基于VAR的电能表降维误差估计模型

为达到远程监控电能表状态并及时准确发现电能表异常的目的,本文提出了一种基于向量自回归模型(VAR)的电能表降维误差估计模型,通过对于电能表电量数据的获取、分析及筛选,采用主成分分析方法(PCA)对于原始数据进行降维,通过VAR提取时间序列中的特征,从而准确预测电能表使用电量并对比出用电异常电能表。其中PCA降维算法处理了实际模型的不可解性,VAR自回归算法提高了估计的稳定性和精度,相较于传统方法具有预测准确度高,所需数据量小的特点。为验证该方法的有效性和实用性,将该方法应用于实际台区中测试,通过对于台区中127块电表半年内的用电数据进行分析,准确定位出8个异常电能表。结果表明,该方法不需要提前独立计算网损,能够实时估计智能电表误差和网损率。

以太网网络通信量的估计

本文以以太网为例讨论一种粗略估计网络通信量的方法,为用户建造自己的网络提供依据。

越南黑胡椒价格趋降

越南一些黑胡椒大出口商初步估计表明,今年越南黑胡椒将会再度获得好收成,从而对黑胡椒价格造成下跌压力。 一家设在胡志明市的出口公司说,尽管湄公河三角洲有水灾问题。

JPEG合成图像的盲篡改检测及定位

提出一种经过JPEG压缩且保存为BMP格式的图像盲篡改检测方法。该算法基于原始量化表不一致性实现篡改定位。首先根据压缩图像特性定位DCT块;然后依据块划分估计原始量化表;最后计算图像块偏离量化表程度,并寻找合适阈值,实现篡改区域的自动检测和定位。改进原始量化表估计算法的实验结果表明:改进算法能实现直流(DC)分量的量化系数估计,并提高量化表估计的正确率,且能有效检测单次JPEG压缩图像的篡改及定位。

Estimation of the Land Surface Emissivity in the Hinterland of Taklimakan Desert

An accurate accounting of land surface emissivity(ε) is important both for the retrieval of surface temperatures and the calculation of the longwave surface energy budgets.Since ε is one of the important parameterizations in land surface models(LSMs),accurate accounting also improves the accuracy of surface temperatures and sensible heat fluxes simulated by LSMs.In order to obtain an accurate emissivity,this paper focuses on estimating ε from data collected in the hinterland of Taklimakan Desert by two different methods.In the first method,ε was derived from the surface broadband emissivity in the 8–14 μm thermal infrared atmospheric window,which was determined from spectral radiances observed by field measurements using a portable Fourier transform infrared spectrometer,the mean ε being 0.9051.The second method compared the observed and calculated heat fluxes under nearneutral atmospheric stability and estimated ε indirectly by minimizing the root-mean-square difference between them.The result of the second method found a mean value of 0.9042,which is consistent with the result by the first method.Although the two methods recover ε from different field experiments and data,the difference of meanvalues is 0.0009.The first method is superior to the indirect method,and is also more convenient.

A modified method to estimate eddy diffusivity in the North Pacific using altimeter eddy statistics

The method proposed by Stammer (1998) is modified using eddy statistics from altimeter observation to obtain more realistic eddy diffusivity (K) for the North Pacific. Compared with original estimates, the modified K has remarkably reduced values in the Kuroshio Extension (KE) and North Equatorial Counter Current (NECC) regions, but slightly enhanced values in the Subtropical Counter Current (STCC) region. In strong eastward flow areas like the KE and NECC, owing to a large difference between mean flow velocity and propagation velocity of mesoscale eddies, tracers inside the mesoscale eddies are transported outside rapidly by advection, and mixing length L is hence strongly suppressed. The low eddy probability (P) is also responsible for the reduced K in the NECC area. In the STCC region, however, L is mildly suppressed and P is very high, so K there is enhanced. The zonally-averaged K has two peaks with comparable magnitudes, in the latitude bands of the STCC and KE. In the core of KE, because of the reduced values of P and L, the zonally-averaged K is a minimum. Zonally-integrated eddy heat transport in the KE band, calculated based on the modified K, is much closer to the results of previous independent research, indicating the robustness of our modified K. The map of modified K provides useful information for modeling studies in the North Pacific.

Application of functional-link neural network in evaluation of sublayer suspension based on FWD test

Several methods for evaluating the sublayer suspension beneath old pavement with falling weight deflectormeter(FWD), were summarized and the respective advantages and disadvantages were analyzed. Based on these methods, the evaluation principles were improved and a new type of the neural network, functional-link neural network was proposed to evaluate the sublayer suspension with FWD test results. The concept of function link, learning method of functional-link neural network and the establishment process of neural network model were studied in detail. Based on the old pavement over-repairing engineering of Kaiping section, Guangdong Province in G325 National Highway, the application of functional-link neural network in evaluation of sublayer suspension beneath old pavement based on FWD test data on the spot was investigated. When learning rate is 0.1 and training cycles are 405, the functional-link network error is less than 0.000 1, while the optimum chosen 4-8-1 BP needs over 10 000 training cycles to reach the same accuracy with less precise evaluation results. Therefore, in contrast to common BP neural network,the functional-link neural network adopts single layer structure to learn and calculate, which simplifies the network, accelerates the convergence speed and improves the accuracy. Moreover the trained functional-link neural network can be (adopted) to directly evaluate the sublayer suspension based on FWD test data on the site. Engineering practice indicates that the functional-link neural model gains very excellent results and effectively guides the pavement over-repairing construction.

Resolving double-sided inverse heat conduction problem using calibration integral equation method

In this paper, a novel calibration integral equation is derived for resolving double-sided, two-probe inverse heat conduction problem of surface heat flux estimation. In contrast to the conventional inverse heat conduction techniques, this calibration approach does not require explicit input of the probe locations, thermophysical properties of the host material and temperature sensor parameters related to thermal contact resistance, sensor capacitance and conductive lead losses. All those parameters and properties are inherently contained in the calibration framework in terms of Volterra integral equation of the first kind. The Laplace transform technique is applied and the frequency domain manipulations of the heat equation are performed for deriving the calibration integral equation. Due to the ill-posed nature, regularization is required for the inverse heat conduction problem, a future-time method or singular value decomposition (SVD) can be used for stabilizing the ill-posed Volterra integral equation of the first kind.

Projections of 2.0°C Warming over the Globe and China under RCP4.5

The outputs of 17 models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) are employed to investigate the temporal and spatial features of 2.0°C warming of the surface temperature over the globe and China under the Representative Concentration Pathways (RCP) 4.5 scenario. The simulations of the period 1860-1899 in the "historical" experiment are chosen as the baseline. The simulations for the 21st century in the RCP4.5 experiment are chosen as the future project. The multi-model ensemble mean (MME) shows that the global mean temperature would cross the 2.0°C warming threshold in 2047. Warming in most of the models would cross the threshold during 2030-2060. For local warming, high-latitude areas in the Northern Hemisphere show the fastest warming over the globe. Land areas warm substantially faster than the oceans. Most of the southern oceans would not exceed the 2.0°C warming threshold within the 21st century. Over China, surface warming is substantially faster than the global mean. The area-averaged warming would cross the 2.0°C threshold in 2034. Locally, Northwest China shows the fastest warming trend, followed by Central North China and Northeast China. Central China, East China, and South China are the last to cross the 2.0°C warming threshold. The diversity of the models is also estimated in this study. Generally, the spread among the models increases with time, and there is smaller spread among the models for the areas with the faster warming.

Improvement of Urban Impervious Surface Estimation in Shanghai Using Landsat7 ETM+ Data

This paper explores the potential to improve the impervious surface estimation accuracy using a multi-stage approach on the basis of vegetation-impervious surface-soil (V-I-S) model. In the first stage of Spectral Mixture Analysis (SMA) process, pixel purity index, a quantitative index for defining endmember quality, and a 3-dimensional endmember selection method were applied to refining endmembers. In the second stage, instead of obtaining impervious surface fraction by adding high and low albedo fractions directly, a linear regression model was built between impervious surface and high/low albedo using a random sampling method. The urban impervious surface distribution in the urban central area of Shanghai was predicted by the linear regression model. Estimation accuracy of spectral mixture analysis and impervious surface fraction were assessed using root mean square (RMS) and color aerial photography respectively. In comparison with three different research methods, this improved estimation method has a higher overall accuracy than traditional Linear Spectral Mixture Analysis (LSMA) method and the normalized SMA model both in root mean square error (RMSE) and standard error (SE). However, the model has a tendency to overestimate the impervious surface distribution.

Estimation of surface tension of organic compounds using quantitative structure-property relationship

A novel quantitative structure-property relationship （QSPR） model for estimating the solution surface tension of 92 organic compounds at 20℃ was developed based on newly introduced atom-type topological indices. The data set contained non-polar and polar liquids, and saturated and unsaturated compounds. The regression analysis shows that excellent result is obtained with multiple linear regression. The predictive power of the proposed model was discussed using the leave-one-out （LOO） cross-validated （CV） method. The correlation coefficient （R） and the leave-one-out cross-validation correlation coefficient （Rcv） of multiple linear regression model are 0.991 4 and 0.991 3, respectively. The new model gives the average absolute relative deviation of 1.81% for 92 substances. The result demonstrates that novel topological indices based on the equilibrium electro-negativity of atom and the relative bond length are useful model parameters for QSPR analysis of compounds.

Single frame super-resolution reconstruction based on sparse representation

In order to effectively improve the quality of recovered images, a single frame super-resolution reconstruction method based on sparse representation is proposed. The combination method of local orientation estimation-based image patch clustering and principal component analysis is used to obtain a series of geometric dictionaries of different orientations in the dictionary learning process. Subsequently, the dictionary of the nearest orientation is adaptively assigned to each of the input patches that need to be represented in the sparse coding process. Moreover, the consistency of gradients is further incorporated into the basic framework to make more substantial progress in preserving more fine edges and producing sharper results. Two groups of experiments on different types of natural images indicate that the proposed method outperforms some state-of- the-art counterparts in terms of both numerical indicators and visual quality.

Two-stage DOA estimation method for passive radar based on sparse representation

In a GPS illuminator based passive radar system,estimation of direction of arriving(DOA) of multiple targets is a difficult problem due to strong interference.A two-stage method combining extensive cancellation algorithm(ECA) and sparse representation is proposed.In the first stage,ECA algorithm is used to eliminate the direct-path and multi-path interference.In the second stage,sparse representation of improved weight constraints based on L1 norm is adopted to estimate DOA and suppress the interference.Simulation results show that the proposed method can effectively estimate DOA in low computation complexity without estimating the disturbance parameter.

Analysis of phenotypic and genetic parameters for growth-related traits in the half smooth tongue sole,Cynoglossus semilaevis

Phenotypic and genetic parameters for growth-related traits in the half-smooth tongue sole, Cynoglossus semilaevis, were estimated in 22 full-sib families produced by normal and neo-male breeding stocks. As phenotypic males with female genotypes, neo-males are harmful in C. semilaevis aquaculture because they reduce overall production. The present study evaluated the difference in the growth-related traits： total length （TL）, body weight （BW） and square root of body weight （SQ_BW） at the age of 570 days between normal and neo-male offspring （neo-males used as male parents）. The difference in the proportion of females between normal and neo-male offspring was also assessed. Based on the linear mixed model, restricted maximum likelihood （REML） and best linear unbiased prediction （BLUP） were used to estimate various （co）variance components and estimated breeding values （EBVs） of growth-related traits. As a result, all the mean values of the three studied traits were significantly larger in normal offspring than in neo-male offspring. Additionally, the female proportion was significantly larger in normal offspring than in neo-male offspring. Heritability was 0.128＋0.066 2 for TL, 0.128-4-0.065 5 for BW and 0.132~0.062 9 for SQBW, all of which were low level heritabilities. The correlation coefficients of EBVs and phenotypic values of the target traits were 0.516 for TL, 0.524 for BW and 0.506 for SQ_BW, all of which were highly significant （P〈0.01）. Genetic correlations among TL, BW and SQ_BW were positive high （0.921-0.969） and higher than those of phenotype （0.711-0.748）, both of which had low standard errors （0.063-0.123 for genotype, and 0.010-0.018 for phenotype）. Compared with normal offspring, neo-male offspring have lower breeding values for each studied trait through EBVs comparison. Therefore, neo-male offspring should not be used as broodstock in a C. semilaevis breeding programs.

Estimation of the Relationship among Fractional Vegetation Cover, Land Surface Temperature and Electricity Consumption in Taipei City

The cooling effects of urban green vegetation cover, which can help decrease LST （land surface temperature） in urban area. When air temperature decreases, the electricity consumption of household will also mitigate loading. Meanwhile, that lack of assessment of green vegetation coverage impact to LST and electricity consumption, so that it could not clearly quantify the environmental contribution of green coves. In Taipei city, for example, FVC （fractional vegetation cover） value and LST was collected from Aster satellite remote sensing images, and data of household electricity consumption was acquired from Taiwan Power Company. Based on these three factors, it analyzed relative model. In the urban area, fractional vegetation cover might influence with land surface temperature and electricity consumption. The result shows that when the value of fractional vegetation cover is low, the air temperature is high. While fractional vegetation cover is increase, not only the land surface temperature is decreasing but the electricity consumption is also reducing. This study hopes can be the reference materials for the future metropolis plan and to inhibit the spread of urban thermal environment.

Comparison of GFR by Creatinine Clearance with Estimated GFR by Various Prediction Equations in a Bangladeshi Population

Glomerular filtration rate （GFR） is considered as the best marker of kidney function. Evaluation of various prediction equations to estimate GFR is rare in our population. The aim of this study was to compare GFR estimated by various prediction equations with GFR by creatinine clearance （GFRer） in Bangladeshi population. Serum creatinine and 24 hours urinary creatinine concentrations were measured in 216 adult Bangladeshi subjects （100 males and 116 females）. Creatinine clearance rate was calculated and adjusted for body surface area to obtain GFRcr. GFR was also calculated by CKD-EPI, MDRD4, Cockcroft-Gault, Jelliffe, Mawer, Bjornsson, Gates, Apollo-Chennai and Mayo Clinic prediction equations and compared with GFRcr. Results were expressed as mean ＋ SD and compared by two-tailed paired t-test, precision （r2） and receiver-operating characteristic curve. Mean ± SD of age of the total subjects was 57.15 ±10.96 years. The mean GFILzr was 42.41 ± 22.95 mL/min/1.73m2. Estimated GFR （eGFR） by CKD-EPI, MDRD4, Cockcroft-Gault, Jelliffc 1, Jelliffe 2, Mawer, Bjornsson, Gates, Apollo-Chennai and Mayo Clinic prediction equations were 8.19 ± 13.80, 5.30 ±13.61, 11.54 ± 16.86, 8.66± 18.64, 17.25 ± 19.98, 10.86 ± 22.48, 14.60 ± 17.92, 12.18 ± 16.42, 39.86 ± 21.96 and 20.47 ± 20.49 mL/min/1.73m2 higher than GFR, （P 〈 0.001）. The precision （r2） of eGFRs were 0.7114, 0.6924, 0.6431, 0.4802, 0.5048, 0.5921, 0.6286, 0.6158, 0.1635, and 0.5586 for CKD-EPI, MDRD4, Cockcroft-Gault, Jelliffe 1, Jelliffe 2, Mawer, Bjornsson, Gates, Apollo-Chennai and Mayo Clinic prediction equations, respectively. The area under receiver-operating characteristic curve was the lowest for MDRD4 equation. This study revealed that GFR estimated by standardized MDRD4 variables equation is closer to creatinine clearance rate in the study population.

C_(p,q)^(s+α)-forms Solution of _b-equ ation and Its L_(p,q)~s Estimates

In this paper, by using holomorphic support f unction of strictly pseudoconvex domain on Stein manifolds and the kernel define d by DEMAILY J P and Laurent Thiebaut, we construct two integral operators T q and S q which are both belong to C s+α p,q-1 (D) and ob tain integral representation of the solution of (p,q)-form b-equation on the boundary of pseudoconvex domain in Stein manifolds and the L s p,q extimates for the solution.

Initial position estimation strategy for a surface permanent magnet synchronous motor used in hybrid electric vehicles

A novel nonlinear model for surface permanent magnet synchronous motors（SPMSMs） is adopted to estimate the initial rotor position for hybrid electric vehicles（HEVs）. Usually, the accuracy of initial rotor position estimation for SPMSMs relies on magnetic saturation. To verify the saturation effect, the transient finite element analysis（FEA） model is presented first. Hybrid injection of a static voltage vector（SVV） superimposed with a high-frequency rotating voltage is proposed. The magnetic polarity is roughly identified with the aid of the saturation evaluation function, based on which an estimation of the position is performed. During this procedure, a special demodulation is suggested to extract signals of iron core saturation and rotor position. A Simulink/MATLAB platform for SPMSMs at standstill is constituted, and the effectiveness of the proposed strategy is verified. The proposed method is also validated by experimental results of an SPMSM drive.

The Bonnesen isoperimetric inequality in a surface of constant curvature

We first estimate the containment measure of a convex domain to contain in another in a surface X of constant curvature.Then we obtain the analogue of the known Bonnesen isoperimetric inequality for convex domain in X.Finally we strengthen the known Bonnesen isoperimetric inequality.

Direct estimation of rupture depths of earthquake faults from coseismic surface deformation

The rupture dimensions of earthquake faults are important parameters for characterizing earthquake ruptures and ground motions. Two key parameters to be determined are the rupture depth and dip angle of earthquake faults. Dislocation theory in an elastic half space indicates that if a seismic rupture directly runs up to the ground surface, there exist zero points of horizontal strain in the surface deformation, which correspond to the rupture depths, except for pure strike-slip faults. In this study, we use numerical simulations to investigate the possibility of inferring rupture depths from zero-strain points for cases of buried faults and heterogeneous media. The results show that the correspondence of zero-strain points to the rupture depths can be influenced by the heterogeneity of the underground media and the stress field. For buried faults, the correspondence relationship is approximately valid when the fault depth is <1 km. In addition, the range of earthquake fault dip angles can be estimated by horizontal displacements on the ground. We also study how to determine the rupture depths of faults from InSAR data after large earthquakes, and successfully apply the method to the 2008 Wenchuan earthquake. The method proposed here, which determines the parameters of fault geometry according to surface deformation, is simple and easy to perform. With independent of aftershocks, it can provide valuable constraints to kinematic inversions.