Tunnels are vital in connecting crucial transportation hubs as transportation infrastructure evolves.Variations in tunnel design standards and driving conditions across different levels directly impact driver visual p...Tunnels are vital in connecting crucial transportation hubs as transportation infrastructure evolves.Variations in tunnel design standards and driving conditions across different levels directly impact driver visual perception and traffic safety.This study employs a Gaussian hybrid clustering machine learning model to explore driver gaze patterns in highway tunnels and exits.By utilizing contour coefficients,the optimal number of classification clusters is determined.Analysis of driver visual behavior across tunnel levels,focusing on gaze point distribution,gaze duration,and sweep speed,was conducted.Findings indicate freeway tunnel exits exhibit three distinct fixation point categories aligning with Gaussian distribution,while highway tunnels display four such characteristics.Notably,in both tunnel types,65%of driver gaze is concentrated on the near area ahead of their lane.Differences emerge in highway tunnels due to oncoming traffic,leading to 13.47%more fixation points and 0.9%increased fixation time in the right lane compared to regular highway tunnel conditions.Moreover,scanning speeds predominantly fall within the 0.25-0.3 range,accounting for 75.47%and 31.14%of the total sweep speed.展开更多
Facing the high demand for faster and heavier freight trains in Australia,researchers and practitioners are endeavouring to develop more innovative and resilient ballasted tracks.In recent years,many studies have been...Facing the high demand for faster and heavier freight trains in Australia,researchers and practitioners are endeavouring to develop more innovative and resilient ballasted tracks.In recent years,many studies have been conducted by the researchers from Transport Research Centre at the University of Technology Sydney(TRC-UTS)to examine the feasibility of incorporating recycled tyre/rubber into rail tracks.This paper reviews three innovative applications using recycled rubber products such as(1)a synthetic energy-absorbing layer for railway subballast using a composite of rubber crumbs and mining byproducts,(2)using rubber intermixed ballast stratum to replace conventional ballast,and(3)installing recycled rubber mat to mitigate ballast degradation under the impact loading.Comprehensive laboratory and field tests as well as numerical modelling have been conducted to examine the performance of rail tracks incorporating these innovative inclusions.The laboratory and field test results and numerical modelling reveal that incorporating these rubber products could increase the energy-absorbing capacity of the track,and mitigate the ballast breakage and settlement significantly,hence increasing the track stability.The research outcomes will facilitate a better understanding of the performance of ballast tracks incorporating these resilient waste tyre materials while promoting more economical and environmentally sustainable tracks for greater passenger comfort and increased safety.展开更多
To propel the application of a bottom-hinged flap breakwater in real sea conditions,a two-dimensional computational fluid dynamics numerical model was conducted to investigate the pitching motion response and wave att...To propel the application of a bottom-hinged flap breakwater in real sea conditions,a two-dimensional computational fluid dynamics numerical model was conducted to investigate the pitching motion response and wave attenuation in random waves.First,the flow velocity distribution characteristic of the pitching flap at typical times was summarized.Then,the effects of random wave and flap parameters on the flap’s significant pitching angle amplitude θ_(s) and hydrodynamic coefficients were investigated.The results reveal that θ_(s) and wave reflection coefficient K_(r) values increase with increasing significant wave height Hs,random wave steepnessλs,and flap relative height.As Hs andλs increase,the wave transmission coefficient K_(t) increases while the wave dissipation coefficient K_(d) decreases.Additionally,K_(t) decreases with increasing flap relative height.With increasing equivalent damping coefficient ratio,θ_(s) and K_(t) decrease,while K_(r) and K_(d) increase.The relationships betweenλs and flap relative height on the one hand andθ_(s),K_(r),K_(t),and K_(d) in random waves on the other hand are compared to those in regular waves.Based on the equal incident wave energy and the equal incident wave energy flux,the pitching flap performs better in the wave attenuation capability under random waves than in regular waves.Finally,the dimensionless parameters with respect to random wave and flap were used to derive the K_(r) and K_(t) for-mulae,which were validated with the related data.展开更多
This paper presents a method for fabricating a low-cost,highly reproducible miniature optical fiber Fabry-Perot(FP)sensor based on a polydimethylsiloxane(PDMS)end-cap structure.The FP cavity end-cap is formed by the o...This paper presents a method for fabricating a low-cost,highly reproducible miniature optical fiber Fabry-Perot(FP)sensor based on a polydimethylsiloxane(PDMS)end-cap structure.The FP cavity end-cap is formed by the optical fiber end-face and a PDMS droplet deposited onto it.The PDMS deposition is achieved by immersing the fiber end into pre-cured PDMS at a fixed speed,a process requiring careful control of PDMS viscosity and surface tension.By leveraging PDMS’s excellent thermal expansion coefficient,Poisson’s ratio,and other parameters,this method achieves high reproducibility via viscosity-optimized pre-curing,enhanced sensitivity for temperature measurements,and significant cost reduction versus commercial counterparts.Fiber FP sensors are increasingly widely used in biomedical and precision detection fields owing to their significant advantages,including small size,light weight,high sensitivity,and immunity to electromagnetic interference.In the fabrication of fiber FP sensors,using polymer materials is an effective technical approach.These polymers can be applied as coatings on the optical fiber end-face or as interlayer materials embedded between fibers to form the FP cavity structure,which not only significantly improves the overall sensor performance,but also enhances its sensitivity to changes in temperature,pressure,and refractive index.In the final part of this study,we successfully validated the exceptional performance of the PDMS end-cap based fiber FP sensor in detecting different temperatures conditions.Experimental results demonstrate a temperature sensitivity of 0.752 nm/℃for sensors with a 60-μm PDMS end-cap,further confirming the sensor’s reliability and efficiency in practical applications.展开更多
By analyzing the bus operation environment and accounting for prediction uncertainties,a bus arrival interval prediction model was developed utilizing a gated recur-rent unit(GRU)neural network.To reduce the impact of...By analyzing the bus operation environment and accounting for prediction uncertainties,a bus arrival interval prediction model was developed utilizing a gated recur-rent unit(GRU)neural network.To reduce the impact of irrelevant data and boost prediction accuracy,an attention mechanism was integrated into the point model to concen-trate on important input sequence information.Based on the point predictions,the lower upper bound estimation(LUBE)method was used,providing a range for the bus interval times predicted by the model.The model was vali-dated using data from 169 bus routes in Nanchang,Jiangxi Province.The results indicated that the attention-GRU model outperformed neural network,long short-term memory and GRU models.Compared with the Bootstrap method,the LUBE method has a narrower average interval width.The coverage width-based criterion(CWC)was reduced by 8.1%,2.2%,and 5.7%at confidence levels of 85%,90%,and 95%,respectively,during the off-peak period,and by 23.2%,26.9%,and 27.3%at confidence levels of 85%,90%,and 95%,respectively,during the peak period.Therefore,it can accurately describe the fluctuation range in bus arrival times with higher accuracy and stability.展开更多
To investigate the response of Roadside Monitoring Stations(RSs)to traffic-related air pollution,traffic and pollutant characteristics,influencing factors,and potential source characterization in Tianjin,China were de...To investigate the response of Roadside Monitoring Stations(RSs)to traffic-related air pollution,traffic and pollutant characteristics,influencing factors,and potential source characterization in Tianjin,China were determined based on roadside monitoring of real-world data conducted at RSs in 2022.The diurnal variation trend of pollutants at RSs was consistent with that at the National Monitoring Station(NM),with notably higher pollutant fluctuations during the morning and evening peak traffic times at RSs,where the average diurnal concentration was 41.46%higher than that at the NM.The generalized additive model(GAM)for nitrogen oxides(NO_(x))and carbon monoxide(CO),responding to themultiple influencing factors,performed well at RSs,with deviance explained by 86.6%and 61.4%,respectively.The synergistic effects of wind direction and speed contributed to most of the variations in NO_(x) and CO,which were 14.74%and 12.87%,respectively.Pollutant concentrations were highest under windless conditions,with pollutants originating primarily from local vehicle emissions.The model results indicated that medium-duty truck(MDT)traffic flow predominantly contributed to the variability in NO_(x) emissions,whereas passenger car(PC)traffic flow was the primary source of CO emissions from traffic variables.MDTs should be the focus of urban NO_(x) traffic emissions control.Potential-source analysis validated the results obtained from the GAM,and both analyses showed that RSs can better characterize traffic-related air pollutants.Furthermore,more stringent emission standards have effectively mitigated the release of pollutants from motor vehicles and contributed to the modernization of vehicle fleet composition,effectively decreasing CO concentrations.展开更多
Polyethylene glycol(PEG)with different chains was used to modify epoxy asphalt.Molecular models of PEG⁃modified epoxy asphalt were developed using molecu⁃lar simulations(MS).The thermodynamic and mechanical properties...Polyethylene glycol(PEG)with different chains was used to modify epoxy asphalt.Molecular models of PEG⁃modified epoxy asphalt were developed using molecu⁃lar simulations(MS).The thermodynamic and mechanical properties of PEG⁃modified epoxy asphalt were analyzed,and its toughening mechanisms were explored.A method based on the Dijkstra algorithm was proposed to evaluate ep⁃oxy asphalt crosslinked networks.The results show that the introduction of PEG chains into epoxy asphalt can lower the glass transition temperature and enhance its toughness be⁃cause of the extended length of the PEG chains,which can in⁃crease the free volume and improve the mobility of the epoxy resin in the epoxy asphalt.The crosslinked network quantita⁃tive evaluation method based on the Dijkstra algorithm can ef⁃fectively evaluate the distribution of epoxy asphalt crosslink⁃ing bonds,providing further explanation of the toughening mechanism of PEG⁃modified epoxy asphalt.The feasibility of designing and screening epoxy asphalt materials by MS is verified,and a guide for toughening mechanism research of epoxy asphalt at the molecular level is provided.展开更多
Within the domain of low-level vision,enhancing low-light images and removing sand-dust from single images are both critical tasks.These challenges are particularly pronounced in real-world applications such as autono...Within the domain of low-level vision,enhancing low-light images and removing sand-dust from single images are both critical tasks.These challenges are particularly pronounced in real-world applications such as autonomous driving,surveillance systems,and remote sensing,where adverse lighting and environmental conditions often degrade image quality.Various neural network models,including MLPs,CNNs,GANs,and Transformers,have been proposed to tackle these challenges,with the Vision KAN models showing particular promise.However,existing models,including the Vision KAN models use deterministic neural networks that do not address the uncertainties inherent in these processes.To overcome this,we introduce the Uncertainty-Aware Kolmogorov-Arnold Network(UAKAN),a novel structure that integrates KAN with uncertainty estimation.Our approach uniquely employs Tokenized KANs for sampling within a U-Net architecture’s encoder and decoder layers,enhancing the network’s ability to learn complex representations.Furthermore,for aleatoric uncertainty,we propose an uncertainty coupling certainty module that couples uncertainty distribution learning and residual learning in a feature fusion manner.For epistemic uncertainty,we propose a feature selection mechanism for spatial and pixel dimension uncertainty modeling,which captures and models uncertainty by learning the uncertainty contained between feature maps.Notably,our uncertainty-aware framework enables the model to produce both high-quality enhanced images and reliable uncertainty maps,which are crucial for downstream applications requiring confidence estimation.Through comparative and ablation studies on our synthetic SLLIE6K dataset,designed for low-light enhancement and sand-dust removal,we validate the effectiveness and theoretical robustness of our methodology.展开更多
With the development of wireless communication,the fifth generation mobile communication technology(5G)has emerged as a hot topic in highspeed railway communication system and has moved towards industrial application....With the development of wireless communication,the fifth generation mobile communication technology(5G)has emerged as a hot topic in highspeed railway communication system and has moved towards industrial application.Investigating the radio propagation characteristics in 5G high-speed train(HST)scenarios is essential for enhancing wireless coverage and overall system performance.We propose a novel 5G passive sounding scheme to extract channel impulse responses(CIRs)using channel state information reference signals(CSI-RS)from the target 5G base station(BS).Detailed procedures for timefrequency synchronization,CSI-RS detection and extraction are presented through simulations.Through the laboratory work involving absolute power calibration,phase coherence calibration and power delay profile(PDP)validation,we validate the accuracy and performance of the developed platform.Furthermore,a measurement campaign was conducted in HST scenarios encompassing both residential and undeveloped areas.The path loss(PL)model and the channel characteristics including stationarity interval(SI),multipath components(MPCs),shadow fading(SF),Rician K-factor,root mean square(RMS)delay spread and received correlation coefficients are analyzed and fitted.The estimated channel characteristics and the statistical model presented in this paper will contribute to the research on HST radio propagation and the development of 5G railway communication systems.展开更多
With the evolution of next-generation communication networks,ensuring robust Core Network(CN)architecture and data security has become paramount.This paper addresses critical vulnerabilities in the architecture of CN ...With the evolution of next-generation communication networks,ensuring robust Core Network(CN)architecture and data security has become paramount.This paper addresses critical vulnerabilities in the architecture of CN and data security by proposing a novel framework based on blockchain technology that is specifically designed for communication networks.Traditional centralized network architectures are vulnerable to Distributed Denial of Service(DDoS)attacks,particularly in roaming scenarios where there is also a risk of private data leakage,which imposes significant operational demands.To address these issues,we introduce the Blockchain-Enhanced Core Network Architecture(BECNA)and the Secure Decentralized Identity Authentication Scheme(SDIDAS).The BECNA utilizes blockchain technology to decentralize data storage,enhancing network security,stability,and reliability by mitigating Single Points of Failure(SPoF).The SDIDAS utilizes Decentralized Identity(DID)technology to secure user identity data and streamline authentication in roaming scenarios,significantly reducing the risk of data breaches during cross-network transmissions.Our framework employs Ethereum,free5GC,Wireshark,and UERANSIM tools to create a robust,tamper-evident system model.A comprehensive security analysis confirms substantial improvements in user privacy and network security.Simulation results indicate that our approach enhances communication CNs security and reliability,while also ensuring data security.展开更多
Substantial effects of photochemical reaction losses of volatile organic compounds(VOCs)on factor profiles can be investigated by comparing the differences between daytime and nighttime dispersion-normalized VOC data ...Substantial effects of photochemical reaction losses of volatile organic compounds(VOCs)on factor profiles can be investigated by comparing the differences between daytime and nighttime dispersion-normalized VOC data resolved profiles.Hourly speciated VOC data measured in Shijiazhuang,China from May to September 2021 were used to conduct study.The mean VOC concentration in the daytime and at nighttime were 32.8 and 36.0 ppbv,respectively.Alkanes and aromatics concentrations in the daytime(12.9 and 3.08 ppbv)were lower than nighttime(15.5 and 3.63 ppbv),whereas that of alkenes showed the opposite tendency.The concentration differences between daytime and nighttime for alkynes and halogenated hydrocarbonswere uniformly small.The reactivities of the dominant species in factor profiles for gasoline emissions,natural gas and diesel vehicles,and liquefied petroleum gas were relatively low and their profiles were less affected by photochemical losses.Photochemical losses produced a substantial impact on the profiles of solvent use,petrochemical industry emissions,combustion sources,and biogenic emissions where the dominant species in these factor profiles had high reactivities.Although the profile of biogenic emissions was substantially affected by photochemical loss of isoprene,the low emissions at nighttime also had an important impact on its profile.Chemical losses of highly active VOC species substantially reduced their concentrations in apportioned factor profiles.This study results were consistent with the analytical results obtained through initial concentration estimation,suggesting that the initial concentration estimation could be the most effective currently availablemethod for the source analyses of active VOCs although with uncertainty.展开更多
Serious fine particulate matter(PM_(2.5))pollution and rapidly increasing of ground-level ozone(O_(3))concentrations are concern issues in China.To achieve the comprehensive control of PM_(2.5)-O_(3) composite air pol...Serious fine particulate matter(PM_(2.5))pollution and rapidly increasing of ground-level ozone(O_(3))concentrations are concern issues in China.To achieve the comprehensive control of PM_(2.5)-O_(3) composite air pollution,exploring the common sources of PM_(2.5) and VOCs is essential.However,previous researches most carried out either PM_(2.5) or VOCs source appointment.In this study,we applied the ensemble source apportionment method to explore the impacts of common sources on PM_(2.5)-VOCs.Subsequently,we obtained the ensemble source impacts on O_(3) combining the extracted VOCs source profile and ozone formation potential.We found that the focus of environmentalmanagement and source control should be varied accordingly for different pollutants.Vehicle emission was the largest contributor(41%)to PM_(2.5)-VOCs,while industrial emission was the main common source(51%)to O_(3).The result showed that the O_(3) production rate is not only related to the VOCs emission,but also to the reactivity of VOCs.In addition,sensitivity tests revealed that temperature was the main factor affecting O_(3) formation.The study provides a framework to explore the common sources impact on PM_(2.5) and VOCs,which is benefit to address both PM_(2.5) and O_(3) mitigations.展开更多
Traffic congestion is widely distributed around a network. Generally, to analyze traffic congestion, static traffic capacity is adopted. But dynamic characteristics must be studied because congestion is a dynamic proc...Traffic congestion is widely distributed around a network. Generally, to analyze traffic congestion, static traffic capacity is adopted. But dynamic characteristics must be studied because congestion is a dynamic process. A Dynamic Traffic Assignment modeling fundamental combined with an urban congestion analysis method is studied in this paper. Three methods are based on congestion analysis, and the stochastic user optimal DTA models are especially considered. Correspondingly, a dynamic system optimal model is suggested for responding congestion countermeasures and an ideal user optimal model for predicted congestion countermeasure respectively.展开更多
The current method of evaluating passenger satisfaction primarily adopts the traditional static evaluation mode,which can hardly satisfy the dynamic regulatory requirements of highway passenger transport service quali...The current method of evaluating passenger satisfaction primarily adopts the traditional static evaluation mode,which can hardly satisfy the dynamic regulatory requirements of highway passenger transport service quality set by industry management departments.In this paper,we summarize the characteristics of real-time dynamic evaluation under the requirements of hierarchical and classified evaluation and analyze the entire process of the one-time travel service of highway passenger transport.We focus on station waiting and in-vehicle services,extract the elements most concerned by passengers as evaluation indexes,and construct a three-level index system.Subsequently,a multi-indicator comprehensive evaluation method based on the analytic hierarchy process and fuzzy comprehensive evaluation is selected to construct a comprehensive evaluation model.By combining with the development level of electronic ticket purchasing and the requirements of satisfaction evaluation,we propose three data collection methods and compare and analyze their strengths and weaknesses.Finally,based on actual survey data,the effectiveness of the model is verified.The verification results show that the real-time dynamic evaluation index system based on the Internet can better satisfy evaluation requirements.展开更多
Multi-pylon multi-span suspension bridge is a new type super flexible structure system, and the rigidity design of middle pylon is one of the main difficult technical issues. Due to the requirements of longitudinal ri...Multi-pylon multi-span suspension bridge is a new type super flexible structure system, and the rigidity design of middle pylon is one of the main difficult technical issues. Due to the requirements of longitudinal rigidity, the structural form and the corresponding foundation type of middle pylon are different from those of the ordinary steel pylon, and the complicated dynamic characteristics make the calculation quite difficult. In this article, exploration has been made in selection of similarity ratio and model materials, section simulation, restriction conditions simulation, fixing of mass blocks, fabrication scheme and testing method by taking into account different construction and working conditions such as restriction conditions and working environment of a three-pylon suspension bridge, to conduct the test experimental design of the dynamic behavior of the middle pylon, with the purpose to reveal its dynamic characteristics and make comparison and analysis with theoretical assumptions, to provide basis for anti-wind and anti-seismic design and reference for the design and research of three-pylon two-span suspension bridges in the future.展开更多
To enhance the serviceability of steel bridge deck pavement(SBDP)in high-temperature and rainy regions,a concept of rigid bottom and flexible top was summarized using engineering practices,which led to the proposal of...To enhance the serviceability of steel bridge deck pavement(SBDP)in high-temperature and rainy regions,a concept of rigid bottom and flexible top was summarized using engineering practices,which led to the proposal of a three-layer ultra-high-performance pavement(UHPP).The high-temperature rutting resistance and wet-weather skid resistance of UHPP were evaluated through composite structure tests.The internal temperature distribution within the pavement under typical high-temperature conditions was analyzed using a temperature field model.Additionally,a temperature-stress coupling model was employed to investigate the key load positions and stress response characteristics of the UHPP.The results indicate that compared with the traditional guss asphalt+stone mastic asphalt structure,the dynamic stability of the UHPP composite structure can be improved by up to 20.4%.Even under cyclic loading,UHPP still exhibits superior surface skid resistance compared to two traditional SBDPs.The thickness composition of UHPP significantly impacts its rutting resistance and skid resistance.UHPP exhibits relatively low tensile stress but higher shear stress levels,with the highest shear stress occurring between the UHPP and the steel plate.This suggests that the potential risk of damage for UHPP primarily lies within the interlayer of the pavement.Based on engineering examples,introducing interlayer gravel and optimizing the amount of bonding layer are advised to ensure that UHPP possesses sufficient interlayer shear resistance.展开更多
When encountering the distribution shift between the source(training) and target(test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain ada...When encountering the distribution shift between the source(training) and target(test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain adaptation research has achieved a lot of success both in theory and practice under the assumption that all the examples in the source domain are welllabeled and of high quality. However, the methods consistently lose robustness in noisy settings where data from the source domain have corrupted labels or features which is common in reality. Therefore, robust domain adaptation has been introduced to deal with such problems. In this paper, we attempt to solve two interrelated problems with robust domain adaptation:distribution shift across domains and sample noises of the source domain. To disentangle these challenges, an optimal transport approach with low-rank constraints is applied to guide the domain adaptation model training process to avoid noisy information influence. For the domain shift problem, the optimal transport mechanism can learn the joint data representations between the source and target domains using a measurement of discrepancy and preserve the discriminative information. The rank constraint on the transport matrix can help recover the corrupted subspace structures and eliminate the noise to some extent when dealing with corrupted source data. The solution to this relaxed and regularized optimal transport framework is a convex optimization problem that can be solved using the Augmented Lagrange Multiplier method, whose convergence can be mathematically proved. The effectiveness of the proposed method is evaluated through extensive experiments on both synthetic and real-world datasets.展开更多
A study was conducted to analyze the deformation mechanism of strongly weathered quartz schist in the Daliangshan Tunnel,located in the western Transverse Mountain area.A large deformation problem was experienced duri...A study was conducted to analyze the deformation mechanism of strongly weathered quartz schist in the Daliangshan Tunnel,located in the western Transverse Mountain area.A large deformation problem was experienced during the tunnel construction.To mitigate this problem,a support system was designed incorporating negative Poisson ratio(NPR)anchor cables with negative Poisson ratio effect.Physical model experiments,field experiments,and numerical simulation experiments were conducted to investigate the compensation mechanical behavior of NPR anchor cables.The large deformations of soft rocks in the Daliangshan Tunnel are caused by a high ground stress,a high degree of joint fracture development,and a high degree of surrounding rock fragmentation.A compensation mechanics support system combining long and short NPR anchor cables was suggested to provide sufficient counter-support force(approximately 350 kN)for the surrounding rock inside the tunnel.Comparing the NPR anchor cable support system with the original support system used in the Daliangshan tunnel showed that an NPR anchor cable support system,combining cables of 6.3 m and 10.3 m in length,effectively prevented convergence of surrounding rock deformation,and the integrated settlement convergence value remained below 300 mm.This study provides an effective scientific basis for resolving large deformation problems in deeply buried soft rocks in western transverse mountain areas.展开更多
Critical infrastructure systems(CISs)play a key role in the socio-economic activity of a society,but are exposed to an array of disruptive events that can greatly impact their function and performance.Therefore,unders...Critical infrastructure systems(CISs)play a key role in the socio-economic activity of a society,but are exposed to an array of disruptive events that can greatly impact their function and performance.Therefore,understanding the underlying behaviors of CISs and their response to perturbations is needed to better prepare for,and mitigate the impact of,future disruptions.Resilience is one characteristic of CISs that influences the extent and severity of the impact induced by extreme events.Resilience is often dissected into four dimensions:robustness,redundancy,resourcefulness,and rapidity,known as the“4Rs”.This study proposes a framework to assess the resilience of an infrastructure network in terms of these four dimensions under optimal resource allocation strategies and incorporates interdependencies between different CISs,with resilience considered as a stochastic variable.The proposed framework combines an agent-based infrastructure interdependency model,advanced optimization algorithms,Bayesian network techniques,and Monte Carlo simulation to assess the resilience of an infrastructure network.The applicability and flexibility of the proposed framework is demonstrated with a case study using a network of CISs in Austin,Texas,where the resilience of the network is assessed and a“what-if”analysis is performed.展开更多
Urban intersections without traffic signals are prone to accidents involving motor vehicles and pedestrians.Utilizing computer vision technology to detect pedestrians crossing the street can effectively mitigate the o...Urban intersections without traffic signals are prone to accidents involving motor vehicles and pedestrians.Utilizing computer vision technology to detect pedestrians crossing the street can effectively mitigate the occurrence of such accidents.Faced with the complex issue of pedestrian occlusion at signal-free intersections,this paper proposes a target detection model called Head feature And ENMS fusion Residual connection For CNN(HAERC).Specifically,the model includes a head feature module that detects occluded pedestrians by integrating their head features with the overall target.Additionally,to address the misselection caused by overlapping candidate boxes in two-stage target detection models,an Extended Non-Maximum Suppression classifier(ENMS)with expanded IoU thresholds is proposed.Finally,leveraging the CityPersons dataset and categorizing it into four classes based on occlusion levels(heavy,reasonable,partial,bare),the HAERC model is experimented on these classes and compared with baseline models.Experimental results demonstrate that HAERC achieves superior False Positives Per Image(FPPI)values of 46.64%,9.59%,9.43%,and 6.78%respectively for the four classes,outperforming all baseline models.The study concludes that the HAERC model effectively identifies occluded pedestrians in the complex environment of urban intersections without traffic signals,thereby enhancing safety for long-range driving at such intersections.展开更多
基金supported by the National Natural Science Foundation of China(52302437)the Cangzhou Science and Technology Plan Project(213101011)+1 种基金the Science and Technology Program Projects of Shandong Provincial Department of Transportation(2024B28)the Doctoral Scientific Research Start-up Foundation of Shandong University of Technology(422049).
文摘Tunnels are vital in connecting crucial transportation hubs as transportation infrastructure evolves.Variations in tunnel design standards and driving conditions across different levels directly impact driver visual perception and traffic safety.This study employs a Gaussian hybrid clustering machine learning model to explore driver gaze patterns in highway tunnels and exits.By utilizing contour coefficients,the optimal number of classification clusters is determined.Analysis of driver visual behavior across tunnel levels,focusing on gaze point distribution,gaze duration,and sweep speed,was conducted.Findings indicate freeway tunnel exits exhibit three distinct fixation point categories aligning with Gaussian distribution,while highway tunnels display four such characteristics.Notably,in both tunnel types,65%of driver gaze is concentrated on the near area ahead of their lane.Differences emerge in highway tunnels due to oncoming traffic,leading to 13.47%more fixation points and 0.9%increased fixation time in the right lane compared to regular highway tunnel conditions.Moreover,scanning speeds predominantly fall within the 0.25-0.3 range,accounting for 75.47%and 31.14%of the total sweep speed.
基金financial support from the Australian Research Council for ARCLP200200915 and ARCDP220102862financial and technical support from industry partners including Sydney Trains,SMEC Australia Pty.
文摘Facing the high demand for faster and heavier freight trains in Australia,researchers and practitioners are endeavouring to develop more innovative and resilient ballasted tracks.In recent years,many studies have been conducted by the researchers from Transport Research Centre at the University of Technology Sydney(TRC-UTS)to examine the feasibility of incorporating recycled tyre/rubber into rail tracks.This paper reviews three innovative applications using recycled rubber products such as(1)a synthetic energy-absorbing layer for railway subballast using a composite of rubber crumbs and mining byproducts,(2)using rubber intermixed ballast stratum to replace conventional ballast,and(3)installing recycled rubber mat to mitigate ballast degradation under the impact loading.Comprehensive laboratory and field tests as well as numerical modelling have been conducted to examine the performance of rail tracks incorporating these innovative inclusions.The laboratory and field test results and numerical modelling reveal that incorporating these rubber products could increase the energy-absorbing capacity of the track,and mitigate the ballast breakage and settlement significantly,hence increasing the track stability.The research outcomes will facilitate a better understanding of the performance of ballast tracks incorporating these resilient waste tyre materials while promoting more economical and environmentally sustainable tracks for greater passenger comfort and increased safety.
基金supported by the National Natural Science Foundation of China(Nos.52271295,52088102).
文摘To propel the application of a bottom-hinged flap breakwater in real sea conditions,a two-dimensional computational fluid dynamics numerical model was conducted to investigate the pitching motion response and wave attenuation in random waves.First,the flow velocity distribution characteristic of the pitching flap at typical times was summarized.Then,the effects of random wave and flap parameters on the flap’s significant pitching angle amplitude θ_(s) and hydrodynamic coefficients were investigated.The results reveal that θ_(s) and wave reflection coefficient K_(r) values increase with increasing significant wave height Hs,random wave steepnessλs,and flap relative height.As Hs andλs increase,the wave transmission coefficient K_(t) increases while the wave dissipation coefficient K_(d) decreases.Additionally,K_(t) decreases with increasing flap relative height.With increasing equivalent damping coefficient ratio,θ_(s) and K_(t) decrease,while K_(r) and K_(d) increase.The relationships betweenλs and flap relative height on the one hand andθ_(s),K_(r),K_(t),and K_(d) in random waves on the other hand are compared to those in regular waves.Based on the equal incident wave energy and the equal incident wave energy flux,the pitching flap performs better in the wave attenuation capability under random waves than in regular waves.Finally,the dimensionless parameters with respect to random wave and flap were used to derive the K_(r) and K_(t) for-mulae,which were validated with the related data.
文摘This paper presents a method for fabricating a low-cost,highly reproducible miniature optical fiber Fabry-Perot(FP)sensor based on a polydimethylsiloxane(PDMS)end-cap structure.The FP cavity end-cap is formed by the optical fiber end-face and a PDMS droplet deposited onto it.The PDMS deposition is achieved by immersing the fiber end into pre-cured PDMS at a fixed speed,a process requiring careful control of PDMS viscosity and surface tension.By leveraging PDMS’s excellent thermal expansion coefficient,Poisson’s ratio,and other parameters,this method achieves high reproducibility via viscosity-optimized pre-curing,enhanced sensitivity for temperature measurements,and significant cost reduction versus commercial counterparts.Fiber FP sensors are increasingly widely used in biomedical and precision detection fields owing to their significant advantages,including small size,light weight,high sensitivity,and immunity to electromagnetic interference.In the fabrication of fiber FP sensors,using polymer materials is an effective technical approach.These polymers can be applied as coatings on the optical fiber end-face or as interlayer materials embedded between fibers to form the FP cavity structure,which not only significantly improves the overall sensor performance,but also enhances its sensitivity to changes in temperature,pressure,and refractive index.In the final part of this study,we successfully validated the exceptional performance of the PDMS end-cap based fiber FP sensor in detecting different temperatures conditions.Experimental results demonstrate a temperature sensitivity of 0.752 nm/℃for sensors with a 60-μm PDMS end-cap,further confirming the sensor’s reliability and efficiency in practical applications.
基金The National Natural Science Foundation of China(No.52162042)General Science and Technology Project of Jiangxi Provincial Department of Transportation(No.2024YB039).
文摘By analyzing the bus operation environment and accounting for prediction uncertainties,a bus arrival interval prediction model was developed utilizing a gated recur-rent unit(GRU)neural network.To reduce the impact of irrelevant data and boost prediction accuracy,an attention mechanism was integrated into the point model to concen-trate on important input sequence information.Based on the point predictions,the lower upper bound estimation(LUBE)method was used,providing a range for the bus interval times predicted by the model.The model was vali-dated using data from 169 bus routes in Nanchang,Jiangxi Province.The results indicated that the attention-GRU model outperformed neural network,long short-term memory and GRU models.Compared with the Bootstrap method,the LUBE method has a narrower average interval width.The coverage width-based criterion(CWC)was reduced by 8.1%,2.2%,and 5.7%at confidence levels of 85%,90%,and 95%,respectively,during the off-peak period,and by 23.2%,26.9%,and 27.3%at confidence levels of 85%,90%,and 95%,respectively,during the peak period.Therefore,it can accurately describe the fluctuation range in bus arrival times with higher accuracy and stability.
基金supported by the National Key Research and Development Program of China(Nos.2023YFC3707301 and 2023YFC3705400)the Fundamental Research Funds for the Central Universities(Nos.ZB23003425 and 63211075)。
文摘To investigate the response of Roadside Monitoring Stations(RSs)to traffic-related air pollution,traffic and pollutant characteristics,influencing factors,and potential source characterization in Tianjin,China were determined based on roadside monitoring of real-world data conducted at RSs in 2022.The diurnal variation trend of pollutants at RSs was consistent with that at the National Monitoring Station(NM),with notably higher pollutant fluctuations during the morning and evening peak traffic times at RSs,where the average diurnal concentration was 41.46%higher than that at the NM.The generalized additive model(GAM)for nitrogen oxides(NO_(x))and carbon monoxide(CO),responding to themultiple influencing factors,performed well at RSs,with deviance explained by 86.6%and 61.4%,respectively.The synergistic effects of wind direction and speed contributed to most of the variations in NO_(x) and CO,which were 14.74%and 12.87%,respectively.Pollutant concentrations were highest under windless conditions,with pollutants originating primarily from local vehicle emissions.The model results indicated that medium-duty truck(MDT)traffic flow predominantly contributed to the variability in NO_(x) emissions,whereas passenger car(PC)traffic flow was the primary source of CO emissions from traffic variables.MDTs should be the focus of urban NO_(x) traffic emissions control.Potential-source analysis validated the results obtained from the GAM,and both analyses showed that RSs can better characterize traffic-related air pollutants.Furthermore,more stringent emission standards have effectively mitigated the release of pollutants from motor vehicles and contributed to the modernization of vehicle fleet composition,effectively decreasing CO concentrations.
基金The Major Science and Technology Project of Nan⁃jing(No.202209012)the Postgraduate Research and Practice Innova⁃tion Program of Jiangsu Province(No.KYCX22⁃0277).
文摘Polyethylene glycol(PEG)with different chains was used to modify epoxy asphalt.Molecular models of PEG⁃modified epoxy asphalt were developed using molecu⁃lar simulations(MS).The thermodynamic and mechanical properties of PEG⁃modified epoxy asphalt were analyzed,and its toughening mechanisms were explored.A method based on the Dijkstra algorithm was proposed to evaluate ep⁃oxy asphalt crosslinked networks.The results show that the introduction of PEG chains into epoxy asphalt can lower the glass transition temperature and enhance its toughness be⁃cause of the extended length of the PEG chains,which can in⁃crease the free volume and improve the mobility of the epoxy resin in the epoxy asphalt.The crosslinked network quantita⁃tive evaluation method based on the Dijkstra algorithm can ef⁃fectively evaluate the distribution of epoxy asphalt crosslink⁃ing bonds,providing further explanation of the toughening mechanism of PEG⁃modified epoxy asphalt.The feasibility of designing and screening epoxy asphalt materials by MS is verified,and a guide for toughening mechanism research of epoxy asphalt at the molecular level is provided.
基金supported by National Key R&D Program of China(2023YFB2504400).
文摘Within the domain of low-level vision,enhancing low-light images and removing sand-dust from single images are both critical tasks.These challenges are particularly pronounced in real-world applications such as autonomous driving,surveillance systems,and remote sensing,where adverse lighting and environmental conditions often degrade image quality.Various neural network models,including MLPs,CNNs,GANs,and Transformers,have been proposed to tackle these challenges,with the Vision KAN models showing particular promise.However,existing models,including the Vision KAN models use deterministic neural networks that do not address the uncertainties inherent in these processes.To overcome this,we introduce the Uncertainty-Aware Kolmogorov-Arnold Network(UAKAN),a novel structure that integrates KAN with uncertainty estimation.Our approach uniquely employs Tokenized KANs for sampling within a U-Net architecture’s encoder and decoder layers,enhancing the network’s ability to learn complex representations.Furthermore,for aleatoric uncertainty,we propose an uncertainty coupling certainty module that couples uncertainty distribution learning and residual learning in a feature fusion manner.For epistemic uncertainty,we propose a feature selection mechanism for spatial and pixel dimension uncertainty modeling,which captures and models uncertainty by learning the uncertainty contained between feature maps.Notably,our uncertainty-aware framework enables the model to produce both high-quality enhanced images and reliable uncertainty maps,which are crucial for downstream applications requiring confidence estimation.Through comparative and ablation studies on our synthetic SLLIE6K dataset,designed for low-light enhancement and sand-dust removal,we validate the effectiveness and theoretical robustness of our methodology.
基金supported by Fundamental Research Funds for the Central Universities(No.2024YJS078)the National Natural Science Foundation of China(No.62341127,62221001 and 62171021)+1 种基金the Fundamental Research Funds for the Natural Science Foundation of Jiangsu Province,Major Project(No.BK2021200)the Key Research and Development Program of Zhejiang Province(No.2023C01003)。
文摘With the development of wireless communication,the fifth generation mobile communication technology(5G)has emerged as a hot topic in highspeed railway communication system and has moved towards industrial application.Investigating the radio propagation characteristics in 5G high-speed train(HST)scenarios is essential for enhancing wireless coverage and overall system performance.We propose a novel 5G passive sounding scheme to extract channel impulse responses(CIRs)using channel state information reference signals(CSI-RS)from the target 5G base station(BS).Detailed procedures for timefrequency synchronization,CSI-RS detection and extraction are presented through simulations.Through the laboratory work involving absolute power calibration,phase coherence calibration and power delay profile(PDP)validation,we validate the accuracy and performance of the developed platform.Furthermore,a measurement campaign was conducted in HST scenarios encompassing both residential and undeveloped areas.The path loss(PL)model and the channel characteristics including stationarity interval(SI),multipath components(MPCs),shadow fading(SF),Rician K-factor,root mean square(RMS)delay spread and received correlation coefficients are analyzed and fitted.The estimated channel characteristics and the statistical model presented in this paper will contribute to the research on HST radio propagation and the development of 5G railway communication systems.
基金supported by the Beijing Natural Science Foundation(L223025,4242003)Qin Xin Talents Cultivation Program of Beijing Information Science&Technology University(QXTCP B202405)。
文摘With the evolution of next-generation communication networks,ensuring robust Core Network(CN)architecture and data security has become paramount.This paper addresses critical vulnerabilities in the architecture of CN and data security by proposing a novel framework based on blockchain technology that is specifically designed for communication networks.Traditional centralized network architectures are vulnerable to Distributed Denial of Service(DDoS)attacks,particularly in roaming scenarios where there is also a risk of private data leakage,which imposes significant operational demands.To address these issues,we introduce the Blockchain-Enhanced Core Network Architecture(BECNA)and the Secure Decentralized Identity Authentication Scheme(SDIDAS).The BECNA utilizes blockchain technology to decentralize data storage,enhancing network security,stability,and reliability by mitigating Single Points of Failure(SPoF).The SDIDAS utilizes Decentralized Identity(DID)technology to secure user identity data and streamline authentication in roaming scenarios,significantly reducing the risk of data breaches during cross-network transmissions.Our framework employs Ethereum,free5GC,Wireshark,and UERANSIM tools to create a robust,tamper-evident system model.A comprehensive security analysis confirms substantial improvements in user privacy and network security.Simulation results indicate that our approach enhances communication CNs security and reliability,while also ensuring data security.
基金supported by the National Key R&D Program of China(No.2023YFC3705801)the National Natural Science Foundation of China(No.42177085).
文摘Substantial effects of photochemical reaction losses of volatile organic compounds(VOCs)on factor profiles can be investigated by comparing the differences between daytime and nighttime dispersion-normalized VOC data resolved profiles.Hourly speciated VOC data measured in Shijiazhuang,China from May to September 2021 were used to conduct study.The mean VOC concentration in the daytime and at nighttime were 32.8 and 36.0 ppbv,respectively.Alkanes and aromatics concentrations in the daytime(12.9 and 3.08 ppbv)were lower than nighttime(15.5 and 3.63 ppbv),whereas that of alkenes showed the opposite tendency.The concentration differences between daytime and nighttime for alkynes and halogenated hydrocarbonswere uniformly small.The reactivities of the dominant species in factor profiles for gasoline emissions,natural gas and diesel vehicles,and liquefied petroleum gas were relatively low and their profiles were less affected by photochemical losses.Photochemical losses produced a substantial impact on the profiles of solvent use,petrochemical industry emissions,combustion sources,and biogenic emissions where the dominant species in these factor profiles had high reactivities.Although the profile of biogenic emissions was substantially affected by photochemical loss of isoprene,the low emissions at nighttime also had an important impact on its profile.Chemical losses of highly active VOC species substantially reduced their concentrations in apportioned factor profiles.This study results were consistent with the analytical results obtained through initial concentration estimation,suggesting that the initial concentration estimation could be the most effective currently availablemethod for the source analyses of active VOCs although with uncertainty.
基金supported by the National Key Research and Development Program of China(Nos.2023YFC3709500,2023YFC3709502 and 2022YFC3703400)the National Natural Science Foundation of China(No.42077191)+1 种基金the Fundamental Research Funds for the Central Universities(No.63233054)Tianjin Science and Technology Plan Project(No.18PTZWHZ00120).
文摘Serious fine particulate matter(PM_(2.5))pollution and rapidly increasing of ground-level ozone(O_(3))concentrations are concern issues in China.To achieve the comprehensive control of PM_(2.5)-O_(3) composite air pollution,exploring the common sources of PM_(2.5) and VOCs is essential.However,previous researches most carried out either PM_(2.5) or VOCs source appointment.In this study,we applied the ensemble source apportionment method to explore the impacts of common sources on PM_(2.5)-VOCs.Subsequently,we obtained the ensemble source impacts on O_(3) combining the extracted VOCs source profile and ozone formation potential.We found that the focus of environmentalmanagement and source control should be varied accordingly for different pollutants.Vehicle emission was the largest contributor(41%)to PM_(2.5)-VOCs,while industrial emission was the main common source(51%)to O_(3).The result showed that the O_(3) production rate is not only related to the VOCs emission,but also to the reactivity of VOCs.In addition,sensitivity tests revealed that temperature was the main factor affecting O_(3) formation.The study provides a framework to explore the common sources impact on PM_(2.5) and VOCs,which is benefit to address both PM_(2.5) and O_(3) mitigations.
文摘Traffic congestion is widely distributed around a network. Generally, to analyze traffic congestion, static traffic capacity is adopted. But dynamic characteristics must be studied because congestion is a dynamic process. A Dynamic Traffic Assignment modeling fundamental combined with an urban congestion analysis method is studied in this paper. Three methods are based on congestion analysis, and the stochastic user optimal DTA models are especially considered. Correspondingly, a dynamic system optimal model is suggested for responding congestion countermeasures and an ideal user optimal model for predicted congestion countermeasure respectively.
基金the National Natural Science Founda-tion of China(No.71803110)the“Chen Guang”Project in Shanghai Municipal Education Commis-sion and Shanghai Education Development Foundation(No.19CG41)。
文摘The current method of evaluating passenger satisfaction primarily adopts the traditional static evaluation mode,which can hardly satisfy the dynamic regulatory requirements of highway passenger transport service quality set by industry management departments.In this paper,we summarize the characteristics of real-time dynamic evaluation under the requirements of hierarchical and classified evaluation and analyze the entire process of the one-time travel service of highway passenger transport.We focus on station waiting and in-vehicle services,extract the elements most concerned by passengers as evaluation indexes,and construct a three-level index system.Subsequently,a multi-indicator comprehensive evaluation method based on the analytic hierarchy process and fuzzy comprehensive evaluation is selected to construct a comprehensive evaluation model.By combining with the development level of electronic ticket purchasing and the requirements of satisfaction evaluation,we propose three data collection methods and compare and analyze their strengths and weaknesses.Finally,based on actual survey data,the effectiveness of the model is verified.The verification results show that the real-time dynamic evaluation index system based on the Internet can better satisfy evaluation requirements.
文摘Multi-pylon multi-span suspension bridge is a new type super flexible structure system, and the rigidity design of middle pylon is one of the main difficult technical issues. Due to the requirements of longitudinal rigidity, the structural form and the corresponding foundation type of middle pylon are different from those of the ordinary steel pylon, and the complicated dynamic characteristics make the calculation quite difficult. In this article, exploration has been made in selection of similarity ratio and model materials, section simulation, restriction conditions simulation, fixing of mass blocks, fabrication scheme and testing method by taking into account different construction and working conditions such as restriction conditions and working environment of a three-pylon suspension bridge, to conduct the test experimental design of the dynamic behavior of the middle pylon, with the purpose to reveal its dynamic characteristics and make comparison and analysis with theoretical assumptions, to provide basis for anti-wind and anti-seismic design and reference for the design and research of three-pylon two-span suspension bridges in the future.
基金The National Natural Science Foundation of China(No.51878167)the Postgraduate Research and Practice Innovation Program of Jiangsu Province(No.KYCX23_0300).
文摘To enhance the serviceability of steel bridge deck pavement(SBDP)in high-temperature and rainy regions,a concept of rigid bottom and flexible top was summarized using engineering practices,which led to the proposal of a three-layer ultra-high-performance pavement(UHPP).The high-temperature rutting resistance and wet-weather skid resistance of UHPP were evaluated through composite structure tests.The internal temperature distribution within the pavement under typical high-temperature conditions was analyzed using a temperature field model.Additionally,a temperature-stress coupling model was employed to investigate the key load positions and stress response characteristics of the UHPP.The results indicate that compared with the traditional guss asphalt+stone mastic asphalt structure,the dynamic stability of the UHPP composite structure can be improved by up to 20.4%.Even under cyclic loading,UHPP still exhibits superior surface skid resistance compared to two traditional SBDPs.The thickness composition of UHPP significantly impacts its rutting resistance and skid resistance.UHPP exhibits relatively low tensile stress but higher shear stress levels,with the highest shear stress occurring between the UHPP and the steel plate.This suggests that the potential risk of damage for UHPP primarily lies within the interlayer of the pavement.Based on engineering examples,introducing interlayer gravel and optimizing the amount of bonding layer are advised to ensure that UHPP possesses sufficient interlayer shear resistance.
基金supported by the National Natural Science Foundation of China (62206204,62176193)the Natural Science Foundation of Hubei Province,China (2023AFB705)the Natural Science Foundation of Chongqing,China (CSTB2023NSCQ-MSX0932)。
文摘When encountering the distribution shift between the source(training) and target(test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain adaptation research has achieved a lot of success both in theory and practice under the assumption that all the examples in the source domain are welllabeled and of high quality. However, the methods consistently lose robustness in noisy settings where data from the source domain have corrupted labels or features which is common in reality. Therefore, robust domain adaptation has been introduced to deal with such problems. In this paper, we attempt to solve two interrelated problems with robust domain adaptation:distribution shift across domains and sample noises of the source domain. To disentangle these challenges, an optimal transport approach with low-rank constraints is applied to guide the domain adaptation model training process to avoid noisy information influence. For the domain shift problem, the optimal transport mechanism can learn the joint data representations between the source and target domains using a measurement of discrepancy and preserve the discriminative information. The rank constraint on the transport matrix can help recover the corrupted subspace structures and eliminate the noise to some extent when dealing with corrupted source data. The solution to this relaxed and regularized optimal transport framework is a convex optimization problem that can be solved using the Augmented Lagrange Multiplier method, whose convergence can be mathematically proved. The effectiveness of the proposed method is evaluated through extensive experiments on both synthetic and real-world datasets.
基金Project(41941018)supported by the National Natural Science Foundation of China for the Special Project FundingProject(22-JKCF-08)supported by the Study on in-situ Stress Database and 3D in-situ Stress Inversion Technology of Highway Tunnel in Shanxi Province,China+1 种基金Project(2022-JKKJ-6)supported by the Study on Disaster Mechanism and NPR Anchor Cable Prevention and Control of Coal Mining Caving Subsidence in Operating Tunnel in Mountainous Area,ChinaProject(BBJ2024032)supported by the Fundamental Research Funds for the Central Universities(PhD Top Innovative Talents Fund of CUMTB),China。
文摘A study was conducted to analyze the deformation mechanism of strongly weathered quartz schist in the Daliangshan Tunnel,located in the western Transverse Mountain area.A large deformation problem was experienced during the tunnel construction.To mitigate this problem,a support system was designed incorporating negative Poisson ratio(NPR)anchor cables with negative Poisson ratio effect.Physical model experiments,field experiments,and numerical simulation experiments were conducted to investigate the compensation mechanical behavior of NPR anchor cables.The large deformations of soft rocks in the Daliangshan Tunnel are caused by a high ground stress,a high degree of joint fracture development,and a high degree of surrounding rock fragmentation.A compensation mechanics support system combining long and short NPR anchor cables was suggested to provide sufficient counter-support force(approximately 350 kN)for the surrounding rock inside the tunnel.Comparing the NPR anchor cable support system with the original support system used in the Daliangshan tunnel showed that an NPR anchor cable support system,combining cables of 6.3 m and 10.3 m in length,effectively prevented convergence of surrounding rock deformation,and the integrated settlement convergence value remained below 300 mm.This study provides an effective scientific basis for resolving large deformation problems in deeply buried soft rocks in western transverse mountain areas.
文摘Critical infrastructure systems(CISs)play a key role in the socio-economic activity of a society,but are exposed to an array of disruptive events that can greatly impact their function and performance.Therefore,understanding the underlying behaviors of CISs and their response to perturbations is needed to better prepare for,and mitigate the impact of,future disruptions.Resilience is one characteristic of CISs that influences the extent and severity of the impact induced by extreme events.Resilience is often dissected into four dimensions:robustness,redundancy,resourcefulness,and rapidity,known as the“4Rs”.This study proposes a framework to assess the resilience of an infrastructure network in terms of these four dimensions under optimal resource allocation strategies and incorporates interdependencies between different CISs,with resilience considered as a stochastic variable.The proposed framework combines an agent-based infrastructure interdependency model,advanced optimization algorithms,Bayesian network techniques,and Monte Carlo simulation to assess the resilience of an infrastructure network.The applicability and flexibility of the proposed framework is demonstrated with a case study using a network of CISs in Austin,Texas,where the resilience of the network is assessed and a“what-if”analysis is performed.
基金Beijing Natural Science Foundation(9234025)National Social Science Fund Project of China(21FGLB014)Humanity and Social Science Youth Foundation of Ministry of Education of China(21YJC630094).
文摘Urban intersections without traffic signals are prone to accidents involving motor vehicles and pedestrians.Utilizing computer vision technology to detect pedestrians crossing the street can effectively mitigate the occurrence of such accidents.Faced with the complex issue of pedestrian occlusion at signal-free intersections,this paper proposes a target detection model called Head feature And ENMS fusion Residual connection For CNN(HAERC).Specifically,the model includes a head feature module that detects occluded pedestrians by integrating their head features with the overall target.Additionally,to address the misselection caused by overlapping candidate boxes in two-stage target detection models,an Extended Non-Maximum Suppression classifier(ENMS)with expanded IoU thresholds is proposed.Finally,leveraging the CityPersons dataset and categorizing it into four classes based on occlusion levels(heavy,reasonable,partial,bare),the HAERC model is experimented on these classes and compared with baseline models.Experimental results demonstrate that HAERC achieves superior False Positives Per Image(FPPI)values of 46.64%,9.59%,9.43%,and 6.78%respectively for the four classes,outperforming all baseline models.The study concludes that the HAERC model effectively identifies occluded pedestrians in the complex environment of urban intersections without traffic signals,thereby enhancing safety for long-range driving at such intersections.
