• Journal of the Korean Society for Library and Information Science
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• v.57 no.4
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• pp.333-351
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• 2023

This study investigates user behavior in library spaces through the lens of AI camera analytics. By leveraging the face recognition and tracking capabilities of AI cameras, we accurately identified the gender and age of visitors and meticulously collected video data to track their movements. Our findings revealed that female users slightly outnumbered male users and the dominant age group was individuals in their 30s. User visits peaked between Tuesday to Friday, with the highest footfall recorded between 14:00 and 15:00 pm, while visits decreased over the weekend. Most visitors utilized one or two specific spaces, frequently consulting the information desk for inquiries, checking out/returning items, or using the rest area for relaxation. The library stacks were used approximately twice as much as they were avoided. The most frequented subject areas were Philosophy(100), Religion(200), Social Sciences(300), Science(400), Technology(500), and Literature(800), with Literature(800) and Religion(200) displaying the most intersections with other areas. By categorizing users into five clusters based on space utilization patterns, we discerned varying objectives and subject interests, providing insights for future library service enhancements. Moreover, the study underscores the need to address the associated costs and privacy concerns when considering the broader application of AI camera analytics in library settings.

• Journal of Korean Library and Information Science Society
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• v.54 no.3
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• pp.321-346
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• 2023

A data paper describing research data helps credit researchers producing the data while helping other researchers verify previous research and start new research by reusing the data. Publishing a data paper and depositing data to a public data repository are increasing with these benefits. A domestic academic society that plans to publish data papers faces challenges, including timely acquiring tremendous knowledge concerning data paper structures and templates, peer review policy and process, and trustworthy data repositories, as a data paper has different characteristics, unlike a research paper. However, the need for more research and information concerning the critical elements of data paper and the peer-review process makes it difficult to operate for data paper review and publication. To address these issues, we propose essential concepts of the data paper and the data paper peer-review, including the process model of the peer-review with in-depth analysis of five data journals' data paper templates, articles, and other guides worldwide. Academic societies intending to publish or add data papers as a new type of paper may establish policies and define a peer-review process by adopting the proposed conceptual models, effectively streamlining the preparation of data paper publication.

• Phonetics and Speech Sciences
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• v.15 no.3
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• pp.75-82
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• 2023

Automatic speech recognition (ASR) has been revolutionized with deep learning-based approaches, among which self-supervised learning methods have proven to be particularly effective. In this study, we aim to enhance the performance of OpenAI's Whisper model, a multilingual ASR system on the Korean language. Whisper was pretrained on a large corpus (around 680,000 hours) of web speech data and has demonstrated strong recognition performance for major languages. However, it faces challenges in recognizing languages such as Korean, which is not major language while training. We address this issue by fine-tuning the Whisper model with an additional dataset comprising about 1,000 hours of Korean speech. We also compare its performance against a Transformer model that was trained from scratch using the same dataset. Our results indicate that fine-tuning the Whisper model significantly improved its Korean speech recognition capabilities in terms of character error rate (CER). Specifically, the performance improved with increasing model size. However, the Whisper model's performance on English deteriorated post fine-tuning, emphasizing the need for further research to develop robust multilingual models. Our study demonstrates the potential of utilizing a fine-tuned Whisper model for Korean ASR applications. Future work will focus on multilingual recognition and optimization for real-time inference.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.953-964
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• 2023

Climate change is undeniably the most urgent challenge that humanity faces today. Despite this, the level of public awareness and understanding of climate change remains insufficient, indicating a need for more proactive education and the development of supportive content. In particular, it is crucial to intensify climate change education during elementary and secondary schooling when values and ethical consciousness begin to form. However, there is a significant lack of age-appropriate, experiential educational content. To address this, our study has developed an innovative 3D simulator, enabling learners to indirectly experience the effects of climate change, specifically sea-level rise. This simulator considers not only sea-level rise caused by climate change but also storm surges, which is a design based on the analysis of long-term wave observation big data. To make the simulator accessible and engaging for students, we utilized the 'Unity' game engine. We further propose using this simulator as a part of a comprehensive educational program on climate change.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.63-65
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• 2023

BIM and AR technologies have been assessed as a means of enhancing productivity within the construction industry, through the provision of effortless access to critical data on site, achieved via the projection of 3D models and associated information onto actual structures. However, most of the previous researches for applying AR technology in construction quality management has been performed for construction projects in general, resulting in only overall on-site management solutions. Also, a few previous researches for the application of AR in the quality management of specific elements like reinforcements focused only on simple projection, so conducting specific quality inspection was impossible. Hence, this study aimed to develop a practically applicable BIM-based AR quality management system targeted for reinforcements. For the development of this system, the reinforcement inspection items on the quality checklist used at railway construction sites were analyzed, and four types of AR functions that can effectively address these items were developed and installed. The validation result of the system for the actual railway bridge showed a degradation of projection stability. This problem was solved through model simplification and enhancement of the AR device's hardware performance, and then the normal operation of the system was validated. Subsequently, the final developed reinforcement quality inspection system was evaluated for practical applicability by on-site quality experts, and the efficiency of inspection would significantly increase when using the AR system compared to the current inspection method for reinforcements.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.3-11
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• 2023

To address the high accident rate in the construction industry, there is a growing interest in implementing virtual reality (VR)-based construction safety training. However, existing training approaches often failed to consider learners' individual characteristics, resulting in inadequate training for some individuals. This study aimed to investigate the impact of personal characteristics on learning performance in VR-based construction safety training using machine learning and SHAP (SHAPley Additional exPlanations). This study revealed that age exerted the greatest influence on learning performance, while work experience had the least impact. Furthermore, age exhibited a negative relationship with learning performance, indicating that the introduction of VR-based construction safety training can be effective for younger individuals. On the other hand, academic degree, qualifications, and work experience exhibited a positive relationship. To enhance learning performance for individuals with lower academic degree, it is necessary to provide content that is easier to understand. The lower qualifications and work experience have minimal impact on learning performance, so it is important to consider other learners' characteristics so as to provide appropriate educational content. This study confirmed that personal characteristics can significantly affect learning performance in VR-based construction safety training, highlighting the potential for leveraging these findings to provide effective safety training for construction workers.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.33-43
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• 2024

This research assessed the applicability of the You Only Look Once (YOLO)v8 and DeepLabv3+ models for the effective detection of compost heaps, identified as a significant source of non-point source pollution. Utilizing high-resolution imagery acquired through Unmanned Aerial Vehicles(UAVs), the study conducted a comprehensive comparison and analysis of the quantitative and qualitative performances. In the quantitative evaluation, the YOLOv8 model demonstrated superior performance across various metrics, particularly in its ability to accurately distinguish the presence or absence of covers on compost heaps. These outcomes imply that the YOLOv8 model is highly effective in the precise detection and classification of compost heaps, thereby providing a novel approach for assessing the management grades of compost heaps and contributing to non-point source pollution management. This study suggests that utilizing UAVs and deep learning technologies for detecting and managing compost heaps can address the constraints linked to traditional field survey methods, thereby facilitating the establishment of accurate and effective non-point source pollution management strategies, and contributing to the safeguarding of aquatic environments.

• The Journal of Sustainable Design and Educational Environment Research
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• v.22 no.4
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• pp.9-17
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• 2023

This study explores school location, school environment, educational conditions, and appropriate scale of schools in the context of Sejong City's development area and identifies effective school establishment plans based on the analysis of the needs of the educational community. The research questions for this study include, first, what is the change trend in the number of students as a result of the opening of schools in the development area of Sejong City to the present, and what differences are there between Sejong and other new cities? Second, what challenges arise in school location due to the occurrence of oversized schools and undergraduate institutions? Third, what challenges arise in school location that would limit the ability to create a safe school environment? Fourth, what aspects need to be improved in school location decisions to promote proper placement? A survey was conducted among parents and faculty members to collect data. The findings revealed that first, when establishing a school, identifying an appropriate location for the school was the top priority of the respondents. The second was the proximity of the school to dense housing, with a parent drop zone next to the school site. Third, to address the issue of lack of playgrounds and special class and care classes, respondents called for various measures such as securing school sites within a certain area. Finally, integrated operation schools and school facilities are required in preparation for decreasing school-age populations due to low birth rates.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.5
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• pp.30-43
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• 2023

Green infrastructure(GI) is considered a key strategy in establishing sustainable communities. However, research on GI from the perspective of urban system dynamics and resilience lacks depth, as does its integration with physical design. This research addresses two primary causes. First, there is a gap in methods between existing GI planning, which considers static variables, and urban modeling research, which addresses dynamic variables. Second, there is a gap in information between landscape design and urban modeling research. To address these issues, this study proposes an integrated modeling approach in consideration of design decision-making. By combining the LEAM model and MCDA model, this study evaluates the relationship between GI services and socioeconomic growth, while spatially forecasting the geographies of GI demand in 2050. The resulting information reveals a potential degradation in ecosystem services over the region due to Chicago's sub-urbanization. This indicates that there would be a spatial shift in GI demand, emphasizing the need for comprehensive, dynamic GI strategies. This study further discusses the applications of evidence-based design in a studio environment. This study aims to contribute to the GeoDesign literature in terms of the creation of a more resilient urban environment by facilitating efficient evidence-based decision-making.

• Journal of Korea Port Economic Association
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• v.39 no.3
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• pp.191-210
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• 2023

The Covid-19 pandemic has had a significant impact on global logistics and supply chains, leading to major discrepancies in logistics performance across countries worldwide. Through an examination of logistics performance index and supply chain tracking data, this study aimed to identify the changes in global supply chains and logistics environments during the pandemic. The analysis of the logistics performance index showed that overall, countries around the world, especially developed nations, showed improvements in metrics such as customs and border management efficiency, the quality of trade and transport infrastructure, capability and quality of logistics services, and cargo tracking abilities. However, the competitive pricing feasibility of international transportation and the on-time delivery frequency of goods saw a decline due to the pandemic's effects. The supply chain tracking data revealed that ports in Asian countries demonstrated high processing efficiency. In contrast, the U.S. and European countries took comparatively more time. Particularly for air cargo, parcels, and express shipments, the U.S. showed relatively longer processing times, leading to logistical delays. In conclusion, during the Covid-19 pandemic, Asian countries maintained relatively high efficiency in their logistics and trade environments. Conversely, the U.S. and some European countries showed delays and decreased efficiency in various metrics. In the future, efforts should be made to address delays and congestion, namely, the deceleration of logistics processes.