With the rapid development of mobile Internet, people pay increasing attention to the wireless network security problem. But due to the specificity of the wireless network, at present it is rare to see the research of...With the rapid development of mobile Internet, people pay increasing attention to the wireless network security problem. But due to the specificity of the wireless network, at present it is rare to see the research of wireless intrusion alerts clustering method for mobile Internet. This paper proposes a Wireless Intrusion Alert Clustering Method(WIACM) based on the information of the mobile terminal. The method includes alert formatting, alert reduction and alert classification. By introducing key information of the mobile terminal device, this method aggregates the original alerts into hyper alerts. The experimental results show that WIACM would be appropriate for real attack scenarios of mobile Internet, and reduce the amount of alerts with more accuracy of alert analysis.展开更多
Back of queue crashes on Interstates are a major concern for all state transportation departments. In 2020, Indiana DOT begin deploying queue warning trucks with message boards, flashers and digital alerts that could ...Back of queue crashes on Interstates are a major concern for all state transportation departments. In 2020, Indiana DOT begin deploying queue warning trucks with message boards, flashers and digital alerts that could be transmitted to navigation systems such as Waze. This study reports on the deployment and impact evaluation of digital alerts on motorist’s assistance patrols and 19 Queue trucks in Indiana. The motorist assistance patrol evaluation is provided qualitatively. A novel analysis of queue warning trucks equipped with digital alerts was conducted during the months of May-July in 2021 using connected vehicle data. This new data set reports locations of anonymous hard-braking events from connected vehicles on the Interstate. Hard-braking events were tabulated for when queueing occurred with and without the presence of a queue warning truck. Approximately 370 hours of queueing with queue trucks present and 58 hours of queueing without queue truck<span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> present were evaluated. Hard-braking events were found to decrease approximately 80% when queue warning trucks were used to alert motorists of impending queues.</span>展开更多
To solve the problem of the aleri flooding and information semantics in theexisting Intrusion Detection Sys-tem(IDS), we present a two-stage algorithm for correlating thealerts. In the first stage- the high-level aler...To solve the problem of the aleri flooding and information semantics in theexisting Intrusion Detection Sys-tem(IDS), we present a two-stage algorithm for correlating thealerts. In the first stage- the high-level alerts is integrated by using the Chronicle patternsbased on time intervals, which describe and match the alerts with the temporal time constrains of aninput sequence. In the second stage, the preparing relationship between the high-level alerts isdefined, which is applied to eorrtlatethe high-level alerts, and the attack scenario is constructedby drawing the attack graph. In the end a given example show? the performances of this two-stagecorrelation algorithm in decreasing the number and improving the information semantic of theintrusion alerts produced by the IDS.展开更多
Warning alerts are specially designed to protect user rights and safety to avoid serious damage caused by overlooking the essence of warning alerts. Today’s world of Information Communication Technology (ICT) needs i...Warning alerts are specially designed to protect user rights and safety to avoid serious damage caused by overlooking the essence of warning alerts. Today’s world of Information Communication Technology (ICT) needs improvement and to review the decisions of security experts in terms of improving warning designs and dialogues, and timely inform the authorities to take quick action at the right time and choice. Human behaviour is deeply involved in most of the security failures and its poor response. If we are able to check and monitor human behaviour in any organisation, we can achieve quality assurance and provide best services to our customers. We have arranged a study in the Center of Post Graduate Studies, International Islamic University, Malaysia (CPS-IIUM), department of Hajj Services-Makkah, and Hospital Management System-Makkah comprised of Observation, Interviews, Questionnaire and discussion based on organizational structure and job activities of people involved in different scenarios and positions under one umbrella of organizational objectives in order to trap the human error in order to take rapid action and response from the management team. Human behaviour is deeply observed and checked while performing different job activities in order to identify the serious errors at the right time during job performance at various levels. We have applied the concept of Brahm’s Language for the simulation of human behaviour which proves an opportunity to simulate human behaviour while performing job activities. Customer service can be improved easily if necessary measures and decisions are taken at the right time and place in any organisation.展开更多
In-cab alerts warn commercial vehicle drivers of upcoming roadway incidents, slowdowns and work zone construction activities. This paper reports on a study evaluating the driver response to in-cab alerts in Ohio. Driv...In-cab alerts warn commercial vehicle drivers of upcoming roadway incidents, slowdowns and work zone construction activities. This paper reports on a study evaluating the driver response to in-cab alerts in Ohio. Driver response was evaluated by measuring the statistical trends of vehicle speeds after the in-cab alerts were received. Vehicle speeds pre and post in-cab alert were collected over a 47 day period in the fall of 2023 for trucks traveling on interstate roadways in Ohio. Results show that approximately 22% of drivers receiving Dangerous Slowdown alerts had reduced their speeds by at least 5 mph 30 seconds after receiving such an alert. Segmenting this analysis by speed found that of vehicles traveling at or above 70 mph at the time of alerting, 26% reduced speeds by at least 5 mph. These speed reductions suggest drivers taking actional measures after receiving alerts. Future studies will involve further analysis on the impact of the types of alerts shown, roadway characteristics and overall traffic conditions on truck speeds passing through work zones.展开更多
A glacier hazard chain can form a long-runout mass flow and generate a large flood,affecting downstream areas hundreds of kilometers away from the initiating hazard site.This study focuses on the Yarlung Zangbo Daxiag...A glacier hazard chain can form a long-runout mass flow and generate a large flood,affecting downstream areas hundreds of kilometers away from the initiating hazard site.This study focuses on the Yarlung Zangbo Daxiagu.The objective is to address two key unresolved issues:the evolution of detached glacier materials into debris flows or debris floods and the amplification of the impact range and threats.A comprehensive framework is developed that considers the impacts of near-field and far-field hazards.Numerical modeling,remote sensing,and field investigations were integrated to understand the interactions,transformations,and amplifications of hazards in the glacier hazard chain.The results indicate that extensive,nearly saturated sediments on the glacier valley floor,when entrained,amplify the magnitude of the mass flow.The topography plays a crucial role.When the valley outlet is perpendicular to the river course,topographic obstacles cause immediate halting,resulting in the formation of high barrier dams.Conversely,when the glacier valley aligns nearly parallel to the river course,the mass flow can travel a much longer distance upon entering the river,causing an enlarged affected area.The barrier dams can breach rapidly,causing breaching floods that amplify the downstream impact from several kilometers to hundreds of kilometers.Our analysis reveals that the overall impacts remain spatially limited.Specifically,downstream areas along the Yarlung Zangbo-Brahmaputra River are unlikely to face greater threats from the upstream floods than local monsoon floods.Our findings provide the foundation for the management of glacier hazard chains.展开更多
Storm surge events(SSEs)involve multiple hazard-causing factors,such as surges,extreme rainfall,strong winds,waves,and ocean currents,which have destructive impacts on coastal regions.For a quantitative multi-hazard a...Storm surge events(SSEs)involve multiple hazard-causing factors,such as surges,extreme rainfall,strong winds,waves,and ocean currents,which have destructive impacts on coastal regions.For a quantitative multi-hazard assessment of SSEs,this study introduced the concept of the storm surge event seawater-atmosphere system(SSE-SAS)and proposed the system energy equivalence(SEE)model from a systemic energy perspective.SEE was obtained by employing a parameterization approach,and the hazard index(HI)and the concept of most significant hazard(MSH)were adopted to evaluate the severity of SSE-SAS.SEE at five stations in the Shandong Peninsula was calculated from 2005 to 2019,and probability analysis and hazard assessment were further conducted.Results show that the SEE of SSE-SAS ranges from 0.029×10^(3) to 30.418×10^(3) J/m^(2),and it exhibits an insignificant decreasing trend from 2005 to 2019.The SEE of SSE-SAS in the west of the Shandong Peninsula is greater than that in the east.Moreover,storm waves,storm surges,and storm rainfall are the major contributors to SEE,which exhibit different spatial patterns and characters in different SSE-SAS types.The HI of SSE-SAS at five stations is no more than medium hazard level,with MSH at return periods of 2-to 4-year level.This study provides a new approach for quantifying multi-hazard SSEs,which offers scientific insights for regional multi-hazard risk reduction and mitigation efforts.展开更多
This study advances the DRASTIC groundwater vulnerability assessment framework by integrating a multi-hazard groundwater index(MHGI)to account for the dynamic impacts of diverse anthropogenic activities and natural fa...This study advances the DRASTIC groundwater vulnerability assessment framework by integrating a multi-hazard groundwater index(MHGI)to account for the dynamic impacts of diverse anthropogenic activities and natural factors on both groundwater quality and quantity.Incorporating factors such as population growth,agricultural practices,and groundwater extraction enhances the framework’s ability to capture multi-dimensional,spatiotemporal changes in groundwater vulnerability.Additional improvements include refined weighting and rating scales for thematic layers based on available observational data,and the inclusion of distributed recharge.We demonstrate the practical utility of this dynamic DRASTIC-based framework through its application to the agro-urban regions of the Irrigated Indus Basin,a major groundwater-dependent agricultural area in South Asia.Results indicate that between 2005 and 2020,54%of the study area became highly vulnerable to pollution.The MHGI revealed a 13%decline in potential groundwater storage and a 25%increase in groundwater-stressed zones,driven primarily by population growth and intensive agriculture.Groundwater vulnerability based on both groundwater quality and quantity dimensions showed a 19%decline in areas of low to very low vulnerability and a 6%reduction in medium vulnerability zones by 2020.Sensitivity analyses indicated that groundwater vulnerability in the region is most influenced by groundwater recharge(42%)and renewable groundwater stress(38%).Validation with in-situ data yielded area under the curve values of 0.71 for groundwater quality vulnerability and 0.63 for MHGI.The framework provides valuable insights to guide sustainable groundwater management,safeguarding both environmental integrity and human well-being.展开更多
Economic losses and catastrophic casualties may occur once super high-rise structures are struck by low-probability but high-consequence scenarios of concurrent earthquakes and winds. Therefore, accurately predicting ...Economic losses and catastrophic casualties may occur once super high-rise structures are struck by low-probability but high-consequence scenarios of concurrent earthquakes and winds. Therefore, accurately predicting multi-hazard dynamic responses to super high-rise structures has significant engineering and scientific value. This study performed a parametric global sensitivity analysis (GSA) for multi-hazard dynamic response prediction of super high-rise structures using the multiple-degree-of-freedom shear (MFS) model. Polynomial chaos Kriging (PCK) was introduced to build a surrogate model that allowed GSA to be combined with Sobol’ indices. Monte Carlo simulation (MCS) is also conducted for the comparison to verify the accuracy and efficiency of the PCK method. Parametric sensitivity analysis is performed for a wide range of aleatory uncertainty (intensities of coupled multi-hazard), epistemic uncertainty (bending stiffness, k_(m);shear stiffness, kq;density, ρ;and damping ratio, ξ), probability distribution types, and coefficients of variation. The results indicate that epistemic uncertainty parameters, k_(m), ρ, and ξ dramatically affect the multi-hazard dynamic responses of super high-rise structures;in addition, Sobol’ indices between the normal and lognormal distributions are insignificant, while the variation levels have remarkably influenced the sensitivity indices.展开更多
The increasing frequency and intensity of natural disasters necessitate advanced prediction techniques to mitigate potential damage.This study presents a comprehensive multi-hazard early warning framework by integrati...The increasing frequency and intensity of natural disasters necessitate advanced prediction techniques to mitigate potential damage.This study presents a comprehensive multi-hazard early warning framework by integrating the multi-source data fusion technique.A multi-source data extraction method was introduced by extracting pressure level and average precipitation data based on the hazard event from the Cooperative Open Online Landslide Repository(COOLR)dataset across multiple temporal intervals(12 h to 1 h prior to events).Feature engineering was performed using Choquet fuzzy integral-based importance scoring,which enables the model to account for interactions and uncertainty across multiple features.Three individual Long Short-Term Memory(LSTM)models were trained for hazard location,average precipitation,and hazard category(i.e.,to detect the potential of natural disasters).These models were trained on varying temporal scales from 12 to 1 h prior to the event.These individual models achieved the performance of Mean Absolute Error(MAE)2.2 and 3.2,respectively,for the hazard location and average precipitation models,and an F1-score of 0.825 for the hazard category model.The results also indicate that the LSTM model outperformed traditional Machine Learning(ML)models,and the use of the fuzzy integral enhanced the prediction capability by 8.12%,2.6%,and 6.37%,respectively,for all three individual models.Furthermore,a rule-based algorithm was developed to synthesize the outputs from the individual models into a 3×3 grid of multi-hazard warnings.These findings underscore the effectiveness of the proposed framework in advancing multi-hazard forecasting and situational awareness,offering valuable support for timely and data-driven emergency response planning.展开更多
基金partially supported by the Zhejiang Provincial Natural Science Foundation of China(No.LY16F020010)the Zhejiang Key Discipline Fund of Computer Applied Technology(No.pd2013457)the Hangzhou Science&Technology Development Project of China(No.20140533B13)
文摘With the rapid development of mobile Internet, people pay increasing attention to the wireless network security problem. But due to the specificity of the wireless network, at present it is rare to see the research of wireless intrusion alerts clustering method for mobile Internet. This paper proposes a Wireless Intrusion Alert Clustering Method(WIACM) based on the information of the mobile terminal. The method includes alert formatting, alert reduction and alert classification. By introducing key information of the mobile terminal device, this method aggregates the original alerts into hyper alerts. The experimental results show that WIACM would be appropriate for real attack scenarios of mobile Internet, and reduce the amount of alerts with more accuracy of alert analysis.
文摘Back of queue crashes on Interstates are a major concern for all state transportation departments. In 2020, Indiana DOT begin deploying queue warning trucks with message boards, flashers and digital alerts that could be transmitted to navigation systems such as Waze. This study reports on the deployment and impact evaluation of digital alerts on motorist’s assistance patrols and 19 Queue trucks in Indiana. The motorist assistance patrol evaluation is provided qualitatively. A novel analysis of queue warning trucks equipped with digital alerts was conducted during the months of May-July in 2021 using connected vehicle data. This new data set reports locations of anonymous hard-braking events from connected vehicles on the Interstate. Hard-braking events were tabulated for when queueing occurred with and without the presence of a queue warning truck. Approximately 370 hours of queueing with queue trucks present and 58 hours of queueing without queue truck<span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> present were evaluated. Hard-braking events were found to decrease approximately 80% when queue warning trucks were used to alert motorists of impending queues.</span>
文摘To solve the problem of the aleri flooding and information semantics in theexisting Intrusion Detection Sys-tem(IDS), we present a two-stage algorithm for correlating thealerts. In the first stage- the high-level alerts is integrated by using the Chronicle patternsbased on time intervals, which describe and match the alerts with the temporal time constrains of aninput sequence. In the second stage, the preparing relationship between the high-level alerts isdefined, which is applied to eorrtlatethe high-level alerts, and the attack scenario is constructedby drawing the attack graph. In the end a given example show? the performances of this two-stagecorrelation algorithm in decreasing the number and improving the information semantic of theintrusion alerts produced by the IDS.
文摘Warning alerts are specially designed to protect user rights and safety to avoid serious damage caused by overlooking the essence of warning alerts. Today’s world of Information Communication Technology (ICT) needs improvement and to review the decisions of security experts in terms of improving warning designs and dialogues, and timely inform the authorities to take quick action at the right time and choice. Human behaviour is deeply involved in most of the security failures and its poor response. If we are able to check and monitor human behaviour in any organisation, we can achieve quality assurance and provide best services to our customers. We have arranged a study in the Center of Post Graduate Studies, International Islamic University, Malaysia (CPS-IIUM), department of Hajj Services-Makkah, and Hospital Management System-Makkah comprised of Observation, Interviews, Questionnaire and discussion based on organizational structure and job activities of people involved in different scenarios and positions under one umbrella of organizational objectives in order to trap the human error in order to take rapid action and response from the management team. Human behaviour is deeply observed and checked while performing different job activities in order to identify the serious errors at the right time during job performance at various levels. We have applied the concept of Brahm’s Language for the simulation of human behaviour which proves an opportunity to simulate human behaviour while performing job activities. Customer service can be improved easily if necessary measures and decisions are taken at the right time and place in any organisation.
文摘In-cab alerts warn commercial vehicle drivers of upcoming roadway incidents, slowdowns and work zone construction activities. This paper reports on a study evaluating the driver response to in-cab alerts in Ohio. Driver response was evaluated by measuring the statistical trends of vehicle speeds after the in-cab alerts were received. Vehicle speeds pre and post in-cab alert were collected over a 47 day period in the fall of 2023 for trucks traveling on interstate roadways in Ohio. Results show that approximately 22% of drivers receiving Dangerous Slowdown alerts had reduced their speeds by at least 5 mph 30 seconds after receiving such an alert. Segmenting this analysis by speed found that of vehicles traveling at or above 70 mph at the time of alerting, 26% reduced speeds by at least 5 mph. These speed reductions suggest drivers taking actional measures after receiving alerts. Future studies will involve further analysis on the impact of the types of alerts shown, roadway characteristics and overall traffic conditions on truck speeds passing through work zones.
基金support from the National Natural Science Foundation of China(U20A20112,42061160480,42377196,and 52479095)the NSFC/RGC Joint Research Scheme(42061160480 and N_HKUST620/20)+1 种基金the Research Grants Council of the Hong Kong SAR Government(16203720,T22-606/23-R,and JRFS25266S09)the Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone(HZQB-KCZYB-2020083)。
文摘A glacier hazard chain can form a long-runout mass flow and generate a large flood,affecting downstream areas hundreds of kilometers away from the initiating hazard site.This study focuses on the Yarlung Zangbo Daxiagu.The objective is to address two key unresolved issues:the evolution of detached glacier materials into debris flows or debris floods and the amplification of the impact range and threats.A comprehensive framework is developed that considers the impacts of near-field and far-field hazards.Numerical modeling,remote sensing,and field investigations were integrated to understand the interactions,transformations,and amplifications of hazards in the glacier hazard chain.The results indicate that extensive,nearly saturated sediments on the glacier valley floor,when entrained,amplify the magnitude of the mass flow.The topography plays a crucial role.When the valley outlet is perpendicular to the river course,topographic obstacles cause immediate halting,resulting in the formation of high barrier dams.Conversely,when the glacier valley aligns nearly parallel to the river course,the mass flow can travel a much longer distance upon entering the river,causing an enlarged affected area.The barrier dams can breach rapidly,causing breaching floods that amplify the downstream impact from several kilometers to hundreds of kilometers.Our analysis reveals that the overall impacts remain spatially limited.Specifically,downstream areas along the Yarlung Zangbo-Brahmaputra River are unlikely to face greater threats from the upstream floods than local monsoon floods.Our findings provide the foundation for the management of glacier hazard chains.
基金supported by the Key Laboratory of Coastal Science and Integrated Management,Ministry of Natural Resources(No.2022COSIMQ002)the Shandong Provincial Social Science Planning Research Project(No.22CXSXJ15)+1 种基金the Guangxi Key Laboratory of Marine Environmental Science,Guangxi Academy of Sciences(No.GXKLHY21-04)the Hainan Province Marxism Project General Program(No.2023HNMGC03).
文摘Storm surge events(SSEs)involve multiple hazard-causing factors,such as surges,extreme rainfall,strong winds,waves,and ocean currents,which have destructive impacts on coastal regions.For a quantitative multi-hazard assessment of SSEs,this study introduced the concept of the storm surge event seawater-atmosphere system(SSE-SAS)and proposed the system energy equivalence(SEE)model from a systemic energy perspective.SEE was obtained by employing a parameterization approach,and the hazard index(HI)and the concept of most significant hazard(MSH)were adopted to evaluate the severity of SSE-SAS.SEE at five stations in the Shandong Peninsula was calculated from 2005 to 2019,and probability analysis and hazard assessment were further conducted.Results show that the SEE of SSE-SAS ranges from 0.029×10^(3) to 30.418×10^(3) J/m^(2),and it exhibits an insignificant decreasing trend from 2005 to 2019.The SEE of SSE-SAS in the west of the Shandong Peninsula is greater than that in the east.Moreover,storm waves,storm surges,and storm rainfall are the major contributors to SEE,which exhibit different spatial patterns and characters in different SSE-SAS types.The HI of SSE-SAS at five stations is no more than medium hazard level,with MSH at return periods of 2-to 4-year level.This study provides a new approach for quantifying multi-hazard SSEs,which offers scientific insights for regional multi-hazard risk reduction and mitigation efforts.
基金funding from the National Science Foundation(NSF Award 2114701)of the United States.
文摘This study advances the DRASTIC groundwater vulnerability assessment framework by integrating a multi-hazard groundwater index(MHGI)to account for the dynamic impacts of diverse anthropogenic activities and natural factors on both groundwater quality and quantity.Incorporating factors such as population growth,agricultural practices,and groundwater extraction enhances the framework’s ability to capture multi-dimensional,spatiotemporal changes in groundwater vulnerability.Additional improvements include refined weighting and rating scales for thematic layers based on available observational data,and the inclusion of distributed recharge.We demonstrate the practical utility of this dynamic DRASTIC-based framework through its application to the agro-urban regions of the Irrigated Indus Basin,a major groundwater-dependent agricultural area in South Asia.Results indicate that between 2005 and 2020,54%of the study area became highly vulnerable to pollution.The MHGI revealed a 13%decline in potential groundwater storage and a 25%increase in groundwater-stressed zones,driven primarily by population growth and intensive agriculture.Groundwater vulnerability based on both groundwater quality and quantity dimensions showed a 19%decline in areas of low to very low vulnerability and a 6%reduction in medium vulnerability zones by 2020.Sensitivity analyses indicated that groundwater vulnerability in the region is most influenced by groundwater recharge(42%)and renewable groundwater stress(38%).Validation with in-situ data yielded area under the curve values of 0.71 for groundwater quality vulnerability and 0.63 for MHGI.The framework provides valuable insights to guide sustainable groundwater management,safeguarding both environmental integrity and human well-being.
基金Dalian Municipal Natural Science Foundation under Grant No.2019RD01。
文摘Economic losses and catastrophic casualties may occur once super high-rise structures are struck by low-probability but high-consequence scenarios of concurrent earthquakes and winds. Therefore, accurately predicting multi-hazard dynamic responses to super high-rise structures has significant engineering and scientific value. This study performed a parametric global sensitivity analysis (GSA) for multi-hazard dynamic response prediction of super high-rise structures using the multiple-degree-of-freedom shear (MFS) model. Polynomial chaos Kriging (PCK) was introduced to build a surrogate model that allowed GSA to be combined with Sobol’ indices. Monte Carlo simulation (MCS) is also conducted for the comparison to verify the accuracy and efficiency of the PCK method. Parametric sensitivity analysis is performed for a wide range of aleatory uncertainty (intensities of coupled multi-hazard), epistemic uncertainty (bending stiffness, k_(m);shear stiffness, kq;density, ρ;and damping ratio, ξ), probability distribution types, and coefficients of variation. The results indicate that epistemic uncertainty parameters, k_(m), ρ, and ξ dramatically affect the multi-hazard dynamic responses of super high-rise structures;in addition, Sobol’ indices between the normal and lognormal distributions are insignificant, while the variation levels have remarkably influenced the sensitivity indices.
文摘The increasing frequency and intensity of natural disasters necessitate advanced prediction techniques to mitigate potential damage.This study presents a comprehensive multi-hazard early warning framework by integrating the multi-source data fusion technique.A multi-source data extraction method was introduced by extracting pressure level and average precipitation data based on the hazard event from the Cooperative Open Online Landslide Repository(COOLR)dataset across multiple temporal intervals(12 h to 1 h prior to events).Feature engineering was performed using Choquet fuzzy integral-based importance scoring,which enables the model to account for interactions and uncertainty across multiple features.Three individual Long Short-Term Memory(LSTM)models were trained for hazard location,average precipitation,and hazard category(i.e.,to detect the potential of natural disasters).These models were trained on varying temporal scales from 12 to 1 h prior to the event.These individual models achieved the performance of Mean Absolute Error(MAE)2.2 and 3.2,respectively,for the hazard location and average precipitation models,and an F1-score of 0.825 for the hazard category model.The results also indicate that the LSTM model outperformed traditional Machine Learning(ML)models,and the use of the fuzzy integral enhanced the prediction capability by 8.12%,2.6%,and 6.37%,respectively,for all three individual models.Furthermore,a rule-based algorithm was developed to synthesize the outputs from the individual models into a 3×3 grid of multi-hazard warnings.These findings underscore the effectiveness of the proposed framework in advancing multi-hazard forecasting and situational awareness,offering valuable support for timely and data-driven emergency response planning.
