Low spatial correlation at base station uniform linear antennas

A spatial channel propagation model is presented. Consider a uniform linear antenna （ULA） at the base station （BS） and narrowband signals transmitted at the mobile. In two types of propagating environments： indoor and outdoor, performance of low spatial correlation is investigated and some results are provided, which are significant to an,3. lyze the performance of diversity systems and configuration of army. The results also show that the configuration of array with either smaller angular spread or bigger angle of arrival （AOA） dominates the impact on spatial correlation, and that increasing angular spread or decreasing AOA diminishes, or even eliminates this impact.

Breaking the linear correlations for enhanced electrochemical nitrogen reduction by carbon-encapsulated mixed-valence Fe_(7)(PO_(4))_(6)

Electrochemical nitrogen reduction(NRR)is deemed as a consummate answer for the traditional Haber–Bosch technology.Breaking the linear correlations between adsorption and transition-state energies of intermediates is vital to improve the kinetics of ammonia synthesis and obtain a less energy-intensive process.Herein,carbon-encapsulated mixed-valence Fe_(7)(PO_(4))_(6) was prepared and applied as an electrocatalyst for high-efficiency NRR.A dramatic faradaic efficiency(FE)of 36.93%and an NH_(3) production rate of 13.1μg h^(-1) mg_(cat)^(-1) were obtained at-0.3 V versus RHE,superior to nearly all Fe-based catalysts.Experiments and DFT calculations revealed that the superior performance was ascribed to the synergistic effect of mixed-valence iron pair,which braked the linear correlations to improve the kinetics of ammonia from collaborative hydrogenation and*NH_(3) separation.This work proves the feasibility of mixedvalence catalysts for nitrogen reduction and thus opening a new avenue towards artificial nitrogenfixation catalysts.

Linear Precoder Design for Correlated Rician Fading Channel Under Imperfect CSI

In this paper,we have modeled a linear precoder for indoor multiuser multiple input multiple output(MU-MIMO)system with imperfect channel state information(CSI)at transmitter.The Rician channel is presumed to be mutually coupled and spatially,temporarily correlated.The imperfection with CSI is primarily due to the channel estimation error at receiver and feedback delay amidst the receiver and transmitter in CSI transmission.Along with,the insufficient spacing between the antenna at transmitter and receiver persuades mutual coupling(MC)among the array elements.In addition,the MIMO channel is presumed to be jointly correlated(Weichselberger correlation model).When we look back on the existing precoder design,it considered spatial correlation alone disregarding joint correlation of antenna array elements.With all above assumption,we have designed a linear precoder which minimizes mean squared error(MSE)subjected to total transmit power constraint for MUMIMO system.The simulation results proven that proposed precoder shows substantial enhancement in bit error rate(BER)performance in comparison with the existing technique.The mathematical analysis corroborates the simulation results.

THE LINEAR CORRELATIONS BETWEEN ELECTRONIC TRANSITION ENERGY AND HAMMETT CONSTANTS FOR THE SUBSTITUTED PORPHYRIN-LIKE MACROCYCLE

The properties of absorption spectra are presented and the linear correlations of Hammett constants with the 0-0 transition energy(E_(o,o))of S_←S_o, and the ratios of oscillator strength(f/f)are used to probe the interactions betwee π-electron of aromatic maerocycles or metal ion of complexes with the sub- stituents on β-position of benzene ring for porphyrin-like maerocyclic compounds.

Estimation of a Linear Model in Terms of Intra-Class Correlations of the Residual Error and the Regressors

Objectives: The objective is to analyze the interaction of the correlation structure and values of the regressor variables in the estimation of a linear model when there is a constant, possibly negative, intra-class correlation of residual errors and the group sizes are equal. Specifically: 1) How does the variance of the generalized least squares (GLS) estimator (GLSE) depend on the regressor values? 2) What is the bias in estimated variances when ordinary least squares (OLS) estimator is used? 3) In what cases are OLS and GLS equivalent. 4) How can the best linear unbiased estimator (BLUE) be constructed when the covariance matrix is singular? The purpose is to make general matrix results understandable. Results: The effects of the regressor values can be expressed in terms of the intra-class correlations of the regressors. If the intra-class correlation of residuals is large, then it is beneficial to have small intra-class correlations of the regressors, and vice versa. The algebraic presentation of GLS shows how the GLSE gives different weight to the between-group effects and the within-group effects, in what cases OLSE is equal to GLSE, and how BLUE can be constructed when the residual covariance matrix is singular. Different situations arise when the intra-class correlations of the regressors get their extreme values or intermediate values. The derivations lead to BLUE combining OLS and GLS weighting in an estimator, which can be obtained also using general matrix theory. It is indicated how the analysis can be generalized to non-equal group sizes. The analysis gives insight to models where between-group effects and within-group effects are used as separate regressors.

Correlation Analysis of Fiscal Revenue and Housing Sales Price Based on Multiple Linear Regression Model

This paper selects seven indicators of financial revenue and housing sales price in recent 19 years in China,and uses SPSS and Excel to carry out descriptive statistics,independent sample t-test,correlation analysis and regression analysis to comprehensively study the correlation between financial revenue and housing sales price in China,and establishes the relationship between financial revenue and housing sales price When the average selling price of commercial housing increases by one unit,the fiscal revenue will increase by 27.855 points.

Rising trends of global precipitable water vapor and its correlation with flood frequency

Using 4 global reanalysis data sets, significant upward trends of precipitable water vapor(PWV) were found in the 3 time periods of 1958-2020, 1979-2020, and 2000-2020. During 1958-2020, the global PWV trends obtained using the ERA5 and JRA55 data sets are 0.19 ± 0.01 mm per decade(1.15 ± 0.31%)and 0.23 ± 0.01 mm per decade(1.45 ± 0.32%), respectively. The PWV trends obtained using the ERA5,JRA55, NCEP-NCAR, and NCEP-DOE data sets are 0.22 ± 0.01 mm per decade(1.18 ± 0.54%),0.21 ± 0.00 mm per decade(1.76 ± 0.56%), 0.27 ± 0.01 mm per decade(2.20 ± 0.70%) and 0.28 ± 0.01 mm per decade(2.19 ± 0.70%) for the period 1979-2020. During 2000-2020, the PWV trends obtained using ERA5, JRA55, NCEP-DOE, and NCEP-NCAR data sets are 0.40 ± 0.25 mm per decade(2.66 ± 1.51%),0.37 ± 0.24 mm per decade(2.19 ± 1.54%), 0.40 ± 0.26 mm per decade(1.96 ± 1.53%) and 0.36 ± 0.25 mm per decade(2.47 ± 1.72%), respectively. Rising PWV has a positive impact on changes in precipitation,increasing the probability of extreme precipitation and then changing the frequency of flood disasters.Therefore, exploring the relationship between PWV(derived from ERA5 and JRA55) change and flood disaster frequency from 1958 to 2020 revealed a significant positive correlation between them, with correlation coefficients of 0.68 and 0.79, respectively, which explains the effect of climate change on the increase in flood disaster frequency to a certain extent. The study can provide a reference for assessing the evolution of flood disasters and predicting their frequency trends.

Night Vision Object Tracking System Using Correlation Aware LSTM-Based Modified Yolo Algorithm

Improved picture quality is critical to the effectiveness of object recog-nition and tracking.The consistency of those photos is impacted by night-video systems because the contrast between high-profile items and different atmospheric conditions,such as mist,fog,dust etc.The pictures then shift in intensity,colour,polarity and consistency.A general challenge for computer vision analyses lies in the horrid appearance of night images in arbitrary illumination and ambient envir-onments.In recent years,target recognition techniques focused on deep learning and machine learning have become standard algorithms for object detection with the exponential growth of computer performance capabilities.However,the iden-tification of objects in the night world also poses further problems because of the distorted backdrop and dim light.The Correlation aware LSTM based YOLO(You Look Only Once)classifier method for exact object recognition and deter-mining its properties under night vision was a major inspiration for this work.In order to create virtual target sets similar to daily environments,we employ night images as inputs;and to obtain high enhanced image using histogram based enhancement and iterative wienerfilter for removing the noise in the image.The process of the feature extraction and feature selection was done for electing the potential features using the Adaptive internal linear embedding(AILE)and uplift linear discriminant analysis(ULDA).The region of interest mask can be segmen-ted using the Recurrent-Phase Level set Segmentation.Finally,we use deep con-volution feature fusion and region of interest pooling to integrate the presently extremely sophisticated quicker Long short term memory based(LSTM)with YOLO method for object tracking system.A range of experimentalfindings demonstrate that our technique achieves high average accuracy with a precision of 99.7%for object detection of SSAN datasets that is considerably more than that of the other standard object detection mechanism.Our approach may therefore satisfy the true demands of night scene target detection applications.We very much believe that our method will help future research.

ON USING NON-LINEAR CANONICAL CORRELATION ANALYSIS FOR VOICE CONVERSION BASED ON GAUSSIAN MIXTURE MODEL

Voice conversion algorithm aims to provide high level of similarity to the target voice with an acceptable level of quality.The main object of this paper was to build a nonlinear relationship between the parameters for the acoustical features of source and target speaker using Non-Linear Canonical Correlation Analysis(NLCCA) based on jointed Gaussian mixture model.Speaker indi-viduality transformation was achieved mainly by altering vocal tract characteristics represented by Line Spectral Frequencies(LSF).To obtain the transformed speech which sounded more like the target voices,prosody modification is involved through residual prediction.Both objective and subjective evaluations were conducted.The experimental results demonstrated that our proposed algorithm was effective and outperformed the conventional conversion method utilized by the Minimum Mean Square Error(MMSE) estimation.

线黏弹性材料数字图像相关实验教学探索

线黏弹性理论是固体力学原理课程的重要内容,目前实验教学一般采用电子万能试验机对线黏弹性材料进行单轴拉伸实验,实验结果不够直观。数字图像相关方法是一种高精度全场应变测量方法,近年来在实验力学领域应用广泛。本文以固体推进剂这种线黏弹性材料为例,采用数字图像相关方法设计了线黏弹性材料单轴拉伸实验,实现了全场变形测量并且实验结果可视化更直观,有助于调动学生积极性。实验发现,数字图像相关方法与国标规定的固体推进剂单向拉伸法测量的材料应变有明显差异,针对该问题设计了实验教学研讨环节,引导学生深入分析,有助于加深对线黏弹性理论的理解。

基于外观性状和指标性成分划分枸杞子不同产地

目的 对不同产地枸杞子外观性状与其指标性成分进行分析,并探究两者是否存在关联性,为进一步研究枸杞子质量评价提供方法。方法 依据《中华人民共和国药典》2020版规定对枸杞子中甜菜碱、枸杞多糖的含量进行测定;对枸杞子的外观性状进行测量统计,采用逐步判别法、线性判别分析法(LDA)对枸杞子外观性状数据进行筛选并优化;并分析枸杞子外观性状与其指标性成分之间的关联性。结果 宁夏枸杞多糖含量高达3.43%,远高于其他产地。对枸杞子外观性状与内在品质进行关联性分析,发现果皮厚度与甜菜碱含量呈负相关性(r=-0.485,P<0.01);纵横比与枸杞多糖含量(r=0.420,P<0.05)、甜菜碱含量(r=0.815,P<0.01)呈正相关性。结论 不同产地的枸杞子在外观性状及内在指标上均有差异,该研究可为枸杞子的综合质量评价提供参考。

从线性校验子分析方法浅析曾肯成先生的密码分析思想

曾肯成先生于1986年洞察到了密码体制中的熵漏现象,后来在此基础上提出著名的线性校验子分析方法.本文全面剖析了线性校验子分析方法的发展历程,由此深刻揭示了曾先生的密码分析思想的精髓.首先,介绍曾先生通过观察Geffe序列生成器的熵漏现象,提出线性校验子分析方法的朴素思想的过程及其蕴含的思想方法;其次,介绍曾先生通过在Geffe序列生成器基础上凝练出的一般问题,提出解决这一问题的一般方法—线性校验子分析方法的过程及其蕴含的思想方法;再次,介绍曾先生通过分析线性校验子分析方法存在的缺陷,进一步完善和改进线性校验子分析方法的过程及其蕴含的思想方法;最后,通过分析从相关分析方法到线性校验子分析方法的进阶之路,阐述了线性校验子分析方法这把利剑的威力.

秦岭北麓乡村植物景观与物种丰富度的关系

选取陕西省秦岭北麓5个村落作为试验区,采用多元线性回归分析和熵值法等相结合,探讨了秦岭北麓乡村地区植物丰富度对乡村景观的影响。结果表明:远离城镇的乡村植物多样性单一,物质丰富度偏低,其乡村景观评价指标体系得分偏低。多元线性逐步回归分析结果表明,Pielou均匀度指数与社会效应、美感效果、生态质量之间存在显著正相关,Menhinick丰富度指数与美感效果、生态质量、文化价值之间存在显著正相关。综上,提出了在乡村景观建设过程中,应立足资源优势,选择适合乡村景观发展的优势特色植物,有效增加评价较低乡村近水生境、居民点周边、农田边缘、林地比例和物种丰富度等建议,以期在促进乡村可持续发展的同时维护农村的环境治理,为乡村景观建设中植物多样性研究提供参考。

稀疏网络编码中秩分布分析模型研究

针对现有稀疏网络编码研究中线性相关概率性能指标精准度较低的问题,提出基于马尔可夫链的性能分析模型。对线性相关概率、秩的概率分布等性能指标及其复杂度进行分析,并通过该性能分析模型分析编码包传输后期的译码成功概率;基于吸收马尔可夫链计算编码包传输过程中的瞬态、吸收态以及各状态间的状态转移概率,并对状态转移概率中蒙特卡罗模拟误差较大的问题进行改进,由状态转移概率构建吸收马尔可夫链基本矩阵,得出信宿端收到非再生包的线性相关概率,进而推导出秩的概率分布和译码成功概率性能指标。仿真结果表明,在相同条件下所提模型性能指标精确度均优于对比模型,且能精确地评估信宿端解码矩阵秩的概率分布、译码成功概率等稀疏网络编码的译码行为。

基于皮尔逊相关系数法的盾构掘进参数对地表沉降影响分析

为研究盾构掘进参数对地表沉降的影响,结合北京地铁19号线某盾构工程的现场监测结果,运用皮尔逊相关系数法对盾构掘进参数对地表沉降影响进行线性回归的相关性分析,检验了线性相关的显著性水平,并针对盾构掘进参数的波动范围和造成的地表沉降规律进行统计分析,继而通过控制参数来实现地表沉降的精细化控制。结果表明:皮尔逊相关系数法在本工程中应用是可靠的,影响地表沉降的两个关键控制参数为同步注浆量、土压力,相关系数分别为0.52和0.41,其他参数与地表沉降表现为极弱相关;右线盾构的掘进参数较左线进行了更加精细化的控制,最优参数控制范围为平均值95%置信区间,最终使右线上方地表沉降较左线大幅度减小,稳定在6mm以内,通过参数精细化控制取得了良好的沉降控制效果。

北京典型汇水区域雨水径流温度特征及影响因素分析

城市化发展导致不透水地表面积率大幅攀升,由此带来的一系列问题逐渐受到人们关注,夏季城市汇水区域地表产生高温径流后汇入下游受纳水体所造成的雨水径流热污染,对水生态、水环境造成不良影响的风险尤为突出。选取北京市典型汇水区域,对2021—2022年多场降雨径流出流温度进行监测与分析,并对气象因素、下垫面温度及管道内径流热量等数据进行同步采集,运用皮尔逊相关系数法分析其影响因素。结果表明:研究区域夏季降雨常出现雨水径流温度升高现象,降水量小于12.5mm、降雨历时短于250 min的降雨场次更易于升温,升温幅度最高可达4.1℃;径流温度升高往往出现在径流过程初期,温度达峰平均时间为38 min;径流是否升温与降雨强度峰值位置之间没有明显关系;气温、不透水地表初始时刻温度、降雨历时及降水量是雨水径流温度的极显著影响因素(P<0.01);降雨期间气温、降雨历时、不透水地表初始时刻温度和管道内壁温度4个指标,可以基本解释研究区域96.7%的径流温度输出情况。

6月龄鲁中肉羊生长性状多元统计分析

为探究鲁中肉羊体尺、体重性状间的关系,测定并收集1 094只(公羊325只,母羊769只)6月龄鲁中肉羊体尺和体重指标数据,对其进行相关性分析、主成分分析和多元线性回归分析。结果表明,公羊和母羊的各体尺指标均与体重呈极显著正相关,各体尺指标之间也均存在极显著的正相关关系。按照累计贡献率在85%以上的标准,公羊选取前3个主成分,分别反映6月龄鲁中肉羊公羊的整体体型结构状况、胸部发育状况和四肢发育状况;母羊选取前2个主成分,分别反映6月龄鲁中肉羊母羊的整体体型结构和四肢发育情况。6月龄鲁中肉羊公羊体重的最佳回归方程为:Y=0.268X_(2)+2.448X_(4)+1.319X_(5)-60.459(R^(2)=0.776,P<0.01),标准化后的最佳回归方程为:Y=0.328X_(2)+0.552X_(4)+0.156X_(5);母羊体重的最佳回归方程为:Y=0.070X_(1)+0.166X_(2)+0.819X_(3)+1.599X_(4)-2.547X_(5)-17.237(R^(2)=0.919,P<0.01),标准化后的最佳回归方程为:Y=0.176X_(1)+0.274X_(2)+0.237X_(3)+0.450X_(4)-0.235X_(5)。本研究结果可为提高鲁中肉羊早期选种选育效率提供理论依据。

无损检测指标与木材横纹局部抗压强度和密度的相关性

【目的】探索不同类型和数量的无损检测(NDT)指标与木材横纹局部抗压强度和密度的相关性差异,确定最优NDT指标组合,为基于无损检测手段评估木材横纹局部抗压强度和密度的研究提供参考。【方法】以某典型藏式古建筑木结构梁构件为研究对象,锯解得到横纹局部抗压无疵试样。通过物理力学试验和NDT试验,获得无疵试样的密度ρ、横纹局部抗压强度f_(lc),以及顺纹应力波速v_(l)、横纹应力波速v和微钻阻力F,计算不同NDT指标或指标组合与ρ、f_(lc)的线性相关系数,进而对比讨论。【结果】(1)使用单一NDT指标预测ρ时,v_(l)效果较好,两者相关系数绝对值为0.662,补充微钻阻力均值Fm后可提高15.56%,达到0.765;使用单一NDT指标预测f_(lc)时,Fm效果较好,两者相关系数为0.526,在此基础上补充横纹应力波速均值v_(m),二者相关系数提升26.80%,达到0.667,进一步补充v_(l)后相关系数继续提升7.20%,达到0.715。(2)当两组NDT指标中的基本指标构成一致时,即便基本指标的形式存在差异,两组NDT指标与被预测参数的相关系数也近似。(3)当两个与被预测参数相关性较好的NDT指标组合时,相关系数可能进一步提高;当相关性较好的指标与较差的指标组合时,相关系数接近于前者;当相关性较差的指标与不相关指标组合时,相关系数可能大幅提升,也可能仍然较低;当两个均不显著相关的指标组合时,指标组合与被预测参数仍不具有显著相关性。【结论】确定合理的NDT指标比一味增加指标数量对相关系数的提高影响更大。综合考虑相关系数提升效果以及由此可能增加的测试工作量,预测木材密度和横纹局部抗压强度时建议分别使用“v_(l),F_(m)”和“F_(m),v_(m)”的NDT指标组合。

一种改进的残余力向量法在结构损伤识别中的应用

残余力向量法是结构损伤识别中常用的方法,复杂结构中单元数量较多而损伤位置较少,容易造成无关变量增多,进而导致计算量过大的问题。鉴于此,本文提出一种改进的残余力向量法用于结构的损伤识别。该方法利用刚度联系向量与残余力向量之间线性相关的特性,以向量投影值作为损伤定位的影响系数,初步筛选出结构可能出现损伤的单元范围。在此基础上,构建出残余力向量对应的线性方程组,根据顺序主子式不为零的条件,对线性方程组进行行初等变换,再根据单元的数量保留前n维线性方程,通过求解该方程组的代数解可得到该结构单元的刚度损伤参数。以简支梁为例的数值模拟表明,本文方法可减少无关单元变量的计算,降低残余力向量的维度并且具有较好的抗噪能力。

宫粉梅花性状的关联分析

为研究宫粉梅花期整体观赏特性及花性状间相互影响程度,并为宫粉梅花期科学管理和性状评价提供理论依据,以宫粉梅为试验材料,采用线性拟合、指标变异情况、R型聚类、主成分和相关性分析对宫粉梅花性状进行研究。对宫粉梅12种开花性状进行调查与关联分析,结果表明,宫粉梅花性状间存在显著的线性相关,花瓣长与花瓣宽拟合效果最好(R^(2)=0.53,Pearson’s r=0.73),开花性状具有较高的不稳定性,未开花数、总花朵数、花瓣宽和花梗长可作为判断花性状特征的参考指标,各项花性状间普遍存在较强的相关性,能协同调控开花特征。