• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.763-780
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• 2024

As the domestic and international landscape undergoes rapid changes, the importance of implementing security measures in response to the growing threats that businesses face is increasing. In this context, the need for Security by Design (SbD), integrating security from the early design stages, is becoming more pronounced, with threat modeling recognized as a fundamental tool of SbD. Particularly, to save costs and time by detecting and resolving security issues early, the application of the Shift Left strategy requires the involvement of personnel with limited security expertise, such as software developers, in threat modeling. Although various automated threat modeling tools have been released, their lack of user-friendliness for personnel lacking security expertise poses challenges in conducting threat modeling effectively. To address this, we conducted an analysis of research related to threat modeling tools and derived usability evaluation criteria based on the GQM(Goal-Question-Metric) approach. An expert survey was conducted to validate both the validity and objectivity of the derived criteria. We performed usability evaluations of three threat modeling tools (MS TMT, SPARTA, PyTM), and the evaluation results led to the conclusion that MS TMT exhibited superior usability compared to other tools. This study aims to contribute to the creation of an environment where personnel with limited security expertise can effectively conduct threat modeling by proposing usability evaluation criteria.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.781-799
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• 2024

Recently, the US and EU have been institutionally introducing and promoting Coordinated Vulnerability Disclosure(CVD) to strengthen the response to security vulnerabilities in ICT products and services, based on collaboration with white-hat hackers. In response to these changes in cybersecurity, we propose a three-step approach to introduce CVD through the Information and Communications Network Act(ICNA). In the first step, to comprehend the necessity and requirements for legislating CVD, we survey the current situation in Korea and the trends of CVD in the US, EU, and OECD. In the second step, we analyze the necessity for legislating CVD and derive the requirements for its legislation. In this paper, we analyze the necessity for legislating CVD from three perspectives: the need for introducing CVD, the need for institutionalization based on law, and the suitability of the ICNA as the legislation. The derived requirements for CVD legislation include the establishment and publication of Vulnerability Disclosure Policy(VDP), legal protection for white-hat hackers, and designation and role assignments of coordinator. In the third step, we introduce approaches to apply the requirements for CVD legislation to the ICNA, which is the law governing prevention and response to cybersecurity incidents in private sector.

• Convergence Security Journal
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• v.24 no.3
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• pp.117-129
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• 2024

With the announcement of Transformer, a new type of architecture, in 2017, there have been many changes in language models. In particular, the development of LLM (Large language model) has enabled generative AI services such as search and chatbot to be utilized in various business areas. However, security issues such as personal information leakage and reliability issues such as hallucination, which generates false information, have raised concerns about the effectiveness of these services. In this study, we aimed to analyze the factors that are increasing the frequency of using generative AI in the workplace despite these concerns. To this end, we derived eight factors that affect the quality of LLM-based generative AI response data and empirically analyzed the impact of these factors on job satisfaction using a valid sample of 195 respondents. The results showed that expertise, accessibility, diversity, and convenience had a significant impact on intention to continue using, security, stability, and reliability had a partially significant impact, and completeness had a negative impact. The purpose of this study is to academically investigate how customer perception of response data quality affects business utilization satisfaction and to provide meaningful practical implications for customer-centered services.

• Journal of Industrial Convergence
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• v.22 no.8
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• pp.63-72
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• 2024

This study attempted to explore the impact of sense of humor and stress coping styles among nursing students on adaptation to clinical practice. The study included 180 nursing students as participants, and data collection was conducted using self-administered questionnaires from April 15 to 26, 2024. The collected data underwent t-test, one-way ANOVA, Pearson's correlation coefficients, and multiple regression analysis. The research findings revealed that the sense of humor scored 3.52, stress coping styles scored 3.40, and adaptation to clinical practice scored 3.46. Adaptation to clinical practice according to general characteristics showed statistically significant differences based on major satisfaction (F=29.80, p<.001), clinical practice satisfaction (F=40.46, p<.001), relationships with peers in clinical practice (F=5.05, p<.001), and personality (t=-3.41, p<.05). Adaptation to clinical practice showed statistically significant positive correlations with sense of humor (r=.31, p<.001) and stress coping styles (r=.43, p<.001). The factors influencing adaptation to clinical practice were clinical practice satisfaction(β=.34, p<.001), stress coping styles (β=.29, p<.001), and major satisfaction (β=.23, p<.05), explaining 42% of the total variance.

• Journal of Advanced Navigation Technology
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• v.28 no.4
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• pp.532-537
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• 2024

In this study, wear characteristics and microstructure changes due to changes in alloy composition of Ni-Cr-Mo-V and Ni-Cr-Mo low-alloy steels used in brake discs for transportation system such as aircraft and high-speed trains. As a result of the hardness test, the hardness of C-Mo-V steel was the highest at 39.4±0.9HRc, and the hardness of Ni-Cr-Mo steel was the lowest at 32.4±0.6HRc. The friction coefficient tended to decrease as the vertical load increased. At a vertical load of 1 N, the friction coefficient of Ni-Cr-Mo steel was the highest at 0.842, and at a vertical load of 5 N, Mn-Cr-V steel was the highest at 0.696. Ni-Cr-Mo showed the largest wear scar width, depth, and wear amount, with a width of 711 ㎛, a depth of 8.24 ㎛, and a wear amount of 11 mg under a vertical load of 1 N, and a width of 1,017 ㎛, a depth of 19.17 ㎛, and a wear amount of 17 mg under a vertical load of 5 N. As a result of wear mechanism analysis, ploughing, delamination, and adhesion in all specimens, with plastic deformation being more prominently observed in Ni-Cr-Mo.

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.11-21
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• 2024

This study explores the use of virtual reality (VR) technology to identify and label key segments of the golf swing. To address the limitations of existing VR devices, we developed a platform to collect kinematic data from various VR devices using the OpenVR SDK (Software Development Kit) and SteamVR, and developed a semi-automated labeling technique to identify and label temporal changes in kinematic behavior through LSTM (Long Short-Term Memory)-based time series data analysis. The experiment consisted of 80 participants, 20 from each of the following age groups: teenage, young-adult, middle-aged, and elderly, collecting data from five swings each to build a total of 400 kinematic datasets. The proposed technique achieved consistently high accuracy (≥0.94) and F1 Score (≥0.95) across all age groups for the seven main phases of the golf swing. This work aims to lay the groundwork for segmenting exercise data and precisely assessing athletic performance on a segment-by-segment basis, thereby providing personalized feedback to individual users during future education and training.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.47-56
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• 2024

This paper proposes a method for fine-tuning BERT-based natural language processing models to perform sentiment analysis on Korean review data. By varying the input sequence length during this process and comparing the performance, we aim to explore the optimal performance according to the input sequence length. For this purpose, text review data collected from the clothing shopping platform M was utilized. Through web scraping, review data was collected. During the data preprocessing stage, positive and negative satisfaction scores were recalibrated to improve the accuracy of the analysis. Specifically, the GPT-4 API was used to reset the labels to reflect the actual sentiment of the review texts, and data imbalance issues were addressed by adjusting the data to 6:4 ratio. The reviews on the clothing shopping platform averaged about 12 tokens in length, and to provide the optimal model suitable for this, five BERT-based pre-trained models were used in the modeling stage, focusing on input sequence length and memory usage for performance comparison. The experimental results indicated that an input sequence length of 64 generally exhibited the most appropriate performance and memory usage. In particular, the KcELECTRA model showed optimal performance and memory usage at an input sequence length of 64, achieving higher than 92% accuracy and reliability in sentiment analysis of Korean review data. Furthermore, by utilizing BERTopic, we provide a Korean review sentiment analysis process that classifies new incoming review data by category and extracts sentiment scores for each category using the final constructed model.

• Journal of Korean Home Economics Education Association
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• v.35 no.4
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• pp.13-31
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• 2023

The purpose of this study was to develop a career education program linked to home economics in middle school to improve adolescents' ability to respond to the rapidly changing future society. The research procedure was conducted in four steps: Analysis, Design, Development, and Evaluation. In the analysis step, related prior studies were analyzed to identify the units and contents that linked home economics and career education. In the design step, learning topics and contents according to the design thinking process were selected and the overall program process was designed to cultivate entrepreneurship based on the textbook analysis results. In the development step, the goals and achievement standards of school career education linked to home economics were set for each class, and a total of eight teaching and learning plans, twenty-three types of teaching and learning materials, and expert validity verification questionnaires were developed. In the evaluation step, the validity of the developed program was verified by nine experts. The developed program was verified for overall programs, and the validity of the program was 0.94. It is expected that the career education program linked to home economics will contribute to foster the adolescents' entrepreneurship so they can design their future on their own and allow them to manage their life proactively.

• Journal of Korea Water Resources Association
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• v.57 no.9
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• pp.571-583
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• 2024

Forecasting dam inflows in the medium to long term is crucial for effective dam operation and the prevention of water-related disasters such as floods and droughts. However, the increasing frequency of extreme weather events due to climate change has made hydrological forecasting more challenging. Since 2000, seasonal weather forecasts, which provide predictions for weather variables up to about seven months ahead, and their hydrological interpretation, known as Seasonal Flow Forecasts (SFFs) have gained significant global interest. This study utilises seasonal weather forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF), converting them into inflow forecasts using a hydrological model for 12 multipurpose dams in South Korea from 2011 to 2020. We then compare the performance of these SFFs with the Ensemble Streamflow Prediction (ESP). Our results indicate that while SFFs are more effective for short-term predictions of 1-2 months, ESP outperforms SFFs for long-term predictions. Seasonally, the performance of SFFs is higher in October-November but lower from December to February. Moreover, our findings demonstrate that SFFs are highly effective in quantitatively predicting dry conditions, although they tend to underestimate inflows under wet conditions.

• Journal of Science Education
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• v.48 no.2
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• pp.75-90
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• 2024

Contemporary society faces increasingly diverse risks with expanding impacts. In response, the importance of science education has become more prominent. This study aims to analyze the characteristics of existing research on science-related risk education and derives implications for such education. Using detailed bibliometric analysis, we collected citation data from 83 international scholarly journals (SSCI) in the field of education indexed in the Web of Science with the keywords 'Scientific Risk.' Subsequently, using the bibliometrix package in R-Studio, we conducted a bibliometric analysis. The findings are as follows. Firstly, research on risk education covers topics such as risk literacy, the structure of risks addressed in science education, and the application and effectiveness of incorporating risk cases into educational practices. Secondly, a significant portion of research on risks related to science education has been conducted within the framework of socioscientific issues (SSI) education. Thirdly, it was observed that research on risks related to science education primarily focuses on the transmission of scientific knowledge, with many studies examining formal education settings such as curricula and school learning environments. These findings imply several key points. Firstly, to effectively address risks in contemporary society, the scope of risk education should extend beyond topics such as nuclear energy and climate change to encompass broader issues like environmental pollution, AI, and various aspects of daily life. Secondly, there is a need to reexamine and further research topics explored in the context of SSI education within the framework of risk education. Thirdly, it is necessary to analyze not only risk perception but also risk assessment and risk management. Lastly, there is a need for research on implementing risk education practices in informal educational settings, such as science museums and media.