Problems In Emergency Management Research Articles

Developing a Community-Based Disaster Relief Management System

This study aimed to enhance disaster relief operations in Tuguegarao City by proposing a more efficient management system framework. Utilizing interviews and thematic analysis, researchers in 2017 identified problems in emergency management, such as inadequate equipment, budget constraints, and issues with relief distribution. The study highlighted confusion and political bias in relief operations, leading to mistrust in the local government. In response, the researchers developed a community-based Disaster Relief Management System (CBDRMS) framework, inspired by Foucault’s power/knowledge analytics. This framework emphasizes transparency, communication, and good relationships among LGUs, NGOs, and recipients. The proposed online system includes a portal and a Facebook Page for data storage and communication, aiming to empower stakeholders and foster discourse for effective disaster relief management. The researchers believe that this approach can overcome barriers, leading to development and improved disaster response.

Influence of the Government Department on the Production Capacity Reserve of Emergency Enterprises Based on Multi-Scenario Evolutionary Game

With the frequent occurrence of world emergency events, the emergency management of government departments in various countries is facing great challenges. In the context of the COVID-19 pandemic, the shortage of various emergency resources is prominent, and the emergency supplies reserve combined by governments and enterprises is an important guarantee for dealing with emergency management problems. This paper mainly studies the impact of a government sustainability-oriented innovation policy on the production capacity reserve of security emergency enterprises (SEEs), and constructs an evolutionary game model between the local government and SEEs. Then, it focuses on the impact of a reputation mechanism on the government enterprise cooperative reserve. According to the condition of a country, the central government’s punishment mechanism is introduced, and the evolutionary and stable strategies of the behavior choices of the local government and SEEs are compared and analyzed. Combined with the evolution degree of emergency events, the numerical simulation analysis is used to deduce and simulate the multi scenario of the example model. The results show that the reputation mechanism can effectively promote the evolution of government and enterprises to the ideal state under various scenarios. When the punishment intensity of the central government is higher than the total benefit of the implementation of the mere formality policy by the local government, it can effectively prevent the omission of the local government. This study provides a new idea for the government to formulate reasonable policies to promote SEEs to reserve production capacity, which is more conducive to government enterprise cooperation to deal with emergency events.

A CAST-Based Analysis of the Metro Accident That Was Triggered by the Zhengzhou Heavy Rainstorm Disaster.

Emergency management research is used to deal with the increasing number of extreme weather threats in urban areas. This paper uses causal analysis based on systems theory (CAST) to review the subway water ingress accident and the government’s emergency management actions in Zhengzhou, Henan Province, during the heavy rainstorm disaster on 20 July 2021. The aims of this article are to establish safety control structures at both the enterprise level and the government level, and to systematically analyze the problems in emergency management in Zhengzhou City. Our analysis found that the construction of disaster prevention facilities restricted emergency management. Therefore, we suggest that enterprises and governments not only pay attention to emergency management, but also to the construction of disaster prevention facilities. This article also points out that the system of chief executive responsibility that is implemented in China is becoming a double-edged sword in emergency management. Our study makes recommendations for enhancing the capacities of emergency management, points out the shortcomings of the existing emergency management structure, and provides knowledge gained for future emergency management research.

CNN-LSTM neural network model for fine-grained negative emotion computing in emergencies

In the Web 2.0 era, governments are facing the challenge of analyzing the emotional tendency of online public opinion during emergencies to regulate people’s emotions more effectively and maintain social stability. When dealing with large-scale short, unordered texts and extracting text features, the existing studies often face the problem of sparse features, ignoring fine-grained negative emotions. Aiming at those drawbacks and inspired by the dependency relationship among Chinese words, an emotion computing algorithm based on a binary tree is designed to assign words with emotional intensity. Then, the paper proposes a CNN-LSTM model for Chinese language sentiment classification to conduct local feature extraction and maintain long-term dependencies. The proposed model is validated using different traditional models and classifiers. The results show that the CNN-LSTM model achieved competitive classification performance. Finally, our approach was applied to practical emergency management problems, exploring the impact of government information release on negative emotion regulation to test its reliability. The experimental results validated that compared with traditional methods, this approach improved the accuracy of sentiment classification and possesses higher classification performance. The empirical analysis demonstrated that the CNN-LSTM method was rapid, effective and feasible and could be more suitable for optimizing emotion regulation policies.

The new normal: A catalyst for leadership adaptation in a tumultuous world-Let's stop applying 20th century solutions to 21st century problems in emergency management.

The COVID-19 Pandemic continues to be one of the most formidable public health challenges in modern history. Amidst the backdrop of new variants of the SARS CoV-2 virus, the pandemic that everyone thought would be over in a year shows little signs of abatement. Concurrently, the emergency management community globally have responded to an unprecedented number of crisis events. From March 2020 to September 2021, there have been sizeable disasters such as wildfires, hurricanes and tropical storms, earthquakes, and flooding. In addition, cyberattacks and terrorist activity have required additional manpower, management resources, and both the talent and funding to adequately study and train differently than we have to date.

A mathematical programming approach to manage group decision making with incomplete hesitant fuzzy linguistic preference relations

Hesitant fuzzy linguistic information can be a useful decision-making tool in uncertain and complex environments. In this paper, we establish a new group decision making (GDM) model based on mathematical programming with incomplete hesitant fuzzy linguistic preference relations (HFLPRs). After developing a definition of incomplete HFLPR and its multiplicative consistency, we propose an equivalence theorem of multiplicative consistency between linguistic preference relation (LPR) and corresponding fuzzy preference relation (FPR). Based on this framework, a mathematical programming to address incomplete HFLPR is established. The proposed mathematical programming method has the dual functionality of finding the incomplete LPR with the highest consistency and increasing inconsistent LPR to complete consistent LPR using multiplicative consistency based on given incomplete HFLPR. In this manner, we construct a novel GDM model based on obtained multiplicative consistency LPRs in consideration of the group consensus reaching process. Finally, a real-world emergency management problem is solved to demonstrate the effectiveness of the proposed GDM model.

Priority-Oriented Route Network Planning for Evacuation in Constrained Space Scenarios

Evacuation planning in three-dimensional (3D) constrained space scenarios is an important kind of emergency management problems. In this paper, we investigate a path planning problem in constrained space evacuation for 3D scenarios, named the Priority-based Route Network Constructing Problem, which has two objectives of maximizing the evacuation exits’ utilization efficiency and minimizing the whole evacuation delay. We propose a 3-phase heuristic to construct a route network based on the Minimum Weighted Set Cover. In the experimental evaluation, we compare the proposed algorithm with the existing algorithms and implement our algorithm in underground mine evacuation, which is a typical kind of constrained space scenarios. Both types of results indicate our strategy can enhance the utilization efficiency of the escaping exits and guarantee a tolerable range of the global escaping time-consumption with a low running time.

Background to the four stages of emergency management: The role of enterprise GIS.

Few examples of enterprise geographic information systems (GISs) implementation are as important and illustrative as the use of GIS to support the four stages of emergency management (EM). The full range of data required to support the four stages of EM are much greater, then any one department can be responsible for by itself. Only with an enterprise-wide GIS perspective can the full range of required data elements be made available to the emergency manager. Most critically, to keep these data sets accurate and up to date, the emergency manager must rely on other agencies and functions to keep all the data current. Without other assistance, the data requirements for the EM team will be quickly overwhelming. Waugh and Hy describe emergency events as either intentional (terrorism) or unintentional (weather/earthquake). The focus of this analysis is primarily on unintentional events, yet examples show that the four stages of EM are applicable with either type of event. Enterprise GIS has not been discussed much lately, but it is absolutely critical to solving the information needs of the contemporary emergency manager. Enterprise GIS means that many of the key data sets needed to support the four stages of EM are readily available, in a consistent manner and are always up to date. An enterprise perspective also means that GIS data are compatible with surrounding areas and GIS products are consistent with local, state, and federal information needs/requirements. The "common operating picture" we hear so much about in today's EM world. Most importantly, an enterprise GIS perspective means that all data and systems work together or can "talk" to each other. Easily sharing data by address or by parcel means that the information/knowledge content can grow quickly and ad-hoc data requirements or events can be handled quickly and reliably. GIS is no longer a system or even just an architecture-it literally is a way of thinking. It is so exciting to implement GIS capabilities only to see that they can be used in ways not originally intended or described. This is analogous to the EM problem of having data/maps collected for the last emergency and not the current one! This means that the GIS staff get involved and more fully understand the in-depth system requirements of each application/data set. By putting these requirements together, in an enterprise-wide perspective, we can begin to see how a school inventory needed for drug free zones (for the district attorney's office) is also useful as a possible shelter/feeding/inoculation site inventory for EM. A cell tower inventory for address assignments (for E-911/CAD) may also prove useful to the assessment professionals who see income potentials in silos, flag poles and steeples, often on tax-exempt properties like churches or municipal water tanks. A gasoline station inventory from Health's Weights and Measures is immediately applicable to EM's requirements for a better understanding of possible gasoline rationing actions/scenarios. Another way of looking at enterprise GIS and its support of EM would be to always think about the other stages of EM as this particular data/map or application is being collected, designed, or implemented. Perhaps just including another data element or two could support other later (or earlier) stages of EM? The GIS data can provide the continuity that EM needs to handle an incident through the four stages.

Emergency decision-making combining cumulative prospect theory and group decision-making

With respect to the characteristic of risk and the potential evolvement of scenarios in emergency management analysis, this study proposes an emergency decision-making method with interval probability based on cumulative prospect theory and group decision-making. Under emergency risk environment, there is a tremendous need to consider decision-maker’s psychological behavior which affects the decision results. In addition, an emergency decision generally involves joint participation among departments, which inevitably brings about group decision-making. Therefore, aiming at decision problems in emergency management, this paper provides an algorithm of emergency group decision-making considering psychological behaviors. For illustration and verification, a numerical example and two comparisons are presented to demonstrate the effectiveness of proposed method. The contribution of this study is characterized by three aspects. First, cumulative prospect theory is introduced to quantify the impact of psychological behaviors. Second, group decision-making is considered as a think tank, which makes the decision more persuasive than single-person methods. Third, this study proposes a novel intelligent optimization algorithm, plant growth simulation algorithm, to integrate the different individual evaluations.

Research on Emergency Resource Scheduling Decision-Making Based on Dynamic Information

Emergency decision-making, especially emergency resource scheduling decision-making, is one of the key problems in emergency management. This article begins with the dynamism of emergency resources, provides a way of decision thinking about multi-stage scheduling of emergency resources based on the two-stage emergency rescue process and dynamic structure with continuous consumption, on the basis of the identification and integration of emergency resources.

Multiple emergency resource allocation for concurrent incidents in natural disasters

Emergency resource allocation, which mainly deals with how to efficiently allocate emergency resources of rescue agencies to process emerging incidents and reduce casualties and economic losses, has been one of the most fundamental and essential problems in emergency management for natural disasters. However, to our best knowledge, the existing deterministic methods concentrate on emergency resource allocation only for a single incident with constraints on response time or emergency resource cost separately, which is too simple to be applied in complex emergency scenarios. To this end, in this paper we commit ourselves to a challenging problem of allocating multiple emergency resources to multiple concurrent incidents in a parallel manner, taking response time and emergency resource cost altogether. For this purpose, we first define disaster response coalition as a form of team play. Besides, we propose a multiply constrained integer linear programming model and develop a differential evolution and heuristic based search algorithm to explore overlapping disaster response coalitions for concurrent incidents. Finally, the comparative experimental results show that technically, the parallel allocation of emergency resources for concurrent incidents is significantly more economical and efficient than the traditional serial allocation.

A REAL-TIME GIS PLATFORM FOR HIGH SOUR GAS LEAKAGE SIMULATION, EVALUATION AND VISUALIZATION

Abstract. The development of high-sulfur gas fields, also known as sour gas field, is faced with a series of safety control and emergency management problems. The GIS-based emergency response system is placed high expectations under the consideration of high pressure, high content, complex terrain and highly density population in Sichuan Basin, southwest China. The most researches on high hydrogen sulphide gas dispersion simulation and evaluation are used for environmental impact assessment (EIA) or emergency preparedness planning. This paper introduces a real-time GIS platform for high-sulfur gas emergency response. Combining with real-time data from the leak detection systems and the meteorological monitoring stations, GIS platform provides the functions of simulating, evaluating and displaying of the different spatial-temporal toxic gas distribution patterns and evaluation results. This paper firstly proposes the architecture of Emergency Response/Management System, secondly explains EPA’s Gaussian dispersion model CALPUFF simulation workflow under high complex terrain and real-time data, thirdly explains the emergency workflow and spatial analysis functions of computing the accident influencing areas, population and the optimal evacuation routes. Finally, a well blow scenarios is used for verify the system. The study shows that GIS platform which integrates the real-time data and CALPUFF models will be one of the essential operational platforms for high-sulfur gas fields emergency management.

KD-ACP: A Software Framework for Social Computing in Emergency Management

This paper addresses the application of a computational theory and related techniques for studying emergency management in social computing. We propose a novel software framework called KD-ACP. The framework provides a systematic and automatic platform for scientists to study the emergency management problems in three aspects: modelling the society in emergency scenario as the artificial society; investigating the emergency management problems by the repeat computational experiments; parallel execution between artificial society and the actual society managed by the decisions from computational experiments. The software framework is composed of a series of tools. These tools are categorized into three parts corresponding to “A,” “C,” and “P,” respectively. Using H1N1 epidemic in Beijing city as the case study, the modelling and data generating of Beijing city, experiments with settings of H1N1, and intervention measures and parallel execution by situation tool are implemented by KD-ACP. The results output by the software framework shows that the emergency response decisions can be tested to find a more optimal one through the computational experiments. In the end, the advantages of the KD-ACP and the future work are summarized in the conclusion.

Decision Making Support Model for the Incident Emergency Management of Migrant’s Group Based on CBR

This paper presents the findings of a study on decision making models for the migrant’s worker group incident emergency management based on Analytic Hierarchic Process (AHP). Analytic Hierarchic Process (AHP) helps to quantitate and layer the complex migrant’s worker incident emergency management problem, the aim of the work is to improve the support for analysis and decision through the importance comparing of various factors associated layer by layer.A case study conduct in Wukan village Shantou city of Guangdong province revealed that AHP model can do effective decision making

A Framework of Computational Experiment within Special Artificial Society Scene

Recently computational experiment based on special artificial society scene have played an important role to deal with various problems in emergency management. In this paper, firstly we summarize the basic theory of artificial society and emergency management. Second, we provide the method of constructing artificial society scene, including building basic models and generating population database. Then, we propose a large-scale individual-based framework of computational experiment within special artificial society scene, namely KD-ACP. Finally, we give a case of H1N1 influenza to introduce the platform workflow in the emergency management.

The Design and Implementation of Urban Emergency Counter-Plan and Management System (UECMS)

A series of large public event highlight the problems in emergency management in China. As a result, it is significant to build an emergency counter-plan and management system. This thesis proposes overall architecture for the system and introduces the implementation of its main modules.

Visualizing Diurnal Population Change in Urban Areas for Emergency Management*

There is an increasing need for a quick, simple method to represent diurnal population change in metropolitan areas for effective emergency management and risk analysis. Many geographic studies rely on decennial U.S. Census data that assume that urban populations are static in space and time. This has obvious limitations in the context of dynamic geographic problems. The U.S. Department of Transportation publishes population data at the transportation analysis zone level in fifteen-minute increments. This level of spatial and temporal detail allows for improved dynamic population modeling. This article presents a methodology for visualizing and analyzing diurnal population change for metropolitan areas based on this readily available data. Areal interpolation within a geographic information system is used to create twenty-four (one per hour) population surfaces for the larger metropolitan area of Salt Lake County, Utah. The resulting surfaces represent diurnal population change for an average workday and are easily combined to produce an animation that illustrates population dynamics throughout the day. A case study of using the method to visualize population distributions in an emergency management context is provided using two scenarios: a chemical release and a dirty bomb in Salt Lake County. This methodology can be used to address a wide variety of problems in emergency management.

Preparing for and Responding to Public Health Emergencies in China: A Focus Group Study

To gather information that would assist China's central government and local governments in public health emergency management, we conducted focus groups to identify current problems. In three provinces, selected to reflect differing economic and social status, we met with two groups each, composed of public health officials and practitioners. Sampling to achieve a mix and for convenience, we followed a guide to cover five topics. Eleven common problems emerged. China's central government and local governments should take immediate action to solve these remaining problems in public health emergency management.

AIDS-associated Cryptococcus infection before and after the highly active antiretroviral therapy era: emerging management problems

The frequency, the microbiology and clinical features of AIDS-related primary episodes and relapses of cryptococcosis, before and after the introduction of highly active antiretroviral therapy (HAART), were compared. The study covered 58 cases diagnosed before the introduction of HAART, and eight episodes since 1997. Because of negative cultures, we sought a sensitive laboratory assay such as detection of polysaccharide antigen. Despite later diagnosis, there was reduced disease mortality. Clinical suspicion for HIV-associated cryptococcosis should be maintained in immunocompromised subjects. The introduction of HAART has led to significant clinical and laboratory changes of HIV-related cryptococcosis.

A pilot decision support system for nuclear power emergency management

ETH-NUKERISK model and associated computer software is designed as modular, GIS-based platform, capable to accommodate and test a variety of models — mathematical and logical — normally concurring in the risk and accident consequence assessment as applicable to nuclear power plants. The current version of the software combines expert system and GIS features into an early-response-oriented knowledge based and decision support system. It combines pre-digested knowledge and casuistry with ad-hoc analysis to diagnose abnormal events and predict/evaluate the amplitude of the entailed environmental contamination and potential health effects. The results can be mapped together with the zones of recommended intervention, including the points of minimum risk. ETH-NUKERISK is believed to hold good potential for steering a many-folded development: towards a DSS, computer assisted learning and expertise instrument, transparent to mitigate several expert-to-decedent communication problems in emergency preparedness and management.