New Results on One Modulo N-Difference Mean Graphs

A graph G is said to be one modulo N-difference mean graph if there is an injective function f from the vertex set of G to the set , where N is the natural number and q is the number of edges of G and f induces a bijection from the edge set of G to given by and the function f is called a one modulo N-difference mean labeling of G. In this paper, we show that the graphs such as arbitrary union of paths, , ladder, slanting ladder, diamond snake, quadrilateral snake, alternately quadrilateral snake, , , , , friendship graph and admit one modulo N-difference mean labeling.

On Cultural Differences between English and Chinese --From the Aspect of Seven Types of Meaning

This paper analyzes cultural differences of English and Chinese in terms of Seven Types of Meaning . It proceeds from the theory of Leech’s Seven Types of meaning , then comparatively illustrates with analysis of each type of meaning and cultural differences. And concludes with the cause of cultural differences and problems of it in cross-cultural communication with the hope that Chinese student could avoid Chinglish in learning and both Chinese and foreigners could avoid cultural shock when communicating with each other.

ON THE m^(th) ORDER DIFFERENCE SEQUENCE SPACE OF GENERALIZED WEIGHTED MEAN AND COMPACT OPERATORS

In this article, using generalized weighted mean and difference matrix of order m, we introduce the paranormed sequence space l（u, v, p; △（m））, which consist of the sequences whose generalized weighted △（m）-difference means are in the linear space l（p） defined by I.J.Maddox. Also, we determine the basis of this space and compute its α-, β- and γ-duals. Further, we give the characterization of the classes of matrix mappings from l（u, v, p, △（m）） to l∞, c, and co. Finally, we apply the Hausdorff measure of noncompacness to characterize some classes of compact operators given by matrices on the space lp（U, v, △（m）） （1 ≤ p 〈 ∞）.

Fast-moving target tracking based on mean shift and frame-difference methods

The mean shift tracker has difficulty in tracking fast moving targets and suffers from tracking error accumulation problem. To overcome the limitations of the mean shift method, a new approach is proposed by integrating the mean shift algorithm and frame-difference methods. The rough position of the moving tar- get is first located by the direct frame-difference algorithm and three-frame-difference algorithm for the immobile camera scenes and mobile camera scenes, respectively. Then, the mean shift algorithm is used to achieve precise tracking of the target. Several tracking experiments show that the proposed method can effectively track first moving targets and overcome the tracking error accumulation problem.

About the Mean Difference of the Inverse Normal Distribution

The calculation of the mean difference for the inverse normal distribution can be obtained by a transformation of variable or a hard integration by parts. This paper shows a simpler formula of the mean difference of the inverse normal distribution that highlights the role of the two parameters on the mean difference of the model. It makes it easier to study the relation of the mean difference with the other indexes of variability for the inverse normal distribution.

Mean Square Convergent Finite Difference Scheme for Stochastic Parabolic PDEs

Stochastic partial differential equations (SPDEs) describe the dynamics of stochastic processes depending on space-time continuum. These equations have been widely used to model many applications in engineering and mathematical sciences. In this paper we use three finite difference schemes in order to approximate the solution of stochastic parabolic partial differential equations. The conditions of the mean square convergence of the numerical solution are studied. Some case studies are discussed.

NOTES ON THE SPECTRAL PROPERTIES OF THE WEIGHTED MEAN DIFFERENCE OPERATOR G(u,v;?) OVER THE SEQUENCE SPACE ?_1

In the study by Baliarsingh and Dutta [Internat. J.Anal., Vol.2014（2014）, Article ID 786437], the authors computed the spectrum and the fine spectrum of the product operator G （u, v; A） over the sequence space e1. The product operator G （u, v; △） over l1 is defined by （G（u,v;△）x）k=^k∑i=0ukvi（xi- xi-1） with xk = 0 for all k 〈 0, where x = （xk）∈e1,and u and v axe either constant or strictly decreasing sequences of positive real numbers satisfying certain conditions. In this article we give some improvements of the computation of the spectrum of the operator G （u, v; △） on the sequence space gl.

Clustering Categorical Data Based on Within-Cluster Relative Mean Difference

The clustering on categorical variables has received intensive attention. In dataset with categorical features, some features show the superior performance on clustering procedure. In this paper, we propose a simple method to find such distinctive features by comparing pooled within-cluster mean relative difference and then partition the data upon such features and give subspace of the subgroups. The applications on zoo data and soybean data illustrate the performance of the proposed method.

Mean Difference and Mean Deviation of Tukey Lambda Distribution

The purpose of this paper is to broaden the knowledge of mean difference and, in particular, of an important distribution model known as Tukey lambda, which is generally used to choose a model to fit data. We have obtained compact formulas, which are not yet reported in literature, of mean deviation and mean difference related to the said distribution model. These results made it possible to analyze the relationships among variability indexes, namely standard deviation, mean deviation and mean difference, regarding Tukey lambda model.

Mean Difference of Truncated Normal Distribution

The purpose of this paper is to broaden the knowledge of mean difference and, in particular, of an important distribution model known as truncated normal distribution, which is widely used in applied sciences and economics. In this work, we obtained the general formula of mean difference, which is not yet reported in literature, for the aforementioned distribution model and also for particular truncated cases.

On the Mean Difference Variance in Random Samples of Student’s Variables

The purpose of this paper is to obtain the expression of the sample mean difference variance of the Student’s distributive model. In the 2007 the study of the mean difference variance, after some decades, was resumed by Campobasso [1]. Using the Nair’s [2] and Lomnicki’s general results [3], he obtained the variance of sample mean difference for different distributive models (Laplace’s, triangular, power, logit, Pareto’s and Gumbel’s model). In addition he extended the knowledge comparing to the ones already known for the other distributive model (normal, rectangular and exponential model).

The Mean Difference for Lognormal Distribution

The calculation of the mean difference for the lognormal distribution involves several hard integrals featuring the error function. In this paper, considering two particular cases of an integral of the exponential function for the complement to one of the error functions, and using various symmetries, we have achieved the result of an extremely simple and useful formula of the mean difference for the lognormal distribution.

The Cultural Difference and Teaching of English Lexicology

Contrast this to be adopted in terms of both language and cultural background reflected in the meaning of life,and address,social etiquette,gender,emotional,and other areas to explore differences in how English vocabulary teaching in the financial and cultural knowledge in the language,into a culture of moderation,thereby enhancing the efficiency of teaching vocabulary to the real purpose of teaching vocabulary.

A new polar motion prediction method combined with the difference between polar motion series

After the first Earth Orientation Parameters Prediction Comparison Campaign(1 st EOP PCC),the traditional method using least-squares extrapolation and autoregressive(LS+AR)models was considered as one of the polar motion prediction methods with higher accuracy.The traditional method predicts individual polar motion series separately,which has a single input data and limited improvement in prediction accuracy.To address this problem,this paper proposes a new method for predicting polar motion by combining the difference between polar motion series.The X,Y,and Y-X series were predicted separately using LS+AR models.Then,the new forecast value of X series is obtained by combining the forecast value of Y series with that of Y-X series;the new forecast value of Y series is obtained by combining the forecast value of X series with that of Y-X series.The hindcast experimental comparison results from January 1,2011 to April 4,2021 show that the new method achieves a maximum improvement of 12.95%and 14.96%over the traditional method in the X and Y directions,respectively.The new method has obvious advantages compared with the differential method.This study tests the stability and superiority of the new method and provides a new idea for the research of polar motion prediction.

Analysis of the Symbolic Meaning of Moby Dick Based on Different Aspects

In the mid-19th century,"White Whale"was written by the famous American writer Hermann Melville. The creation of this work is a new chapter in the creation of literary history. The text has a unique symbolic creative approach. This article will analyze the symbolic meaning of"Moby Dick"from different aspects, and has a high literary and artistic creation value.

Elementary Introduction to the differences in Vocabulary between British English and American English

With the development of the two countries, the differences in some fields are clear and are also reflected in their languages. This paper discusses the differences in vocabulary between British English and American English through three aspects - - - the same words but different meaning, the same meanings but different words,characteistic words.

基于AR-ECM平均差异模型的串联电池组SOC、容量多尺度联合估计方法

考虑电池单体老化差异所致的电池组不一致性,针对串联电池组荷电状态(state of charge,SOC)、容量估计问题,提出一种基于自回归等效电路模型(autoregression equivalent circuit model,AR-ECM)的平均差异模型(mean-difference model,MDM)。基于此模型,提出串联电池组SOC、容量多尺度联合估计算法。该算法由2个部分组成,一是基于AR-ECM的MDM及差异化模型参数辨识策略:条件辨识策略和定频分组辨识策略;二是基于多时间尺度H无穷滤波(multi-timescale H infinity filter,Mts-HIF)的电池组SOC、容量联合估计算法。通过将所提出MDM中的自回归平均模型(autoregression mean model,AR-MM)与传统MDM中的n阶RC平均模型(nRC mean model,nRC-MM)比较,结果表明所提出的AR-MM在复杂运行工况下具有更优的动态跟随性能。依据最小化信息量准则(akaike information criterion,AIC),AR-MM具有更优的复杂度与精度的权衡。通过与基于多时间尺度扩展卡尔曼滤波(multi-timescale extended Kalman filter,Mts-EKF)联合状态估计算法比较,结果表明所提出的Mts-HIF状态估计算法具有更优的鲁棒性、精度和收敛速度。

汪榕培与理雅各英译老庄术语“达意”之辨

老庄经典英译进程中,相去百年的汪榕培、理雅各两种英译本以各自交流性“输出”、学术型“译入”的特质成为跨文化时空性对话的英译经典。通过平行考察上述老庄两译本核心术语的英译实务,着重分析了两译者传达原典关键术语意义“达意”向度、程度上的差异,侧重阐释了两译者翻译“学术”与“普及”观念各从其类的道家英译贡献。

局灶性癫痫围发作期心率变异性变化特点

目的探讨局灶性癫痫围发作期心率变异性变化特点。方法收集2014年9月至2019年9月在首都医科大学附属北京天坛医院癫痫中心进行术前评估并完成手术的癫痫患者102例,选择局灶性发作198次,手动测量相邻两个心电活动的RR间期,计算心率变异性时域参数-相邻正常心跳间期差值平方和的均方根(RMSSD),比较发作前60 s、发作期、终止后60 s RMSSD差异,并比较不同心率变化类型、不同发作类型、不同发作前状态以及不同致痫灶部位和侧别RMSSD差异。结果发作期和发作前60 s及终止后60 s RMSSD相比差异有统计学意义(P<0.001),提示发作期RMSSD降低;心率增快类型癫痫发作期RMSSD降低(P<0.001);复杂部分性癫痫发作期RMSSD降低(P<0.001);颞叶内侧癫痫发作期RMSSD降低(右颞叶内侧P<0.001;左颞叶内侧P<0.001);心率无变化(P=0.556)和心率减慢(P=0.983)类型癫痫发作、单纯部分性癫痫(P=0.869)、颞叶外侧癫痫(右颞叶外侧P=0.204;左颞叶外侧P=0.849)和颞叶外癫痫(右颞外P=0.188;左颞外P=0.068)发作期RMSSD无降低。发作期和发作前60 s RMSSD差值在睡眠期更明显(P=0.039)。结论心率增快类型癫痫发作、复杂部分性癫痫、颞叶内侧癫痫发作期易发生心率变异性下降,提示癫痫发作期副交感活性下降;睡眠期状态下发生的癫痫发作期心率变异性下降相比清醒期显著,提示睡眠期癫痫发作副交感活性下降更加明显。