An accurate assessment of the evacuation efficiency in case of disasters is of vital importance to the safety design of buildings and street blocks.Hazard sources not only physically but psychologically affect the ped...An accurate assessment of the evacuation efficiency in case of disasters is of vital importance to the safety design of buildings and street blocks.Hazard sources not only physically but psychologically affect the pedestrians,which may further alter their behavioral patterns.This effect is especially significant in narrow spaces,such as corridors and alleys.This study aims to integrate a non-spreading hazard source into the social force model following the results from a previous experiment and simulation,and to simulate unidirectional pedestrian flows over various crowd densities and clarity–intensity properties of the hazard source.The integration include a virtual repulsion force from the hazard source and a decay on the social force term.The simulations reveal(i)that the hazard source creates virtual bottlenecks that suppress the flow,(ii)that the inter-pedestrian push forms a stabilisation phase on the flow-density curve within medium-to-high densities,and(iii)that the pedestrians are prone to a less orderly and stable pattern of movement in low clarity–intensity scenarios,possibly with lateral collisions passing the hazard source.展开更多
As an emerging technology,blockchain provides a range of advantages,such as decentralized and transparent data storage,secure access control,and enhanced data traceability.However,it is rarely applied in the field of ...As an emerging technology,blockchain provides a range of advantages,such as decentralized and transparent data storage,secure access control,and enhanced data traceability.However,it is rarely applied in the field of public safety.This paper presents an in-depth survey of blockchain technology,focusing on its potential applications and implications within the field of public safety research.We explore the practical needs of multi-party data collaboration in emergency management and discusses the applicability and value of blockchain technology in this context.Additionally,this paper introduces and compares several popular blockchain platforms.By providing a comprehensive examination of blockchain technology and its potential benefits for public safety,this paper seeks to enhance understanding of the technology’s capabilities,encourage further research,and inspire innovation in this domain.展开更多
Gas drainage at low gas permeability coal seam is a main barrier affecting safety and efficient production in coal mines. Therefore, the research and application of drainage technology at low permeability coal seam is...Gas drainage at low gas permeability coal seam is a main barrier affecting safety and efficient production in coal mines. Therefore, the research and application of drainage technology at low permeability coal seam is a key factor for gas control of coal mine. In order to improve the drainage effect, this paper establishes a three-dimensional solid-gas-liquid coupling numerical model, and the gas drainage amounts of different schemes are examined inside the overburden material around the goaf. The Yangquan mine area is selected for the case study, and the gas movement regularity and emission characteristics are analyzed in detail, as well as the stress and fissure variation regularity. Also examinations are the released gas movement, enrichment range and movement regularity during coal extraction. Moreover, the gas drainage technology and drainage parameters for the current coal seam are studied. After measuring the gas drainage flow in-situ, it is concluded that the technology can achieve notable drainage results, with gas drainage rate increase by 30%–40% in a low permeability coal seam.展开更多
The study of the panic evacuation process is of great significance to emergency management.Panic not only causes negative emotions such as irritability and anxiety,but also affects the pedestrians decision-making proc...The study of the panic evacuation process is of great significance to emergency management.Panic not only causes negative emotions such as irritability and anxiety,but also affects the pedestrians decision-making process,thereby inducing the abnormal crowd behavior.Prompted by the epidemiological SIR model,an extended floor field cellular automaton model was proposed to investigate the pedestrian dynamics under the threat of hazard resulting from the panic contagion.In the model,the conception of panic transmission status(PTS)was put forward to describe pedestrians’behavior who could transmit panic emotions to others.The model also indicated the pedestrian movement was governed by the static and hazard threat floor field.Then rules that panic could influence decision-making process were set up based on the floor field theory.The simulation results show that the stronger the pedestrian panic,the more sensitive pedestrians are to hazards,and the less able to rationally find safe exits.However,when the crowd density is high,the panic contagion has a less impact on the evacuation process of pedestrians.It is also found that when the hazard position is closer to the exit,the panic will propagate for a longer time and have a greater impact on the evacuation.The results also suggest that as the extent of pedestrian’s familiarity with the environment increases,pedestrians spend less time to escape from the room and are less sensitive to the hazard.In addition,it is essential to point out that,compared with the impact of panic contagion,the pedestrian’s familiarity with environment has a more significant influence on the evacuation.展开更多
Campus security has aroused many concerns from the whole society.Stampede is one of the most frequent and influential accidents in campus.Studies on pedestrian dynamics especially focusing on students are essential fo...Campus security has aroused many concerns from the whole society.Stampede is one of the most frequent and influential accidents in campus.Studies on pedestrian dynamics especially focusing on students are essential for campus security,which are helpful to improve facility design and emergency evacuation strategy.In this paper,primary and middle school students were recruited to participate in the single-file experiments.The microscopic movement characteristics,including walking speed,headway,gait characteristics(step length,step frequency and swaying amplitude)and their relations were investigated.Age and gender differences in the headway-speed diagram and space requirements were analyzed by statistical tests.The results indicated that the impacts of age and gender were significant.There were three stages for the influence of gender on the headway-speed diagram for both age groups.The impacts on students'space requirements were consistent for different age and gender groups.But the impacts of age and gender on free-flow speed were affected by each other.Due to the connection of walking speed and gait characteristics,the comparisons of gait characteristics between different ages and genders were performed to understand the corresponding differences in speed more deeply.The results showed that differences in step length and swaying amplitude between males and females were significant for both age groups.The effect of gender on step frequency was significant for primary students.But for middle school students,whether gender had significant impact on step frequency was not clear here because of the large P-value.Besides,the influence of age on gait characteristics changed with gender.展开更多
Pre-warning plays an important role in emergency handling, especially in urban areas with high population density like Beijing. Knowing the information dissemination mechanisms clearly could help us reduce losses and ...Pre-warning plays an important role in emergency handling, especially in urban areas with high population density like Beijing. Knowing the information dissemination mechanisms clearly could help us reduce losses and ensure the safety of human beings during emergencies. In this paper, we propose the models of pre-warning information dissemination via five classical media based on actual pre-warning issue processes, including television, radio, short message service (SMS), electronic screens, and online social networks. The population coverage ability and dissemination efficiency at different issue time of these five issue channels are analyzed by simulation methods, and their advantages and disadvantages are compared by radar graphs. Results show that SMS is the most appropriate way to issue long-term pre-warning for its large population coverage, but it is not suitable for issuing urgent warnings to large population because of the limitation of telecom company's issue ability. TV shows the best performance to combine the dissemination speed and range, and the performance of radio and electronic screens are not as satisfactory as the others. In addition, online social networks might become one of the most promising communication method for its potential in further diffusion. These models and results could help us make pre-warning issue plans and provide guidance for future construction of information diffusion systems, thus reducing injuries, deaths, and other losses under different emergencies.展开更多
Human settlements are embedded in traffic networks with hierarchical structures. In order to understand the spreading mechanism of infectious diseases and deploy control measures, the susceptible-infected-removed spre...Human settlements are embedded in traffic networks with hierarchical structures. In order to understand the spreading mechanism of infectious diseases and deploy control measures, the susceptible-infected-removed spreading process is studied with agents moving globally on the hierarchical geographic network, taking into account agents’ preference for node layers and memory of initial nodes. We investigate the spreading behavior in the case of global infection under different scenarios, including different directions of human flow, different locations of infection source, and different moving behaviors of agents between layers. Based on the above-mentioned analysis, we propose screening strategies based on layer rank and moving distance, and compare their effects on delaying epidemic spreading. We find that in the case of global infection,infection spreads faster in high layers than in low layers, and early infection in high layers and moving to high layers both accelerate epidemic spreading. Travels of high-layer and low-layer residents have different effects on accelerating epidemic spreading, and moving between high and low layers increases the peak value of new infected cases more than moving in the same layer or between adjacent layers. Infection in intermediate nodes enhances the effects of moving of low-layer residents more than the moving of high-layer residents on accelerating epidemic spreading. For screening measures, improving the success rate is more effective on delaying epidemic spreading than expanding the screening range. With the same number of moves screened, screening moves into or out of high-layer nodes combined with screening moves between subnetworks has better results than only screening moves into or out of high-layer nodes, and screening long-distance moves has the worst results when the screening range is small, but it achieves the best results in reducing the peak value of new infected cases when the screening range is large enough. This study probes into the spreading process and control measures under different scenarios on the hierarchical geographical network, and is of great significance for epidemic control in the real world.展开更多
The prevention and treatment of epidemic is always an urgent problem faced by the human being. Due to the special space structure, huge passenger flow and great people mobility, the subway lines have become the areas ...The prevention and treatment of epidemic is always an urgent problem faced by the human being. Due to the special space structure, huge passenger flow and great people mobility, the subway lines have become the areas with high epidemic transmission risks. However, there is no recent study related to epidemic transmission in the subway network on urban-scale. In this article, from the perspective of big data, we study the transmission risk of epidemic in Beijing subway network by using urban subway mobility data. By reintegrating and mining the urban subway mobility data, we preliminary assess the transmission risk in the subway lines from the passenger behaviors, station features, route features and individual case on the basis of subway network structure. This study has certain practical significance for the early stage of epidemic tracking and prevention.展开更多
In order to improve the accuracy and efficiency of early warning system, the incident chain model and the targeted dissemination technology are proposed in this paper. Firstly, the occurrence probability, affected are...In order to improve the accuracy and efficiency of early warning system, the incident chain model and the targeted dissemination technology are proposed in this paper. Firstly, the occurrence probability, affected area and duration of disaster are predicted with the incident chain model and GIS. According to prediction results, the early warning system can accurately deliver early warning information specifically to the affected areas through targeted dissemination. Moreover, dissemination performance can also be evaluated in real time after early warning information dissemination, so that everyone in the affected area can receive early warning information successfully. The incident chain model and the targeted dissemination technology presented in this study are of great significance for improving the information dissemination ability of early warning system.展开更多
Vulnerability to hazards includes not only components of a physical nature, but also those arising from social factors. In developing measures for disaster prevention or emergency response for disaster relief of big c...Vulnerability to hazards includes not only components of a physical nature, but also those arising from social factors. In developing measures for disaster prevention or emergency response for disaster relief of big cities, an analysis of social vulnerability is very necessary but quite difficult. In order to address the problem, using Beijing as an example, we established a social vulnerability index system including 26 factors and developed an improved analytic hierarchy process (AHP) method. The weight of each factor was evaluated using the improved AHP process that obviously increased the passing rate of consistency of the experts' questionnaire. The population, career, economy, infrastructure and social vulnerability distribution maps of Beijing were obtained. From them, it's easy to see the characteristics of various vulnerability distributions. Through sensitivity analysis, the influencing factors of each area were listed in order of importance. The approach are useful for assessing, reducing the social vulnerability of big cities in China.展开更多
With the rapid development of China's economy,external dependence on petroleum resources continues to increase,and their security has become an important part of national security.To evaluate the security of China...With the rapid development of China's economy,external dependence on petroleum resources continues to increase,and their security has become an important part of national security.To evaluate the security of China's petroleum resource supply in a scientific and objective manner,this study establishes a corresponding petroleum life-cycle evaluation index system,based on the theory and method of the whole life-cycle security evaluation of mineral resources,and conducts further independence and grey correlation analysis on the indexes for the purpose of evaluating the petroleum risk situation in China,based on relevant public data from the past 10 years.The results show that the overall trend of China's oil risk has a“U”-shaped characteristic of first decreasing and then increasing.Furthermore,the analysis finds that China's mineral resources have been greatly influenced by the domestic production situation and international trade.These results suggest that the security of petroleum supply can be improved by safeguarding international trade in petroleum resources,strengthening the strategic reserves of domestic petroleum resources,and developing new alternative clean energy sources to improve the resilience of petroleum supply security.This study's research methodology is more logical and systematic than traditional methods,and the analysis of the factors is comprehensive and of high application value,providing implications for the establishment of a big data analysis and evaluation index system for oil resource security.展开更多
Virtual reality(VR) training technology in the mining industry is a new field of research and utilization.The successful application of VR training system is critical to mine safety and production. Through the statist...Virtual reality(VR) training technology in the mining industry is a new field of research and utilization.The successful application of VR training system is critical to mine safety and production. Through the statistics of the current research and applications of VR training systems in mining industry, all the input/output devices are classified. Based on the classifications of the input/output devices that are used in the VR system, the current VR training systems for the mining industry could be divided into three types: screen-based general type, projector-based customized type, and head-mounted display(HMD)-based intuitive type. By employing a VR headset, a smartphone and a leap motion device, an HMDbased intuitive type VR training system prototype for drilling in underground mines has been developed.Ten trainees tried both the HMD-based intuitive system and the screen-based general control system to compare the experiences and training effects. The results show that the HMD-based system can give a much better user experience and is easy to use. Three of the five components of a VR training system,namely, the user, the tasks, and software and database should be given more attention in future research.With more available technologies of input and output devices, VR engines, and system software, the VR training system will eventually yield much better training results, and will play a more important role in as a training tool for mine safety.展开更多
In complex networks,identifying influential spreader is of great significance for improving the reliability of networks and ensuring the safe and effective operation of networks.Nowadays,it is widely used in power net...In complex networks,identifying influential spreader is of great significance for improving the reliability of networks and ensuring the safe and effective operation of networks.Nowadays,it is widely used in power networks,aviation networks,computer networks,and social networks,and so on.Traditional centrality methods mainly include degree centrality,closeness centrality,betweenness centrality,eigenvector centrality,k-shell,etc.However,single centrality method is onesided and inaccurate,and sometimes many nodes have the same centrality value,namely the same ranking result,which makes it difficult to distinguish between nodes.According to several classical methods of identifying influential nodes,in this paper we propose a novel method that is more full-scaled and universally applicable.Taken into account in this method are several aspects of node’s properties,including local topological characteristics,central location of nodes,propagation characteristics,and properties of neighbor nodes.In view of the idea of the multi-attribute decision-making,we regard the basic centrality method as node’s attribute and use the entropy weight method to weigh different attributes,and obtain node’s combined centrality.Then,the combined centrality is applied to the gravity law to comprehensively identify influential nodes in networks.Finally,the classical susceptible-infected-recovered(SIR)model is used to simulate the epidemic spreading in six real-society networks.Our proposed method not only considers the four topological properties of nodes,but also emphasizes the influence of neighbor nodes from the aspect of gravity.It is proved that the new method can effectively overcome the disadvantages of single centrality method and increase the accuracy of identifying influential nodes,which is of great significance for monitoring and controlling the complex networks.展开更多
As a physical model,the cellular automata(CA) model is widely used in many areas,such as stair evacuation.However,existing CA models do not consider evacuees' walk preferences nor psychological status,and the stru...As a physical model,the cellular automata(CA) model is widely used in many areas,such as stair evacuation.However,existing CA models do not consider evacuees' walk preferences nor psychological status,and the structure of the basic model is unapplicable for the stair structure.This paper is to improve the stair evacuation simulation by addressing these issues,and a new cellular automata model is established.Several evacuees' walk preference and how evacuee's psychology influences their behaviors are introduced into this model.Evacuees' speeds will be influenced by these features.To validate this simulation,two fire drills held in two high-rise buildings are video-recorded.It is found that the simulation results are similar to the fire drill results.The structure of this model is simple,and it is easy to further develop and utilize in different buildings with various kinds of occupants.展开更多
A new reliable cellular automaon(CA) model designed to account for stochasticity in traffic flow induced by heterogeneity in driving behavior is presented.The proposed model differs from most existing CA models in tha...A new reliable cellular automaon(CA) model designed to account for stochasticity in traffic flow induced by heterogeneity in driving behavior is presented.The proposed model differs from most existing CA models in that this new model focuses on describing traffic phenomena by coding into its rules the key idea that a vehicle's moving state is directly determined by a driver stepping on the accelerator or on the brake(the vehicle's acceleration).Acceleration obeys a deformed continuous distribution function when considering the heterogeneity in driving behavior and the safe distance, rather than equaling a fixed acceleration value with a probability, as is the rule in many existing CA models.Simulation results show that the new proposed model is capable of reproducing empirical findings in real traffic system.Moreover, this new model makes it possible to implement in-depth analysis of correlations between a vehicle's state parameters.展开更多
Pedestrian evacuation is actually a process of behavioral evolution. Interaction behaviors between pedestrians affect not only the evolution of their cooperation strategy, but also their evacuation paths-scheduling an...Pedestrian evacuation is actually a process of behavioral evolution. Interaction behaviors between pedestrians affect not only the evolution of their cooperation strategy, but also their evacuation paths-scheduling and dynamics features. The existence of interaction behaviors and cooperation evolution is therefore critical for pedestrian evacuation. To address this issue, an extended cellular automaton(CA) evacuation model considering the effects of interaction behaviors and cooperation evolution is proposed here. The influence mechanism of the environment factor and interaction behaviors between neighbors on the decision-making of one pedestrian to path scheduling is focused. Average payoffs interacting with neighbors are used to represent the competitive ability of one pedestrian, aiming to solve the conflicts when more than one pedestrian competes for the same position based on a new method. Influences of interaction behaviors, the panic degree and the conflict cost on the evacuation dynamics and cooperation evolution of pedestrians are discussed. Simulation results of the room evacuation show that the interaction behaviors between pedestrians to a certain extent are beneficial to the evacuation efficiency and the formation of cooperation behaviors as well. The increase of conflict cost prolongs the evacuation time. Panic emotions of pedestrians are bad for cooperation behaviors of the crowd and have complex effects on evacuation time. A new self-organization effect is also presented.展开更多
In most situations,staircase is the only egress to evacuate from high-rise buildings.The merging flow on the stair landing has a great influence on the evacuation efficiency.In this paper,we develop an improved cellul...In most situations,staircase is the only egress to evacuate from high-rise buildings.The merging flow on the stair landing has a great influence on the evacuation efficiency.In this paper,we develop an improved cellular automaton model to describe the merging behavior,and the model is validated by a series of real experiments.It is found that the flow rate of simulation results is similar to the drills,which means that the improved model is reasonable and can be used to describe the merging behavior on stairs.Furthermore,some scenarios with different door locations and building floor numbers are simulated by the model.The results show that(i)the best door location is next to the upward staircase;(ii)the total evacuation time and the building floor number are linearly related to each other;(iii)the pedestrians on upper floors have a negative influence on the evacuation flow rate.展开更多
To track human across non-overlapping cameras in depression angles for applications such as multi-airplane visual human tracking and urban multi-camera surveillance,an adaptive human tracking method is proposed,focusi...To track human across non-overlapping cameras in depression angles for applications such as multi-airplane visual human tracking and urban multi-camera surveillance,an adaptive human tracking method is proposed,focusing on both feature representation and human tracking mechanism.Feature representation describes individual by using both improved local appearance descriptors and statistical geometric parameters.The improved feature descriptors can be extracted quickly and make the human feature more discriminative.Adaptive human tracking mechanism is based on feature representation and it arranges the human image blobs in field of view into matrix.Primary appearance models are created to include the maximum inter-camera appearance information captured from different visual angles.The persons appeared in camera are first filtered by statistical geometric parameters.Then the one among the filtered persons who has the maximum matching scale with the primary models is determined to be the target person.Subsequently,the image blobs of the target person are used to update and generate new primary appearance models for the next camera,thus being robust to visual angle changes.Experimental results prove the excellence of the feature representation and show the good generalization capability of tracking mechanism as well as its robustness to condition variables.展开更多
Individuals’ preventive measures,as an effective way to suppress epidemic transmission and to protect themselves from infection,have attracted much academic concern,especially during the COVID-19 pandemic.In this pap...Individuals’ preventive measures,as an effective way to suppress epidemic transmission and to protect themselves from infection,have attracted much academic concern,especially during the COVID-19 pandemic.In this paper,a reinforcement learning-based model is proposed to explore individuals’ effective preventive measures against epidemics.Through extensive simulations,we find that the cost of preventive measures influences the epidemic transmission process significantly.The infection scale increases as the cost of preventive measures grows,which means that the government needs to provide preventive measures with low cost to suppress the epidemic transmission.In addition,the effective preventive measures vary from individual to individual according to the social contacts.Individuals who contact with others frequently in daily life are highly recommended to take strict preventive measures to protect themselves from infection,while those who have little social contacts do not need to take any measures considering the inevitable cost.Our research contributes to exploring the effective measures for individuals,which can provide the government and individuals useful suggestions in response to epidemics.展开更多
Grain security guarantees national security.China has many widely distributed grain depots to supervise grain storage security.However,this has led to a lack of regulatory capacity and manpower.Amid the development of...Grain security guarantees national security.China has many widely distributed grain depots to supervise grain storage security.However,this has led to a lack of regulatory capacity and manpower.Amid the development of reserve-level information technology,big data supervision of grain storage security should be improved.This study proposes big data research architecture and an analysis model for grain storage security;as an example,it illustrates the supervision of the grain loss problem in storage security.The statistical analysis model and the prediction and clustering-based model for grain loss supervision were used to mine abnormal data.A combination of feature extraction and feature selection reduction methods were chosen for dimensionality.A comparative analysis showed that the nonlinear prediction model performed better on the grain loss data set,with R2 of 87.21%,87.83%,91.97%,and 89.40%for Gradient Boosting Regressor(GBR),Random Forest,Decision Tree,XGBoost regression on test sets,respectively.Nineteen abnormal data were filtered out by GBR combined with residuals as an example.The deep learning model had the best performance on the mean absolute error,with an R2 of 85.14%on the test set and only one abnormal data identified.This is contrary to the original intention of finding as many anomalies as possible for supervisory purposes.Five classes were generated using principal component analysis dimensionality reduction combined with Density-Based Spatial Clustering of Applications with Noise(DBSCAN)clustering,with 11 anomalous data points screened by adding the amount of normalized grain loss.Based on the existing grain information system,this paper provides a supervision model for grain storage that can help mine abnormal data.Unlike the current post-event supervision model,this study proposes a pre-event supervision model.This study provides a framework of ideas for subsequent scholarly research;the addition of big data technology will help improve efficient supervisory capacity in the field of grain supervision.展开更多
基金Project supported by National Key Research and Development Program of China(Grant Nos.2022YFC3320800 and 2021YFC1523500)the National Natural Science Foundation of China(Grant Nos.71971126,71673163,72304165,72204136,and 72104123).
文摘An accurate assessment of the evacuation efficiency in case of disasters is of vital importance to the safety design of buildings and street blocks.Hazard sources not only physically but psychologically affect the pedestrians,which may further alter their behavioral patterns.This effect is especially significant in narrow spaces,such as corridors and alleys.This study aims to integrate a non-spreading hazard source into the social force model following the results from a previous experiment and simulation,and to simulate unidirectional pedestrian flows over various crowd densities and clarity–intensity properties of the hazard source.The integration include a virtual repulsion force from the hazard source and a decay on the social force term.The simulations reveal(i)that the hazard source creates virtual bottlenecks that suppress the flow,(ii)that the inter-pedestrian push forms a stabilisation phase on the flow-density curve within medium-to-high densities,and(iii)that the pedestrians are prone to a less orderly and stable pattern of movement in low clarity–intensity scenarios,possibly with lateral collisions passing the hazard source.
基金Funded by National Key R&D Program of China(No.2022YFC2602400)National Natural Science Foundation of China(No.72174102,No.72334003)High-tech Discipline Construction Fundings for Universities in Beijing(Safety Science and Engineering).
文摘As an emerging technology,blockchain provides a range of advantages,such as decentralized and transparent data storage,secure access control,and enhanced data traceability.However,it is rarely applied in the field of public safety.This paper presents an in-depth survey of blockchain technology,focusing on its potential applications and implications within the field of public safety research.We explore the practical needs of multi-party data collaboration in emergency management and discusses the applicability and value of blockchain technology in this context.Additionally,this paper introduces and compares several popular blockchain platforms.By providing a comprehensive examination of blockchain technology and its potential benefits for public safety,this paper seeks to enhance understanding of the technology’s capabilities,encourage further research,and inspire innovation in this domain.
基金supported by the Ministry of Science and Technology of P.R.C, which is the International Cooperation Program in Science and Technology (No. 2008DFB70100)
文摘Gas drainage at low gas permeability coal seam is a main barrier affecting safety and efficient production in coal mines. Therefore, the research and application of drainage technology at low permeability coal seam is a key factor for gas control of coal mine. In order to improve the drainage effect, this paper establishes a three-dimensional solid-gas-liquid coupling numerical model, and the gas drainage amounts of different schemes are examined inside the overburden material around the goaf. The Yangquan mine area is selected for the case study, and the gas movement regularity and emission characteristics are analyzed in detail, as well as the stress and fissure variation regularity. Also examinations are the released gas movement, enrichment range and movement regularity during coal extraction. Moreover, the gas drainage technology and drainage parameters for the current coal seam are studied. After measuring the gas drainage flow in-situ, it is concluded that the technology can achieve notable drainage results, with gas drainage rate increase by 30%–40% in a low permeability coal seam.
基金supported by the National Key Technology Research and Development Program of China(Grant No.2019YFC0810804)the National Natural Science Foundation of China(Grant No.7197010332)。
文摘The study of the panic evacuation process is of great significance to emergency management.Panic not only causes negative emotions such as irritability and anxiety,but also affects the pedestrians decision-making process,thereby inducing the abnormal crowd behavior.Prompted by the epidemiological SIR model,an extended floor field cellular automaton model was proposed to investigate the pedestrian dynamics under the threat of hazard resulting from the panic contagion.In the model,the conception of panic transmission status(PTS)was put forward to describe pedestrians’behavior who could transmit panic emotions to others.The model also indicated the pedestrian movement was governed by the static and hazard threat floor field.Then rules that panic could influence decision-making process were set up based on the floor field theory.The simulation results show that the stronger the pedestrian panic,the more sensitive pedestrians are to hazards,and the less able to rationally find safe exits.However,when the crowd density is high,the panic contagion has a less impact on the evacuation process of pedestrians.It is also found that when the hazard position is closer to the exit,the panic will propagate for a longer time and have a greater impact on the evacuation.The results also suggest that as the extent of pedestrian’s familiarity with the environment increases,pedestrians spend less time to escape from the room and are less sensitive to the hazard.In addition,it is essential to point out that,compared with the impact of panic contagion,the pedestrian’s familiarity with environment has a more significant influence on the evacuation.
基金Project supported by the Social Science Foundation of Beijing(Grant No.19GLC078)the Fundamental Research Funds for the Central Universities,China(Grant No.2019JKF429).
文摘Campus security has aroused many concerns from the whole society.Stampede is one of the most frequent and influential accidents in campus.Studies on pedestrian dynamics especially focusing on students are essential for campus security,which are helpful to improve facility design and emergency evacuation strategy.In this paper,primary and middle school students were recruited to participate in the single-file experiments.The microscopic movement characteristics,including walking speed,headway,gait characteristics(step length,step frequency and swaying amplitude)and their relations were investigated.Age and gender differences in the headway-speed diagram and space requirements were analyzed by statistical tests.The results indicated that the impacts of age and gender were significant.There were three stages for the influence of gender on the headway-speed diagram for both age groups.The impacts on students'space requirements were consistent for different age and gender groups.But the impacts of age and gender on free-flow speed were affected by each other.Due to the connection of walking speed and gait characteristics,the comparisons of gait characteristics between different ages and genders were performed to understand the corresponding differences in speed more deeply.The results showed that differences in step length and swaying amplitude between males and females were significant for both age groups.The effect of gender on step frequency was significant for primary students.But for middle school students,whether gender had significant impact on step frequency was not clear here because of the large P-value.Besides,the influence of age on gait characteristics changed with gender.
基金Project supported by the Science Fund from the Ministry of Science and Technology of China(Grant No.2018YFC0807000).
文摘Pre-warning plays an important role in emergency handling, especially in urban areas with high population density like Beijing. Knowing the information dissemination mechanisms clearly could help us reduce losses and ensure the safety of human beings during emergencies. In this paper, we propose the models of pre-warning information dissemination via five classical media based on actual pre-warning issue processes, including television, radio, short message service (SMS), electronic screens, and online social networks. The population coverage ability and dissemination efficiency at different issue time of these five issue channels are analyzed by simulation methods, and their advantages and disadvantages are compared by radar graphs. Results show that SMS is the most appropriate way to issue long-term pre-warning for its large population coverage, but it is not suitable for issuing urgent warnings to large population because of the limitation of telecom company's issue ability. TV shows the best performance to combine the dissemination speed and range, and the performance of radio and electronic screens are not as satisfactory as the others. In addition, online social networks might become one of the most promising communication method for its potential in further diffusion. These models and results could help us make pre-warning issue plans and provide guidance for future construction of information diffusion systems, thus reducing injuries, deaths, and other losses under different emergencies.
基金Project supported by the National Key R&D Program of China(Grant No.2018YFF0301005)the National Natural Science Foundation of China(Grant Nos.71673161 and 71790613)the Collaborative Innovation Center of Public Safety,China
文摘Human settlements are embedded in traffic networks with hierarchical structures. In order to understand the spreading mechanism of infectious diseases and deploy control measures, the susceptible-infected-removed spreading process is studied with agents moving globally on the hierarchical geographic network, taking into account agents’ preference for node layers and memory of initial nodes. We investigate the spreading behavior in the case of global infection under different scenarios, including different directions of human flow, different locations of infection source, and different moving behaviors of agents between layers. Based on the above-mentioned analysis, we propose screening strategies based on layer rank and moving distance, and compare their effects on delaying epidemic spreading. We find that in the case of global infection,infection spreads faster in high layers than in low layers, and early infection in high layers and moving to high layers both accelerate epidemic spreading. Travels of high-layer and low-layer residents have different effects on accelerating epidemic spreading, and moving between high and low layers increases the peak value of new infected cases more than moving in the same layer or between adjacent layers. Infection in intermediate nodes enhances the effects of moving of low-layer residents more than the moving of high-layer residents on accelerating epidemic spreading. For screening measures, improving the success rate is more effective on delaying epidemic spreading than expanding the screening range. With the same number of moves screened, screening moves into or out of high-layer nodes combined with screening moves between subnetworks has better results than only screening moves into or out of high-layer nodes, and screening long-distance moves has the worst results when the screening range is small, but it achieves the best results in reducing the peak value of new infected cases when the screening range is large enough. This study probes into the spreading process and control measures under different scenarios on the hierarchical geographical network, and is of great significance for epidemic control in the real world.
文摘The prevention and treatment of epidemic is always an urgent problem faced by the human being. Due to the special space structure, huge passenger flow and great people mobility, the subway lines have become the areas with high epidemic transmission risks. However, there is no recent study related to epidemic transmission in the subway network on urban-scale. In this article, from the perspective of big data, we study the transmission risk of epidemic in Beijing subway network by using urban subway mobility data. By reintegrating and mining the urban subway mobility data, we preliminary assess the transmission risk in the subway lines from the passenger behaviors, station features, route features and individual case on the basis of subway network structure. This study has certain practical significance for the early stage of epidemic tracking and prevention.
文摘In order to improve the accuracy and efficiency of early warning system, the incident chain model and the targeted dissemination technology are proposed in this paper. Firstly, the occurrence probability, affected area and duration of disaster are predicted with the incident chain model and GIS. According to prediction results, the early warning system can accurately deliver early warning information specifically to the affected areas through targeted dissemination. Moreover, dissemination performance can also be evaluated in real time after early warning information dissemination, so that everyone in the affected area can receive early warning information successfully. The incident chain model and the targeted dissemination technology presented in this study are of great significance for improving the information dissemination ability of early warning system.
基金supported by the National Natural Science Foundation of China (71173128)Ministry of Science and Technology of China(2011BAK07B02)
文摘Vulnerability to hazards includes not only components of a physical nature, but also those arising from social factors. In developing measures for disaster prevention or emergency response for disaster relief of big cities, an analysis of social vulnerability is very necessary but quite difficult. In order to address the problem, using Beijing as an example, we established a social vulnerability index system including 26 factors and developed an improved analytic hierarchy process (AHP) method. The weight of each factor was evaluated using the improved AHP process that obviously increased the passing rate of consistency of the experts' questionnaire. The population, career, economy, infrastructure and social vulnerability distribution maps of Beijing were obtained. From them, it's easy to see the characteristics of various vulnerability distributions. Through sensitivity analysis, the influencing factors of each area were listed in order of importance. The approach are useful for assessing, reducing the social vulnerability of big cities in China.
基金This work was financially supported by the Fundamental Research Funds for Central Universities(Grant No.2021NTSS10)the National Natural Science Foundation of China(Grant No.72004141).
文摘With the rapid development of China's economy,external dependence on petroleum resources continues to increase,and their security has become an important part of national security.To evaluate the security of China's petroleum resource supply in a scientific and objective manner,this study establishes a corresponding petroleum life-cycle evaluation index system,based on the theory and method of the whole life-cycle security evaluation of mineral resources,and conducts further independence and grey correlation analysis on the indexes for the purpose of evaluating the petroleum risk situation in China,based on relevant public data from the past 10 years.The results show that the overall trend of China's oil risk has a“U”-shaped characteristic of first decreasing and then increasing.Furthermore,the analysis finds that China's mineral resources have been greatly influenced by the domestic production situation and international trade.These results suggest that the security of petroleum supply can be improved by safeguarding international trade in petroleum resources,strengthening the strategic reserves of domestic petroleum resources,and developing new alternative clean energy sources to improve the resilience of petroleum supply security.This study's research methodology is more logical and systematic than traditional methods,and the analysis of the factors is comprehensive and of high application value,providing implications for the establishment of a big data analysis and evaluation index system for oil resource security.
基金funded by the ‘‘twelfth five” National Key Technology Research and Development Program of the Ministry of Science and Technology of China (Grant No. 2015BAK10B00)
文摘Virtual reality(VR) training technology in the mining industry is a new field of research and utilization.The successful application of VR training system is critical to mine safety and production. Through the statistics of the current research and applications of VR training systems in mining industry, all the input/output devices are classified. Based on the classifications of the input/output devices that are used in the VR system, the current VR training systems for the mining industry could be divided into three types: screen-based general type, projector-based customized type, and head-mounted display(HMD)-based intuitive type. By employing a VR headset, a smartphone and a leap motion device, an HMDbased intuitive type VR training system prototype for drilling in underground mines has been developed.Ten trainees tried both the HMD-based intuitive system and the screen-based general control system to compare the experiences and training effects. The results show that the HMD-based system can give a much better user experience and is easy to use. Three of the five components of a VR training system,namely, the user, the tasks, and software and database should be given more attention in future research.With more available technologies of input and output devices, VR engines, and system software, the VR training system will eventually yield much better training results, and will play a more important role in as a training tool for mine safety.
基金Project support by the National Key Research and Development Program of China(Grant No.2018YFF0301000)the National Natural Science Foundation of China(Grant Nos.71673161 and 71790613)。
文摘In complex networks,identifying influential spreader is of great significance for improving the reliability of networks and ensuring the safe and effective operation of networks.Nowadays,it is widely used in power networks,aviation networks,computer networks,and social networks,and so on.Traditional centrality methods mainly include degree centrality,closeness centrality,betweenness centrality,eigenvector centrality,k-shell,etc.However,single centrality method is onesided and inaccurate,and sometimes many nodes have the same centrality value,namely the same ranking result,which makes it difficult to distinguish between nodes.According to several classical methods of identifying influential nodes,in this paper we propose a novel method that is more full-scaled and universally applicable.Taken into account in this method are several aspects of node’s properties,including local topological characteristics,central location of nodes,propagation characteristics,and properties of neighbor nodes.In view of the idea of the multi-attribute decision-making,we regard the basic centrality method as node’s attribute and use the entropy weight method to weigh different attributes,and obtain node’s combined centrality.Then,the combined centrality is applied to the gravity law to comprehensively identify influential nodes in networks.Finally,the classical susceptible-infected-recovered(SIR)model is used to simulate the epidemic spreading in six real-society networks.Our proposed method not only considers the four topological properties of nodes,but also emphasizes the influence of neighbor nodes from the aspect of gravity.It is proved that the new method can effectively overcome the disadvantages of single centrality method and increase the accuracy of identifying influential nodes,which is of great significance for monitoring and controlling the complex networks.
基金Project supported by the National Basic Research Program of China(Grant No.2012CB719705)the National Natural Science Foundation of China(Grant Nos.91224008,91024032,and 71373139)
文摘As a physical model,the cellular automata(CA) model is widely used in many areas,such as stair evacuation.However,existing CA models do not consider evacuees' walk preferences nor psychological status,and the structure of the basic model is unapplicable for the stair structure.This paper is to improve the stair evacuation simulation by addressing these issues,and a new cellular automata model is established.Several evacuees' walk preference and how evacuee's psychology influences their behaviors are introduced into this model.Evacuees' speeds will be influenced by these features.To validate this simulation,two fire drills held in two high-rise buildings are video-recorded.It is found that the simulation results are similar to the fire drill results.The structure of this model is simple,and it is easy to further develop and utilize in different buildings with various kinds of occupants.
基金Project supported by the National Key Research and Development Program of China(Grant No.2018YFC0809900)the National Natural Science Foundation of China(Grant Nos.71774093 and 71473146)
文摘A new reliable cellular automaon(CA) model designed to account for stochasticity in traffic flow induced by heterogeneity in driving behavior is presented.The proposed model differs from most existing CA models in that this new model focuses on describing traffic phenomena by coding into its rules the key idea that a vehicle's moving state is directly determined by a driver stepping on the accelerator or on the brake(the vehicle's acceleration).Acceleration obeys a deformed continuous distribution function when considering the heterogeneity in driving behavior and the safe distance, rather than equaling a fixed acceleration value with a probability, as is the rule in many existing CA models.Simulation results show that the new proposed model is capable of reproducing empirical findings in real traffic system.Moreover, this new model makes it possible to implement in-depth analysis of correlations between a vehicle's state parameters.
基金Project supported by the National Key Technology Research and Development Program of the Ministry of Science and Technology of China(Grant No.2017YFC083300)the National Natural Science Foundation of China(Grant Nos.91646201,U1633203,and 51808422)the Independent Innovation Foundation of Wuhan University and Technology,China(Grant No.2019IVA011)。
文摘Pedestrian evacuation is actually a process of behavioral evolution. Interaction behaviors between pedestrians affect not only the evolution of their cooperation strategy, but also their evacuation paths-scheduling and dynamics features. The existence of interaction behaviors and cooperation evolution is therefore critical for pedestrian evacuation. To address this issue, an extended cellular automaton(CA) evacuation model considering the effects of interaction behaviors and cooperation evolution is proposed here. The influence mechanism of the environment factor and interaction behaviors between neighbors on the decision-making of one pedestrian to path scheduling is focused. Average payoffs interacting with neighbors are used to represent the competitive ability of one pedestrian, aiming to solve the conflicts when more than one pedestrian competes for the same position based on a new method. Influences of interaction behaviors, the panic degree and the conflict cost on the evacuation dynamics and cooperation evolution of pedestrians are discussed. Simulation results of the room evacuation show that the interaction behaviors between pedestrians to a certain extent are beneficial to the evacuation efficiency and the formation of cooperation behaviors as well. The increase of conflict cost prolongs the evacuation time. Panic emotions of pedestrians are bad for cooperation behaviors of the crowd and have complex effects on evacuation time. A new self-organization effect is also presented.
基金Project supported by the National Key Research and Development Program of China(Grant Nos.2017YFC0803300 and 2017YFC0820400)the National Natural Science Foundation of China(Grant No.71673163)
文摘In most situations,staircase is the only egress to evacuate from high-rise buildings.The merging flow on the stair landing has a great influence on the evacuation efficiency.In this paper,we develop an improved cellular automaton model to describe the merging behavior,and the model is validated by a series of real experiments.It is found that the flow rate of simulation results is similar to the drills,which means that the improved model is reasonable and can be used to describe the merging behavior on stairs.Furthermore,some scenarios with different door locations and building floor numbers are simulated by the model.The results show that(i)the best door location is next to the upward staircase;(ii)the total evacuation time and the building floor number are linearly related to each other;(iii)the pedestrians on upper floors have a negative influence on the evacuation flow rate.
基金funded by the Natural Science Foundation of Jiangsu Province(No.BK2012389)the National Natural Science Foundation of China(Nos.71303110,91024024)the Foundation of Graduate Innovation Center in NUAA(Nos.kfjj201471,kfjj201473)
文摘To track human across non-overlapping cameras in depression angles for applications such as multi-airplane visual human tracking and urban multi-camera surveillance,an adaptive human tracking method is proposed,focusing on both feature representation and human tracking mechanism.Feature representation describes individual by using both improved local appearance descriptors and statistical geometric parameters.The improved feature descriptors can be extracted quickly and make the human feature more discriminative.Adaptive human tracking mechanism is based on feature representation and it arranges the human image blobs in field of view into matrix.Primary appearance models are created to include the maximum inter-camera appearance information captured from different visual angles.The persons appeared in camera are first filtered by statistical geometric parameters.Then the one among the filtered persons who has the maximum matching scale with the primary models is determined to be the target person.Subsequently,the image blobs of the target person are used to update and generate new primary appearance models for the next camera,thus being robust to visual angle changes.Experimental results prove the excellence of the feature representation and show the good generalization capability of tracking mechanism as well as its robustness to condition variables.
基金Project supported by the National Key Technology Research and Development Program of China(Grant No.2018YFF0301000)the National Natural Science Foundation of China(Grant Nos.71673161 and 71790613)。
文摘Individuals’ preventive measures,as an effective way to suppress epidemic transmission and to protect themselves from infection,have attracted much academic concern,especially during the COVID-19 pandemic.In this paper,a reinforcement learning-based model is proposed to explore individuals’ effective preventive measures against epidemics.Through extensive simulations,we find that the cost of preventive measures influences the epidemic transmission process significantly.The infection scale increases as the cost of preventive measures grows,which means that the government needs to provide preventive measures with low cost to suppress the epidemic transmission.In addition,the effective preventive measures vary from individual to individual according to the social contacts.Individuals who contact with others frequently in daily life are highly recommended to take strict preventive measures to protect themselves from infection,while those who have little social contacts do not need to take any measures considering the inevitable cost.Our research contributes to exploring the effective measures for individuals,which can provide the government and individuals useful suggestions in response to epidemics.
文摘Grain security guarantees national security.China has many widely distributed grain depots to supervise grain storage security.However,this has led to a lack of regulatory capacity and manpower.Amid the development of reserve-level information technology,big data supervision of grain storage security should be improved.This study proposes big data research architecture and an analysis model for grain storage security;as an example,it illustrates the supervision of the grain loss problem in storage security.The statistical analysis model and the prediction and clustering-based model for grain loss supervision were used to mine abnormal data.A combination of feature extraction and feature selection reduction methods were chosen for dimensionality.A comparative analysis showed that the nonlinear prediction model performed better on the grain loss data set,with R2 of 87.21%,87.83%,91.97%,and 89.40%for Gradient Boosting Regressor(GBR),Random Forest,Decision Tree,XGBoost regression on test sets,respectively.Nineteen abnormal data were filtered out by GBR combined with residuals as an example.The deep learning model had the best performance on the mean absolute error,with an R2 of 85.14%on the test set and only one abnormal data identified.This is contrary to the original intention of finding as many anomalies as possible for supervisory purposes.Five classes were generated using principal component analysis dimensionality reduction combined with Density-Based Spatial Clustering of Applications with Noise(DBSCAN)clustering,with 11 anomalous data points screened by adding the amount of normalized grain loss.Based on the existing grain information system,this paper provides a supervision model for grain storage that can help mine abnormal data.Unlike the current post-event supervision model,this study proposes a pre-event supervision model.This study provides a framework of ideas for subsequent scholarly research;the addition of big data technology will help improve efficient supervisory capacity in the field of grain supervision.
