Electromechanical cracking in ferroelectrics driven by large scale domain switching

Experimental results indicate three regimes for cracking in a ferroelectric double cantilever beam (DCB) under combined electromechanical loading. In the loading, the maximum amplitude of the applied electric field reaches almost twice the coercive field of ferroelectrics. Thus, the model of small scale domain switching is not applicable any more, which is dictated only by the singular term of the crack tip field. In the DCB test, a large or global scale domain switching takes place instead, which is driven jointly by both the singular and non-singular terms of the crack-tip electric field. Combining a full field solution with an energy based switching criterion, we obtain the switching zone by the large scale model around the tip of a stationary impermeable crack. It is observed that the switching zone by the large scale model is significantly different from that by the small scale model. According to the large scale switching zone, the switch-induced stress intensity factor (SIF) and the transverse stress (T-stress) are evaluated numerically. Via the SIF and T-stress induced by the combined loading and corresponding criteria, we address the crack initiation and crack growth stability simultaneously. The two theoretical predictions roughly coincide with the experimental observations.

Modified slow-fast analysis method for slow-fast dynamical systems with two scales in frequency domain

A modified slow-fast analysis method is presented for the periodically excited non-autonomous dynamical system with an order gap between the exciting frequency and the natural frequency.By regarding the exciting term as a slow-varying parameter,a generalized autonomous fast subsystem can be defined,the equilibrium branches as well as the bifurcations of which can be employed to account for the mechanism of the bursting oscillations by combining the transformed phase portrait introduced.As an example,a typical periodically excited Hartley model is used to demonstrate the validness of the method,in which the exciting frequency is far less than the natural frequency.The equilibrium branches and their bifurcations of the fast subsystem with the variation of the slow-varying parameter are presented.Bursting oscillations for two typical cases are considered,which reveals that,fold bifurcation may cause the the trajectory to jump between different equilibrium branches,while Hopf bifurcation may cause the trajectory to oscillate around the stable limit cycle.

Positively Worded Subscale Score of the Perceived Stress Scale Is Associated with Cognitive Domain Function

Objectives: To examine the cross-sectional associations of the separate subscales of the Perceived Stress Scale (PSS) and tests measuring cognitive domains in older adults. Methods: 897 adults over the age of 70 free of amnestic mild cognitive impairment and dementia and enrolled in the Einstein Aging Study made up the study sample. The PSS-14 was used to measure stress. Three cognitive domains (language, episodic memory, and frontal-executive) had previously been found using principle component analysis. Linear regression analyses were used to determine the relationship between the PSS subscales and cognitive domain function. Results: The study sample had a mean age of 79.1 years and 62.8% were female. Bivariate correlations show that the PSS-14 positively worded subscale of the PSS (PSS-PW) was significantly associated with all three cognitive domains (language: r = -0.15, p < 0.001;episodic memory: r = -0.16, p < 0.001;frontal-executive: r = -0.21, p <0.001) while the negatively worded subscale of the PSS (PSS-NW) was not significantly associated with any cognitive domain. In linear regression analyses adjusted for age, white race, gender, years of education, and depressive symptoms, the PSS-PW remained significantly associated with each of the cognitive domains. The PSS-NW was not associated with any cognitive domains in any model. The PSS-14 was significantly associated with language and episodic memory, but not the frontal-executive domain. Conclusion: Worse PSS-PW scores are associated with reduced cognitive function in the executive, memory, and language domains in nondemented older adults. The PSS-PW subscale correlated better with cognitive function than the overall PSS-14. Future research should evaluate the temporality of the association and if stress reduction therapies improve cognitive performance.

Radio-frequency transistors from millimeter-scale graphene domains

Graphene is a new promising candidate for application in radio-frequency （RF） electronics due to its excellent elec- tronic properties such as ultrahigh carrier mobility, large threshold current density, and high saturation velocity. Recently, much progress has been made in the graphene-based RF field-effect transistors （RF-FETs）. Here we present for the first time the high-performance top-gated RF transistors using millimeter-scale single graphene domain on a SiO2/Si substrate through a conventional microfabrication process. A maximum cut-off frequency of 178 GHz and a peak maximum os- cillation frequency of 35 GHz are achieved in the graphene-domain-based FET with a gate length of 50 nm and 150 nm, respectively. This work shows that the millimeter-scale single graphene domain has great potential applications in RF devices and circuits.

Large-Scale Ontology Development and Agricultural Application Based on Knowledge Domain Framework

The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management- the knowledge domain framework （KDF）, and introduces an integrated development environment （IDE） named large-scale ontology development environment （LODE）, which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the described briefly. principle of knowledge domain framework and LODE was

Bayesian seismic multi-scale inversion in complex Laplace mixed domains

Seismic inversion performed in the time or frequency domain cannot always recover the long-wavelength background of subsurface parameters due to the lack of low-frequency seismic records. Since the low-frequency response becomes much richer in the Laplace mixed domains, one novel Bayesian impedance inversion approach in the complex Laplace mixed domains is established in this study to solve the model dependency problem. The derivation of a Laplace mixed-domain formula of the Robinson convolution is the first step in our work. With this formula, the Laplace seismic spectrum, the wavelet spectrum and time-domain reflectivity are joined together. Next, to improve inversion stability, the object inversion function accompanied by the initial constraint of the linear increment model is launched under a Bayesian framework. The likelihood function and prior probability distribution can be combined together by Bayesian formula to calculate the posterior probability distribution of subsurface parameters. By achieving the optimal solution corresponding to maximum posterior probability distribution, the low-frequency background of subsurface parameters can be obtained successfully. Then, with the regularization constraint of estimated low frequency in the Laplace mixed domains, multi-scale Bayesian inversion inthe pure frequency domain is exploited to obtain the absolute model parameters. The effectiveness, anti-noise capability and lateral continuity of Laplace mixed-domain inversion are illustrated by synthetic tests. Furthermore,one field case in the east of China is discussed carefully with different input frequency components and different inversion algorithms. This provides adequate proof to illustrate the reliability improvement in low-frequency estimation and resolution enhancement of subsurface parameters, in comparison with conventional Bayesian inversion in the frequency domain.

Dynamic interaction numerical models in the time domain based on the high performance scaled boundary finite element method

Consideration of structure-foundation-soil dynamic interaction is a basic requirement in the evaluation of the seismic safety of nuclear power facilities. An efficient and accurate dynamic interaction numerical model in the time domain has become an important topic of current research. In this study, the scaled boundary finite element method （SBFEM） is improved for use as an effective numerical approach with good application prospects. This method has several advantages, including dimensionality reduction, accuracy of the radial analytical solution, and unlike other boundary element methods, it does not require a fundamental solution. This study focuses on establishing a high performance scaled boundary finite element interaction analysis model in the time domain based on the acceleration unit-impulse response matrix, in which several new solution techniques, such as a dimensionless method to solve the interaction force, are applied to improve the numerical stability of the actual soil parameters and reduce the amount of calculation. Finally, the feasibility of the time domain methods are illustrated by the response of the nuclear power structure and the accuracy of the algorithms are dynamically verified by comparison with the refinement of a large-scale viscoelastic soil model.

A seismic free field input model for FE-SBFE coupling in time domain

A seismic free field input formulation of the coupling procedure of the finite elelnent(FE)and the scaled boundary finite-element(SBFE)is proposed to perform the unbounded soil-structure interaction analysis in time domain. Based on the substructure technique,seismic excitation of the soil-structure system is represented by the free-field motion of an elastic half-space.To reduce the computational effort,the acceleration unit-impulse response function of the unbounded soil is decomposed into two functions:linear and residual.The latter converges to zero and can be truncated as required. With the prescribed tolerance parameter,the balance between accuracy and effMency of the procedure can be controlled. The validity of the model is verified by the scattering analysis of a hemi-spherical canyon subjected to plane harmonic P,SV and SH wave incidence.Numerical results show that the new procedure is very efficient for seismic problems within a nor- real range of frequency.The coupling procedure presented herein can be applied to linear and nonlinear earthquake re- sponse analysis of practical structures which are built on unbounded soil.

基于多尺度梯度域引导滤波的煤矿井下图像增强方法

煤矿井下图像存在较严重的光照不均匀和噪声干扰,现有基于Retinex的方法直接应用于煤矿井下图像增强易出现光晕伪影、边缘模糊、过增强和噪声放大等问题。针对上述问题,提出了一种基于多尺度梯度域引导滤波的煤矿井下图像增强方法。首先,将多尺度思想引入梯度域引导滤波中,实现对非均匀光照的准确估计,有效解决了增强图像时光晕伪影及边缘模糊的问题。然后,利用Retinex模型分离出光照分量和反射分量:对于光照分量,通过自适应伽马校正函数逐像素地修正光照信息,实现对图像暗区域增强的同时,抑制亮区域过增强,并使用限制对比度自适应直方图均衡化方法调整图像对比度;对于反射分量,将梯度域引导滤波与多尺度细节提升相结合,在准确去除噪声后提升纹理细节,避免了增强图像时噪声放大的问题。最后,将处理后的光照分量及反射分量融合,计算图像增益系数,并使用线性色彩恢复方法实现对原始RGB图像的逐像素增强,提升方法处理效率。实验结果表明,从主客观角度与现有方法相比,经所提方法处理后的图像在色彩保持、对比度、噪声抑制、细节保留等方面均取得了较好的增强效果,同时处理效率较高。

Frequency-domain generelaized singular peruturbation method for relative error model order reduction

A new mixed method for relative error model order reduction is proposed. In the proposed method the frequency domain balanced stochastic truncation method is improved by applying the generalized singular perturbation method to the frequency domain balanced system in the reduction procedure. The frequency domain balanced stochastic truncation method, which was proposed in [15] and [17] by the author, is based on two recently developed methods, namely frequency domain balanced truncation within a desired frequency bound and inner-outer factorization techniques. The proposed method in ttiis paper is a carry over of the frequency-domain balanced stochastic truncation and is of interest for practical model order reduction because in this context it shows to keep the accuracy of the approximation as high as possible without sacrificing the computational efficiency and important system properties. It is shown that some important properties of the frequency domain stochastic balanced reduction technique are extended to the proposed reduction method by using the concept and properties of the reciprocal systems. Numerical results show the accuracy, simplicity and flexibility enhancement of the method.

An Alternate Approach for Designing a Domain Specific Image Search Prototype Using Histogram

Everyone knows that thousand of words are represented by a single image. As a result, image search has become a very popular mechanism for the Web-searchers. Image search means, the search results are produced by the search engine should be a set of images along with their Web-page Unified Resource Locator (URL). Now Web-searcher can perform two types of image search, they are “Text to Image” and “Image to Image” search. In “Text to Image” search, search query should be a text. Based on the input text data, system will generate a set of images along with their Web-page URL as an output. On the other hand, in “Image to Image” search, search query should be an image and based on this image, system will generate a set of images along with their Web-page URL as an output. According to the current scenarios, “Text to Image” search mechanism always not returns perfect result. It matches the text data and then displays the corresponding images as an output, which is not always perfect. To resolve this problem, Web researchers have introduced the “Image to Image” search mechanism. In this paper, we have also proposed an alternate approach of “Image to Image” search mechanism using Histogram.

融合多特征信息与GWO-SVM的机械关键设备故障诊断

为了提高机械关键设备故障诊断的精度,建立机械关键设备故障诊断模型。文章提出一种融合机械关键设备故障信号多特征信息与灰狼优化算法(Grey Wolf Optimization Algorithm,GWO)改进支持向量机(Support Vector Machine,SVM)(GWO-SVM)的机械关键设备故障诊断模型。首先,提取机械关键设备故障信号的时域特征、频域特征和多尺度加权排列熵特征,分别对比不同特征的机械关键设备故障诊断结果。其次,为提高SVM模型性能,运用GWO算法对SVM模型的惩罚参数P和核函数参数g进行优化选择,提出一种融合多特征信息与GWO-SVM的机械设备故障诊断模型。与GA-SVM、PSO-SVM和SVM相比,基于GWO-SVM的机械设备故障诊断模型的诊断精度最高。这里算法可以有效提高机械关键设备故障诊断正确率,为机械关键设备故障诊断提供了新的方法。

考虑多尺度纹理特征的红外传感图像频域增强

红外传感图像质量容易受探测器和传输距离影响,导致图像亮度和对比度较低、轮廓细节模糊等问题。为此,提出了考虑多尺度纹理特征的红外传感图像频域增强方法。引入残差学习策略,基于多尺度纹理特征搭建多尺度卷积神经网络模型,进行图像去噪。对去噪后图像进行傅里叶变换,获取红外传感图像的低频图像和高频图像。针对低频图像部分,调节图像灰度和对比度以增强低频分量。针对高频图像部分,利用Log算子和Laplace算子增强图像细节及边缘。加权融合两者处理结果,选取Gamma校正调节对比度,增强高频分量。融合两种增强后图像,实现红外传感图像频域增强。实验结果表明,该方法峰值信噪比高于43,信息熵大于8,边缘强度超过82,对比度熵大于8.1,平均梯度大于8。

Time-Spectral Solution of Initial-Value Problems—Subdomain Approach

Temporal and spatial subdomain techniques are proposed for a time-spectral method for solution of initial-value problems. The spectral method, called the generalised weighted residual method (GWRM), is a generalisation of weighted residual methods to the time and parameter domains [1]. A semi-analytical Chebyshev polynomial ansatz is employed, and the problem reduces to determine the coefficients of the ansatz from linear or nonlinear algebraic systems of equations. In order to avoid large memory storage and computational cost, it is preferable to subdivide the temporal and spatial domains into subdomains. Methods and examples of this article demonstrate how this can be achieved.

基于多尺度混合域注意力机制的笔迹鉴别方法

针对笔迹鉴别任务中图像大面积是背景、笔迹信息稀疏、关键性信息难以捕捉,并且个人笔迹签名风格具有微小变化而刻意模仿的笔迹高度相似,以及公开的中文笔迹数据集的匮乏的问题,通过对注意力机制和孪生网络模型进行改进,提出一种基于多尺度混合域注意力机制的笔迹鉴别方法(MMDANet)。首先,在有效通道注意力模块上并联一个最大池化层,并将二维条带池化模块的通道数扩展到三维,将改进的有效通道注意力模块和条带池化模块融合生成混合域模块(MDM),解决了笔迹图像大面积是背景、笔迹信息稀疏、细节特征难以提取的问题;其次,利用PANet特征金字塔进行多尺度提取特征,捕获真伪笔迹间的细微差异,采用孪生网络的对比损失与AM-Softmax损失加权融合进行训练,增加类别间的区分度,解决个人笔迹风格变化和真伪笔迹高度相似的问题;最后自制了总体样本数为8000的中文笔迹数据集(CHD)。所提方法在自制中文数据集CHD上的准确率达到了84.25%,且相较于次优的Two-stage SiamNet方法,所提方法在3个外文数据集Cedar、Bengla和Hindi上准确率分别提升了4.53%、1.02%和1.67%。实验结果表明,MMDANet可以更准确地捕获真伪笔迹的细微差异,完成复杂的笔迹鉴别任务。

基于改进Faster R-CNN的红外目标检测算法

为提升红外目标的检测精度,提出了一种引入频域注意力机制的Faster R-CNN红外目标检测算法。首先,针对红外图像边缘模糊和噪声问题,设计了一种并行的图像增强预处理结构;其次,在Faster R-CNN中引入频域注意力机制,设计了一种新型红外目标检测主干网络;最后,引入路径增强金字塔结构,融合多尺度特征进行预测,利用底层网络丰富的位置信息,提升检测精度。在红外飞机的数据集上进行实验,结果表明,改进后的Faster R-CNN目标检测框架比以ResNet50为主干的算法的AP提升了7.6%。此外,与目前主流算法对比,本文算法提高了红外目标的检测精度,验证了算法改进的有效性。

多尺度域视频监控图像光照分量智能校正方法

针对视频监控图像中存在的清晰度不足和光照不均匀等问题,提出了多尺度域视频监控图像光照分量智能校正方法。应用背景差分法与差值图二值化法对视频监控图像进行预处理,以减少噪声干扰。通过融合TH变换和BH变换来加强图像多尺度细节特征;利用控制因子控制锐化强度,以凸显细节特征,避免出现图像伪影情况。对图像光照分量进行自适应调节,利用二维伽马函数计算画面亮度平均值,以防止出现过度校正的情况,从而实现智能校正。测试结果表明,采用该方法校正的图像更清晰,画面光照分量均匀,图像失真较少,视觉效果较好。

大模型在军事垂直领域的应用

大模型技术是人工智能技术的飞跃式发展,使得大众看到人工智能的切实应用,利用大模型技术开展垂直领域应用是目前的研究热点,针对军事垂直领域的行业特点,本文提出一种基于开源大模型训练军事垂域大模型的技术路线。

亚波长尺度裂缝地震散射分辨分析

裂缝储层地震特征的准确识别已成为当前地震勘探的难点之一,特别是深层礁滩或碳酸盐岩储层,其大部分裂缝都在亚波长尺度,按照传统地震反射四分之一波长几何分辨准则是不能完全分辨的.传统研究裂缝地震响应的方法主要基于各向异性等效介质理论,但由于亚波长尺度裂缝微小且其地震反射弱并存在噪声干扰等问题,故该传统方法逼近精度有限.然而,这类部分可分辨裂缝可在地震散射范畴来分析和预测,本文基于散射聚焦分辨分析理论,提出了表征裂缝系统空间分布和形态特征的波数域散射成像矩阵方法,据此计算了含裂缝与不含裂缝的波数域成像矩阵之间的振幅差异性和结构差异性,从散射能量及其各向异性的角度分析了亚波长尺度裂缝的地震可识别性.均匀和复杂背景介质下的算例表明,振幅差异性随裂缝厚度和密度的变化规律显著,结构差异性随裂缝角度变化规律更加明显.同时讨论了随机噪声和排列长度等因素对裂缝系统地震散射可识别性的影响.排列长度和噪声对于裂缝厚度响应影响较小,主要影响高角度裂缝的识别,同时要求排列长度大于三倍目标深度才可应用该方法进行裂缝参数识别.