• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.6
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• pp.3-14
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• 2018

The aim of this study is to propose a method for calculating the weight of walking energy in ERAM model by calculating it for the analysis of vertical and horizontal spaces in a building. Conventional theories on the space analysis in the field of architectural planning predict the pedestrian volume of network spaces in urban street or in two-dimensional plane within a building, however, for vertical and horizontal spaces in a building, estimates of the pedestrian volume by those theories are limited. Because in the spatial syntax and ERAM model have been applied weights such as the spatial depth, adjacent angles, and physical distances available only to the two-dimensional same layer or plane. Therefore, the following basic assumptions and analysis conditions in this study were established for deriving a predictor of pedestrian volume in vertical and horizontal spaces of a building. The basic premise of space analysis is not to address the relationship between the pedestrian volume and the spatial structure itself but to the properties of spatial structure connection that human beings experience. The analysis conditions in three-dimensional spaces are as follows : 1) Measurement units should be standardized on the same scale, and 2) The connection characteristics between spaces should influence the accessibility of human beings. In this regard, a factor of walking energy has the attributes to analyze the connection of vertical and horizontal spaces and satisfies the analysis conditions presented in this study. This study has two implications. First, this study has shown how to quantitatively calculate the walking energy after a factor of walking energy was derived to predict the pedestrian volume in vertical and horizontal spaces. Second, the method of calculating the walking energy can be applied to the weights of the ERAM model, which provided the theoretical basis for future studies to predict the pedestrian volume of vertical and horizontal spaces in a building.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.146-159
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• 2021

vehicle simulator as part of an empirical analysis the driving characteristics of elderly drivers. To this end, the driving characteristics of the elderly driver from previous study review. he driving characteristics of the elderly the driving elderly driver and general driverIn summarizing these experimental results, the -test showed different driving characteristics from general drivers in all items except for one side of the lane, such as driving speed and driving operation (brake, throttle, steering operation) at a significance level of 95%. Second, when changing lanes, it was difficult for elderly driver to maintain speed and secure an appropriate distance between carslderly driver changed lanes even in inappropriate situations (short distances between cars). Third, in unexpected situation, elderly drivers needed more distance and time.

• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.45-52
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• 2022

In the field of UAM, which is attracting attention as a next-generation transportation system, technology developments for using UAVs have been actively conducted in recent years. Since UAVs adopted with these technologies are mainly operated in urban areas, it is imperative that accidents are prevented. However, it is not easy to predict the abnormal flight state of an UAV causing a crash, because of its strong non-linearity. In this paper, we propose a method for predicting a flight state of an UAV, based on a CNN-LSTM hybrid model. To predict flight state variables at a specific point in the future, the proposed model combines the CNN model extracting temporal and spatial features between flight data, with the LSTM model extracting a short and long-term temporal dependence of the extracted features. Simulation results show that the proposed method has better performance than the prediction methods, which are based on the existing artificial neural network model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.1
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• pp.123-140
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• 2022

Recently, research on solving problems that have introduced the concept of smart city in countries and companies around the world is in progress due to various urban problems. A smart city converges the city's ICT, connects all the city's components with a network, collects and delivers data, and consists of a supply chain composed of various IoT products and services. The increase in various cyber security threats and supply chain threats in smart cities is inevitable, in addition to establishing a framework such as supply chain security policy, authentication of each data provider and service according to data linkage and appropriate access control are required in a Zero-Trust point of view. To this end, a smart city security model has been developed for smart city security threats in Korea, but security requirements related to supply chain security and zero trust are insufficient. This paper examines overseas smart city security trends, presents international standard security requirements related to ISMS-P and supply chain security, as well as security requirements for applying zero trust related technologies to domestic smart city security models.

• Smart Structures and Systems
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• v.29 no.1
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• pp.17-28
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• 2022

The cable component of cable-stayed bridges is gradually impacted by weather conditions, vehicle loads, and material corrosion. The stayed cable is a critical load-carrying part that closely affects the operational stability of a cable-stayed bridge. Damaged cables might lead to the bridge collapse due to their tension capacity reduction. Thus, it is necessary to develop structural health monitoring (SHM) techniques that accurately identify damaged cables. In this work, a combinational identification method of three efficient techniques, including statistical analysis, clustering, and neural network models, is proposed to detect the damaged cable in a cable-stayed bridge. The measured dataset from the bridge was initially preprocessed to remove the outlier channels. Then, the theory and application of each technique for damage detection were introduced. In general, the statistical approach extracts the parameters representing the damage within time series, and the clustering approach identifies the outliers from the data signals as damaged members, while the deep learning approach uses the nonlinear data dependencies in SHM for the training model. The performance of these approaches in classifying the damaged cable was assessed, and the combinational identification method was obtained using the voting ensemble. Finally, the combination method was compared with an existing outlier detection algorithm, support vector machines (SVM). The results demonstrate that the proposed method is robust and provides higher accuracy for the damaged cable detection in the cable-stayed bridge.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.1
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• pp.54-65
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• 2022

Species distribution models are a useful tool for predicting future distribution and establishing a preemptive response of invasive species. However, few studies considered the possibility of habitat for the aquatic organism and the number of target sites was relatively small compared to the area. Environmental DNA (eDNA) is the emerging tool as the methodology obtaining the bulk of species presence data with high detectability. Thus, this study applied eDNA survey results of Micropterus salmoides and Lepomis macrochirus to species distribution modeling by seasons in the Anyang stream network. Maximum Entropy (MaxEnt) model evaluated that both species extended potential distribution area in October compared to July from 89.1% (12,110,675 m²) to 99.3% (13,625,525 m²) for M. salmoides and 76.6% (10,407,350 m²) to 100% (13,724,225 m²) for L. macrochirus. The prediction value by streams was varied according to species and seasons. Also, models elucidate the significant environmental variables which affect the distribution by seasons and species. Our results identified the potential of eDNA methodology as a way to retrieve species data effectively and use data for building a model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.83-95
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• 2022

This paper proposes a system that performs object detection and distance estimation for application to autonomous vehicles. Object detection is performed by a network that adjusts the split grid to the input image ratio using the characteristics of the recently actively used deep learning model YOLOv4, and is trained to a custom dataset. The distance to the detected object is estimated using a bounding box and homography. As a result of the experiment, the proposed method improved in overall detection performance and processing speed close to real-time. Compared to the existing YOLOv4, the total mAP of the proposed method increased by 4.03%. The accuracy of object recognition such as pedestrians, vehicles, construction sites, and PE drums, which frequently occur when driving to the city center, has been improved. The processing speed is approximately 55 FPS. The average of the distance estimation error was 5.25m in the X coordinate and 0.97m in the Y coordinate.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.269-269
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• 2023

기후 변화로 인한 강우 패턴의 변화는 도심지 방재성능 목표를 상회하는 홍수로 이어져 침수피해를 가중시키고 있다. 이로 인한 도시침수 피해를 저감하기 위하여 도시침수 예측모형 개발이 활발히 이루어지고 있으나, 대규모 관망으로 이루어진 복잡한 도심지 우수관망을 모의하기 때문에 분석속도가 느려 실시간 예측 적용에 한계점이 있다. 도시침수 분석에 가장 많이 활용되는 대표적인 모형인 SWMM(Storm Water Management Model)은 복잡한 관망을 비교적 빠르고 정확히 해석할 수 있어 유용하지만, 이 또한 대도심의 우수관망 모의 시 많은 시간이 소요되며, 관망 정밀도 기준이 정의되어 있지 않아 분석에 어려움이 있다. 이러한 문제점을 해결하기 위하여 본 연구에서는 관망 간소화 기법(유역면적의 밀도, 관거 직경, 관로의 길이 등)을 적용하고, 이에 따른 주요 지선과 간선의 수위 변화와 침수흔적도를 비교하여 분석결과의 정확성을 담보하는 관망 간소화 수준을 파악하고 도시침수 분석 시 적정 간소화 기준과 자동 간소화 방안을 제시하고자 한다. 도시침수 분석 시 우수관망 자동 간소화를 위하여 Python을 활용한 코드를 작성하였으며, SWMM의 .inp 파일을 읽어들여 Dataframe형태로 저장한 후 분석을 위한 데이터 가공, 간소화 기준에 따른 분류, 간소화 대상 수리·수문인자 연산, 인접 간선에 연결, 간소화된 .inp파일 저장의 총 6단계로 구성하였다. 연구 대상지역은 도림천 유역으로 설정하였으며, 초기자료는 맨홀 30,469, 관거 32,443, 소유역 30,586개로 이루어져 있으며, 모의 시간은 약 2시간 30분이 소요되었다. 유역면적 100x100 미만을 대상으로 수행 시 맨홀 9,965, 관거 10,464, 소유역 9,240개로 관거의 복잡도가 약 1/3 감소하였으며, 모의 시간은 약 43분으로 기존대비 약 72% 단축되는 것으로 나타났다. 실제 침수가 발생한 주요지점들을 비교한 결과 R² 0.85 ~ 0.92로 예측모형의 정확도에 큰 영향을 끼치지 않는 것으로 나타났다. 도시침수모형 최적 간소화를 통해 모형의 복잡성을 줄이고, 계산량을 줄여 모형의 수행시간을 단축시킬 수 있으며, 불필요한 우수관망을 제거하거나 병합함으로써, 모형의 예측력 향상과 분석과 해석에 효율적으로 사용될 수 있을 것으로 기대한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.294-294
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• 2022

In 2013, the Asian Development Bank classified the Philippines among the countries facing high food security risks. Evidence has suggested that climate change has affected agricultural productivity, and the effect of extreme climatic events notably drought has worsened each year. This had resulted in serious hydrological repercussions by limiting the timely water availability for the agriculture sector. Laguna is the 3^rd most populated province in the country, and it serves as one of the food baskets that feed the region and nearby provinces. In addition to climate change, population growth, rapid industrialization, and urban encroachment are also straining the delicate balance between water demand and supply. Studies have projected that the province will experience less rainfall and an increase in temperature, which could simultaneously affect water availability and crop yield. Hence, understanding the composite threat of climate change for crop yield and water consumption is imperative to devise mitigation plans and judicious use of water resources. The water footprint concept elaborates the water used per unit of crop yield production and it can approximate the dual impacts of climate change on water and agricultural production. In this study, the water footprint (WF) of six main crops produced in Laguna were estimated during 2010-2020 by following the methodology proposed by the Water Footprint Network. The result of this work gives importance to WF studies in a local setting which can be used as a comparison between different provinces as well as a piece of vital information to guide policy makers to adopt plans for crop-related use of water and food security in the Philippines.

• Land and Housing Review
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• v.14 no.2
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• pp.1-17
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• 2023

In Korea, the population size of the elderly is rapidly increasing, and housing for them is emerging as an important issue. In particular, Aging in Place (AIP) has steadily been presented as a direction of welfare for the elderly. This study empirically examines the effect of the interactions of the elderly with their children on residential mobility for older Koreans. To do so, this study employed random effect logistic regression models with the dataset of the 2008-2020 Korean Longitudinal Study of Aging. The findings are as follows. First, it was found that the interaction with their children increased the probability of residential mobility for older Koreans in both metropolitan areas and non-metropolitan areas. Second, as age increased, the interaction with their children tended to further promote residential mobility for older Koreans, but such effects varied depending on related variables. Third, it was confirmed that the possibility of further promoting residential mobility for older Koreans increased through the interaction effects of the variables associated with the interaction with their children. This study suggests policy implications for the residential mobility of older Koreans, i.e., whether the interactions with their children improve independent residential environments by enhancing housing stability, in terms of AIP.