Strontium titanate(SrTiO_(3))is a thermoelectric material with large Seebeck coefficient that has potential applications in high-temperature power generators.To simultaneously achieve a low thermal conductivity and hi...Strontium titanate(SrTiO_(3))is a thermoelectric material with large Seebeck coefficient that has potential applications in high-temperature power generators.To simultaneously achieve a low thermal conductivity and high electrical conductivity,polycrystalline SrTiO_(3)with a multi-scale architecture was designed by the co-doping with lanthanum,cerium,and niobium.High-quality nano-powders were synthesized via a hydrothermal method.Nano-inclusions and a nano/micro-sized second phase precipitated during sintering to form mosaic crystal-like and epitaxial-like structures,which decreased the thermal conductivity.Substituting trivalent Ce and/or La with divalent Sr and substituting pentavalent Nb with tetravalent Ti enhanced the electrical conductivity without decreasing the Seebeck coefficient.By optimizing the dopant type and ratio,a low thermal conductivity of 2.77 W·m^(-1)·K^(-1)and high PF of 1.1 mW·m^(-1)·K^(-2)at 1000 K were obtained in the sample co-doped with 5-mol%La,5-mol%Ce,and 5-mol%Nb,which induced a large ZT of 0.38 at 1000 K.展开更多
Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer ...Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer composite plate by explosive welding.The microscopic properties of each bonding interface were elucidated through field emission scanning electron microscope and electron backscattered diffraction(EBSD).A methodology combining finite element method-smoothed particle hydrodynamics(FEM-SPH)and molecular dynamics(MD)was proposed for the analysis of the forming and evolution characteristics of explosive welding interfaces at multi-scale.The results demonstrate that the bonding interface morphologies of TC4/Al 6063 and Al 6063/Al 7075 exhibit a flat and wavy configuration,without discernible defects or cracks.The phenomenon of grain refinement is observed in the vicinity of the two bonding interfaces.Furthermore,the degree of plastic deformation of TC4 and Al 7075 is more pronounced than that of Al 6063 in the intermediate layer.The interface morphology characteristics obtained by FEM-SPH simulation exhibit a high degree of similarity to the experimental results.MD simulations reveal that the diffusion of interfacial elements predominantly occurs during the unloading phase,and the simulated thickness of interfacial diffusion aligns well with experimental outcomes.The introduction of intermediate layer in the explosive welding process can effectively produce high-quality titanium/aluminum alloy composite plates.Furthermore,this approach offers a multi-scale simulation strategy for the study of explosive welding bonding interfaces.展开更多
The influence of homogenization parameters on element segregation,dendritic structure,and the precipitate evolution in the GH3535-0.08wt%Y alloy was investigated.Additionally,some specific homogenization parameters we...The influence of homogenization parameters on element segregation,dendritic structure,and the precipitate evolution in the GH3535-0.08wt%Y alloy was investigated.Additionally,some specific homogenization parameters were maintained constant throughout the experiments.Results indicate that the heat treatment at 1150℃for 10 h is the optimal homogenization condition.Following this optimal treatment,dendrite structures and element segregation are eliminated.Furthermore,both SiC and Y_(5)Si_(3)precipitates in the as-cast alloy decrease significantly.Conversely,the homogenization at 1188℃induces overheating defects within the alloy.Although SiC and Y_(5)Si_(3)phases also decrease,some large M6C phases can still be observed,adversely affecting subsequent forging processes.展开更多
The combustion behavior of Ti-Al-Mo-Zr-Sn-W alloy(TC25G)was studied in a high-temperature and high-speed air flow environment using the laser ignition method combined with ultra-high temperature infrared thermometer,s...The combustion behavior of Ti-Al-Mo-Zr-Sn-W alloy(TC25G)was studied in a high-temperature and high-speed air flow environment using the laser ignition method combined with ultra-high temperature infrared thermometer,scanning electron microscope,X-ray diffractometer,and transmission electron microscope.The burn-resistant performance of TC25G and TC11 alloys was compared.Meanwhile,the microstructural characteristics,crystal structure,and formation mechanism of the combustion products of TC25G alloy were analyzed in detail.The results show that the high-temperature and high-speed air flow promotes combustion within the air flow temperature range of 200–400℃and the air flow velocity range of 0–100 m/s.The combustion path advances along the direction of the air flow.The combustion of TC25G alloy mainly relies on the diffusion of the oxygen and the expansion of the combustion area caused by the movement of the melt.Based on the microstructure and composition of combustion product,it can be divided into the combustion zone,the melting zone,and the heat affected zone.During combustion,the formation of microstructures is closely correlated with the behavior of alloying elements and their selective combination with O.The major oxidation products of Ti are TiO and TiO_(2).The oxides formed by Mo and W hinder the movement of the melt during the combustion.Al and Zr tend to undergo internal oxidation.Al_(2)O_(3)precipitates on the surface of ZrO_(2),forming a protective oxide layer that inhibits the inward diffusion of O.Moreover,the element enrichment at the interface between the melting zone and the heat affected zone increases the melting point on the solid side,hindering the migration of the solid-liquid interface.展开更多
To investigate the influence of Al-Zn-Mg-Cu alloy with as-homogenized and as-rolled initial microstructures on the tensile flow behavior,isothermal tensile tests were conducted on a GLEEBLE-3500 isothermal simulator a...To investigate the influence of Al-Zn-Mg-Cu alloy with as-homogenized and as-rolled initial microstructures on the tensile flow behavior,isothermal tensile tests were conducted on a GLEEBLE-3500 isothermal simulator at temperatures of 380-440℃and strain rates of 0.05-1 s^(−1).The Johnson-Cook model,Hensel-Spittel model,strain-compensated Arrhenius model,and critical fracture strain model were established.Results show that through the evaluation of the models using the correlation coefficient(R)and the average absolute relative error,the strain-compensated Arrhenius model can represent the flow behavior of the alloy more accurately.Shear bands are more pronounced in the as-homogenized specimens,whereas dynamic recrystallization is predominantly observed in as-rolled specimens.Fracture morphology analysis reveals that a mixed fracture mechanism is prevalent in the as-homogenized specimen,whereas a ductile fracture mechanism is predominant in the as-rolled specimen.The processing maps indicate that the unstable region is reduced in the as-rolled specimens compared with that in the as-homogenized specimens.The optimal hot working windows for the as-homogenized and as-rolled specimens are determined as 410-440℃/0.14-1 s^(−1)and 380-400℃/0.05-0.29 s^(−1),respectively.展开更多
The core-shell structure in bulk TiNb binary alloy was designed and studied by phase-field simulations,where various core-shell structures were obtained by precise control of the initial and boundary conditions of the...The core-shell structure in bulk TiNb binary alloy was designed and studied by phase-field simulations,where various core-shell structures were obtained by precise control of the initial and boundary conditions of the TiNb binary alloy system during spinodal decomposition,and then the formation mechanism of core-shell structure was revealed.In addition,the influences of initial temperature gradient,average temperature,and initial concentration distribution of the system on the core-shell structure were investigated.Results show that the initial concentration gradient is the key factor for forming the core-shell structure.Besides,larger initial temperature gradient and higher average temperature can promote the formation of core-shell structure,which can be stabilized by adjusting the initial concentration distribution of the Nb-rich region in TiNb binary alloy.As a theoretical basis,this research provides a novel and simple strategy for the preparation of TiNb-based alloys and other materials with peculiar core-shell structures and desirable mechanical and physical properties.展开更多
Dissimilar AZ31B magnesium alloy and DC56D steel were welded via AA1060 aluminum alloy by magnetic pulse welding.The effects of primary and secondary welding processes on the welded interface were comparatively invest...Dissimilar AZ31B magnesium alloy and DC56D steel were welded via AA1060 aluminum alloy by magnetic pulse welding.The effects of primary and secondary welding processes on the welded interface were comparatively investigated.Macroscopic morphology,microstructure,and interfacial structure of the joints were analyzed using scanning electron microscope,energy dispersive spectrometer,and X-ray diffractometer(XRD).The results show that magnetic pulse welding of dissimilar Mg/Fe metals is achieved using an Al interlayer,which acts as a bridge for deformation and diffusion.Specifically,the AZ31B/AA1060 interface exhibits a typical wavy morphology,and a transition zone exists at the joint interface,which may result in an extremely complex microstructure.The microstructure of this transition zone differs from that of AZ31B magnesium and 1060 Al alloys,and it is identified as brittle intermetallic compounds(IMCs)Al_(3)Mg_(2) and Al_(12)Mg_(17).The transition zone is mainly distributed on the Al side,with the maximum thickness of Al-side transition layer reaching approximately 13.53μm.Incomplete melting layers with varying thicknesses are observed at the primary weld interface,while micron-sized hole defects appear in the transition zone of the secondary weld interface.The AA1060/DC56D interface is mainly straight,with only a small number of discontinuous transition zones distributed intermittently along the interface.These transition zones are characterized by the presence of the brittle IMC FeAl_(3),with a maximum thickness of about 4μm.展开更多
A multi-physics approach was used to quantify the effect of process parameters (laser power, scanning speed, hatch spacing, and scanning strategy) on the thermal history and corresponding microstructure evolution of T...A multi-physics approach was used to quantify the effect of process parameters (laser power, scanning speed, hatch spacing, and scanning strategy) on the thermal history and corresponding microstructure evolution of Ti-25Nb (at%) alloy during the dual-track selective laser melting (SLM) process. Simulation results reveal that during the dual-track SLM process, increasing laser power results in greater thermal accumulation, leading to a molten pool of larger volume and coarser grains. Reducing scanning speed enhances remelting and promotes cellular growth at the top of molten pool, whereas faster scanning speed leads to rougher melt tracks and finer grains. Notably, hatch spacing significantly influences the molten pool dimensions and microstructures, and smaller hatch spacing promotes remelting. Furthermore, the orientations of grains in the second track during zigzag scanning differ markedly from those in the first track. More importantly, compared with those after the first track, both the temperature gradient and cooling rate at the boundaries of remelting molten pool are reduced after the second track scanning, resulting in slower interface velocity and significant change in solidification microstructure. This research provides a theoretical foundation for controlling non-equilibrium microstructure and offering novel insights into the optimization of SLM process parameters of titanium alloys.展开更多
Images taken in dim environments frequently exhibit issues like insufficient brightness,noise,color shifts,and loss of detail.These problems pose significant challenges to dark image enhancement tasks.Current approach...Images taken in dim environments frequently exhibit issues like insufficient brightness,noise,color shifts,and loss of detail.These problems pose significant challenges to dark image enhancement tasks.Current approaches,while effective in global illumination modeling,often struggle to simultaneously suppress noise and preserve structural details,especially under heterogeneous lighting.Furthermore,misalignment between luminance and color channels introduces additional challenges to accurate enhancement.In response to the aforementioned difficulties,we introduce a single-stage framework,M2ATNet,using the multi-scale multi-attention and Transformer architecture.First,to address the problems of texture blurring and residual noise,we design a multi-scale multi-attention denoising module(MMAD),which is applied separately to the luminance and color channels to enhance the structural and texture modeling capabilities.Secondly,to solve the non-alignment problem of the luminance and color channels,we introduce the multi-channel feature fusion Transformer(CFFT)module,which effectively recovers the dark details and corrects the color shifts through cross-channel alignment and deep feature interaction.To guide the model to learn more stably and efficiently,we also fuse multiple types of loss functions to form a hybrid loss term.We extensively evaluate the proposed method on various standard datasets,including LOL-v1,LOL-v2,DICM,LIME,and NPE.Evaluation in terms of numerical metrics and visual quality demonstrate that M2ATNet consistently outperforms existing advanced approaches.Ablation studies further confirm the critical roles played by the MMAD and CFFT modules to detail preservation and visual fidelity under challenging illumination-deficient environments.展开更多
Video emotion recognition is widely used due to its alignment with the temporal characteristics of human emotional expression,but existingmodels have significant shortcomings.On the one hand,Transformermultihead self-...Video emotion recognition is widely used due to its alignment with the temporal characteristics of human emotional expression,but existingmodels have significant shortcomings.On the one hand,Transformermultihead self-attention modeling of global temporal dependency has problems of high computational overhead and feature similarity.On the other hand,fixed-size convolution kernels are often used,which have weak perception ability for emotional regions of different scales.Therefore,this paper proposes a video emotion recognition model that combines multi-scale region-aware convolution with temporal interactive sampling.In terms of space,multi-branch large-kernel stripe convolution is used to perceive emotional region features at different scales,and attention weights are generated for each scale feature.In terms of time,multi-layer odd-even down-sampling is performed on the time series,and oddeven sub-sequence interaction is performed to solve the problem of feature similarity,while reducing computational costs due to the linear relationship between sampling and convolution overhead.This paper was tested on CMU-MOSI,CMU-MOSEI,and Hume Reaction.The Acc-2 reached 83.4%,85.2%,and 81.2%,respectively.The experimental results show that the model can significantly improve the accuracy of emotion recognition.展开更多
In a multiple voltage source converter(VSC)system,the nonlinear characteristics of phase-locked loops(PLLs)and their interactions have a significant influence on the synchronization stability of converters.In this pap...In a multiple voltage source converter(VSC)system,the nonlinear characteristics of phase-locked loops(PLLs)and their interactions have a significant influence on the synchronization stability of converters.In this paper,these influences are investigated from the perspective of the time domain.First,a novel time-domain model of the multi-VSC system is obtained by using a multi-scale method.On this basis,a stability criterion is proposed to assess the synchronization stability of the system.Then,the accuracy of the time-domain model and its stability criterion in various conditions are discussed.Moreover,the negative impact of the interaction on the system is quantified.Finally,the above theoretical analysis is also verified in the controller hardware-in-the-loop(CHIL)experiments.展开更多
Camouflaged Object Detection(COD)aims to identify objects that share highly similar patterns—such as texture,intensity,and color—with their surrounding environment.Due to their intrinsic resemblance to the backgroun...Camouflaged Object Detection(COD)aims to identify objects that share highly similar patterns—such as texture,intensity,and color—with their surrounding environment.Due to their intrinsic resemblance to the background,camouflaged objects often exhibit vague boundaries and varying scales,making it challenging to accurately locate targets and delineate their indistinct edges.To address this,we propose a novel camouflaged object detection network called Edge-Guided and Multi-scale Fusion Network(EGMFNet),which leverages edge-guided multi-scale integration for enhanced performance.The model incorporates two innovative components:a Multi-scale Fusion Module(MSFM)and an Edge-Guided Attention Module(EGA).These designs exploit multi-scale features to uncover subtle cues between candidate objects and the background while emphasizing camouflaged object boundaries.Moreover,recognizing the rich contextual information in fused features,we introduce a Dual-Branch Global Context Module(DGCM)to refine features using extensive global context,thereby generatingmore informative representations.Experimental results on four benchmark datasets demonstrate that EGMFNet outperforms state-of-the-art methods across five evaluation metrics.Specifically,on COD10K,our EGMFNet-P improves F_(β)by 4.8 points and reduces mean absolute error(MAE)by 0.006 compared with ZoomNeXt;on NC4K,it achieves a 3.6-point increase in F_(β).OnCAMO and CHAMELEON,it obtains 4.5-point increases in F_(β),respectively.These consistent gains substantiate the superiority and robustness of EGMFNet.展开更多
Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectra...Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectral similarity between buildings and backgrounds,sensor variations,and insufficient computational efficiency.To address these challenges,this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network(MewCDNet),which integrates the advantages of Convolutional Neural Networks and Transformers,balances computational costs,and achieves high-performance building change detection.The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction,integrates multi-level feature maps through a multi-scale fusion strategy,and incorporates two key modules:Cross-temporal Difference Detection(CTDD)and Cross-scale Wavelet Refinement(CSWR).CTDD adopts a dual-branch architecture that combines pixel-wise differencing with semanticaware Euclidean distance weighting to enhance the distinction between true changes and background noise.CSWR integrates Haar-based Discrete Wavelet Transform with multi-head cross-attention mechanisms,enabling cross-scale feature fusion while significantly improving edge localization and suppressing spurious changes.Extensive experiments on four benchmark datasets demonstrate MewCDNet’s superiority over comparison methods:achieving F1 scores of 91.54%on LEVIR,93.70%on WHUCD,and 64.96%on S2Looking for building change detection.Furthermore,MewCDNet exhibits optimal performance on the multi-class⋅SYSU dataset(F1:82.71%),highlighting its exceptional generalization capability.展开更多
In current research,Li_(2)O-Al_(2)O_(3)-SiO_(2)glass-ceramics were prepared by conventional meltquenching and subsequent heat treatment method.The effect of Al_(2)O_(3)content on microstructures,thermal properties,cry...In current research,Li_(2)O-Al_(2)O_(3)-SiO_(2)glass-ceramics were prepared by conventional meltquenching and subsequent heat treatment method.The effect of Al_(2)O_(3)content on microstructures,thermal properties,crystallization behaviours and mechanical properties were investigated.FTIR,Raman spectroscopy and nuclear magnetic resonance spectroscopy microstructure analysis showed that the silico-oxygen network was damaged,while the increase of[AlO_(4)]content repaired the glass network,and finally made the glass network have better connectivity,with the decrease of SiO_(2).The thermal analysis confirmed the increasing glass transition and crystallization temperatures from growing Al_(2)O_(3)content.In addition,different crystal phases can be precipitated in the glass matrix,such as LiAlSi_(4)O_(10),Li_(2)Si_(2)O_(5) in glass with low Al_(2)O_(3)content,the combination of Li_xAl_xSi_(1-x)O_(2),LiAlSi_(3)O_(8),Li_(2)SiO_(3)in glass with intermediate Al_(2)O_(3)content,and the combination of LiAlSi_(2)O_(6),SiO_(2)in glass with high Al_(2)O_(3)content.The hardness of as-prepared glass gradually increases with the increase of the Al_(2)O_(3)content.The Vickers hardness of the glass-ceramics is highly dependent on the Al_(2)O_(3)content in the glass and the heat treatment temperatures,reaching a maximum of 10.11 GPa.Scanning electron microscope images show that the crystals change from spherical to massive and finally to sheet.The change of glass structure,crystal phase and morphology is the main reason for the different mechanical properties.展开更多
Tomato is a major economic crop worldwide,and diseases on tomato leaves can significantly reduce both yield and quality.Traditional manual inspection is inefficient and highly subjective,making it difficult to meet th...Tomato is a major economic crop worldwide,and diseases on tomato leaves can significantly reduce both yield and quality.Traditional manual inspection is inefficient and highly subjective,making it difficult to meet the requirements of early disease identification in complex natural environments.To address this issue,this study proposes an improved YOLO11-based model,YOLO-SPDNet(Scale Sequence Fusion,Position-Channel Attention,and Dual Enhancement Network).The model integrates the SEAM(Self-Ensembling Attention Mechanism)semantic enhancement module,the MLCA(Mixed Local Channel Attention)lightweight attention mechanism,and the SPA(Scale-Position-Detail Awareness)module composed of SSFF(Scale Sequence Feature Fusion),TFE(Triple Feature Encoding),and CPAM(Channel and Position Attention Mechanism).These enhancements strengthen fine-grained lesion detection while maintaining model lightweightness.Experimental results show that YOLO-SPDNet achieves an accuracy of 91.8%,a recall of 86.5%,and an mAP@0.5 of 90.6%on the test set,with a computational complexity of 12.5 GFLOPs.Furthermore,the model reaches a real-time inference speed of 987 FPS,making it suitable for deployment on mobile agricultural terminals and online monitoring systems.Comparative analysis and ablation studies further validate the reliability and practical applicability of the proposed model in complex natural scenes.展开更多
Driven by rapid advances in deep learning,object detection has been widely adopted across diverse application scenarios.However,in low-light conditions,critical visual cues of target objects are severely degraded,posi...Driven by rapid advances in deep learning,object detection has been widely adopted across diverse application scenarios.However,in low-light conditions,critical visual cues of target objects are severely degraded,posing a significant challenge for accurate low-light object detection.Existing methods struggle to preserve discriminative features while maintaining semantic consistency between low-light and normal-light images.For this purpose,this study proposes a DL-YOLO model specially tailored for low-light detection.To mitigate target feature attenuation introduced by repeated downsampling,we design aMulti-Scale FeatureConvolution(MSF-Conv)module that captures rich,multi-level details via multi-scale feature learning,thereby reducing model complexity and computational cost.For feature fusion,we integrated the C3k2-DWRmodule by embedding the Dilation-wise Residual(DWR)mechanism into the 2-core optimized Cross Stage Partial(C3)framework,achieving efficient feature integration.In addition,we replace conventional localization losses with WIoU(Weighted Intersection over Union),which dynamically adjusts gradient gain according to sample quality,thereby improving localization robustness and precision.Experiments on the ExDark dataset demonstrate that DL-YOLO delivers strong low-light detection performance.The relevant code is published at https://github.com/cym0997/DL-YOLO.展开更多
Semantic segmentation for mixed scenes of aerial remote sensing and road traffic is one of the key technologies for visual perception of flying cars.The State-of-the-Art(SOTA)semantic segmentation methods have made re...Semantic segmentation for mixed scenes of aerial remote sensing and road traffic is one of the key technologies for visual perception of flying cars.The State-of-the-Art(SOTA)semantic segmentation methods have made remarkable achievements in both fine-grained segmentation and real-time performance.However,when faced with the huge differences in scale and semantic categories brought about by the mixed scenes of aerial remote sensing and road traffic,they still face great challenges and there is little related research.Addressing the above issue,this paper proposes a semantic segmentation model specifically for mixed datasets of aerial remote sensing and road traffic scenes.First,a novel decoding-recoding multi-scale feature iterative refinement structure is proposed,which utilizes the re-integration and continuous enhancement of multi-scale information to effectively deal with the huge scale differences between cross-domain scenes,while using a fully convolutional structure to ensure the lightweight and real-time requirements.Second,a welldesigned cross-window attention mechanism combined with a global information integration decoding block forms an enhanced global context perception,which can effectively capture the long-range dependencies and multi-scale global context information of different scenes,thereby achieving fine-grained semantic segmentation.The proposed method is tested on a large-scale mixed dataset of aerial remote sensing and road traffic scenes.The results confirm that it can effectively deal with the problem of large-scale differences in cross-domain scenes.Its segmentation accuracy surpasses that of the SOTA methods,which meets the real-time requirements.展开更多
The Qingtongxia Irrigation District in Ningxia is an important hydrological and ecological region.To assess its ecological environment quality from 2001 to 2021 across multiple scales and identify driving factors,a mo...The Qingtongxia Irrigation District in Ningxia is an important hydrological and ecological region.To assess its ecological environment quality from 2001 to 2021 across multiple scales and identify driving factors,a modified remote sensing ecological index(MRSEI)was developed by incorporating evapotranspiration.Spatial and temporal patterns were analyzed using the coefficient of variation,spatial autocorrelation,and semi-variogram methods,while influencing factors were explored via the optimal parameter geographical detector model.The MRSEI’s first principal component loadings and rankings aligned with those of RSEI(average contribution:81.31%),effectively reflecting spatiotemporal variations.At sub-irrigation district and landscape scales,ecological quality was slightly lower than at the district level but remained stable.Moderate and good ecological grades accounted for 36.28%and 33.38%of the area,respectively,at the district scale,and the moderate grade reached 70.48%on smaller scales.Spatial heterogeneity intensified with decreasing scale,and human activity lost explanatory power below a 5 km range.Human factors mainly drove ecological differentiation at the district scale,while natural factors dominated at finer scales.The MRSEI offers a novel tool for ecological assessment in arid/semi-arid areas and supports scale-adapted ecological protection strategies.展开更多
Distributed Denial of Service(DDoS)attacks are one of the severe threats to network infrastructure,sometimes bypassing traditional diagnosis algorithms because of their evolving complexity.PresentMachine Learning(ML)t...Distributed Denial of Service(DDoS)attacks are one of the severe threats to network infrastructure,sometimes bypassing traditional diagnosis algorithms because of their evolving complexity.PresentMachine Learning(ML)techniques for DDoS attack diagnosis normally apply network traffic statistical features such as packet sizes and inter-arrival times.However,such techniques sometimes fail to capture complicated relations among various traffic flows.In this paper,we present a new multi-scale ensemble strategy given the Graph Neural Networks(GNNs)for improving DDoS detection.Our technique divides traffic into macro-and micro-level elements,letting various GNN models to get the two corase-scale anomalies and subtle,stealthy attack models.Through modeling network traffic as graph-structured data,GNNs efficiently learn intricate relations among network entities.The proposed ensemble learning algorithm combines the results of several GNNs to improve generalization,robustness,and scalability.Extensive experiments on three benchmark datasets—UNSW-NB15,CICIDS2017,and CICDDoS2019—show that our approach outperforms traditional machine learning and deep learning models in detecting both high-rate and low-rate(stealthy)DDoS attacks,with significant improvements in accuracy and recall.These findings demonstrate the suggested method’s applicability and robustness for real-world implementation in contexts where several DDoS patterns coexist.展开更多
Fiber-optic sensing technology has the advantages of passivity, anti-electromagnetic interference, longdistancemeasurement, high sensitivity and high accuracy, small size, and adaptability to harsh environments such a...Fiber-optic sensing technology has the advantages of passivity, anti-electromagnetic interference, longdistancemeasurement, high sensitivity and high accuracy, small size, and adaptability to harsh environments such ashigh-vacuum, high-pressure, and strong magnetic fields compared with the traditional electrical sensing technology.However, with the increasing application requirements, how to further improve the sensitivity of fiber-optic sensors,extend the detection limit and improve the maintenance-free capability has become one of the core issues of thecurrent research. This paper reviews the principle, preparation, and application of fiber-optic microstructured sensingbased on abrupt field type. It specifically outlines the development and applications of micro-nano optical fibers,photonic crystal optical fibers, optical fiber gratings and structured optical fibers, and lists the main preparationmethods of two types of micro-nano optical fibers from the basic theory of optical fiber microstructured sensordevices.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.51702168 and 51532006).
文摘Strontium titanate(SrTiO_(3))is a thermoelectric material with large Seebeck coefficient that has potential applications in high-temperature power generators.To simultaneously achieve a low thermal conductivity and high electrical conductivity,polycrystalline SrTiO_(3)with a multi-scale architecture was designed by the co-doping with lanthanum,cerium,and niobium.High-quality nano-powders were synthesized via a hydrothermal method.Nano-inclusions and a nano/micro-sized second phase precipitated during sintering to form mosaic crystal-like and epitaxial-like structures,which decreased the thermal conductivity.Substituting trivalent Ce and/or La with divalent Sr and substituting pentavalent Nb with tetravalent Ti enhanced the electrical conductivity without decreasing the Seebeck coefficient.By optimizing the dopant type and ratio,a low thermal conductivity of 2.77 W·m^(-1)·K^(-1)and high PF of 1.1 mW·m^(-1)·K^(-2)at 1000 K were obtained in the sample co-doped with 5-mol%La,5-mol%Ce,and 5-mol%Nb,which induced a large ZT of 0.38 at 1000 K.
基金Opening Foundation of Key Laboratory of Explosive Energy Utilization and Control,Anhui Province(BP20240104)Graduate Innovation Program of China University of Mining and Technology(2024WLJCRCZL049)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_2701)。
文摘Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer composite plate by explosive welding.The microscopic properties of each bonding interface were elucidated through field emission scanning electron microscope and electron backscattered diffraction(EBSD).A methodology combining finite element method-smoothed particle hydrodynamics(FEM-SPH)and molecular dynamics(MD)was proposed for the analysis of the forming and evolution characteristics of explosive welding interfaces at multi-scale.The results demonstrate that the bonding interface morphologies of TC4/Al 6063 and Al 6063/Al 7075 exhibit a flat and wavy configuration,without discernible defects or cracks.The phenomenon of grain refinement is observed in the vicinity of the two bonding interfaces.Furthermore,the degree of plastic deformation of TC4 and Al 7075 is more pronounced than that of Al 6063 in the intermediate layer.The interface morphology characteristics obtained by FEM-SPH simulation exhibit a high degree of similarity to the experimental results.MD simulations reveal that the diffusion of interfacial elements predominantly occurs during the unloading phase,and the simulated thickness of interfacial diffusion aligns well with experimental outcomes.The introduction of intermediate layer in the explosive welding process can effectively produce high-quality titanium/aluminum alloy composite plates.Furthermore,this approach offers a multi-scale simulation strategy for the study of explosive welding bonding interfaces.
基金National Natural Science Foundation of China(51801227,52071331)。
文摘The influence of homogenization parameters on element segregation,dendritic structure,and the precipitate evolution in the GH3535-0.08wt%Y alloy was investigated.Additionally,some specific homogenization parameters were maintained constant throughout the experiments.Results indicate that the heat treatment at 1150℃for 10 h is the optimal homogenization condition.Following this optimal treatment,dendrite structures and element segregation are eliminated.Furthermore,both SiC and Y_(5)Si_(3)precipitates in the as-cast alloy decrease significantly.Conversely,the homogenization at 1188℃induces overheating defects within the alloy.Although SiC and Y_(5)Si_(3)phases also decrease,some large M6C phases can still be observed,adversely affecting subsequent forging processes.
基金China“Ye Qisun”Science Foundation Project of National Natural Science Foundation(U2141222)Innovation Fund(8F231527Z)。
文摘The combustion behavior of Ti-Al-Mo-Zr-Sn-W alloy(TC25G)was studied in a high-temperature and high-speed air flow environment using the laser ignition method combined with ultra-high temperature infrared thermometer,scanning electron microscope,X-ray diffractometer,and transmission electron microscope.The burn-resistant performance of TC25G and TC11 alloys was compared.Meanwhile,the microstructural characteristics,crystal structure,and formation mechanism of the combustion products of TC25G alloy were analyzed in detail.The results show that the high-temperature and high-speed air flow promotes combustion within the air flow temperature range of 200–400℃and the air flow velocity range of 0–100 m/s.The combustion path advances along the direction of the air flow.The combustion of TC25G alloy mainly relies on the diffusion of the oxygen and the expansion of the combustion area caused by the movement of the melt.Based on the microstructure and composition of combustion product,it can be divided into the combustion zone,the melting zone,and the heat affected zone.During combustion,the formation of microstructures is closely correlated with the behavior of alloying elements and their selective combination with O.The major oxidation products of Ti are TiO and TiO_(2).The oxides formed by Mo and W hinder the movement of the melt during the combustion.Al and Zr tend to undergo internal oxidation.Al_(2)O_(3)precipitates on the surface of ZrO_(2),forming a protective oxide layer that inhibits the inward diffusion of O.Moreover,the element enrichment at the interface between the melting zone and the heat affected zone increases the melting point on the solid side,hindering the migration of the solid-liquid interface.
文摘To investigate the influence of Al-Zn-Mg-Cu alloy with as-homogenized and as-rolled initial microstructures on the tensile flow behavior,isothermal tensile tests were conducted on a GLEEBLE-3500 isothermal simulator at temperatures of 380-440℃and strain rates of 0.05-1 s^(−1).The Johnson-Cook model,Hensel-Spittel model,strain-compensated Arrhenius model,and critical fracture strain model were established.Results show that through the evaluation of the models using the correlation coefficient(R)and the average absolute relative error,the strain-compensated Arrhenius model can represent the flow behavior of the alloy more accurately.Shear bands are more pronounced in the as-homogenized specimens,whereas dynamic recrystallization is predominantly observed in as-rolled specimens.Fracture morphology analysis reveals that a mixed fracture mechanism is prevalent in the as-homogenized specimen,whereas a ductile fracture mechanism is predominant in the as-rolled specimen.The processing maps indicate that the unstable region is reduced in the as-rolled specimens compared with that in the as-homogenized specimens.The optimal hot working windows for the as-homogenized and as-rolled specimens are determined as 410-440℃/0.14-1 s^(−1)and 380-400℃/0.05-0.29 s^(−1),respectively.
基金National Natural Science Foundation of China(12372152)Guangdong Basic and Applied Basic Research Foundation(2023A1515011819,2024A1515012469)Shandong Provincial Natural Science Foundation(ZR2023MA058)。
文摘The core-shell structure in bulk TiNb binary alloy was designed and studied by phase-field simulations,where various core-shell structures were obtained by precise control of the initial and boundary conditions of the TiNb binary alloy system during spinodal decomposition,and then the formation mechanism of core-shell structure was revealed.In addition,the influences of initial temperature gradient,average temperature,and initial concentration distribution of the system on the core-shell structure were investigated.Results show that the initial concentration gradient is the key factor for forming the core-shell structure.Besides,larger initial temperature gradient and higher average temperature can promote the formation of core-shell structure,which can be stabilized by adjusting the initial concentration distribution of the Nb-rich region in TiNb binary alloy.As a theoretical basis,this research provides a novel and simple strategy for the preparation of TiNb-based alloys and other materials with peculiar core-shell structures and desirable mechanical and physical properties.
文摘Dissimilar AZ31B magnesium alloy and DC56D steel were welded via AA1060 aluminum alloy by magnetic pulse welding.The effects of primary and secondary welding processes on the welded interface were comparatively investigated.Macroscopic morphology,microstructure,and interfacial structure of the joints were analyzed using scanning electron microscope,energy dispersive spectrometer,and X-ray diffractometer(XRD).The results show that magnetic pulse welding of dissimilar Mg/Fe metals is achieved using an Al interlayer,which acts as a bridge for deformation and diffusion.Specifically,the AZ31B/AA1060 interface exhibits a typical wavy morphology,and a transition zone exists at the joint interface,which may result in an extremely complex microstructure.The microstructure of this transition zone differs from that of AZ31B magnesium and 1060 Al alloys,and it is identified as brittle intermetallic compounds(IMCs)Al_(3)Mg_(2) and Al_(12)Mg_(17).The transition zone is mainly distributed on the Al side,with the maximum thickness of Al-side transition layer reaching approximately 13.53μm.Incomplete melting layers with varying thicknesses are observed at the primary weld interface,while micron-sized hole defects appear in the transition zone of the secondary weld interface.The AA1060/DC56D interface is mainly straight,with only a small number of discontinuous transition zones distributed intermittently along the interface.These transition zones are characterized by the presence of the brittle IMC FeAl_(3),with a maximum thickness of about 4μm.
基金Guangdong Basic and Applied Basic Research Foundation (2024A1515011873)Shenzhen Basic Research Project (JCYJ20241202123504007)Shenzhen Science and Technology Innovation Commission (KJZD20240903101400001, KJZD20240903102006009)。
文摘A multi-physics approach was used to quantify the effect of process parameters (laser power, scanning speed, hatch spacing, and scanning strategy) on the thermal history and corresponding microstructure evolution of Ti-25Nb (at%) alloy during the dual-track selective laser melting (SLM) process. Simulation results reveal that during the dual-track SLM process, increasing laser power results in greater thermal accumulation, leading to a molten pool of larger volume and coarser grains. Reducing scanning speed enhances remelting and promotes cellular growth at the top of molten pool, whereas faster scanning speed leads to rougher melt tracks and finer grains. Notably, hatch spacing significantly influences the molten pool dimensions and microstructures, and smaller hatch spacing promotes remelting. Furthermore, the orientations of grains in the second track during zigzag scanning differ markedly from those in the first track. More importantly, compared with those after the first track, both the temperature gradient and cooling rate at the boundaries of remelting molten pool are reduced after the second track scanning, resulting in slower interface velocity and significant change in solidification microstructure. This research provides a theoretical foundation for controlling non-equilibrium microstructure and offering novel insights into the optimization of SLM process parameters of titanium alloys.
基金funded by the National Natural Science Foundation of China,grant numbers 52374156 and 62476005。
文摘Images taken in dim environments frequently exhibit issues like insufficient brightness,noise,color shifts,and loss of detail.These problems pose significant challenges to dark image enhancement tasks.Current approaches,while effective in global illumination modeling,often struggle to simultaneously suppress noise and preserve structural details,especially under heterogeneous lighting.Furthermore,misalignment between luminance and color channels introduces additional challenges to accurate enhancement.In response to the aforementioned difficulties,we introduce a single-stage framework,M2ATNet,using the multi-scale multi-attention and Transformer architecture.First,to address the problems of texture blurring and residual noise,we design a multi-scale multi-attention denoising module(MMAD),which is applied separately to the luminance and color channels to enhance the structural and texture modeling capabilities.Secondly,to solve the non-alignment problem of the luminance and color channels,we introduce the multi-channel feature fusion Transformer(CFFT)module,which effectively recovers the dark details and corrects the color shifts through cross-channel alignment and deep feature interaction.To guide the model to learn more stably and efficiently,we also fuse multiple types of loss functions to form a hybrid loss term.We extensively evaluate the proposed method on various standard datasets,including LOL-v1,LOL-v2,DICM,LIME,and NPE.Evaluation in terms of numerical metrics and visual quality demonstrate that M2ATNet consistently outperforms existing advanced approaches.Ablation studies further confirm the critical roles played by the MMAD and CFFT modules to detail preservation and visual fidelity under challenging illumination-deficient environments.
基金supported,in part,by the National Nature Science Foundation of China under Grant 62272236,62376128in part,by the Natural Science Foundation of Jiangsu Province under Grant BK20201136,BK20191401.
文摘Video emotion recognition is widely used due to its alignment with the temporal characteristics of human emotional expression,but existingmodels have significant shortcomings.On the one hand,Transformermultihead self-attention modeling of global temporal dependency has problems of high computational overhead and feature similarity.On the other hand,fixed-size convolution kernels are often used,which have weak perception ability for emotional regions of different scales.Therefore,this paper proposes a video emotion recognition model that combines multi-scale region-aware convolution with temporal interactive sampling.In terms of space,multi-branch large-kernel stripe convolution is used to perceive emotional region features at different scales,and attention weights are generated for each scale feature.In terms of time,multi-layer odd-even down-sampling is performed on the time series,and oddeven sub-sequence interaction is performed to solve the problem of feature similarity,while reducing computational costs due to the linear relationship between sampling and convolution overhead.This paper was tested on CMU-MOSI,CMU-MOSEI,and Hume Reaction.The Acc-2 reached 83.4%,85.2%,and 81.2%,respectively.The experimental results show that the model can significantly improve the accuracy of emotion recognition.
基金supported by the Science and Technology Project of State Grid Corporation of China(5400-202199281A-0-0-00).
文摘In a multiple voltage source converter(VSC)system,the nonlinear characteristics of phase-locked loops(PLLs)and their interactions have a significant influence on the synchronization stability of converters.In this paper,these influences are investigated from the perspective of the time domain.First,a novel time-domain model of the multi-VSC system is obtained by using a multi-scale method.On this basis,a stability criterion is proposed to assess the synchronization stability of the system.Then,the accuracy of the time-domain model and its stability criterion in various conditions are discussed.Moreover,the negative impact of the interaction on the system is quantified.Finally,the above theoretical analysis is also verified in the controller hardware-in-the-loop(CHIL)experiments.
基金financially supported byChongqingUniversity of Technology Graduate Innovation Foundation(Grant No.gzlcx20253267).
文摘Camouflaged Object Detection(COD)aims to identify objects that share highly similar patterns—such as texture,intensity,and color—with their surrounding environment.Due to their intrinsic resemblance to the background,camouflaged objects often exhibit vague boundaries and varying scales,making it challenging to accurately locate targets and delineate their indistinct edges.To address this,we propose a novel camouflaged object detection network called Edge-Guided and Multi-scale Fusion Network(EGMFNet),which leverages edge-guided multi-scale integration for enhanced performance.The model incorporates two innovative components:a Multi-scale Fusion Module(MSFM)and an Edge-Guided Attention Module(EGA).These designs exploit multi-scale features to uncover subtle cues between candidate objects and the background while emphasizing camouflaged object boundaries.Moreover,recognizing the rich contextual information in fused features,we introduce a Dual-Branch Global Context Module(DGCM)to refine features using extensive global context,thereby generatingmore informative representations.Experimental results on four benchmark datasets demonstrate that EGMFNet outperforms state-of-the-art methods across five evaluation metrics.Specifically,on COD10K,our EGMFNet-P improves F_(β)by 4.8 points and reduces mean absolute error(MAE)by 0.006 compared with ZoomNeXt;on NC4K,it achieves a 3.6-point increase in F_(β).OnCAMO and CHAMELEON,it obtains 4.5-point increases in F_(β),respectively.These consistent gains substantiate the superiority and robustness of EGMFNet.
基金supported by the Henan Province Key R&D Project under Grant 241111210400the Henan Provincial Science and Technology Research Project under Grants 252102211047,252102211062,252102211055 and 232102210069+2 种基金the Jiangsu Provincial Scheme Double Initiative Plan JSS-CBS20230474,the XJTLU RDF-21-02-008the Science and Technology Innovation Project of Zhengzhou University of Light Industry under Grant 23XNKJTD0205the Higher Education Teaching Reform Research and Practice Project of Henan Province under Grant 2024SJGLX0126。
文摘Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectral similarity between buildings and backgrounds,sensor variations,and insufficient computational efficiency.To address these challenges,this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network(MewCDNet),which integrates the advantages of Convolutional Neural Networks and Transformers,balances computational costs,and achieves high-performance building change detection.The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction,integrates multi-level feature maps through a multi-scale fusion strategy,and incorporates two key modules:Cross-temporal Difference Detection(CTDD)and Cross-scale Wavelet Refinement(CSWR).CTDD adopts a dual-branch architecture that combines pixel-wise differencing with semanticaware Euclidean distance weighting to enhance the distinction between true changes and background noise.CSWR integrates Haar-based Discrete Wavelet Transform with multi-head cross-attention mechanisms,enabling cross-scale feature fusion while significantly improving edge localization and suppressing spurious changes.Extensive experiments on four benchmark datasets demonstrate MewCDNet’s superiority over comparison methods:achieving F1 scores of 91.54%on LEVIR,93.70%on WHUCD,and 64.96%on S2Looking for building change detection.Furthermore,MewCDNet exhibits optimal performance on the multi-class⋅SYSU dataset(F1:82.71%),highlighting its exceptional generalization capability.
基金Funded by the National Key Research Program(No.2024-1129-954-112)National Natural Science Foundation of China(No.52372033)Guangxi Science and Technology Major Program(No.AA24263054)。
文摘In current research,Li_(2)O-Al_(2)O_(3)-SiO_(2)glass-ceramics were prepared by conventional meltquenching and subsequent heat treatment method.The effect of Al_(2)O_(3)content on microstructures,thermal properties,crystallization behaviours and mechanical properties were investigated.FTIR,Raman spectroscopy and nuclear magnetic resonance spectroscopy microstructure analysis showed that the silico-oxygen network was damaged,while the increase of[AlO_(4)]content repaired the glass network,and finally made the glass network have better connectivity,with the decrease of SiO_(2).The thermal analysis confirmed the increasing glass transition and crystallization temperatures from growing Al_(2)O_(3)content.In addition,different crystal phases can be precipitated in the glass matrix,such as LiAlSi_(4)O_(10),Li_(2)Si_(2)O_(5) in glass with low Al_(2)O_(3)content,the combination of Li_xAl_xSi_(1-x)O_(2),LiAlSi_(3)O_(8),Li_(2)SiO_(3)in glass with intermediate Al_(2)O_(3)content,and the combination of LiAlSi_(2)O_(6),SiO_(2)in glass with high Al_(2)O_(3)content.The hardness of as-prepared glass gradually increases with the increase of the Al_(2)O_(3)content.The Vickers hardness of the glass-ceramics is highly dependent on the Al_(2)O_(3)content in the glass and the heat treatment temperatures,reaching a maximum of 10.11 GPa.Scanning electron microscope images show that the crystals change from spherical to massive and finally to sheet.The change of glass structure,crystal phase and morphology is the main reason for the different mechanical properties.
基金Tianmin Tianyuan Boutique Vegetable Industry Technology Service Station(Grant No.2024120011003081)Development of Environmental Monitoring and Traceability System for Wuqing Agricultural Production Areas(Grant No.2024120011001866)。
文摘Tomato is a major economic crop worldwide,and diseases on tomato leaves can significantly reduce both yield and quality.Traditional manual inspection is inefficient and highly subjective,making it difficult to meet the requirements of early disease identification in complex natural environments.To address this issue,this study proposes an improved YOLO11-based model,YOLO-SPDNet(Scale Sequence Fusion,Position-Channel Attention,and Dual Enhancement Network).The model integrates the SEAM(Self-Ensembling Attention Mechanism)semantic enhancement module,the MLCA(Mixed Local Channel Attention)lightweight attention mechanism,and the SPA(Scale-Position-Detail Awareness)module composed of SSFF(Scale Sequence Feature Fusion),TFE(Triple Feature Encoding),and CPAM(Channel and Position Attention Mechanism).These enhancements strengthen fine-grained lesion detection while maintaining model lightweightness.Experimental results show that YOLO-SPDNet achieves an accuracy of 91.8%,a recall of 86.5%,and an mAP@0.5 of 90.6%on the test set,with a computational complexity of 12.5 GFLOPs.Furthermore,the model reaches a real-time inference speed of 987 FPS,making it suitable for deployment on mobile agricultural terminals and online monitoring systems.Comparative analysis and ablation studies further validate the reliability and practical applicability of the proposed model in complex natural scenes.
文摘Driven by rapid advances in deep learning,object detection has been widely adopted across diverse application scenarios.However,in low-light conditions,critical visual cues of target objects are severely degraded,posing a significant challenge for accurate low-light object detection.Existing methods struggle to preserve discriminative features while maintaining semantic consistency between low-light and normal-light images.For this purpose,this study proposes a DL-YOLO model specially tailored for low-light detection.To mitigate target feature attenuation introduced by repeated downsampling,we design aMulti-Scale FeatureConvolution(MSF-Conv)module that captures rich,multi-level details via multi-scale feature learning,thereby reducing model complexity and computational cost.For feature fusion,we integrated the C3k2-DWRmodule by embedding the Dilation-wise Residual(DWR)mechanism into the 2-core optimized Cross Stage Partial(C3)framework,achieving efficient feature integration.In addition,we replace conventional localization losses with WIoU(Weighted Intersection over Union),which dynamically adjusts gradient gain according to sample quality,thereby improving localization robustness and precision.Experiments on the ExDark dataset demonstrate that DL-YOLO delivers strong low-light detection performance.The relevant code is published at https://github.com/cym0997/DL-YOLO.
基金supported by the National Key Research and Development of China(No.2022YFB2503400).
文摘Semantic segmentation for mixed scenes of aerial remote sensing and road traffic is one of the key technologies for visual perception of flying cars.The State-of-the-Art(SOTA)semantic segmentation methods have made remarkable achievements in both fine-grained segmentation and real-time performance.However,when faced with the huge differences in scale and semantic categories brought about by the mixed scenes of aerial remote sensing and road traffic,they still face great challenges and there is little related research.Addressing the above issue,this paper proposes a semantic segmentation model specifically for mixed datasets of aerial remote sensing and road traffic scenes.First,a novel decoding-recoding multi-scale feature iterative refinement structure is proposed,which utilizes the re-integration and continuous enhancement of multi-scale information to effectively deal with the huge scale differences between cross-domain scenes,while using a fully convolutional structure to ensure the lightweight and real-time requirements.Second,a welldesigned cross-window attention mechanism combined with a global information integration decoding block forms an enhanced global context perception,which can effectively capture the long-range dependencies and multi-scale global context information of different scenes,thereby achieving fine-grained semantic segmentation.The proposed method is tested on a large-scale mixed dataset of aerial remote sensing and road traffic scenes.The results confirm that it can effectively deal with the problem of large-scale differences in cross-domain scenes.Its segmentation accuracy surpasses that of the SOTA methods,which meets the real-time requirements.
基金National Key Research&Development Program of China,No.2021YFC3201201Ningxia Key Research and Development Program(Special Talents),No.2023BSB03021+1 种基金Natural Science Foundation of Ningxia,No.2023AAC05014University First-Class Discipline Construction Project of Ningxia,No.NXYLXK2021A03。
文摘The Qingtongxia Irrigation District in Ningxia is an important hydrological and ecological region.To assess its ecological environment quality from 2001 to 2021 across multiple scales and identify driving factors,a modified remote sensing ecological index(MRSEI)was developed by incorporating evapotranspiration.Spatial and temporal patterns were analyzed using the coefficient of variation,spatial autocorrelation,and semi-variogram methods,while influencing factors were explored via the optimal parameter geographical detector model.The MRSEI’s first principal component loadings and rankings aligned with those of RSEI(average contribution:81.31%),effectively reflecting spatiotemporal variations.At sub-irrigation district and landscape scales,ecological quality was slightly lower than at the district level but remained stable.Moderate and good ecological grades accounted for 36.28%and 33.38%of the area,respectively,at the district scale,and the moderate grade reached 70.48%on smaller scales.Spatial heterogeneity intensified with decreasing scale,and human activity lost explanatory power below a 5 km range.Human factors mainly drove ecological differentiation at the district scale,while natural factors dominated at finer scales.The MRSEI offers a novel tool for ecological assessment in arid/semi-arid areas and supports scale-adapted ecological protection strategies.
文摘Distributed Denial of Service(DDoS)attacks are one of the severe threats to network infrastructure,sometimes bypassing traditional diagnosis algorithms because of their evolving complexity.PresentMachine Learning(ML)techniques for DDoS attack diagnosis normally apply network traffic statistical features such as packet sizes and inter-arrival times.However,such techniques sometimes fail to capture complicated relations among various traffic flows.In this paper,we present a new multi-scale ensemble strategy given the Graph Neural Networks(GNNs)for improving DDoS detection.Our technique divides traffic into macro-and micro-level elements,letting various GNN models to get the two corase-scale anomalies and subtle,stealthy attack models.Through modeling network traffic as graph-structured data,GNNs efficiently learn intricate relations among network entities.The proposed ensemble learning algorithm combines the results of several GNNs to improve generalization,robustness,and scalability.Extensive experiments on three benchmark datasets—UNSW-NB15,CICIDS2017,and CICDDoS2019—show that our approach outperforms traditional machine learning and deep learning models in detecting both high-rate and low-rate(stealthy)DDoS attacks,with significant improvements in accuracy and recall.These findings demonstrate the suggested method’s applicability and robustness for real-world implementation in contexts where several DDoS patterns coexist.
基金support by National Natural Science Foundation of China (Nos. 51606158, 12104402)
文摘Fiber-optic sensing technology has the advantages of passivity, anti-electromagnetic interference, longdistancemeasurement, high sensitivity and high accuracy, small size, and adaptability to harsh environments such ashigh-vacuum, high-pressure, and strong magnetic fields compared with the traditional electrical sensing technology.However, with the increasing application requirements, how to further improve the sensitivity of fiber-optic sensors,extend the detection limit and improve the maintenance-free capability has become one of the core issues of thecurrent research. This paper reviews the principle, preparation, and application of fiber-optic microstructured sensingbased on abrupt field type. It specifically outlines the development and applications of micro-nano optical fibers,photonic crystal optical fibers, optical fiber gratings and structured optical fibers, and lists the main preparationmethods of two types of micro-nano optical fibers from the basic theory of optical fiber microstructured sensordevices.
