The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical m...The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts.展开更多
Bit-plane decomposition makes images obtain a number of layers. According to the amount of data information, images are encrypted, and the paper proposes image encryption method with Chaotic Mapping based on multi-lay...Bit-plane decomposition makes images obtain a number of layers. According to the amount of data information, images are encrypted, and the paper proposes image encryption method with Chaotic Mapping based on multi-layer parameter disturbance. The advantage of multi-layer parameter disturbance is that it not only scrambles pixel location of images, but also changes pixel values of images. Bit-plane decomposition can increase the space of key. And using chaotic sequence generated by chaotic system with different complexities to encrypt layers with different information content can save operation time. The simulation experiments show that using chaotic mapping in image encryption method based on multi-layer parameter disturbance can cover plaintext effectively and safely, which makes it achieve ideal encryption effect.展开更多
The long awaited cloud computing concept is a reality now due to the transformation of computer generations.However,security challenges have become the biggest obstacles for the advancement of this emerging technology...The long awaited cloud computing concept is a reality now due to the transformation of computer generations.However,security challenges have become the biggest obstacles for the advancement of this emerging technology.A well-established policy framework is defined in this paper to generate security policies which are compliant to requirements and capabilities.Moreover,a federated policy management schema is introduced based on the policy definition framework and a multi-level policy application to create and manage virtual clusters with identical or common security levels.The proposed model consists in the design of a well-established ontology according to security mechanisms,a procedure which classifies nodes with common policies into virtual clusters,a policy engine to enhance the process of mapping requests to a specific node as well as an associated cluster and matchmaker engine to eliminate inessential mapping processes.The suggested model has been evaluated according to performance and security parameters to prove the efficiency and reliability of this multilayered engine in cloud computing environments during policy definition,application and mapping procedures.展开更多
At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-laye...At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool head.The material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum alloys.The results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center area.Repeated friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped zone.The tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition sample.It is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping area.The multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components.展开更多
目的基于T2^(*)mapping定量分析业余马拉松运动员足踝部关节软骨的T2^(*)值,并分析其与性别、年龄、身体质量指数(body mass index,BMI)、跑龄、跑量之间的相关性。材料与方法于2023年7月份至2023年9月份招募重庆市长跑运动爱好者48名,...目的基于T2^(*)mapping定量分析业余马拉松运动员足踝部关节软骨的T2^(*)值,并分析其与性别、年龄、身体质量指数(body mass index,BMI)、跑龄、跑量之间的相关性。材料与方法于2023年7月份至2023年9月份招募重庆市长跑运动爱好者48名,其中跑量<300 km/月的36例(中低跑量组),跑量≥300 km/月的12例(高跑量组)。所有受试者均进行单侧无症状踝关节的MRI扫描,扫描序列包括T2^(*)mapping多回波自旋回波(spin echo,SE)序列矢状位、质子密度加权成像脂肪抑制(proton density-weighted imaging fat-saturated,PDWI-FS)序列矢状位、冠状位、横轴位以及T1加权脂肪抑制成像(T1-weighted imaging fat-saturated,T1WI-FS)序列横轴位。沿关节软骨轮廓边缘勾画距骨穹窿、跟骰关节跟骨面、骰骨面及后距下关节跟骨面、距骨面软骨作为感兴趣区(region of interest,ROI),获得相应的T2^(*)值。采用线性回归分析软骨T2^(*)值与年龄、BMI、跑龄的相关性,采用独立样本t检验分析不同跑量及不同性别间的软骨T2^(*)值差异。结果(1)距骨穹窿、跟骰关节跟骨面及骰骨面、后距下关节跟骨面及距骨面软骨T2^(*)值在性别上的差异均具有统计学意义(P=0.001、P<0.001、P=0.002、P=0.008、P=0.004);(2)高跑量组的距骨穹窿、后距下关节跟骨面软骨T2^(*)值高于中低跑量组(P=0.014、0.023),不同跑量的跟骰关节跟骨面及骰骨面、后距下关节距骨面软骨T2^(*)值的差异均无统计学意义(P=0.987、0.072、0.724);(3)距骨穹窿、跟骰关节跟骨面及骰骨面、后距下关节跟骨面、距骨面软骨T2^(*)值均与BMI呈正相关(r=0.376、0.384、0.300、0.422、0.455,P=0.005、0.004、0.019、0.001、0.001)。结论在业余马拉松运动员这一跑步群体中,与中低跑量相比,高跑量更有可能导致距骨穹窿、后距下关节跟骨面软骨损伤;而与较低的BMI相比,高BMI增加了距骨穹窿、跟骰关节跟骨面、骰骨面及后距下关节跟骨面、距骨面软骨损伤的风险。展开更多
目的探讨心脏磁共振组织追踪(cardiac magnetic resonance tissue tracing,CMR-TT)技术及T1 mapping技术在2型糖尿病(type 2 diabetes mellitus,T2DM)患者心肌损伤评估中的应用价值。材料与方法前瞻性收集2023年12月至2025年4月在我院...目的探讨心脏磁共振组织追踪(cardiac magnetic resonance tissue tracing,CMR-TT)技术及T1 mapping技术在2型糖尿病(type 2 diabetes mellitus,T2DM)患者心肌损伤评估中的应用价值。材料与方法前瞻性收集2023年12月至2025年4月在我院进行心脏磁共振检查的T2DM患者64例,健康对照(healthy controls,HC)32例。所有心脏磁共振图像数据导入专用软件进行分析,获取全心心肌应变参数、双心室功能参数以及左心室T1 mapping参数,采用t检验,Mann-Whitney U检验及卡方检验对两组间上述参数进行比较,采用Pearson及Spearman相关性分析心肌结构、功能与心肌应变的关联。结果T2DM组左心室心肌质量指数(left ventricular myocardial mass index,LVMI)、左心室重塑指数(left ventricular remodeling index,LVRI)增加(均P<0.001),左心室全局纵向应变(global longitudinal peak strain in the left ventricle,LV GLS)、右心室全局纵向应变降低(均P<0.05),T2DM组周向左心室收缩期峰值应变率(peak systolic strain rate of the left ventricle,LV PSSR)、纵向LV PSSR及左心室舒张期峰值应变率(diastolic peak strain rate of the left ventricle,LV PDSR)绝对值均降低(均P<0.019)。T2DM患者左心房/右心房(leftatrium/rightatrium,LA/RA)储存应变、LA/RA导管应变均降低(均P<0.001)。T2DM患者的细胞外容积(extracellular volume,ECV)较HC组升高(P<0.001)。双心室射血分数、收缩末期容积指数与双心室应变功能均相关(均P<0.003)。LVMI与左心室全局径向应变(global radial strain of the left ventricle,LV GRS)、左心室全局周向应变(global circumferential strain of the left ventricle,LV GCS)、LV GLS、周向LV PSSR、纵向LV PSSR、径向LV PDSR、周向LV PDSR、纵向LV PDSR相关(均P<0.021)。左心室舒张末期容积指数与LV GCS、LV GLS、周向LV PSSR、纵向LV PSSR、周向LV PDSR相关(均P<0.044)。右心室舒张末期容积指数与右心室全局周向应变相关(r=0.331,P=0.007)。LVRI与LV GLS及纵向LV PDSR相关(均P<0.01),且与径向LV PSSR弱相关(r=0.266,P=0.034)。结论T2DM患者全心心肌应变较对照组降低,ECV值升高,双心室心肌结构、功能与心肌应变相互关联,CMR-TT及T1 mapping技术可以有效检测糖尿病心肌损伤。展开更多
An increasing number of drivers are relying on digital map navigation systems in vehicles or mobile phones to select optimal driving routes in order to save time and improve safety. In the near future, digital map nav...An increasing number of drivers are relying on digital map navigation systems in vehicles or mobile phones to select optimal driving routes in order to save time and improve safety. In the near future, digital map navigation systems are expected to play more important roles in transportation systems. In order to extend current navigation systems to more applications, two fundamental problems must be resolved: the lane-level map model and lane-level route planning. This study proposes solutions to both problems. The current limitation of the lane-level map model is not its accuracy but its flexibility;this study proposes a novel seven-layer map structure, called as Tsinghua map model, which is able to support autonomous driving in a flexible and efficient way. For lane-level route planning, we propose a hierarchical route-searching algorithm to accelerate the planning process, even in the presence of complicated lane networks. In addition, we model the travel costs allocated for lane-level road networks by analyzing vehicle maneuvers in traversing lanes, changing lanes, and turning at intersections. Tests were performed on both a grid network and a real lane-level road network to demonstrate the validity and efficiency of the proposed algorithm.展开更多
This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble lear...This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.展开更多
基金National Natural Science Foundation of China(52175237)。
文摘The key parameters that characterize the morphological quality of multi-layer and multi-pass metal laser deposited parts are the surface roughness and the error between the actual printing height and the theoretical model height.The Taguchi method was employed to establish the correlations between process parameter combinations and multi-objective characterization of metal deposition morphology(height error and roughness).Results show that using the signal-to-noise ratio and grey relational analysis,the optimal parameter combination for multi-layer and multi-pass deposition is determined as follows:laser power of 800 W,powder feeding rate of 0.3 r/min,step distance of 1.6 mm,and scanning speed of 20 mm/s.Subsequently,a Genetic Bayesian-back propagation(GB-BP)network is constructed to predict multi-objective responses.Compared with the traditional back propagation network,the GB-back propagation network improves the prediction accuracy of height error and surface roughness by 43.14%and 71.43%,respectively.This network can accurately predict the multi-objective characterization of morphological quality of multi-layer and multi-pass metal deposited parts.
文摘Bit-plane decomposition makes images obtain a number of layers. According to the amount of data information, images are encrypted, and the paper proposes image encryption method with Chaotic Mapping based on multi-layer parameter disturbance. The advantage of multi-layer parameter disturbance is that it not only scrambles pixel location of images, but also changes pixel values of images. Bit-plane decomposition can increase the space of key. And using chaotic sequence generated by chaotic system with different complexities to encrypt layers with different information content can save operation time. The simulation experiments show that using chaotic mapping in image encryption method based on multi-layer parameter disturbance can cover plaintext effectively and safely, which makes it achieve ideal encryption effect.
文摘The long awaited cloud computing concept is a reality now due to the transformation of computer generations.However,security challenges have become the biggest obstacles for the advancement of this emerging technology.A well-established policy framework is defined in this paper to generate security policies which are compliant to requirements and capabilities.Moreover,a federated policy management schema is introduced based on the policy definition framework and a multi-level policy application to create and manage virtual clusters with identical or common security levels.The proposed model consists in the design of a well-established ontology according to security mechanisms,a procedure which classifies nodes with common policies into virtual clusters,a policy engine to enhance the process of mapping requests to a specific node as well as an associated cluster and matchmaker engine to eliminate inessential mapping processes.The suggested model has been evaluated according to performance and security parameters to prove the efficiency and reliability of this multilayered engine in cloud computing environments during policy definition,application and mapping procedures.
基金supported by the National Key Research and Development Program of China(No.2022YFB3404700)the National Natural Science Foundation of China(Nos.52105313 and 52275299)+2 种基金the Research and Development Program of Beijing Municipal Education Commission,China(No.KM202210005036)the Natural Science Foundation of Chongqing,China(No.CSTB2023NSCQ-MSX0701)the National Defense Basic Research Projects of China(No.JCKY2022405C002).
文摘At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass components.In this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool head.The material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum alloys.The results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center area.Repeated friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped zone.The tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition sample.It is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping area.The multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components.
文摘目的探讨心脏磁共振组织追踪(cardiac magnetic resonance tissue tracing,CMR-TT)技术及T1 mapping技术在2型糖尿病(type 2 diabetes mellitus,T2DM)患者心肌损伤评估中的应用价值。材料与方法前瞻性收集2023年12月至2025年4月在我院进行心脏磁共振检查的T2DM患者64例,健康对照(healthy controls,HC)32例。所有心脏磁共振图像数据导入专用软件进行分析,获取全心心肌应变参数、双心室功能参数以及左心室T1 mapping参数,采用t检验,Mann-Whitney U检验及卡方检验对两组间上述参数进行比较,采用Pearson及Spearman相关性分析心肌结构、功能与心肌应变的关联。结果T2DM组左心室心肌质量指数(left ventricular myocardial mass index,LVMI)、左心室重塑指数(left ventricular remodeling index,LVRI)增加(均P<0.001),左心室全局纵向应变(global longitudinal peak strain in the left ventricle,LV GLS)、右心室全局纵向应变降低(均P<0.05),T2DM组周向左心室收缩期峰值应变率(peak systolic strain rate of the left ventricle,LV PSSR)、纵向LV PSSR及左心室舒张期峰值应变率(diastolic peak strain rate of the left ventricle,LV PDSR)绝对值均降低(均P<0.019)。T2DM患者左心房/右心房(leftatrium/rightatrium,LA/RA)储存应变、LA/RA导管应变均降低(均P<0.001)。T2DM患者的细胞外容积(extracellular volume,ECV)较HC组升高(P<0.001)。双心室射血分数、收缩末期容积指数与双心室应变功能均相关(均P<0.003)。LVMI与左心室全局径向应变(global radial strain of the left ventricle,LV GRS)、左心室全局周向应变(global circumferential strain of the left ventricle,LV GCS)、LV GLS、周向LV PSSR、纵向LV PSSR、径向LV PDSR、周向LV PDSR、纵向LV PDSR相关(均P<0.021)。左心室舒张末期容积指数与LV GCS、LV GLS、周向LV PSSR、纵向LV PSSR、周向LV PDSR相关(均P<0.044)。右心室舒张末期容积指数与右心室全局周向应变相关(r=0.331,P=0.007)。LVRI与LV GLS及纵向LV PDSR相关(均P<0.01),且与径向LV PSSR弱相关(r=0.266,P=0.034)。结论T2DM患者全心心肌应变较对照组降低,ECV值升高,双心室心肌结构、功能与心肌应变相互关联,CMR-TT及T1 mapping技术可以有效检测糖尿病心肌损伤。
基金the National Key Research and Development Program of China (2018YFB0105000)the National Natural Science Foundation of China (61773234 and U1864203)+2 种基金the Project of Tsinghua University and Toyota Joint Research Center for AI Technology of Automated Vehicle (TT2018-02)the International Science and Technology Cooperation Program of China (2016YFE0102200)the software developed in the Beijing Municipal Science and Technology Program (D171100005117001 and Z181100005918001).
文摘An increasing number of drivers are relying on digital map navigation systems in vehicles or mobile phones to select optimal driving routes in order to save time and improve safety. In the near future, digital map navigation systems are expected to play more important roles in transportation systems. In order to extend current navigation systems to more applications, two fundamental problems must be resolved: the lane-level map model and lane-level route planning. This study proposes solutions to both problems. The current limitation of the lane-level map model is not its accuracy but its flexibility;this study proposes a novel seven-layer map structure, called as Tsinghua map model, which is able to support autonomous driving in a flexible and efficient way. For lane-level route planning, we propose a hierarchical route-searching algorithm to accelerate the planning process, even in the presence of complicated lane networks. In addition, we model the travel costs allocated for lane-level road networks by analyzing vehicle maneuvers in traversing lanes, changing lanes, and turning at intersections. Tests were performed on both a grid network and a real lane-level road network to demonstrate the validity and efficiency of the proposed algorithm.
基金the University of Transport Technology under the project entitled“Application of Machine Learning Algorithms in Landslide Susceptibility Mapping in Mountainous Areas”with grant number DTTD2022-16.
文摘This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.
