Ytterbium(Yb)-based mode-locked fiber lasers have undergone significant development and found widespread applications owing to their high efficiency,compact size,and low cost.However,these lasers typically operate wit...Ytterbium(Yb)-based mode-locked fiber lasers have undergone significant development and found widespread applications owing to their high efficiency,compact size,and low cost.However,these lasers typically operate within the 1030 to 1080 nm range,and expanding their operational wavelength is crucial for applications across various fields.We present the direct generation of a mode-locked laser at 1120.06 nm using an all-polarization-maintaining structure,establishing the longest wavelength reported to date for Yb-doped fiber-based mode-locked lasers.A stable picosecond pulse laser at 1120 nm was realized by combining high-concentration Yb-doping and phase-biasing technology within a figure-9 cavity configuration.The laser delivers a pulse duration of 6.20 ps,a spectral width of 0.19 nm centered at 1120.06 nm,and a repetition rate of 21.52 MHz and reaches a maximum output power of 1.39 W via a double-cladding Yb fiber power amplifier in a master oscillator power amplifier configuration.Furthermore,we present a theoretical investigation of the laser performance,with simulation results aligning well with experimental findings.In addition,a 560.06-nm ultrafast yellow-green laser was generated through frequency doubling in a lithium triborate crystal.We present an approach for long-wavelength Yb-doped mode-locked lasers,with the potential to advance the development and application of Yb-based fiber lasers.展开更多
Consider the model Yt = βYt-1＋g（Yt-2）＋εt for 3 〈 t 〈 T. Hereg is anunknown function, β is an unknown parameter, εt are i.i.d, random errors with mean 0 andvariance σ2 and the fourth moment α4, and α4 are ...Consider the model Yt = βYt-1＋g（Yt-2）＋εt for 3 〈 t 〈 T. Hereg is anunknown function, β is an unknown parameter, εt are i.i.d, random errors with mean 0 andvariance σ2 and the fourth moment α4, and α4 are independent of Y8 for all t ≥ 3 and s = 1, 2.Pseudo-LS estimators σ, σ2T α4τ and D2T of σ^2,α4 and Var（ε2↑3） are respectively constructedbased on piecewise polynomial approximator of g. The weak consistency of α4T and D2T are proved. The asymptotic normality of σ2T is given, i.e., √T（σ2T -σ^2）/DT converges indistribution to N（0, 1）. The result can be used to establish large sample interval estimatesof σ^2 or to make large sample tests for σ^2.展开更多
A k-L(2,1)-labeling for a graph G is a function such that whenever and whenever u and v are at distance two apart. The λ-number for G, denoted by λ(G), is the minimum k over all k-L(2,1)-labelings of G. In this pape...A k-L(2,1)-labeling for a graph G is a function such that whenever and whenever u and v are at distance two apart. The λ-number for G, denoted by λ(G), is the minimum k over all k-L(2,1)-labelings of G. In this paper, we show that for or 11, which confirms Conjecture 6.1 stated in [X. Li, V. Mak-Hau, S. Zhou, The L(2,1)-labelling problem for cubic Cayley graphs on dihedral groups, J. Comb. Optim. (2013) 25: 716-736] in the case when or 11. Moreover, we show that? if 1) either (mod 6), m is odd, r = 3, or 2) (mod 3), m is even (mod 2), r = 0.展开更多
Carbon stars are excellent kinematic tracers of galaxies and can serve as a viable standard candle, so it is worthwhile to automatically search for them in a large amount of spectra. In this paper, we apply the effici...Carbon stars are excellent kinematic tracers of galaxies and can serve as a viable standard candle, so it is worthwhile to automatically search for them in a large amount of spectra. In this paper, we apply the efficient manifold ranking algorithm to search for carbon stars from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope （LAMOST） pilot survey, whose performance and robustness are verified comprehensively with four test experiments. Using this algorithm, we find a total of 183 carbon stars, and 158 of them are new findings. According to different spectral features, our carbon stars are classified as 58 C-H stars, 11 C-H star candidates, 56 C-R stars, ten C-R star candidates, 30 C-N stars, three C-N star candidates, and four C-J stars. There are also ten objects which have no spectral type because of low spec- tral quality, and a composite spectrum consisting of a white dwarf and a carbon star. Applying the support vector machine algorithm, we obtain the linear optimum clas- sification plane in the J - H versus/-/- Ks color diagram which can be used to distinguish C-H from C-N stars with their J - H and H - Ks colors. In addition, we identify 18 dwarf carbon stars with their relatively high proper motions, and find three carbon stars with FUV detections likely have optical invisible companions by cross matching with data from the Galaxy Evolution Explorer. In the end, we detect four variable carbon stars with the Northern Sky Variability Survey, the Catalina Sky Survey and the LINEAR variability databases. According to their periods and ampli- tudes derived by fitting light curves with a sinusoidal function, three of them are likely semiregular variable stars and one is likely a Mira variable star.展开更多
A novel method toward color image segmentation is proposed based on edge linking and region grouping. Firstly,the edges extracted by the Canny detector are linked to form regions.Each of the end points of edges is con...A novel method toward color image segmentation is proposed based on edge linking and region grouping. Firstly,the edges extracted by the Canny detector are linked to form regions.Each of the end points of edges is connected by a direct line to the nearest pixel on another edge segment within a sub-window.A new distance is defined based on the feature that the edge tends to preserve its original direction.By sampling the lines to the image,the image is over-segmented to labeled regions.Secondly,the labeled regions are grouped both locally and globally.A decision tree is constructed to decide the importance of properties that affect the merging procedure.Finally,the result is refined by user’s selection of regions that compose the desired object. Experiments show that the method can effectively segment the object and is much faster than the state-of-the-art color image segmentation methods.展开更多
Lung image registration plays an important role in lung analysis applications,such as respiratory motion modeling.Unsupervised learning-based image registration methods that can compute the deformation without the req...Lung image registration plays an important role in lung analysis applications,such as respiratory motion modeling.Unsupervised learning-based image registration methods that can compute the deformation without the requirement of supervision attract much attention.However,it is noteworthy that they have two drawbacks:they do not handle the problem of limited data and do not guarantee diffeomorphic(topologypreserving)properties,especially when large deformation exists in lung scans.In this paper,we present an unsupervised few-shot learning-based diffeomorphic lung image registration,namely Dlung.We employ fine-tuning techniques to solve the problem of limited data and apply the scaling and squaring method to accomplish the diffeomorphic registration.Furthermore,atlas-based registration on spatio-temporal(4D)images is performed and thoroughly compared with baseline methods.Dlung achieves the highest accuracy with diffeomorphic properties.It constructs accurate and fast respiratory motion models with limited data.This research extends our knowledge of respiratory motion modeling.展开更多
Addiction is a chronic and often relapsing brain disorder characterized by drug abuse and withdrawal symptoms and compulsive drug seeking(Koob and Volkow,2010)when access to the drug is restricted.Addiction leads to s...Addiction is a chronic and often relapsing brain disorder characterized by drug abuse and withdrawal symptoms and compulsive drug seeking(Koob and Volkow,2010)when access to the drug is restricted.Addiction leads to structural and functional brain changes implicated in reward,memory,motivation,and control(Volkow et al.,2019;Lüscher et al.,2020).展开更多
Currently,the ultra-wideband(UWB)positioning scheme is widely applied to indoor robot positioning and has achieved high positioning accuracy.However,in some narrow and complex environments,its accuracy is still signif...Currently,the ultra-wideband(UWB)positioning scheme is widely applied to indoor robot positioning and has achieved high positioning accuracy.However,in some narrow and complex environments,its accuracy is still significantly degraded by the multipath effect or non-line-of-sight situations.In addition,the current single tag-based pure UWB positioning methods only estimate the tag position and ignore the rotation estimation of the robot.Therefore,in this paper,we propose a multiple tags-based UWB positioning method to estimate the position and rotation simultaneously,and further improve the position estimation accuracy.To be specific,we first install four fixed tags on the robot.Then,based on the ranging measurements,anchor positions and geometric relationships between each tag,we design five different geometric constraints and smooth constraints to build a whole optimization function.With this optimization function,both the rotations and positions at each time step can be estimated by the iterative optimization algorithm,and the results of tag positions can be improved.Both simulation and real-world experiments are conducted to evaluate the proposed method.Furthermore,we also explore the effect of relative distances between multiple tags on the rotations in the experiments.The experimental results suggest that the proposed method can effectively improve the position estimation performance,while the large relative distances between multiple tags benefit the rotation estimation.展开更多
Based on the analysis of the shortcomings of broadband MUSIC algorithm with short-time Fourier transform （SF-MUSIC） for sound source localization, a broadband MUSIC algorithm with auditory filter （AF-MUSIC） was pr...Based on the analysis of the shortcomings of broadband MUSIC algorithm with short-time Fourier transform （SF-MUSIC） for sound source localization, a broadband MUSIC algorithm with auditory filter （AF-MUSIC） was proposed. The proposed algorithm first em- ploys auditory filter bank to decompose the signals received on the microphone array, and then locates the sound source with MUSIC algorithm over every frequency channel. At last, by combining with the subinterval frequency estimation, the final localization result is gained. Evaluations on the proposed algorithm prove that comparing with the SF-MUSIC algorithm, the AF-MUSIC algorithm decreases the average error of the estimation results with 2.5479 de- gree in different source conditions. The accuracy of sound source DOA estimation is enhanced effectively.展开更多
A generalized multiresolution likelihood ratio （GMLR）, which can increase the distinction between different signals by fusing their more features, is defined. Multiresolution representation of image characterizes in...A generalized multiresolution likelihood ratio （GMLR）, which can increase the distinction between different signals by fusing their more features, is defined. Multiresolution representation of image characterizes inherent structure of image well, and the GMLR combines each resolution image features with corresponding region features. A spatially variant mixture multiscale autoregressive prediction （SVMMARP） model is proposed to estimate the parameters of GMLR based on maximum likelihood estimation via expectation maximization （EM） algorithm. In the parameter estimation, bootstrap sampling technique is employed. Experimental results demonstrate that the algorithm performs fairly well. OCIS codes： 100.0100, 150.0150, 070.4560.展开更多
Graph conjoint attention(CAT)network is one of the best graph convolutional networks(GCNs)frameworks,which uses a weighting mechanism to identify important neighbor nodes.However,this weighting mechanism is learned ba...Graph conjoint attention(CAT)network is one of the best graph convolutional networks(GCNs)frameworks,which uses a weighting mechanism to identify important neighbor nodes.However,this weighting mechanism is learned based on static information,which means it is susceptible to noisy nodes and edges,resulting in significant limitations.In this paper,a method is proposed to obtain context dynamically based on random walk,which allows the context-based weighting mechanism to better avoid noise interference.Furthermore,the proposed context-based weighting mechanism is combined with the node content-based weighting mechanism of the graph attention(GAT)network to form a model based on a mixed weighting mechanism.The model is named as the context-based and content-based graph convolutional network(CCGCN).CCGCN can better discover important neighbors,eliminate noise edges,and learn node embedding by message passing.Experiments show that CCGCN achieves state-of-the-art performance on node classification tasks in multiple datasets.展开更多
The general mutual information(GMI)and general conditional mutual information(GCMI)are considered to measure lag dependences in nonlinear time series.Both of the measures have the property of invariance with transform...The general mutual information(GMI)and general conditional mutual information(GCMI)are considered to measure lag dependences in nonlinear time series.Both of the measures have the property of invariance with transform.The statistics based on GMI and GCMI are estimated using the correlation integral.Under the hypothesis of independent series,the estimators have Gaussian asymptotic distributions.Simulations applied to generated nonlinear series demonstrate that the methods appear to find frequently the correct lags.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.92477133)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2025A1515011662)+1 种基金the National Natural Science Foundation of Fujian Province(Grant No.2025J01060)the National Natural Science Foundation of Xiamen(Grant No.3502Z202571016).
文摘Ytterbium(Yb)-based mode-locked fiber lasers have undergone significant development and found widespread applications owing to their high efficiency,compact size,and low cost.However,these lasers typically operate within the 1030 to 1080 nm range,and expanding their operational wavelength is crucial for applications across various fields.We present the direct generation of a mode-locked laser at 1120.06 nm using an all-polarization-maintaining structure,establishing the longest wavelength reported to date for Yb-doped fiber-based mode-locked lasers.A stable picosecond pulse laser at 1120 nm was realized by combining high-concentration Yb-doping and phase-biasing technology within a figure-9 cavity configuration.The laser delivers a pulse duration of 6.20 ps,a spectral width of 0.19 nm centered at 1120.06 nm,and a repetition rate of 21.52 MHz and reaches a maximum output power of 1.39 W via a double-cladding Yb fiber power amplifier in a master oscillator power amplifier configuration.Furthermore,we present a theoretical investigation of the laser performance,with simulation results aligning well with experimental findings.In addition,a 560.06-nm ultrafast yellow-green laser was generated through frequency doubling in a lithium triborate crystal.We present an approach for long-wavelength Yb-doped mode-locked lasers,with the potential to advance the development and application of Yb-based fiber lasers.
基金Supported by the National Natural Science Foundation of China（60375003） Supported by the Chinese Aviation Foundation（03153059）
文摘Consider the model Yt = βYt-1＋g（Yt-2）＋εt for 3 〈 t 〈 T. Hereg is anunknown function, β is an unknown parameter, εt are i.i.d, random errors with mean 0 andvariance σ2 and the fourth moment α4, and α4 are independent of Y8 for all t ≥ 3 and s = 1, 2.Pseudo-LS estimators σ, σ2T α4τ and D2T of σ^2,α4 and Var（ε2↑3） are respectively constructedbased on piecewise polynomial approximator of g. The weak consistency of α4T and D2T are proved. The asymptotic normality of σ2T is given, i.e., √T（σ2T -σ^2）/DT converges indistribution to N（0, 1）. The result can be used to establish large sample interval estimatesof σ^2 or to make large sample tests for σ^2.
文摘A k-L(2,1)-labeling for a graph G is a function such that whenever and whenever u and v are at distance two apart. The λ-number for G, denoted by λ(G), is the minimum k over all k-L(2,1)-labelings of G. In this paper, we show that for or 11, which confirms Conjecture 6.1 stated in [X. Li, V. Mak-Hau, S. Zhou, The L(2,1)-labelling problem for cubic Cayley graphs on dihedral groups, J. Comb. Optim. (2013) 25: 716-736] in the case when or 11. Moreover, we show that? if 1) either (mod 6), m is odd, r = 3, or 2) (mod 3), m is even (mod 2), r = 0.
基金funded by the National Natural Science Foundation of China(Grant Nos.11390371,11303036,11390374,11233004 and 61202315)The Guo Shou Jing Telescope(the Large Sky Area Multi-Object Fiber Spectroscopic Telescope,LAMOST) is a National Major Scientific Project built by the Chinese Academy of Sciences+6 种基金Funding for the project has been provided by the National Development and Reform CommissionFunding for SDSS-Ⅲ has been provided by the Alfred P.Sloan Foundationthe Participating Institutionsthe National Science Foundationthe U.S.Department of Energy Office of Sciencefunded by NASANSF
文摘Carbon stars are excellent kinematic tracers of galaxies and can serve as a viable standard candle, so it is worthwhile to automatically search for them in a large amount of spectra. In this paper, we apply the efficient manifold ranking algorithm to search for carbon stars from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope （LAMOST） pilot survey, whose performance and robustness are verified comprehensively with four test experiments. Using this algorithm, we find a total of 183 carbon stars, and 158 of them are new findings. According to different spectral features, our carbon stars are classified as 58 C-H stars, 11 C-H star candidates, 56 C-R stars, ten C-R star candidates, 30 C-N stars, three C-N star candidates, and four C-J stars. There are also ten objects which have no spectral type because of low spec- tral quality, and a composite spectrum consisting of a white dwarf and a carbon star. Applying the support vector machine algorithm, we obtain the linear optimum clas- sification plane in the J - H versus/-/- Ks color diagram which can be used to distinguish C-H from C-N stars with their J - H and H - Ks colors. In addition, we identify 18 dwarf carbon stars with their relatively high proper motions, and find three carbon stars with FUV detections likely have optical invisible companions by cross matching with data from the Galaxy Evolution Explorer. In the end, we detect four variable carbon stars with the Northern Sky Variability Survey, the Catalina Sky Survey and the LINEAR variability databases. According to their periods and ampli- tudes derived by fitting light curves with a sinusoidal function, three of them are likely semiregular variable stars and one is likely a Mira variable star.
基金the National Natural Science Foundation of China(No.60704047)the Science and Technology Commission of Shanghai Municipality (No.09410700700)
文摘A novel method toward color image segmentation is proposed based on edge linking and region grouping. Firstly,the edges extracted by the Canny detector are linked to form regions.Each of the end points of edges is connected by a direct line to the nearest pixel on another edge segment within a sub-window.A new distance is defined based on the feature that the edge tends to preserve its original direction.By sampling the lines to the image,the image is over-segmented to labeled regions.Secondly,the labeled regions are grouped both locally and globally.A decision tree is constructed to decide the importance of properties that affect the merging procedure.Finally,the result is refined by user’s selection of regions that compose the desired object. Experiments show that the method can effectively segment the object and is much faster than the state-of-the-art color image segmentation methods.
基金the National Natural Science Foundation of China(No.61801413)the Natural Science Foundation of Fujian Province(Nos.2019J05123 and 2017J05110)。
文摘Lung image registration plays an important role in lung analysis applications,such as respiratory motion modeling.Unsupervised learning-based image registration methods that can compute the deformation without the requirement of supervision attract much attention.However,it is noteworthy that they have two drawbacks:they do not handle the problem of limited data and do not guarantee diffeomorphic(topologypreserving)properties,especially when large deformation exists in lung scans.In this paper,we present an unsupervised few-shot learning-based diffeomorphic lung image registration,namely Dlung.We employ fine-tuning techniques to solve the problem of limited data and apply the scaling and squaring method to accomplish the diffeomorphic registration.Furthermore,atlas-based registration on spatio-temporal(4D)images is performed and thoroughly compared with baseline methods.Dlung achieves the highest accuracy with diffeomorphic properties.It constructs accurate and fast respiratory motion models with limited data.This research extends our knowledge of respiratory motion modeling.
基金supported by the National Natural Science Foun-dation of China (Grant Nos.82260359,U22A20303)STI2030:2022ZD0214500.
文摘Addiction is a chronic and often relapsing brain disorder characterized by drug abuse and withdrawal symptoms and compulsive drug seeking(Koob and Volkow,2010)when access to the drug is restricted.Addiction leads to structural and functional brain changes implicated in reward,memory,motivation,and control(Volkow et al.,2019;Lüscher et al.,2020).
基金supported in part by the National NaturalScience Foundation of China(62303230)in part by the KeyLaboratory of Pattern Recognition and Intelligent InformationProcessing,Institutions of Higher Education of Sichuan Province(MSSB-2024-05).
文摘Currently,the ultra-wideband(UWB)positioning scheme is widely applied to indoor robot positioning and has achieved high positioning accuracy.However,in some narrow and complex environments,its accuracy is still significantly degraded by the multipath effect or non-line-of-sight situations.In addition,the current single tag-based pure UWB positioning methods only estimate the tag position and ignore the rotation estimation of the robot.Therefore,in this paper,we propose a multiple tags-based UWB positioning method to estimate the position and rotation simultaneously,and further improve the position estimation accuracy.To be specific,we first install four fixed tags on the robot.Then,based on the ranging measurements,anchor positions and geometric relationships between each tag,we design five different geometric constraints and smooth constraints to build a whole optimization function.With this optimization function,both the rotations and positions at each time step can be estimated by the iterative optimization algorithm,and the results of tag positions can be improved.Both simulation and real-world experiments are conducted to evaluate the proposed method.Furthermore,we also explore the effect of relative distances between multiple tags on the rotations in the experiments.The experimental results suggest that the proposed method can effectively improve the position estimation performance,while the large relative distances between multiple tags benefit the rotation estimation.
基金supported by the National Nature Science Foundation of China(91120303,61273267,90820011)FuJian Nature Science Foundation(2009J01296)
文摘Based on the analysis of the shortcomings of broadband MUSIC algorithm with short-time Fourier transform （SF-MUSIC） for sound source localization, a broadband MUSIC algorithm with auditory filter （AF-MUSIC） was proposed. The proposed algorithm first em- ploys auditory filter bank to decompose the signals received on the microphone array, and then locates the sound source with MUSIC algorithm over every frequency channel. At last, by combining with the subinterval frequency estimation, the final localization result is gained. Evaluations on the proposed algorithm prove that comparing with the SF-MUSIC algorithm, the AF-MUSIC algorithm decreases the average error of the estimation results with 2.5479 de- gree in different source conditions. The accuracy of sound source DOA estimation is enhanced effectively.
基金This work was supported by the National Natural Science Foundation of China (No. 60375003)Aeronautics and Astronautics Basal Science Foundation ofChina (No. 03I53059)
文摘A generalized multiresolution likelihood ratio （GMLR）, which can increase the distinction between different signals by fusing their more features, is defined. Multiresolution representation of image characterizes inherent structure of image well, and the GMLR combines each resolution image features with corresponding region features. A spatially variant mixture multiscale autoregressive prediction （SVMMARP） model is proposed to estimate the parameters of GMLR based on maximum likelihood estimation via expectation maximization （EM） algorithm. In the parameter estimation, bootstrap sampling technique is employed. Experimental results demonstrate that the algorithm performs fairly well. OCIS codes： 100.0100, 150.0150, 070.4560.
基金Supported by the Natural Science Foundation of Xiamen (3502Z20227067)。
文摘Graph conjoint attention(CAT)network is one of the best graph convolutional networks(GCNs)frameworks,which uses a weighting mechanism to identify important neighbor nodes.However,this weighting mechanism is learned based on static information,which means it is susceptible to noisy nodes and edges,resulting in significant limitations.In this paper,a method is proposed to obtain context dynamically based on random walk,which allows the context-based weighting mechanism to better avoid noise interference.Furthermore,the proposed context-based weighting mechanism is combined with the node content-based weighting mechanism of the graph attention(GAT)network to form a model based on a mixed weighting mechanism.The model is named as the context-based and content-based graph convolutional network(CCGCN).CCGCN can better discover important neighbors,eliminate noise edges,and learn node embedding by message passing.Experiments show that CCGCN achieves state-of-the-art performance on node classification tasks in multiple datasets.
基金Supported by the National Natural Science Foundation of China(Grant Nos.6037500360972150)the Science and Technology Innovation Foundation of Northwestern Polytechnical University(Grant No.2007KJ01033)
文摘The general mutual information(GMI)and general conditional mutual information(GCMI)are considered to measure lag dependences in nonlinear time series.Both of the measures have the property of invariance with transform.The statistics based on GMI and GCMI are estimated using the correlation integral.Under the hypothesis of independent series,the estimators have Gaussian asymptotic distributions.Simulations applied to generated nonlinear series demonstrate that the methods appear to find frequently the correct lags.
