An efficient data-driven numerical framework is developed for transient heat conduction analysis in thin-walled structures.The proposed approach integrates spectral time discretization with neural network approximatio...An efficient data-driven numerical framework is developed for transient heat conduction analysis in thin-walled structures.The proposed approach integrates spectral time discretization with neural network approximation,forming a spectral-integrated neural network(SINN)scheme tailored for problems characterized by long-time evolution.Temporal derivatives are treated through a spectral integration strategy based on orthogonal polynomial expansions,which significantly alleviates stability constraints associated with conventional time-marching schemes.A fully connected neural network is employed to approximate the temperature-related variables,while governing equa-tions and boundary conditions are enforced through a physics-informed loss formulation.Numerical investigations demonstrate that the proposed method maintains high accuracy even when large time steps are adopted,where standard numerical solvers often suffer from instability or excessive computational cost.Moreover,the framework exhibits strong robustness for ultrathin configurations with extreme aspect ratios,achieving relative errors on the order of 10−5 or lower.These results indicate that the SINN framework provides a reliable and efficient alternative for transient thermal analysis of thin-walled structures under challenging computational conditions.展开更多
Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sen...Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sensitive to long-wavelength(15–120 m)and lateral irregularities,which are often overlooked in traditional roughness models.This study aims to construct a three-dimensional runway roughness modeling framework integrating"precise detection-spectrum analysis-spatial reconstruction"in response to this issue.Combining the elevation data of 37 runways(5 asphalt runways and 32 cement runways)measured by a vehicle-mounted laser profilometer and the BeiDou positioning system,the power spectrum analysis was carried out by the Burg method and the spectrum models of asphalt and cement runways were fitted respectively.Meanwhile,a new exponential lateral coherence function was proposed.Finally,the three-dimensional spatial model was reconstructed by using the transfer function and genetic algorithm.The results show that the error of the measured elevation data is less than 1 cm.The spectral characteristics of different pavement types are significantly different.Among them,the R^(2) of the asphalt runway fitted with the Sussman model is greater than 0.9.The cement runway needs to be characterized by a piecewise function to represent the spectral mutation.The fitting error of the new index's lateral coherence function has been reduced to 0.012.The reconstructed three-dimensional model is in good agreement with the theoretical value and the error does not exceed 0.18 mm^(2) m/c.Finally,a three-dimensional model of 0–20 m in the lateral direction and 3000 m in the longitudinal direction is generated,providing support for aircraft vibration simulation and pavement maintenance.展开更多
This study employed tri-component continuous monitoring data from 10 measurement points on both sides of a base isolation layer in the basement of a large-span high-rise building in Beijing,as well as from a free-fiel...This study employed tri-component continuous monitoring data from 10 measurement points on both sides of a base isolation layer in the basement of a large-span high-rise building in Beijing,as well as from a free-field station and roof frame,during a Mw 5.5 magnitude earthquake in Pingyuan,Shandong,in 2023.The H/V spectral ratio method was used to evaluate the structural dynamic response characteristics of the building and analyze the regulatory effect of the base-isolation layer on seismic waves.The results indicate that during the earthquake,the peak frequency of the free-field and the measurement points below the base-isolation layer was stable at 0.17 Hz,whereas the main frequency of the measurement points above the base-isolation layer increased to 0.75–1.18 Hz,which is 4–6 times greater than that of the points below.The amplitude was suppressed by more than 70%,confirming that the base isolation layer effectively isolated the low-frequency energy from the ground and increased the response frequency of the building.When the building was excited by an earthquake,a three-tier frequency gradient was formed throughout the building:“base-isolation layer(0.17 Hz)-main body(1.18 Hz)-roof frame(3.83 Hz)”,which can effectively avoid resonance of the entire building.In addition,the composite base-isolation device changed the dynamic characteristics of the structure.The resonance period was extended from 0.74 s(theoretical value without base isolation)to 5.9 s(calculated value),and the resonance frequency was reduced from 1.35 to 0.17 Hz.This finding indicates that the base-isolation layer can enhance seismic performance by increasing flexibility and damping.展开更多
Sand dust belts span approximately one-fifth of the global land surface.In these regions,dust tends to settle on vegetation surfaces,altering the observed reflectance and affecting remote sensing detections.To enhance...Sand dust belts span approximately one-fifth of the global land surface.In these regions,dust tends to settle on vegetation surfaces,altering the observed reflectance and affecting remote sensing detections.To enhance the accuracy of maize growth monitoring in dust-affected regions,this study aims to quantify the effect of sand dust retention on maize during the tasseling stage in the Kashgar Prefecture,Xinjiang Uygur Autonomous Region,China,by analyzing changes in canopy reflectance and vegetation indices.First,field sampling was conducted to measure the key canopy structure parameters and dust retention levels of maize,and laboratory spectral measurements were performed on leaf spectral properties under gradient dust retention.The measured data were then used to drive the LargE-Scale remote sensing data and image Simulation framework(LESS)model for simulating realistic maize canopy spectra across different dust levels,with validation against Sentinel-2 imagery.Second,on the basis of the simulated and satellite-derived spectra,the dust resistance of 36 common vegetation indices was systematically evaluated,and new robust dust-resistant indices were developed.The results showed that compared with dust-free maize,the canopy reflectance of dust-retained maize followed an increase–decrease–increase pattern,with critical turning points at 735 and 1325 nm.The maximum reflectance difference of–0.11755(change rate:29.002%)occurred within the 735–1325 nm range at 24 g/m^(2)dust retention,and the minimum reflectance difference of 0.04285(change rate:148.950%)was observed in the 350–735 nm range under the same dust retention level.Among the 36 vegetation indices,only the global environment monitoring index(GEMI)and the ratio of transformed chlorophyll absorption in reflectance index to optimized soil-adjusted vegetation index(TCARI/OSAVI)exhibited dust resistance,with GEMI being effective below 6 g/m^(2)and TCARI/OSAVI remaining stable across all levels(average ratio:0.970).The newly developed indices in this study,(RE3–RE2)/(NIR–RE2),(RE3–RE2)/(RE4–RE2),and(NIR–RE2)/(RE4–RE2),retained values within the predefined dust-resistant range over the full dust retention levels of 0–24 g/m^(2),thus showing a more stable dust resistance compared with the commonly used 36 vegetation indices.Specially,(RE3–RE2)/(RE4–RE2)performed the most robustly in Sentinel-2 imagery,that is,58.020%of pixels were within the dust-resistant range,and an average ratio of 0.937 was obtained for the original-spectra index.This study provides a scientific basis for crop monitoring and management in dust-affected regions.展开更多
Regular expression matching is playing an important role in deep inspection. The rapid development of SDN and NFV makes the network more dynamic, bringing serious challenges to traditional deep inspection matching eng...Regular expression matching is playing an important role in deep inspection. The rapid development of SDN and NFV makes the network more dynamic, bringing serious challenges to traditional deep inspection matching engines. However, state-of-theart matching methods often require a significant amount of pre-processing time and hence are not suitable for this fast updating scenario. In this paper, a novel matching engine called BFA is proposed to achieve high-speed regular expression matching with fast pre-processing. Experiments demonstrate that BFA obtains 5 to 20 times more update abilities compared to existing regular expression matching methods, and scales well on multi-core platforms.展开更多
In order to carry out numerical simulation using geologic structural data obtained from Landmark(seismic interpretation system), underground geological structures are abstracted into mechanical models which can reflec...In order to carry out numerical simulation using geologic structural data obtained from Landmark(seismic interpretation system), underground geological structures are abstracted into mechanical models which can reflect actual situations and facilitate their computation and analyses.Given the importance of model building, further processing methods about traditional seismic interpretation results from Landmark should be studied and the processed result can then be directly used in numerical simulation computations.Through this data conversion procedure, Landmark and FLAC(the international general stress software) are seamlessly connected.Thus, the format conversion between the two systems and the pre-and post-processing in simulation computation is realized.A practical application indicates that this method has many advantages such as simple operation, high accuracy of the element subdivision and high speed, which may definitely satisfy the actual needs of floor grid cutting.展开更多
The Low Earth Orbit(LEO)remote sensing satellite mega-constellation has the characteristics of large quantity and various types which make it have unique superiority in the realization of concurrent multiple tasks.How...The Low Earth Orbit(LEO)remote sensing satellite mega-constellation has the characteristics of large quantity and various types which make it have unique superiority in the realization of concurrent multiple tasks.However,the complexity of resource allocation is increased because of the large number of tasks and satellites.Therefore,the primary problem of implementing concurrent multiple tasks via LEO mega-constellation is to pre-process tasks and observation re-sources.To address the challenge,we propose a pre-processing algorithm for the mega-constellation based on highly Dynamic Spatio-Temporal Grids(DSTG).In the first stage,this paper describes the management model of mega-constellation and the multiple tasks.Then,the coding method of DSTG is proposed,based on which the description of complex mega-constellation observation resources is realized.In the third part,the DSTG algorithm is used to realize the processing of concurrent multiple tasks at multiple levels,such as task space attribute,time attribute and grid task importance evaluation.Finally,the simulation result of the proposed method in the case of constellation has been given to verify the effectiveness of concurrent multi-task pre-processing based on DSTG.The autonomous processing process of task decomposition and task fusion and mapping to grids,and the convenient indexing process of time window are verified.展开更多
In order to meet the demands for high transmission rates and high service quality in broadband wireless communication systems, orthogonal frequency division multiplexing （OFDM） has been adopted in some standards. Ho...In order to meet the demands for high transmission rates and high service quality in broadband wireless communication systems, orthogonal frequency division multiplexing （OFDM） has been adopted in some standards. However, the inter-block interference （IBI） and inter-carrier interference （ICI） in an OFDM system affect the performance. To mitigate IBI and ICI, some pre-processing approaches have been proposed based on full channel state information （CSI）, which improved the system performance. A pre-processing filter based on partial CSI at the transmitter is designed and investigated. The filter coefficient is given by the optimization processing, the symbol error rate （SER） is tested, and the computation complexity of the proposed scheme is analyzed. Computer simulation results show that the proposed pre-processing filter can effectively mitigate IBI and ICI and the performance can be improved. Compared with pre-processing approaches at the transmitter based on full CSI, the proposed scheme has high spectral efficiency, limited CSI feedback and low computation complexity.展开更多
The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1...The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1） investigate the morphological features and geological structures at the landing site; （2） integrated in-situ analysis of minerals and chemical compositions; （3） integrated exploration of the structure of the lunar interior; （4） exploration of the lunar-terrestrial space environment, lunar sur- face environment and acquire Moon-based ultraviolet astronomical observations. The Ground Research and Application System （GRAS） is in charge of data acquisition and pre-processing, management of the payload in orbit, and managing the data products and their applications. The Data Pre-processing Subsystem （DPS） is a part of GRAS. The task of DPS is the pre-processing of raw data from the eight instruments that are part of CE-3, including channel processing, unpacking, package sorting, calibration and correction, identification of geographical location, calculation of probe azimuth angle, probe zenith angle, solar azimuth angle, and solar zenith angle and so on, and conducting quality checks. These processes produce Level 0, Level 1 and Level 2 data. The computing platform of this subsystem is comprised of a high-performance computing cluster, including a real-time subsystem used for processing Level 0 data and a post-time subsystem for generating Level 1 and Level 2 data. This paper de- scribes the CE-3 data pre-processing method, the data pre-processing subsystem, data classification, data validity and data products that are used for scientific studies.展开更多
High-resolution ice core records covering long time spans enable reconstruction of the past climatic and environmental conditions allowing the investigation of the earth system's evolution.Preprocessing of ice cor...High-resolution ice core records covering long time spans enable reconstruction of the past climatic and environmental conditions allowing the investigation of the earth system's evolution.Preprocessing of ice cores has direct impacts on the data quality control for further analysis since the conventional ice core processing is time-consuming,produces qualitative data,leads to ice mass loss,and leads to risks of potential secondary pollution.However,over the past several decades,preprocessing of ice cores has received less attention than the improvement of ice drilling,the analytical methodology of various indices,and the researches on the climatic and environmental significance of ice core records.Therefore,this papers reviews the development of the processing for ice cores including framework,design as well as materials,analyzes the technical advantages and disadvantages of the different systems.In the past,continuous flowanalysis(CFA)has been successfully applied to process the polar ice cores.However,it is not suitable for ice cores outside polar region because of high level of particles,the memory effect between samples,and the filtration before injection.Ice core processing is a subtle and professional operation due to the fragility of the nonmetallic materials and the random distribution of particles and air bubbles in ice cores,which aggravates uncertainty in the measurements.The future developments of CFA are discussed in preprocessing,memory effect,challenge for brittle ice,coupling with real-time analysis and optimization of CFA in the field.Furthermore,non-polluting cutters with many different configurations could be designed to cut and scrape in multiple directions and to separate inner and outer portions of the core.This system also needs to be coupled with streamlined operation of packaging,coding,and stacking that can be implemented at high resolution and rate,avoiding manual intervention.At the same time,information of the longitudinal sections could be scanned andidentified,and then classified to obtain quantitative data.In addition,irregular ice volume and weight can also be obtained accurately.These improvements are recorded automatically via user-friendly interfaces.These innovations may be applied to other paleomedias with similar features and needs.展开更多
Mathematical morphology is widely applicated in digital image procesing.Vari- ary morphology construction and algorithm being developed are used in deferent digital image processing.The basic idea of mathematical morp...Mathematical morphology is widely applicated in digital image procesing.Vari- ary morphology construction and algorithm being developed are used in deferent digital image processing.The basic idea of mathematical morphology is to use construction ele- ment measure image morphology for solving understand problem.The article presented advanced cellular neural network that forms mathematical morphological cellular neural network (MMCNN) equation to be suit for mathematical morphology filter.It gave the theo- ries of MMCNN dynamic extent and stable state.It is evidenced that arrived mathematical morphology filter through steady of dynamic process in definite condition.展开更多
There are a number of dirty data in observation data set derived from integrated ocean observing network system. Thus, the data must be carefully and reasonably processed before they are used for forecasting or analys...There are a number of dirty data in observation data set derived from integrated ocean observing network system. Thus, the data must be carefully and reasonably processed before they are used for forecasting or analysis. This paper proposes a data pre-processing model based on intelligent algorithms. Firstly, we introduce the integrated network platform of ocean observation. Next, the preprocessing model of data is presemed, and an imelligent cleaning model of data is proposed. Based on fuzzy clustering, the Kohonen clustering network is improved to fulfill the parallel calculation of fuzzy c-means clustering. The proposed dynamic algorithm can automatically f＇md the new clustering center with the updated sample data. The rapid and dynamic performance of the model makes it suitable for real time calculation, and the efficiency and accuracy of the model is proved by test results through observation data analysis.展开更多
A signal pre-processing method based on optimal variational mode decomposition(OVMD)is proposed to improve the efficiency and accuracy of local data filtering and analysis of edge nodes in distributed electromechanica...A signal pre-processing method based on optimal variational mode decomposition(OVMD)is proposed to improve the efficiency and accuracy of local data filtering and analysis of edge nodes in distributed electromechanical systems.Firstly,the singular points of original signals are eliminated effectively by using the first-order difference method.Then the OVMD method is applied for signal modal decomposition.Furthermore,correlation analysis is conducted to determine the degree of correlation between each mode and the original signal,so as to accurately separate the real operating signal from noise signal.On the basis of theoretical analysis and simulation,an edge node pre-processing system for distributed electromechanical system is designed.Finally,by virtue of the signal-to-noise ratio(SNR)and root-mean-square error(RMSE)indicators,the signal pre-processing effect is evaluated.The experimental results show that the OVMD-based edge node pre-processing system can extract signals with different characteristics and improve the SNR of reconstructed signals.Due to its high fidelity and reliability,this system can also provide data quality assurance for subsequent system health monitoring and fault diagnosis.展开更多
The solution of linear equation group can be applied to the oil exploration, the structure vibration analysis, the computational fluid dynamics, and other fields. When we make the in-depth analysis of some large or ve...The solution of linear equation group can be applied to the oil exploration, the structure vibration analysis, the computational fluid dynamics, and other fields. When we make the in-depth analysis of some large or very large complicated structures, we must use the parallel algorithm with the aid of high-performance computers to solve complex problems. This paper introduces the implementation process having the parallel with sparse linear equations from the perspective of sparse linear equation group.展开更多
Microarray data is inherently noisy due to the noise contaminated from various sources during the preparation of microarray slide and thus it greatly affects the accuracy of the gene expression. How to eliminate the e...Microarray data is inherently noisy due to the noise contaminated from various sources during the preparation of microarray slide and thus it greatly affects the accuracy of the gene expression. How to eliminate the effect of the noise constitutes a challenging problem in microarray analysis. Efficient denoising is often a necessary and the first step to be taken before the image data is analyzed to compensate for data corruption and for effective utilization for these data. Hence preprocessing of microarray image is an essential to eliminate the background noise in order to enhance the image quality and effective quantification. Existing denoising techniques based on transformed domain have been utilized for microarray noise reduction with their own limitations. The objective of this paper is to introduce novel preprocessing techniques such as optimized spatial resolution (OSR) and spatial domain filtering (SDF) for reduction of noise from microarray data and reduction of error during quantification process for estimating the microarray spots accurately to determine expression level of genes. Besides combined optimized spatial resolution and spatial filtering is proposed and found improved denoising of microarray data with effective quantification of spots. The proposed method has been validated in microarray images of gene expression profiles of Myeloid Leukemia using Stanford Microarray Database with various quality measures such as signal to noise ratio, peak signal to noise ratio, image fidelity, structural content, absolute average difference and correlation quality. It was observed by quantitative analysis that the proposed technique is more efficient for denoising the microarray image which enables to make it suitable for effective quantification.展开更多
Bayesian-optimized lithology identification has important basic geological research significance and engineering application value,and this paper proposes a Bayesian-optimized lithology identification method based on ...Bayesian-optimized lithology identification has important basic geological research significance and engineering application value,and this paper proposes a Bayesian-optimized lithology identification method based on machine learning of rock visible and near-infrared spectral data.First,the rock spectral data are preprocessed using Savitzky-Golay(SG)smoothing to remove the noise of the spectral data;then,the preprocessed rock spectral data are downscaled using Principal Component Analysis(PCA)to reduce the redundancy of the data,optimize the effective discriminative information,and obtain the rock spectral features;finally,a Bayesian-optimized lithology identification model is established based on rock spectral features,optimize the model hyperparameters using Bayesian optimization(BO)algorithm to avoid the combination of hyperparameters falling into the local optimal solution,and output the predicted type of rock,so as to realize the Bayesian-optimized lithology identification.In addition,this paper conducts comparative analysis on models based on Artificial Neural Network(ANN)/Random Forest(RF),dimensionality reduction/full band,and optimization algorithms.It uses the confusion matrix,accuracy,Precison(P),Recall(R)and F_(1)values(F_(1))as the evaluation indexes of model accuracy.The results indicate that the lithology identification model optimized by the BO-ANN after dimensionality reduction achieves an accuracy of up to 99.80%,up to 99.79%and up to 99.79%.Compared with the BO-RF model,it has higher identification accuracy and better stability for each type of rock identification.The experiments and reliability analysis show that the Bayesian-optimized lithology identification method proposed in this paper has good robustness and generalization performance,which is of great significance for realizing fast,accurate and Bayesian-optimized lithology identification in tunnel site.展开更多
This paper studies the problem of the spectral radius of the uniform hypergraph determined by the signless Laplacian matrix.The upper bound of the spectral radius of a uniform hypergraph is obtained by using Rayleigh ...This paper studies the problem of the spectral radius of the uniform hypergraph determined by the signless Laplacian matrix.The upper bound of the spectral radius of a uniform hypergraph is obtained by using Rayleigh principle and the perturbation of the spectral radius under moving the edge operation,and the extremal hypergraphs are characterized for both supertree and unicyclic hypergraphs.The spectral radius of the graph is generalized.展开更多
A graph G is H-free,if it contains no H as a subgraph.A graph G is said to be H-minor free,if it does not contain H as a minor.In 2010,Nikiforov asked that what the maximum spectral radius of an H-free graph of order ...A graph G is H-free,if it contains no H as a subgraph.A graph G is said to be H-minor free,if it does not contain H as a minor.In 2010,Nikiforov asked that what the maximum spectral radius of an H-free graph of order n is.In this paper,we consider some Brualdi-Solheid-Turan type problems on bipartite graphs.In 2015,Zhai,Lin and Gong in[Linear Algebra Appl.,2015,471:21-27]proved that if G is a bipartite graph with order n≥2k+2 and ρ(G)≥ρ(K_(k,n-k)),then G contains a C_(2k+2) unless G≌K_(k,n-k).First,we give a new and more simple proof for the above theorem.Second,we prove that if G is a bipartite graph with order n≥2k+2 and ρ(G)≥ρ(K_(k,n-k)),then G contains all T_(2k+3) unless G≌K_(k,n-k).Finally,we prove that among all outerplanar bipartite graphs on n≥308026 vertices,K_(1,n-1) attains the maximum spectral radius.展开更多
For a graph G,a vertex is said to be pendant if its neighborhood contains exactly one vertex.In this paper,we determine the extremal graphs among all n-vertex graphs with the minimum spectral radius andβpendant verti...For a graph G,a vertex is said to be pendant if its neighborhood contains exactly one vertex.In this paper,we determine the extremal graphs among all n-vertex graphs with the minimum spectral radius andβpendant vertices,whereβe{1,2,3,4,n-3,n-2,n-1}.展开更多
For segmented detectors,surface flatness is critical as it directly influences both energy resolution and image clarity.Additionally,the limited adjustment range of the segmented detectors necessitates precise benchma...For segmented detectors,surface flatness is critical as it directly influences both energy resolution and image clarity.Additionally,the limited adjustment range of the segmented detectors necessitates precise benchmark construction.This paper proposes an architecture for detecting detector flatness based on channel spectral dispersion.By measuring the dispersion fringes for coplanar adjustment,the final adjustment residual is improved to better than 300 nm.This result validates the feasibility of the proposed technology and provides significant technical support for the development of next-generation large-aperture sky survey equipment.展开更多
基金supported by the National Natural Science Foundation of China(Nos.12422207 and 12372199).
文摘An efficient data-driven numerical framework is developed for transient heat conduction analysis in thin-walled structures.The proposed approach integrates spectral time discretization with neural network approximation,forming a spectral-integrated neural network(SINN)scheme tailored for problems characterized by long-time evolution.Temporal derivatives are treated through a spectral integration strategy based on orthogonal polynomial expansions,which significantly alleviates stability constraints associated with conventional time-marching schemes.A fully connected neural network is employed to approximate the temperature-related variables,while governing equa-tions and boundary conditions are enforced through a physics-informed loss formulation.Numerical investigations demonstrate that the proposed method maintains high accuracy even when large time steps are adopted,where standard numerical solvers often suffer from instability or excessive computational cost.Moreover,the framework exhibits strong robustness for ultrathin configurations with extreme aspect ratios,achieving relative errors on the order of 10−5 or lower.These results indicate that the SINN framework provides a reliable and efficient alternative for transient thermal analysis of thin-walled structures under challenging computational conditions.
基金supported by the National Natural Science Foundation of China(Grant No.52402430,52572380)the Natural Science Foundation of Shanghai(Grant No.23ZR1466300).
文摘Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sensitive to long-wavelength(15–120 m)and lateral irregularities,which are often overlooked in traditional roughness models.This study aims to construct a three-dimensional runway roughness modeling framework integrating"precise detection-spectrum analysis-spatial reconstruction"in response to this issue.Combining the elevation data of 37 runways(5 asphalt runways and 32 cement runways)measured by a vehicle-mounted laser profilometer and the BeiDou positioning system,the power spectrum analysis was carried out by the Burg method and the spectrum models of asphalt and cement runways were fitted respectively.Meanwhile,a new exponential lateral coherence function was proposed.Finally,the three-dimensional spatial model was reconstructed by using the transfer function and genetic algorithm.The results show that the error of the measured elevation data is less than 1 cm.The spectral characteristics of different pavement types are significantly different.Among them,the R^(2) of the asphalt runway fitted with the Sussman model is greater than 0.9.The cement runway needs to be characterized by a piecewise function to represent the spectral mutation.The fitting error of the new index's lateral coherence function has been reduced to 0.012.The reconstructed three-dimensional model is in good agreement with the theoretical value and the error does not exceed 0.18 mm^(2) m/c.Finally,a three-dimensional model of 0–20 m in the lateral direction and 3000 m in the longitudinal direction is generated,providing support for aircraft vibration simulation and pavement maintenance.
基金supported by the Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project(Grant No.2025ZD005100)by Beijing Geolight Technology Co.,Ltd.under the project“The Impact of Strong Ground Motion on Buildings”(YF-202520).
文摘This study employed tri-component continuous monitoring data from 10 measurement points on both sides of a base isolation layer in the basement of a large-span high-rise building in Beijing,as well as from a free-field station and roof frame,during a Mw 5.5 magnitude earthquake in Pingyuan,Shandong,in 2023.The H/V spectral ratio method was used to evaluate the structural dynamic response characteristics of the building and analyze the regulatory effect of the base-isolation layer on seismic waves.The results indicate that during the earthquake,the peak frequency of the free-field and the measurement points below the base-isolation layer was stable at 0.17 Hz,whereas the main frequency of the measurement points above the base-isolation layer increased to 0.75–1.18 Hz,which is 4–6 times greater than that of the points below.The amplitude was suppressed by more than 70%,confirming that the base isolation layer effectively isolated the low-frequency energy from the ground and increased the response frequency of the building.When the building was excited by an earthquake,a three-tier frequency gradient was formed throughout the building:“base-isolation layer(0.17 Hz)-main body(1.18 Hz)-roof frame(3.83 Hz)”,which can effectively avoid resonance of the entire building.In addition,the composite base-isolation device changed the dynamic characteristics of the structure.The resonance period was extended from 0.74 s(theoretical value without base isolation)to 5.9 s(calculated value),and the resonance frequency was reduced from 1.35 to 0.17 Hz.This finding indicates that the base-isolation layer can enhance seismic performance by increasing flexibility and damping.
基金supported by the Fundamental Research Funds for the Central Universities(N2001020)the National Natural Science Foundation of China(41201359).
文摘Sand dust belts span approximately one-fifth of the global land surface.In these regions,dust tends to settle on vegetation surfaces,altering the observed reflectance and affecting remote sensing detections.To enhance the accuracy of maize growth monitoring in dust-affected regions,this study aims to quantify the effect of sand dust retention on maize during the tasseling stage in the Kashgar Prefecture,Xinjiang Uygur Autonomous Region,China,by analyzing changes in canopy reflectance and vegetation indices.First,field sampling was conducted to measure the key canopy structure parameters and dust retention levels of maize,and laboratory spectral measurements were performed on leaf spectral properties under gradient dust retention.The measured data were then used to drive the LargE-Scale remote sensing data and image Simulation framework(LESS)model for simulating realistic maize canopy spectra across different dust levels,with validation against Sentinel-2 imagery.Second,on the basis of the simulated and satellite-derived spectra,the dust resistance of 36 common vegetation indices was systematically evaluated,and new robust dust-resistant indices were developed.The results showed that compared with dust-free maize,the canopy reflectance of dust-retained maize followed an increase–decrease–increase pattern,with critical turning points at 735 and 1325 nm.The maximum reflectance difference of–0.11755(change rate:29.002%)occurred within the 735–1325 nm range at 24 g/m^(2)dust retention,and the minimum reflectance difference of 0.04285(change rate:148.950%)was observed in the 350–735 nm range under the same dust retention level.Among the 36 vegetation indices,only the global environment monitoring index(GEMI)and the ratio of transformed chlorophyll absorption in reflectance index to optimized soil-adjusted vegetation index(TCARI/OSAVI)exhibited dust resistance,with GEMI being effective below 6 g/m^(2)and TCARI/OSAVI remaining stable across all levels(average ratio:0.970).The newly developed indices in this study,(RE3–RE2)/(NIR–RE2),(RE3–RE2)/(RE4–RE2),and(NIR–RE2)/(RE4–RE2),retained values within the predefined dust-resistant range over the full dust retention levels of 0–24 g/m^(2),thus showing a more stable dust resistance compared with the commonly used 36 vegetation indices.Specially,(RE3–RE2)/(RE4–RE2)performed the most robustly in Sentinel-2 imagery,that is,58.020%of pixels were within the dust-resistant range,and an average ratio of 0.937 was obtained for the original-spectra index.This study provides a scientific basis for crop monitoring and management in dust-affected regions.
基金supported by the National Key Technology R&D Program of China under Grant No. 2015BAK34B00the National Key Research and Development Program of China under Grant No. 2016YFB1000102
文摘Regular expression matching is playing an important role in deep inspection. The rapid development of SDN and NFV makes the network more dynamic, bringing serious challenges to traditional deep inspection matching engines. However, state-of-theart matching methods often require a significant amount of pre-processing time and hence are not suitable for this fast updating scenario. In this paper, a novel matching engine called BFA is proposed to achieve high-speed regular expression matching with fast pre-processing. Experiments demonstrate that BFA obtains 5 to 20 times more update abilities compared to existing regular expression matching methods, and scales well on multi-core platforms.
基金Projects 50221402, 50490271 and 50025413 supported by the National Natural Science Foundation of Chinathe National Basic Research Program of China (2009CB219603, 2009 CB724601, 2006CB202209 and 2005CB221500)+1 种基金the Key Project of the Ministry of Education (306002)the Program for Changjiang Scholars and Innovative Research Teams in Universities of MOE (IRT0408)
文摘In order to carry out numerical simulation using geologic structural data obtained from Landmark(seismic interpretation system), underground geological structures are abstracted into mechanical models which can reflect actual situations and facilitate their computation and analyses.Given the importance of model building, further processing methods about traditional seismic interpretation results from Landmark should be studied and the processed result can then be directly used in numerical simulation computations.Through this data conversion procedure, Landmark and FLAC(the international general stress software) are seamlessly connected.Thus, the format conversion between the two systems and the pre-and post-processing in simulation computation is realized.A practical application indicates that this method has many advantages such as simple operation, high accuracy of the element subdivision and high speed, which may definitely satisfy the actual needs of floor grid cutting.
基金supported by the National Natural Science Foundation of China(Nos.62003115 and 11972130)the Shenzhen Science and Technology Program,China(JCYJ20220818102207015)the Heilongjiang Touyan Team Program,China。
文摘The Low Earth Orbit(LEO)remote sensing satellite mega-constellation has the characteristics of large quantity and various types which make it have unique superiority in the realization of concurrent multiple tasks.However,the complexity of resource allocation is increased because of the large number of tasks and satellites.Therefore,the primary problem of implementing concurrent multiple tasks via LEO mega-constellation is to pre-process tasks and observation re-sources.To address the challenge,we propose a pre-processing algorithm for the mega-constellation based on highly Dynamic Spatio-Temporal Grids(DSTG).In the first stage,this paper describes the management model of mega-constellation and the multiple tasks.Then,the coding method of DSTG is proposed,based on which the description of complex mega-constellation observation resources is realized.In the third part,the DSTG algorithm is used to realize the processing of concurrent multiple tasks at multiple levels,such as task space attribute,time attribute and grid task importance evaluation.Finally,the simulation result of the proposed method in the case of constellation has been given to verify the effectiveness of concurrent multi-task pre-processing based on DSTG.The autonomous processing process of task decomposition and task fusion and mapping to grids,and the convenient indexing process of time window are verified.
基金supported by the National Natural Science Foundation of China(60902045)the National High-Tech Research and Developmeent Program of China(863 Program)(2011AA01A105)
文摘In order to meet the demands for high transmission rates and high service quality in broadband wireless communication systems, orthogonal frequency division multiplexing （OFDM） has been adopted in some standards. However, the inter-block interference （IBI） and inter-carrier interference （ICI） in an OFDM system affect the performance. To mitigate IBI and ICI, some pre-processing approaches have been proposed based on full channel state information （CSI）, which improved the system performance. A pre-processing filter based on partial CSI at the transmitter is designed and investigated. The filter coefficient is given by the optimization processing, the symbol error rate （SER） is tested, and the computation complexity of the proposed scheme is analyzed. Computer simulation results show that the proposed pre-processing filter can effectively mitigate IBI and ICI and the performance can be improved. Compared with pre-processing approaches at the transmitter based on full CSI, the proposed scheme has high spectral efficiency, limited CSI feedback and low computation complexity.
文摘The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1） investigate the morphological features and geological structures at the landing site; （2） integrated in-situ analysis of minerals and chemical compositions; （3） integrated exploration of the structure of the lunar interior; （4） exploration of the lunar-terrestrial space environment, lunar sur- face environment and acquire Moon-based ultraviolet astronomical observations. The Ground Research and Application System （GRAS） is in charge of data acquisition and pre-processing, management of the payload in orbit, and managing the data products and their applications. The Data Pre-processing Subsystem （DPS） is a part of GRAS. The task of DPS is the pre-processing of raw data from the eight instruments that are part of CE-3, including channel processing, unpacking, package sorting, calibration and correction, identification of geographical location, calculation of probe azimuth angle, probe zenith angle, solar azimuth angle, and solar zenith angle and so on, and conducting quality checks. These processes produce Level 0, Level 1 and Level 2 data. The computing platform of this subsystem is comprised of a high-performance computing cluster, including a real-time subsystem used for processing Level 0 data and a post-time subsystem for generating Level 1 and Level 2 data. This paper de- scribes the CE-3 data pre-processing method, the data pre-processing subsystem, data classification, data validity and data products that are used for scientific studies.
基金supported by the National Natural Science Foundation of China(Grant No.41630754)the State Key Laboratory of Cryospheric Science(SKLCS-ZZ-2017)CAS Key Technology Talent Program and Open Foundation of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering(2017490711)
文摘High-resolution ice core records covering long time spans enable reconstruction of the past climatic and environmental conditions allowing the investigation of the earth system's evolution.Preprocessing of ice cores has direct impacts on the data quality control for further analysis since the conventional ice core processing is time-consuming,produces qualitative data,leads to ice mass loss,and leads to risks of potential secondary pollution.However,over the past several decades,preprocessing of ice cores has received less attention than the improvement of ice drilling,the analytical methodology of various indices,and the researches on the climatic and environmental significance of ice core records.Therefore,this papers reviews the development of the processing for ice cores including framework,design as well as materials,analyzes the technical advantages and disadvantages of the different systems.In the past,continuous flowanalysis(CFA)has been successfully applied to process the polar ice cores.However,it is not suitable for ice cores outside polar region because of high level of particles,the memory effect between samples,and the filtration before injection.Ice core processing is a subtle and professional operation due to the fragility of the nonmetallic materials and the random distribution of particles and air bubbles in ice cores,which aggravates uncertainty in the measurements.The future developments of CFA are discussed in preprocessing,memory effect,challenge for brittle ice,coupling with real-time analysis and optimization of CFA in the field.Furthermore,non-polluting cutters with many different configurations could be designed to cut and scrape in multiple directions and to separate inner and outer portions of the core.This system also needs to be coupled with streamlined operation of packaging,coding,and stacking that can be implemented at high resolution and rate,avoiding manual intervention.At the same time,information of the longitudinal sections could be scanned andidentified,and then classified to obtain quantitative data.In addition,irregular ice volume and weight can also be obtained accurately.These improvements are recorded automatically via user-friendly interfaces.These innovations may be applied to other paleomedias with similar features and needs.
文摘Mathematical morphology is widely applicated in digital image procesing.Vari- ary morphology construction and algorithm being developed are used in deferent digital image processing.The basic idea of mathematical morphology is to use construction ele- ment measure image morphology for solving understand problem.The article presented advanced cellular neural network that forms mathematical morphological cellular neural network (MMCNN) equation to be suit for mathematical morphology filter.It gave the theo- ries of MMCNN dynamic extent and stable state.It is evidenced that arrived mathematical morphology filter through steady of dynamic process in definite condition.
基金Key Science and Technology Project of the Shanghai Committee of Science and Technology, China (No.06dz1200921)Major Basic Research Project of the Shanghai Committee of Science and Technology(No.08JC1400100)+1 种基金Shanghai Talent Developing Foundation, China(No.001)Specialized Foundation for Excellent Talent of Shanghai,China
文摘There are a number of dirty data in observation data set derived from integrated ocean observing network system. Thus, the data must be carefully and reasonably processed before they are used for forecasting or analysis. This paper proposes a data pre-processing model based on intelligent algorithms. Firstly, we introduce the integrated network platform of ocean observation. Next, the preprocessing model of data is presemed, and an imelligent cleaning model of data is proposed. Based on fuzzy clustering, the Kohonen clustering network is improved to fulfill the parallel calculation of fuzzy c-means clustering. The proposed dynamic algorithm can automatically f＇md the new clustering center with the updated sample data. The rapid and dynamic performance of the model makes it suitable for real time calculation, and the efficiency and accuracy of the model is proved by test results through observation data analysis.
基金National Natural Science Foundation of China(No.61903291)Industrialization Project of Shaanxi Provincial Department of Education(No.18JC018)。
文摘A signal pre-processing method based on optimal variational mode decomposition(OVMD)is proposed to improve the efficiency and accuracy of local data filtering and analysis of edge nodes in distributed electromechanical systems.Firstly,the singular points of original signals are eliminated effectively by using the first-order difference method.Then the OVMD method is applied for signal modal decomposition.Furthermore,correlation analysis is conducted to determine the degree of correlation between each mode and the original signal,so as to accurately separate the real operating signal from noise signal.On the basis of theoretical analysis and simulation,an edge node pre-processing system for distributed electromechanical system is designed.Finally,by virtue of the signal-to-noise ratio(SNR)and root-mean-square error(RMSE)indicators,the signal pre-processing effect is evaluated.The experimental results show that the OVMD-based edge node pre-processing system can extract signals with different characteristics and improve the SNR of reconstructed signals.Due to its high fidelity and reliability,this system can also provide data quality assurance for subsequent system health monitoring and fault diagnosis.
文摘The solution of linear equation group can be applied to the oil exploration, the structure vibration analysis, the computational fluid dynamics, and other fields. When we make the in-depth analysis of some large or very large complicated structures, we must use the parallel algorithm with the aid of high-performance computers to solve complex problems. This paper introduces the implementation process having the parallel with sparse linear equations from the perspective of sparse linear equation group.
文摘Microarray data is inherently noisy due to the noise contaminated from various sources during the preparation of microarray slide and thus it greatly affects the accuracy of the gene expression. How to eliminate the effect of the noise constitutes a challenging problem in microarray analysis. Efficient denoising is often a necessary and the first step to be taken before the image data is analyzed to compensate for data corruption and for effective utilization for these data. Hence preprocessing of microarray image is an essential to eliminate the background noise in order to enhance the image quality and effective quantification. Existing denoising techniques based on transformed domain have been utilized for microarray noise reduction with their own limitations. The objective of this paper is to introduce novel preprocessing techniques such as optimized spatial resolution (OSR) and spatial domain filtering (SDF) for reduction of noise from microarray data and reduction of error during quantification process for estimating the microarray spots accurately to determine expression level of genes. Besides combined optimized spatial resolution and spatial filtering is proposed and found improved denoising of microarray data with effective quantification of spots. The proposed method has been validated in microarray images of gene expression profiles of Myeloid Leukemia using Stanford Microarray Database with various quality measures such as signal to noise ratio, peak signal to noise ratio, image fidelity, structural content, absolute average difference and correlation quality. It was observed by quantitative analysis that the proposed technique is more efficient for denoising the microarray image which enables to make it suitable for effective quantification.
基金support from the National Natural Science Foundation of China(Grant Nos:52379103 and 52279103)the Natural Science Foundation of Shandong Province(Grant No:ZR2023YQ049).
文摘Bayesian-optimized lithology identification has important basic geological research significance and engineering application value,and this paper proposes a Bayesian-optimized lithology identification method based on machine learning of rock visible and near-infrared spectral data.First,the rock spectral data are preprocessed using Savitzky-Golay(SG)smoothing to remove the noise of the spectral data;then,the preprocessed rock spectral data are downscaled using Principal Component Analysis(PCA)to reduce the redundancy of the data,optimize the effective discriminative information,and obtain the rock spectral features;finally,a Bayesian-optimized lithology identification model is established based on rock spectral features,optimize the model hyperparameters using Bayesian optimization(BO)algorithm to avoid the combination of hyperparameters falling into the local optimal solution,and output the predicted type of rock,so as to realize the Bayesian-optimized lithology identification.In addition,this paper conducts comparative analysis on models based on Artificial Neural Network(ANN)/Random Forest(RF),dimensionality reduction/full band,and optimization algorithms.It uses the confusion matrix,accuracy,Precison(P),Recall(R)and F_(1)values(F_(1))as the evaluation indexes of model accuracy.The results indicate that the lithology identification model optimized by the BO-ANN after dimensionality reduction achieves an accuracy of up to 99.80%,up to 99.79%and up to 99.79%.Compared with the BO-RF model,it has higher identification accuracy and better stability for each type of rock identification.The experiments and reliability analysis show that the Bayesian-optimized lithology identification method proposed in this paper has good robustness and generalization performance,which is of great significance for realizing fast,accurate and Bayesian-optimized lithology identification in tunnel site.
基金Supported by Natural Science Foundation of HuBei Province(2022CFB299).
文摘This paper studies the problem of the spectral radius of the uniform hypergraph determined by the signless Laplacian matrix.The upper bound of the spectral radius of a uniform hypergraph is obtained by using Rayleigh principle and the perturbation of the spectral radius under moving the edge operation,and the extremal hypergraphs are characterized for both supertree and unicyclic hypergraphs.The spectral radius of the graph is generalized.
基金Supported by NSFC(No.12271162)Natural Science Foundation of Shanghai(No.22ZR1416300).
文摘A graph G is H-free,if it contains no H as a subgraph.A graph G is said to be H-minor free,if it does not contain H as a minor.In 2010,Nikiforov asked that what the maximum spectral radius of an H-free graph of order n is.In this paper,we consider some Brualdi-Solheid-Turan type problems on bipartite graphs.In 2015,Zhai,Lin and Gong in[Linear Algebra Appl.,2015,471:21-27]proved that if G is a bipartite graph with order n≥2k+2 and ρ(G)≥ρ(K_(k,n-k)),then G contains a C_(2k+2) unless G≌K_(k,n-k).First,we give a new and more simple proof for the above theorem.Second,we prove that if G is a bipartite graph with order n≥2k+2 and ρ(G)≥ρ(K_(k,n-k)),then G contains all T_(2k+3) unless G≌K_(k,n-k).Finally,we prove that among all outerplanar bipartite graphs on n≥308026 vertices,K_(1,n-1) attains the maximum spectral radius.
文摘For a graph G,a vertex is said to be pendant if its neighborhood contains exactly one vertex.In this paper,we determine the extremal graphs among all n-vertex graphs with the minimum spectral radius andβpendant vertices,whereβe{1,2,3,4,n-3,n-2,n-1}.
文摘For segmented detectors,surface flatness is critical as it directly influences both energy resolution and image clarity.Additionally,the limited adjustment range of the segmented detectors necessitates precise benchmark construction.This paper proposes an architecture for detecting detector flatness based on channel spectral dispersion.By measuring the dispersion fringes for coplanar adjustment,the final adjustment residual is improved to better than 300 nm.This result validates the feasibility of the proposed technology and provides significant technical support for the development of next-generation large-aperture sky survey equipment.
