• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.137-142
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• 2024

User interface (UI) functions are distorted and appear as a dark pattern that intentionally deceives or entices users. Consumers who are unaware of dark patterns are constrained in their choices, resulting in unnecessary economic damage. In this study, we aimed to investigate consumers' various shopping emotions and behavioral intentions after recognizing dark patterns in online shopping malls through qualitative research methods. As a result of the study, the rate of perception differed slightly depending on the type of dark pattern, and it was found that it induced consumer emotions such as distrust of the company, user deception, and displeasure. It has been found that the behavior after recognizing the dark pattern shows passive behaviors such as vowing to prevent recurrence and warning acquaintances rather than actively protesting to the company and demanding compensation for damages.

• Journal of Advanced Technology Convergence
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• v.3 no.3
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• pp.71-76
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• 2024

This study is a theoretically based study that understands the midlife crisis from the perspective of Jung's Archetypes and the Collective Unconscious, explores psychological changes, and suggests methods that can be applied to social welfare practice. The midlife crisis is not simply a period of confusion, but is viewed as an important journey toward individualization and self-actualization. We seek to understand how Jung's archetypes appear in middle age and what meaning they have for the psychological changes that occur during adulthood. In addition, it explains the impact of the collective unconscious on an individual's experience and behavior during a midlife crisis, and provides theoretical basic research to social welfare practitioners and researchers studying midlife to help clients overcome the midlife crisis more positively. I want to do it. The purpose is to suggest that the integrated approach of Jungian psychology in social welfare practice and education can play a role as meaningful theoretical basic research in effectively supporting the midlife crisis

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.113-122
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• 2024

In this paper, we conducted a thorough investigation of existing simulators for running simulations of Vehicular Adhoc Networks (VANET) in realistic road environments, such as digital twins. After careful consideration, we chose a simulator that combines OSM (OpenStreetMap), SUMO (Simulation of Urban MObility), and OMNeT++ due to its open-source nature and efficient performance. Using this integrated simulator, we carried out VANET simulations in both simple virtual road environments and realistic road environments. Our findings revealed significant differences in VANET performance between the two types of environments, emphasizing the need to consider realistic road and traffic environments for reliable VANET operation. Furthermore, our simulations demonstrated significant performance variability, with performance degradation observed as vehicle density decreased and dynamic changes in network topology increased. These results underscore the importance of digital twin-based approaches in VANET research, highlighting the need to simulate real-world road and traffic conditions rather than relying on simple virtual road environments.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.3
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• pp.87-98
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• 2024

Changwon City is one of the major industrial cities in Korea. In the past, it grew rapidly with an economic structure centered on manufacturing, but due to changes in the global economic environment and domestic industrial structure, Changwon City's economic growth engine has weakened and a new growth engine must be sought. are facing Accordingly, this study analyzed the goals and strategies of the urban development base project for activation of Local Cities, focusing on the case of Changwon Digital Innovation Town. Specifically, we sought ways to overcome the spatial limitations and saturation of the Masan Free Trade Zone and to activation the local economy by attracting and fostering new, cutting-edge industries. To this end, strategic approaches such as building digital infrastructure, fostering future new technologies, social integration and community formation, and eco-friendly development were proposed, and a plan was presented for Changwon City to leap forward as a new 21st century free trade zone.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.3
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• pp.145-168
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• 2024

This study analyzed the current status of late fee policies for overdue books in public libraries in the United States and Korea and derived measures to improve the late fee policy in public libraries in Korea. Therefore, this study analyzed the current status of late fee policies in public libraries in Seoul, Korea. The results indicated that 14.8% of public library operators and 21.6% of public libraries in Seoul had late fee policies. In the US, the American Library Association and major public libraries were found to have recently eliminated late fees. The main justification for this policy change was their recognition of late fees as a form of social inequality. In fact, this study confirmed that the elimination of late fees led to users' increased access to information. This study also found that public libraries in the US turned books not returned after a certain period into lost items and imposed fines for lost items. In conclusion, this study suggested integrating measures for late fees and lost items to manage non-returned books and clarifying the legal basis for such measures.

• The Transactions of the Korea Information Processing Society
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• v.13 no.8
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• pp.388-394
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• 2024

Since recommendation systems play a key role in increasing the revenue of companies, various approaches and models have been studied in the past. However, this diversity also leads to a complexity in the types of recommendation systems, which makes it difficult to select a recommendation model. Therefore, this study aims to solve the difficulty of selecting an appropriate recommendation model for recommendation systems by providing a unified criterion for categorizing various recommendation models and comparing their performance in a unified environment. The experiments utilized MovieLens and Coursera datasets, and the performance of linear models(ADMM-SLIM, EASER, LightGCN) and non-linear models(Caser, BERT4Rec) were evaluated using HR@10 and NDCG@10 metrics. This study will provide researchers and practitioners with useful information for selecting the best model based on dataset characteristics and recommendation context.

• Journal of IKEEE
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• v.28 no.3
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• pp.451-457
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• 2024

This paper proposes a method for predicting agricultural product prices by utilizing various variables such as price, climate factors, demand, and import volume as data, and applying the Long Short-Term Memory (LSTM) model. The analysis of prediction performance using the LSTM model, which learns the long-term dependencies of time series data, showed that integrating diverse data improved performance compared to traditional methods. Furthermore, even when predicting without price data as a dependent variable, meaningful results were achieved using only independent variables, indicating the potential for further model development. Moreover, it was found that using a multi-variable model could further enhance prediction performance, suggesting that this complex approach is effective in improving the accuracy of cabbage price predictions.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.3
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• pp.277-287
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• 2024

Transcranial Doppler (TCD) ultrasound is a crucial non-invasive tool for assessing cerebral blood flow and is widely used to diagnose and monitor cerebrovascular diseases. This paper reaffirms the importance of TCD, details examination methods and precautions, and provides a guide for practitioners. TCD evaluates the blood flow velocity to assess stenosis, occlusion, and hemodynamic changes. Distinguishing between increased blood flow volume and decreased vessel diameter based solely on velocity is challenging, necessitating a comprehensive approach to integrating clinical findings and hemodynamic changes. The reliability of TCD results depends on the skill of the examiner and requires standardized procedures and continuous training. Advances in automation and artificial intelligence promise enhanced accuracy and reliability. Future research should focus on validating and clinically applying these technologies. This paper is a review of the clinical significance of TCD, methods, and precautions, offering a valuable guide for practitioners and highlighting the potential benefits of ongoing advancements in TCD for the diagnosis and treatment of cerebrovascular diseases.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.5
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• pp.915-925
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• 2024

As non-face-to-face work increases due to the COVID-19 pandemic, companies have introduced collaboration tools to perform work without spatial constraints. The rapidly growing collaboration tool market continues to show high utilization rates even after the endemic due to the increase in demand for hybrid work that combines face-to-face and non-face-to-face work. The use of collaboration tools increases work efficiency, facilitates smooth collaboration, and increases data integration, generating various data. However, at the same time, it also increases the risk of exposure of corporate confidential information due to the possibility of external access by internal users. In response to this, an analysis method is needed to collect and acquire data during digital investigations targeting collaboration tools. In this paper, we identified local artifacts targeting JANDI, a collaboration tool in a Windows environment, and explained how to collect and analyze data through API reconstruction. Finally, we presented a digital forensic utilization method through scenario and chat room reconstruction.

• Journal of Practical Engineering Education
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• v.16 no.5_spc
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• pp.701-708
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• 2024

The challenges of exploring distant locations have become increasingly apparent, especially since COVID-19 has made visiting even nearby museums and attractions more difficult. Various factors contribute to this, including time constraints, financial limitations or language barriers. However, these challenges can be overcome with recent technologies by transforming how users experience and interact with spaces. With the latest advancements, it is now possible to create virtual representations of famous attractions, allowing users to take virtual tours as if they were physically present. This paper presents a comprehensive framework for creating virtual tours using Matterport, a leading 3D scanning technology, and Unity 3D, a powerful game engine. The paper outlines methodologies for capturing 3D data with Matterport, importing it into Unity, enhancing user interaction, and optimizing the overall experience. By integrating these tools, the framework aims to facilitate immersive virtual experiences. This approach will allow affordable virtual tickets for famous attractions around the world which will be great educational opportunities. In addition, this framework can be applicable to facilitate easier navigation in complex environments such as airports and hospitals.