NOVEL APPROACH TO LOCATOR LAYOUT OPTIMIZATION BASED ON GENETIC ALGORITHM

Proper fixture design is crucial to obtain the better product quality according to the design specification during the workpiece fabrication. Locator layout planning is one of the most important tasks in the fixture design process. However, the design of a fixture relies heavily on the designerts expertise and experience up to now. Therefore, a new approach to loeator layout determination for workpieces with arbitrary complex surfaces is pro- posed for the first time. Firstly, based on the fuzzy judgment method, the proper locating reference and locator - numbers are determined with consideration of surface type, surface area and position tolerance. Secondly, the lo- cator positions are optimized by genetic algorithm（GA）. Finally, a typical example shows that the approach is su- perior to the experiential method and can improve positioning accuracy effectively.

The Spatial Patterns of Initial Errors Related to the “Winter Predictability Barrier” of the Indian Ocean Dipole

In this study, using the Geophysical Fluid Dynamics Laboratory Climate Model version 2pl （GFDL CM2pl） coupled model, the winter predictability barrier （WPB） is found to exist in the model not only in the growing phase but also the Indian Ocean dipole （IOD） decaying phase of positive events due to the effect of initial errors. In particular, the WPB is stronger in the growing phase than in the decaying phase. These results indicate that initial errors can cause the WPB. The domi- nant patterns of the initial errors that cause the occurrence of the WPB often present an eastern-western dipole both in the surface and subsurface temperature components. These initial errors tend to concentrate in a few areas, and these areas may represent the sensitive areas of the predictions of positive IOD events. By increasing observations over these areas and eliminating initial errors here, the WPB phenomenon may be largely weakened and the forecast skill greatly improved.

A NOVEL ESTIMATION METHOD OF TIMING OFFSET FOR OFDM BASED WLAN SYSTEMS

The conventional timing synchronization methods based on time domain correlation have the problems of timing metric plateau in Additive White Gaussian Noise(AWGN) channel and estimation error in multipath fading channel. To resolve the problems, this paper proposes a novel timing metric using the characteristics of long training symbols in IEEE802.11a and a new timing recovery method based on the new timing metric for Orthogonal Frequency Division MuItiplexing(OFDM)-based WLAN systems. The proposed timing metric is defined as a sum of absolute values of the imaginary parts of all the subcarrier samples. It exhibits a unique characteristic that is very sensitive to the true synchronization point since it has minimum value at the true synchronization point and maximum around the true synchronization point. The simulation results show that the performance of timing synchronization is significantly improved, as a result, the probability of error estimation is lower than 10-4 when Signal-to-Noise Ratio(SNR) is more than 10dB.

AN ERROR-RESILIENT H.263+ CODING SCHEME FOR VIDEO TRANSMISSION OVER WIRELESS NETWORKS

Video transmission over wireless networks has received much attention recently for its restricted bandwidth and high bit-error rate, Based on H.263＋, by reversing part stream sequences of each Group Of Block （GOB）, an error resilient scheme is presented to improve video robustness without additional bandwidth burden. Error patterns are employed to simulate Widcband Code Division Multiple Acccss,（WCDMA） channels to check out error resilience performances. Simulation results show that both subjective and objective qualities of the reconstructed images are improved remarkably. The mean Peak Signal to Noise Ratio （PSNR） is increased by 0.5dB, and the highest increment is 2dB.

Stability Analysis for Stochastic Delayed High-order Neural Networks

In this paper, the global asymptotic stability analysis problem is considered for a class of stochastic high-order neural networks with tin.delays. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, several sufficient conditions are derived in order to guarantee the global asymptotic convergence of the equilibtium paint in the mean square. Investigation shows that the addressed stochastic highorder delayed neural networks are globally asymptotically stable in the mean square if there are solutions to some linear matrix inequalities （LMIs）. Hence, the global asymptotic stability of the studied stochastic high-order delayed neural networks can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria.

体育文化史与中西古代体育文化比较中的若干误区

由于古代各个民族文化导向的原因,形成了不同的体育传统。作为中西古代体育史的比较研究,应从文化史的角度揭示中西方文化取向与体育发展道路之间的联系与异同。运用现代科技哲学、文化学、史学研究的理论成果与方法,从体育文化史研究的角度指出了中西体育文化比较中在体育价值观、体育理论与方法论、体育哲学思辨等方面的误局或错位现象,为中西古代体育史的比较研究提供了一些可借鉴的方法。

Single Ended Fault Location Estimation for EHV Transmission Systems

A novel numerical algorithm for fault location estimation of single-phase-to-earth fault on EHV transmission lines is presented in this paper. The method is based on one-terminal voltage and current data and is used in a procedure that provides the automatic determination of faulted types and phases, rather than requires engineer to specify them. The loop and nodal equations comparing the faulted phase to non-fauhed phases of multi-parallel lines are introduced in the fauh location estimation models, in which source impedance of remote end is not involved. Precise algorithms of locating fault are derived. The effect of load flow and fauh resistance, on the location accuracy, are effectively eliminated. The algorithms are demonstrated by digital computer simulations.

GLOBAL SUPERCONVERGENCE ANALYSIS OF WILSON ELEMENT FOR SOBOLEV AND VISCOELASTICITY TYPE EQUATIONS

In this paper the Wilson nonconforming finite element is employed to solve Sobolev and viscoelasticity type equations. By means of post-processing technique, global superconvergence estimates are obtained for quasi-uniform rectangular meshes. Finally, an error correction scheme is presented.

Science Letters:Finite time-horizon Markov model for IEEE 802.11e

We model wireless local area network channel utilization over a finite interval through a finite time-horizon Markov(FTHM) model.By accurately capturing time-varying utilization,the FTHM model allows for generally distributed transmis-sion-opportunity(TXOP) duration,which most existing models do not account for.An absorbing state is introduced to limit the lifetime of the counting process,resulting in a non-ergodic Markov chain that is solved via transient analysis.The model predic-tions for time-varying utilization are validated by simulation with errors of no more than 0.1% after eight beacon intervals.Moreover,we show that the FTHM model prediction error is below 4% for Poisson distributed and uniformly distributed TXOP durations.

High-Precision Direct Method for the Radiative Transfer Problems

It is the main aim of this paper to investigate the numerical methods of the radiative transfer equation. Using the five-point formula to approximate the differential part and the Simpson formula to substitute for integral part respectively, a new high-precision numerical scheme, which has 4-order local truncation error, is obtained. Subsequently, a numerical example for radiative transfer equation is carried out, and the calculation results show that the new numerical scheme is more accurate.

Global characteristics of the second-order ionospheric delay error using inversion of electron density profiles from COSMIC occultation data

It is a well known fact that ionospheric delay error is a predominant factor which influences the positioning accuarcy of GNSS.Although the main part of the first-order ionospheric delay error can be removed by the frequency-dependent behaviors of the ionosphere,the second-order ionospheric delay error must be eliminated to achieve millimetre-scale positioning accuracy.Due to COSMIC occultation providing electron density profiles on the global scale,the paper presents the first-order and the second-order ionospheric delay error analysis on the global scale using the inversion of electron density profiles from COSMIC occultation data during 2009–2011.Firstly,because of the special geographical location of three ISR(incoherent scatter radar),the first-order and the second-order ionospheric delay errors are calculated and discussed;the paper also shows and analyzes the diurnal,seasonal,semi-annual variation of ionospheric delay error with respect to signal direction.Results show that for the L1 signal path,the first-order ionospheric delay error is the largest near the equator,which is circa 7 m;the maximum second-order ionospheric delay error are circa 0.6 cm,0.8 cm and 0.6 cm respectively for L1 signals coming from the zenith,the north and the south at 10 degree elevation angles.The second-order ionospheric delay error on the L1 signal path from zenith are the symmetry between 15°and 15°with respect to magnetic equator,and are nearly zero at the magnetic equator.For the first time,the second-order ionospheric delay error on the global scale is presented,so this research will greatly contribute to analysing the higher-order ionospheric delay error characteristics on the global scale.

ESTIMATION AND INFERENCE FOR VARYING-COEFFICIENT REGRESSION MODELS WITH ERROR-PRONE COVARIATES

This paper studies the estimation and inference for a class of varying-coefficient regression models with error-prone covariates.The authors focus on the situation where the covariates are unobserved,there are no repeated measurements,and the covariance matrix of the measurement errors is unknown,but some auxiliary information is available.The authors propose an instrumental variable type local polynomial estimator for the unknown varying-coefficient functions,and show that the estimator achieves the optimal nonparametric convergence rate,is asymptotically normal,and avoids using undersmoothing to allow the bandwidths to be selected using data-driven methods.A simulation is carried out to study the finite sample performance of the proposed estimator,and a real date set is analyzed to illustrate the usefulness of the developed methodology.

Weighted Profile Least Squares Estimation for a Panel Data Varying-Coefficient Partially Linear Model

This paper is concerned with inference of panel data varying-coefficient partially linear models with a one-way error structure. The model is a natural extension of the well-known panel data linear model （due to Baltagi 1995） to the setting of semiparametric regressions. The authors propose a weighted profile least squares estimator （WPLSE） and a weighted local polynomial estimator （WLPE） for the parametric and nonparametric components, respectively. It is shown that the WPLSE is asymptotically more efficient than the usual profile least squares estimator （PLSE）, and that the WLPE is also asymptotically more efficient than the usual local polynomial estimator （LPE）. The latter is an interesting result. According to Ruckstuhl, Welsh and Carroll （2000） and Lin and Carroll （2000）, ignoring the correlation structure entirely and ＂pretending＂ that the data are really independent will result in more efficient estimators when estimating nonparametric regression with longitudinal or panel data. The result in this paper shows that this is not true when the design points of the nonparametric component have a closeness property within groups. The asymptotic properties of the proposed weighted estimators are derived. In addition, a block bootstrap test is proposed for the goodness of fit of models, which can accommodate the correlations within groups illustrate the finite sample performances of the Some simulation studies are conducted to proposed procedures.