• Journal of Contemporary Eastern Asia
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• 제15권1호
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• pp.98-110
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• 2016

Building resilient community is often a complicated process to be gained by interorganizational collaboration. Since patterns of interorganizational relations among governments and sectors are constantly changing due to internal and external factors in the field of emergency management, understanding the dynamic nature of interorganizational collaboration is a critical step for improving a community’s ability to bounce back from a catastrophic event. From two theoretical perspectives, this research aims to examine the essential role of working across levels of governments and sectors in building resilient community by focusing on sources of community resiliency and a strong commitment. The empirical evidence highlights the importance of studying resilience as a way to understand the motivation and incentive for organizations to work jointly during emergency response. The study of organizational resilience also draws attention for the importance of various forms of interorganizational collaboration such as formal and informal relations. It also highlights how local organizations can utilize their relations to seek resources without necessarily jeopardizing their ability to perform their core organizational functions.

• 디지털콘텐츠학회 논문지
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• 제18권3호
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• pp.567-575
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• 2017

위치기반 서비스는 재난 경보 시스템 및 추천시스템 등의 다양한 응용에서 중요한 역할을 한다. 이들 응용들은 위치정보(위도, 경도 등) 뿐만 아니라 위치에 대한 사건(지진, 태풍 등)의 영향력을 필요로 한다. 최근 이러한 위치에 대한 사건의 영향력을 제공하기 위해, 다양한 형태의 정보(지진 정보와 센서 정보)를 이용한 위치 신뢰도 계산 방법이 연구 되었다. 이전의 연구에서는 사건의 영향을 선형으로 감소시키는 형태로 위치 신뢰도를 계산하였다. 이 논문에서는 소셜 미디어를 추가적으로 활용하여 사건의 위치에 대한 영향력, 즉 위치 신뢰도를 향상 시키는 만드는 방법을 제안하였다. 우선 지진정보와 소셜 미디어 데이터를 수집하는 시스템을 설계하였다. 두번째로, 지진정보에 기반한 위치 신뢰도 계산 방법을 소개하였다. 최종적으로 소셜 미디어에 기반하여 공간적으로 분산되는 형태로 신뢰도를 증강시키는 방법을 통해 위치 신뢰도 정보를 더욱 풍부하게 제공하는 방법을 제안하였다.

• Steel and Composite Structures
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• 제52권5호
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• pp.571-581
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• 2024

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. This work studies the tracking control problem of a class of strict-feedback nonlinear systems with input saturation nonlinearity. Under the framework of dynamic surface control design, RBF neural networks are introduced to approximate the unknown nonlinear dynamics. In order to address the impact of input saturation nonlinearity in the system, an auxiliary control system is constructed, and by introducing a class of first-order low-pass filters, the problems of large computation and computational explosion caused by repeated differentiation are effectively solved. In response to unknown parameters, corresponding adaptive updating control laws are designed. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

• 한국농공학회논문집
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• 제62권3호
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• pp.71-83
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• 2020

Resilience is the capacity to maintain essential services under a range of circumstances from normal to extreme. It is achieved through the ability of assets, networks, systems and management to anticipate, absorb and recover from disturbance. It requires adaptive capacity in respect of current and future risks and uncertainties as well as experience to date. The agricultural infrastructures with high resilience can not only reduce the size of the disaster relatively, but also minimize the loss by reducing the time required for recovery. This study aims to evaluate the most suitable drought countermeasures with the analysis of various resilience indices by predicting future agricultural water shortage under land use and climate change scenarios for agricultural areas in Jeju Island. The results showed that the permanent countermeasure is suitable than the temporary countermeasures as drought size and the cost required for recovery increase. Wide-area water supply system, which is a kind of water grid system, is identified as the most advantageous among countermeasures. It is recommended to evaluate the capability of agricultural infrastructure against drought with the various Resilience Indices for reliable assessment of long-term effect.

• Ecology and Resilient Infrastructure
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• 제7권4호
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• pp.345-352
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• 2020

최근 하천범람에 따른 피해를 최소화하기 위해서는 대피를 위한 선행시간을 확보하는 것이 매우 중요하다. 본 연구에서는 현재 하천에서 측정되고 있는 수위 관측 자료를 이용하여 이상호우 발생시 하류의 수위를 예측하였다. 수위 예측을 위해 다중회귀모형 및 인공신경망 모형을 섬강시험유역에 적용하였다. 다중회귀모형 및 인공신경망 모형의 학습에는 섬강시험유역의 2002년부터 2010년까지의 수위 관측 자료를 이용하였으며, 학습된 모형을 이용하여 발생 가능한 수위를 예측하였다. 모의 결과 인공신경망 수위예측모형의 결정계수는 0.991 - 0.999로 나타났으며, 다중회귀수위예측 모형의 결정계수는 0.945 - 0.990로 나타나 인공신경망을 이용한 수위예측모형이 다중회귀모형보다 좀 더 나은 예측 결과를 나타내는 것을 확인할 수 있었다. 본 연구결과는 향후 하천에서 선행시간을 확보한 홍수 예보 구축에 활용할 수 있을 것으로 판단된다.