An Efficient Approach to Rules-Based Optical Proximity Correction

A new approach for rules-based optical proximity correction is presented.The discussion addresses on how to select and construct more concise and practical rules-base as well as how to apply that rules-base.Based on those ideas,several primary rules are suggested.The v-support vector regression method is used to generate a mathematical expression according to rule data.It enables to make correction according to any given rules parameters.Experimental results demonstrate applying rules calculated from the expression match well with that from the rule table.

A New Method to Solve Robust Data Reconciliation in Nonlinear Process

Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. Robust estimators can significantly reduce the effect of gross errors and yield less-biased results. In this article, a new method is proposed to solve the robust data reconciliation problem of nonlinear chemical process. By using several technologies including linearization method, penalty function, virtual observation equation, and equivalent weights method, the robust data reconciliation problem can be transformed into least squares estimator problem which leads to the convenience in computation. Simulation results in a nonlinear chemical process demonstrate the efficiency of the proposed method.

A Novel Robust Nonlinear Dynamic Data Reconciliation

Outlier in one variable will smear the estimation of other measurements in data reconciliation （DR）. In this article, a novel robust method is proposed for nonlinear dynamic data reconciliation, to reduce the influence of outliers on the result of DR. This method introduces a penalty function matrix in a conventional least-square objective function, to assign small weights for outliers and large weights for normal measurements. To avoid the loss of data information, element-wise Mahalanobis distance is proposed, as an improvement on vector-wise distance, to construct a penalty function matrix. The correlation of measurement error is also considered in this article. The method introduces the robust statistical theory into conventional least square estimator by constructing the penalty weight matrix and gets not only good robustness but also simple calculation. Simulation of a continuous stirred tank reactor, verifies the effectiveness of the proposed algorithm.

On the Generation Algorithm of VRS Virtual Observations

In the past few years, network RTK positioning technology, especially the VRS technology, has been widely used in some parts of China and in many countries around the world. The principle of the VRS technology is discussed with corresponding formula deduction, and detailed descriptions and applications of VRS corrections and virtual observations generation algorithm are given.

An NT-MT Combined Method for Gross Error Detection and Data Reconciliation

An NT-MT combined method based on nodal test (NT) and measurement test (MT) is developed for gross error detection and data reconciliation for industrial application. The NT-MT combined method makes use of both NT and MT tests and this combination helps to overcome the defects in the respective methods. It also avoids any artificial manipulation and eliminates the huge combinatorial problem that is created in the combined method based on the nodal test in the case of more than one gross error for a large process system. Serial compensation strategy is also used to avoid the decrease of the coefficient matrix rank during the computation of the proposed method. Simulation results show that the proposed method is very effective and possesses good performance.

A Modified Outlier Detection Method in Dynamic Data Reconciliation

Data reconciliation technology can decrease the level of corruption of process data due to measurement noise, but the presence of outliers caused by process peaks or unmeasured disturbances will smear the reconciled results. Based on the analysis of limitation of conventional outlier detection algorithms, a modified outlier detection method in dynamic data reconciliation (DDR) is proposed in this paper. In the modified method, the outliers of each variable are distinguished individually and the weight is modified accordingly. Therefore, the modified method can use more information of normal data, and can efficiently decrease the effect of outliers. Simulation of a continuous stirred tank reactor (CSTR) process verifies the effectiveness of the proposed algorithm.

System for Measuring Elevator Guide Rail Quality and Its Calibration

A system for measuring the quality parameters of elevator guide rails is developed. The quality parameters the system can measure include straightness, flatness, squareness, width and height of the rail. The system consists of six parts：main guideway, auxiliary guideway, reference rail, saddle, control casing and measured rail. The guide rail to be measured is mounted on a bed. The straightness errors of surfaces are checked by five linear displacement sensors mounted on the saddle. The deviation of readings from the sensor, which is in contact with top guiding surface, gives the straightness error of the surface and height of the rail. The other four sensors are used to measure side guiding surfaces respectively and give other parameters including flatness on the surfaces, squareness, width and height of the rail. A novel calibration method is also developed to calibrate the straightness motion error of the system in horizontal and vertical directions. The deflection deformation of the measured rail is fitted by using a fourth-order polynomial. Experimental results show that the uncertainty of the system on the side surfaces after compensating the straightness motion error is less than 0. 01 mm, and the uncertainty of the system on the top surface after compensating the straightness motion error and the deflection deformation of the rail is less than 0. 03 mm.

Mathematical Programming Method as a Means of Calibration of NIR Analyzers

In addition to the conventional methods of the calibration model construction, such as PCR （principal components regression） and PLS （partial least-squares）, a MPM （mathematical programming method） is developed and proposed for practical use in NIR analyses of agricultural and food products. The proposed method involves the mathematical programming techniques to seek the regression coefficients for the calibration model calculation. It is based on the optimization theory used for finding the extremum of the objective function in the given domain of a vector space and employs the method of the complementarity problems solving. The MPM algorithm is described in detail. The MPM was tested on an InfraLUM FT-10 NIR analyzer of Lumex company with samples of dry milk （for fat）, corn （for protein） and rye flour （for moisture）. The obtained results show that the MPM can be used for constructing multivariate calibrations with the qualitative characteristics superior over those of the classical PCR and PLS methods of analysis.

Estimation of the Gauging and the Calibration Time Interval for the Modern Total Stations

The modern TSs （total stations） have reached a very high level in the provided reading and reliability （accuracy and precision） of their measurements. The evolution of the digital technology has helped in this direction. Thus, the TSs can support all requirements for the stake out and monitoring of modern survey engineering and constructions projects. Their complicated manufacturing process and the sensitivity of their components require gauging, adjusting and calibration at certain time intervals. This appears to be the only way in order to assure the precision of measurements provided by the manufacturer and the reliability of the works they are used for. The goal of this paper is to propose a method for the estimation of the gauging time interval for modern YSs. which could be used by any user. More specifically, the indispensable need for the TSs gauging is elevated and documented. All the parameters that influence their operation are registered. A model expressed by a scale of grades is defined, leading thus to an equation for the calculation of the time interval for the next needed gauging and calibration.

Regular Quasi Cyclic Low Density Parity Check Codes with Girth 8 from Elementary Number Theory

This paper is concerned with (3,n) and (4,n) regular quasi-cyclic Low Density Parity Check (LDPC) code constructions from elementary number theory.Given the column weight,we determine the shift values of the circulant permutation matrices via arithmetic analysis.The proposed constructions of quasi-cyclic LDPC codes achieve the following main advantages simultaneously:1) our methods are constructive in the sense that we avoid any searching process;2) our methods ensure no four or six cycles in the bipartite graphs corresponding to the LDPC codes;3) our methods are direct constructions of quasi-cyclic LDPC codes which do not use any other quasi-cyclic LDPC codes of small length like component codes or any other algorithms/cyclic codes like building block;4)the computations of the parameters involved are based on elementary number theory,thus very simple and fast.Simulation results show that the constructed regular codes of high rates perform almost 1.25 dB above Shannon limit and have no error floor down to the bit-error rate of 10-6.

The Future University Choices of Secondary Schools Students： Statistical Evaluations in Messina Side

In the last decades, especially since the 1990s, there was a gradual rising of educational levels, due to a growing schooling. This paper aims to analyze the propensity toward university enrolment in the Messina area, by means of appropriate statistical methods. In particular, we compared the students of different secondary school institutes in Messina, with reference to the choice of the future university career and other information about the scholastic profit and the scholastic context. Our comparative analysis has been performed through a non-parametric approach, using the Non Parametric Combination （NPC） test based on permutation test. This methodology was chosen for optimal characteristics of which it is characterized.

Study on Mathematical Modeling Software MATLAB Teaching in Higher Vocational Colleges

The present situation of the mathematics teaching in higher vocational colleges is not optimistic. In the new education system, it is an urgent problem for the mathematics teachers in higher vocational colleges to bring forth new ideas for the teaching methods, improve the students＇ interest in learning, and train the application-oriented talented personnel needed by the society. MATLAB software package can help set up a bridge and link for the mathematics teaching and the practical application. Its powerful numerical calculation ability can quickly solve all kinds of calculation problems, so that the basic thinking methods are more closely focused in mathematics teaching and also more conditions are created for mathematics teaching to combine the actual major conditions and life conditions. In this paper, the related problems in the implementation of mathematical modeling software MATLAB and model in higher vocational colleges are discussed.

Efficient splitting schemes for magneto-hydrodynamic equations

We present in this paper several efficient numerical schemes for the magneto-hydrodynamic(MHD)equations. These semi-discretized(in time) schemes are based on the standard and rotational pressure-correction schemes for the Navier-Stokes equations and do not involve a projection step for the magnetic field. We show that these schemes are unconditionally energy stable, present an effective algorithm for their fully discrete versions and carry out demonstrative numerical experiments.

ALMOST SURE AND MOMENT EXPONENTIAL STABILITY OF PREDICTOR-CORRECTOR METHODS FOR STOCHASTIC DIFFERENTIAL EQUATIONS

This paper deals with almost sure and moment exponential stability of a class of predictor- corrector methods applied to the stochastic differential equations of Ito-type. Stability criteria for this type of methods are derived. The methods are shown to maintain almost sure and moment exponential stability for all sufficiently small timesteps under appropriate conditions. A numerical experiment further testifies these theoretical results.

Empirical likelihood for single-index models with responses missing at random

The missing response problem in single-index models is studied, and a bias-correction method to infer the index coefficients is developed. Two weighted empirical log-likelihood ratios with asymptotic chisquare are derived, and the corresponding empirical likelihood confidence regions for the index coefficients are constructed. In addition, the estimators of the index coefficients and the link function are defined, and their asymptotic normalities are proved. A simulation study is conducted to compare the empirical likelihood and the normal approximation based method in terms of coverage probabilities and average lengths of confidence intervals. A real example illustrates our methods.

HPLC-DAD data coupled with second-order calibration method applied to food analysis: Simultaneous determination of six benzoylurea insecticides in various fruit samples by selecting time region of chromatogram

This work presents a novel application of second-order calibration based on self-weighted alternating trilinear decomposition(SWATLD)algorithm for analyzing the HPLC-DAD data.The proposed method makes it possible to simultaneously determine teflubenzuron,hexaflumuron,flufenoxuron,chlorfluazuron,diflubenzuron and benzoylurea in different fruit samples,i.e.pear,apple and banana,in the selected time region of chromatogram.The concentration,elution time and spectral information of these benzoylurea insecticides are selectively extracted from complex matrices even in the presence of unknown interferences.The root-mean-square error of prediction(RMSEP)and figures of merit,including sensitivity(SEN),selectivity(SEL)and limit of detection(LOD)are employed to access the performance of the method.The LODs obtained for these insecticides are within the range 0.017–0.26 ppm in pears,0.039–0.33 ppm in apples,0.041–0.44 ppm in bananas,respectively.Such a chemometrics-based protocol holds great potential to be extended as a promising alternative for more practical applications in food safety and quality monitoring.

Numerical studies of penetration problems by an improved particle method

A particle mapping transportation algorithm was proposed on the basis of the particle-in-cell method.The particles with rectangular influence domains were employed in the transportation algorithm to reduce the numerical fluctuations.Based on the error analysis in the process of particle motion computation,a prediction-correction algorithm was introduced to improve the computational accuracy.Furthermore,the performance of the particle mapping transportation method was evaluated by using the rotation,the slotted disk and the shear advection tests,and the results were compared with other interface reconstruction methods.Finally,the hemispherical projectile penetration into a steel target was numerically simulated.The results showed that the proposed method produced less numerical fluctuations and exhibited clear material interfaces,which indicated that it is accurate and effective.

An Iterative Stabilized Scheme for Unsteady Incompressible Viscous Flow

An efficient iterative algorithm is presented for the numerical solution of viscous incompressible Navier-Stokes equations based on Taylor-Galerkin like split and pressure correction method in this paper. Taylor-Hood element is introduced to overcome the numerical difficulties arising from the fluid incompressibility. In order to confirm the properties of the algorithm, the numerical simulation on plane Poisseuille flow problem and lid- driven cavity flow problem with different Reynolds numbers is presented. The numerical results indicate that the proposed iterative version can be effectively applied to the simulation of viscous incompressible flows. Moreover, the proposed iterative version has a better overall performance in maximum time step size allowed, under comparable convergence rate, stability and accuracy, than other tested versions in numerical solutions of the plane PoisseuiUe flow with different Reynolds numbers ranging from low to high viscosities.

Method study and uncertainty analysis of calibration coefficients validation based on the Inner Mongolia test site

Calibration coefficients validation is the foundation for ascertaining the sensor performance and carrying out the quantitative application.Based on the analysis of the differences between the calibration and validation,two calibration coefficients validation methods were introduced in this paper.Taking the HJ-1A satellite CCD1 camera as an example,the uncertainties of calibration coefficients validation were analyzed.The calibration coefficients validation errors were simulated based on the measured data at an Inner Mongolia test site.The result showed that in the large view angle,the ground directional reflectance variation and the atmospheric path variation were the main error sources in calibration coefficients validation.The ground directional reflectance correction and atmospheric observation angle normalization should be carried out to improve the validation accuracy of calibration coefficients.