Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-de...Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.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
Soil cement bentonite(SCB)is a common material for constructing vertical cutoff walls to prevent groundwater migration at contaminated industrial sites.However,site contaminants can degrade the durability of the cutof...Soil cement bentonite(SCB)is a common material for constructing vertical cutoff walls to prevent groundwater migration at contaminated industrial sites.However,site contaminants can degrade the durability of the cutoff wall.To enhance its performance,this study developed a silica fume-SCB(SSCB).The macroscopic and microscopic properties of SSCB were assessed by unconfined compressive strength test,variable head permeability test,X-ray diffraction(XRD),scanning electron microscopy(SEM)and nuclear magnetic resonance(NMR)spectroscopy.The correlation between its multi-scale properties was analyzed based on pore characteristics.The results indicate that increasing the silica fume substitution ratio improved SSCB strength,especially in the middle and late curing stages.Moreover,increasing the substitution ratio decreased SSCB permeability coefficient,with a more pronounced effect in earlier curing stages.Silica fume addition also refined SSCB pore structure and reduced its porosity.The fractal dimension was used to quantify SSCB pore structure complexity.Increasing silica fume content reduced small pore fractal dimension in SSCB.Concurrently,SSCB strength increased and SSCB permeability coefficient decreased.The findings of this research will demonstrate the great potential of SSCB backfill for practical applications.展开更多
The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results ...The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results of various sensors for the fusion of the detection layer.This paper proposes a multi-scale and multi-sensor data fusion strategy in the front end of perception and accomplishes a multi-sensor function disparity map generation scheme.A binocular stereo vision sensor composed of two cameras and a light deterction and ranging(LiDAR)sensor is used to jointly perceive the environment,and a multi-scale fusion scheme is employed to improve the accuracy of the disparity map.This solution not only has the advantages of dense perception of binocular stereo vision sensors but also considers the perception accuracy of LiDAR sensors.Experiments demonstrate that the multi-scale multi-sensor scheme proposed in this paper significantly improves disparity map estimation.展开更多
In this study,an underwater image enhancement method based on multi-scale adversarial network was proposed to solve the problem of detail blur and color distortion in underwater images.Firstly,the local features of ea...In this study,an underwater image enhancement method based on multi-scale adversarial network was proposed to solve the problem of detail blur and color distortion in underwater images.Firstly,the local features of each layer were enhanced into the global features by the proposed residual dense block,which ensured that the generated images retain more details.Secondly,a multi-scale structure was adopted to extract multi-scale semantic features of the original images.Finally,the features obtained from the dual channels were fused by an adaptive fusion module to further optimize the features.The discriminant network adopted the structure of the Markov discriminator.In addition,by constructing mean square error,structural similarity,and perceived color loss function,the generated image is consistent with the reference image in structure,color,and content.The experimental results showed that the enhanced underwater image deblurring effect of the proposed algorithm was good and the problem of underwater image color bias was effectively improved.In both subjective and objective evaluation indexes,the experimental results of the proposed algorithm are better than those of the comparison algorithm.展开更多
In order to extract the richer feature information of ship targets from sea clutter, and address the high dimensional data problem, a method termed as multi-scale fusion kernel sparse preserving projection(MSFKSPP) ba...In order to extract the richer feature information of ship targets from sea clutter, and address the high dimensional data problem, a method termed as multi-scale fusion kernel sparse preserving projection(MSFKSPP) based on the maximum margin criterion(MMC) is proposed for recognizing the class of ship targets utilizing the high-resolution range profile(HRRP). Multi-scale fusion is introduced to capture the local and detailed information in small-scale features, and the global and contour information in large-scale features, offering help to extract the edge information from sea clutter and further improving the target recognition accuracy. The proposed method can maximally preserve the multi-scale fusion sparse of data and maximize the class separability in the reduced dimensionality by reproducing kernel Hilbert space. Experimental results on the measured radar data show that the proposed method can effectively extract the features of ship target from sea clutter, further reduce the feature dimensionality, and improve target recognition performance.展开更多
Large calculation error can be formed by directly employing the conventional Yee’s grid to curve surfaces.In order to alleviate such condition,unconditionally stable CrankNicolson Douglas-Gunn(CNDG)algorithm with is ...Large calculation error can be formed by directly employing the conventional Yee’s grid to curve surfaces.In order to alleviate such condition,unconditionally stable CrankNicolson Douglas-Gunn(CNDG)algorithm with is proposed for rotationally symmetric multi-scale problems in anisotropic magnetized plasma.Within the CNDG algorithm,an alternative scheme for the simulation of anisotropic plasma is proposed in body-of-revolution domains.Convolutional perfectly matched layer(CPML)formulation is proposed to efficiently solve the open region problems.Numerical example is carried out for the illustration of effectiveness including the efficiency,resources,and absorption.Through the results,it can be concluded that the proposed scheme shows considerable performance during the simulation.展开更多
This paper conducted a systematic survey and zoogeographical region analysis of the family Sphingidae in the Guokui Mountain,Heilongjiang Province.Collections were made from May 2023 to August 2024 using the light-tra...This paper conducted a systematic survey and zoogeographical region analysis of the family Sphingidae in the Guokui Mountain,Heilongjiang Province.Collections were made from May 2023 to August 2024 using the light-trap method.A total of 14 species and 11 subspecies from 18 genera and three subfamilies were recorded.One species(Ambulyx tobii)and two subspecies(Ambulyx japonica koreana and Clanis undulosa undulosa)were new records for Heilongjiang Province.The study showed that the subfamily Smerinthinae had the most species(subspecies),while the subfamily Sphinginae had the fewest.Among the world's zoogeographical region,most species(subspecies)in the Guokui Mountain belonged to the palearctic region,with eight species and seven subspecies were also found in the oriental region.This indicated a close biogeographic connection between the two regions.Among the Chinese zoogeographical regions,the northeastern territory,northern territory and northwestern territory had the most abundant species(subspecies).It was also found that the distribution pattern types of hawkmoths in the Guokui Mountain were diverse,with the'northeastern territory-northern territory-northwestern territory'and'northeastern territory-northern territorynorthwestern territory-western plateau-southwestern territory-central territory-southeastern territory'types having the most species(subspecies).In addition,the Guokui Mountain hawkmoths were mostly distributed interregionally.The distribution patterns that contained the northeastern territory were the most numerous,followed by the northern territory.The rich diversity of the family Sphingidae in the Guokui Mountain was closely related to the unique climate,environment and vegetation types in the area.The results could help to improve the biodiversity database of Heilongjiang Province and researches on hawkmoths.展开更多
A new algorithm for segmentation of suspected lung ROI(regions of interest)by mean-shift clustering and multi-scale HESSIAN matrix dot filtering was proposed.Original image was firstly filtered by multi-scale HESSIAN ...A new algorithm for segmentation of suspected lung ROI(regions of interest)by mean-shift clustering and multi-scale HESSIAN matrix dot filtering was proposed.Original image was firstly filtered by multi-scale HESSIAN matrix dot filters,round suspected nodular lesions in the image were enhanced,and linear shape regions of the trachea and vascular were suppressed.Then,three types of information,such as,shape filtering value of HESSIAN matrix,gray value,and spatial location,were introduced to feature space.The kernel function of mean-shift clustering was divided into product form of three kinds of kernel functions corresponding to the three feature information.Finally,bandwidths were calculated adaptively to determine the bandwidth of each suspected area,and they were used in mean-shift clustering segmentation.Experimental results show that by the introduction of HESSIAN matrix of dot filtering information to mean-shift clustering,nodular regions can be segmented from blood vessels,trachea,or cross regions connected to the nodule,non-nodular areas can be removed from ROIs properly,and ground glass object(GGO)nodular areas can also be segmented.For the experimental data set of 127 different forms of nodules,the average accuracy of the proposed algorithm is more than 90%.展开更多
Focused on the task of fast and accurate armored target detection in ground battlefield,a detection method based on multi-scale representation network(MS-RN) and shape-fixed Guided Anchor(SF-GA)scheme is proposed.Firs...Focused on the task of fast and accurate armored target detection in ground battlefield,a detection method based on multi-scale representation network(MS-RN) and shape-fixed Guided Anchor(SF-GA)scheme is proposed.Firstly,considering the large-scale variation and camouflage of armored target,a new MS-RN integrating contextual information in battlefield environment is designed.The MS-RN extracts deep features from templates with different scales and strengthens the detection ability of small targets.Armored targets of different sizes are detected on different representation features.Secondly,aiming at the accuracy and real-time detection requirements,improved shape-fixed Guided Anchor is used on feature maps of different scales to recommend regions of interests(ROIs).Different from sliding or random anchor,the SF-GA can filter out 80% of the regions while still improving the recall.A special detection dataset for armored target,named Armored Target Dataset(ARTD),is constructed,based on which the comparable experiments with state-of-art detection methods are conducted.Experimental results show that the proposed method achieves outstanding performance in detection accuracy and efficiency,especially when small armored targets are involved.展开更多
Effective bearing fault diagnosis is vital for the safe and reliable operation of rotating machinery.In practical applications,bearings often work at various rotational speeds as well as load conditions.Yet,the bearin...Effective bearing fault diagnosis is vital for the safe and reliable operation of rotating machinery.In practical applications,bearings often work at various rotational speeds as well as load conditions.Yet,the bearing fault diagnosis under multiple conditions is a new subject,which needs to be further explored.Therefore,a multi-scale deep belief network(DBN)method integrated with attention mechanism is proposed for the purpose of extracting the multi-scale core features from vibration signals,containing four primary steps:preprocessing of multi-scale data,feature extraction,feature fusion,and fault classification.The key novelties include multi-scale feature extraction using multi-scale DBN algorithm,and feature fusion using attention mecha-nism.The benchmark dataset from University of Ottawa is applied to validate the effectiveness as well as advantages of this method.Furthermore,the aforementioned method is compared with four classical fault diagnosis methods reported in the literature,and the comparison results show that our pro-posed method has higher diagnostic accuracy and better robustness.展开更多
In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on m...In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. With the only priori knowledge of signal to noise ratio(SNR), the method of extracting multi-scale wavelet entropy features of wavelet coefficients from different received signals were combined with calculating uneven weight factor and stability weight factor of the extracted multi-dimensional characteristics. Radar emitter signals of different modulation types and different parameters modulated were recognized through feature weighting and feature fusion. Theoretical analysis and simulation results show that the presented algorithm has a high recognition rate. Additionally, when the SNR is greater than-4 d B, the correct recognition rate is higher than 93%. Hence, the proposed algorithm has great application value.展开更多
The vibration problem of a fluid conveying cylindrical shell consisted of newly developed multi-scale hybrid nanocomposites is solved in the present manuscript within the framework of an analytical solution.The consis...The vibration problem of a fluid conveying cylindrical shell consisted of newly developed multi-scale hybrid nanocomposites is solved in the present manuscript within the framework of an analytical solution.The consistent material is considered to be made from an initial matrix strengthened via both macro-and nano-scale reinforcements.The influence of nanofillers’agglomeration,generated due to the high surface to volume ratio in nanostructures,is included by implementing Eshelby-Mori-Tanaka homogenization scheme.Afterwards,the equivalent material properties of the carbon nanotube reinforced(CNTR)nanocomposite are coupled with those of CFs within the framework of a modified rule of mixture.On the other hand,the influences of viscous flow are covered by extending the Navier-Stokes equation for cylinders.A cylindrical coordinate system is chosen and mixed with the infinitesimal strains of first-order shear deformation theory of shells to obtain the motion equations on the basis of the dynamic form of principle of virtual work.Next,the achieved governing equations will be solved by Galerkin’s method to reach the natural frequency of the structure for both simply supported and clamped boundary conditions.Presenting a set of illustrations,effects of each parameter on the dimensionless frequency of nanocomposite shells will be shown graphically.展开更多
The Daubechies second order wavelet was applied to decompose pressure fluctuation signals with the gas flux varying from 0.18 to 0.90 m3/h and the solid mass fraction from 0 to 20% and scales 1?9 detail signals and th...The Daubechies second order wavelet was applied to decompose pressure fluctuation signals with the gas flux varying from 0.18 to 0.90 m3/h and the solid mass fraction from 0 to 20% and scales 1?9 detail signals and the 9th scale approximation signals. The pressure signals were studied by multi-scale and R/S analysis method. Hurst analysis method was applied to analyze multi-fractal characteristics of different scale signals. The results show that the characteristics of mono-fractal under scale 1 and scale 2, and bi-fractal under scale 3?9 are effective in deducing the hydrodynamics in slurry bubbling flow system. The measured pressure signals are decomposed to micro-scale signals, meso-scale signals and macro-scale signals. Micro-scale and macro-scale signals are of mono-fractal characteristics, and meso-scale signals are of bi-fractal characteristics. By analyzing energy distribution of different scale signals,it is shown that pressure fluctuations mainly reflects meso-scale interaction between the particles and the bubble.展开更多
The cold regions are located in high latitudes and cold climates.The local excellent ornamental plant resources are relatively scarce.The plant species that are suitable for both ornamental and productive benefits of ...The cold regions are located in high latitudes and cold climates.The local excellent ornamental plant resources are relatively scarce.The plant species that are suitable for both ornamental and productive benefits of landscape of flower sea construction are also even fewer.Therefore,it is imperative to introduce and screen the plant resources suitable for cold regions to create the landscape of flower sea.The rape,an oilseed crop,was used as a research object in order to create a productive flower landscape with both ornamental and economic values in cold regions.Four rape flower varieties,Qingza No.5,7,9,and 11,were introduced from Qinghai Hufeng Agricultural Science and Technology Group Co.,Ltd.They were planted in the experimental practice base of Northeast Agricultural University in three batches.Development characteristics and seed yield of rape flowers on different sowing dates were studied.The fuzzy probability method was used to comprehensively evaluate the varieties.The results showed that the rape flowers grew well in Harbin City during the experimental sowing period,which could form a good landscape of flower sea and had a considerable rapeseed yield.It could be widely used in cold urban and rural areas,such as Harbin City.In view of the experimental results,the strategies of creating a productive landscape of rape flower sea were proposed and the economic benefits were analyzed.It could change the status quo of a uniform landscape of flower sea in cold regions,help the development of rural tourism,and promote local economic income.展开更多
[Background]As one of the most serious environmental issues in the world,soil erosion causes water pollution,reservoir siltation,soil productivity decline,thus threatens agricultural systems and even affects global cl...[Background]As one of the most serious environmental issues in the world,soil erosion causes water pollution,reservoir siltation,soil productivity decline,thus threatens agricultural systems and even affects global climate.The benefits of ecological soil and water conservation measures(ESWCMs,such as micro basins tillage and contour tillage)are widely understood,including runoff and soil loss reducing to a certain extent when compared with traditional tillage.While few studies have focused on China’s different soil types and erosion characteristics.[Methods]We reviewed literature from Web of Science,Scopus,and China National Knowledge Infrastructure using terms like“Conservation practice”“Contour tillage”“Runoff”“Sediment”“Erosion”and“China”and retained literatures based on criteria such as natural or simulated precipitation,runoff or soil loss data,reported replications and statistics,recorded factors like location and slope,and at least two data pairs per group.Ultimately,49 literatures were selected to quantify the impacts on different ESWCMs and identify the slope and precipitation for the greatest runoff and sediment reduction by calculating the log response ratio(LRR).[Results]The three regions’soil and water conservation benefits varied due to the differences in climate,terrain,and soil properties:1)ESWCMs applied in the black soil region of Northeast China were the most effective in reducing runoff and soil loss(66.65%runoff and 75.83%sediment),followed by those applied in the purple soil region of Southwest China(39.98%runoff and 58.30%sediment)and loess soil region of Northwest China(16.36%runoff and 32.44%sediment).2)Micro basins tillage(MBT)(71.79%runoff and 87.03%sediment)no-tillage with mulch(NTM)(17.30%runoff and 32.51%sediment),collecting soil to form a ridge with no-till(CSNT)(55.78%runoff and 71.36%sediment reduction)were the most efficient soil and water conservation measures in controlling water erosion in the black soil of Northeast China,the loess soil region of Northwest China and the purple soil region of Southwest China,respectively.3)The slope gradients ranged from 0-3°,>3°-5°and>10°-15°(0-3°:97.09%;>3°-5°:74.62%;and>10°-15°:39.41%)caused the largest reduction of runoff in the black soil region of Northeast China,the loess soil region of Northwest China,and the purple soil region of Southwest China.Meanwhile,the effects of sediment reduction were the most obvious,ranging from 0-3°,>10°-15°,and>20°-25°(0-3°:89.32%;>10°-15°:75.94%;and>20°-25°:67.25%).4)The effect of ESWCMs under rainstorms was the most obvious in the black soil region of Northeast China.The effect on runoff reduction under light rain in the purple soil region of Southwest China was the most obvious,but it failed to pass the significance test in sediment reduction.[Conclusions]The results provided optimal conservation tillage measures for three regions,different slopes and different rainfalls,and provided data support for reducing regional soil and water loss in China.展开更多
With the development of the economy in China,the regionalization of China Yuan is accelerated. This paper analyzes the existing conditions of the regionalization of China Yuan in ASEAN theoretically and practically,po...With the development of the economy in China,the regionalization of China Yuan is accelerated. This paper analyzes the existing conditions of the regionalization of China Yuan in ASEAN theoretically and practically,points out the restricting factors and puts forward the path of the regionalization of China Yuan in ASEAN — with Singapore,Thailand,Malaysia and Indonesia being the pilot countries and realizing regionalization of China Yuan in ASEAN gradually.展开更多
Forest fire accidents caused by distribution line faults occur frequently,resulting in heavy impacts on people’s safety and social and economic development.Currently,there are few risk assessments for forest fires in...Forest fire accidents caused by distribution line faults occur frequently,resulting in heavy impacts on people’s safety and social and economic development.Currently,there are few risk assessments for forest fires induced by over-head distribution lines,and existing assessment methods may have difficulties in data acquisition.On this basis,a novel as-sessment framework based on an analytic hierarchy process,a Bayesian network and a Fussel-Vesely importance metric is proposed in this paper.The framework combines field research and historical operation and maintenance data to assess the regional-scale risk of forest fires induced by overhead distribution lines to derive the probability of forest fires and to identify high-risk lines and key hazard events in the assessment region.Finally,taking the southern Anhui region as an ex-ample,the annual fire probability of forest fires induced by overhead distribution lines in the southern Anhui region is 5.88%,and rectification measures are proposed.This study provides management with a complete assessment framework that optimizes the difficulty of data collection and allows for additional targeted corrective measures to be proposed for the entire region and route on the basis of the assessment results.展开更多
The laser-guided bomb(LGB)is an air-to-ground pre-cision-guided weapon that offers high hit rates,great power,and ease of use.LGBs are guided by semi-active laser ground-seek-ing technology,which means that atmospheri...The laser-guided bomb(LGB)is an air-to-ground pre-cision-guided weapon that offers high hit rates,great power,and ease of use.LGBs are guided by semi-active laser ground-seek-ing technology,which means that atmospheric conditions can affect their accuracy.The spatial release region(SRR)of LGBs is difficult to calculate precisely,especially when there is a poor field of view.This can result in a lower real hit probability.To increase the hit probability of LGBs in tough atmospheric situa-tions,a novel method for calculating the SRR has been pro-posed.This method is based on the transmittance model of the 1.06μm laser in atmospheric species and the laser diffuse reflection model of the target surface to determine the capture target time of the laser seeker.Then,it calculates the boundary ballistic space starting position by ballistic model and gets the spatial scope of the spatial release region.This method can determine the release region of LGBs based on flight test data such as instantaneous velocity,altitude,off-axis angle,and atmospheric visibility.By more effectively employing aircraft release conditions,atmospheric visibility and other factors,the SRR calculation method can improve LGB hit probabi-lity by 9.2%.展开更多
Biochar is widely used to improve soil physical properties and carbon sequestration. However, few studies focuse on the impact of maize stalk biochar on labile organic carbon(LOC) pool and the relationship between phy...Biochar is widely used to improve soil physical properties and carbon sequestration. However, few studies focuse on the impact of maize stalk biochar on labile organic carbon(LOC) pool and the relationship between physical properties and LOC fractions. A field positioning experiment was performed in Mollisols region of Northeast China to evaluate the influence of maize stalk biochar on the spatial distribution and temporal changes of physical properties and LOC fractions. Maize stalk biochar treatments included C1(1.5 kg·hm^(-2)), C2(3 kg·hm^(-2)), C3(15 kg·hm^(-2)), C4(30 kg·hm^(-2)), and CK(0). The results showed that maize stalk biochar increased soil water contents(SWC) and soil porosity(SP), but reduced bulk density(BD). Maize stalk biochar reduced dissolved organic carbon(DOC) contents in the 0-20 cm soil layer, ranging from 0.25 g·kg^(-1) to 0.31 g·kg^(-1) in harvest period, while increased in the 20-40 cm soil layer. In addition, the application of biochar had a significant impact on the spatial distribution and temporal change of SWC, BD, SP, DOC, hot-water extractable carbon(HWC), acid hydrolyzed organic carbon(AHC Ⅰ, Ⅱ), and readily oxidized organic carbon(ROC). High amounts of maize stalk biochar up-regulated the contents of soil organic carbon SOC, HWC, AHC Ⅰ, AHC Ⅱ, and ROC. In addition, SWC and SP were the key physical factors to affect LOC fractions. In conclusions, maize stalk biochar could improve physical properties, and then influence LOC fractions, and maize stalk biochar could be used as an organic amendment for restoring degraded soils governed by their rates of addition.展开更多
基金Projects(41601424,41171351)supported by the National Natural Science Foundation of ChinaProject(2012CB719906)supported by the National Basic Research Program of China(973 Program)+2 种基金Project(14JJ1007)supported by the Hunan Natural Science Fund for Distinguished Young Scholars,ChinaProject(2017M610486)supported by the China Postdoctoral Science FoundationProjects(2017YFB0503700,2017YFB0503601)supported by the National Key Research and Development Foundation of China
文摘Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.
基金Supported by the Henan Province Key Research and Development Project(231111211300)the Central Government of Henan Province Guides Local Science and Technology Development Funds(Z20231811005)+2 种基金Henan Province Key Research and Development Project(231111110100)Henan Provincial Outstanding Foreign Scientist Studio(GZS2024006)Henan Provincial Joint Fund for Scientific and Technological Research and Development Plan(Application and Overcoming Technical Barriers)(242103810028)。
文摘The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.
基金Project(2019YFC1803601)supported by the National Key Research and Development Program of ChinaProject(52274182)supported by the National Natural Science Foundation of China+1 种基金Project(2021zzts0274)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(CX20210295)supported by the Postgraduate Scientific Research Innovation Project of Hunan Province,China。
文摘Soil cement bentonite(SCB)is a common material for constructing vertical cutoff walls to prevent groundwater migration at contaminated industrial sites.However,site contaminants can degrade the durability of the cutoff wall.To enhance its performance,this study developed a silica fume-SCB(SSCB).The macroscopic and microscopic properties of SSCB were assessed by unconfined compressive strength test,variable head permeability test,X-ray diffraction(XRD),scanning electron microscopy(SEM)and nuclear magnetic resonance(NMR)spectroscopy.The correlation between its multi-scale properties was analyzed based on pore characteristics.The results indicate that increasing the silica fume substitution ratio improved SSCB strength,especially in the middle and late curing stages.Moreover,increasing the substitution ratio decreased SSCB permeability coefficient,with a more pronounced effect in earlier curing stages.Silica fume addition also refined SSCB pore structure and reduced its porosity.The fractal dimension was used to quantify SSCB pore structure complexity.Increasing silica fume content reduced small pore fractal dimension in SSCB.Concurrently,SSCB strength increased and SSCB permeability coefficient decreased.The findings of this research will demonstrate the great potential of SSCB backfill for practical applications.
基金the National Key R&D Program of China(2018AAA0103103).
文摘The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results of various sensors for the fusion of the detection layer.This paper proposes a multi-scale and multi-sensor data fusion strategy in the front end of perception and accomplishes a multi-sensor function disparity map generation scheme.A binocular stereo vision sensor composed of two cameras and a light deterction and ranging(LiDAR)sensor is used to jointly perceive the environment,and a multi-scale fusion scheme is employed to improve the accuracy of the disparity map.This solution not only has the advantages of dense perception of binocular stereo vision sensors but also considers the perception accuracy of LiDAR sensors.Experiments demonstrate that the multi-scale multi-sensor scheme proposed in this paper significantly improves disparity map estimation.
文摘In this study,an underwater image enhancement method based on multi-scale adversarial network was proposed to solve the problem of detail blur and color distortion in underwater images.Firstly,the local features of each layer were enhanced into the global features by the proposed residual dense block,which ensured that the generated images retain more details.Secondly,a multi-scale structure was adopted to extract multi-scale semantic features of the original images.Finally,the features obtained from the dual channels were fused by an adaptive fusion module to further optimize the features.The discriminant network adopted the structure of the Markov discriminator.In addition,by constructing mean square error,structural similarity,and perceived color loss function,the generated image is consistent with the reference image in structure,color,and content.The experimental results showed that the enhanced underwater image deblurring effect of the proposed algorithm was good and the problem of underwater image color bias was effectively improved.In both subjective and objective evaluation indexes,the experimental results of the proposed algorithm are better than those of the comparison algorithm.
基金supported by the National Natural Science Foundation of China (62271255,61871218)the Fundamental Research Funds for the Central University (3082019NC2019002)+1 种基金the Aeronautical Science Foundation (ASFC-201920007002)the Program of Remote Sensing Intelligent Monitoring and Emergency Services for Regional Security Elements。
文摘In order to extract the richer feature information of ship targets from sea clutter, and address the high dimensional data problem, a method termed as multi-scale fusion kernel sparse preserving projection(MSFKSPP) based on the maximum margin criterion(MMC) is proposed for recognizing the class of ship targets utilizing the high-resolution range profile(HRRP). Multi-scale fusion is introduced to capture the local and detailed information in small-scale features, and the global and contour information in large-scale features, offering help to extract the edge information from sea clutter and further improving the target recognition accuracy. The proposed method can maximally preserve the multi-scale fusion sparse of data and maximize the class separability in the reduced dimensionality by reproducing kernel Hilbert space. Experimental results on the measured radar data show that the proposed method can effectively extract the features of ship target from sea clutter, further reduce the feature dimensionality, and improve target recognition performance.
文摘Large calculation error can be formed by directly employing the conventional Yee’s grid to curve surfaces.In order to alleviate such condition,unconditionally stable CrankNicolson Douglas-Gunn(CNDG)algorithm with is proposed for rotationally symmetric multi-scale problems in anisotropic magnetized plasma.Within the CNDG algorithm,an alternative scheme for the simulation of anisotropic plasma is proposed in body-of-revolution domains.Convolutional perfectly matched layer(CPML)formulation is proposed to efficiently solve the open region problems.Numerical example is carried out for the illustration of effectiveness including the efficiency,resources,and absorption.Through the results,it can be concluded that the proposed scheme shows considerable performance during the simulation.
基金Supported by the Department of Ecology and Environment of Heilongjiang Province(HST2022ST003)。
文摘This paper conducted a systematic survey and zoogeographical region analysis of the family Sphingidae in the Guokui Mountain,Heilongjiang Province.Collections were made from May 2023 to August 2024 using the light-trap method.A total of 14 species and 11 subspecies from 18 genera and three subfamilies were recorded.One species(Ambulyx tobii)and two subspecies(Ambulyx japonica koreana and Clanis undulosa undulosa)were new records for Heilongjiang Province.The study showed that the subfamily Smerinthinae had the most species(subspecies),while the subfamily Sphinginae had the fewest.Among the world's zoogeographical region,most species(subspecies)in the Guokui Mountain belonged to the palearctic region,with eight species and seven subspecies were also found in the oriental region.This indicated a close biogeographic connection between the two regions.Among the Chinese zoogeographical regions,the northeastern territory,northern territory and northwestern territory had the most abundant species(subspecies).It was also found that the distribution pattern types of hawkmoths in the Guokui Mountain were diverse,with the'northeastern territory-northern territory-northwestern territory'and'northeastern territory-northern territorynorthwestern territory-western plateau-southwestern territory-central territory-southeastern territory'types having the most species(subspecies).In addition,the Guokui Mountain hawkmoths were mostly distributed interregionally.The distribution patterns that contained the northeastern territory were the most numerous,followed by the northern territory.The rich diversity of the family Sphingidae in the Guokui Mountain was closely related to the unique climate,environment and vegetation types in the area.The results could help to improve the biodiversity database of Heilongjiang Province and researches on hawkmoths.
基金Projects(61172002,61001047,60671050)supported by the National Natural Science Foundation of ChinaProject(N100404010)supported by Fundamental Research Grant Scheme for the Central Universities,China
文摘A new algorithm for segmentation of suspected lung ROI(regions of interest)by mean-shift clustering and multi-scale HESSIAN matrix dot filtering was proposed.Original image was firstly filtered by multi-scale HESSIAN matrix dot filters,round suspected nodular lesions in the image were enhanced,and linear shape regions of the trachea and vascular were suppressed.Then,three types of information,such as,shape filtering value of HESSIAN matrix,gray value,and spatial location,were introduced to feature space.The kernel function of mean-shift clustering was divided into product form of three kinds of kernel functions corresponding to the three feature information.Finally,bandwidths were calculated adaptively to determine the bandwidth of each suspected area,and they were used in mean-shift clustering segmentation.Experimental results show that by the introduction of HESSIAN matrix of dot filtering information to mean-shift clustering,nodular regions can be segmented from blood vessels,trachea,or cross regions connected to the nodule,non-nodular areas can be removed from ROIs properly,and ground glass object(GGO)nodular areas can also be segmented.For the experimental data set of 127 different forms of nodules,the average accuracy of the proposed algorithm is more than 90%.
基金supported by the National Key Research and Development Program of China under grant 2016YFC0802904National Natural Science Foundation of China under grant61671470the Postdoctoral Science Foundation Funded Project of China under grant 2017M623423。
文摘Focused on the task of fast and accurate armored target detection in ground battlefield,a detection method based on multi-scale representation network(MS-RN) and shape-fixed Guided Anchor(SF-GA)scheme is proposed.Firstly,considering the large-scale variation and camouflage of armored target,a new MS-RN integrating contextual information in battlefield environment is designed.The MS-RN extracts deep features from templates with different scales and strengthens the detection ability of small targets.Armored targets of different sizes are detected on different representation features.Secondly,aiming at the accuracy and real-time detection requirements,improved shape-fixed Guided Anchor is used on feature maps of different scales to recommend regions of interests(ROIs).Different from sliding or random anchor,the SF-GA can filter out 80% of the regions while still improving the recall.A special detection dataset for armored target,named Armored Target Dataset(ARTD),is constructed,based on which the comparable experiments with state-of-art detection methods are conducted.Experimental results show that the proposed method achieves outstanding performance in detection accuracy and efficiency,especially when small armored targets are involved.
基金supported by the National Natural Science Foundation of China(62020106003,61873122,62303217)Aero Engine Corporation of China Industry-university-research Cooperation Project(HFZL2020CXY011)the Research Fund of State Key Laboratory of Mechanics and Control of Mechanical Structures(Nanjing University of Aeronautics and Astronautics)(MCMS-I-0121G03).
文摘Effective bearing fault diagnosis is vital for the safe and reliable operation of rotating machinery.In practical applications,bearings often work at various rotational speeds as well as load conditions.Yet,the bearing fault diagnosis under multiple conditions is a new subject,which needs to be further explored.Therefore,a multi-scale deep belief network(DBN)method integrated with attention mechanism is proposed for the purpose of extracting the multi-scale core features from vibration signals,containing four primary steps:preprocessing of multi-scale data,feature extraction,feature fusion,and fault classification.The key novelties include multi-scale feature extraction using multi-scale DBN algorithm,and feature fusion using attention mecha-nism.The benchmark dataset from University of Ottawa is applied to validate the effectiveness as well as advantages of this method.Furthermore,the aforementioned method is compared with four classical fault diagnosis methods reported in the literature,and the comparison results show that our pro-posed method has higher diagnostic accuracy and better robustness.
基金Project(61301095)supported by the National Natural Science Foundation of ChinaProject(QC2012C070)supported by Heilongjiang Provincial Natural Science Foundation for the Youth,ChinaProjects(HEUCF130807,HEUCFZ1129)supported by the Fundamental Research Funds for the Central Universities of China
文摘In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. With the only priori knowledge of signal to noise ratio(SNR), the method of extracting multi-scale wavelet entropy features of wavelet coefficients from different received signals were combined with calculating uneven weight factor and stability weight factor of the extracted multi-dimensional characteristics. Radar emitter signals of different modulation types and different parameters modulated were recognized through feature weighting and feature fusion. Theoretical analysis and simulation results show that the presented algorithm has a high recognition rate. Additionally, when the SNR is greater than-4 d B, the correct recognition rate is higher than 93%. Hence, the proposed algorithm has great application value.
文摘The vibration problem of a fluid conveying cylindrical shell consisted of newly developed multi-scale hybrid nanocomposites is solved in the present manuscript within the framework of an analytical solution.The consistent material is considered to be made from an initial matrix strengthened via both macro-and nano-scale reinforcements.The influence of nanofillers’agglomeration,generated due to the high surface to volume ratio in nanostructures,is included by implementing Eshelby-Mori-Tanaka homogenization scheme.Afterwards,the equivalent material properties of the carbon nanotube reinforced(CNTR)nanocomposite are coupled with those of CFs within the framework of a modified rule of mixture.On the other hand,the influences of viscous flow are covered by extending the Navier-Stokes equation for cylinders.A cylindrical coordinate system is chosen and mixed with the infinitesimal strains of first-order shear deformation theory of shells to obtain the motion equations on the basis of the dynamic form of principle of virtual work.Next,the achieved governing equations will be solved by Galerkin’s method to reach the natural frequency of the structure for both simply supported and clamped boundary conditions.Presenting a set of illustrations,effects of each parameter on the dimensionless frequency of nanocomposite shells will be shown graphically.
基金Project(NCET-05-0413)support by the Program for New Century Excellent Talents in UniversityProject(YB0142112) support by Priming Foundation of East China University of Science and Technology
文摘The Daubechies second order wavelet was applied to decompose pressure fluctuation signals with the gas flux varying from 0.18 to 0.90 m3/h and the solid mass fraction from 0 to 20% and scales 1?9 detail signals and the 9th scale approximation signals. The pressure signals were studied by multi-scale and R/S analysis method. Hurst analysis method was applied to analyze multi-fractal characteristics of different scale signals. The results show that the characteristics of mono-fractal under scale 1 and scale 2, and bi-fractal under scale 3?9 are effective in deducing the hydrodynamics in slurry bubbling flow system. The measured pressure signals are decomposed to micro-scale signals, meso-scale signals and macro-scale signals. Micro-scale and macro-scale signals are of mono-fractal characteristics, and meso-scale signals are of bi-fractal characteristics. By analyzing energy distribution of different scale signals,it is shown that pressure fluctuations mainly reflects meso-scale interaction between the particles and the bubble.
基金the National Nature Science Foundation of China(31770437)。
文摘The cold regions are located in high latitudes and cold climates.The local excellent ornamental plant resources are relatively scarce.The plant species that are suitable for both ornamental and productive benefits of landscape of flower sea construction are also even fewer.Therefore,it is imperative to introduce and screen the plant resources suitable for cold regions to create the landscape of flower sea.The rape,an oilseed crop,was used as a research object in order to create a productive flower landscape with both ornamental and economic values in cold regions.Four rape flower varieties,Qingza No.5,7,9,and 11,were introduced from Qinghai Hufeng Agricultural Science and Technology Group Co.,Ltd.They were planted in the experimental practice base of Northeast Agricultural University in three batches.Development characteristics and seed yield of rape flowers on different sowing dates were studied.The fuzzy probability method was used to comprehensively evaluate the varieties.The results showed that the rape flowers grew well in Harbin City during the experimental sowing period,which could form a good landscape of flower sea and had a considerable rapeseed yield.It could be widely used in cold urban and rural areas,such as Harbin City.In view of the experimental results,the strategies of creating a productive landscape of rape flower sea were proposed and the economic benefits were analyzed.It could change the status quo of a uniform landscape of flower sea in cold regions,help the development of rural tourism,and promote local economic income.
基金Science and Technology Major Project of Tibetan Autonomous Region of China(XZ202201ZD0005G02)National Natural Science Foundation of China(42277353)Chengdu Science and Technology Project(2022-YF05-01162-SN)。
文摘[Background]As one of the most serious environmental issues in the world,soil erosion causes water pollution,reservoir siltation,soil productivity decline,thus threatens agricultural systems and even affects global climate.The benefits of ecological soil and water conservation measures(ESWCMs,such as micro basins tillage and contour tillage)are widely understood,including runoff and soil loss reducing to a certain extent when compared with traditional tillage.While few studies have focused on China’s different soil types and erosion characteristics.[Methods]We reviewed literature from Web of Science,Scopus,and China National Knowledge Infrastructure using terms like“Conservation practice”“Contour tillage”“Runoff”“Sediment”“Erosion”and“China”and retained literatures based on criteria such as natural or simulated precipitation,runoff or soil loss data,reported replications and statistics,recorded factors like location and slope,and at least two data pairs per group.Ultimately,49 literatures were selected to quantify the impacts on different ESWCMs and identify the slope and precipitation for the greatest runoff and sediment reduction by calculating the log response ratio(LRR).[Results]The three regions’soil and water conservation benefits varied due to the differences in climate,terrain,and soil properties:1)ESWCMs applied in the black soil region of Northeast China were the most effective in reducing runoff and soil loss(66.65%runoff and 75.83%sediment),followed by those applied in the purple soil region of Southwest China(39.98%runoff and 58.30%sediment)and loess soil region of Northwest China(16.36%runoff and 32.44%sediment).2)Micro basins tillage(MBT)(71.79%runoff and 87.03%sediment)no-tillage with mulch(NTM)(17.30%runoff and 32.51%sediment),collecting soil to form a ridge with no-till(CSNT)(55.78%runoff and 71.36%sediment reduction)were the most efficient soil and water conservation measures in controlling water erosion in the black soil of Northeast China,the loess soil region of Northwest China and the purple soil region of Southwest China,respectively.3)The slope gradients ranged from 0-3°,>3°-5°and>10°-15°(0-3°:97.09%;>3°-5°:74.62%;and>10°-15°:39.41%)caused the largest reduction of runoff in the black soil region of Northeast China,the loess soil region of Northwest China,and the purple soil region of Southwest China.Meanwhile,the effects of sediment reduction were the most obvious,ranging from 0-3°,>10°-15°,and>20°-25°(0-3°:89.32%;>10°-15°:75.94%;and>20°-25°:67.25%).4)The effect of ESWCMs under rainstorms was the most obvious in the black soil region of Northeast China.The effect on runoff reduction under light rain in the purple soil region of Southwest China was the most obvious,but it failed to pass the significance test in sediment reduction.[Conclusions]The results provided optimal conservation tillage measures for three regions,different slopes and different rainfalls,and provided data support for reducing regional soil and water loss in China.
基金the staged achievement of the scientific research project of Beijing Language and Culture University(funded by basic scientific research of central colleges and universities)(15YJ0403)
文摘With the development of the economy in China,the regionalization of China Yuan is accelerated. This paper analyzes the existing conditions of the regionalization of China Yuan in ASEAN theoretically and practically,points out the restricting factors and puts forward the path of the regionalization of China Yuan in ASEAN — with Singapore,Thailand,Malaysia and Indonesia being the pilot countries and realizing regionalization of China Yuan in ASEAN gradually.
基金This work was supported by the National Key Research and Development Program of China(2022YFC3003101)the Fundamental Research Funds for the Central Universities(WK2320000050)the Science and Technology Program of State Grid Anhui Electric Power Co.,Ltd.(521205220001).
文摘Forest fire accidents caused by distribution line faults occur frequently,resulting in heavy impacts on people’s safety and social and economic development.Currently,there are few risk assessments for forest fires induced by over-head distribution lines,and existing assessment methods may have difficulties in data acquisition.On this basis,a novel as-sessment framework based on an analytic hierarchy process,a Bayesian network and a Fussel-Vesely importance metric is proposed in this paper.The framework combines field research and historical operation and maintenance data to assess the regional-scale risk of forest fires induced by overhead distribution lines to derive the probability of forest fires and to identify high-risk lines and key hazard events in the assessment region.Finally,taking the southern Anhui region as an ex-ample,the annual fire probability of forest fires induced by overhead distribution lines in the southern Anhui region is 5.88%,and rectification measures are proposed.This study provides management with a complete assessment framework that optimizes the difficulty of data collection and allows for additional targeted corrective measures to be proposed for the entire region and route on the basis of the assessment results.
基金This work was supported by the major research projects within the military-international class(JY2021B077).
文摘The laser-guided bomb(LGB)is an air-to-ground pre-cision-guided weapon that offers high hit rates,great power,and ease of use.LGBs are guided by semi-active laser ground-seek-ing technology,which means that atmospheric conditions can affect their accuracy.The spatial release region(SRR)of LGBs is difficult to calculate precisely,especially when there is a poor field of view.This can result in a lower real hit probability.To increase the hit probability of LGBs in tough atmospheric situa-tions,a novel method for calculating the SRR has been pro-posed.This method is based on the transmittance model of the 1.06μm laser in atmospheric species and the laser diffuse reflection model of the target surface to determine the capture target time of the laser seeker.Then,it calculates the boundary ballistic space starting position by ballistic model and gets the spatial scope of the spatial release region.This method can determine the release region of LGBs based on flight test data such as instantaneous velocity,altitude,off-axis angle,and atmospheric visibility.By more effectively employing aircraft release conditions,atmospheric visibility and other factors,the SRR calculation method can improve LGB hit probabi-lity by 9.2%.
基金Supported by the National Natural Science Foundation of China Project(31770582)。
文摘Biochar is widely used to improve soil physical properties and carbon sequestration. However, few studies focuse on the impact of maize stalk biochar on labile organic carbon(LOC) pool and the relationship between physical properties and LOC fractions. A field positioning experiment was performed in Mollisols region of Northeast China to evaluate the influence of maize stalk biochar on the spatial distribution and temporal changes of physical properties and LOC fractions. Maize stalk biochar treatments included C1(1.5 kg·hm^(-2)), C2(3 kg·hm^(-2)), C3(15 kg·hm^(-2)), C4(30 kg·hm^(-2)), and CK(0). The results showed that maize stalk biochar increased soil water contents(SWC) and soil porosity(SP), but reduced bulk density(BD). Maize stalk biochar reduced dissolved organic carbon(DOC) contents in the 0-20 cm soil layer, ranging from 0.25 g·kg^(-1) to 0.31 g·kg^(-1) in harvest period, while increased in the 20-40 cm soil layer. In addition, the application of biochar had a significant impact on the spatial distribution and temporal change of SWC, BD, SP, DOC, hot-water extractable carbon(HWC), acid hydrolyzed organic carbon(AHC Ⅰ, Ⅱ), and readily oxidized organic carbon(ROC). High amounts of maize stalk biochar up-regulated the contents of soil organic carbon SOC, HWC, AHC Ⅰ, AHC Ⅱ, and ROC. In addition, SWC and SP were the key physical factors to affect LOC fractions. In conclusions, maize stalk biochar could improve physical properties, and then influence LOC fractions, and maize stalk biochar could be used as an organic amendment for restoring degraded soils governed by their rates of addition.
