基于SOA光纤环镜的NRZ信号时钟分量的提取

采用 SOA(sem iconductor optical am plifier)光纤环镜将 2 .5 Gbit/ s的 NRZ(non- return- to- zero)信号转换为相应的 PRZ(pseudo- return- to- zero)信号 ,实现了 NRZ信号时钟分量的提取 .并分析了 SOA注入电流、环镜探测光光功率等系统参数的选取对转换输出的 PRZ信号的光信噪比、消光比及环镜透过率的影响 .

Schur Forms and Normal-Nilpotent Decompositions

Real and complex Schur forms have been receiving increasing attention from the fluid mechanics community recently,especially related to vortices and turbulence.Several decompositions of the velocity gradient tensor,such as the triple decomposition of motion(TDM)and normal-nilpotent decomposition(NND),have been proposed to analyze the local motions of fluid elements.However,due to the existence of different types and non-uniqueness of Schur forms,as well as various possible definitions of NNDs,confusion has spread widely and is harming the research.This work aims to clean up this confusion.To this end,the complex and real Schur forms are derived constructively from the very basics,with special consideration for their non-uniqueness.Conditions of uniqueness are proposed.After a general discussion of normality and nilpotency,a complex NND and several real NNDs as well as normal-nonnormal decompositions are constructed,with a brief comparison of complex and real decompositions.Based on that,several confusing points are clarified,such as the distinction between NND and TDM,and the intrinsic gap between complex and real NNDs.Besides,the author proposes to extend the real block Schur form and its corresponding NNDs for the complex eigenvalue case to the real eigenvalue case.But their justification is left to further investigations.

Ballistic Penetration Damage of Hybrid Thermoplastic Composites Reinforced with Kevlar and UHMWPE Fabrics

Polymer matrix types of fiber hybrid composites are key factors to improve ballistic impact damage tolerances.Here we report ballistic penetration damages of Kevlar/ultra-high molecular weight polyethylene(UHMWPE)hybrid composites with thermoplastic polyurethane(PU)matrix.The hybrid composites were penetrated by fragment-simulating projectiles(FSPs)using an air gun impact system.The effects of stacking sequences on the ballistic performance of hybrid composites were analyzed.Two types of specific energy absorption(the energy absorption per unit area density and the energy absorption per unit thickness)were investigated.It was found that the main damage modes of PU hybrid composites were fiber breakage,matrix damage,fiber pullout and interlayer delamination.The instantaneous deformation could not be used as a reference index for evaluating the ballistic performance of the target plate.The energy absorption process of the PU hybrid composites showed a nonlinear pattern.The hybrid structure affected the specific energy absorption of the materials.

Balancing the minimum error rate and minimum copy consumption in quantum state discrimination

Extracting more information and saving quantum resources are two main aims for quantum measurements.However,the optimization of strategies for these two objectives varies when discriminating between quantum states■and■through multiple measurements.In this study,we introduce a novel state discrimination model that reveals the intricate relationship between the average error rate and average copy consumption.By integrating these two crucial metrics and minimizing their weighted sum for any given weight value,our research underscores the infeasibility of simultaneously minimizing these metrics through local measurements with one-way communication.Our findings present a compelling trade-off curve,highlighting the advantages of achieving a balance between error rate and copy consumption in quantum discrimination tasks,offering valuable insights into the optimization of quantum resources while ensuring the accuracy of quantum state discrimination.

Short-term prediction of photovoltaic power generation based on LMD-EE-ESN with error correction

Considering the instability of the output power of photovoltaic(PV)generation system,to improve the power regulation ability of PV power during grid-connected operation,based on the quantitative analysis of meteorological conditions,a short-term prediction method of PV power based on LMD-EE-ESN with iterative error correction was proposed.Firstly,through the fuzzy clustering processing of meteorological conditions,taking the power curves of PV power generation in sunny,rainy or snowy,cloudy,and changeable weather as the reference,the local mean decomposition(LMD)was carried out respectively,and their energy entropy(EE)was taken as the meteorological characteristics.Then,the historical generation power series was decomposed by LMD algorithm,and the hierarchical prediction of the power curve was realized by echo state network(ESN)prediction algorithm combined with meteorological characteristics.Finally,the iterative error theory was applied to the correction of power prediction results.The analysis of the historical data in the PV power generation system shows that this method avoids the influence of meteorological conditions in the short-term prediction of PV output power,and improves the accuracy of power prediction on the condition of hierarchical prediction and iterative error correction.

Real-time instance segmentation based on contour learning

Instance segmentation plays an important role in image processing.The Deep Snake algorithm based on contour iteration deforms an initial bounding box to an instance contour end-to-end,which can improve the performance of instance segmentation,but has defects such as slow segmentation speed and sub-optimal initial contour.To solve these problems,a real-time instance segmentation algorithm based on contour learning was proposed.Firstly,ShuffleNet V2 was used as backbone network,and the receptive field of the model was expanded by using a 5×5 convolution kernel.Secondly,a lightweight up-sampling module,multi-stage aggregation(MSA),performs residual fusion of multi-layer features,which not only improves segmentation speed,but also extracts effective features more comprehensively.Thirdly,a contour initialization method for network learning was designed,and a global contour feature aggregation mechanism was used to return a coarse contour,which solves the problem of excessive error between manually initialized contour and real contour.Finally,the Snake deformation module was used to iteratively optimize the coarse contour to obtain the final instance contour.The experimental results showed that the proposed method improved the instance segmentation accuracy on semantic boundaries dataset(SBD),Cityscapes and Kins datasets,and the average precision reached 55.8 on the SBD;Compared with Deep Snake,the model parameters were reduced by 87.2%,calculation amount was reduced by 78.3%,and segmentation speed reached 39.8 frame·s−1 when instance segmentation was performed on an image with a size of 512×512 pixels on a 2080Ti GPU.The proposed method can reduce resource consumption,realize instance segmentation tasks quickly and accurately,and therefore is more suitable for embedded platforms with limited resources.

Modified multiple-component scattering power decomposition for PolSAR data based on eigenspace of coherency matrix

A modified multiple-component scattering power decomposition for analyzing polarimetric synthetic aperture radar(PolSAR)data is proposed.The modified decomposition involves two distinct steps.Firstly,ei⁃genvectors of the coherency matrix are used to modify the scattering models.Secondly,the entropy and anisotro⁃py of targets are used to improve the volume scattering power.With the guarantee of high double-bounce scatter⁃ing power in the urban areas,the proposed algorithm effectively improves the volume scattering power of vegeta⁃tion areas.The efficacy of the modified multiple-component scattering power decomposition is validated using ac⁃tual AIRSAR PolSAR data.The scattering power obtained through decomposing the original coherency matrix and the coherency matrix after orientation angle compensation is compared with three algorithms.Results from the experiment demonstrate that the proposed decomposition yields more effective scattering power for different PolSAR data sets.

Improved AVOA based on LSSVM for wind power prediction

Improving the prediction accuracy of wind power is an effective means to reduce the impact of wind power on power grid.Therefore,we proposed an improved African vulture optimization algorithm(AVOA)to realize the prediction model of multi-objective optimization least squares support vector machine(LSSVM).Firstly,the original wind power time series was decomposed into a certain number of intrinsic modal components(IMFs)using variational modal decomposition(VMD).Secondly,random numbers in population initialization were replaced by Tent chaotic mapping,multi-objective LSSVM optimization was introduced by AVOA improved by elitist non-dominated sorting and crowding operator,and then each component was predicted.Finally,Tent multi-objective AVOA-LSSVM(TMOALSSVM)method was used to sum each component to obtain the final prediction result.The simulation results show that the improved AVOA based on Tent chaotic mapping,the improved non-dominated sorting algorithm with elite strategy,and the improved crowding operator are the optimal models for single-objective and multi-objective prediction.Among them,TMOALSSVM model has the smallest average error of stroke power values in four seasons,which are 0.0694,0.0545 and 0.0211,respectively.The average value of DS statistics in the four seasons is 0.9902,and the statistical value is the largest.The proposed model effectively predicts four seasons of wind power values on lateral and longitudinal precision,and faster and more accurately finds the optimal solution on the current solution space sets,which proves that the method has a certain scientific significance in the development of wind power prediction technology.

Instantaneous polarization filtering focused on suppression of surface waves

The different characteristics of polarization of body and Rayleigh waves make it possible to separate these two types of waves by their characteristics and suppress the latter.The moving time-window analysis often is used in polarization filtering but it is difficult to determine a suitable time-window length,resulting in some problems,such as complex eigenvalues and non-convergence.For overcoming these disadvantages,in this paper,we introduce the concept of complex-trace analysis and conduct de-noise processing to suppress undesirable surface waves by instantaneous polarization analysis in the case of horizontal and vertical component seismic recordings from the Hauinan coal mine.The performance of the method is illustrated by examples with synthetic and field data and its effectiveness to remove surface waves from multi-component seismic data is demonstrated.

基于区域限制的EM和图割的非监督彩色图像分割方法

提出一种基于区域限制的EM(Expectation Maximization)和图割的非监督彩色图像分割方法,以解决自动确定分割类数问题.首先,生成图像的超像素,提取图像的CIE Lab颜色特征和多尺度四元数Gabor滤波特征;为了高效自动地确定分割类数,同时避免因直接使用超像素造成的奇异值问题,对每一个超像素采样并使用采样像素表示超像素;然后采用高斯混合模型对采样像素集合进行建模,使用加入区域限制的分量EM自动获取模型组件数及参数,最后使用图割结合高斯混合模型对图像进行优化,获取最终分割结果.实验结果表明,该方法在分割效率和分割质量上均得到较大提升.

Modeling dam deformation using independent component regression method

In the application of regression analysis method to model dam deformation, the ill-condition problem occurred in coefficient matrix always prevents an accurate modeling mainly due to the multicollinearity of the variables. Independent component regression （ICR） was proposed to model the dam deformation and identify the physical origins of the deformation. Simulation experiment shows that ICR can successfully resolve the problem of ill-condition and produce a reliable deformation model. After that, the method is applied to model the deformation of the Wuqiangxi Dam in Hunan province, China. The result shows that ICR can not only accurately model the deformation of the dam, but also help to identify the physical factors that affect the deformation through the extracted independent components.

Modified algorithm of principal component analysis for face recognition

In principal component analysis （PCA） algorithms for face recognition, to reduce the influence of the eigenvectors which relate to the changes of the illumination on abstract features, a modified PCA （MPCA） algorithm is proposed. The method is based on the idea of reducing the influence of the eigenvectors associated with the large eigenvalues by normalizing the feature vector element by its corresponding standard deviation. The Yale face database and Yale face database B are used to verify the method. The simulation results show that, for front face and even under the condition of limited variation in the facial poses, the proposed method results in better performance than the conventional PCA and linear discriminant analysis （LDA） approaches, and the computational cost remains the same as that of the PCA, and much less than that of the LDA.

Numerical analysis of multicomponent responses of surface-hole transient electromagnetic method

We calculate the multicomponent responses of surface-hole transient electromagnetic method. The methods and models are unsuitable as geoelectric models of conductive surrounding rocks because they are based on regular local targets. We also propose a calculation and analysis scheme based on numerical simulations of the subsurface transient electromagnetic fields. In the modeling of the electromagnetic fields, the forward modeling simulations are performed by using the finite-difference time-domain method and the discrete image method, which combines the Gaver–Stehfest inverse Laplace transform with the Prony method to solve the initial electromagnetic fields. The precision in the iterative computations is ensured by using the transmission boundary conditions. For the response analysis, we customize geoelectric models consisting of near-borehole targets and conductive wall rocks and implement forward modeling simulations. The observed electric fields are converted into induced electromotive force responses using multicomponent observation devices. By comparing the transient electric fields and multicomponent responses under different conditions, we suggest that the multicomponent-induced electromotive force responses are related to the horizontal and vertical gradient variations of the transient electric field at different times. The characteristics of the response are determined by the varying the subsurface transient electromagnetic fields, i.e., diffusion, attenuation and distortion, under different conditions as well as the electromagnetic fields at the observation positions. The calculation and analysis scheme of the response consider the surrounding rocks and the anomalous field of the local targets. It therefore can account for the geological data better than conventional transient field response analysis of local targets.

Effects of Nitrogen Fertigation Rate on Protein Components in Grains and Processing Quality of Different Wheat Varieties

[Objective] This study aimed to explore the effects of nitrogen fertigation rate on the protein components in grains and processing quality of different wheat varieties. [Method] Under the condition of higher soil fertility, different amounts of N-fertilizer were applied in the plots, and then the contents of total protein and its components, percentage of the component content to total protein content as well as the processing quality of grains of two strong-gluten wheat varieties （Linyou145 and Zhengmai9023） and two weak-gluten wheat varieties （Ningmai9 and Baofeng949） were determined. [Result] The contents of total protein and globulin, gliadin and glutenin were improved significantly with the increase of the N-fertilizer amount; but the content of albumin did not show remarkable increase; in addition, the percentage of each protein component was relative stable and did not increase significantly. Increase in the amount of N-fertilizer improved the sedimentation value, wet gluten content, loaf volume and loaf score, decreased the volume weight of grain. [Conclusion] This study provideed theoretical support for high-quality wheat production.

Adaptability Comparison of Chinese Milk Vetch (Astragalus sinicus) Varieties for Double-rice Cropping System in Hunan

Five Chinese milk vetch（Astragalus sinicus） varieties were selected to make a comparison in order to screen effective varieties which could suit for the double-rice cropping system of Hunan Province. The results showed that the growth period of Xiangzi 2 is shorter than that of Xiangfei 2, Xiangfei 3 and Yujiangdaye,and is similar to that of Xinyang Chinese milk vetch. The full-bloom stage of Xiangzi 2 is also similar to Xinyang variety and obviously earlier than that of the other three varieties. The fresh grass yield of Xiangzi 2 in full-bloom stage is 23 842.5kg/hm^2, which increases by 39.9% compared with Xinyang variety. Nitrogen content in the fresh grass of Xiangzi 2 is higher than that of the other four varieties. In conclusion, Xiangzi 2 is an extremely early-blossoming and early-maturing Chinese milk vetch variety with moderate fresh grass yield, high nutrient contents, stable characters and wide adaptability. So, Xiangzi 2 is suitable for planting in double-rice cropping region in Hunan Province and other same latitude regions which have similar ecological conditions.

A study of perfectly matched layers for joint multicomponent reverse-time migration

Reverse-time migration in finite space requires effective boundary processing technology to eliminate the artificial truncation boundary effect in the migration result.On the basis of the elastic velocity-stress equations in vertical transversely isotropic media and the idea of the conventional split perfectly matched layer（PML）,the PML wave equations in reverse-time migration are derived in this paper and then the high order staggered grid discrete schemes are subsequently given.Aiming at the＂reflections＂from the boundary to the computational domain,as well as the effect of seismic event＇s abrupt changes at the two ends of the seismic array,the PML arrangement in reverse-time migration is given.The synthetic and real elastic,prestack,multi-component,reverse-time depth migration results demonstrate that this method has much better absorbing effects than other methods and the joint migration produces good imaging results.

氘核中ΔΔ的成分

采用推广的夸克蜕定域色屏蔽模型计算了氘核中ΔΔ的成分 ,并与现有的实验数据和理论计算进行比较 ,所得结果与实验数据相符 ,与其它理论计算略有差别 ,并探讨了可能的原因 .

Robust adaptive polarization analysis method for eliminating ground roll in 3C land seismics

To improve the data quality of converted waves, and better identify and suppress the strong ground-roll interference in three-component （3C） seismic recordings on land, we present an adaptive polarization filtering method, which can effectively separate the ground- roll interference by combining complex polarization and instantaneous polarization analysis. The ground roll noise is characterized by elliptical plane polarization, strong energy, low apparent velocity, and low frequency. After low-pass filtering of the 3C data input within a given time-window of the ground roll, the complex covariance matrix is decomposed using the sliding time window with overlapping data and length that depends on the dominant ground-roll frequency. The ground-roll model is established using the main eigenvectors, and the ground roll is detected and identified using the instantaneous polarization area attributes and average energy constraints of the ground-roll zone. Finally, the ground roll is subtracted. The threshold of the method is stable and easy to select, and offers good ground- roll detection. The method is a robust polarization filtering method. Model calculations and actual data indicate that the method can effectively identify and attenuate ground roll while preserving the effective signals.

Elastic envelope inversion using multicomponent seismic data with filtered-out low frequencies

The absence of low-frequency information in seismic data is one of the most difficult problems in elastic full waveform inversion. Without low-frequency data, it is difficult to recover the long-wavelength components of subsurface models and the inversion converges to local minima. To solve this problem, the elastic envelope inversion method is introduced. Based on the elastic envelope operator that is capable of retrieving low- frequency signals hidden in multicomponent data, the proposed method uses the envelope of multicomponent seismic signals to construct a misfit function and then recover the long- wavelength components of the subsurface model. Numerical tests verify that the elastic envelope method reduces the inversion nonlinearity and provides better starting models for the subsequent conventional elastic full waveform inversion and elastic depth migration, even when low frequencies are missing in multicomponent data and the starting model is far from the true model. Numerical tests also suggest that the proposed method is more effective in reconstructing the long-wavelength components of the S-wave velocity model. The inversion of synthetic data based on the Marmousi-2 model shows that the resolution of conventional elastic full waveform inversion improves after using the starting model obtained using the elastic envelope method. Finally, the limitations of the elastic envelope inversion method are discussed.

Effects of Phosphate Treatment on Growth Dynamics of Wheat in Wheat/Corn Intercropping System in Southwest Hilly Area

We aimed to investigate the effects of phosphate treatment on growth dynamics of wheat in wheat/corn intercropping system in southwest hil y area. [Method] Five phosphate fertilization levels were designed for wheat and corn respectively to investigate the effects of phosphate fertilization level on wheat/corn intercropping system by field block experiment. [Result] The number of til ers, plant height and yield component of wheat trended to increase with the increase of phos-phate fertilization amount and al reached the peak for phosphate fertilization amount of 135 kg/hm2. However, the number of til ers, plant height and yield component of wheat al decreased significantly with the further increase of phosphate fertilization amount. [Conclusion] Phosphate fertilization contributed to the wheat growth in a certain degree. However, excessive phosphate fertilization would affect final yield.