• Journal of Korean Library and Information Science Society
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• v.54 no.1
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• pp.191-220
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• 2023

This research attempts to identify how members of an online community collaboratively engaged with particular social information behaviors and accomplished a defined collective action. While responding to the Sewol Ferry tragedy, MissyUSA members quickly communicated and mobilized a collective action, a full-page ad campaign in The New York Times. As a follow up study, this secondary analysis quantitatively analyzes the primary data from a previous study to explore potential relationships or underlying factors among the various identified information behaviors. In this study, nineteen of the previously identified information behaviors were analyzed using exploratory factor analysis, yielding a total of eight factors. The two major factors of shared representation/collective identification and mobilizing resources verified the findings of the previous study and are in line with the findings typical of political science. The three factors of collaborative decision-making, reaction to tension, and brainstorming were factors that maximized communication and mobilization online, without any face-to-face communication or physical organization. Three emergent factors of outburst of dissent, boycott, and planning explained how members used negative emotions of anger, referential information for boycott, and incubated next collective actions. Through exploratory factor analysis, this study verifies and expands on the findings of the previous study by identifying several emergent factors that relate to the collaborative information behaviors of an online community engaged in a collective action.

• Korean Journal of Social Welfare Studies
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• v.43 no.2
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• pp.5-29
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• 2012

Previous performance evaluation focusing on objective data of service agency has the limitations that did not reflect user-centered evaluation. With the expansion of voucher service, importance of perspective of service user such as satisfaction index is increasing. As voucher service has been delivered by the financial burden of government and user, we need the performance evaluation system that reflects the both performance indices to meet the accountability of two stake-holders. So this study focuses on deriving integrated evaluation system developing systems what mixed objective and subjective performance. Data used in this study is collected form 70 social service agencies that deliver voucher service and 1445 service users. Using General Satisfaction Index and Efficiency Index by DEA, this study analysed the correlation between efficiency and satisfaction index, and integrated performance evaluation model is constructed through portfolio map. This study has the following implication. This study theoretically explains the relation of objective performance and subjective performance and gives practical guidance in performance evaluation criterion and interpretation of performance.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.178-193
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• 2023

The aim of this study was to investigate differences in the achievement standards from the 2015 to the 2022 revised national science curriculum and to present the implications for science teaching under the revised curriculum. Achievement standards relevant to primary science education were therefore extracted from the national curriculum documents; conceptual domains in the two curricula were analyzed for differences; various kinds of centrality were computed; and the Louvain algorithm was used to identify clusters. These methods revealed that, in the revised compared with the preceding curriculum, the total number of nodes and links had increased, while the number of achievement standards had decreased by 10 percent. In the revised curriculum, keywords relevant to procedural skills and behavior received more emphasis and were connected to collaborative learning and digital literacy. Observation, survey, and explanation remained important, but varied in application across the fields of science. Clustering revealed that the number of categories in each field of science remained mostly unchanged in the revised compared with the previous curriculum, but that each category highlighted different skills or behaviors. Based on those findings, some implications for science instruction in the classroom are discussed.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.189-210
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• 2022

Cities around the world have paid attention to public transportation as an alternative to reducing traffic congestion caused by automobile usage, excessive energy consumption, and environmental pollution. This study measures accessibility to subway stations in Seoul using a supply-demand-based accessibility technique. Then, the impacts were analyzed through land prices by use and segment. As a result of analysis using the multilevel hedonic price models, accessibility considering both supply and demand for the subway had a positive effect on both residential and non-residential land prices. The effect was stronger for residential than for non-residential. Further, among the accessibility measured by the three functions, the accessibility by the Exponential function was most suitable for the residential land price, and the accessibility measured by the Power function for the non-residential land price had the highest explanatory power. Also, looking at the impacts by land price segments, it was found that higher access to metro stations had the greatest positive impacts on the most expensive segment of residential and non-residential land prices. The results of this study can be applied not only to identify the impacts of public investment on neighborhoods, but also to support real estate valuation.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.241-265
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• 2023

A corporate insolvency prediction model serves as a vital tool for objectively monitoring the financial condition of companies. It enables timely warnings, facilitates responsive actions, and supports the formulation of effective management strategies to mitigate bankruptcy risks and enhance performance. Investors and financial institutions utilize default prediction models to minimize financial losses. As the interest in utilizing artificial intelligence (AI) technology for corporate insolvency prediction grows, extensive research has been conducted in this domain. However, there is an increasing demand for explainable AI models in corporate insolvency prediction, emphasizing interpretability and reliability. The SHAP (SHapley Additive exPlanations) technique has gained significant popularity and has demonstrated strong performance in various applications. Nonetheless, it has limitations such as computational cost, processing time, and scalability concerns based on the number of variables. This study introduces a novel approach to variable selection that reduces the number of variables by averaging SHAP values from bootstrapped data subsets instead of using the entire dataset. This technique aims to improve computational efficiency while maintaining excellent predictive performance. To obtain classification results, we aim to train random forest, XGBoost, and C5.0 models using carefully selected variables with high interpretability. The classification accuracy of the ensemble model, generated through soft voting as the goal of high-performance model design, is compared with the individual models. The study leverages data from 1,698 Korean light industrial companies and employs bootstrapping to create distinct data groups. Logistic Regression is employed to calculate SHAP values for each data group, and their averages are computed to derive the final SHAP values. The proposed model enhances interpretability and aims to achieve superior predictive performance.

• Convergence Security Journal
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• v.23 no.2
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• pp.11-25
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• 2023

Since President Biden's inauguration, significant cyberattacks have occurred several times in the United States, and cybersecurity was emphasized as a national priority. The U.S. is advancing efforts to strengthen the cybersecurity both domestically and internationally, including with allies. In particular, the Biden administration announced the National Cybersecurity Strategy in March 2023. The National Cybersecurity Strategy is the top guideline of cybersecurity and is the foundation of other cybersecurity policies. And it includes public-privates as well as international policy directions, so it is expected to affect the international order. Meanwhile, In Korea, a new administration was launched in 2022, and the revision of the National Cybersecurity Strategy is necessary. In addition, cooperation between Korea and the U.S. has recently been strengthened, and cybersecurity is being treated as a key agenda in the cooperative relationship. In this paper, we examine the cyber security strategies of the Trump and Biden administration, and analyze how the strategies have changed, their characteristics and implications in qualitative and quantitative terms. And we derive the implications of these changes for Korea's cybersecurity policy.

• Journal of Korea Entertainment Industry Association
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• v.10 no.4
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• pp.77-92
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• 2016

In this study, the relationship of images and sounds of the animations "Dots" and "Loops" which Norman McLaren animated with his Animated sound technique when he worked at Guggenheim museum at New York, are analyzed through the audiovisual analysis theory by Michel Chion, and through the theory of synchronism/asynchronism and parallelism/counterpoint by Siegfried Kracauer. For the results of the analysis, there are a few difference between "Dots" and "Loops" regarding the aspect of sound arrangement and expressive aspect of abstract animation. However, there are being of two main elements of sound, composing with monophony sound, making musical structure with sound effects, and the emphasizing of parallelism with synchronization bewteen images and sounds in common with both "Dots" and "Loops". In "Dots" and "Loops", there are close correlations between pitch of sound and arrangement/shape of image, between loudness of sound and size of image, and between length of sound and length/shape of image. The image and sound of "Dots" and "Loops" have equal relationship each other, rather than subordinate relationship according as image become sound and the sound become new image with the animated sound technique. "Dots" and "Loops" show tendency of minimal art and music video. Since these two films, and remind about the new approach to sound creation in today's animation production.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.6
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• pp.61-74
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• 2023

The concept of "green infrastructure" emphasizes the close relationship between natural and urban social systems, thereby providing services that protect the ecological environment and improve the quality of human life. The Green View Index(GVI) is an important indicator for measuring the supply of urban green space and contains more 3D spatial elements concerning the green space ratio. This study focused on an area within the Third Ring Road in the city of Chengdu, Sichuan Province, China. The purposes of this study were three-fold. First, this study analyzed the spatial distribution characteristics of the GVI in urban streets and its correlation with the urban park green space system using Street View image data. Second to analyze the characteristics of low GVI streets were analyzed. Third, to analyze the connectivity between road traffic and street GVI using space syntax were analyzed. This study found that the Street GVI was higher in the southwestern part of the study area than in the northeastern part. The spatial distribution of the street GVI correlated with urban park green space. Second, the street areas with low GVI are mainly concentrated in areas with dense commercial facilities, areas with new construction, areas around elevated roads, roads below Class 4, and crossroads areas. Third, the high integration and low GVI areas were mainly concentrated within the First Ring Road in the city as judged by the concentration of vehicles and population. This study provides base material for future programs to improve the GVI of streets in Chengdu, Sichuan Province.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.597-603
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• 2023

The paradigm of military operations has evolved from platform-centric warfare to network-centric warfare and further to information-centric warfare, driven by advancements in information technology. In recent years, with the development of cutting-edge technologies such as big data, artificial intelligence, and the Internet of Things (IoT), military operations are transitioning towards knowledge-centric warfare (KCW), based on artificial intelligence. Consequently, the military places significant emphasis on integrating advanced information and communication technologies (ICT) to establish reliable C4I (Command, Control, Communication, Computer, Intelligence) systems. This research emphasizes the need to apply data mining techniques to analyze and evaluate various aspects of C4I systems, including enhancing combat capabilities, optimizing utilization in network-based environments, efficiently distributing information flow, facilitating smooth communication, and effectively implementing knowledge sharing. Data mining serves as a fundamental technology in modern big data analysis, and this study utilizes it to analyze real-world cases and propose practical strategies to maximize the efficiency of military command and control systems. The research outcomes are expected to provide valuable insights into the performance of C4I systems and reinforce knowledge-centric warfare in contemporary military operations.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.347-373
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• 2023

As the significance of ESG (Environmental, Social, and Governance) management amplifies in driving sustainable growth, this study delves into and compares ESG trends and interrelationships from both corporate and societal viewpoints. Employing a combination of Latent Dirichlet Allocation Topic Modeling (LDA) and Semantic Network Analysis, we analyzed sustainability reports alongside corresponding social media datasets. Additionally, an in-depth examination of social media content was conducted using Joint Sentiment Topic Modeling (JST), further enriched by Semantic Network Analysis (SNA). Complementing text mining analysis with the assistance of ChatGPT, this study identified 25 different ESG topics. It highlighted differences between companies aiming to avoid risks and build trust, and the general public's diverse concerns like investment options and working conditions. Key terms like 'greenwashing,' 'serious accidents,' and 'boycotts' show that many people doubt how companies handle ESG issues. The findings from this study set the foundation for a plan that serves key ESG groups, including businesses, government agencies, customers, and investors. This study also provide to guide the creation of more trustworthy and effective ESG strategies, helping to direct the discussion on ESG effectiveness.