• Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
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• v.12 no.6
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• pp.627-640
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• 2018

Submetering electricity consumption data enables more detail input of end use components, such as lighting, plug, HVAC, and occupancy in building energy modeling. However, such an modeling efforts and results are rarely tried and published in terms of the estimation accuracy of electricity demand. In this research, actual submetering data obtained from a university building is analyzed and provided for building energy modeling practice. As alternative modeling cases, conventional modeling method (Case-1), using reference schedule per building usage, and main metering data based modeling method (Case-2) are established. Detail efforts are added to derive prototypical schedules from the metered data by introducing variability index. The simulation results revealed that Case-1 showed the largest error as we can expect. And Case-2 showed comparative error relative to Case-3 in terms of total electricity estimation. But Case-2 showed about two times larger error in CV (RMSE) in lighting energy demand due to lack of End Use consumption information.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.1
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• pp.1-9
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• 2021

Most commercial buildings among existing RC buildings in Korea have a multi-story wall-frame structure where RC shear wall is commonly used as its core at stairways or elevators. The members of the existing middle and low-rise wall-frame buildings are likely arranged in ordinary details considering building occupancy, and the importance and difficulty of member design. This is because there are few limitations, considerations, and financial burdens on the code for designing members with ordinary details. Compared with the intermediate or unique details, the ductility and overstrength are insufficient. Furthermore, the behavior of the member can be shear-dominated. Since shear failure in vertical members can cause a collapse of the entire structure, nonlinear characteristics such as shear strength and stiffness deterioration should be adequately reflected in the analysis model. With this background, an 8-story RC wall-frame building was designed as a building frame system with ordinary shear walls, and the effect of reflecting the shear failure mode of columns and walls on the collapse mechanism was investigated. As a result, the shear failure mode effect on the collapse mechanism was evident in walls, not columns. Consequently, it is recommended that the shear behavior characteristics of walls are explicitly considered in the analysis of wall-frame buildings with ordinary details.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.167-180
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• 2021

The "sharing economy" describes a type of business built on the sharing of resources - allowing customers to access goods when needed. While sharing goods has always been a common practice among friends, family, and neighbors, in recent years, the concept of sharing has moved from a community practice into a profitable business model. This study explores gaps between customers' actual usages and current policies on accommodation sharing by analyzing what needs to be done for the better establishment of sharing economy in society. The purpose of this study is to investigate perceptions of accommodation sharing by analyzing reviews and negative aspects that help resolve complaints and improve better services through policy establishment. This study investigates key attributes that influence business performance to improve citizens' decision-making for the usage of accommodation sharing. This study applies qualitative research by collecting demand- and supply-side reviews from selected registered accommodations using a random sampling procedure. This study finds that guests prefer entire house sharing with instrumental attributes related to properties. Entire house sharing of multiple dwellings shows business impacts in terms of high occupancy rate on the platform, while there are policy concerns with entire house sharing. The results provide policy and managerial implications by suggesting proper policies and considering relationships with citizens.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1146-1153
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• 2022

As the population is aging, accidents involving elderly people are also increasing (2014:11,667 persons; 2018: 11,797 persons). In the case of the elderly population, falling accidents are the primary direct or indirect causes of death; in particular, they face an elevated risk of staircase falls. This study proposes a method of evaluating the safety of staircases using Building Information Modeling (BIM)-based virtual simulation. By making a virtual user with the behavioral characteristics of the elderly respond to a staircase in a BIM model, its safety performance can be evaluated. The evaluation criteria were derived from regulations, elements, and characteristics relevant to the safety of staircases. To validate the proposed method, safety evaluation tests were simulated on actual staircases. The evaluation result of the test simulation shows the safety scores of 1.97 points for the elderly user and 2.95 points for the average male adult user against a required safety score of a minimum of 2 points. That is, safety is relative to users as the safety of the same staircase can be different depending upon the different behavioral characteristics of users. The study suggests that the risk of staircase-related fall accidents to the elderly can be reduced by improving staircase designs through the proposed method.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.28-35
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• 2013

The construction industry has introduced the Leadership in Energy and Environmental Design (LEED) rating system to promote objective evaluations of the sustainability of buildings. Three important values to consider when implementing sustainability are the associated environmental, social, and economic impacts. Recently, researchers have begun to investigate the real estate value of LEED certified buildings in terms of the rental cost, occupancy rate, cost per unit area, and resale value in order to better understand the economic benefits of the LEED rating system. However, the economic benefits also encompass economic effects such as the impact of LEED certified buildings on neighborhood real estate values surrounding the certified buildings. This research examines whether the enhanced real estate value of LEED certified buildings in New York City extends to surrounding commercial buildings, utilizing spatial analysis via a Geographic Information System (GIS) and the hedonic pricing method to derive meaningful economic relationships. The results provide practical insights into the economic effect of LEED certified buildings that will be of interest to city officials and planners, as well as the owners, developers, investors and other stakeholders of surrounding buildings.

• Journal of Navigation and Port Research
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• v.41 no.3
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• pp.137-148
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• 2017

Port service level is a metric of competitiveness among ports for the operating/managing bodies such as the terminal operation company (TOC), Port Authority, or the government, and is used as an important indicator for shipping companies and freight haulers when selecting a port. Considering the importance of metrics, we developed software to objectively define and manage six important service indicators exclusive to container and bulk terminals including: berth occupancy rate, ship's waiting ratio, berth throughput, number of berths, average number of vessels waiting, and average waiting time. We computed the six service indicators utilizing berth 1 through berth 5 in the container terminals and berth 1 through berth 4 in the bulk terminals. The software model allows easy computation of expected ship's waiting ratio over berth occupancy rate, berth throughput, counts of berth, average number of vessels waiting and average waiting time. Further, the software allows prediction of yearly throughput by utilizing a ship's waiting ratio and other productivity indicators and making calculations based on arrival patterns of ship traffic. As a result, a TOC is able to make strategic decisions on the trade-offs in the optimal operating level of the facility with better predictors of the service factors (ship's waiting ratio) and productivity factors (yearly throughput). Successful implementation of the software would attract more shipping companies and shippers and maximize TOC profits.

• Journal of IKEEE
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• v.23 no.1
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• pp.112-119
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• 2019

In this paper, we propose a deep learning structure suitable for embedded system. The flame detection process of the proposed deep learning structure consists of four steps : flame area detection using flame color model, flame image classification using deep learning structure for flame color specialization, $N{\times}N$ cell separation in detected flame area, flame image classification using deep learning structure for flame shape specialization. First, only the color of the flame is extracted from the input image and then labeled to detect the flame area. Second, area of flame detected is the input of a deep learning structure specialized in flame color and is classified as flame image only if the probability of flame class at the output is greater than 75%. Third, divide the detected flame region of the images classified as flame images less than 75% in the preceding section into $N{\times}N$ units. Fourthly, small cells divided into $N{\times}N$ units are inserted into the input of a deep learning structure specialized to the shape of the flame and each cell is judged to be flame proof and classified as flame images if more than 50% of cells are classified as flame images. To verify the effectiveness of the proposed deep learning structure, we experimented with a flame database of ImageNet. Experimental results show that the proposed deep learning structure has an average resource occupancy rate of 29.86% and an 8 second fast flame detection time. The flame detection rate averaged 0.95% lower compared to the existing deep learning structure, but this was the result of light construction of the deep learning structure for application to embedded systems. Therefore, the deep learning structure for flame detection proposed in this paper has been proved suitable for the application of embedded system.

• Journal of Auto-vehicle Safety Association
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• v.10 no.2
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• pp.20-28
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• 2018

Currently, sharp increase of car is on the rise as a serious social problem due to loss of lives from car accident and environmental pollution. There is a study on ITS (Intelligent Transportation System) to seek coping measures. As for the commercialization of ITS, we aim for occupancy of world market through ASV (Advanced Safety Vehicle) related system development and international standardization. However, the domestic environment is very insufficient. Core factor technologies of ITS are Adaptive Cruise Control, Lane Keeping Assist System, Forward Collision Warning System, AEB (Autonomous Emergency Braking) system etc. These technologies are applied to cars to support driving of a driver. AEB system is stop the car automatically based on the result decided by the relative speed and distance with obstacle detected through sensor attached on car rather than depending on the driver. The purpose of AEB system is to measure the distance and speed of car and to prevent accident. Thus, AEB will be a system useful for prevention of accident by decreasing car accident along with the development of automobile technology. This study suggests a scenario to suggest a test evaluation method that accords with domestic environment and active response of international standard regarding the test evaluation method of AEB. Also, by setting the goal with function for distance, it suggests theoretic model according to the result. And the study aims to verify the theoretic evaluation standard per proposed scenario using car which is installed with AEB device through field car driving test on test road. It will be useful to utilize the suggested scenario and theoretical model when conducting AEB test evaluation.

• Structural Engineering and Mechanics
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• v.85 no.3
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• pp.381-391
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• 2023

The seismic performance of the tall building equipped with a tuned mass damper (TMD) considering soil-structure interaction (SSI) effects is well studied in the literature. However, these studies are performed on the nominal model of the seismic-excited structural system with SSI. Hence, the outcomes of the studies may not valid for the actual structural system. To address the study gap, the reliability theory as a useful and powerful method is utilized in the paper. The present study aims to carry out reliability analyses on tall buildings equipped with TMD under near-field pulse-like (NFPL) ground motions considering SSI effects using a subset simulation (SS) method. In the presence of uncertainties of the structural model, TMD device, foundation, soil, and near-field pulse-like ground motions, the numerical studies are performed on a benchmark 40-story building and the failure probabilities of the structures with and without TMD are evaluated. Three types of soils (dense, medium, and soft soils), different earthquake magnitudes (M_w = 7,0. 7,25. 7,5 ), different nearest fault distances (r = 5. 10 and 15 km), and three seismic performance levels of immediate occupancy (IO), life safety (LS), and collapse prevention (CP) are considered in this study. The results show that tall buildings built near faults and on soft soils are more affected by uncertainties of the structural and ground motion models. Hence, ignoring these uncertainties may result in an inaccurate estimation of the maximum seismic responses. Also, it is found the TMD is not able to reduce the failure probabilities of the structure in the IO seismic performance level, especially for high earthquake magnitudes and structures built near the fault. However, TMD is significantly effective in the reduction of failure probability for the LS and CP performance levels. For weak earthquakes and long fault distances, the failure probabilities of both structures with and without TMD are near zero, and the efficiency of the TMD in the reduction of failure probabilities is reduced by increasing earthquake magnitudes and the reduction of fault distance. As soil softness increases, the failure probability of structures both with and without TMD often increases, especially for severe near-fault earthquake motion.

• Journal of The Korea Institute of Healthcare Architecture
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• v.29 no.3
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• pp.7-15
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• 2023

Purpose: This study was conducted with the aim of presenting spatial planning directions for evacuation spaces based on an analysis of the performance of horizontal evacuation during the early stages of fire incidents in a geriatric hospital. Methods: Based on a review of previous studies, the research model was designed by establishing occupancy conditions, evacuation, and fire scenarios. The analysis model was developed by considering vulnerable areas in terms of evacuation movement and analyzing the results of evacuation performance. Furthermore, the study analyzed the improvement in evacuation performance by arranging refuge areas. Results: The results of the study are as follows. Firstly, vulnerability spots were identified in terms of evacuation performance by schematizing Required Safe Egress Time, Available Safe Egress Time, and their differences. Secondly, the Required Safe Egress Time in the adjacent public spaces along the escape routes of occupants was found to be higher compared to the Available Safe Egress Time. Thirdly, the results of the correlation analysis between the difference in Available Safe Egress Time and Required Safe Egress Time during the early stages of a fire, as well as their constituent factors, demonstrated that user congestion is a more significant factor in compromising evacuation safety than the physical changes in the fire condition. Fourthly, the analysis of evacuation time was conducted by designating refuge areas where occupants can evacuate within a sufficient timeframe. This led to a decrease in the Required Safe Egress Time. Implications: This study is expected to be used as data on the direction of evacuation space planning to improve the evacuation performance of Geriatric Hospital.