Penetration testing plays a critical role in ensuring security in an increasingly interconnected world. Despite advancements in technology leading to smaller, more portable devices, penetration testing remains reliant...Penetration testing plays a critical role in ensuring security in an increasingly interconnected world. Despite advancements in technology leading to smaller, more portable devices, penetration testing remains reliant on traditional laptops and computers, which, while portable, lack true ultra-portability. This paper explores the potential impact of developing a dedicated, ultra-portable, low-cost device for on-the-go penetration testing. Such a device could replicate the core functionalities of advanced penetration testing tools, including those found in Kali Linux, within a compact form factor that fits easily into a pocket. By offering the convenience and portability akin to a smartphone, this innovative device could redefine the way penetration testers operate, enabling them to carry essential tools wherever they go and ensuring they are always prepared to conduct security assessments efficiently. This approach aims to revolutionize penetration testing by merging high functionality with unparalleled portability.展开更多
Ground improvement has been used on many construction sites to densify granular materials, in other word, to improve soil properties and reduce potential settlement. This work presents a case study of ground improveme...Ground improvement has been used on many construction sites to densify granular materials, in other word, to improve soil properties and reduce potential settlement. This work presents a case study of ground improvement using rapid impact compaction （RIC）. The research site comprises the construction of workshop and depots as part of railway development project at Batu Gajah-Ipoh, Malaysia. In-situ testing results show that the subsurface soil comprises mainly of sand and silty sand through the investigated depth extended to 10 m. Groundwater is approximately 0.5 m below the ground surface. Evaluation of improvement was based on the results of pre- and post-improvement cone penetration test （CPT）. Interpretation software has been used to infer soil properties. Load test was conducted to estimate soil settlement. It is found that the technique succeeds in improving soil properties namely the relative density increases from 45% to 70%, the friction angle of soil is increased by an average of 3°, and the soil settlement is reduced by 50%： The technique succeeds in improving soil properties to approximately 5.0 m in depth depending on soil uniformity with depth.展开更多
Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test paths.In view of the difficulty for attack...Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test paths.In view of the difficulty for attackers to obtain complete network information in realistic network scenarios,Reinforcement Learning(RL)is a promising solution to discover the optimal penetration path under incomplete information about the target network.Existing RL-based methods are challenged by the sizeable discrete action space,which leads to difficulties in the convergence.Moreover,most methods still rely on experts’knowledge.To address these issues,this paper proposes a penetration path planning method based on reinforcement learning with episodic memory.First,the penetration testing problem is formally described in terms of reinforcement learning.To speed up the training process without specific prior knowledge,the proposed algorithm introduces episodic memory to store experienced advantageous strategies for the first time.Furthermore,the method offers an exploration strategy based on episodic memory to guide the agents in learning.The design makes full use of historical experience to achieve the purpose of reducing blind exploration and improving planning efficiency.Ultimately,comparison experiments are carried out with the existing RL-based methods.The results reveal that the proposed method has better convergence performance.The running time is reduced by more than 20%.展开更多
In today’s era, where mobile devices have become an integral part of our daily lives, ensuring the security of mobile applications has become increasingly crucial. Mobile penetration testing, a specialized subfield w...In today’s era, where mobile devices have become an integral part of our daily lives, ensuring the security of mobile applications has become increasingly crucial. Mobile penetration testing, a specialized subfield within the realm of cybersecurity, plays a vital role in safeguarding mobile ecosystems against the ever-evolving landscape of threats. The ubiquity of mobile devices has made them a prime target for cybercriminals, and the data and functionality accessed through mobile applications make them valuable assets to protect. Mobile penetration testing is designed to identify vulnerabilities, weaknesses, and potential exploits within mobile applications and the devices themselves. Unlike traditional penetration testing, which often focuses on network and server security, mobile penetration testing zeroes in on the unique challenges posed by mobile platforms. Mobile penetration testing, a specialized field within cybersecurity, is an essential tool in the Cybersecurity specialists’ toolkit to protect mobile ecosystems from emerging threats. This article introduces mobile penetration testing, emphasizing its significance, including comprehensive learning labs for Android and iOS platforms, and highlighting how it distinctly differs from traditional penetration testing methodologies.展开更多
Soil liquefaction is one of the complex research topics in geotechnical engineering and engineering geology. Especially after the 1964 Niigata earthquake (Japan) induced many soil liquefaction incidents, a variety of ...Soil liquefaction is one of the complex research topics in geotechnical engineering and engineering geology. Especially after the 1964 Niigata earthquake (Japan) induced many soil liquefaction incidents, a variety of soil liquefaction studies were conducted and reported, including the liquefaction potential assessment methods utilizing the shear wave velocity (V<sub>s</sub>) or SPT-N profiles (SPT: standard penetration test). This study used the V<sub>s</sub> and SPT methods recommended by the National Center for Earthquake Engineering Research (NCEER) to examine which is more conservative according to the assessment results on 41 liquefiable soil layers at sites in two major cities in Taiwan. Statistical hypothesis testing was used to make the analysis more quantitative and objective. Based on three sets of hypothesis tests, it shows that the hypothesis—the SPT method is more conservative than the V<sub>s</sub> method—was not rejected on a 5% level of significance.展开更多
Currently,there is a lack of in-situ or model test results for cone penetration tests(CPTs)conducted in deep,dense sand layers under high overburden stresses,restricting the development of empirical relationships betw...Currently,there is a lack of in-situ or model test results for cone penetration tests(CPTs)conducted in deep,dense sand layers under high overburden stresses,restricting the development of empirical relationships between CPT results and the characteristics of such deep,dense sand layers.This study addresses this gap by proposing an empirical relationship to predict the relative density of dense silica sand based on stress level and cone tip resistance.The relationship was developed through CPTs performed in a calibration chamber using dense sand specimens(with relative densities of 74%-91%)subjected to high stresses(under overburden stresses of 0.5-2.0 MPa)and numerical simulations employing the large deformation finite element method.The Arbitrary Lagrangian Eulerian method was used to regularly regenerate the mesh to prevent soil element distortion around the cone tip.Additionally,the modified Mohr-Coulomb model was integrated to capture the stress-strain behavior of dense silica sand under high stresses.A reasonable agreement was achieved between the numerical and experimental penetration profiles,which verifies the reliability of the numerical model.A sufficient number of parametric analyses were carried out,and then an empirical equation was proposed to establish the relationship between the relative density of dense sand,stress level and cone resistance.The empirical equation provides predictions with acceptable accuracy,as the discrepancies between the predicted and measured relative density values fall within±30%.展开更多
Geotechnical parameters derived from an intrusive cone penetration test(CPT)are used to asses mechanical properties to inform the design phase of infrastructure projects.However,local,in situ 1D measurements can fail ...Geotechnical parameters derived from an intrusive cone penetration test(CPT)are used to asses mechanical properties to inform the design phase of infrastructure projects.However,local,in situ 1D measurements can fail to capture 3D subsurface variations,which could mean less than optimal design decisions for foundation engineering.By coupling the localised measurements from CPTs with more global 3D measurements derived from geophysical methods,a higher fidelity 3D overview of the subsurface can be obtained.Machine Learning(ML)may offer an effective means to capture all types of geophysical information associated with CPT data at a site scale to build a 2D or 3D ground model.In this paper,we present an ML approach to build a 3D ground model of cone resistance and sleeve friction by combining several CPT measurements with Multichannel Analysis of Surface Waves(MASW)and Electrical Resistivity Tomography(ERT)data on a land site characterisation project in the United Arab Emirates(UAE).To avoid a potential overfitting problem inherent to the use of machine learning and a lack of data at certain locations,we explore the possibility of using a prior Geo-Statistical(GS)approach that attempts to constrain the overfitting process by“artificially”increasing the amount of input data.A sensitivity study is also performed on input features used to train the ML algorithm to better define the optimal combination of input features for the prediction.Our results showed that ERT data were not useful in capturing 3D variations of geotechnical properties compared to Vs due to the geographical location of the site(200 m east from the Oman Gulf)and the possible effect of saline water intrusion.Additionally,we demonstrate that the use of a prior GS phase could be a promising and interesting means to make the prediction of ground properties more robust,especially for this specific case study described in this paper.Looking ahead,better representation of the subsurface can lead to a number of benefits for stakeholders involved in developing assets.Better ground/geotechnical models mean better site calibration of design methods and fewer design assumptions for reliability-based design,creating an opportunity for value engineering in the form of lighter construction without compromising safety,shorter construction timelines,and reduced resource requirements.展开更多
The Fifth Generation of Mobile Communications for Railways(5G-R)brings significant opportunities for the rail industry.However,alongside the potential and benefits of the railway 5G network are complex security challe...The Fifth Generation of Mobile Communications for Railways(5G-R)brings significant opportunities for the rail industry.However,alongside the potential and benefits of the railway 5G network are complex security challenges.Ensuring the security and reliability of railway 5G networks is therefore essential.This paper presents a detailed examination of security assessment techniques for railway 5G networks,focusing on addressing the unique security challenges in this field.In this paper,various security requirements in railway 5G networks are analyzed,and specific processes and methods for conducting comprehensive security risk assessments are presented.This study provides a framework for securing railway 5G network development and ensuring its long-term sustainability.展开更多
Cone penetration testing(CPT)and its variant with pore pressure measurements(CPTu)are versatile tools that have been traditionally used for in situ geotechnical site investigations.These investigations are among the m...Cone penetration testing(CPT)and its variant with pore pressure measurements(CPTu)are versatile tools that have been traditionally used for in situ geotechnical site investigations.These investigations are among the most challenging yet indispensable tasks,providing a crucial reference for infrastructure planning,design and construction.However,data obtained through the CPT/CPTu testing often exhibit significant variability,even at closely spaced test points.This variability is primarily attributed to the complex mineral compositions and sedimentary process of the Quaternary sediments.Problems induced by the scattering data include the difficulties in estimating the shear strength of the sediments and determining the appropriate bearing stratum for pile foundations.In this paper,the conventional interpretation methods of the CPT/CPTu data are enhanced with sedimentary facies knowledge.The geotechnical investigation mainly involves 42 CPTu tests(39 essential data sets available)and 4 boring samples.Sediment types are interpreted from the CPTu data and calibrated by the nearby boring samples.Sedimentary facies are derived from the interpreted sequence stratigraphy,for which the interpretation skills are summarized in the form of characteristic curves of the CPTu data.Scattering distribution of the sediment types and their mechanical parameters are well explained by the sedimentary facies.The sediments are then categorized into a few groups by their sedimentary facies,resulting in reduced uncertainties and scattering in terms of shear strength.Bearing stratum of pile foundations is also suggested based on the sedimentary regulations.展开更多
Sinkhole formation poses a significant geohazard in karst regions,where unpredictable subsurface erosion often necessitates costly grouting for stabilization.Accurate estimation of grout volume remains a persistent ch...Sinkhole formation poses a significant geohazard in karst regions,where unpredictable subsurface erosion often necessitates costly grouting for stabilization.Accurate estimation of grout volume remains a persistent challenge due to spatial variability,site-specific conditions,and the limitations of traditional empirical methods.This study introduces a novel machine learning-based regression model for grout volume prediction that integrates cone penetration test(CPT)-derived Sinkhole Resistance Ratio(SRR)values,spatial correlations between CPT and grouting points(GPs),and field-recorded grout volumes from six sinkhole sites in Florida.Three data trans-formation methods,the Proximal Allocation Method(PAM),the Equitable Distribution Method(EDM),and the Threshold-based Equitable Distribution Method(TEDM),were applied to distribute grout influence across CPTs,with TEDM demonstrating superior predictive performance.Synthetic data augmentation using spline method-ology further improved model robustness.A high-degree polynomial regression model,optimized with ridge regularization,achieved high accuracy(R^(2)=0.95;PEV=0.94)and significantly outperformed existing linear and logarithmic models.Results confirm that lower SRR values correlate with higher grout demand,and the proposed model reliably captures these nonlinear relationships.This research advances sinkhole remediation practice by providing a data-driven,accurate,and generalizable framework for grout volume estimation,enabling more efficient resource allocation and improved project outcomes.展开更多
Conventional empirical equations for estimating undrained shear strength(s_(u))from piezocone penetration test(CPTu)data,without incorporating soil physical properties,often lack the accuracy and robustness required f...Conventional empirical equations for estimating undrained shear strength(s_(u))from piezocone penetration test(CPTu)data,without incorporating soil physical properties,often lack the accuracy and robustness required for geotechnical site investigations.This study introduces a hybrid virus colony search(VCS)algorithm that integrates the standard VCS algorithm with a mutation-based search mechanism to develop high-performance XGBoost learning models to address this limitation.A dataset of 372 seismic CPTu and corresponding soil physical properties data from 26 geotechnical projects in Jiangs_(u)Province,China,was collected for model development.Comparative evaluations demonstrate that the proposed hybrid VCS-XGBoost model exhibits s_(u)perior performance compared to standard meta-heuristic algorithm-based XGBoost models.The res_(u)lts highlight that the consideration of soil physical properties significantly improves the predictive accuracy of s_(u),emphasizing the importance of considering additional soil information beyond CPTu data for accurate s_(u)estimation.展开更多
MICP(Microbially induced calcite precipitation),an environmentally friendly soil improvement technique,has great potential in ocean engineering due to its ability to promote the precipitation of calcium carbonate thro...MICP(Microbially induced calcite precipitation),an environmentally friendly soil improvement technique,has great potential in ocean engineering due to its ability to promote the precipitation of calcium carbonate through microbial activity to enhance the engineering properties of geomaterials.In this study,piezocone penetration test(CPTU)is used to evaluate the effectiveness of MICP treatment in calcareous sand.The change of physical properties(relative density D and total unit weight)of MICP treated calcareous sand is investigated by conducting CPTU on the geomaterials prepared in a series of mini calibration chambers(25 cm×50 cm).Results indicate that CPTU(tip stress,sleeve friction,and porewater pressure)measurements can be used to interpret the physical characteristics of calcareous sand treated with MICP under seawater conditions.Additionally,a relationship between CPTU measurements,physical parameters(relative density D,and total unit weight y)of MICP treated calcareous sand is proposed and calibrated.The findings of the research extend the implementation of in-situ testing techniques such as CPTU towards physical property evaluation of bio-treated geomaterials in ocean environment,and demonstrate the potential of scaling up MICP techniques for broader engineeringapplication.展开更多
With the increasing construction of port facilities,cross-sea bridges,and offshore engineering projects,uplift piles embedded in marine sedimentary soft soil are becoming increasingly necessary.The load-displacement c...With the increasing construction of port facilities,cross-sea bridges,and offshore engineering projects,uplift piles embedded in marine sedimentary soft soil are becoming increasingly necessary.The load-displacement curve of uplift piles is crucial for evaluating their uplift bearing characteristics,which facilitates the risk evaluation,design,and construction of large infrastructural supports.In this study,a load-displacement curve model based on piezocone penetration test(CPTU)data is proposed via the load transfer method.Experimental tests are conducted to analyze the uplift bearing characteristics and establish a correlation between the proposed model and CPTU data.The results of the proposed load-displacement curve are compared with the results from numerical simulations and those calculated by previous methods.The results show that the proposed curves appropriately evaluated the uplift bearing characteristics and improved the accuracy in comparison with previous methods.展开更多
The water drop penetration time(WDPT)test consists of placing water drops on a material's surface in order to evaluate how long it takes to penetrate the pores.It is used to evaluate the hydrophobicity of material...The water drop penetration time(WDPT)test consists of placing water drops on a material's surface in order to evaluate how long it takes to penetrate the pores.It is used to evaluate the hydrophobicity of materials.This study aims at investigating in more detail the soil-water interaction during the test,exposing its mechanism.For that,a model soil named Hamburg Sand was coated with a hydrophobic fluoropolymer and then a WDPT test was performed while computed tomography(CT)images were taken.Tomography experiments were performed at the P07 high-energy materials science(HEMS)beamline,operated by Helmholtz–Zentrum Hereon,at the storage ring PETRA III at the Deutsches Elektronen-Synchrotron(DESY)in Hamburg.Using synchrotron radiation,a tomogram can be obtained in about 10 min,way less time than regular laboratory X-ray sources usually owned by universities.The faster imaging enables the observation of the drop penetration during time and thus provides insight into the dynamics of the process.After that,digital discrete image correlation is performed to track the displacement of the grains throughout time.From the results one can observe that,as the drop is absorbed at the material's surface,the grains directly around the droplet base are dragged to the liquid-air interface around the drop,revealing grain kinematics during capillary interactions of the penetrating liquid and sand grains.展开更多
The methodology of predicting pile shaft skin ultimate friction has been studied in a systematic way. In the light of that, the analysis of the pile shaft resistance for bored and cast in situ piles in cohesive soil...The methodology of predicting pile shaft skin ultimate friction has been studied in a systematic way. In the light of that, the analysis of the pile shaft resistance for bored and cast in situ piles in cohesive soils was carried out thoroughly in the basis of field performance data of 10 fully instrumented large diameter bored piles (LDBPs) used as the bridge foundation. The undrained strength index μ in term of cohesive soils was brought forward in allusion to the cohesive soils in the consistence plastic state, and can effectively combine the friction angle and the cohesion of cohesive soils in undrained condition. And that the classical ' α method' was modified much in effect to predict the pile shaft skin friction of LDBPs in cohesive soils. Furthermore, the approach of standard penetration test (SPT) N value used to estimate the pile shaft skin ultimate friction was analyzed, and the calculating formulae were established for LDBPs in clay and silt clay respectively.展开更多
Discernment of seismic soil liquefaction is a complex and non-linear procedure that is affected by diversified factors of uncertainties and complexity.The Bayesian belief network(BBN)is an effective tool to present a ...Discernment of seismic soil liquefaction is a complex and non-linear procedure that is affected by diversified factors of uncertainties and complexity.The Bayesian belief network(BBN)is an effective tool to present a suitable framework to handle insights into such uncertainties and cause–effect relationships.The intention of this study is to use a hybrid approach methodology for the development of BBN model based on cone penetration test(CPT)case history records to evaluate seismic soil liquefaction potential.In this hybrid approach,naive model is developed initially only by an interpretive structural modeling(ISM)technique using domain knowledge(DK).Subsequently,some useful information about the naive model are embedded as DK in the K2 algorithm to develop a BBN-K2 and DK model.The results of the BBN models are compared and validated with the available artificial neural network(ANN)and C4.5 decision tree(DT)models and found that the BBN model developed by hybrid approach showed compatible and promising results for liquefaction potential assessment.The BBN model developed by hybrid approach provides a viable tool for geotechnical engineers to assess sites conditions susceptible to seismic soil liquefaction.This study also presents sensitivity analysis of the BBN model based on hybrid approach and the most probable explanation of liquefied sites,owing to know the most likely scenario of the liquefaction phenomenon.展开更多
Determining the liquefaction potential of soil is important in earthquake engineering. This study proposes the use of the Relevance Vector Machine （RVM） to determine the liquefaction potential of soil by using actua...Determining the liquefaction potential of soil is important in earthquake engineering. This study proposes the use of the Relevance Vector Machine （RVM） to determine the liquefaction potential of soil by using actual cone penetration test （CPT） data. RVM is based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. The results are compared with a widely used artificial neural network （ANN） model. Overall, the RVM shows good performance and is proven to be more accurate than the ANN model. It also provides probabilistic output. The model provides a viable tool for earthquake engineers to assess seismic conditions for sites that are susceptible to liquefaction.展开更多
In this study, th e least sq u are su p p o rt v ecto r m achine （LSSVM） alg o rith m w as applied to predicting th ebearing capacity o f b ored piles e m b ed d ed in sand an d m ixed soils. Pile g eo m etry an d c...In this study, th e least sq u are su p p o rt v ecto r m achine （LSSVM） alg o rith m w as applied to predicting th ebearing capacity o f b ored piles e m b ed d ed in sand an d m ixed soils. Pile g eo m etry an d cone p e n e tra tio nte s t （CPT） resu lts w ere used as in p u t variables for pred ictio n o f pile bearin g capacity. The d ata u se d w erecollected from th e existing litera tu re an d consisted o f 50 case records. The application o f LSSVM w ascarried o u t by dividing th e d ata into th re e se ts： a train in g se t for learning th e pro b lem an d obtain in g arelationship b e tw e e n in p u t variables an d pile bearin g capacity, and testin g an d validation sets forevaluation o f th e predictive an d g en eralization ability o f th e o b tain ed relationship. The predictions o f pilebearing capacity by LSSVM w ere evaluated by com paring w ith ex p erim en tal d ata an d w ith th o se bytrad itio n al CPT-based m eth o d s and th e gene ex pression pro g ram m in g （GEP） m odel. It w as found th a t th eLSSVM perform s w ell w ith coefficient o f d eterm in atio n , m ean, an d sta n d ard dev iatio n equivalent to 0.99,1.03, an d 0.08, respectively, for th e testin g set, an d 1, 1.04, an d 0.11, respectively, for th e v alidation set. Thelow values o f th e calculated m ean squared e rro r an d m ean ab so lu te e rro r indicated th a t th e LSSVM w asaccurate in p redicting th e pile bearing capacity. The results o f com parison also show ed th a t th e p roposedalg o rith m p red icted th e pile bearin g capacity m ore accurately th a n th e trad itio n al m eth o d s including th eGEP m odel.展开更多
Cone penetration test(CPT)is an appropriate technique for quickly determining the geotechnical properties of lunar soil,which is valuable for in situ lunar exploration.Utilizing a typical coupling method recently deve...Cone penetration test(CPT)is an appropriate technique for quickly determining the geotechnical properties of lunar soil,which is valuable for in situ lunar exploration.Utilizing a typical coupling method recently developed by the authors,a finite element method(FEM)-discrete element method(DEM)coupled model of CPTs is obtained.A series of CPTs in lunar soil are simulated to qualitatively reveal the flow of particles and the development of resistance throughout the penetration process.In addition,the effects of major factors,such as penetration velocity,penetration depth,cone tip angle,and the low gravity on the Moon surface are investigated.展开更多
文摘Penetration testing plays a critical role in ensuring security in an increasingly interconnected world. Despite advancements in technology leading to smaller, more portable devices, penetration testing remains reliant on traditional laptops and computers, which, while portable, lack true ultra-portability. This paper explores the potential impact of developing a dedicated, ultra-portable, low-cost device for on-the-go penetration testing. Such a device could replicate the core functionalities of advanced penetration testing tools, including those found in Kali Linux, within a compact form factor that fits easily into a pocket. By offering the convenience and portability akin to a smartphone, this innovative device could redefine the way penetration testers operate, enabling them to carry essential tools wherever they go and ensuring they are always prepared to conduct security assessments efficiently. This approach aims to revolutionize penetration testing by merging high functionality with unparalleled portability.
基金Projects(RG148/12AET,RG086/10AET) supported by the UMRG,MalaysiaProject(PS05812010B) supported by the Post Graduate Research Fund,Malaysia
文摘Ground improvement has been used on many construction sites to densify granular materials, in other word, to improve soil properties and reduce potential settlement. This work presents a case study of ground improvement using rapid impact compaction （RIC）. The research site comprises the construction of workshop and depots as part of railway development project at Batu Gajah-Ipoh, Malaysia. In-situ testing results show that the subsurface soil comprises mainly of sand and silty sand through the investigated depth extended to 10 m. Groundwater is approximately 0.5 m below the ground surface. Evaluation of improvement was based on the results of pre- and post-improvement cone penetration test （CPT）. Interpretation software has been used to infer soil properties. Load test was conducted to estimate soil settlement. It is found that the technique succeeds in improving soil properties namely the relative density increases from 45% to 70%, the friction angle of soil is increased by an average of 3°, and the soil settlement is reduced by 50%： The technique succeeds in improving soil properties to approximately 5.0 m in depth depending on soil uniformity with depth.
文摘Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test paths.In view of the difficulty for attackers to obtain complete network information in realistic network scenarios,Reinforcement Learning(RL)is a promising solution to discover the optimal penetration path under incomplete information about the target network.Existing RL-based methods are challenged by the sizeable discrete action space,which leads to difficulties in the convergence.Moreover,most methods still rely on experts’knowledge.To address these issues,this paper proposes a penetration path planning method based on reinforcement learning with episodic memory.First,the penetration testing problem is formally described in terms of reinforcement learning.To speed up the training process without specific prior knowledge,the proposed algorithm introduces episodic memory to store experienced advantageous strategies for the first time.Furthermore,the method offers an exploration strategy based on episodic memory to guide the agents in learning.The design makes full use of historical experience to achieve the purpose of reducing blind exploration and improving planning efficiency.Ultimately,comparison experiments are carried out with the existing RL-based methods.The results reveal that the proposed method has better convergence performance.The running time is reduced by more than 20%.
文摘In today’s era, where mobile devices have become an integral part of our daily lives, ensuring the security of mobile applications has become increasingly crucial. Mobile penetration testing, a specialized subfield within the realm of cybersecurity, plays a vital role in safeguarding mobile ecosystems against the ever-evolving landscape of threats. The ubiquity of mobile devices has made them a prime target for cybercriminals, and the data and functionality accessed through mobile applications make them valuable assets to protect. Mobile penetration testing is designed to identify vulnerabilities, weaknesses, and potential exploits within mobile applications and the devices themselves. Unlike traditional penetration testing, which often focuses on network and server security, mobile penetration testing zeroes in on the unique challenges posed by mobile platforms. Mobile penetration testing, a specialized field within cybersecurity, is an essential tool in the Cybersecurity specialists’ toolkit to protect mobile ecosystems from emerging threats. This article introduces mobile penetration testing, emphasizing its significance, including comprehensive learning labs for Android and iOS platforms, and highlighting how it distinctly differs from traditional penetration testing methodologies.
文摘Soil liquefaction is one of the complex research topics in geotechnical engineering and engineering geology. Especially after the 1964 Niigata earthquake (Japan) induced many soil liquefaction incidents, a variety of soil liquefaction studies were conducted and reported, including the liquefaction potential assessment methods utilizing the shear wave velocity (V<sub>s</sub>) or SPT-N profiles (SPT: standard penetration test). This study used the V<sub>s</sub> and SPT methods recommended by the National Center for Earthquake Engineering Research (NCEER) to examine which is more conservative according to the assessment results on 41 liquefiable soil layers at sites in two major cities in Taiwan. Statistical hypothesis testing was used to make the analysis more quantitative and objective. Based on three sets of hypothesis tests, it shows that the hypothesis—the SPT method is more conservative than the V<sub>s</sub> method—was not rejected on a 5% level of significance.
基金National Natural Science Foundation of China(Nos.42025702,52394251)。
文摘Currently,there is a lack of in-situ or model test results for cone penetration tests(CPTs)conducted in deep,dense sand layers under high overburden stresses,restricting the development of empirical relationships between CPT results and the characteristics of such deep,dense sand layers.This study addresses this gap by proposing an empirical relationship to predict the relative density of dense silica sand based on stress level and cone tip resistance.The relationship was developed through CPTs performed in a calibration chamber using dense sand specimens(with relative densities of 74%-91%)subjected to high stresses(under overburden stresses of 0.5-2.0 MPa)and numerical simulations employing the large deformation finite element method.The Arbitrary Lagrangian Eulerian method was used to regularly regenerate the mesh to prevent soil element distortion around the cone tip.Additionally,the modified Mohr-Coulomb model was integrated to capture the stress-strain behavior of dense silica sand under high stresses.A reasonable agreement was achieved between the numerical and experimental penetration profiles,which verifies the reliability of the numerical model.A sufficient number of parametric analyses were carried out,and then an empirical equation was proposed to establish the relationship between the relative density of dense sand,stress level and cone resistance.The empirical equation provides predictions with acceptable accuracy,as the discrepancies between the predicted and measured relative density values fall within±30%.
文摘Geotechnical parameters derived from an intrusive cone penetration test(CPT)are used to asses mechanical properties to inform the design phase of infrastructure projects.However,local,in situ 1D measurements can fail to capture 3D subsurface variations,which could mean less than optimal design decisions for foundation engineering.By coupling the localised measurements from CPTs with more global 3D measurements derived from geophysical methods,a higher fidelity 3D overview of the subsurface can be obtained.Machine Learning(ML)may offer an effective means to capture all types of geophysical information associated with CPT data at a site scale to build a 2D or 3D ground model.In this paper,we present an ML approach to build a 3D ground model of cone resistance and sleeve friction by combining several CPT measurements with Multichannel Analysis of Surface Waves(MASW)and Electrical Resistivity Tomography(ERT)data on a land site characterisation project in the United Arab Emirates(UAE).To avoid a potential overfitting problem inherent to the use of machine learning and a lack of data at certain locations,we explore the possibility of using a prior Geo-Statistical(GS)approach that attempts to constrain the overfitting process by“artificially”increasing the amount of input data.A sensitivity study is also performed on input features used to train the ML algorithm to better define the optimal combination of input features for the prediction.Our results showed that ERT data were not useful in capturing 3D variations of geotechnical properties compared to Vs due to the geographical location of the site(200 m east from the Oman Gulf)and the possible effect of saline water intrusion.Additionally,we demonstrate that the use of a prior GS phase could be a promising and interesting means to make the prediction of ground properties more robust,especially for this specific case study described in this paper.Looking ahead,better representation of the subsurface can lead to a number of benefits for stakeholders involved in developing assets.Better ground/geotechnical models mean better site calibration of design methods and fewer design assumptions for reliability-based design,creating an opportunity for value engineering in the form of lighter construction without compromising safety,shorter construction timelines,and reduced resource requirements.
基金supported in part by the Fundamental Research Funds for the Central Universities under Grant No.2025JBXT010in part by NSFC under Grant No.62171021,in part by the Project of China State Railway Group under Grant No.N2024B004in part by ZTE IndustryUniversityInstitute Cooperation Funds under Grant No.l23L00010.
文摘The Fifth Generation of Mobile Communications for Railways(5G-R)brings significant opportunities for the rail industry.However,alongside the potential and benefits of the railway 5G network are complex security challenges.Ensuring the security and reliability of railway 5G networks is therefore essential.This paper presents a detailed examination of security assessment techniques for railway 5G networks,focusing on addressing the unique security challenges in this field.In this paper,various security requirements in railway 5G networks are analyzed,and specific processes and methods for conducting comprehensive security risk assessments are presented.This study provides a framework for securing railway 5G network development and ensuring its long-term sustainability.
基金supported by the National Natural Science Foundation of China(Grant Nos.42272328 and 52108356).
文摘Cone penetration testing(CPT)and its variant with pore pressure measurements(CPTu)are versatile tools that have been traditionally used for in situ geotechnical site investigations.These investigations are among the most challenging yet indispensable tasks,providing a crucial reference for infrastructure planning,design and construction.However,data obtained through the CPT/CPTu testing often exhibit significant variability,even at closely spaced test points.This variability is primarily attributed to the complex mineral compositions and sedimentary process of the Quaternary sediments.Problems induced by the scattering data include the difficulties in estimating the shear strength of the sediments and determining the appropriate bearing stratum for pile foundations.In this paper,the conventional interpretation methods of the CPT/CPTu data are enhanced with sedimentary facies knowledge.The geotechnical investigation mainly involves 42 CPTu tests(39 essential data sets available)and 4 boring samples.Sediment types are interpreted from the CPTu data and calibrated by the nearby boring samples.Sedimentary facies are derived from the interpreted sequence stratigraphy,for which the interpretation skills are summarized in the form of characteristic curves of the CPTu data.Scattering distribution of the sediment types and their mechanical parameters are well explained by the sedimentary facies.The sediments are then categorized into a few groups by their sedimentary facies,resulting in reduced uncertainties and scattering in terms of shear strength.Bearing stratum of pile foundations is also suggested based on the sedimentary regulations.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.2022R1C1C1005409)supported by the Korea Agency for Infrastructure Technology Advancement(KAIA)grant funded by the Ministry of Land,Infrastructure and Trans-port(Grant RS-2023-00251002)+2 种基金the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(Grant No.RS-2025-00516147)support provided by the NSF PREM program(DMR-2122178)the Institute of Advanced Manufacturing(IAM)at the University of Texas at Rio Grande Valley(UTRGV).
文摘Sinkhole formation poses a significant geohazard in karst regions,where unpredictable subsurface erosion often necessitates costly grouting for stabilization.Accurate estimation of grout volume remains a persistent challenge due to spatial variability,site-specific conditions,and the limitations of traditional empirical methods.This study introduces a novel machine learning-based regression model for grout volume prediction that integrates cone penetration test(CPT)-derived Sinkhole Resistance Ratio(SRR)values,spatial correlations between CPT and grouting points(GPs),and field-recorded grout volumes from six sinkhole sites in Florida.Three data trans-formation methods,the Proximal Allocation Method(PAM),the Equitable Distribution Method(EDM),and the Threshold-based Equitable Distribution Method(TEDM),were applied to distribute grout influence across CPTs,with TEDM demonstrating superior predictive performance.Synthetic data augmentation using spline method-ology further improved model robustness.A high-degree polynomial regression model,optimized with ridge regularization,achieved high accuracy(R^(2)=0.95;PEV=0.94)and significantly outperformed existing linear and logarithmic models.Results confirm that lower SRR values correlate with higher grout demand,and the proposed model reliably captures these nonlinear relationships.This research advances sinkhole remediation practice by providing a data-driven,accurate,and generalizable framework for grout volume estimation,enabling more efficient resource allocation and improved project outcomes.
基金funded by the National Science Fund for Distinguished Young Scholars(Grant No.42225206)the National Key R&D Program of China(Grant No.2020YFC1807200)the National Natural Science Foundation of China(Grant No.42072299).
文摘Conventional empirical equations for estimating undrained shear strength(s_(u))from piezocone penetration test(CPTu)data,without incorporating soil physical properties,often lack the accuracy and robustness required for geotechnical site investigations.This study introduces a hybrid virus colony search(VCS)algorithm that integrates the standard VCS algorithm with a mutation-based search mechanism to develop high-performance XGBoost learning models to address this limitation.A dataset of 372 seismic CPTu and corresponding soil physical properties data from 26 geotechnical projects in Jiangs_(u)Province,China,was collected for model development.Comparative evaluations demonstrate that the proposed hybrid VCS-XGBoost model exhibits s_(u)perior performance compared to standard meta-heuristic algorithm-based XGBoost models.The res_(u)lts highlight that the consideration of soil physical properties significantly improves the predictive accuracy of s_(u),emphasizing the importance of considering additional soil information beyond CPTu data for accurate s_(u)estimation.
基金funded by the Tsinghua Shenzhen International Graduate School Research Startup Funds[item number:01030100009].
文摘MICP(Microbially induced calcite precipitation),an environmentally friendly soil improvement technique,has great potential in ocean engineering due to its ability to promote the precipitation of calcium carbonate through microbial activity to enhance the engineering properties of geomaterials.In this study,piezocone penetration test(CPTU)is used to evaluate the effectiveness of MICP treatment in calcareous sand.The change of physical properties(relative density D and total unit weight)of MICP treated calcareous sand is investigated by conducting CPTU on the geomaterials prepared in a series of mini calibration chambers(25 cm×50 cm).Results indicate that CPTU(tip stress,sleeve friction,and porewater pressure)measurements can be used to interpret the physical characteristics of calcareous sand treated with MICP under seawater conditions.Additionally,a relationship between CPTU measurements,physical parameters(relative density D,and total unit weight y)of MICP treated calcareous sand is proposed and calibrated.The findings of the research extend the implementation of in-situ testing techniques such as CPTU towards physical property evaluation of bio-treated geomaterials in ocean environment,and demonstrate the potential of scaling up MICP techniques for broader engineeringapplication.
基金supported by the China Postdoctoral Science Foundation(Grant No.2024M760734)National Science Fund for Distinguished Young Scholars(Grant No.42225206)the National Natural Science Foundation of China(Grant Nos.41877231 and 42072299).
文摘With the increasing construction of port facilities,cross-sea bridges,and offshore engineering projects,uplift piles embedded in marine sedimentary soft soil are becoming increasingly necessary.The load-displacement curve of uplift piles is crucial for evaluating their uplift bearing characteristics,which facilitates the risk evaluation,design,and construction of large infrastructural supports.In this study,a load-displacement curve model based on piezocone penetration test(CPTU)data is proposed via the load transfer method.Experimental tests are conducted to analyze the uplift bearing characteristics and establish a correlation between the proposed model and CPTU data.The results of the proposed load-displacement curve are compared with the results from numerical simulations and those calculated by previous methods.The results show that the proposed curves appropriately evaluated the uplift bearing characteristics and improved the accuracy in comparison with previous methods.
基金funding of this research by the German Research Foundation(Deutsche Forschungsgemeinschaft,DFG)in the framework of Research Training Group GRK 2462:Processes in natural and technical Particle-Fluid-Systems at Hamburg University of Technology(TUHH).
文摘The water drop penetration time(WDPT)test consists of placing water drops on a material's surface in order to evaluate how long it takes to penetrate the pores.It is used to evaluate the hydrophobicity of materials.This study aims at investigating in more detail the soil-water interaction during the test,exposing its mechanism.For that,a model soil named Hamburg Sand was coated with a hydrophobic fluoropolymer and then a WDPT test was performed while computed tomography(CT)images were taken.Tomography experiments were performed at the P07 high-energy materials science(HEMS)beamline,operated by Helmholtz–Zentrum Hereon,at the storage ring PETRA III at the Deutsches Elektronen-Synchrotron(DESY)in Hamburg.Using synchrotron radiation,a tomogram can be obtained in about 10 min,way less time than regular laboratory X-ray sources usually owned by universities.The faster imaging enables the observation of the drop penetration during time and thus provides insight into the dynamics of the process.After that,digital discrete image correlation is performed to track the displacement of the grains throughout time.From the results one can observe that,as the drop is absorbed at the material's surface,the grains directly around the droplet base are dragged to the liquid-air interface around the drop,revealing grain kinematics during capillary interactions of the penetrating liquid and sand grains.
文摘The methodology of predicting pile shaft skin ultimate friction has been studied in a systematic way. In the light of that, the analysis of the pile shaft resistance for bored and cast in situ piles in cohesive soils was carried out thoroughly in the basis of field performance data of 10 fully instrumented large diameter bored piles (LDBPs) used as the bridge foundation. The undrained strength index μ in term of cohesive soils was brought forward in allusion to the cohesive soils in the consistence plastic state, and can effectively combine the friction angle and the cohesion of cohesive soils in undrained condition. And that the classical ' α method' was modified much in effect to predict the pile shaft skin friction of LDBPs in cohesive soils. Furthermore, the approach of standard penetration test (SPT) N value used to estimate the pile shaft skin ultimate friction was analyzed, and the calculating formulae were established for LDBPs in clay and silt clay respectively.
基金Projects(2016YFE0200100,2018YFC1505300-5.3)supported by the National Key Research&Development Plan of ChinaProject(51639002)supported by the Key Program of National Natural Science Foundation of China
文摘Discernment of seismic soil liquefaction is a complex and non-linear procedure that is affected by diversified factors of uncertainties and complexity.The Bayesian belief network(BBN)is an effective tool to present a suitable framework to handle insights into such uncertainties and cause–effect relationships.The intention of this study is to use a hybrid approach methodology for the development of BBN model based on cone penetration test(CPT)case history records to evaluate seismic soil liquefaction potential.In this hybrid approach,naive model is developed initially only by an interpretive structural modeling(ISM)technique using domain knowledge(DK).Subsequently,some useful information about the naive model are embedded as DK in the K2 algorithm to develop a BBN-K2 and DK model.The results of the BBN models are compared and validated with the available artificial neural network(ANN)and C4.5 decision tree(DT)models and found that the BBN model developed by hybrid approach showed compatible and promising results for liquefaction potential assessment.The BBN model developed by hybrid approach provides a viable tool for geotechnical engineers to assess sites conditions susceptible to seismic soil liquefaction.This study also presents sensitivity analysis of the BBN model based on hybrid approach and the most probable explanation of liquefied sites,owing to know the most likely scenario of the liquefaction phenomenon.
文摘Determining the liquefaction potential of soil is important in earthquake engineering. This study proposes the use of the Relevance Vector Machine （RVM） to determine the liquefaction potential of soil by using actual cone penetration test （CPT） data. RVM is based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. The results are compared with a widely used artificial neural network （ANN） model. Overall, the RVM shows good performance and is proven to be more accurate than the ANN model. It also provides probabilistic output. The model provides a viable tool for earthquake engineers to assess seismic conditions for sites that are susceptible to liquefaction.
文摘In this study, th e least sq u are su p p o rt v ecto r m achine （LSSVM） alg o rith m w as applied to predicting th ebearing capacity o f b ored piles e m b ed d ed in sand an d m ixed soils. Pile g eo m etry an d cone p e n e tra tio nte s t （CPT） resu lts w ere used as in p u t variables for pred ictio n o f pile bearin g capacity. The d ata u se d w erecollected from th e existing litera tu re an d consisted o f 50 case records. The application o f LSSVM w ascarried o u t by dividing th e d ata into th re e se ts： a train in g se t for learning th e pro b lem an d obtain in g arelationship b e tw e e n in p u t variables an d pile bearin g capacity, and testin g an d validation sets forevaluation o f th e predictive an d g en eralization ability o f th e o b tain ed relationship. The predictions o f pilebearing capacity by LSSVM w ere evaluated by com paring w ith ex p erim en tal d ata an d w ith th o se bytrad itio n al CPT-based m eth o d s and th e gene ex pression pro g ram m in g （GEP） m odel. It w as found th a t th eLSSVM perform s w ell w ith coefficient o f d eterm in atio n , m ean, an d sta n d ard dev iatio n equivalent to 0.99,1.03, an d 0.08, respectively, for th e testin g set, an d 1, 1.04, an d 0.11, respectively, for th e v alidation set. Thelow values o f th e calculated m ean squared e rro r an d m ean ab so lu te e rro r indicated th a t th e LSSVM w asaccurate in p redicting th e pile bearing capacity. The results o f com parison also show ed th a t th e p roposedalg o rith m p red icted th e pile bearin g capacity m ore accurately th a n th e trad itio n al m eth o d s including th eGEP m odel.
基金Project(51278451) supported by the National Natural Science Foundation of ChinaProject(LZ12E09001) supported by the Zhejiang Natural Science Foundation,China
文摘Cone penetration test(CPT)is an appropriate technique for quickly determining the geotechnical properties of lunar soil,which is valuable for in situ lunar exploration.Utilizing a typical coupling method recently developed by the authors,a finite element method(FEM)-discrete element method(DEM)coupled model of CPTs is obtained.A series of CPTs in lunar soil are simulated to qualitatively reveal the flow of particles and the development of resistance throughout the penetration process.In addition,the effects of major factors,such as penetration velocity,penetration depth,cone tip angle,and the low gravity on the Moon surface are investigated.
