We develop and implement a Stochastic Discrete Event Simulation(SDES)algorithm to model the housing re-covery trajectory after an extreme event.The algorithm models discrete events and their underlying uncertainties i...We develop and implement a Stochastic Discrete Event Simulation(SDES)algorithm to model the housing re-covery trajectory after an extreme event.The algorithm models discrete events and their underlying uncertainties in each construction phase.Specifically,the algorithm is developed for the Government Assisted Owner Driven(GAOD)reconstruction system to simulate long-term recovery trajectory.SDES,as a flexible modeling approach,can simulate any housing recovery scenario that follows phased reconstruction.The 2015 M 7.8 Gorkha earthquake sequence in Nepal is considered the extreme event,with 796,245 buildings requiring reconstruction.We present some recovery trajectories from severely hit,crisis hit,and earthquake hit parishes,comparing them with the actual reconstruction progress.We also assess quality and improvement of reconstructed buildings using seismic fragility functions,compared to pre-earthquake constructions.Housing recovery uncertainties are dissected in relation to reconstruction pace.We conclude that the vast majority of the reconstructed buildings followed the Build Back Better(BBB)approach and missed the opportunity to pursue the Build Back Resilient(BBR)approach due to multifaceted challenges ranging from unclear policies to economic constraints.We critically assess the GAOD vs Owner Driven(OD)recovery framework and conclude that insurance-supported and technically assisted OD approach could be the most suitable model for post extreme event housing recovery.展开更多
This letter addressed the impactful study by Zhong et al,which introduced a risk prediction and stratification model for surgical adverse events following minimally invasive esophagectomy.By identifying key risk facto...This letter addressed the impactful study by Zhong et al,which introduced a risk prediction and stratification model for surgical adverse events following minimally invasive esophagectomy.By identifying key risk factors such as chronic obstructive pulmonary disease and hypoalbuminemia,the model demonstrated strong predictive accuracy and offered a pathway to personalized perioperative care.This correspondence highlighted the clinical significance,emphasizing its potential to optimize patient outcomes through tailored inter-ventions.Further prospective validation and application across diverse settings are essential to realize its full potential in advancing esophageal surgery practices.展开更多
Hydrological extremes,such as floods,droughts,and compound events,are extremely dangerous to human societies,ecosystems,and infrastructures,whose frequency and severity are affected by climate change more and more.Eff...Hydrological extremes,such as floods,droughts,and compound events,are extremely dangerous to human societies,ecosystems,and infrastructures,whose frequency and severity are affected by climate change more and more.Effective disaster preparedness,water resource management,and climate adaptation have to do with accurate prediction and extensive risk assessment.This review sums up recent progress in predictive modeling and risk assessment systems in the framework of hydrological extremes in the changing climatic conditions.Statistical and empirical techniques,including extreme value theory and nonstationary frequency analysis,give probabilistic information using historic records,whereas process-based models give an understanding of physical hydrological processes at different climate and land-use conditions.New information-based and hybrid methods that use machine learning and high-resolution data take advantage of the complexity and nonlinearities and enhance the predictive power.Hazard,exposure,vulnerability,and adaptive capacity risk assessment models allow predictive output to be translated into actionable decision support,with socio-economic aspects and analysis of the scenario.Case studies of various regions across the globe show the use of these techniques to address floods,droughts,and compound events,with success and current problems.The review also addresses current trends such as compound hazard,multi-hazard integration,AI-enabled modelling,and cross-sectoral decision support,and outlines research priorities of improving predictive capability and resilience.This review will inform researchers,policymakers,and practitioners by offering a synthesis of all the effects of the hydrological extremes in climate change to formulate sound strategies for alleviating these effects.展开更多
Rainfall is an important factor in estimating the event mean concentration （EMC） which is used to quantify the washed-off pollutant concentrations from non-point sources （NPSs）. Pollutant loads could also be calcu...Rainfall is an important factor in estimating the event mean concentration （EMC） which is used to quantify the washed-off pollutant concentrations from non-point sources （NPSs）. Pollutant loads could also be calculated using rainfall, catchment area and runoff coefficient. In this study, runoff quantity and quality data gathered from a 28-month monitoring conducted on the road and parking lot sites in Korea were evaluated using multiple linear regression （MLR） to develop equations for estimating pollutant loads and EMCs as a function of rainfall variables. The results revealed that total event rainfall and average rainfall intensity are possible predictors of pollutant loads. Overall, the models are indicators of the high uncertainties of NPSs; perhaps estimation of EMCs and loads could be accurately obtained by means of water quality sampling or a long term monitoring is needed to gather more data that can be used for the development of estimation models.展开更多
Business processes described by formal or semi-formal models are realized via information systems.Event logs generated from these systems are probably not consistent with the existing models due to insufficient design...Business processes described by formal or semi-formal models are realized via information systems.Event logs generated from these systems are probably not consistent with the existing models due to insufficient design of the information system or the system upgrade.By comparing an existing process model with event logs,we can detect inconsistencies called deviations,verify and extend the business process model,and accordingly improve the business process.In this paper,some abnormal activities in business processes are formally defined based on Petri nets.An efficient approach to detect deviations between the process model and event logs is proposed.Then,business process models are revised when abnormal activities exist.A clinical process in a healthcare information system is used as a case study to illustrate our work.Experimental results show the effectiveness and efficiency of the proposed approach.展开更多
The data of several rainfall products, including those estimated from satellite measurements and those forecasted via numerical weather modeling, for a severe debris-flow event in Zhouqu, Northwest China, are compared...The data of several rainfall products, including those estimated from satellite measurements and those forecasted via numerical weather modeling, for a severe debris-flow event in Zhouqu, Northwest China, are compared and analyzed in this paper. The satellite products, including CPC MORPHing technique（CMORPH）, TMPA-RT, and PERSIANN are all near-real-time retrieved with high temporal and spatial resolutions. The numerical weather model used in this paper for precipitation forecasting is WRF. The results show that all three satellite products can basically reproduce the rainfall pattern, distribution, timing, scale, and extreme values of the event, compared with gauge data. Their temporal and spatial correlation coefficients with gauge data are as high as about 0.6, which is statistically significant at 0.01 level. The performance of the forecasted results modeled with different spatial resolutions are not as good as the satellite-estimated results, although their correlation coefficients are still statistically significant at 0.05 level. From the total rainfall and extreme value time series for the domain, it is clear that, from the grid-to-grid perspective, the passive microwave-based CMORPH and TRMM products are more accurate than the infrared-based PERSIANN, while PERSIANN performs very well from the general point of view, especially when considering the whole domain or the whole convective precipitation system. The forecasted data — especially the highest resolution model domain data — are able to represent the total or mean precipitation very well in the research domain, while for extreme values the errors are large. This study suggests that satellite-retrieved and model-forecasted rainfall data are a useful complement to gauge data, especially for areas without gauge stations and areas not covered by weather radars.展开更多
A state/event fault tree(SEFT)is a modeling technique for describing the causal chains of events leading to failure in software-controlled complex systems.Such systems are ubiquitous in all areas of everyday life,and ...A state/event fault tree(SEFT)is a modeling technique for describing the causal chains of events leading to failure in software-controlled complex systems.Such systems are ubiquitous in all areas of everyday life,and safety and reliability analyses are increasingly required for these systems.SEFTs combine elements from the traditional fault tree with elements from state-based techniques.In the context of the real-time safety-critical systems,SEFTs do not describe the time properties and important timedependent system behaviors that can lead to system failures.Further,SEFTs lack the precise semantics required for formally modeling time behaviors.In this paper,we present a qualitative analysis method for SEFTs based on transformation from SEFT to timed automata(TA),and use the model checker UPPAAL to verify system requirements’properties.The combination of SEFT and TA is an important step towards an integrated design and verification process for real-time safety-critical systems.Finally,we present a case study of a powerboat autopilot system to confirm our method is viable and valid after achieving the verification goal step by step.展开更多
There are mainly four kinds of models to record and deal with historical information.By taking them as reference,the spatio-temporal model based on event semantics is proposed.In this model,according to the way for de...There are mainly four kinds of models to record and deal with historical information.By taking them as reference,the spatio-temporal model based on event semantics is proposed.In this model,according to the way for describing an event,all the information are divided into five domains.This paper describes the model by using the land parcel change in the cadastral information system,and expounds the model by using five tables corresponding to the five domains.With the aid of this model,seven examples are given on historical query,trace back and recurrence.This model can be implemented either in the extended relational database or in the object-oriented database.展开更多
The aim of this paper is to present a discrete event model-based approach to simulate train movement with the con- sidered energy-saving factor. We conduct extensive case studies to show the dynamic characteristics of...The aim of this paper is to present a discrete event model-based approach to simulate train movement with the con- sidered energy-saving factor. We conduct extensive case studies to show the dynamic characteristics of the traffic flow and demonstrate the effectiveness of the proposed approach. The simulation results indicate that the proposed discrete event model-based simulation approach is suitable for characterizing the movements of a group of trains on a single railway line with less iterations and CPU time. Additionally, some other qualitative and quantitative characteristics are investigated. In particular, because of the cumulative influence from the previous trains, the following trains should be accelerated or braked frequently to control the headway distance, leading to more energy consumption.展开更多
In this paper, the changes in temperature and precipitation extremes over the next 20-30 years (2021-2050) in relative to the present day (1986-2005) under the Intergovernmental Panel on Climate Change (IPCC) Special ...In this paper, the changes in temperature and precipitation extremes over the next 20-30 years (2021-2050) in relative to the present day (1986-2005) under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario are analyzed based on a high-resolution climate change simulation performed by a regional climate model (the Abdus Salam International Center for Theoretical Physics (ICTP) RegCM3). The extreme indices of summer days (SU), frost days (FD), and growing season length (GSL) for temperature and simple daily intensity index (SDII), number of days with precipitation ≥10 mm d-1 (R10), and consecutive dry days (CDD) for precipitation are used as the indicators of the extremes. The results show that the indices simulated by RegCM3 in the present day show good agreement with the observed. A general increase in SU, a decrease in FD, and an increase in GSL are found to occur in the next 20-30 years over China. A general increase in SDII, an increase in R10 over western China, and a decrease in R10 in north, northeast, and central China are simulated by the model. Changes in CDD are characterized by a decrease in the north and an increase in the south and the Tibetan Plateau.展开更多
Methods of improving seismic event locations were investigated as part of a research study aimed at reducing ground control safety hazards. Seismic event waveforms collected with a 23-station three-dimensional sensor ...Methods of improving seismic event locations were investigated as part of a research study aimed at reducing ground control safety hazards. Seismic event waveforms collected with a 23-station three-dimensional sensor array during longwall coal mining provide the data set used in the analyses. A spatially variable seismic velocity model is constructed using seismic event sources in a passive tomographic method. The resulting three-dimensional velocity model is used to relocate seismic event positions. An evolutionary optimization algorithm is implemented and used in both the velocity model development and in seeking improved event location solutions. Results obtained using the different velocity models are compared. The combination of the tomographic velocity model development and evolutionary search algorithm provides improvement to the event locations.展开更多
A global forecast model is used to examine various sensitivities of numerical predictions of three extreme winter storms that occurred near the eastern continental margin of North America: the Ohio Valley blizzard of ...A global forecast model is used to examine various sensitivities of numerical predictions of three extreme winter storms that occurred near the eastern continental margin of North America: the Ohio Valley blizzard of January 1978, the New England blizzard of February 1978, and the Mid-Atlantic cyclone of February 1979. While medium-resolution simulations capture much of the intensification, the forecasts of the precise timing and intensity levels suffer from various degrees of error. The coastal cyclones show a 5-10 hPa dependence on the western North Atlantic sea surface temperature, which is varied within a range (± 2.5℃) compatible with interannual fluctuations. The associated vertical velocities and precipitation rates show proportionately stronger dependences on the ocean temperature perturbations. The Ohio Valley blizzard, which intensified along a track 700-800 km from the coast, shows little sensitivity to ocean temperature. The effect of a shift of - 10?latitude in the position of the snow boundary is negligible in each case. The forecasts depend strongly on the model resolution, and the coarse-resolution forecasts are consistently inferior to the medium-resolution forecasts. Studies of the corresponding sensitivities of extreme cyclonic events over eastern Asia are encouraged in order to identify characteristics that are common to numerical forecasts for the two regions.展开更多
A conceptual hydrological model that links the Xin＇anjiang hydrological model and a physically based snow energy and mass balance model, described as the XINSNOBAL model, was developed in this study for simulating ra...A conceptual hydrological model that links the Xin＇anjiang hydrological model and a physically based snow energy and mass balance model, described as the XINSNOBAL model, was developed in this study for simulating rain-on-snow events that commonly occur in the Pacific Northwest of the United States. The resultant model was applied to the Lookout Creek Watershed in the H. J. Andrews Experimental Forest in the western Cascade Mountains of Oregon, and its ability to simulate streamflow was evaluated. The simulation was conducted at 24-hour and one-hour time scales for the period of 1996 to 2005. The results indicated that runoffand peak discharge could be underestimated if snowpack accumulation and snowmelt under rain-on-snow conditions were not taken into account. The average deterministic coefficient of the hourly model in streamflow simulation in the calibration stage was 0.837, which was significantly improved over the value of 0.762 when the Xin＇anjiang model was used alone. Good simulation performance of the XINSNOBAL model in the WS 10 catchment, using the calibrated parameter of the Lookout Creek Watershed for proxy-basin testing, demonstrates that transplanting model parameters between similar watersheds can orovide a useful tool for discharge forecastin~, in un^au^ed basins.展开更多
After the occurrence of unexpected group events of network, the relevant opinion information will spread rapidly through micro-blog, and the negative public opinion information will aggravate the unexpected the group ...After the occurrence of unexpected group events of network, the relevant opinion information will spread rapidly through micro-blog, and the negative public opinion information will aggravate the unexpected the group events to upgrade and expand the scope of harm. It is difficult to deal. So public opinion control is very important. In this paper, we establish an influence model for spreading of public opinion based on SIR model. Through the political analysis, this paper finds that the network group events will subside, but the influence scope, time and ability of event cannot be ignored. As a result of this study, the corresponding strategies are put forward in this paper.展开更多
A new event-handling paradigm and its application model are proposed. The working mechanism and principle of event listener model is given in detail. Finally, the launching event mechanisms, the choosing event handlin...A new event-handling paradigm and its application model are proposed. The working mechanism and principle of event listener model is given in detail. Finally, the launching event mechanisms, the choosing event handling models and the dispatching mechanism are illustrated.展开更多
Single-event microkinetic(SEMK) model of the catalytic cracking of methylcyclohexane admixed with 1-octene over REUSY zeolites at 693 K—753 K in the absence of coke formation is enhanced. To keep consistency with the...Single-event microkinetic(SEMK) model of the catalytic cracking of methylcyclohexane admixed with 1-octene over REUSY zeolites at 693 K—753 K in the absence of coke formation is enhanced. To keep consistency with the wellknown carbenium ion chemistry, hydride transfer forming and consuming allylic carbenium ions in the aromatization of cycloparaffins are further investigated and differentiated. The reversibility of endocyclic β-scission and cyclization reactions is refined by accounting explicitly for the reacting olefins and resulting cycloparaffins in the corresponding thermodynamics. 24 activation energies for the reactions involved in the cracking of cycloparaffins are obtained by the regression of 15 sets of experimental data upon taking the resulting 37 main cracking products, i. e., responses into account. The enhanced SEMK model can adequately describe the catalytic behavior of 37 main products with conversion and temperature.展开更多
There has been much interest in studying quasi-periodic events on earthquake models.Here we investigate quasiperiodic events in the avalanche time series on structured earthquake models by the analysis of the autocorr...There has been much interest in studying quasi-periodic events on earthquake models.Here we investigate quasiperiodic events in the avalanche time series on structured earthquake models by the analysis of the autocorrelation function and the fast Fourier transform.For random spatial earthquake models, quasi-periodic events are robust and we obtain a simple rule for a period that is proportional to the choice of unit time and the dissipation of the system.Moreover, computer simulations validate this rule for two-dimensional lattice models and cycle graphs, but our simulation results also show that small-world models, scale-free models, and random rule graphs do not have periodic phenomena.Although the periodicity of avalanche does not depend on the criticality of the system or the average degree of the system or the size of the system,there is evidence that it depends on the time series of the average force of the system.展开更多
In order to keep decision-makers better informed with emergencies, it is useful to retrieve the user-oriented disaster relevant event information in an aggregated results list through meta-search engine. However, emer...In order to keep decision-makers better informed with emergencies, it is useful to retrieve the user-oriented disaster relevant event information in an aggregated results list through meta-search engine. However, emergent event is dynamic which makes it difficult to use fixed search word or word combinations. This paper proposes an event situation monitoring model（ESMM） event detection model, which realizes heuristic query word vector dynamic expanding by adopting emergency fuzzy scenario reasoning ontology cluster. Disaster event facet information automatic searching is discussed as an example in this paper. The experimental results show that the proposed method can increase accuracy and extra clues not supplied by commercial search engines, which can be used as a supplement information source for government and individuals.展开更多
The emergence of Event-based Social Network(EBSN) data that contain both social and event information has cleared the way to study the social interactive relationship between the virtual interactions and physical inte...The emergence of Event-based Social Network(EBSN) data that contain both social and event information has cleared the way to study the social interactive relationship between the virtual interactions and physical interactions. In existing studies, it is not really clear which factors affect event similarity between online friends and the influence degree of each factor. In this study, a multi-layer network based on the Plancast service data is constructed. The the user’s events belongingness is shuffled by constructing two null models to detect offline event similarity between online friends. The results indicate that there is a strong correlation between online social proximity and offline event similarity. The micro-scale structures at multi-levels of the Plancast online social network are also maintained by constructing 0 k–3 k null models to study how the micro-scale characteristics of online networks affect the similarity of offline events. It is found that the assortativity pattern is a significant micro-scale characteristic to maintain offline event similarity. Finally, we study how structural diversity of online friends affects the offline event similarity. We find that the subgraph structure of common friends has no positive impact on event similarity while the number of common friends plays a key role, which is different from other studies. In addition, we discuss the randomness of different null models, which can measure the degree of information availability in privacy protection. Our study not only uncovers the factors that affect offline event similarity between friends but also presents a framework for understanding the pattern of human mobility.展开更多
文摘We develop and implement a Stochastic Discrete Event Simulation(SDES)algorithm to model the housing re-covery trajectory after an extreme event.The algorithm models discrete events and their underlying uncertainties in each construction phase.Specifically,the algorithm is developed for the Government Assisted Owner Driven(GAOD)reconstruction system to simulate long-term recovery trajectory.SDES,as a flexible modeling approach,can simulate any housing recovery scenario that follows phased reconstruction.The 2015 M 7.8 Gorkha earthquake sequence in Nepal is considered the extreme event,with 796,245 buildings requiring reconstruction.We present some recovery trajectories from severely hit,crisis hit,and earthquake hit parishes,comparing them with the actual reconstruction progress.We also assess quality and improvement of reconstructed buildings using seismic fragility functions,compared to pre-earthquake constructions.Housing recovery uncertainties are dissected in relation to reconstruction pace.We conclude that the vast majority of the reconstructed buildings followed the Build Back Better(BBB)approach and missed the opportunity to pursue the Build Back Resilient(BBR)approach due to multifaceted challenges ranging from unclear policies to economic constraints.We critically assess the GAOD vs Owner Driven(OD)recovery framework and conclude that insurance-supported and technically assisted OD approach could be the most suitable model for post extreme event housing recovery.
文摘This letter addressed the impactful study by Zhong et al,which introduced a risk prediction and stratification model for surgical adverse events following minimally invasive esophagectomy.By identifying key risk factors such as chronic obstructive pulmonary disease and hypoalbuminemia,the model demonstrated strong predictive accuracy and offered a pathway to personalized perioperative care.This correspondence highlighted the clinical significance,emphasizing its potential to optimize patient outcomes through tailored inter-ventions.Further prospective validation and application across diverse settings are essential to realize its full potential in advancing esophageal surgery practices.
文摘Hydrological extremes,such as floods,droughts,and compound events,are extremely dangerous to human societies,ecosystems,and infrastructures,whose frequency and severity are affected by climate change more and more.Effective disaster preparedness,water resource management,and climate adaptation have to do with accurate prediction and extensive risk assessment.This review sums up recent progress in predictive modeling and risk assessment systems in the framework of hydrological extremes in the changing climatic conditions.Statistical and empirical techniques,including extreme value theory and nonstationary frequency analysis,give probabilistic information using historic records,whereas process-based models give an understanding of physical hydrological processes at different climate and land-use conditions.New information-based and hybrid methods that use machine learning and high-resolution data take advantage of the complexity and nonlinearities and enhance the predictive power.Hazard,exposure,vulnerability,and adaptive capacity risk assessment models allow predictive output to be translated into actionable decision support,with socio-economic aspects and analysis of the scenario.Case studies of various regions across the globe show the use of these techniques to address floods,droughts,and compound events,with success and current problems.The review also addresses current trends such as compound hazard,multi-hazard integration,AI-enabled modelling,and cross-sectoral decision support,and outlines research priorities of improving predictive capability and resilience.This review will inform researchers,policymakers,and practitioners by offering a synthesis of all the effects of the hydrological extremes in climate change to formulate sound strategies for alleviating these effects.
基金provided by the Korean Ministry of Environment and Eco Star Project
文摘Rainfall is an important factor in estimating the event mean concentration （EMC） which is used to quantify the washed-off pollutant concentrations from non-point sources （NPSs）. Pollutant loads could also be calculated using rainfall, catchment area and runoff coefficient. In this study, runoff quantity and quality data gathered from a 28-month monitoring conducted on the road and parking lot sites in Korea were evaluated using multiple linear regression （MLR） to develop equations for estimating pollutant loads and EMCs as a function of rainfall variables. The results revealed that total event rainfall and average rainfall intensity are possible predictors of pollutant loads. Overall, the models are indicators of the high uncertainties of NPSs; perhaps estimation of EMCs and loads could be accurately obtained by means of water quality sampling or a long term monitoring is needed to gather more data that can be used for the development of estimation models.
基金supported by the National Natural Science Foundation of China(61170078,61472228,61903229,61902222)the “Taishan Scholar” Construction Project of Shandong Province,China,the Natural Science Foundation of Shandong Province(ZR2018MF001)+1 种基金the Scientific Research Foundation of Shandong University of Science and Technology for Recruited Talents(2017RCJJ044)the Key Research and Development Program of Shandong Province(2018GGX101011)
文摘Business processes described by formal or semi-formal models are realized via information systems.Event logs generated from these systems are probably not consistent with the existing models due to insufficient design of the information system or the system upgrade.By comparing an existing process model with event logs,we can detect inconsistencies called deviations,verify and extend the business process model,and accordingly improve the business process.In this paper,some abnormal activities in business processes are formally defined based on Petri nets.An efficient approach to detect deviations between the process model and event logs is proposed.Then,business process models are revised when abnormal activities exist.A clinical process in a healthcare information system is used as a case study to illustrate our work.Experimental results show the effectiveness and efficiency of the proposed approach.
基金supported by the National Natural Science Foundation of China[grant numbers 41421004 and 41210007]the International Innovation Team project of the Chinese Academy of Sciences entitled ‘High Resolution Numerical Simulation of Regional Environment’
文摘The data of several rainfall products, including those estimated from satellite measurements and those forecasted via numerical weather modeling, for a severe debris-flow event in Zhouqu, Northwest China, are compared and analyzed in this paper. The satellite products, including CPC MORPHing technique（CMORPH）, TMPA-RT, and PERSIANN are all near-real-time retrieved with high temporal and spatial resolutions. The numerical weather model used in this paper for precipitation forecasting is WRF. The results show that all three satellite products can basically reproduce the rainfall pattern, distribution, timing, scale, and extreme values of the event, compared with gauge data. Their temporal and spatial correlation coefficients with gauge data are as high as about 0.6, which is statistically significant at 0.01 level. The performance of the forecasted results modeled with different spatial resolutions are not as good as the satellite-estimated results, although their correlation coefficients are still statistically significant at 0.05 level. From the total rainfall and extreme value time series for the domain, it is clear that, from the grid-to-grid perspective, the passive microwave-based CMORPH and TRMM products are more accurate than the infrared-based PERSIANN, while PERSIANN performs very well from the general point of view, especially when considering the whole domain or the whole convective precipitation system. The forecasted data — especially the highest resolution model domain data — are able to represent the total or mean precipitation very well in the research domain, while for extreme values the errors are large. This study suggests that satellite-retrieved and model-forecasted rainfall data are a useful complement to gauge data, especially for areas without gauge stations and areas not covered by weather radars.
基金supported by the National Natural Science Foundation of China(11832012)
文摘A state/event fault tree(SEFT)is a modeling technique for describing the causal chains of events leading to failure in software-controlled complex systems.Such systems are ubiquitous in all areas of everyday life,and safety and reliability analyses are increasingly required for these systems.SEFTs combine elements from the traditional fault tree with elements from state-based techniques.In the context of the real-time safety-critical systems,SEFTs do not describe the time properties and important timedependent system behaviors that can lead to system failures.Further,SEFTs lack the precise semantics required for formally modeling time behaviors.In this paper,we present a qualitative analysis method for SEFTs based on transformation from SEFT to timed automata(TA),and use the model checker UPPAAL to verify system requirements’properties.The combination of SEFT and TA is an important step towards an integrated design and verification process for real-time safety-critical systems.Finally,we present a case study of a powerboat autopilot system to confirm our method is viable and valid after achieving the verification goal step by step.
文摘There are mainly four kinds of models to record and deal with historical information.By taking them as reference,the spatio-temporal model based on event semantics is proposed.In this model,according to the way for describing an event,all the information are divided into five domains.This paper describes the model by using the land parcel change in the cadastral information system,and expounds the model by using five tables corresponding to the five domains.With the aid of this model,seven examples are given on historical query,trace back and recurrence.This model can be implemented either in the extended relational database or in the object-oriented database.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.71271020 and 71271022)the Program for New Century Excellent Talents in University(Grant No.NCET-10-0218)
文摘The aim of this paper is to present a discrete event model-based approach to simulate train movement with the con- sidered energy-saving factor. We conduct extensive case studies to show the dynamic characteristics of the traffic flow and demonstrate the effectiveness of the proposed approach. The simulation results indicate that the proposed discrete event model-based simulation approach is suitable for characterizing the movements of a group of trains on a single railway line with less iterations and CPU time. Additionally, some other qualitative and quantitative characteristics are investigated. In particular, because of the cumulative influence from the previous trains, the following trains should be accelerated or braked frequently to control the headway distance, leading to more energy consumption.
基金supported by the National Basic Research Program of China(Grant No.2009CB421407)the China-UK-Swiss Adapting to Climate Change in China Project (ACCC)-Climate Science
文摘In this paper, the changes in temperature and precipitation extremes over the next 20-30 years (2021-2050) in relative to the present day (1986-2005) under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario are analyzed based on a high-resolution climate change simulation performed by a regional climate model (the Abdus Salam International Center for Theoretical Physics (ICTP) RegCM3). The extreme indices of summer days (SU), frost days (FD), and growing season length (GSL) for temperature and simple daily intensity index (SDII), number of days with precipitation ≥10 mm d-1 (R10), and consecutive dry days (CDD) for precipitation are used as the indicators of the extremes. The results show that the indices simulated by RegCM3 in the present day show good agreement with the observed. A general increase in SU, a decrease in FD, and an increase in GSL are found to occur in the next 20-30 years over China. A general increase in SDII, an increase in R10 over western China, and a decrease in R10 in north, northeast, and central China are simulated by the model. Changes in CDD are characterized by a decrease in the north and an increase in the south and the Tibetan Plateau.
文摘Methods of improving seismic event locations were investigated as part of a research study aimed at reducing ground control safety hazards. Seismic event waveforms collected with a 23-station three-dimensional sensor array during longwall coal mining provide the data set used in the analyses. A spatially variable seismic velocity model is constructed using seismic event sources in a passive tomographic method. The resulting three-dimensional velocity model is used to relocate seismic event positions. An evolutionary optimization algorithm is implemented and used in both the velocity model development and in seeking improved event location solutions. Results obtained using the different velocity models are compared. The combination of the tomographic velocity model development and evolutionary search algorithm provides improvement to the event locations.
文摘A global forecast model is used to examine various sensitivities of numerical predictions of three extreme winter storms that occurred near the eastern continental margin of North America: the Ohio Valley blizzard of January 1978, the New England blizzard of February 1978, and the Mid-Atlantic cyclone of February 1979. While medium-resolution simulations capture much of the intensification, the forecasts of the precise timing and intensity levels suffer from various degrees of error. The coastal cyclones show a 5-10 hPa dependence on the western North Atlantic sea surface temperature, which is varied within a range (± 2.5℃) compatible with interannual fluctuations. The associated vertical velocities and precipitation rates show proportionately stronger dependences on the ocean temperature perturbations. The Ohio Valley blizzard, which intensified along a track 700-800 km from the coast, shows little sensitivity to ocean temperature. The effect of a shift of - 10?latitude in the position of the snow boundary is negligible in each case. The forecasts depend strongly on the model resolution, and the coarse-resolution forecasts are consistently inferior to the medium-resolution forecasts. Studies of the corresponding sensitivities of extreme cyclonic events over eastern Asia are encouraged in order to identify characteristics that are common to numerical forecasts for the two regions.
基金supported by the National Natural Science Foundation of China (Grants No. 40901015 and41001011)the Major Program of the National Natural Science Foundation of China (Grants No. 51190090 and 51190091)+3 种基金the Fundamental Research Funds for the Central Universities (Grants No. B1020062 andB1020072)the Ph. D. Programs Foundation of the Ministry of Education of China (Grant No.20090094120008)the Special Fund of State Key Laboratories of China (Grants No. 2009586412 and 2009585412)the Programme of Introducing Talents of Disciplines to Universities of the Ministry of Education and State Administration of the Foreign Experts Affairs of China (the 111 Project, Grant No.B08048)
文摘A conceptual hydrological model that links the Xin＇anjiang hydrological model and a physically based snow energy and mass balance model, described as the XINSNOBAL model, was developed in this study for simulating rain-on-snow events that commonly occur in the Pacific Northwest of the United States. The resultant model was applied to the Lookout Creek Watershed in the H. J. Andrews Experimental Forest in the western Cascade Mountains of Oregon, and its ability to simulate streamflow was evaluated. The simulation was conducted at 24-hour and one-hour time scales for the period of 1996 to 2005. The results indicated that runoffand peak discharge could be underestimated if snowpack accumulation and snowmelt under rain-on-snow conditions were not taken into account. The average deterministic coefficient of the hourly model in streamflow simulation in the calibration stage was 0.837, which was significantly improved over the value of 0.762 when the Xin＇anjiang model was used alone. Good simulation performance of the XINSNOBAL model in the WS 10 catchment, using the calibrated parameter of the Lookout Creek Watershed for proxy-basin testing, demonstrates that transplanting model parameters between similar watersheds can orovide a useful tool for discharge forecastin~, in un^au^ed basins.
文摘After the occurrence of unexpected group events of network, the relevant opinion information will spread rapidly through micro-blog, and the negative public opinion information will aggravate the unexpected the group events to upgrade and expand the scope of harm. It is difficult to deal. So public opinion control is very important. In this paper, we establish an influence model for spreading of public opinion based on SIR model. Through the political analysis, this paper finds that the network group events will subside, but the influence scope, time and ability of event cannot be ignored. As a result of this study, the corresponding strategies are put forward in this paper.
文摘A new event-handling paradigm and its application model are proposed. The working mechanism and principle of event listener model is given in detail. Finally, the launching event mechanisms, the choosing event handling models and the dispatching mechanism are illustrated.
基金financial support from the China Scholarship Councilthe Long Term Structural Methusalem Funding by the Flemish Government
文摘Single-event microkinetic(SEMK) model of the catalytic cracking of methylcyclohexane admixed with 1-octene over REUSY zeolites at 693 K—753 K in the absence of coke formation is enhanced. To keep consistency with the wellknown carbenium ion chemistry, hydride transfer forming and consuming allylic carbenium ions in the aromatization of cycloparaffins are further investigated and differentiated. The reversibility of endocyclic β-scission and cyclization reactions is refined by accounting explicitly for the reacting olefins and resulting cycloparaffins in the corresponding thermodynamics. 24 activation energies for the reactions involved in the cracking of cycloparaffins are obtained by the regression of 15 sets of experimental data upon taking the resulting 37 main cracking products, i. e., responses into account. The enhanced SEMK model can adequately describe the catalytic behavior of 37 main products with conversion and temperature.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11575072 and 11675096)the Fundamental Research Funds for the Central Universities,China(Grant No.GK201702001)the FPALAB-SNNU,China(Grant No.16QNGG007)
文摘There has been much interest in studying quasi-periodic events on earthquake models.Here we investigate quasiperiodic events in the avalanche time series on structured earthquake models by the analysis of the autocorrelation function and the fast Fourier transform.For random spatial earthquake models, quasi-periodic events are robust and we obtain a simple rule for a period that is proportional to the choice of unit time and the dissipation of the system.Moreover, computer simulations validate this rule for two-dimensional lattice models and cycle graphs, but our simulation results also show that small-world models, scale-free models, and random rule graphs do not have periodic phenomena.Although the periodicity of avalanche does not depend on the criticality of the system or the average degree of the system or the size of the system,there is evidence that it depends on the time series of the average force of the system.
基金Supported by the National Natural Science Foundation of China(61100133)
文摘In order to keep decision-makers better informed with emergencies, it is useful to retrieve the user-oriented disaster relevant event information in an aggregated results list through meta-search engine. However, emergent event is dynamic which makes it difficult to use fixed search word or word combinations. This paper proposes an event situation monitoring model（ESMM） event detection model, which realizes heuristic query word vector dynamic expanding by adopting emergency fuzzy scenario reasoning ontology cluster. Disaster event facet information automatic searching is discussed as an example in this paper. The experimental results show that the proposed method can increase accuracy and extra clues not supplied by commercial search engines, which can be used as a supplement information source for government and individuals.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61773091,61603073,61601081,and 61501107)the Natural Science Foundation of Liaoning Province,China(Grant No.201602200)
文摘The emergence of Event-based Social Network(EBSN) data that contain both social and event information has cleared the way to study the social interactive relationship between the virtual interactions and physical interactions. In existing studies, it is not really clear which factors affect event similarity between online friends and the influence degree of each factor. In this study, a multi-layer network based on the Plancast service data is constructed. The the user’s events belongingness is shuffled by constructing two null models to detect offline event similarity between online friends. The results indicate that there is a strong correlation between online social proximity and offline event similarity. The micro-scale structures at multi-levels of the Plancast online social network are also maintained by constructing 0 k–3 k null models to study how the micro-scale characteristics of online networks affect the similarity of offline events. It is found that the assortativity pattern is a significant micro-scale characteristic to maintain offline event similarity. Finally, we study how structural diversity of online friends affects the offline event similarity. We find that the subgraph structure of common friends has no positive impact on event similarity while the number of common friends plays a key role, which is different from other studies. In addition, we discuss the randomness of different null models, which can measure the degree of information availability in privacy protection. Our study not only uncovers the factors that affect offline event similarity between friends but also presents a framework for understanding the pattern of human mobility.
