• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.209-217
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• 2024

Recent years have seen a notable increase in fire incidents in university cafeterias, yet the social attention to these occurrences remains limited. Despite quick responses to these incidents preventing loss of life, the need for large-scale evacuation in such high foot traffic areas can cause significant disruptions, economic losses, and panic among students. The potential for stampedes and unpredictable damage during inadequate evacuations underscores the importance of fire safety and evacuation research in these settings. Previous studies have explored evacuation models in various university environments, emphasizing the influence of environmental conditions, personal characteristics, and behavioral patterns on evacuation efficiency. However, research specifically focusing on university cafeterias is scarce. This paper addresses this gap by employing Pathfinder software to analyze fire spread and evacuation safety in a university cafeteria. Pathfinder, an advanced emergency evacuation assessment system, offers realistic 3D simulations, crucial for intuitive and scientific evacuation analysis. The studied cafeteria, encompassing three floors and various functional areas, often exceeds a capacity of 1500 people, primarily students, during peak times. The study includes constructing a model of the cafeteria in Pathfinder and analyzing evacuation scenarios under different fire outbreak conditions on each floor. The paper sets standard safe evacuation criteria (ASET > RSET) and formulates three distinct evacuation scenarios, considering different fire outbreak locations and initial evacuation times on each floor. The simulation results reveal the impact of the fire's location and the evacuation preparation time on the overall evacuation process, highlighting that fires on higher floors or longer evacuation preparation times tend to reduce overall evacuation time.In conclusion, the study emphasizes a multifaceted approach to improve evacuation safety and efficiency in educational settings. Recommendations include expanding staircase widths, optimizing evacuation routes, conducting regular drills, strengthening command during evacuations, and upgrading emergency facilities. The use of information and communication technology for managing emergencies is also suggested. These measures collectively form a comprehensive framework for ensuring safety in educational institutions during fire emergencies.

• Steel and Composite Structures
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• v.52 no.2
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• pp.199-215
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• 2024

The Caynarachi Bridge is a 130 m long posttensioned steel-concrete composite bridge built in Peru. The structural performance of this bridge under construction loads is reviewed in this paper using numerical simulation. Hence, a numerical model using shell finite elements to trace its deformational behavior at service conditions is proposed. The geometry and boundary conditions of the superstructure are updated according to the construction schedule. Firstly, the adequacy of the proposed model is validated with the field measurements obtained from the static truck load test. Secondly, the study of other scenarios less explored in research are performed to investigate the effect of some variables on bridge performance such as time effects, sequence of execution of concrete slabs and type of supports conditions at the abutments. The obtained results show that the original sequence of execution of the superstructure better behaves mechanically in relation to the other studied scenarios, yielding smaller stresses at critical cross sections with staging. It is also demonstrated that an improper slab staging may lead to more critical stresses at the studied cross sections and that casting the concrete slab at the negative moment regions first can lead to an optimal design. Also, the long-term displacements can be accurately predicted using an equivalent composite resistance cross section defined by a steel to concrete modulus ratio equal to three. This article gives some insights into the potential shortcomings or advantages of the original design through high-fidelity finite element simulations and reinforces the understating of posttensioned composite bridges with staging.

• Knowledge Management Research
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• v.25 no.3
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• pp.173-200
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• 2024

This study investigates the dynamics of the digital divide and social inclusion in a society increasingly influenced by artificial intelligence (AI) by 2035. Using a 2×2 matrix scenario analysis, the research explores future scenarios based on two axes: the level of AI technological advancement and societal response. The scenarios range from an "Inclusive AI Society," characterized by advanced AI technology and comprehensive societal measures, to an "AI Polarized Society," marked by rapid AI advancement but fragmented social responses, exacerbating inequalities. The study emphasizes the critical role of both technological and social strategies in addressing the challenges of AI-driven societies. It provides policy recommendations to mitigate potential disparities, highlighting the need for inclusive education, equitable access to AI benefits, and adaptive governance frameworks. The findings aim to inform policymakers and stakeholders about the impacts of AI on social inclusion and the digital divide, proposing strategies for fostering a balanced and equitable AI future.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1293-1293
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• 2024

Virtual reality (VR) is increasingly utilized in the construction industry for diverse applications. Immersive virtual reality (IVR) offers practical experiences and educational opportunities for workers, enhancing productivity and safety. Efforts to optimize IVR involve analyzing biometric responses to monitor concentration, assess learning efficiency, and deliver personalized content. However, IVR faces challenges such as high production costs and prolonged production periods. Additionally, integrating biometric response recording into IVR experiences requires separate modules, further extending production timelines. To address these challenges, an integrated platform is necessary to streamline IVR production, user experience, and biometric response setup and recording. This study introduces such a platform designed to enhance the efficacy of IVR experiences through real-time biometric response analysis. The proposed platform comprises three main processes: (i) IVR content production using Unity; (ii) biometric response definition; and (iii) IVR content experience accompanied by generated logs for biometric responses. Firstly, IVR content production using Unity involves the development of IVR environments and scenarios. The platform incorporates diverse 3D models, including urban landscapes, building elements, and furniture, as the basis for IVR environments. Scenarios are constructed by integrating events into these environments, triggered by conditions such as reaching specific locations, the passage of time, or user interactions. Upon event activation, participants are presented with description UIs, quiz UIs, or route guidance, facilitating engagement and progression through interaction. Secondly, biometric responses encompass eye tracking and EEG. Eye tracking captures pupil diameter and fixation status on Areas of Interest (AOI), defined during IVR content production. EEG recording options include signals from each channel by default, as well as frequency-specific signals and EEG metrics such as attention, stress, fatigue, valence, and arousal. The platform supports the addition of new EEG metrics, enhancing customization and recording capabilities. Lastly, IVR content can be experienced alongside generated logs for biometric responses. The dataset enables monitoring and evaluation of participants' learning performance during IVR experiences, with the potential to enhance worker safety and productivity through immersive practical training and education.

• Journal of Korean Neurosurgical Society
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• v.67 no.5
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• pp.493-509
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• 2024

In neurointensive care units (NICUs), particularly in cases involving traumatic brain injury (TBI), swift and accurate decision-making is critical because of rapidly changing patient conditions and the risk of secondary brain injury. The use of artificial intelligence (AI) in NICU can enhance clinical decision support and provide valuable assistance in these complex scenarios. This article aims to provide a comprehensive review of the current status and future prospects of AI utilization in the NICU, along with the challenges that must be overcome to realize this. Presently, the primary application of AI in NICU is outcome prediction through the analysis of preadmission and high-resolution data during admission. Recent applications include augmented neuromonitoring via signal quality control and real-time event prediction. In addition, AI can integrate data gathered from various measures and support minimally invasive neuromonitoring to increase patient safety. However, despite the recent surge in AI adoption within the NICU, the majority of AI applications have been limited to simple classification tasks, thus leaving the true potential of AI largely untapped. Emerging AI technologies, such as generalist medical AI and digital twins, harbor immense potential for enhancing advanced neurocritical care through broader AI applications. If challenges such as acquiring high-quality data and ethical issues are overcome, these new AI technologies can be clinically utilized in the actual NICU environment. Emphasizing the need for continuous research and development to maximize the potential of AI in the NICU, we anticipate that this will further enhance the efficiency and accuracy of TBI treatment within the NICU.

• Journal of Korean Society on Water Environment
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• v.24 no.2
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• pp.147-155
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• 2008

Because of increased nonpoint source runoff potential at highland agricultural fields of Kangwon province, effective agricultural management practices are required to reduce the inflow of sediment and other nonpoint source pollutants into the water bodies. The watershed-scale model, Soil and Water Assessment Tool (SWAT), model has been used worldwide for developing effective watershed management. However, the SWAT model simulated sediment values are significantly affected by the number of subwatershed delineated. This result indicates that the SWAT estimated watershed characteristics from the watershed delineation process affects the soil erosion and sediment behaviors. However, most SWAT users do not spend time and efforts to analyze variations in sediment estimation due to watershed delineation with various threshold value although topography falsification affecting soil erosion process can be caused with watershed delineation processes. The SWAT model estimates the field slope length of Hydrologic Response Unit (HRU) based on average slope of subwatershed within the watershed. Thus the SWAT ArcView GIS Patch, developed by using the regression relationship between average watershed slope and field slope length, was utilized in this study to compare the simulated sediment from various watershed delineation scenarios. Four watershed delineation scenarios were made with various threshold values (700 ha, 300 ha, 100 ha, and 75 ha) and the SWAT estimated flow and sediment values were compared with and without applying the SWAT ArcView GIS Patch. With the SWAT ArcView GIS Patch applied, the simulated flow values are almost same irrespective of the number of subwatershed delineated while the simulated flow values changes to some extent without the SWAT ArcView GIS Patch applied. However when the SWAT ArcView GIS Patch applied, the simulated sediment values vary 9.7% to 29.8% with four watershed delineation scenarios, while the simulated sediment values vary 0.5% to 126.6% without SWAT ArcView GIS applied. As shown, the SWAT estimated flow and sediment values are not affected by the number of watershed delineation significant compared with the estimated flow and sediment value without applying the SWAT ArcView GIS Patch.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.11-19
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• 2014

This study is analyze future climate and land cover change affects behaviors for amount of streamflow and sediment discharge within basin. We used the climate forecast data in RCP 4.5 and 8.5 (2011-2100) which is opposite view for each other among RCP scenarios that are discussed for 5th report for IPCC. Land cover map built based on a social economic storyline in RCP 4.5/8.5 using Logistic Regression model. In this study we set three scenarios: one scenario for climate change only, one for land cover change only, one for Last both climate change and land cover change. It simulated amount of streamflow and sediment discharge and the result showed a very definite change in the seasonal variation both of them. For climate change, spring and winter increased the amount of streamflow while summer and fall decreased them. Sediment showed the same pattern of change steamflow. Land cover change increases the amount of streamflow while it decreases the amount of sediment discharge, which is believed to be caused by increase of impervious Surface due to urbanization. Although land cover change less affects the amount of streamflow than climate change, it may maximize problems related to the amount of streamflow caused by climate change. Therefore, it's required to address potential influence from climate change for effective water resource management and prepare suitable measurement for water resource.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.47-56
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• 2020

Decline of pine forests happens in Korea due to various disturbances such as insect pests, forest fires and extreme climate, which may further continue with ongoing climate change. For conserving and reestablishing pine forests, understanding climate-induced future shifts of pine tree distribution is a critical concern. This study predicts future geographical distribution of Pinus densiflora, using Maximum Entropy Model (MaxEnt). Input data of the model are locations of pine tree stands and their environmental variables such as climate were prepared for the model inputs. Alternative future projections for P. densiflora distribution were conducted with RCP 4.5 and RCP 8.5 climate change scenarios. As results, the future distribution of P. densiflora steadily decreased under both scenarios. In the case of RCP 8.5, the areal reductions amounted to 11.1% and 18.7% in 2050s and 2070s, respectively. In 2070s, P. densiflora mainly remained in Kangwon and Gyeongsang Provinces. Changes in temperature seasonality and warming winter temperature contributed primarily for the decline of P. densiflora., in which altitude also exerted a critical role in determining its future distribution geographic vulnerability. The results of this study highlighted the temporal and spatial contexts of P. densiflora decline in Korea that provides useful ecological information for developing sound management practices of pine forests.

• Ecology and Resilient Infrastructure
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• v.8 no.3
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• pp.154-163
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• 2021

This study was carried out to identify the factors affecting the distribution of suitable habitats for Geranium carolinianum, which was naturalized in South Korea, and to predict the changes of distribution in the future. We collected occurrence data of G. carolinianum at 68 sites in South Korea, and applied the MaxEnt model under climate change scenarios (SSP2-4.5, and SSP5-8.5). Precipitation seasonality (bio15), mean temperature of warmest quarter (bio10), and mean temperature of driest quarter (bio09) had high contribution for potential distribution of G. carolinianum. According to climate change scenarios, high suitable habitats of G. carolinianum occupied 6.43% of the land of South Korea in historical period (1981~2010), and 92.60% under SSP2-4.5, and 98.36% undr SSP5-8.5 in far future (2071~2100).

• Economic and Environmental Geology
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• v.57 no.2
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• pp.107-117
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• 2024

The objective of this study is to estimate riverbed fluctuations and the volume of aggregate extraction attributable to climate change. Rainfall-runoff modeling, utilizing the SWAT model based on climate change scenarios, as well as long-term riverbed fluctuation modeling, employing the HEC-RAS model, were conducted for the Nonsan River basin. The analysis of rainfall-runoff and sediment transport under the SSP5-8.5 scenario for the early part of the future indicates that differences in annual precipitation may exceed 600 mm, resulting in a corresponding variation in the basin's sediment discharge by more than 30,000 tons per year. Additionally, long-term riverbed fluctuation modeling of the lower reaches of the Nonsan Stream has identified a potential aggregate extraction area. It is estimated that aggregate extraction could be feasible within a 2.455 km stretch upstream, approximately 4.6 to 6.9 km from the confluence with the Geum River. These findings suggest that the risk of climate crises, such as extreme rainfall or droughts, could increase due to abnormal weather conditions, and the increase in variability could affect long-term aggregate extraction. Therefore, it is considered important to take into account the impact of climate change in future long-term aggregate extraction planning and policy formulation.