• Tunnel and Underground Space
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• v.34 no.3
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• pp.231-247
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• 2024

In the field of high-level radioactive waste disposal targeting deep rock environments, hydraulic characteristic information serves as the most important key factor in selecting relevant disposal sites, detailed design of disposal facilities, derivation of optimal construction plans, and safety evaluation during operation. Since various rock types are mixed and distributed in a small area in Korea, it is important to conduct preliminary work to analyze the hydrogeological characteristics of rock aquifers for various rock types and compile the resulting data into a database. In this paper, we obtained hydraulic conductivity data, which is the most representative field hydraulic characteristic of a high-depth volcanic bedrock aquifer, and also analyzed and evaluated the field data. To acquire field data, we used a high-performance hydraulic testing system developed in-house and applied standardized test methods and investigation procedures. In the process of hydraulic characteristic data analysis, hydraulic conductivity values were obtained for each depth, and the pattern of groundwater flow through permeable rock joints located in the test section was also evaluated. It is expected that the series of data acquisition methods, procedures, and analysis results proposed in this report can be used to build a database of hydraulic characteristics data for high-depth rock aquifers in Korea. In addition, it is expected that it will play a role in improving technical know-how to be applied to research on hydraulic characteristic according to various bedrock types in the future.

• Convergence Security Journal
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• v.24 no.2
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• pp.89-104
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• 2024

This study is an empirical study to examine the factors that influence the intention to use artificial intelligence (AI) technology for SW engineering-related tasks, and the purpose of the study is to understand the key factors that influence the use in terms of AI augmentation characteristics and interactive UI/UX characteristics. For this purpose, a survey was conducted among information and communication workers who have experience in using AI-related technologies and the collected data was analyzed. The results of the empirical analysis showed that perceived usefulness was positively influenced by the factors of expertise, interestingness, realism, aesthetics, efficiency, and flexibility, and perceived ease of use was positively influenced by the factors of expertise, interestingness, realism, aesthetics, and flexibility. Variety had no effect on both perceived ease of use and perceived usefulness. Perceived ease of use had a significant effect on perceived immersion, which positively influenced intention to use. These findings are significant in that they provide an academic understanding of the factors that influence the use of AI-enhanced tools in SW engineering-related tasks such as application design, development, testing, and process automation, as well as practical directions for the creators of tools that provide AI-enhanced development services to develop user acquisition strategies.

• Industry Promotion Research
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• v.9 no.1
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• pp.149-157
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• 2024

The purpose of this study is to objectively examine the effects of integrated art therapy on cognitive function and depression in the early dementia elderly, and to identify and discuss the process of change in the early dementia elderly through a comprehensive analysis through behavior change observation diary. As a research method, a mixed study was designed using in-depth analysis through qualitative studies as well as quantitative studies on the effect of integrated art therapy on cognitive function and depression in the elderly with early dementia. The quantitative study conducted a pre-post examination of 20 elderly people with early dementia using the day care center in P-gu, Suwon, and the qualitative study analyzed the behavioral change observation diary of 10 elderly people with early dementia. These findings show that first, integrated art therapy had a significant effect on the cognitive function of the elderly with early dementia (p<.001, t=-5.871). Second, integrated art therapy had a significant effect on the depression of the elderly with early dementia (p<.001, t=5.325). Third, the integrated art therapy program changed to a positive attitude before and after cognitive function and depression of the elderly with early dementia. By revealing the effect of integrated art therapy on cognitive function and depression of the elderly with early dementia through the results of this study, it is meaningful as basic data for research related to the elderly with early dementia as well as providing effective information on integrated art therapy programs related to the elderly with early dementia.

• Journal of Korean Society of Rural Planning
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• v.30 no.2
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• pp.13-24
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• 2024

This study conducts an analysis of social media big data pertaining to island tourism resources, aiming to discern the diverse forms and categories of island tourism favored by consumers, ascertain predominant resources, and facilitate objective decision-making grounded in scientific methodologies. To achieve this objective, an examination of blog posts published on Naver from 2022 to 2023 was undertaken, utilizing keywords such as 'Island tourism', 'Island travel', and 'Island backpacking' as focal points for analysis. Text mining techniques were applied to sift through the data. Among the resources identified, the port emerged as a significant asset, serving as a pivotal conduit linking the island and mainland and holding substantial importance as a focal point and resource for tourist access to the island. Furthermore, an analysis of the disparity between existing island tourism resources and those acknowledged by tourists who actively engage with and appreciate island destinations led to the identification of 186 newly emerging resources. These nascent resources predominantly clustered within five regions: Incheon Metropolitan City, Tongyeong/Geoje City, Jeju Island, Ulleung-gun, and Shinan-gun. A scrutiny of these resources, categorized according to the tourism resource classification system, revealed a notable presence of new resources, chiefly in the domains of 'rural landscape', 'tourist resort/training facility', 'transportation facility', and 'natural resource'. Notably, many of these emerging resources were previously overlooked in official management targets or resource inventories pertaining to existing island tourism resources. Noteworthy examples include ports, beaches, and mountains, which, despite constituting a substantial proportion of the newly identified tourist resources, were not accorded prominence in spatial information datasets. This study holds significance in its ability to unearth novel tourism resources recognized by island tourism consumers through a gap analysis approach that juxtaposes the existing status of island tourism resource data with techniques utilizing social media big data. Furthermore, the methodology delineated in this research offers a valuable framework for domestic local governments to gauge local tourism demand and embark on initiatives for tourism development or regional revitalization.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.517-524
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• 2024

This study aims to train and implement a deep learning model for the fusion of website creation and artificial intelligence, in the era known as the AI revolution following the launch of the ChatGPT service. The deep learning model was trained using 3,000 collected web page images, processed based on a system of component and layout classification. This process was divided into three stages. First, prior research on AI models was reviewed to select the most appropriate algorithm for the model we intended to implement. Second, suitable web page and paragraph images were collected, categorized, and processed. Third, the deep learning model was trained, and a serving interface was integrated to verify the actual outcomes of the model. This implemented model will be used to detect multiple paragraphs on a web page, analyzing the number of lines, elements, and features in each paragraph, and deriving meaningful data based on the classification system. This process is expected to evolve, enabling more precise analysis of web pages. Furthermore, it is anticipated that the development of precise analysis techniques will lay the groundwork for research into AI's capability to automatically generate perfect web pages.

• The Journal of Korean Society for School & Community Health Education
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• v.25 no.3
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• pp.39-49
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• 2024

Purpose: This study aims to analyze the current status of research related to infants and school-age-child published in the journal of Korean society for school & community health education from 2000 to 2023, with the goal of contributing to the future development and enhancement of the journal. Method: From 2000 to 2023, 52 papers were analyzed, comparing and classifying their journal topic, research types, data collection methods, and data analysis methods. Results: The results shows that the highest publication trend occurred between 2008 and 2012, with most studies focusing on school-age children. In terms of research topic, 'health behavior and health education' was the most frequent with 14 papers (26.9%), followed by oral health with 9 papers (17.3%), safety management with 7 papers (13.5%), and sexual awareness with 6 papers (11.5%). Quantitative research was the most common research type, with surveys being the primary data collection method. Descriptive statistics and t-test were the most frequently used data analysis methods. Conclusion: To enhance the quality of the journal of Korean society for school & community health education, there should be an expansion of evidence-based research focusing on infants and school-age children. Additionally, there is a need for greater diversity in research design, data collection, and analysis methods.

• Journal of Platform Technology
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• v.12 no.1
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• pp.91-105
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• 2024

As the number of cases of applying IT systems to the existing isolated ICS (Industrial Control System) network environment continues to increase, security threats in the ICS environment have rapidly increased. Security threat scenarios help to design security strategies in cybersecurity training, including analysis, prediction, and response to cyberattacks. For successful cybersecurity training, research is needed to develop valid and reliable security threat scenarios for meaningful training. Therefore, this paper proposes a case-based security threat scenario development methodology for cybersecurity training in the ICS environment. To this end, we develop a methodology consisting of five steps based on analyzing actual cybersecurity incident cases targeting ICS. Threat techniques are standardized in the same form using objective data based on the MITER ATT&CK framework, and then a list of CVEs and CWEs corresponding to the threat technique is identified. Additionally, it analyzes and identifies vulnerable functions in programming used in CWE and ICS assets. Based on the data generated up to the previous stage, develop security threat scenarios for cybersecurity training for new ICS. As a result of verification through a comparative analysis between the proposed methodology and existing research confirmed that the proposed method was more effective than the existing method regarding scenario validity, appropriateness of evidence, and development of various scenarios.

• Journal of Platform Technology
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• v.11 no.6
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• pp.56-67
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• 2023

The increased demand for electronic components, spurred by the Fourth Industrial Revolution and the COVID-19 pandemic, has facilitated human life but also escalated the production of e-waste. Discussions on the impact of e-waste have primarily revolved around environmental, health, and social issues, with global legislations focusing on addressing these concerns. However, e-waste poses unique security risks, such as potential technological and personal information leaks, unlike conventional waste. Current discourse on e-waste security is notably insufficient. This study aims to empirically analyze the relatively overlooked trends in e-waste security, employing three methodologies. Firstly, it assesses the general trend in discussions on e-waste by analyzing year-wise documents and media reports. Secondly, it identifies key trends in e-waste security by examining documents on the subject. Thirdly, the study reviews national security guidelines related to e-waste disposal to assess the necessity of designing security strategies for e-waste management. This research is significant as it is one of the first in korea to address e-waste from a security perspective and offers a multi-dimensional analysis of e-waste security trends. The findings are expected to enhance domestic awareness of e-waste and its security issues, providing an opportunity for proactive response to these security risks.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.4
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• pp.69-85
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• 2024

The creation of open spaces has both direct and indirect impacts on the local economy, society, culture, and environment. Since the public usually finances these spaces, it is necessary to ensure procedural rationality by promoting consensus among residents and other stakeholders. This study examines the extent of public participation in the creation of open spaces and summarizes trends. By analyzing seven cases of open space development based on participation in South Korea, the study identifies the characteristics and progression of participation during four phases of the development process in the Gwanghwamun Plaza Restructuring Project (2016-2022). During the agenda-setting phase, the Gwanghwamun Forum was convened to establish agendas for the plaza's restructuring. The design and governance phase included a design competition to select a proposal for the plaza, alongside the establishment of the Gwanghwamun Citizens' Committee for governance. Despite proactive efforts in the conflict resolution phase to halt extensive restructuring and enhance communication, civic groups opposed the project by presenting five distinct agendas. In the implementation phase, multiple public participation programs were conducted before the plaza's reopening. The study found that public participation in the Gwanghwamun Plaza project faced challenges such as inadequate participation conditions, limited information sharing, and monotonous participation opportunities. Although the institutional environment for public participation is improving, practical limitations remain. Therefore, a comprehensive examination of open space creation through public participation is necessary.

• Tunnel and Underground Space
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• v.34 no.4
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• pp.312-329
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• 2024

In various underground research projects such as energy storage and development and radioactive waste disposal targeting deep underground, the characteristics of permeable rock fractures that serve as major pathway of groundwater flow in deep rock aquifer are considered as an important evaluation factor in the design, construction, and operation of research facilities. In Korea, there is little research and database on the location and hydraulic characteristics of permeable rock fractures and the pattern of groundwater flow patterns that may occur between fractures in deep rock boreholes. In this paper, the hydraulic characteristics of permeable rock fractures in deep rock aquifer were evaluated through the analysis of geothermal gradient and pumping test data. First, the deep geothermal distribution was identified through temperature logging, and the geothermal gradient was obtained through linear regression analysis using temperature data by depth. In addition, the hydraulic characteristics of the fractured rock were analyzed using outflow temperature obtained from pumping tests. Ultimately, the potential location and hydraulic characteristics of permeable rock fractures, as well as groundwater flow within the boreholes, were evaluated by integrating and analyzing the geophysical logging and hydraulic testing data. The process and results of the evaluation of deep permeable rock fractures proposed in this study are expected to serve as foundational data for the successful implementation of underground research projects targeting deep rock aquifers.