• Title/Summary/Keyword: emergency response systems

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Feasibility study on using crowdsourced smartphones to estimate buildings' natural frequencies during earthquakes

  • Ting-Yu Hsu;Yi-Wen Ke;Yo-Ming Hsieh;Chi-Ting Weng
    • Smart Structures and Systems
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    • v.31 no.2
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    • pp.141-154
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    • 2023
  • After an earthquake, information regarding potential damage to buildings close to the epicenter is very important during the initial emergency response. This study proposes the use of crowdsourced measured acceleration response data collected from smartphones located within buildings to perform system identification of building structures during earthquake excitations, and the feasibility of the proposed approach is studied. The principal advantage of using crowdsourced smartphone data is the potential to determine the condition of millions of buildings without incurring hardware, installation, and long-term maintenance costs. This study's goal is to assess the feasibility of identifying the lowest fundamental natural frequencies of buildings without knowing the orientations and precise locations of the crowds' smartphones in advance. Both input-output and output-only identification methods are used to identify the lowest fundamental natural frequencies of numerical finite element models of a real building structure. The effects of time synchronization and the orientation alignment between nearby smartphones on the identification results are discussed, and the proposed approach's performance is verified using large-scale shake table tests of a scaled steel building. The presented results illustrate the potential of using crowdsourced smartphone data with the proposed approach to identify the lowest fundamental natural frequencies of building structures, information that should be valuable in making emergency response decisions.

A Selection Method of Implementation Area for Emergency Vehicle Preemption System Using Dispatch Data Analysis (출동현황자료 분석을 통한 재난대비 긴급차량 우선신호제어 시스템 도입지역 선정방안 연구)

  • Sung, Joong Gi;Ha, Dongik
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.2
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    • pp.24-35
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    • 2016
  • Emergency Vehicle Preemption(EVP) is an operation method which helps to improve response condition of Emergency Vehicle(EV) and it has not yet been introduced in Korea. In order to implement the system, it requires step-by-step plan and selecting a priority area for trial operation. Since a municipal government such as Seoul is too large so it is limited in time and cost to analyze the whole area. Therefore, quantitative and effective selection method for priority area is critical. The aim of this study is to propose a selection method of implementation area for EVP system using the dispatch data analysis. This study also determined the priority area for EVP implementation by analyzing the dispatch data in Seoul and conducted a simulation to evaluate the effects of implementing EVP.

Research on the Convergence of CCTV Video Information with Disaster Recognition and Real-time Crisis Response System (CCTV 영상 정보와 재난재해 인식 및 실시간 위기 대응 시스템의 융합에 관한 연구)

  • Kim, Ki-Bong;Geum, Gi-Moon;Jang, Chang-Bok
    • Journal of the Korea Convergence Society
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    • v.8 no.3
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    • pp.15-22
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    • 2017
  • People generally believe that disaster forecast and warning systems and response systems are well established in the age of cutting edge technology. As a matter of fact, reliable systems to respond to disasters are not properly equipped, as we witnessed the Sewol ferry disaster in 2014. The existing forecast and warning systems are based on sensor information with low efficiency, and image information is only operated by monitoring staff manually. In addition, the interconnection between a warning system and a response system in order to decide how to cope with the recognized disaster is very insufficient. This paper introduces the CCTV based disaster recognition and real time crisis response system composed of the CCTV image recognition engine and the crisis response technique. This system has brought the possibility to overcome the limitations of existing sensor based forecast and warning systems, and to resolve the problems in the absence of monitoring staff when responding to crisis.

The Road Reservation Scheme in Emergency Situation for Intelligent Transportation Systems (지능형 교통 시스템을 위한 긴급 상황에서의 도로 예약 방식)

  • Yoo, Jae-Bong;Park, Chan-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.11B
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    • pp.1346-1356
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    • 2011
  • Transportation has been playing important role in our society by providing for people, freight, and information. However, it cuts its own throat by causing car accidents, traffic congestion, and air pollution. The main cause of these problems is a noticeable growth in the number of vehicles. The easiest way to mitigate these problems is to build new road infrastructures unless resources such as time, money, and space are limited. Therefore, there is a need to manage the existing road infrastructures effectively and safely. In this paper, we propose a road reservation scheme that provides fast and safe response for emergency vehicles using ubiquitous sensor network. Our idea is to allow emergency vehicle to reserve a road on a freeway for arriving to the scene of the accident quickly and safely. We evaluate the performance by three reservation method (No, Hop, and Full) to show that emergency vehicles such as ambulances, fire trucks, or police cars can rapidly and safely reach their destination. Simulation results show that the average speed of road reservation is about 1.09 ~ 1.20 times faster than that of non-reservation at various flow rates. However, road reservation should consider the speed of the emergency vehicle and the road density of the emergency vehicle processing direction, as a result of Hop Reservation and Full Reservation performance comparison analysis. We confirm that road reservation can guarantee safe driving of emergency vehicles without reducing their speed and help to mitigate traffic congestion.

The commercialization of ESS PCS replacing Emergency Generator (비상발전용 ESS(Energy Storage System) 상용화 개발)

  • Park, Minjun;Seo, Jungwon;Hwang, Kwangkyu;Park, Juhyun;Jang, Jeahoon;Kim, Heejung
    • Proceedings of the KIPE Conference
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    • 2016.07a
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    • pp.461-462
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    • 2016
  • 본 논문은 100kW 급 비상발전용 ESS 상용화 개발을 제안한다. 비상발전기란 전력계통이 정지되었을 때 발전장치를 구동시켜 전력을 생산하는 자가발전설비를 말한다. 제안하는 시스템은 2Level 전압형 100kW 급 비상발전용 ESS 로써 정상 시 계통 전원과 동기 운전을 수행하는 계통 연계형 전력변환장치이다. 수배전 수용가에 설치되어 운영이 가능하며 일반적인 ESS PCS 기능인 주파수 조정 (Frequency Regulation), 출력 안정화, 첨두부하 저감 (Peak Shaving), 부하평준화 (Load Leveling), 수요반응 (Demand Response)에 추가하여, 자가발전 (Black Start), 무효전력제어 등의 기능을 적용 하였다. 제안된 100kW 급 비상발전기용 ESS PCS 는 시뮬레이션 및 프로토 타입을 이용하여 성능을 검증하였다.

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Evaluating the Quality of the Differential Police Response Strategy: Applications of Statistical Quality Control Charts (통계적 품질관리도를 활용한 차별적 경찰대응전략의 평가)

  • Lee, Myungwoo;Kim, Jihoon;Park, Hanho
    • The Journal of the Korea Contents Association
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    • v.16 no.6
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    • pp.529-536
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    • 2016
  • The purpose of this research is to evaluate the quality of Differential Police Response strategy. Although it has been approximately three years since these new police response systems were introduced, there is no research to evaluate them empirically. Using two types of statistical quality control techniques, Xbar-R control charts for variables data and P charts for attributes data, this study analyzes approximately 3,000 calls reported throughout the year 2012 to the 112 Integrated Dispatch Center in Ik-san police station. The Xbar-R control charts revealed that the police did not consistently respond to an emergency call for service (i.e., code one case) within 3 minutes. The P control chart also identified that there was a significant variation in the portion/number of defective calls where police failed to respond to non-emergency calls for service within 5 minutes. The results from this study suggest the police may need to review the target response time for code 1 and code 2 respectively.

Methodology of seismic-response-correlation-coefficient calculation for seismic probabilistic safety assessment of multi-unit nuclear power plants

  • Eem, Seunghyun;Choi, In-Kil;Yang, Beomjoo;Kwag, Shinyoung
    • Nuclear Engineering and Technology
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    • v.53 no.3
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    • pp.967-973
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    • 2021
  • In 2011, an earthquake and subsequent tsunami hit the Fukushima Daiichi Nuclear Power Plant, causing simultaneous accidents in several reactors. This accident shows us that if there are several reactors on site, the seismic risk to multiple units is important to consider, in addition to that to single units in isolation. When a seismic event occurs, a seismic-failure correlation exists between the nuclear power plant's structures, systems, and components (SSCs) due to their seismic-response and seismic-capacity correlations. Therefore, it is necessary to evaluate the multi-unit seismic risk by considering the SSCs' seismic-failure-correlation effect. In this study, a methodology is proposed to obtain the seismic-response-correlation coefficient between SSCs to calculate the risk to multi-unit facilities. This coefficient is calculated from a probabilistic multi-unit seismic-response analysis. The seismic-response and seismic-failure-correlation coefficients of the emergency diesel generators installed within the units are successfully derived via the proposed method. In addition, the distribution of the seismic-response-correlation coefficient was observed as a function of the distance between SSCs of various dynamic characteristics. It is demonstrated that the proposed methodology can reasonably derive the seismic-response-correlation coefficient between SSCs, which is the input data for multi-unit seismic probabilistic safety assessment.

Learning Probabilistic Kernel from Latent Dirichlet Allocation

  • Lv, Qi;Pang, Lin;Li, Xiong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.6
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    • pp.2527-2545
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    • 2016
  • Measuring the similarity of given samples is a key problem of recognition, clustering, retrieval and related applications. A number of works, e.g. kernel method and metric learning, have been contributed to this problem. The challenge of similarity learning is to find a similarity robust to intra-class variance and simultaneously selective to inter-class characteristic. We observed that, the similarity measure can be improved if the data distribution and hidden semantic information are exploited in a more sophisticated way. In this paper, we propose a similarity learning approach for retrieval and recognition. The approach, termed as LDA-FEK, derives free energy kernel (FEK) from Latent Dirichlet Allocation (LDA). First, it trains LDA and constructs kernel using the parameters and variables of the trained model. Then, the unknown kernel parameters are learned by a discriminative learning approach. The main contributions of the proposed method are twofold: (1) the method is computationally efficient and scalable since the parameters in kernel are determined in a staged way; (2) the method exploits data distribution and semantic level hidden information by means of LDA. To evaluate the performance of LDA-FEK, we apply it for image retrieval over two data sets and for text categorization on four popular data sets. The results show the competitive performance of our method.

Learning Similarity with Probabilistic Latent Semantic Analysis for Image Retrieval

  • Li, Xiong;Lv, Qi;Huang, Wenting
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.4
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    • pp.1424-1440
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    • 2015
  • It is a challenging problem to search the intended images from a large number of candidates. Content based image retrieval (CBIR) is the most promising way to tackle this problem, where the most important topic is to measure the similarity of images so as to cover the variance of shape, color, pose, illumination etc. While previous works made significant progresses, their adaption ability to dataset is not fully explored. In this paper, we propose a similarity learning method on the basis of probabilistic generative model, i.e., probabilistic latent semantic analysis (PLSA). It first derives Fisher kernel, a function over the parameters and variables, based on PLSA. Then, the parameters are determined through simultaneously maximizing the log likelihood function of PLSA and the retrieval performance over the training dataset. The main advantages of this work are twofold: (1) deriving similarity measure based on PLSA which fully exploits the data distribution and Bayes inference; (2) learning model parameters by maximizing the fitting of model to data and the retrieval performance simultaneously. The proposed method (PLSA-FK) is empirically evaluated over three datasets, and the results exhibit promising performance.

A Research on the Vehicle Routing Problem in the Disaster Scene (재난 현장의 구호 자원 운송 차량 경로에 관한 연구)

  • Han, Sumin;Jeong, Hanil;Kim, Kidong;Park, Jinwoo
    • Korean Management Science Review
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    • v.33 no.1
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    • pp.101-117
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    • 2016
  • In 2000s, incidence of natural disaster is increasing continuously. Therefore, the necessity of research on the effective disaster response is emphasized. Korea is not safe from natural disaster. Natural disasters like torrential downpours, typhoons have occurred more frequently than before. In addition disasters like droughts and MERS has also occurred. Therefore, needs for effective systems and algorithms to respond disaster are increased. This study covers the vehicle routing problem for effective logistics in disaster situations caused by natural disasters. The emergency vehicle route problem has different property from the general vehicle route problem. It has the property of the importance of deadline, the uncertain and dynamic demand information, and the uncertainty in information transfer. In this study, a solution that focused on the importance of deadline. In this study, the heuristic solution using the genetic algorithm are suggested. Finally the simulation experiment which reflects the actual environment are conducted to verify the performance of the solution.