AVS编码器运动估计中内插的快速算法

为了降低AVS编码器在运动估计中进行像素内插的运算复杂度,通过对1/2精度像素进行整帧内插减少了总的内插运算量和内存存取量;提出了利用1/2精度像素的最终值代替中间值滤波的简化算法,进一步降低了运动估计中内插运算实现的复杂度。在PNX1500平台上实验表明在保证编码质量的情况下,运动估计时间得到了大幅度降低。

Finite-difference numerical modeling with even-order accuracy in two-phase anisotropic media

To improve the accuracy of the conventional finite-difference method, finitedifference numerical modeling methods of any even-order accuracy are recommended. We introduce any even-order accuracy difference schemes of any-order derivatives derived from Taylor series expansion. Then, a finite-difference numerical modeling method with any evenorder accuracy is utilized to simulate seismic wave propagation in two-phase anisotropic media. Results indicate that modeling accuracy improves with the increase of difference accuracy order number. It is essential to find the optimal order number, grid size, and time step to balance modeling precision and computational complexity. Four kinds of waves, static mode in the source point, SV wave cusps, reflection and transmission waves are observed in two-phase anisotropic media through modeling.

Effect of inlet configuration on hydrocyclone performance

Inlet configuration is important parameter of hydrocyclones,which has great impact on the classification performance.The effects of inlet configuration on the precise classification were studied by computational fluid dynamics under variouscombinations of inlet diameter and inlet velocity.The results showed that a high sharpness of classification was achieved withspecific inlet diameter and inlet velocity.The separation efficiency of the coarse particles by underflow significantly decreased wheninlet had an oversize diameter owing to a stronger short-circuit flow.It is resulted from the chaotic flow and the stronger pressuregradient around the vortex finder.Meanwhile,a low separation efficiency of the fine particles by overflow was achieved when inletvelocity was high,which indicated a low sharpness caused by the overlarge centrifugal force.

H.264中快速运动估计算法及其架构

提出了一种新的可应用于H.264中的运动估计算法和架构。该算法改进多级顺序排除算法(MSEA),将不同模式的块分为相同数量的子块,去除流程分支使数据流规则而有利于硬件实现,使其适用于H.264的可变块大小与分数像素精度的运动补偿预测。实验证明,该算法在提高搜索效率的前提下仍能保持优良的性能。

Thermo-structural analysis on evaluating effects of friction and transient heat transfer on performance of gears in high-precision assemblies

The high precision assemblies with considerable radial interference should be accompanied by heating and cooling processes.However,the mechanical properties of metals are greatly affected by thermal operations.So,for evaluating the stress distribution and distortion of teeth profiles in a gear/shaft assembly,a transient thermal analysis is necessary for finding the change in mechanical properties.The friction on the contact surface is another important parameter in interaction of the gear with the shaft.Evaluating the gear stress and deformation fields for several modes of heat transfer and friction coefficients showed that the maximum radial or tangential stresses on contact surface of the joint may have more than 8%increase by increasing friction coefficient;while the intensity of heat transfer at cooling stage has lower effect on stress distribution.

Estimating van Genuchten Model Parameters of Undisturbed Soils Using an Integral Method

The van Genuchten model is the most widely used soil water retention curve （SWRC） model. Two undisturbed soils （clay and loam） were used to evaluate the accuracy of the integral method to estimate van Genuchten model parameters and to determine SWRCs of undisturbed soils. SWRCs calculated by the integral method were compared with those measured by a high speed centrifuge technique. The accuracy of the calculated results was evaluated graphically, as well as by root mean square error （RMSE）, normalized root mean square error （NRMSE） and Willmott＇s index of agreement （1）. The results obtained from the integral method were quite similar to those by the centrifuge technique. The RMSEs （4.61 ×10^-5 for Eum-Orthic Anthrosol and 2.74 × 10^-4 for Los-Orthic Entisol） and NRMSEs （1.56 × 10^-4 for Eum- Orthic Anthrosol and 1.45 ×10^-3 for Los-Orthic Entisol） were relatively small. The 1 values were 0.973 and 0.943 for Eum-Orthic Anthrosol and Los-Orthic Entisol, respectively, indicating a good agreement between the integral method values and the centrifuge values. Therefore, the integral method could be used to estimate SWRCs of undisturbed clay and loam soils.

Crop Classification Using MODIS NDVI Data Denoised by Wavelet: A Case Study in Hebei Plain, China

Time-series Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data have been widely used for large area crop mapping.However,the temporal crop signatures generated from these data were always accompanied by noise.In this study,a denoising method combined with Time series Inverse Distance Weighted (T-IDW) interpolating and Discrete Wavelet Transform (DWT) was presented.The detail crop planting patterns in Hebei Plain,China were classified using denoised time-series MODIS NDVI data at 250 m resolution.The denoising approach improved original MODIS NDVI product significantly in several periods,which may affect the accuracy of classification.The MODIS NDVI-derived crop map of the Hebei Plain achieved satisfactory classification accuracies through validation with field observation,statistical data and high resolution image.The field investigation accuracy was 85% at pixel level.At county-level,for winter wheat,there is relatively more significant correlation between the estimated area derived from satellite data with noise reduction and the statistical area (R2 = 0.814,p < 0.01).Moreover,the MODIS-derived crop patterns were highly consistent with the map generated by high resolution Landsat image in the same period.The overall accuracy achieved 91.01%.The results indicate that the method combining T-IDW and DWT can provide a gain in time-series MODIS NDVI data noise reduction and crop classification.

A strip thickness prediction method of hot rolling based on D_S information reconstruction

To improve prediction accuracy of strip thickness in hot rolling, a kind of Dempster/Shafer(D_S) information reconstitution prediction method(DSIRPM) was presented. DSIRPM basically consisted of three steps to implement the prediction of strip thickness. Firstly, iba Analyzer was employed to analyze the periodicity of hot rolling and find three sensitive parameters to strip thickness, which were used to undertake polynomial curve fitting prediction based on least square respectively, and preliminary prediction results were obtained. Then, D_S evidence theory was used to reconstruct the prediction results under different parameters, in which basic probability assignment(BPA) was the key and the proposed contribution rate calculated using grey relational degree was regarded as BPA, which realizes BPA selection objectively. Finally, from this distribution, future strip thickness trend was inferred. Experimental results clearly show the improved prediction accuracy and stability compared with other prediction models, such as GM(1,1) and the weighted average prediction model.

Accuracy Analysis on Bundle Adjustment of Remote Sensing Images Based on Dual Quaternion

A bundle adjustment method of remote sensing images based on dual quaternion is presented,which conducted the uniform disposal corresponding location and attitude of sequence images by the dual quaternion.The constraint relationship of image itself and sequence images is constructed to compensate the systematic errors.The feasibility of this method used in bundle adjustment is theoretically tested by the analysis of the structural characteristics of error equation and normal equation based on dual quaternion.Different distributions of control points and stepwise regression analysis are introduced into the experiment for RC30 image.The results show that the adjustment accuracy can achieve 0.2min plane and 1min elevation.As a result,this method provides a new technique for geometric location problem of remote sensing images.

Accuracy Analysis of Geopotential Coefficients Recovered from In-situ Disturbing Potential by Energy Conservation Method

The characteristics of the normal equation created in recovering the Earth gravity model （EGM） by least-squares （LS） adjustment from the in-situ disturbing potential is discussed in detail. It can be concluded that the normal equation only depends on the orbit, and the choice of a priori gravity model has no effect on the LS solution. Therefore, the accuracy of the recovered gravity model can be accurately simulated. Starting from this point, four sets of disturbing potential along the orbit with different level of noise were simulated and were used to recover the EGM. The results show that on the current accuracy level of the accelerometer calibration, the accuracy of the EGM is not sufficient to reflect the time variability of the Earth＇s gravity field, as the dynamic method revealed.

Application of micro-seismic facies to coal bed methane exploration

A neural network is applied to high-quality 3-D seismic data during micro-seismic facies analysis to perform the waveform analysis and training on single reflection events. Modeled seismic channels are established and the real seismic channels are classified. Thus, a distribution of micro-seismic facies having a high precision over a fiat surface was acquired. This method applied to existing geological data allows the distribution of areas rich in coal bed methane to be clearly defined. A distribution map of the micro-seismic facies in the research area is shown. The data accord well with measured methane con- tents, indicating that the analysis using micro-seismic facies is reliable and effective. This method could be applied to coal bed methane exploration and is of great importance to future exploration work and to an increase in the drilling success rate.

Morphological Variation of Coilia Mystus （Clupeiformes： Engraulidae） in Three Chinese Estuaries

Truss network data were collected and investigated in order to clarify the morphological variation in populations of Coilia mystus from three Chinese estuaries. Nineteen morphometric measurements were made for each individual, and Burnaby＇s multivariate method was used to obtain size-adjusted shape data. The cluster analysis and discriminant analysis were used to discriminate morphological differences among populations. The results indicated that 1） the three populations were clustered into two distinct groups： the first group included Changiiang C. mystus and Zhujiang C. mystus, the last one included Minjiang C. mystus, and 2） discriminant analysis with selected 5 morphological parameters showed that the identification accuracy was between 98.7952% and 100%, and global identification accuracy was 99.2933%. Reproductive isolation and adaption to environmental condition are determinant factors for morphological variation between populations of C. mystus.

Classifying Data Sets Using Support Vector Machines Based on Geometric Distance

Support vector machines （SVMs） are not as favored for large-scale data mining as for pattern recognition and machine learning because the training complexity of SVMs is highly dependent on the size of data set. This paper presents a geometric distance-based SVM （GDB-SVM）. It takes the distance between a point and classified hyperplane as classification rule,and is designed on the basis of theoretical analysis and geometric intuition. Experimental code is derived from LibSVM with Microsoft Visual C ＋＋ 6.0 as system of translating and editing. Four predicted results of five of GDB-SVM are better than those of the method of one against all （OAA）. Three predicted results of five of GDB-SVM are better than those of the method of one against one （OAO）. Experiments on real data sets show that GDB-SVM is not only superior to the methods of OAA and OAO, but highly scalable for large data sets while generating high classification accuracy.

Soft measurement for component content based on adaptive model of Pr/Nd color features

For measurement of component content in the extraction and separation process of praseodymium/neodymium(Pr/Nd), a soft measurement method was proposed based on modeling of ion color features, which is suitable for fast estimation of component content in production field. Feature analysis on images of the solution is conducted,which are captured from Pr/Nd extraction/separation field. H/S components in the HSI color space are selected as model inputs, so as to establish the least squares support vector machine(LSSVM) model for Nd(Pr) content,while the model parameters are determined with the GA algorithm. To improve the adaptability of the model,the adaptive iteration algorithm is used to correct parameters of the LSSVM model, on the basis of model correction strategy and new sample data. Using the field data collected from rare earth extraction production, predictive methods for component content and comparisons are given. The results indicate that the proposed method presents good adaptability and high prediction precision, so it is applicable to the fast detection of element content in the rare earth extraction.

Research on Co-seismic Displacement of the Yutian MS7.3 Earthquake Based on the High Frequency Data of GNSS

After the Yutian M_S7.3 earthquake,the authors instantly collected 1Hz high frequency data of the 4 reference stations within 350 km around the epicenter,and calculated the GNSS data with the TRACK module. The results showed that:( 1) The co-seismic displacement of Yutian station,about 54 km from the epicenter,is the most obvious,particularly in the EW component,with a change of about 52.5 ± 11mm,which is more than three times the mean-square error of calculating precision.( 2) In the Yutian reference station,the biggest variation in the EW component appeared within 1 minute after the earthquake.( 3) The change in the NS component is not great.

Enhancing pose accuracy of space robot by improved differential evolution

Due to the intense vibration durirLg launching and rigorous orbital temperature environment, the kinematic parameters of space robot may be largely deviated from their nominal parameters. The disparity will cause the real pose （including position and orientation） of the end effector not to match the desired one, and further hinder the space robot from performing the scheduled mission. To improve pose accuracy of space robot, a new self-calibration method using the distance measurement provided by a laser-ranger fixed on the end-effector is proposed. A distance-measurement model of the space robot is built according to the distance from the starting point of the laser beam to the intersection point at the declining plane. Based on the model, the cost function about the pose error is derived. The kinematic calibration is transferred to a non-linear system optimization problem, which is solved by the improved differential evolution （DE） algoritlun. A six-degree of freedom （6-DOF） robot is used as a practical simulation example, and the simulation results show： 1） A significant improvement of pose accuracy of space robot can be obtained by distance measurement only; 2） Search efficiency is increased by improved DE; 3） More calibration configurations may make calibration results better.

Accurate vision measurement for kinematic parameters of satellite separation tests

The accurate measurement of kinematic parameters in satellite separation tests has great significance in evaluating separation performance. A novel study is made on the measuring accuracy of monocular and binocular, which are the two main vision measurement methods used for kinematic parameters. As satellite separation process is transient and high-dynamic, it will bring more extraction errors to the binocular. Based on the design approach of intersection measure and variance ratio, the monocular method reflects higher precision, simpler structure and easier calibration for level satellite separation. In ground separation tests, a high-speed monocular system is developed to gain and analyze twelve kinematic parameters of a small satellite. Research shows that this monocular method can be widely applied for its high precision, with position accuracy of 0.5 mm, speed accuracy of 5 mm/s, and angular velocity accuracy of 1 (°)/s.

Elastic catenary cable element considering frictional slip effect

Conventional analysis methods of cable structures do not consider sliding of cables inside the joint,which may lead to inaccuracy of the theoretical behavior of the structure.In order to develop an effective method for cable sliding,a two-node cable element based on the analytical solution for an elastic catenary was studied.The cable sliding stiffness and the effect of friction were investigated.To validate the proposed numerical method,analyses of two examples given in the literature were conducted.The results demonstrated that the method given in this paper is accurate and effective,and can take into account cable sliding in cable structures.In addition,it was shown that the effect of cable sliding on the behavior of cable structures is significant.It was also shown that the friction at the support hampers the flow of the cable force,leading to unequal cable tensions on both sides of the support.

Classification of hyperspectral remote sensing images using frequency spectrum similarity

An algorithm of hyperspectral remote sensing images classification is proposed based on the frequency spectrum of spectral signature.The spectral signature of each pixel in the hyperspectral image is taken as a discrete signal,and the frequency spectrum is obtained using discrete Fourier transform.The discrepancy of frequency spectrum between ground objects' spectral signatures is visible,thus the difference between frequency spectra of reference and target spectral signature is used to measure the spectral similarity.Canberra distance is introduced to increase the contribution from higher frequency components.Then,the number of harmonics involved in the proposed algorithm is determined after analyzing the frequency spectrum energy cumulative distribution function of ground object.In order to evaluate the performance of the proposed algorithm,two hyperspectral remote sensing images are adopted as experimental data.The proposed algorithm is compared with spectral angle mapper (SAM),spectral information divergence (SID) and Euclidean distance (ED) using the product accuracy,user accuracy,overall accuracy,average accuracy and Kappa coefficient.The results show that the proposed algorithm can be applied to hyperspectral image classification effectively.

Constructing confidence intervals of extreme rainfall quantiles using Bayesian,bootstrap,and profile likelihood approaches

Hydrological risk is highly dependent on the occurrence of extreme rainfalls.This fact has led to a wide range of studies on the estimation and uncertainty analysis of the extremes.In most cases,confidence intervals(CIs)are constructed to represent the uncertainty of the estimates.Since the accuracy of CIs depends on the asymptotic normality of the data and is questionable with limited observations in practice,a Bayesian highest posterior density(HPD)interval,bootstrap percentile interval,and profile likelihood(PL)interval have been introduced to analyze the uncertainty that does not depend on the normality assumption.However,comparison studies to investigate their performances in terms of the accuracy and uncertainty of the estimates are scarce.In addition,the strengths,weakness,and conditions necessary for performing each method also must be investigated.Accordingly,in this study,test experiments with simulations from varying parent distributions and different sample sizes were conducted.Then,applications to the annual maximum rainfall(AMR)time series data in South Korea were performed.Five districts with 38-year(1973–2010)AMR observations were fitted by the three aforementioned methods in the application.From both the experimental and application results,the Bayesian method is found to provide the lowest uncertainty of the design level while the PL estimates generally have the highest accuracy but also the largest uncertainty.The bootstrap estimates are usually inferior to the other two methods,but can perform adequately when the distribution model is not heavy-tailed and the sample size is large.The distribution tail behavior and the sample size are clearly found to affect the estimation accuracy and uncertainty.This study presents a comparative result,which can help researchers make decisions in the context of assessing extreme rainfall uncertainties.