ASSESSMENT OF LOCAL INFLUENCE FOR GENERALIZED CORRELATION COEFFICIENTS

In this paper, we study local influence analysis for Zhang's generalized correlation coefficients and Hotelling's generalized correlation coefficient by using approach. of local influence analysis suggested by Shi (1991), i.e., generalized influence function (GIF) and generalized Cook distance (GCD). An example is given to illustrate our results.

Generalized Correlativity of Median Filtering Operator on Signals

The generalized correlativity of input signal and output signal of a stack filtering operator is defined and used for numerously measuring these filtering operators's behavior in removing noise in signals. We show that under the criterion of the generalized correlativity, of stack filtering operators the median filtering operator is optimal, which implies that this filtering operator possesses better filtering behavior than the others.

An improved bidirectional generative adversarial network model for multivariate estimation of correlated and imbalanced tunnel construction parameters

Estimation of construction parameters is crucial for optimizing tunnel construction schedule.Due to the influence of routine activities and occasional risk events,these parameters are usually correlated and imbalanced.To solve this issue,an improved bidirectional generative adversarial network(BiGAN)model with a joint discriminator structure and zero-centered gradient penalty(0-GP)is proposed.In this model,in order to improve the capability of original BiGAN in learning imbalanced parameters,the joint discriminator separately discriminates the routine activities and risk event durations to balance their influence weights.Then,the self-attention mechanism is embedded so that the discriminator can pay more attention to the imbalanced parameters.Finally,the 0-GP is adapted for the loss of the discrimi-nator to improve its convergence and stability.A case study of a tunnel in China shows that the improved BiGAN can obtain parameter estimates consistent with the classical Gauss mixture model,without the need of tedious and complex correlation analysis.The proposed joint discriminator can increase the ability of BiGAN in estimating imbalanced construction parameters,and the 0-GP can ensure the stability and convergence of the model.

Correlation Dimension in Fault Diagnosis of 600 MW Steam Turbine Generator

GP algorithm of correlation dimension computation is ameliorated which overcomes the shortage of traditional one. Improved process of GP algorithm takes the influence of temporal correlative pairs of points on correlation dimension into account and promotes the computational efficiency prominently. Iterative SVD method is applied to remove the influence of noise on the result of correlation dimension. The faults of steam flow turbulence and oil film disturbance which occur in 600 MW Steam Turbine Generator are analyzed and whose correlation dimensions are computed. More distinct quantitative index than FFT is gained to distinguish two faults and it’s of little importance to apply correlation dimension to study the influence of various factors on steam flow turbulence fault for nonexistence of convergent floor in correlation integral curve, which presents a new way to learn the operational function of large capacity steam turbine generator and carry out comprehensive condition monitoring.

Vacuum Dependent Bell Local Hidden Variable Models and Generalized C.H.S.H. Inequalities

We extend a previous model of the author which generalizes Bell local hidden variable models to the case of entangled photon pairs assuming that the standard Bell correlation functions depend on a hidden vacuum index. We deduce a generalization of Bell theorem assuming that classical observables are not dichotomic and that photon pair emission and detection is not a stationary stochastic process. We derive a photon imperfect polarization correlation functions due to rotational invariance breaking induced by hidden vacuum spin currents. We implement formally this approach deducing a generalization of C.H.S.H. inequalities which asymptotically converges to the standard one and which might be competitive with standard quantum mechanics predictions. We suggest to test this inequalities conceiving new E.P.R.-Bell like tests with time dependent detector efficiency and photon flux. Finally, we suggest to apply these generalized inequalities to the correlation functions of entangled classical spinning waves realized recently with metamaterials.

Performance Improvement in Estimation of Spatially Correlated Rician Fading MIMO Channels Using a New LMMSE Estimator

In most of the previous researches on the multiple-input multiple-output (MIMO) channel estimation, the fading model has been assumed to be Rayleigh distributed. However, the Rician fading model is suitable for microcellular mobile systems or line of sight mode of WiMAX. In this paper, the training based channel es-timation (TBCE) scheme in the spatially correlated Rician flat fading MIMO channels is investigated. First, the least squares (LS) channel estimator is probed. Simulation results show that the Rice factor has no effect on the performance of this estimator. Then, a new linear minimum mean square error (LMMSE) technique, appropriate for Rician fading channels, is proposed. The optimal choice of training sequences with mean square error (MSE) criteria is investigated for these estimators. Analytical and numerical results show that the performance of proposed estimator in the Rician channel model compared with Rayleigh one is much better. It is illustrated that when the channel Rice factor and/or the correlation coefficient increase, the per-formance of the proposed estimator significantly improves.

Generalized Energy-Based Fragmentation Approach for Accurate Binding Energies and Raman Spectra of Methane Hydrate Clusters

Methane hydrates(MHs)play important roles in the fields of chemistry,energy,environmental sciences,etc.In this work,we employ the generalized energy-based fragmentation(GEBF)approach to compute the binding energies and Raman spectra of various MH clusters.For the GEBF binding energies of various MH clusters,we first evaluated the various functionals of density functional theory(DFT),and compared them with the results of explicitly correlated combined coupled-cluster singles and doubles with noniterative triples corrections[CCSD(T)(F12^(*))]method.Our results show that the two best functionals are B3PW91-D3 and B97D,with mean absolute errors of only 0.27 and 0.47 kcal/mol,respectively.Then we employed GEBF-B3PW91-D3 to obtain the structures and Raman spectra of MH clusters with mono-and double-cages.Our results show that the B3PW91-D3 functional can well reproduce the experimental C-H stretching Raman spectra of methane in MH crystals,with errors less than 3 cm^(-1).As the size of the water cages increased,the C-H stretching Raman spectra exhibited a redshift,which is also in agreement with the experimental“loose cage-tight cage”model.In addition,the Raman spectra are only slightly affected by the neighboring environment(cages)of methane.The blueshifts of C-H stretching frequencies are no larger than 3 cm^(-1) for CH_(4) from monocages to doublecages.The Raman spectra of the MH clusters could be combined with the experimental Raman spectra to investigate the structures of methane hydrates in the ocean bottom or in the interior of interstellar icy bodies.Based on the B3PW91-D3 or B97D functional and machine learning models,molecular dynamics simulations could be applied to the nucleation and growth mechanisms,and the phase transitions of methane hydrates.

Effect of electron correlation on high-order harmonic generation in helium model atom

High-order harmonic generation （HHG） of a helium model atom in an intense laser field has been numerically investigated. The influence of electron correlation on HHG is analysed by changing the strength between the electrons. The numerical results show that as the electron interaction strength becomes small, the first ionization energy increases rapidly, which results in the decrease in ionization. So the conversion efficiency of the high harmonic lying in the plateau decreases greatly, while the cutoff harmonic order in the harmonic spectrum increases.

Variable Selection for Generalized Linear Model with Highly Correlated Covariates

The penalized variable selection methods are often used to select the relevant covariates and estimate the unknown regression coefficients simultaneously,but these existing methods may fail to be consistent for the setting with highly correlated covariates.In this paper,the semi-standard partial covariance(SPAC)method with Lasso penalty is proposed to study the generalized linear model with highly correlated covariates,and the consistencies of the estimation and variable selection are shown in high-dimensional settings under some regularity conditions.Some simulation studies and an analysis of colon tumor dataset are carried out to show that the proposed method performs better in addressing highly correlated problem than the traditional penalized variable selection methods.

The Correlation between the Zeroth-Order General Randic Indices and the π-Electronic Energies of Hexagonal Systems

A formula was proved for computing the zeroth-order general Randic index of a hexagonal system to explore the correlation between the zeroth-order general Randic index and the π-electronic energy of a hexagonal system.As a consequence,the extremal hexagonal systems with minimum or maximum zeroth-order general Randic index were completely characterized.Moreover,by using the least-square fit method and regression analysis,a new and close relation was found between the zeroth-order general Randic index and the π-electronic energy of a hexagonal system.So the zeroth-order general Randic index is a good measure of the π-electronic energies for benzenoid hydrocarbons.

基于System Generator的快速视频跟踪系统设计

文中基于System Generator和FPGA技术设计了一种快速视频跟踪系统,构建了图像采集和处理的硬件平台,给出了归一化互相关匹配算法的System Generator模型,在Simulink仿真环境下进行了算法验证,并将该模型转化为VHDL语言下载进FPGA中进行硬件调试,最后将系统成功应用于实践中。相比于传统环境下实现的目标跟踪算法,本系统一方面实现了算法和硬件的分离,提高了系统开发速度,另一方面大大提高了目标跟踪的速度和精度。实践结果表明,该系统能够迅速准确地识别目标,从而实现对目标的实时跟踪。

Long-term Correlations and Extreme Wind Speed Estimations

In this paper, we use fluctuation analysis to study statistical correlations in wind speed time series. Each time series used here was recorded hourly over 40 years. The fluctuation functions of wind speed time series were found to scale with a universal exponent approximating to 0.7, which means that the wind speed time series are long-term correlated. In the classical method of extreme estimations, data are commonly assumed to be independent (without correlations). This assumption will lead to an overestimation if data are long-term correlated. We thus propose a simple method to improve extreme wind speed estimations based on correlation analysis. In our method, extreme wind speeds are obtained by simply scaling the mean return period in the classical method. The scaling ratio is an analytic function of the scaling exponent in the fluctuation analysis.

关于对Shrinking Generator及Self－Shrinking Generator的熵漏分析

本文主要针对文献［１］、［２］先后于９３和９４年分别提出的两种新的流密码体制（即收缩序列产生器ＳｈｒｉｎｋｉｎｇＧｅｎｅｒａｔｏｒ与自收缩序列产生器Ｓｅｌｆ－ＳｈｒｉｎｋｉｎｇＧｅｎｅｒａｔｏｒ），运用概率统计等数学工具和有关密码学理论进行了熵漏分析。首先利用统计分析方法，构造出了与上述密码机制的输入序列有较大符合优势的拟合序列，进而，运用文［３］中提出的快速相关攻击方法，可以破译自收缩序列体制，部分攻破收缩序列体制。本文附有具体实验，且实验结果与理论结果基本吻合。

Dibenzofuran Series in Terrestrial Source Rocks and Crude Oils and Applications to Oil-Source Rock Correlations in the Kuche Depression of Tarim Basin, NW China

Ten series of aromatic hydrocarbon compounds (biphenyl, naphthalene, phenanthrene, anthracene, retene, chrysene, benzoanthracene, dibenzofuran, fluorene, dibenzothiophene) isolated from seven Triassic and Jurassic lacustrine mudstone samples and three swamp coal samples, as well as five crude oil samples collected in the Kuche depression of the Tarim Basin, NW China, have been analysed by GC-MS techniques. It is found that the relative abundances of dibenzofuran series are higher in the three swamp coal samples than those in the lacustrine mudstone samples. Based on the similar relative abundances of dibenzofuran series, especially dibenzofuran compound, in the TICs of aromatic hydrocarbons, crude oils from wells SA3 (K), YTK5 (E, K) and QL1 (E) are thought to have been derived predominantly from the coals of the Lower Jurassic Yangxia Formation or Middle Jurassic Kezilenuer Formation, whereas those from wells YM7 (O) and YH1 (E) were derived mainly from Triassic and Jurassic lacustrine mudstones in the Kuche depression. This is the first report about how to distinguish coal-generated oils from lacustrine mudstone-generated oils in the Kuche depression in terms of the dibenzofuran series. The present paper has enlightening and directive significance for further oil-source rock correlations and oil and/or gas exploration in the Kuche depression of the Tarim Basin.

PROBABILITY MODEL OF GUNTHER GENERATOR

This paper constructs the probability model of Gunther generator at first, and the finite dimension union distribution of the output sequence is presented. The result shows that the output sequence is an independent and uniformly distributed 0,1 random variable sequence. It gives the theoretical foundation about why Gunther generator can avoid the statistic weakness of the output sequence of stop-and-go generator, and analyzes the coincidence between output sequence and input sequences of Gunther generator. The conclusions of this paper would offer theoretical references for designers and analyzers of clock-controlled generators.

The geochemical characteristics and oil-source rock correlation of oilshow from the Majiashan profile, Chaoxian County, South of Anhui Province

In the future time the exploration of marine oil and gas will be one of the significant domains in China. In this paper the biomarker assemblage characteristics of oilshow in the Nanlinghu Formation of the Majiashan pro- file, which is located in Chaoxian County, south of Anhui Province, are described in the light of gas chromatogra- phy/mass spectrometric (GCMS) analysis on the qualitative and quantitative basis. Based on the investigation of the biomarker assemblage characteristics of possible source rocks developed in the area studied, a conclusion is drawn that the oilshow was generated from the Nanlinghu Formation source rocks (abbreviated as T1n), instead of the Qixia Formation source rocks (abbreviated as P1q). It is pointed out that the T1n is of strong potential for future oil explora- tion, and therefore much attention should be paid to it.

The Probability Model of the Multi-valued KM_1M_2 Clock Controlled Generator

This paper constructs the probability model of the multi-valued KM_1M_2 clock controlled generator,and discusses the probability distributing,homogeneous Markov property,ergodic property,strict placidity,numeral character and the property of large numbers of the random variables with this kind of output sequence.It gets the probability formula of the coincidence of the output sequence with the input sequence,and gives important reference to the design and analysis of the multi-valued key stream clock controlled generator in cryptography.

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.

Time-consistent investment and reinsurance strategies for insurers under multi-period mean-variance formulation with generalized correlated returns

The existing literature on investment and reinsurance is limited to the study of continuous-time problems,while discrete-time problems are always ignored by re-searchers.In this study,we first discuss a multi-period investment and reinsurance opti-mization problem under the classical mean-variance framework.When the asset returns with a serially correlated structure,the time-consistent investment and reinsurance strategies are acquired via backward induction.In addition,we propose an alternative time-consistent mean-variance optimization model that contrasts with the classical mean-variance model,and the corresponding optimal strategy and value function are also derived.We find that the investment and reinsurance strategies are both independent of the current wealth for the above two optimization problems,which coincides with the conclusion presented in the continuous-time problems.Most importantly,the above in-vestment strategies with serially correlated structures are both conditional mean-based strategies,rather than unconditional ones.Finally,we compare the investment and rein-surance strategies suggested above based on the simulation approach,to shed light on which investment-reinsurance strategies are more suitable for insurers.

全科医学和初级保健横断面研究的基本设计和实施步骤

横断面研究是经典的研究设计方法之一,在临床各个专业中均有广泛的应用。在全科医学研究中大量科学问题的解答采用了横断面研究设计。这其中不仅包括了对人群健康特征,疾病特征或卫生服务现状的调查研究,还包括了面向社区人群的疾病筛查诊断方法构建等多种研究场景。在全科医学领域中,横断面研究可以做现况描述和比较分析,关联因素分析以及社区筛查诊断方法探索。开展横断面研究应包括研究设计和研究实施两个阶段,研究设计包括准确提炼研究目标,明确研究人群,研究因素及结局指标等临床要素以及确定样本获取方式,明确样本量的确定依据及合理的统计分析策略等方法学要素。研究实施,则需要通过完备的研究方案和病例报告表呈现研究设计思路,在伦理批准的前提下开展数据收集工作,同时注重数据管理工作质量并严格执行方案中的统计分析方法,求证医学问题。横断面研究的特点是相比于随访观察研究所需要的研究周期相对较短,不同基础的研究团队都能找到适合的研究方向,通过了解健康医疗现状,从探讨关联因素创建筛查方法等角度,服务社区医疗。