Snow cover in mountainous areas is characterized by high reflectivity,strong spatial heterogeneity,rapid changes,and susceptibility to cloud interference.However,due to the limitations of a single sensor,it is challen...Snow cover in mountainous areas is characterized by high reflectivity,strong spatial heterogeneity,rapid changes,and susceptibility to cloud interference.However,due to the limitations of a single sensor,it is challenging to obtain high-resolution satellite remote sensing data for monitoring the dynamic changes of snow cover within a day.This study focuses on two typical data fusion methods for polar-orbiting satellites(Sentinel-3 SLSTR)and geostationary satellites(Himawari-9 AHI),and explores the snow cover detection accuracy of a multitemporal cloud-gap snow cover identification model(Loose data fusion)and the ESTARFM(Spatiotemporal data fusion).Taking the Qilian Mountains as the research area,the accuracy of two data fusion results was verified using the snow cover extracted from Landsat-8 SR products.The results showed that both data fusion models could effectively capture the spatiotemporal variations of snow cover,but the ESTARFM demonstrated superior performance.It not only obtained fusion images at any target time,but also extracted snow cover that was closer to the spatial distribution of real satellite images.Therefore,the ESTARFM was utilized to fuse images for hourly reconstruction of the snow cover on February 14–15,2023.It was found that the maximum snow cover area of this snowfall reached 83.84%of the Qilian Mountains area,and the melting rate of the snow was extremely rapid,with a change of up to 4.30%per hour of the study area.This study offers reliable high spatiotemporal resolution satellite remote sensing data for monitoring snow cover changes in mountainous areas,contributing to more accurate and timely assessments.展开更多
Multi-modal fusion technology gradually become a fundamental task in many fields,such as autonomous driving,smart healthcare,sentiment analysis,and human-computer interaction.It is rapidly becoming the dominant resear...Multi-modal fusion technology gradually become a fundamental task in many fields,such as autonomous driving,smart healthcare,sentiment analysis,and human-computer interaction.It is rapidly becoming the dominant research due to its powerful perception and judgment capabilities.Under complex scenes,multi-modal fusion technology utilizes the complementary characteristics of multiple data streams to fuse different data types and achieve more accurate predictions.However,achieving outstanding performance is challenging because of equipment performance limitations,missing information,and data noise.This paper comprehensively reviews existing methods based onmulti-modal fusion techniques and completes a detailed and in-depth analysis.According to the data fusion stage,multi-modal fusion has four primary methods:early fusion,deep fusion,late fusion,and hybrid fusion.The paper surveys the three majormulti-modal fusion technologies that can significantly enhance the effect of data fusion and further explore the applications of multi-modal fusion technology in various fields.Finally,it discusses the challenges and explores potential research opportunities.Multi-modal tasks still need intensive study because of data heterogeneity and quality.Preserving complementary information and eliminating redundant information between modalities is critical in multi-modal technology.Invalid data fusion methods may introduce extra noise and lead to worse results.This paper provides a comprehensive and detailed summary in response to these challenges.展开更多
Considerable efforts are being made to transition current lithium-ion and sodium-ion batteries towards the use of solid-state electrolytes.Computational methods,specifically nudged elastic band(NEB)and molecular dynam...Considerable efforts are being made to transition current lithium-ion and sodium-ion batteries towards the use of solid-state electrolytes.Computational methods,specifically nudged elastic band(NEB)and molecular dynamics(MD)methods,provide powerful tools for the design of solid-state electrolytes.The MD method is usually the choice for studying the materials involving complex multiple diffusion paths or having disordered structures.However,it relies on simulations at temperatures much higher than working temperature.This paper studies the reliability of the MD method using the system of Na diffusion in MgO as a benchmark.We carefully study the convergence behavior of the MD method and demonstrate that total effective simulation time of 12 ns can converge the calculated diffusion barrier to about 0.01 eV.The calculated diffusion barrier is 0.31 eV from both methods.The diffusion coefficients at room temperature are 4.3×10^(-9) cm^(2)⋅s^(−1) and 2.2×10^(-9) cm^(2)⋅s^(−1),respectively,from the NEB and MD methods.Our results justify the reliability of the MD method,even though high temperature simulations have to be employed to overcome the limitation on simulation time.展开更多
Thunderstorm wind gusts are small in scale,typically occurring within a range of a few kilometers.It is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather stations.There...Thunderstorm wind gusts are small in scale,typically occurring within a range of a few kilometers.It is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather stations.Therefore,it is necessary to establish thunderstorm wind gust identification techniques based on multisource high-resolution observations.This paper introduces a new algorithm,called thunderstorm wind gust identification network(TGNet).It leverages multimodal feature fusion to fuse the temporal and spatial features of thunderstorm wind gust events.The shapelet transform is first used to extract the temporal features of wind speeds from automatic weather stations,which is aimed at distinguishing thunderstorm wind gusts from those caused by synoptic-scale systems or typhoons.Then,the encoder,structured upon the U-shaped network(U-Net)and incorporating recurrent residual convolutional blocks(R2U-Net),is employed to extract the corresponding spatial convective characteristics of satellite,radar,and lightning observations.Finally,by using the multimodal deep fusion module based on multi-head cross-attention,the temporal features of wind speed at each automatic weather station are incorporated into the spatial features to obtain 10-minutely classification of thunderstorm wind gusts.TGNet products have high accuracy,with a critical success index reaching 0.77.Compared with those of U-Net and R2U-Net,the false alarm rate of TGNet products decreases by 31.28%and 24.15%,respectively.The new algorithm provides grid products of thunderstorm wind gusts with a spatial resolution of 0.01°,updated every 10minutes.The results are finer and more accurate,thereby helping to improve the accuracy of operational warnings for thunderstorm wind gusts.展开更多
In the article“A Lightweight Approach for Skin Lesion Detection through Optimal Features Fusion”by Khadija Manzoor,Fiaz Majeed,Ansar Siddique,Talha Meraj,Hafiz Tayyab Rauf,Mohammed A.El-Meligy,Mohamed Sharaf,Abd Ela...In the article“A Lightweight Approach for Skin Lesion Detection through Optimal Features Fusion”by Khadija Manzoor,Fiaz Majeed,Ansar Siddique,Talha Meraj,Hafiz Tayyab Rauf,Mohammed A.El-Meligy,Mohamed Sharaf,Abd Elatty E.Abd Elgawad Computers,Materials&Continua,2022,Vol.70,No.1,pp.1617–1630.DOI:10.32604/cmc.2022.018621,URL:https://www.techscience.com/cmc/v70n1/44361,there was an error regarding the affiliation for the author Hafiz Tayyab Rauf.Instead of“Centre for Smart Systems,AI and Cybersecurity,Staffordshire University,Stoke-on-Trent,UK”,the affiliation should be“Independent Researcher,Bradford,BD80HS,UK”.展开更多
Magnetostrictive Fe-Ga alloys have captivated substantial focus in biomedical applications because of their exceptional transition efficiency and favorable cytocompatibility.Nevertheless,Fe-Ga alloys always exhibit fr...Magnetostrictive Fe-Ga alloys have captivated substantial focus in biomedical applications because of their exceptional transition efficiency and favorable cytocompatibility.Nevertheless,Fe-Ga alloys always exhibit frustrating magnetostriction coefficients when presented in bulk dimensions.It is well-established that the magnetostrictive performance of Fe-Ga alloys is intimately linked to their phase and crystal structures.In this study,various concentrations of boron(B)were doped into Fe_(81)Ga_(19) alloys via the laser-beam powder bed fusion(LPBF)technique to tailor the crystal and phase structures,thereby improving the magnetostrictive performance.The results revealed the capacity for quick solidification of the LPBF process in expediting the solid solution of B element,which increased both lattice distortion and dislocations within the Fe-Ga matrix.These factors contributed to an elevation in the density of the modified-D0_(3) phase structure.Moreover,the prepared Fe-Ga-B alloys also exhibited a(001)preferred grain orientation caused by the high thermal gradients during the LPBF process.As a result,a maximum magnetostriction coefficient of 105 ppm was achieved in the(Fe_(81)Ga_(19))_(98.5)B_(1.5) alloy.In alternating magnetic fields,all the LPBF-prepared alloys showed good dynamic magnetostriction response without visible hysteresis,while the(Fe_(81)Ga_(19))_(98.5)B_(1.5) alloy presented a notable enhancement of~30%in magnetostriction coefficient when compared with the Fe_(81)Ga_(19) alloy.Moreover.the(Fe_(81)Ga_(19))_(98.5)B_(1.5) alloy exhibited favorable biocompatibility and osteogenesis,as confirmed by increased alkaline phosphatase(ALP)activity and the formation of mineralized nodules.These findings suggest that the B-doped Fe-Ga alloys combined with the LPBF technique hold promise for the development of bulk magnetostrictive alloys that are applicable for bone repair applications.展开更多
The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytica...The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.展开更多
This article explores the design of a wireless fire alarm system supported by advanced data fusion technology.It includes discussions on the basic design ideas of the wireless fire alarm system,hardware design analysi...This article explores the design of a wireless fire alarm system supported by advanced data fusion technology.It includes discussions on the basic design ideas of the wireless fire alarm system,hardware design analysis,software design analysis,and simulation analysis,all supported by data fusion technology.Hopefully,this analysis can provide some reference for the rational application of data fusion technology to meet the actual design and application requirements of the system.展开更多
This work investigated the anisotropy tensile properties of Inconel 625 alloy fabricated by laser powder bed fusion (LPBF) under various tests temperature, focusing the anisotropy evolution during the high temperature...This work investigated the anisotropy tensile properties of Inconel 625 alloy fabricated by laser powder bed fusion (LPBF) under various tests temperature, focusing the anisotropy evolution during the high temperature. The microstructure contained columnar grains with (111) texture in the vertical plane (90° sample), while a large equiaxed grain with (100) texture was produced in the horizontal plane (0° sample). As for 45° sample, a large number of equiaxed grains and a few columnar grains with (111) texture can be observed. The sample produced at a 0° orientation demonstrates the highest tensile strength, whereas the 90° sample exhibits the greatest elongation. Conversely, the 45° sample displays the least favorable overall performance. As the tests temperature increased from room temperature to 600℃, the anisotropy rate of ultimate tensile strength, yield strength and ductility between 0° and 45° samples, decreased from 8.98 to 6.96%, 2.36 to 1.28%, 19.93 to 12.23%, as well as between 0° and 90° samples decreased from 4.87 to 4.03%, 11.88 to 7.21% and 14.11 to 6.89%, respectively, because of the recovery of oriented columnar grains.展开更多
Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vi...Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.展开更多
Solar flare prediction is an important subject in the field of space weather.Deep learning technology has greatly promoted the development of this subject.In this study,we propose a novel solar flare forecasting model...Solar flare prediction is an important subject in the field of space weather.Deep learning technology has greatly promoted the development of this subject.In this study,we propose a novel solar flare forecasting model integrating Deep Residual Network(ResNet)and Support Vector Machine(SVM)for both≥C-class(C,M,and X classes)and≥M-class(M and X classes)flares.We collected samples of magnetograms from May 1,2010 to September 13,2018 from Space-weather Helioseismic and Magnetic Imager(HMI)Active Region Patches and then used a cross-validation method to obtain seven independent data sets.We then utilized five metrics to evaluate our fusion model,based on intermediate-output extracted by ResNet and SVM using the Gaussian kernel function.Our results show that the primary metric true skill statistics(TSS)achieves a value of 0.708±0.027 for≥C-class prediction,and of 0.758±0.042 for≥M-class prediction;these values indicate that our approach performs significantly better than those of previous studies.The metrics of our fusion model’s performance on the seven datasets indicate that the model is quite stable and robust,suggesting that fusion models that integrate an excellent baseline network with SVM can achieve improved performance in solar flare prediction.Besides,we also discuss the performance impact of architectural innovation in our fusion model.展开更多
Solar cell defect detection is crucial for quality inspection in photovoltaic power generation modules.In the production process,defect samples occur infrequently and exhibit random shapes and sizes,which makes it cha...Solar cell defect detection is crucial for quality inspection in photovoltaic power generation modules.In the production process,defect samples occur infrequently and exhibit random shapes and sizes,which makes it challenging to collect defective samples.Additionally,the complex surface background of polysilicon cell wafers complicates the accurate identification and localization of defective regions.This paper proposes a novel Lightweight Multiscale Feature Fusion network(LMFF)to address these challenges.The network comprises a feature extraction network,a multi-scale feature fusion module(MFF),and a segmentation network.Specifically,a feature extraction network is proposed to obtain multi-scale feature outputs,and a multi-scale feature fusion module(MFF)is used to fuse multi-scale feature information effectively.In order to capture finer-grained multi-scale information from the fusion features,we propose a multi-scale attention module(MSA)in the segmentation network to enhance the network’s ability for small target detection.Moreover,depthwise separable convolutions are introduced to construct depthwise separable residual blocks(DSR)to reduce the model’s parameter number.Finally,to validate the proposed method’s defect segmentation and localization performance,we constructed three solar cell defect detection datasets:SolarCells,SolarCells-S,and PVEL-S.SolarCells and SolarCells-S are monocrystalline silicon datasets,and PVEL-S is a polycrystalline silicon dataset.Experimental results show that the IOU of our method on these three datasets can reach 68.5%,51.0%,and 92.7%,respectively,and the F1-Score can reach 81.3%,67.5%,and 96.2%,respectively,which surpasses other commonly usedmethods and verifies the effectiveness of our LMFF network.展开更多
In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utili...In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.展开更多
BACKGROUND Ependymoma with lipomatous differentiation is a rare type of ependymoma.The ZFTA fusion-positive supratentorial ependymoma is a novel tumor type in the 2021 World Health Organization classification of centr...BACKGROUND Ependymoma with lipomatous differentiation is a rare type of ependymoma.The ZFTA fusion-positive supratentorial ependymoma is a novel tumor type in the 2021 World Health Organization classification of central nervous system tumors.ZFTA fusion-positive lipomatous ependymoma has not been reported to date.CASE SUMMARY We reported a case of a 15-year-old Chinese male who had a sudden convulsion lasting approximately six minutes.Magnetic resonance imaging showed a round cystic shadow of approximately 1.9 cm×1.5 cm×1.9 cm under the right parieto-occipital cortex.Microscopic examination showed characteristic perivascular pseudorosettes and adipose differentiation in the cytoplasm.Immunohisto-chemical staining showed that the tumor cells were negative for cytokeratin,NeuN,Syn and p53,but positive for GFAP,vimentin and S-100 protein.Signi-ficant punctate intracytoplasmic EMA immunoreactivity was observed.The level of Ki-67 was about 5%.Genetic analysis revealed ZFTA:RELA fusion.A cranio-tomy with total excision of the tumor was performed.The follow-up time was 36 months,no evidence of disease recurrence was found in magnetic resonance imaging.CONCLUSION Based on these findings,the patient was diagnosed as a ependymoma with ZFTA fusion and lipomatous differentiation.This case report provides information on the microscopic morphological features of ependymoma with ZFTA fusion and lipomatous differentiation,which can help pathologists to make a definitive diagnosis of this tumor.展开更多
To increase the strength of the laser powder-bed fusion (LPBF) Al-Si-based aluminum alloy, TiB_(2) ceramic particles were selected to be mixed with high-Mg content Al-Si-Mg-Zr powder, and then a novel TiB_(2)/Al-Si-Mg...To increase the strength of the laser powder-bed fusion (LPBF) Al-Si-based aluminum alloy, TiB_(2) ceramic particles were selected to be mixed with high-Mg content Al-Si-Mg-Zr powder, and then a novel TiB_(2)/Al-Si-Mg-Zr composite was fabricated using LPBF. The results indicated that a dense sample with a maximum relative density of 99.85% could be obtained by adjusting the LPBF process parameters. Incorporating TiB_(2) nanoparticles enhanced the powder's laser absorption rate, thereby raising the alloy's intrinsic heat treatment temperature and consequently facilitating the precipitation of Si and βʺ nanoparticles in the α-Al cells. Moreover, the rapid cooling process during LPBF resulted in numerous alloying elements with low-stacking fault energy dissolving in the α-Al matrix, thus promoting the formation of the 9R phase. After a 48 h direct aging treatment at 150℃, the strength of the alloy slightly increased due to the increase of nanoprecipitates. Both yield strength and ultimate tensile strength of the LPBF TiB_(2)/Al-Si-Mg-Zr alloy were significantly higher than that of other LPBF TiB_(2)-modified aluminum alloys with external addition.展开更多
While automatic image captioning systems have made notable progress in the past few years,generating captions that fully convey sentiment remains a considerable challenge.Although existing models achieve strong perfor...While automatic image captioning systems have made notable progress in the past few years,generating captions that fully convey sentiment remains a considerable challenge.Although existing models achieve strong performance in visual recognition and factual description,they often fail to account for the emotional context that is naturally present in human-generated captions.To address this gap,we propose the Sentiment-Driven Caption Generator(SDCG),which combines transformer-based visual and textual processing withmulti-level fusion.RoBERTa is used for extracting sentiment from textual input,while visual features are handled by the Vision Transformer(ViT).These features are fused using several fusion approaches,including Concatenation,Attention,Visual-Sentiment Co-Attention(VSCA),and Cross-Attention.Our experiments demonstrate that SDCG significantly outperforms baseline models such as the Generalized Image Transformer(GIT),which achieves 82.01%,and Bootstrapping Language-Image Pre-training(BLIP),which achieves 83.07%,in sentiment accuracy.While SDCG achieves 94.52%sentiment accuracy and improves scores in BLEU and ROUGE-L,the model demonstrates clear advantages.More importantly,the captions aremore natural,as they incorporate emotional cues and contextual awareness,making them resemble those written by a human.展开更多
The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method f...The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.展开更多
Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.Howev...Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.However,the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current,even resulting in blade fatigue and destructively interfering with grid stability.A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio(HDR).However,HDR is difficult to obtain due to the complex fluid-structure interaction(FSI).Therefore,a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures.The experimental and simulation methods used to identify and obtain the HDR quantitatively were described,placing emphasis on the experimental processes and simulation setups.Moreover,the accuracy and efficiency of different simulation methods were compared,and the modal work approach was recommended.The effects of key typical parameters,including flow velocity,angle of attack,gap,rotational speed,and cavitation,on the HDR were then summarized,and the suggestions on operating conditions were presented from the perspective of increasing the HDR.Subsequently,considering multiple flow parameters,several theoretical derivations and semi-empirical prediction formulas for HDR were introduced,and the accuracy and application were discussed.Based on the shortcomings of the existing research,the direction of future research was finally determined.The current work offers a clear understanding of the HDR of blade-like structures,which could improve the evaluation accuracy of flow-induced vibration in the design stage.展开更多
Semi-crystalline polymer laser powder bed fusion(L-PBF)has recently attracted increasing interest due to its potential for fabricating complex geometry.However,a more comprehensive understanding of the underlying phys...Semi-crystalline polymer laser powder bed fusion(L-PBF)has recently attracted increasing interest due to its potential for fabricating complex geometry.However,a more comprehensive understanding of the underlying physics during L-PBF is required to better control the properties of the final part.This work proposed a multi-layer numerical model to study the temperature and phase evolution during the polyamide-12(PA12)L-PBF process.The Descend and Parallel Chord methods were introduced to improve the convergence of the non-linear thermal solver.The level-set-based mesh adaptation strategy,governed by multi-physical fields,was applied to alleviate the calculation and accurately track the phase evolution.The processing simulation on the dog-bone model revealed that preheating temperature significantly influences the crystallization behavior.Finally,the multi-layer simulation demonstrated that such a developed numerical model can be used to study the phase transformation during powder layer updating and the cyclic laser sintering phenomena.Moreover,the numerical study suggested that crystallization occurs slowly during the L-PBF process.展开更多
基金funded by the National Natural Science Foundation of China(42361058)supported by the Science and Technology Program of Gansu Province(22YF7FA074)。
文摘Snow cover in mountainous areas is characterized by high reflectivity,strong spatial heterogeneity,rapid changes,and susceptibility to cloud interference.However,due to the limitations of a single sensor,it is challenging to obtain high-resolution satellite remote sensing data for monitoring the dynamic changes of snow cover within a day.This study focuses on two typical data fusion methods for polar-orbiting satellites(Sentinel-3 SLSTR)and geostationary satellites(Himawari-9 AHI),and explores the snow cover detection accuracy of a multitemporal cloud-gap snow cover identification model(Loose data fusion)and the ESTARFM(Spatiotemporal data fusion).Taking the Qilian Mountains as the research area,the accuracy of two data fusion results was verified using the snow cover extracted from Landsat-8 SR products.The results showed that both data fusion models could effectively capture the spatiotemporal variations of snow cover,but the ESTARFM demonstrated superior performance.It not only obtained fusion images at any target time,but also extracted snow cover that was closer to the spatial distribution of real satellite images.Therefore,the ESTARFM was utilized to fuse images for hourly reconstruction of the snow cover on February 14–15,2023.It was found that the maximum snow cover area of this snowfall reached 83.84%of the Qilian Mountains area,and the melting rate of the snow was extremely rapid,with a change of up to 4.30%per hour of the study area.This study offers reliable high spatiotemporal resolution satellite remote sensing data for monitoring snow cover changes in mountainous areas,contributing to more accurate and timely assessments.
基金supported by the Natural Science Foundation of Liaoning Province(Grant No.2023-MSBA-070)the National Natural Science Foundation of China(Grant No.62302086).
文摘Multi-modal fusion technology gradually become a fundamental task in many fields,such as autonomous driving,smart healthcare,sentiment analysis,and human-computer interaction.It is rapidly becoming the dominant research due to its powerful perception and judgment capabilities.Under complex scenes,multi-modal fusion technology utilizes the complementary characteristics of multiple data streams to fuse different data types and achieve more accurate predictions.However,achieving outstanding performance is challenging because of equipment performance limitations,missing information,and data noise.This paper comprehensively reviews existing methods based onmulti-modal fusion techniques and completes a detailed and in-depth analysis.According to the data fusion stage,multi-modal fusion has four primary methods:early fusion,deep fusion,late fusion,and hybrid fusion.The paper surveys the three majormulti-modal fusion technologies that can significantly enhance the effect of data fusion and further explore the applications of multi-modal fusion technology in various fields.Finally,it discusses the challenges and explores potential research opportunities.Multi-modal tasks still need intensive study because of data heterogeneity and quality.Preserving complementary information and eliminating redundant information between modalities is critical in multi-modal technology.Invalid data fusion methods may introduce extra noise and lead to worse results.This paper provides a comprehensive and detailed summary in response to these challenges.
基金supported by the National Natural Science Foundation of China (Grant Nos.12164019,11991060,12088101,and U1930402)the Natural Science Foundation of Jiangxi Province of China (Grant No.20212BAB201017).
文摘Considerable efforts are being made to transition current lithium-ion and sodium-ion batteries towards the use of solid-state electrolytes.Computational methods,specifically nudged elastic band(NEB)and molecular dynamics(MD)methods,provide powerful tools for the design of solid-state electrolytes.The MD method is usually the choice for studying the materials involving complex multiple diffusion paths or having disordered structures.However,it relies on simulations at temperatures much higher than working temperature.This paper studies the reliability of the MD method using the system of Na diffusion in MgO as a benchmark.We carefully study the convergence behavior of the MD method and demonstrate that total effective simulation time of 12 ns can converge the calculated diffusion barrier to about 0.01 eV.The calculated diffusion barrier is 0.31 eV from both methods.The diffusion coefficients at room temperature are 4.3×10^(-9) cm^(2)⋅s^(−1) and 2.2×10^(-9) cm^(2)⋅s^(−1),respectively,from the NEB and MD methods.Our results justify the reliability of the MD method,even though high temperature simulations have to be employed to overcome the limitation on simulation time.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFC3004104)the National Natural Science Foundation of China(Grant No.U2342204)+4 种基金the Innovation and Development Program of the China Meteorological Administration(Grant No.CXFZ2024J001)the Open Research Project of the Key Open Laboratory of Hydrology and Meteorology of the China Meteorological Administration(Grant No.23SWQXZ010)the Science and Technology Plan Project of Zhejiang Province(Grant No.2022C03150)the Open Research Fund Project of Anyang National Climate Observatory(Grant No.AYNCOF202401)the Open Bidding for Selecting the Best Candidates Program(Grant No.CMAJBGS202318)。
文摘Thunderstorm wind gusts are small in scale,typically occurring within a range of a few kilometers.It is extremely challenging to monitor and forecast thunderstorm wind gusts using only automatic weather stations.Therefore,it is necessary to establish thunderstorm wind gust identification techniques based on multisource high-resolution observations.This paper introduces a new algorithm,called thunderstorm wind gust identification network(TGNet).It leverages multimodal feature fusion to fuse the temporal and spatial features of thunderstorm wind gust events.The shapelet transform is first used to extract the temporal features of wind speeds from automatic weather stations,which is aimed at distinguishing thunderstorm wind gusts from those caused by synoptic-scale systems or typhoons.Then,the encoder,structured upon the U-shaped network(U-Net)and incorporating recurrent residual convolutional blocks(R2U-Net),is employed to extract the corresponding spatial convective characteristics of satellite,radar,and lightning observations.Finally,by using the multimodal deep fusion module based on multi-head cross-attention,the temporal features of wind speed at each automatic weather station are incorporated into the spatial features to obtain 10-minutely classification of thunderstorm wind gusts.TGNet products have high accuracy,with a critical success index reaching 0.77.Compared with those of U-Net and R2U-Net,the false alarm rate of TGNet products decreases by 31.28%and 24.15%,respectively.The new algorithm provides grid products of thunderstorm wind gusts with a spatial resolution of 0.01°,updated every 10minutes.The results are finer and more accurate,thereby helping to improve the accuracy of operational warnings for thunderstorm wind gusts.
文摘In the article“A Lightweight Approach for Skin Lesion Detection through Optimal Features Fusion”by Khadija Manzoor,Fiaz Majeed,Ansar Siddique,Talha Meraj,Hafiz Tayyab Rauf,Mohammed A.El-Meligy,Mohamed Sharaf,Abd Elatty E.Abd Elgawad Computers,Materials&Continua,2022,Vol.70,No.1,pp.1617–1630.DOI:10.32604/cmc.2022.018621,URL:https://www.techscience.com/cmc/v70n1/44361,there was an error regarding the affiliation for the author Hafiz Tayyab Rauf.Instead of“Centre for Smart Systems,AI and Cybersecurity,Staffordshire University,Stoke-on-Trent,UK”,the affiliation should be“Independent Researcher,Bradford,BD80HS,UK”.
基金supported by the National Natural Science Foundation of China(Nos.52275395,51935014,and 82072084)the Science and Technology Innovation Program of Hunan Province(No.2023RC3046)+4 种基金the Young Elite Scientists Sponsorship Program byCAST(No.2020QNRC002)the NationalKeyResearchand Development Program of China(No.2023YFB4605800)the Central South University Innovation-Driven Research Programme(No.2023CXQD023)the Jiangxi Provincial Natural Science Foundation of China(No.20224ACB204013)the Project of State Key Laboratory of Precision Manufacturing for Extreme Service Performance,Central South University.
文摘Magnetostrictive Fe-Ga alloys have captivated substantial focus in biomedical applications because of their exceptional transition efficiency and favorable cytocompatibility.Nevertheless,Fe-Ga alloys always exhibit frustrating magnetostriction coefficients when presented in bulk dimensions.It is well-established that the magnetostrictive performance of Fe-Ga alloys is intimately linked to their phase and crystal structures.In this study,various concentrations of boron(B)were doped into Fe_(81)Ga_(19) alloys via the laser-beam powder bed fusion(LPBF)technique to tailor the crystal and phase structures,thereby improving the magnetostrictive performance.The results revealed the capacity for quick solidification of the LPBF process in expediting the solid solution of B element,which increased both lattice distortion and dislocations within the Fe-Ga matrix.These factors contributed to an elevation in the density of the modified-D0_(3) phase structure.Moreover,the prepared Fe-Ga-B alloys also exhibited a(001)preferred grain orientation caused by the high thermal gradients during the LPBF process.As a result,a maximum magnetostriction coefficient of 105 ppm was achieved in the(Fe_(81)Ga_(19))_(98.5)B_(1.5) alloy.In alternating magnetic fields,all the LPBF-prepared alloys showed good dynamic magnetostriction response without visible hysteresis,while the(Fe_(81)Ga_(19))_(98.5)B_(1.5) alloy presented a notable enhancement of~30%in magnetostriction coefficient when compared with the Fe_(81)Ga_(19) alloy.Moreover.the(Fe_(81)Ga_(19))_(98.5)B_(1.5) alloy exhibited favorable biocompatibility and osteogenesis,as confirmed by increased alkaline phosphatase(ALP)activity and the formation of mineralized nodules.These findings suggest that the B-doped Fe-Ga alloys combined with the LPBF technique hold promise for the development of bulk magnetostrictive alloys that are applicable for bone repair applications.
基金supported by the National Natural Science Foundation of China(12172023).
文摘The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.
基金Chongqing Engineering University Undergraduate Innovation and Entrepreneurship Training Program Project:Wireless Fire Automatic Alarm System(Project No.:CXCY2024017)Chongqing Municipal Education Commission Science and Technology Research Project:Development and Research of Chongqing Wireless Fire Automatic Alarm System(Project No.:KJQN202401906)。
文摘This article explores the design of a wireless fire alarm system supported by advanced data fusion technology.It includes discussions on the basic design ideas of the wireless fire alarm system,hardware design analysis,software design analysis,and simulation analysis,all supported by data fusion technology.Hopefully,this analysis can provide some reference for the rational application of data fusion technology to meet the actual design and application requirements of the system.
基金supported by the National Natural Science Foundation of China(Grant Nos.52205140,52175129)the Outstanding Youth Foundation of Hunan Province(Grant No.2023JJ20041)the Science and Technology Innovation Program of Hunan Province(2023RC3241).
文摘This work investigated the anisotropy tensile properties of Inconel 625 alloy fabricated by laser powder bed fusion (LPBF) under various tests temperature, focusing the anisotropy evolution during the high temperature. The microstructure contained columnar grains with (111) texture in the vertical plane (90° sample), while a large equiaxed grain with (100) texture was produced in the horizontal plane (0° sample). As for 45° sample, a large number of equiaxed grains and a few columnar grains with (111) texture can be observed. The sample produced at a 0° orientation demonstrates the highest tensile strength, whereas the 90° sample exhibits the greatest elongation. Conversely, the 45° sample displays the least favorable overall performance. As the tests temperature increased from room temperature to 600℃, the anisotropy rate of ultimate tensile strength, yield strength and ductility between 0° and 45° samples, decreased from 8.98 to 6.96%, 2.36 to 1.28%, 19.93 to 12.23%, as well as between 0° and 90° samples decreased from 4.87 to 4.03%, 11.88 to 7.21% and 14.11 to 6.89%, respectively, because of the recovery of oriented columnar grains.
基金funded by the National Natural Science Foundation of China(No.41962016)the Natural Science Foundation of NingXia(Nos.2023AAC02023,2023A1218,and 2021AAC02006).
文摘Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.
基金supported by the National Key R&D Program of China (Grant No.2022YFF0503700)the National Natural Science Foundation of China (42074196, 41925018)
文摘Solar flare prediction is an important subject in the field of space weather.Deep learning technology has greatly promoted the development of this subject.In this study,we propose a novel solar flare forecasting model integrating Deep Residual Network(ResNet)and Support Vector Machine(SVM)for both≥C-class(C,M,and X classes)and≥M-class(M and X classes)flares.We collected samples of magnetograms from May 1,2010 to September 13,2018 from Space-weather Helioseismic and Magnetic Imager(HMI)Active Region Patches and then used a cross-validation method to obtain seven independent data sets.We then utilized five metrics to evaluate our fusion model,based on intermediate-output extracted by ResNet and SVM using the Gaussian kernel function.Our results show that the primary metric true skill statistics(TSS)achieves a value of 0.708±0.027 for≥C-class prediction,and of 0.758±0.042 for≥M-class prediction;these values indicate that our approach performs significantly better than those of previous studies.The metrics of our fusion model’s performance on the seven datasets indicate that the model is quite stable and robust,suggesting that fusion models that integrate an excellent baseline network with SVM can achieve improved performance in solar flare prediction.Besides,we also discuss the performance impact of architectural innovation in our fusion model.
基金supported in part by the National Natural Science Foundation of China under Grants 62463002,62062021 and 62473033in part by the Guiyang Scientific Plan Project[2023]48–11,in part by QKHZYD[2023]010 Guizhou Province Science and Technology Innovation Base Construction Project“Key Laboratory Construction of Intelligent Mountain Agricultural Equipment”.
文摘Solar cell defect detection is crucial for quality inspection in photovoltaic power generation modules.In the production process,defect samples occur infrequently and exhibit random shapes and sizes,which makes it challenging to collect defective samples.Additionally,the complex surface background of polysilicon cell wafers complicates the accurate identification and localization of defective regions.This paper proposes a novel Lightweight Multiscale Feature Fusion network(LMFF)to address these challenges.The network comprises a feature extraction network,a multi-scale feature fusion module(MFF),and a segmentation network.Specifically,a feature extraction network is proposed to obtain multi-scale feature outputs,and a multi-scale feature fusion module(MFF)is used to fuse multi-scale feature information effectively.In order to capture finer-grained multi-scale information from the fusion features,we propose a multi-scale attention module(MSA)in the segmentation network to enhance the network’s ability for small target detection.Moreover,depthwise separable convolutions are introduced to construct depthwise separable residual blocks(DSR)to reduce the model’s parameter number.Finally,to validate the proposed method’s defect segmentation and localization performance,we constructed three solar cell defect detection datasets:SolarCells,SolarCells-S,and PVEL-S.SolarCells and SolarCells-S are monocrystalline silicon datasets,and PVEL-S is a polycrystalline silicon dataset.Experimental results show that the IOU of our method on these three datasets can reach 68.5%,51.0%,and 92.7%,respectively,and the F1-Score can reach 81.3%,67.5%,and 96.2%,respectively,which surpasses other commonly usedmethods and verifies the effectiveness of our LMFF network.
基金supported in part by the National Natural Science Foundation of China(12171124,61933007)the Natural Science Foundation of Heilongjiang Province of China(ZD2022F003)+2 种基金the National High-End Foreign Experts Recruitment Plan of China(G2023012004L)the Royal Society of UKthe Alexander von Humboldt Foundation of Germany
文摘In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.
文摘BACKGROUND Ependymoma with lipomatous differentiation is a rare type of ependymoma.The ZFTA fusion-positive supratentorial ependymoma is a novel tumor type in the 2021 World Health Organization classification of central nervous system tumors.ZFTA fusion-positive lipomatous ependymoma has not been reported to date.CASE SUMMARY We reported a case of a 15-year-old Chinese male who had a sudden convulsion lasting approximately six minutes.Magnetic resonance imaging showed a round cystic shadow of approximately 1.9 cm×1.5 cm×1.9 cm under the right parieto-occipital cortex.Microscopic examination showed characteristic perivascular pseudorosettes and adipose differentiation in the cytoplasm.Immunohisto-chemical staining showed that the tumor cells were negative for cytokeratin,NeuN,Syn and p53,but positive for GFAP,vimentin and S-100 protein.Signi-ficant punctate intracytoplasmic EMA immunoreactivity was observed.The level of Ki-67 was about 5%.Genetic analysis revealed ZFTA:RELA fusion.A cranio-tomy with total excision of the tumor was performed.The follow-up time was 36 months,no evidence of disease recurrence was found in magnetic resonance imaging.CONCLUSION Based on these findings,the patient was diagnosed as a ependymoma with ZFTA fusion and lipomatous differentiation.This case report provides information on the microscopic morphological features of ependymoma with ZFTA fusion and lipomatous differentiation,which can help pathologists to make a definitive diagnosis of this tumor.
基金supported by the National Natural Science Foundation of China(Nos.51801079 and 52001140)the National Science Centre,Poland(Narodowe Centrum Nauki)(No.UMO-2021/42/E/ST5/00339).
文摘To increase the strength of the laser powder-bed fusion (LPBF) Al-Si-based aluminum alloy, TiB_(2) ceramic particles were selected to be mixed with high-Mg content Al-Si-Mg-Zr powder, and then a novel TiB_(2)/Al-Si-Mg-Zr composite was fabricated using LPBF. The results indicated that a dense sample with a maximum relative density of 99.85% could be obtained by adjusting the LPBF process parameters. Incorporating TiB_(2) nanoparticles enhanced the powder's laser absorption rate, thereby raising the alloy's intrinsic heat treatment temperature and consequently facilitating the precipitation of Si and βʺ nanoparticles in the α-Al cells. Moreover, the rapid cooling process during LPBF resulted in numerous alloying elements with low-stacking fault energy dissolving in the α-Al matrix, thus promoting the formation of the 9R phase. After a 48 h direct aging treatment at 150℃, the strength of the alloy slightly increased due to the increase of nanoprecipitates. Both yield strength and ultimate tensile strength of the LPBF TiB_(2)/Al-Si-Mg-Zr alloy were significantly higher than that of other LPBF TiB_(2)-modified aluminum alloys with external addition.
基金funded by the Committee of Science of the Ministry of Science andHigher Education of the Republic of Kazakhstan(Grant No.BR24993166).
文摘While automatic image captioning systems have made notable progress in the past few years,generating captions that fully convey sentiment remains a considerable challenge.Although existing models achieve strong performance in visual recognition and factual description,they often fail to account for the emotional context that is naturally present in human-generated captions.To address this gap,we propose the Sentiment-Driven Caption Generator(SDCG),which combines transformer-based visual and textual processing withmulti-level fusion.RoBERTa is used for extracting sentiment from textual input,while visual features are handled by the Vision Transformer(ViT).These features are fused using several fusion approaches,including Concatenation,Attention,Visual-Sentiment Co-Attention(VSCA),and Cross-Attention.Our experiments demonstrate that SDCG significantly outperforms baseline models such as the Generalized Image Transformer(GIT),which achieves 82.01%,and Bootstrapping Language-Image Pre-training(BLIP),which achieves 83.07%,in sentiment accuracy.While SDCG achieves 94.52%sentiment accuracy and improves scores in BLEU and ROUGE-L,the model demonstrates clear advantages.More importantly,the captions aremore natural,as they incorporate emotional cues and contextual awareness,making them resemble those written by a human.
基金Supported by the Henan Province Key Research and Development Project(231111211300)the Central Government of Henan Province Guides Local Science and Technology Development Funds(Z20231811005)+2 种基金Henan Province Key Research and Development Project(231111110100)Henan Provincial Outstanding Foreign Scientist Studio(GZS2024006)Henan Provincial Joint Fund for Scientific and Technological Research and Development Plan(Application and Overcoming Technical Barriers)(242103810028)。
文摘The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.
基金Supported by the National Natural Science Foundation of China(Nos.52222904 and 52309117)China Postdoctoral Science Foundation(Nos.2022TQ0168 and 2023M731895).
文摘Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.However,the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current,even resulting in blade fatigue and destructively interfering with grid stability.A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio(HDR).However,HDR is difficult to obtain due to the complex fluid-structure interaction(FSI).Therefore,a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures.The experimental and simulation methods used to identify and obtain the HDR quantitatively were described,placing emphasis on the experimental processes and simulation setups.Moreover,the accuracy and efficiency of different simulation methods were compared,and the modal work approach was recommended.The effects of key typical parameters,including flow velocity,angle of attack,gap,rotational speed,and cavitation,on the HDR were then summarized,and the suggestions on operating conditions were presented from the perspective of increasing the HDR.Subsequently,considering multiple flow parameters,several theoretical derivations and semi-empirical prediction formulas for HDR were introduced,and the accuracy and application were discussed.Based on the shortcomings of the existing research,the direction of future research was finally determined.The current work offers a clear understanding of the HDR of blade-like structures,which could improve the evaluation accuracy of flow-induced vibration in the design stage.
文摘Semi-crystalline polymer laser powder bed fusion(L-PBF)has recently attracted increasing interest due to its potential for fabricating complex geometry.However,a more comprehensive understanding of the underlying physics during L-PBF is required to better control the properties of the final part.This work proposed a multi-layer numerical model to study the temperature and phase evolution during the polyamide-12(PA12)L-PBF process.The Descend and Parallel Chord methods were introduced to improve the convergence of the non-linear thermal solver.The level-set-based mesh adaptation strategy,governed by multi-physical fields,was applied to alleviate the calculation and accurately track the phase evolution.The processing simulation on the dog-bone model revealed that preheating temperature significantly influences the crystallization behavior.Finally,the multi-layer simulation demonstrated that such a developed numerical model can be used to study the phase transformation during powder layer updating and the cyclic laser sintering phenomena.Moreover,the numerical study suggested that crystallization occurs slowly during the L-PBF process.
