• The Journal of Bigdata
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• v.9 no.1
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• pp.31-47
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• 2024

With the advancement of artificial intelligence, the travel and hospitality industry is also adopting AI and machine learning technologies for various purposes. In the tourism industry, demand forecasting is recognized as a very important factor, as it directly impacts service efficiency and revenue maximization. Demand forecasting requires the consideration of time-varying data flows, which is why statistical techniques and machine learning models are used. In recent years, variations and integration of existing models have been studied to account for the diversity of demand forecasting data and the complexity of the natural world, which have been reported to improve forecasting performance concerning uncertainty and variability. This study also proposes a new model that integrates various machine-learning approaches to improve the accuracy of hotel sales demand forecasting. Specifically, this study proposes a new time series forecasting model based on XGBoost that selectively utilizes a local model by clustering with DTW K-means and a global model using the entire data to improve forecasting performance. The hotel demand forecasting model that selectively utilizes global and regional models proposed in this study is expected to impact the growth of the hotel and travel industry positively and can be applied to forecasting in other business fields in the future.

• Journal of Wetlands Research
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• v.26 no.3
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• pp.227-235
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• 2024

Inland wetlands provide important ecosystem services or functions, including biodiversity conservation, water purification, flood control, and carbon sequestration. However, many inland wetlands are being degraded by urbanization and industrialization, raising the need for conservation and restoration. This study proposes the adoption of No Net Loss(NLL) of Wetland for wetland conservation and restoration in Korea by the review of the literatures. To this end,, we analyzed the wetland conservation and management systems of the United States, Canada, Germany, Japan, and Australia, and identified institutional features and success factors of each country, and sought ways to adapt them to domestic conditions of Korea. The case of the United States highlights the importance of legal frameworks and public-private collaboration, Canada demonstrates systematic management approaches, Germany maintains a balance between development and conservation, Japan underscores the need for cooperative conservation efforts, and Australia emphasizes the efficiency of offset markets. The introduction and operation of these schemes are expected to contribute to climate change mitigation, biodiversity conservation, and water quality improvement, but ongoing research and policy efforts are needed to ensure that the schemes are well established.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.645-661
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• 2024

Today, the development of new technologies due to the 4th industrial revolution requires work performance methods such as non-face-to-face collaboration. In response to this, various VR collaboration tools are emerging, but VR collaboration tools for brainstorming, which are used in collaboration or design development work, are not provided. Therefore, despite the advantages and possibilities of VR for non-face-to-face collaboration, there are limitations in practical use. Accordingly, the development of VR collaboration tools in a digitalized work environment is necessary, and research on UI design development for this is required. The purpose of this study is to propose a VR collaboration tool prototype by developing an interaction UI design that applies user hand behavior elements that appear during collaboration sessions through user research. This study was a qualitative study. The research method was to conduct user research through observation and in-depth interviews, and as a result of analyzing the data obtained from this, five types of user hand behavior elements were derived. In this study, an interaction UI design was developed that reflects hand gestures as behavioral elements. And using Unity and the Oculus Integration SDK Kit, we created a prototype VR collaboration tool that can be used without a controller. As a result of conducting a user evaluation of the prototype produced in this study, it was found that users had difficulty making hand gestures accurately, and it was possible to find areas for improvement in UI design. It is expected that this study will help develop interaction UI design for VR collaboration tools that can increase work efficiency.

• Journal of Service Research and Studies
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• v.14 no.3
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• pp.231-250
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• 2024

This research aims to enhance donor engagement by increasing the transparency of nonprofit donation platforms. Donations are primarily based on social trust, and a lack of transparency on these platforms can significantly reduce donor motivation. To address this issue, the study analyzes the user experience of existing donation platforms, identifies problems, and explores potential improvements. The research began with a literature review to examine the social need for donations and their effectiveness. The findings indicate that donors place a high value on transparency and are less willing to donate when this element is lacking. Specifically, when donors can clearly see how their contributions are being utilized, they experience greater psychological satisfaction and are more likely to continue donating. The study analyzed various platforms to identify issues causing user discomfort and compared elements aimed at enhancing transparency. By employing the KJ affinity method and the Double Diamond process, the study aimed to understand the problem's nature and propose solutions considering the interactions between donors and nonprofits. A key conclusion is the critical importance of making information more accessible and intuitive. The findings suggest that greater transparency can help build donor trust, improve nonprofit efficiency, and contribute to a more robust giving ecosystem. Additionally, platforms with increased transparency facilitate ongoing communication between donors and nonprofits, fostering an environment where donors become more actively engaged in their giving. This strategy is expected to play a vital role in promoting a sustainable culture of giving based on mutual trust.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.3
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• pp.76-86
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• 2024

This study sought to introduce smart urban regeneration to solve the problem of aging and substandard housing in large cities that occurred during the rapid industrialization and urbanization of local cities in Korea. Accordingly, this study aims to activative the old downtown through the convergence of the existing urban regeneration project and smart city project and to improve the physical, social, and economic aspects. As a research method, the literature related to smart cities and urban regeneration was systematically reviewed, and the possibility of introducing smart city services in the Samho-dong district of Yangsan City was explored through domestic and foreign case analysis. As a result of the research, the necessity of smart urban regeneration was highlighted, and the conclusion was reached that it is important to improve the efficiency of urban regeneration projects by using information and communication technology and strengthen sustainability by urban regeneration. This study is expected to contribute to the activative the old downtown and the improvement of the quality of life of citizens, and it is necessary to strengthen the interaction between smart city and urban regeneration in the future, and the introduction of smart city services suitable for local characteristics is judged to play an important role in sustainable urban development through local community and citizen participation.

• Journal of Radiation Industry
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• v.18 no.3
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• pp.167-171
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• 2024

Technetium-99 (⁹⁹Tc) is recognized as a critical concern in the disposal of spent nuclear fuel due to its long half-life and remarkable stability, existing predominantly as TcO₄^- in the natural environment. The anionic form of technetium is highly soluble and mobile, posing significant environmental risks from the viewpoint of nuclear waste management. Thus, developing efficient and cost-effective sorbents for aqueous Tc(VII) is essential for mitigating relevant contamination. In the present work, the adsorption characteristics of Re(VII), a chemical analog of Tc(VII), were investigated using the clay mineral bentonite, modified with two different organic cations: hexadecylpyridinium (HDPy) and hexadecyltrimethylammonium (HDTMA). Sorption experiments were conducted at a liquid-to-solid ratio of 1 g/L with Re(VII) solutions prepared at concentrations from 10^-4 mol/L to 10^-6 mol/L. The sorption ratio and distribution coefficients were determined with samples collected at reaction times of 10, 50, 100, and 500 minutes after 0.45 ㎛ syringe filtration. In parallel, the modified bentonite samples were further analyzed using the X-ray diffraction (XRD) method to understand the adsorption mechanism of Re(VII) onto the target minerals. According to the quantification analysis results, a rapid equilibrium reaction of aqueous Re(VII) for all modified bentonite samples was identified. Moreover, near-complete adsorption of Re(VII) was observed when the bentonite was modified at 200-400% of its cation exchange capacity (CEC) for both organic cations. For cases of lower modification, the HDTMA-modified bentonite showed relatively higher adsorption efficiency compared with the one modified with HDPy. This result was inferred to be due to the difference in inter-layer spacing based on the characteristics of the organic cations. It is expected that the results obtained through this study will serve as a preliminary case for the synthesis of adsorbents for the retardation of highly mobile anionic radionuclides, such as I and Tc, in the natural environment.

• Journal of the Korean Geotechnical Society
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• v.40 no.4
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• pp.69-79
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• 2024

Field geotechnical data are obtained from various field and laboratory tests and are documented in geotechnical investigation reports. For efficient design and construction, digitizing these geotechnical parameters is essential. However, current practices involve manual data entry, which is time-consuming, labor-intensive, and prone to errors. Thus, this study proposes an automatic data extraction method from geotechnical investigation reports using image-based deep learning models and text-mining techniques. A deep-learning-based page classification model and a text-searching algorithm were employed to classify geotechnical investigation report pages with 100% accuracy. Computer vision algorithms were utilized to identify valid data regions within report pages, and text analysis was used to match and extract the corresponding geotechnical data. The proposed model was validated using a dataset of 205 geotechnical investigation reports, achieving an average data extraction accuracy of 93.0%. Finally, a user-interface-based program was developed to enhance the practical application of the extraction model. It allowed users to upload PDF files of geotechnical investigation reports, automatically analyze these reports, and extract and edit data. This approach is expected to improve the efficiency and accuracy of digitizing geotechnical investigation reports and building geotechnical databases.

• Economic and Environmental Geology
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• v.57 no.4
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• pp.353-362
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• 2024

This study examined the spectral characteristics of sediments according to moisture content using an unmanned aerial vehicle (UAV)-based hyperspectral sensor and evaluated the efficiency of moisture content detection at different flight altitudes. For this purpose, hyperspectral images in the 400-1000nm wavelength range were acquired and analyzed at altitudes of 40m and 80m for sediment samples with various moisture contents. The reflectance of the sediments generally showed a decreasing trend as the moisture content increased. Correlation analysis between moisture content and reflectance showed a strong negative correlation (r < -0.8) across the entire 400-900nm range. The moisture content detection model constructed using the Random Forest technique showed detection accuracies of RMSE 2.6%, R² 0.92 at 40m altitude and RMSE 2.2%, R² 0.95 at 80m altitude, confirming that the difference in accuracy between altitudes was minimal. Variable importance analysis revealed that the 600-700nm band played a crucial role in moisture content detection. This study is expected to be utilized in efficient sediment moisture management and natural disaster prediction in the field of environmental monitoring in the future.

• Journal of Internet of Things and Convergence
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• v.10 no.3
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• pp.19-24
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• 2024

Recent advances in large-scale data processing technologies such as big data, cloud computing, and artificial intelligence have increased the demand for high-performance storage devices in data centers and enterprise environments. In particular, the fast data response speed of storage devices is a key factor that determines the overall system performance. Solid state drives (SSDs) based on the Non-Volatile Memory Express (NVMe) interface are gaining traction, but new bottlenecks are emerging in the process of handling large data input and output requests from multiple hosts simultaneously. SSDs typically process host requests by sequentially stacking them in an internal queue. When long transfer length requests are processed first, shorter requests wait longer, increasing the average response time. To solve this problem, data transfer timeout and data partitioning methods have been proposed, but they do not provide a fundamental solution. In this paper, we propose a dual queue based scheduling scheme (DQBS), which manages the data transfer order based on the request order in one queue and the transfer length in the other queue. Then, the request time and transmission length are comprehensively considered to determine the efficient data transmission order. This enables the balanced processing of long and short requests, thus reducing the overall average response time. The simulation results show that the proposed method outperforms the existing sequential processing method. This study presents a scheduling technique that maximizes data transfer efficiency in a high-performance SSD environment, which is expected to contribute to the development of next-generation high-performance storage systems

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.219-227
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• 2024

The rapidly changing security environment and technological innovations of the 21st century present new challenges to military organizations. Particularly, as the MZ generation, comprised of Millennials (born 1981-1996) and Generation Z (born 1997-2012), emerges as the primary workforce in the military, traditional military personnel management methods are being called into question. The MZ generation, as digital natives, are technologically proficient, prioritize personal growth and quality of life, and prefer horizontal communication and participation. The purpose of this study is to reestablish talent acquisition and retention strategies for military organizations, considering the characteristics and demands of the MZ generation. To this end, we analyzed advanced talent management techniques from the corporate sector and explored ways to apply them to the unique context of military organizations. Additionally, by examining the current status and challenges of the Korean military, we attempted a balanced approach that considers both global trends and Korea's specific circumstances. The research results suggest various strategies including career development programs, cultural innovation, improvement of reward systems, participatory decision-making, enhancement of digital competencies, and creation of flexible work environments. These strategies are expected to improve the efficiency and competitiveness of military organizations while simultaneously enhancing job satisfaction and organizational commitment among MZ generation service members.