Finite Difference Schemes for Time-Space Fractional Diffusion Equations in One-and Two-Dimensions

In this paper,finite difference schemes for solving time-space fractional diffusion equations in one dimension and two dimensions are proposed.The temporal derivative is in the Caputo-Hadamard sense for both cases.The spatial derivative for the one-dimensional equation is of Riesz definition and the two-dimensional spatial derivative is given by the fractional Laplacian.The schemes are proved to be unconditionally stable and convergent.The numerical results are in line with the theoretical analysis.

基于多尺度Laws纹理能量和低秩分解的织物疵点检测算法

为提高织物疵点检测算法对简单纹理织物、模式纹理织物及条纹纹理织物检测时的普适性和准确性,提出了一种基于多尺度Laws纹理能量和低秩分解的织物疵点检测算法。首先,对织物图像进行直方图均衡化并将处理后的图像均匀划分为子图像块;其次,对每个子图像块提取28个纹理能量特征(利用7个Laws滤波模板在4个尺度上提取),计算所有子图像块提取到的特征均值并组成特征矩阵;然后,利用特征矩阵构建低秩分解模型,通过方向交替方法(ADM)优化求解,得到低秩部分和稀疏部分;最后,由稀疏部分生成疵点显著图,采用迭代阈值分割法对其进行分割,得到织物疵点检测结果。为验证该算法的有效性,在织物图像数据集选取了包含错纬、断经、跳花、破洞等常见疵点的织物图像,并将实验结果与已有3种算法进行了对比。实验结果表明,该算法在简单纹理织物、模式纹理织物及条纹纹理织物检测上具有更好的普适性和准确性,且检测效率具有一定优势。

Nonuniform Dependence on the Initial Data for Solutions of Conservation Laws

In this paper,we study systems of conservation laws in one space dimension.We prove that for classical solutions in Sobolev spaces H^(s),with s>3/2,the data-to-solution map is not uniformly continuous.Our results apply to all nonlinear scalar conservation laws and to nonlinear hyperbolic systems of two equations.

Triple reverse order law for the Drazin inverse

In this paper,we investigate the reverse order law for Drazin inverse of three bound-ed linear operators under some commutation relations.Moreover,the Drazin invertibility of sum is also obtained for two bounded linear operators and its expression is presented.

Literature overview of basic characteristics and flotation laws of flocs

Flocculation flotation is the most efficient method for recovering fine-grained minerals,and its essence lies in flotation and recovery of flocs.Fundamental physical characteristics of flocs are mainly determined by their apparent particle size and structure(density and morphology).Substantial researches have been conducted regarding the effect of floc characteristics on particle settling and water treatment.However,the influence of floc characteristics on flotation has not been widely studied.Based on the floc formation and flocculation flotation,this study reviews the fundamental physical characteristics of flocs from the perspectives of floc particle size and structure,summarizing the interaction between floc particle size and structure.Moreover,it thoroughly discusses the effect of floc particle size and structure on floc floatability,further revealing the influence of floc characteristics on bubble collision and adhesion and elucidating the mechanisms of interaction between flocs and bubbles.Thus,it is observed that floc particle size is not the only factor influencing flocculation flotation.Within the appropriate apparent particle size range,flocs with a compact structure exhibit higher efficiency in bubble collision and adhesion during flotation,thereby resulting in enhanced flotation performance.This study aims to provide a reference for flocculation flotation,targeting the development of more efficient and refined flocculation flotation processes in the future.

Dimension by Dimension Finite Volume HWENO Method for Hyperbolic Conservation Laws

In this paper,we propose a finite volume Hermite weighted essentially non-oscillatory(HWENO)method based on the dimension by dimension framework to solve hyperbolic conservation laws.It can maintain the high accuracy in the smooth region and obtain the high resolution solution when the discontinuity appears,and it is compact which will be good for giving the numerical boundary conditions.Furthermore,it avoids complicated least square procedure when we implement the genuine two dimensional(2D)finite volume HWENO reconstruction,and it can be regarded as a generalization of the one dimensional(1D)HWENO method.Extensive numerical tests are performed to verify the high resolution and high accuracy of the scheme.

Distribution law and susceptibility of geohazards across a gradient belt of the Western Sichuan Plateau

Across a gradient belt of the Western Sichuan Plateau,geohazards have seriously limited economic and social development.According to incomplete statistics,15,673 geohazards have been recorded in the study area.In order to mitigate the threat of geohazards to human engineering activities in the region,an overall understanding of the distribution pattern of geohazards and susceptibility assessment are necessary.In this paper,a gradient belt of the Western Sichuan Plateau and its zoning criteria were defined.Subsequently,on the basis of relief amplitude,distance to faults,rainfall,and human activities,three indicators of endogenic process were introduced:Bouguer gravity anomaly gradient,vertical deformation gradient,and horizontal deformation gradient.Thereafter,the distribution patterns of geohazards were investigated through mathematical statistics and ArcGIS software.By randomly selecting 10,449 hazards,a geohazard susceptibility map was generated using the Information Value(IV)model.Finally,the IV model was validated against 5224 hazards using the Area Under Curve(AUC)method.The results show that 47.6%of the geohazards were distributed in the zone of steep slope.Geohazards showed strong responses to distance to faults,human activities,and annual rainfall.The distribution of geohazards in the gradient belt of the Western Sichuan Plateau is more sensitive to vertical internal dynamics factors(such as vertical deformation gradient and Bouguer gravity anomaly gradient)without any apparent sensitivity to horizontal internal dynamics factors.The areas of high and very-high risk account for up to 32.22%,mainly distributed in the Longmenshan and Anning River faults.According to the AUC plot,the success rate of the IV model for generating the susceptibility map is 76%.This susceptibility map and geohazard distribution pattern can provide a reference for geological disaster monitoring,preparation of post-disaster emergency measures,and town planning.

Nuclear magnetic resonance experiments on the time-varying law of oil viscosity and wettability in high-multiple waterflooding sandstone cores

A simulated oil viscosity prediction model is established according to the relationship between simulated oil viscosity and geometric mean value of T2spectrum,and the time-varying law of simulated oil viscosity in porous media is quantitatively characterized by nuclear magnetic resonance(NMR)experiments of high multiple waterflooding.A new NMR wettability index formula is derived based on NMR relaxation theory to quantitatively characterize the time-varying law of rock wettability during waterflooding combined with high-multiple waterflooding experiment in sandstone cores.The remaining oil viscosity in the core is positively correlated with the displacing water multiple.The remaining oil viscosity increases rapidly when the displacing water multiple is low,and increases slowly when the displacing water multiple is high.The variation of remaining oil viscosity is related to the reservoir heterogeneity.The stronger the reservoir homogeneity,the higher the content of heavy components in the remaining oil and the higher the viscosity.The reservoir wettability changes after water injection:the oil-wet reservoir changes into water-wet reservoir,while the water-wet reservoir becomes more hydrophilic;the degree of change enhances with the increase of displacing water multiple.There is a high correlation between the time-varying oil viscosity and the time-varying wettability,and the change of oil viscosity cannot be ignored.The NMR wettability index calculated by considering the change of oil viscosity is more consistent with the tested Amott(spontaneous imbibition)wettability index,which agrees more with the time-varying law of reservoir wettability.

Weber Law Based Approach for Multi-Class Image Forgery Detection

Today’s forensic science introduces a new research area for digital image analysis formultimedia security.So,Image authentication issues have been raised due to the wide use of image manipulation software to obtain an illegitimate benefit or createmisleading publicity by using tempered images.Exiting forgery detectionmethods can classify only one of the most widely used Copy-Move and splicing forgeries.However,an image can contain one or more types of forgeries.This study has proposed a hybridmethod for classifying Copy-Move and splicing images using texture information of images in the spatial domain.Firstly,images are divided into equal blocks to get scale-invariant features.Weber law has been used for getting texture features,and finally,XGBOOST is used to classify both Copy-Move and splicing forgery.The proposed method classified three types of forgeries,i.e.,splicing,Copy-Move,and healthy.Benchmarked(CASIA 2.0,MICCF200)and RCMFD datasets are used for training and testing.On average,the proposed method achieved 97.3% accuracy on benchmarked datasets and 98.3% on RCMFD datasets by applying 10-fold cross-validation,which is far better than existing methods.

Two innovative equivalent statements of the third law of thermodynamics

It is found from textbooks and literature that there are three different statements for the third law of thermodynamics,i.e., the Nernst theorem, the unattainability statement of absolute zero temperature, and the heat capacity statement. It is pointed out that such three statements correspond to three thermodynamic parameters, which are, respectively, the entropy,temperature, and heat capacity, and can be obtained by extrapolating the experimental results of different parameters at ultralow temperatures to absolute zero. It is expounded that because there is no need for additional assumptions in the derivation of the Nernst equation, the Nernst theorem should be renamed as the Nernst statement. Moreover, it is proved that both the Nernst statement and the heat capacity statement are mutually deducible and equivalent, while the unattainability of absolute zero temperature is only a corollary of the Nernst statement or the heat capacity statement so that it is unsuitably referred to as one statement of the third law of thermodynamics. The conclusion is that the Nernst statement and the heat capacity statement are two equivalent statements of the third law of thermodynamics.

Development and Application of a Power Law Constitutive Model for Eddy Current Dampers

Eddy current dampers (ECDs) have emerged as highly desirable solutions for vibration control due to theirexceptional damping performance and durability. However, the existing constitutive models present challenges tothe widespread implementation of ECD technology, and there is limited availability of finite element analysis (FEA)software capable of accurately modeling the behavior of ECDs. This study addresses these issues by developing anewconstitutivemodel that is both easily understandable and user-friendly for FEAsoftware. By utilizing numericalresults obtained from electromagnetic FEA, a novel power law constitutive model is proposed to capture thenonlinear behavior of ECDs. The effectiveness of the power law constitutive model is validated throughmechanicalproperty tests and numerical seismic analysis. Furthermore, a detailed description of the application process ofthe power law constitutive model in ANSYS FEA software is provided. To facilitate the preliminary design ofECDs, an analytical derivation of energy dissipation and parameter optimization for ECDs under harmonicmotionis performed. The results demonstrate that the power law constitutive model serves as a viable alternative forconducting dynamic analysis using FEA and optimizing parameters for ECDs.

The Rule of Law is the Most Important Means of Human Rights Protection

Today,we are here to commemorate the 75^(th) anniversary of the adoption of the Universal Declaration of Human Rights.In this Declaration,which consists of only30 articles,seven articles are related to the constitution,law,court,and the rule of law,making it a declaration filled with the rule of law.Coincidentally,today is also the 10^(th) National Constitution Day of China.Nineteen years ago,“the state respects and protects human rights”was enshrined in the Constitution,becoming a constitutional principle.Since then,human rights protection in China has been based on fundamental law.

A Spectral Convolutional Neural Network Model Based on Adaptive Fick’s Law for Hyperspectral Image Classification

Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm(AFLA-SCNN)is proposed.The Adaptive Fick’s Law Algorithm(AFLA)constitutes a novel metaheuristic algorithm introduced herein,encompassing three new strategies:Adaptive weight factor,Gaussian mutation,and probability update policy.With adaptive weight factor,the algorithmcan adjust theweights according to the change in the number of iterations to improve the performance of the algorithm.Gaussianmutation helps the algorithm avoid falling into local optimal solutions and improves the searchability of the algorithm.The probability update strategy helps to improve the exploitability and adaptability of the algorithm.Within the AFLA-SCNN model,AFLA is employed to optimize two hyperparameters in the SCNN model,namely,“numEpochs”and“miniBatchSize”,to attain their optimal values.AFLA’s performance is initially validated across 28 functions in 10D,30D,and 50D for CEC2013 and 29 functions in 10D,30D,and 50D for CEC2017.Experimental results indicate AFLA’s marked performance superiority over nine other prominent optimization algorithms.Subsequently,the AFLA-SCNN model was compared with the Spectral Convolutional Neural Network model based on Fick’s Law Algorithm(FLA-SCNN),Spectral Convolutional Neural Network model based on Harris Hawks Optimization(HHO-SCNN),Spectral Convolutional Neural Network model based onDifferential Evolution(DE-SCNN),SpectralConvolutionalNeuralNetwork(SCNN)model,and SupportVector Machines(SVM)model using the Indian Pines dataset and PaviaUniversity dataset.The experimental results show that the AFLA-SCNN model outperforms other models in terms of Accuracy,Precision,Recall,and F1-score on Indian Pines and Pavia University.Among them,the Accuracy of the AFLA-SCNN model on Indian Pines reached 99.875%,and the Accuracy on PaviaUniversity reached 98.022%.In conclusion,our proposed AFLA-SCNN model is deemed to significantly enhance the precision of hyperspectral image classification.

Analysis of the Characterization of the Old Man in“The Law of Life”from the Narrative Perspective

“The Law of Life”is one of Jack London’s representative works,depicting the story of an elderly Native American abandoned by his family,alone and waiting for life to fade away.This paper,based on narrative theory,aims to explore how the author employs narrative techniques to present the image of the old man in the short story.The narrative techniques of dual focalization and dual narrative timelines in the text demonstrate the abandonment of the old man’s homeland and his inescapable death under a naturalistic view of life and reflect a desolate life picture of resignation towards death under naturalistic determinism,depicting a grim elderly world under the naturalistic concept of“survival of the fittest.”Studying this short story helps us reflect on the living conditions of the elderly and provides insights into how to better care for the elderly population amid the global trend of aging.

Malawi Opens Tourism Doors No visa’s needed for Chinese tourists and others,as Malawi makes visits more convenient

When Malawian President Lazarus Chakwera delivered a State of the Nation Address at the 50th Parliamentary Session and Budget Meeting in February,tourism was top of mind.

基于Laws与Gabor滤波的田间西兰花花球识别技术

正确识别西兰花田间位置是实现西兰花自动化采收的基础,西兰花花球颜色与植株的叶片、茎秆相似,仅通过颜色特征无法对西兰花进行识别,本文以成熟期的田间西兰花为研究对象,提出了一种基于纹理特征与颜色特征的西兰花识别算法。首先通过预处理以及Laws滤波对图像进行边界纹理强化,再通过Gabor滤波对图像进行纹理特征向量提取,并对提取后的纹理特征向量进行z⁃score标准化,随后对标准化后的纹理特征向量进行K⁃means聚类与开运算,获取花球潜在存在区域。同时对RGB图像进行HSV转换,通过对图像的H分量进行阈值分割达到滤除地面像素的效果。最终对纹理特征识别与颜色特征识别的结果进行融合,实现对田间西兰花的识别。算法通过结合纹理与颜色特征,对田间西兰花进行了识别,解决了西兰花的花球与茎叶等背景颜色相近难以识别的问题。本文共使用792幅图像进行试验,试验结果表明,本方法可以准确地对西兰花田间图像进行识别,其精确率为96.96%,召回率为94.41%,F1值为95.67%。通过对3组不同拍摄环境的数据集进行算法识别,3组数据集的F1值始终保持在94%以上,具有良好的拍摄环境适应性,为农业机器人进行西兰花自动化采收奠定了基础。

TIME-SPACE CONCEPT FOR PRECISION MEASUREMENT

The transformation between time and space is discussed. To improve real-time response speed of intelligent measuring system, the concept of exchanging program execution time with more circuitry is presented working in cycle mode. Displacement measuring by magnification is achieved with period measurement by magnification. To change the condition that traditional precision measurement depends on machining precision greatly, the concept of measuring space with time and theory of time-space coordinate transformation are proposed. Guided by the idea of measuring space with time, differential frequency measurement system and time grating displacement sensor are developed based on the proposed novel methods. And high-precision measurement is achieved without high-precision manufacture, which embeds the remarkable characteristics of low cost but high precision to the devices. Experiment and test results conform the validity of the proposed time-space concept.

Adaptive time-space resource and waveform control for collocated MIMO radar with simultaneous multi-beam

Collocated multiple input multiple output(MIMO)radar,which has agile multi-beam working mode,can offer enhanced multiple targets tracking(MTT)ability.In detail,it can illuminate different targets simultaneously with multi-beam or one wide beam among multi-beam,providing greater degree of freedom in system resource control.An adaptive time-space resource and waveform control optimization model for the collocated MIMO radar with simultaneous multi-beam is proposed in this paper.The aim of the proposed scheme is to improve the overall tracking accuracy and meanwhile minimize the resource consumption under the guarantee of effective targets detection.A resource and waveform control algorithm which integrates the genetic algorithm(GA)is proposed to solve the optimization problem.The optimal transmitting waveform parameters,system sampling period,sub-array number,binary radar tracking parameterχ_i(t_k),transmitting energy and multi-beam direction vector combination are chosen adaptively,where the first one realizes the waveform control and the latter five realize the timespace resource allocation.Simulation results demonstrate the effectiveness of the proposed control method.

Adaptive resource management for multi-target tracking in co-located MIMO radar based on time-space joint allocation

Compared with the traditional phased array radar, the co-located multiple-input multiple-output(MIMO) radar is able to transmit orthogonal waveforms to form different illuminating modes, providing a larger freedom degree in radar resource management. In order to implement the effective resource management for the co-located MIMO radar in multi-target tracking,this paper proposes a resource management optimization model,where the system resource consumption and the tracking accuracy requirements are considered comprehensively. An adaptive resource management algorithm for the co-located MIMO radar is obtained based on the proposed model, where the sub-array number, sampling period, transmitting energy, beam direction and working mode are adaptively controlled to realize the time-space resource joint allocation. Simulation results demonstrate the superiority of the proposed algorithm. Furthermore, the co-located MIMO radar using the proposed algorithm can satisfy the predetermined tracking accuracy requirements with less comprehensive cost compared with the phased array radar.

结合Cannikin’s Law的离线数据增广方法研究

数据增广是提升深度学习模型性能的有效方法之一。针对多类别目标检测任务中检测性能不平衡问题,提出一种针对“短板类别”(检测性能远低于模型平均检测性能的类别)的离线数据增广方法。受Cannikin’s Law的启发,采用基于复制粘贴(copy-paste)机制的场景多样性增广方法。随机采集训练集中“短板类别”实例区域,通过相似性度量机制选取训练集中增广目标样本进行随机粘贴。为了降低随机粘贴导致的遮挡问题,采用基于自遮挡(cut-replace)机制的增广方法提升模型遮挡表达能力。通过截取样本自身区域,对特征表达最显著区域进行遮挡。实验表明,FCOS目标检测框架在PASCAL VOC数据上的平均检测精度(mean average precision,mAP)从79.10%提升到83.90%,其中短板类别更为显著,提升了20.8个百分点。在MS-COCO数据上平均检测精度提升了0.9个百分点。