An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Sin...An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.展开更多
In this article,the multi-parameters Mittag-Leffler function is studied in detail.As a consequence,a series of novel results such as the integral representation,series representation and Mellin transform to the above ...In this article,the multi-parameters Mittag-Leffler function is studied in detail.As a consequence,a series of novel results such as the integral representation,series representation and Mellin transform to the above function,are obtained.Especially,we associate the multi-parameters Mittag-Leffler function with two special functions which are the generalized Wright hypergeometric and the Fox’s-H functions.Meanwhile,some interesting integral operators and derivative operators of this function,are also discussed.展开更多
Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in...Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in time-independent Hamiltonians.Here,our work makes an effort to explore multi-parameter estimation with time-dependent Hamiltonians.In particular,we focus on the discrimination of two close frequencies of a magnetic field by using a single qubit.We optimize the quantum controls by employing both traditional optimization methods and reinforcement learning to improve the precision for estimating the frequencies of the two magnetic fields.In addition to the estimation precision,we also evaluate the robustness of the optimization schemes against the shift of the control parameters.The results demonstrate that the hybrid reinforcement learning approach achieves the highest estimation precision,and exhibits superior robustness.Moreover,a fundamental challenge in multi-parameter quantum estimation stems from the incompatibility of the optimal control strategies for different parameters.We demonstrate that the hybrid control strategies derived through numerical optimization remain effective in enhancing the precision of multi-parameter estimation in spite of the incompatibilities,thereby mitigating incompatibilities between control strategies on the estimation precision.Finally,we investigate the trade-offs in estimation precision among different parameters for different scenarios,revealing the inherent challenges in balancing the optimization of multiple parameters simultaneously and providing insights into the fundamental distinction between quantum single-parameter estimation and multi-parameter estimation.展开更多
Based on waveform fitting,full waveform inversion(FWI)is an important inversion method with the ability to reconstruct multi-parameter models in high precision.However,the strong nonlinear equation used in FWI present...Based on waveform fitting,full waveform inversion(FWI)is an important inversion method with the ability to reconstruct multi-parameter models in high precision.However,the strong nonlinear equation used in FWI presents the following challenges,such as low convergence efficiency,high dependence on the initial model,and the energy imbalance in deep region of the inverted model.To solve these inherent problems,we develop a timedomain elastic FWI method based on gradient preconditioning with the following details:(1)the limited memory Broyden Fletcher Goldfarb Shanno method with faster convergence is adopted to im-prove the inversion stability;(2)a multi-scaled inversion strategy is used to alleviate the nonlinear inversion instead of falling into the local minimum;(3)in addition,the pseudo-Hessian preconditioned illumination operator is involved for preconditioning the parameter gradients to improve the illumination equilibrium degree of deep structures.Based on the programming implementation of the new method,a deep depression model with five diffractors is used for testing.Compared with the conventional elastic FWI method,the technique proposed by this study has better effectiveness and accuracy on the inversion effect and con-vergence,respectively.展开更多
Though atomic decomposition is a very useful tool for studying the boundedness on Hardy spaces for some sublinear operators,untill now,the boundedness of operators on weighted Hardy spaces in a multi-parameter setting...Though atomic decomposition is a very useful tool for studying the boundedness on Hardy spaces for some sublinear operators,untill now,the boundedness of operators on weighted Hardy spaces in a multi-parameter setting has been established only by almost orthogonality estimates.In this paper,we mainly establish the boundedness on weighted multi-parameter local Hardy spaces via atomic decomposition.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
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
Micrometer-sized,irregularly shaped Ti particles(0.5wt%and 1.0wt%)were mixed with an Al-Si-Mg-Zr matrix powder,and a novel Ti-modified Al-Si-Mg-Zr aluminum alloy was subsequently fabricated via laser-powder bed fusion...Micrometer-sized,irregularly shaped Ti particles(0.5wt%and 1.0wt%)were mixed with an Al-Si-Mg-Zr matrix powder,and a novel Ti-modified Al-Si-Mg-Zr aluminum alloy was subsequently fabricated via laser-powder bed fusion(L-PBF).The results demonstrated that the introduction of Ti particles promoted the formation of near-fully equiaxed grains in the alloy owing to the strong grain refinement of the primary(Al,Si)3(Ti,Zr)nanoparticles.Furthermore,the presence of(Al,Si)3(Ti,Zr)nanoparticles inhibited the decomposition of Si-rich cell boundaries and the precipitation of Si nanoparticles in theα-Al cells.The ultimate tensile strength(UTS),yield strength(YS),and elongation of the asbuilt 0.5wt%Ti(0.5Ti)alloy were(468±11),(350±1)MPa,and(10.0±1.4)%,respectively,which are comparable to those of the L-PBF Al-Si-Mg-Zr matrix alloy and significantly higher than those of traditional L-PBF Al-Si-Mg alloys.After direct aging treatment at 150°C,the precipitation of secondary nanoparticles notably enhanced the strength of the 0.5Ti alloy.Specifically,the 0.5Ti alloy achieved a maximum UTS of(479±11)MPa and YS of(376±10)MPa.At 250°C,the YS of the L-PBF Ti/Al-Si-Mg-Zr alloy was higher than that of the L-PBF Al-Si-Mg-Zr matrix alloy due to the retention of Si-rich cell boundaries,indicating a higher thermal stability.As the aging temperature was increased to 300°C,the dissolution of Si-rich cell boundaries,desolvation of solid-solution elements,and coarsening of nanoprecipitates led to a decrease in the UTS and YS of the alloy to below 300 and 200 MPa,respectively.However,the elongation increased significantly.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
Laser additively manufactured(LAM)Ni-based superalloys commonly exhibit low strength and high residual stress in the as-built state,requiring post-heat treatment to improve mechanical properties.We propose a modified ...Laser additively manufactured(LAM)Ni-based superalloys commonly exhibit low strength and high residual stress in the as-built state,requiring post-heat treatment to improve mechanical properties.We propose a modified heat treatment(MHT)process that only involves a single-step aging at 650℃ for 4 h to achieve high strength,high ductility,and low residual stress simultaneously in a laser powder bed fusion(LPBF)-processed Inconel 718(IN718)alloy.The MHT treated alloy exhibits comparable tensile strength(1368 MPa)to the conventional solution plus two-step aging(SA)treated alloy(1398 MPa),while the tensile elongation(∼21.7%for MHT treated alloy and 13.4%for SA treated alloy)is 60%higher and the residual stress(∼195 MPa)is 20%lower than the SA treated alloy.The balanced high performance of the MHT IN718 alloy was mainly attributed to the precipitation of abundantγ’’phase with a size of∼5 nm,while the original nano-sized Laves precipitates and dislocation cells were mostly retained.The finer size and higher fraction ofγ”of the MHT sample mainly result from the dislocation structure and compositional variations in the as-built IN718,which promotes precipitation during aging.The retention of Laves phase,and cellular dislocation network in the MHT alloy also contributes to work hardening during tension and suspends the occurrence of necking.This study unveils a unique strengthening and toughening mechanism in the Ni-based superalloy produced by LAM with the presence of abundant Laves precipitates and provides a simple,low energy-consumption and cost-effective heat treatment route for achieving desirable mechanical properties.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
Additive manufacturing (AM) of high-strength metallic alloys frequently encounters detrimental distortion and cracking, attributed to the accumulation of thermal stresses. These issues significantly impede the practic...Additive manufacturing (AM) of high-strength metallic alloys frequently encounters detrimental distortion and cracking, attributed to the accumulation of thermal stresses. These issues significantly impede the practical application of as-printed components. This study examines the Mg-15Gd-1Zn-0.4Zr (GZ151K, wt.%) alloy, a prototypical high-strength casting Mg-RE alloy, fabricated through laser powder bed fusion (LPBF). Despite achieving ultra-high strength, the GZ151K alloy concurrently exhibits a pronounced cold-cracking susceptibility. The as-printed GZ151K alloy consists of almost fully fine equiaxed grains with an average grain size of merely 2.87 µm. Subsequent direct aging (T5) heat treatment induces the formation of dense prismatic β' precipitates. Consequently, the LPBF-T5 GZ151K alloy manifests an ultra-high yield strength of 405 MPa, surpassing all previously reported yield strengths for Mg alloys fabricated via LPBF and even exceeding that of its extrusion-T5 counterpart. Interestingly, as-printed GZ151K samples with a build height of 2 mm exhibit no cracking, whereas samples with build heights ranging from 4 to 18 mm demonstrate severe cold cracking. Thermal stress simulation also suggests that the cold cracking susceptibility increases significantly with increasing build height. The combination of high thermal stress and low ductility in the as-printed GZ151K alloy culminates in a high cold cracking susceptibility. This study offers novel insights into the intricate issue of cold cracking in the LPBF process of high-strength Mg alloys, highlighting the critical balance between achieving high strength and mitigating cold cracking susceptibility.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
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
基金supported by the National Natural Science Foundation of China(6153102061471383)
文摘An algorithm of highly maneuvering target tracking is proposed to solve the problem of large tracking error caused by strong maneuver. In this algorithm, a new estimator, named as multi-parameter fusion Singer (MF-Singer) model is derived based on the Singer model and the fuzzy reasoning method by using radial acceleration and velocity of the target, and applied to the problem of maneuvering target tracking in strong maneuvering environment and operating environment. The tracking performance of the MF-Singer model is evaluated and compared with other manuevering tracking models. It is shown that the MF-Singer model outperforms these algorithms in several examples.
基金Supported by The National Undergraduate Innovation Training Program(Grant No.202310290069Z).
文摘In this article,the multi-parameters Mittag-Leffler function is studied in detail.As a consequence,a series of novel results such as the integral representation,series representation and Mellin transform to the above function,are obtained.Especially,we associate the multi-parameters Mittag-Leffler function with two special functions which are the generalized Wright hypergeometric and the Fox’s-H functions.Meanwhile,some interesting integral operators and derivative operators of this function,are also discussed.
基金supported by the National Natural Science Foundation of China(Grant No.12075323)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0300702).
文摘Multi-parameter quantum estimation has attracted considerable attention due to its broad applications.Due to the complexity of quantum dynamics,existing research places significant emphasis on estimating parameters in time-independent Hamiltonians.Here,our work makes an effort to explore multi-parameter estimation with time-dependent Hamiltonians.In particular,we focus on the discrimination of two close frequencies of a magnetic field by using a single qubit.We optimize the quantum controls by employing both traditional optimization methods and reinforcement learning to improve the precision for estimating the frequencies of the two magnetic fields.In addition to the estimation precision,we also evaluate the robustness of the optimization schemes against the shift of the control parameters.The results demonstrate that the hybrid reinforcement learning approach achieves the highest estimation precision,and exhibits superior robustness.Moreover,a fundamental challenge in multi-parameter quantum estimation stems from the incompatibility of the optimal control strategies for different parameters.We demonstrate that the hybrid control strategies derived through numerical optimization remain effective in enhancing the precision of multi-parameter estimation in spite of the incompatibilities,thereby mitigating incompatibilities between control strategies on the estimation precision.Finally,we investigate the trade-offs in estimation precision among different parameters for different scenarios,revealing the inherent challenges in balancing the optimization of multiple parameters simultaneously and providing insights into the fundamental distinction between quantum single-parameter estimation and multi-parameter estimation.
基金supported by the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(Grant No.2021QNLM020001)the National Key R&D Program of China(Grant No.2019YFC0605503C)+2 种基金the Major Scientific and Technological Projects of China National Petroleum Corporation(CNPC)(Grant No.ZD2019-183-003)the National Outstanding Youth Science Foundation(Grant No.41922028)the National Innovation Group Project(Grant No.41821002).
文摘Based on waveform fitting,full waveform inversion(FWI)is an important inversion method with the ability to reconstruct multi-parameter models in high precision.However,the strong nonlinear equation used in FWI presents the following challenges,such as low convergence efficiency,high dependence on the initial model,and the energy imbalance in deep region of the inverted model.To solve these inherent problems,we develop a timedomain elastic FWI method based on gradient preconditioning with the following details:(1)the limited memory Broyden Fletcher Goldfarb Shanno method with faster convergence is adopted to im-prove the inversion stability;(2)a multi-scaled inversion strategy is used to alleviate the nonlinear inversion instead of falling into the local minimum;(3)in addition,the pseudo-Hessian preconditioned illumination operator is involved for preconditioning the parameter gradients to improve the illumination equilibrium degree of deep structures.Based on the programming implementation of the new method,a deep depression model with five diffractors is used for testing.Compared with the conventional elastic FWI method,the technique proposed by this study has better effectiveness and accuracy on the inversion effect and con-vergence,respectively.
文摘Though atomic decomposition is a very useful tool for studying the boundedness on Hardy spaces for some sublinear operators,untill now,the boundedness of operators on weighted Hardy spaces in a multi-parameter setting has been established only by almost orthogonality estimates.In this paper,we mainly establish the boundedness on weighted multi-parameter local Hardy spaces via atomic decomposition.
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(Nos.52001140 and 52475361).
文摘Micrometer-sized,irregularly shaped Ti particles(0.5wt%and 1.0wt%)were mixed with an Al-Si-Mg-Zr matrix powder,and a novel Ti-modified Al-Si-Mg-Zr aluminum alloy was subsequently fabricated via laser-powder bed fusion(L-PBF).The results demonstrated that the introduction of Ti particles promoted the formation of near-fully equiaxed grains in the alloy owing to the strong grain refinement of the primary(Al,Si)3(Ti,Zr)nanoparticles.Furthermore,the presence of(Al,Si)3(Ti,Zr)nanoparticles inhibited the decomposition of Si-rich cell boundaries and the precipitation of Si nanoparticles in theα-Al cells.The ultimate tensile strength(UTS),yield strength(YS),and elongation of the asbuilt 0.5wt%Ti(0.5Ti)alloy were(468±11),(350±1)MPa,and(10.0±1.4)%,respectively,which are comparable to those of the L-PBF Al-Si-Mg-Zr matrix alloy and significantly higher than those of traditional L-PBF Al-Si-Mg alloys.After direct aging treatment at 150°C,the precipitation of secondary nanoparticles notably enhanced the strength of the 0.5Ti alloy.Specifically,the 0.5Ti alloy achieved a maximum UTS of(479±11)MPa and YS of(376±10)MPa.At 250°C,the YS of the L-PBF Ti/Al-Si-Mg-Zr alloy was higher than that of the L-PBF Al-Si-Mg-Zr matrix alloy due to the retention of Si-rich cell boundaries,indicating a higher thermal stability.As the aging temperature was increased to 300°C,the dissolution of Si-rich cell boundaries,desolvation of solid-solution elements,and coarsening of nanoprecipitates led to a decrease in the UTS and YS of the alloy to below 300 and 200 MPa,respectively.However,the elongation increased significantly.
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financially supported by the Ministry of Science and Technology of China via the National Key Research&Development Plan(Nos.2022YFB3707105 and 2020YFA0405900)Jiangsu Department of Science and Technology via Provincial Key Research&Development(Industrial Foresight and Key Core Technology,No.BE2021037)+1 种基金Department of the National Science Foundation of China(No.52204390)the Natural Science Foundation of Jiangsu Province(No.BK20202010).
文摘Laser additively manufactured(LAM)Ni-based superalloys commonly exhibit low strength and high residual stress in the as-built state,requiring post-heat treatment to improve mechanical properties.We propose a modified heat treatment(MHT)process that only involves a single-step aging at 650℃ for 4 h to achieve high strength,high ductility,and low residual stress simultaneously in a laser powder bed fusion(LPBF)-processed Inconel 718(IN718)alloy.The MHT treated alloy exhibits comparable tensile strength(1368 MPa)to the conventional solution plus two-step aging(SA)treated alloy(1398 MPa),while the tensile elongation(∼21.7%for MHT treated alloy and 13.4%for SA treated alloy)is 60%higher and the residual stress(∼195 MPa)is 20%lower than the SA treated alloy.The balanced high performance of the MHT IN718 alloy was mainly attributed to the precipitation of abundantγ’’phase with a size of∼5 nm,while the original nano-sized Laves precipitates and dislocation cells were mostly retained.The finer size and higher fraction ofγ”of the MHT sample mainly result from the dislocation structure and compositional variations in the as-built IN718,which promotes precipitation during aging.The retention of Laves phase,and cellular dislocation network in the MHT alloy also contributes to work hardening during tension and suspends the occurrence of necking.This study unveils a unique strengthening and toughening mechanism in the Ni-based superalloy produced by LAM with the presence of abundant Laves precipitates and provides a simple,low energy-consumption and cost-effective heat treatment route for achieving desirable mechanical properties.
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 by the National Key Research and Development Program of China(No.2021YFB3701000)the National Natural Science Foundation of China(Nos.51971130,52201129,U21A2047,51821001,U2037601)+2 种基金support by the China Postdoctoral Science Foun-dation(2023M742219)the Postdoctoral Fellowship Program of CPSF under Grant Number GZB20240419support by the Ministry of Education,Singapore,under its Academic Research Fund Tier 2(MOE-T2EP50221-0013).
文摘Additive manufacturing (AM) of high-strength metallic alloys frequently encounters detrimental distortion and cracking, attributed to the accumulation of thermal stresses. These issues significantly impede the practical application of as-printed components. This study examines the Mg-15Gd-1Zn-0.4Zr (GZ151K, wt.%) alloy, a prototypical high-strength casting Mg-RE alloy, fabricated through laser powder bed fusion (LPBF). Despite achieving ultra-high strength, the GZ151K alloy concurrently exhibits a pronounced cold-cracking susceptibility. The as-printed GZ151K alloy consists of almost fully fine equiaxed grains with an average grain size of merely 2.87 µm. Subsequent direct aging (T5) heat treatment induces the formation of dense prismatic β' precipitates. Consequently, the LPBF-T5 GZ151K alloy manifests an ultra-high yield strength of 405 MPa, surpassing all previously reported yield strengths for Mg alloys fabricated via LPBF and even exceeding that of its extrusion-T5 counterpart. Interestingly, as-printed GZ151K samples with a build height of 2 mm exhibit no cracking, whereas samples with build heights ranging from 4 to 18 mm demonstrate severe cold cracking. Thermal stress simulation also suggests that the cold cracking susceptibility increases significantly with increasing build height. The combination of high thermal stress and low ductility in the as-printed GZ151K alloy culminates in a high cold cracking susceptibility. This study offers novel insights into the intricate issue of cold cracking in the LPBF process of high-strength Mg alloys, highlighting the critical balance between achieving high strength and mitigating cold cracking susceptibility.
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.
