing various educational programs to nurture talent in these emerging technology fields. However, the lack of a clear definition of competencies, which is the foundation of curriculum development and operation, has posed challenges in effectively designing digital technology education programs. This study systematically reviews the definitions and characteristics of competencies presented in prior research based on a literature review. Subsequently, in-depth interviews were conducted with 30 experts in emerging technology fields to derive a definition of competencies suitable for technology education programs. This research defines competencies for the development of technology education programs as 'a set of one or more knowledge and skills required to perform effectively at the expected level of a given task.' Additionally, the study identifies the elements of competencies, including knowledge and skills, as well as the principles of competency construction. The definition and characteristics of competencies provided in this study can be utilized to create more systematic and effective educational programs in emerging technology fields and bridge the gap between education and industry practice.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.129-141
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• 2024

Amidst the acceleration of digital transformation across various sectors, the financial market is increasingly focusing on the development of digital and electronic payment methods, including currency. Among these, Central Bank Digital Currencies (CBDC) are emerging as future digital currencies that could replace physical cash. They are stable, not subject to value fluctuation, and can be exchanged one-to-one with existing physical currencies. Recently, both domestic and international efforts are underway in researching and developing CBDCs. However, current CBDC systems face scalability issues such as delays in processing large transactions, response times, and network congestion. To build a universal CBDC system, it is crucial to resolve these scalability issues, including the low throughput and network overload problems inherent in existing blockchain technologies. Therefore, this study proposes a solution based on reinforcement learning for handling large-scale data in a CBDC environment, aiming to improve throughput and reduce network congestion. The proposed technology can increase throughput by more than 64 times and reduce network congestion by over 20% compared to existing systems.

• Education of Primary School Mathematics
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• v.27 no.3
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• pp.199-226
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• 2024

In response to the era of transformation necessitating the introduction of Artificial Intelligence (AI) and digital technologies, educational innovation is undertaken with the implementation of AI digital textbooks in Mathematics, English, and Information subjects by 2025 in Korea. Within this context, this study analyzed the perceptions and needs of elementary school teachers regarding mathematics AI digital textbook. Based on a survey conducted in November 2023, involving 132 elementary school teachers across the country, the analysis revealed that the majority of elementary school teachers had a low perception of the introduction and need for mathematics AI digital textbooks. However, some recognized the potential for personalized learning and effective teaching support. Furthermore, among the core technologies of the AI digital textbook, teachers highly valued the necessity of learning diagnostics and teacher reconfiguration functions and had the most positive perception of their usefulness in math lessons, while their perception of interactivity was relatively low. These findings suggest the need for changing teachers' perceptions through professional development and information provision to ensure the successful adoption and use of mathematics AI digital textbooks. Specifically, providing concrete and practical ways to use the AI digital textbook, exploring alternatives to digital overload, and continuing development and research on core technologies.