智能识点法实现MD模型上的自动布线

给出了一种MD模型上的布线算法。首先,提出了MD模型上的广义线段的概念;其次,依据人工智能的思维给出绕障点的定义方法;最后,以绕障点和待布点组成布线点集合,以布线点集合中的所有点为顶点构造带边权值的完全图,将布线问题转化为在带边权值的完全图中求布线点间的最短路径,从而得到最优布线路径。实验证明算法的性能良好。

基于徽派建筑的《雨巷》展示动画制作研究

徽派建筑具有极强的徽州地域特征,有着深厚的文化底蕴。文章着重阐述了如何表现徽派建筑的艺术特征与建筑美感,探讨了场景模型制作流程与制作规范,分析了徽派建筑模型制作过程中遇到的问题及其解决方法与技巧;同时深入研究了场景模型UV贴图制作环节,如何高效地利用MAYA贴图来表现人工场景产生的千变万化的自然、逼真的视觉效果。

FOUR-AXIS WIRE-EDM SIMULATION OF COMPLICATED MODELS

In the verification of wire electrical discharge machining （EDM）, the motion and the performance of the wire-EDM system are analyzed. The maximum inclining angle of the wire is calculated. The relevant judgment methods are used for the collision between the wire, the fixture, and the machining table. In the wire-EDM simulation, the generated solid model can he used to investigate programming results and to check the machining accuracy. The generation algorithm for the solid model in the simulation is solved based on Boolean operations. The wire swept volume for each cutting step is united to form the entire wire swept volume. Through Boolean subtraction between the stock model and the entire wire swept volume, the solid model in the wire-EDM simulation is generated. The method is also suitable for the wire path intersection occurred in cutting cone-shaped models. Finally, experiments are given to prove the method.

A Novel Statistical Delay Model Based on the Birnbaum-Saunders Distribution for RLC Interconnects in 90nm Technologies

For performance optimization such as placement,interconnect synthesis,and routing, an efficient and accurate interconnect delay metric is critical,even in design tools development like design for yield （DFY） and design for manufacture （DFM）. In the nanometer regime, the recently proposed delay models for RLC interconnects based on statistical probability density function （PDF）interpretation such as PRIMO,H-gamma,WED and RLD bridge the gap between accuracy and efficiency. However, these models always require table look-up when operating. In this paper, a novel delay model based on the Birnbaum-Saunders distribution （BSD） is presented. BSD can accomplish interconnect delay estimation fast and accurately without table look-up operations. Furthermore, it only needs the first two moments to match. Experimental results in 90nm technology show that BSD is robust, easy to implement,efficient,and accurate.

Potential-Decomposition Strategy in Markov Chain Monte Carlo Sampling Algorithms

We introduce the potential-decomposition strategy （PDS）, which can be used in Markov chain Monte Carlo sampling algorithms. PDS can be designed to make particles move in a modified potential that favors diffusion in phase space, then, by rejecting some trial samples, the target distributions can be sampled in an unbiased manner. Furthermore, if the accepted trial samples are insumcient, they can be recycled as initial states to form more unbiased samples. This strategy can greatly improve efficiency when the original potential has multiple metastable states separated by large barriers. We apply PDS to the 2d Ising model and a double-well potential model with a large barrier, demonstrating in these two representative examples that convergence is accelerated by orders of magnitude.

THERMAL AWARE FLOORPLANNING USING GAUSS-SEIDEL METHOD

The Gauss-Seidel method is effective to solve the traditional sparse linear system. In the paper, we define a class of sparse linear systems in iterative algorithm. The iterative method for linear system can be extended to the dummy sparse linear system. We apply the Gauss-Seidel method, which is one of the iterative methods for linear system, to the thermal model of floorplan of VLSI physical design. The experimental results of dummy sparse linear system are computed by using Gauss-Seidel method that have shown our theory analysis and extendibility. The iterative time of our incremental thermal model is 5 times faster than that of the inverting matrix method.

A fast commonly-used algorithm of P-III distribution curve and its application

Based on theoretical analysis and studying other methods, P-III curve is transformed into an incomplete G function by means of mathematical expression transformation, thus the mathematical model of the fast commonly-used algorithm is drawn out. Algorithm comparison and practices demonstrate that the mathematical model has an easy algorithm, agile resolution process, very good commonality, faster convergence rate and better calculation accuracy, and can be applied to other respects.

Gillnet Selectivity and Length at Maturity of Nile Tilapia （Oreochromis niloticus L.） in a Tropical Reservoir （Amerti： Ethiopia）

The selectivity of gillnets for Oreochromis niloticus in Amerti reservoir （9°63′ N, 37°23′ E） was determined from gillnets with four mesh sizes （60, 80, 100 and 120 mm）. Four selectivity models （a normal model assuming fixed spread, a normal model assuming that spread is proportional to mesh size, a lognormal model and a gamma model） were fitted to the data by using the share each length＇s catch total （SELECT） method. A total of 657 specimens of Oreochromis niloticus were caught （12.0-35.5 cm total length, TD. The sizes at first sexual maturity were 21.5 cm TL and 18.9 cm TL, respectively, for male and female Oreochromis niloticus. The lognormal selectivity curve provided the best fit to the data according to model deviance estimates with optimum selectivity of 16.66, 22.26, 27.78 and 33.38 cm TL for the 60, 80, 100 and 120 mm mesh sizes, respectively.

Dverview and Main Advances in Permutation Tests for Linear Regression Models

When the population, from which the samples are extracted, is not normally distributed, or if the sample size is particularly reduced, become preferable the use of not parametric statistic test. An alternative to the normal model is the permutation or randomization model. The permutation model is nonparametric because no formal assumptions are made about the population parameters of the reference distribution, i.e., the distribution to which an obtained result is compared to determine its probability when the null hypothesis is true. Typically the reference distribution is a sampling distribution for parametric tests and a permutation distribution for many nonparametric tests. Within the regression models, it is possible to use the permutation tests, considering their ownerships of optimality, especially in the multivariate context and the normal distribution of the response variables is not guaranteed. In the literature there are numerous permutation tests applicable to the estimation of the regression models. The purpose of this study is to examine different kinds of permutation tests applied to linear models, focused our attention on the specific test statistic on which they are based. In this paper we focused our attention on permutation test of the independent variables, proposed by Oja, and other methods to effect the inference in non parametric way, in a regression model. Moreover, we show the recent advances in this context and try to compare them.

Interference Coordination for Secrecy Enhancement in Random Wireless Networks

The co-channel interference modeling is vital for evaluating the secrecy performance in random wireless networks,where the legitimate nodes and eavesdroppers are randomly distributed.In this paper,a new interference model is proposed from the userdominant perspective.The model can provide a better analytical assessment of secrecy performance with interference coordination for the presence of eavesdroppers.The typical legitimate is assumed to be located at the origin,and chooses the closest base station(BS) as its serving BS.The field of interferers is obtained by excluding the desired BSs(including the serving BS and its cooperative BS(s)).In contract with the exiting interference model,it is assumed that desired BSs and interferers belong to the same Poisson Point Process(PPP),and eavesdroppers are distributed according to another independent PPP.Based on this model,the average secrecy transmission capacity is derived in simply analytical forms with interference coordination.Analysis and simulation results show that the secrecy performance can be significantly enhanced by exploiting interference coordination.Furthermore,the average secrecy transmission capacity increases with increasing number of cooperative BSs.

A Comparison of Several 5-Minute Radar-Rainfall Estimation Models

For the Z-R relationship in radar-based rainfall estimation, the distribution of corresponding R values for a given Z value (or the corresponding Z value for a given R value) may be highly skewed. However, the traditional power-law model is physically deduced and fitted under the normal-distribution presumption of radar wave echoes associated with a rain rate value, and it may not be very appropriate. Considering this problem, the authors devised several generalized linear models with different forms and distribution presumptions to represent the Z-R relationship. Radar-reflectivity scans observed by a CINRAD/SC Doppler radar and 5-minute rainfall accumulation recorded by 10 ground gauges were used to fit these models. All data used in this study were collected during some large rainfalls of the period from 2005 to 2007. The radar and all gauges were installed in the catchment of the Yishu River, a branch of the Huaihe River in China. Three models based on normal distribution and a dBZ presumption of gamma distribution were fitted using maximum-likelihood techniques, which were resolved by genetic algorithms. Comparisons of estimated maximized likelihoods based on assumptions of gamma and normal distribution showed that all generalized linear models (GLMs) of presumed gamma distribution were better fitted than GLMs based on normal distribution. In a comparison of maximum-likelihood, the differences between these three models were small. Three error statistics were used to assess the agreement between radar estimated rainfall and gauge rainfall: relative bias (B), root mean square error (RMSE), and correlation coefficient (r). The results showed that no one model was excellent in all criteria. On the whole, the GLM-based models gave smaller relative bias than the traditional power-law model. It is suggested that validations conducted in many previous works should have been made against a specific criterion but overlooked others.

Bayesian Variable Selection via Perfect Gibbs Coupler Using Approximate Bounds

Variable selection is one of the most fundamental problems in regression analysis. By sampling from the posterior distributions of candidate models, Bayesian variable selection via MCMC （Markov chain Monte-Carlo） is effective to overcome the computational burden of all-subset variable selection approaches. However, the convergence of the MCMC is often hard to determine and one is often not sure about if obtained samples are unbiased. This complication has limited the application of Bayesian variable selection in practice. Based on the idea of CFTP （coupling from the past）, perfect sampling schemes have been developed to obtain independent samples from the posterior distribution for a variety of problems. Here the authors propose an efficient and effective perfect sampling algorithm for Bayesian variable selection of linear regression models, which independently and identically sample from the posterior distribution of the model space and can efficiently handle thousands of variables. The effectiveness of the authors＇ algorithm is illustrated by three simulation studies, which have up to thousands of variables, the authors＇ method is further illustrated in SNPs （single nucleotide polymorphisms） association study among RA （rheumatoid arthritis） patients.

浅析三维MAYA动画中面部表情制作

现实生活中人们心理情绪的变化主要是通过表情和声音来表现的,而在虚拟的三维动画世界中体现角色内心世界变化最明显的当属面部表情。本文主要从面部表情在三维动画作品中的作用及重要性、表情的设计制作过程以及如何制作出优秀的面部表情三方面入手,详细的分析讲解三维MAYA动画中人物面部表情的制作流程。

RANDOM WEIGHTING METHOD FOR CENSORED REGRESSION MODEL

Rao and Zhao (1992) used random weighting method to derive the approximate distribution of the M-estimator in linear regression model.In this paper we extend the result to the censored regression model (or censored “Tobit” model).

Linear Bayes Estimators Applied to the Inverse Gaussian Lifetime Model

For the two-parameter inverse Gaussian distribution denoted by IG（μ,A）, the authors employ a linear Bayes procedure to estimate the parameters μ and A. The superiority of the proposed linear Bayes estimator （LBE） over both the classical UMVUE and the maximum likelihood estimator （MLE） is established in terms of the mean squared error matrix （MSEM） criterion. Compared with the usual Bayes estimator, which is obtained by an MCMC method, the proposed LBE is simple and easy to use. Some numerical results are presented to verify that the LBE performs well.

GEOMETRIC METHOD OF SEQUENTIAL ESTIMATION RELATED TO MULTINOMIAL DISTRIBUTION MODELS

In 1980's, differential geometric methods are successfully used to study curved exponential families and normal nonlinear repression models. This paper presents a new geometric structure to study multinomial distributipn models which contain a set of nonlinear parameters. Based on this geometric structure, the authors study several asymptotic properties for sequential estimation. The bias, the variance and the information loss of the sequeatial estimates are given from geometric viewpoint, and a limit theorem connected with the obServed and expected Fisher information is obtained ill terms of curVature measures. The results show that the sequeotial estimation procedure has some better properties which are generally impossible for nonsequeotial estimation procedures.

Zero-Absorption Isolines in a 2-Photon 2-Level Atom Model

The c-number atomic Bloch equations modelling the coupling of a 2-photon 2-1evel single atom with a non-resonant （A # O） squeezed vacuum （SV） radiation reservoir show that： （i） The quantum interference （QI） process, of parameter f O, between the 2-photon transition channels causes coupling of the atomic variables （inversion and polarisation）, and, （ii） The SV reservoir parameters （N, M） induce periodic coefficients and hence inhibited oscillatory behaviour in the atomic variables. Perturbative analytical solutions of these non-autonomous B1och equations are derived and used to calculate the absorption spectrum of a weak field probing the system. Of particular, the zero-absorption isolines in the relevant （N, f）- and （A, f ）-planes of the the largest set of points, where absorption is zero, in parameter （M） of the SV reservoir. system parameters are identified computationally. It is found that, the （A, f）-plane depends on the choice of the degree of squeezing

Nonlinear magnetic network models for flux-switching permanent magnet machines

In this paper, firstly, a basic nonlinear magnetic network model considering iron saturations is proposed for a three-phase 12-stator-slot/10-rotor-pole flux-switching permanent magnet(FSPM) machine. This model is built under cylindrical coordinates and enables the open-circuit air-gap flux-density distributions, phase permanent magnet(PM) flux-linkage, and electromotive-force(EMF) to be predicted with acceptable accuracy. However, large discrepancies are found in the predictions of armature inductances. Then, the basic model is modified by taking into account the localized saturation effect. As a result, the electromagnetic performance can be predicted more accurately, especially for the air-gap flux-density distributions. Furthermore, two improved models are proposed by adding bypass-bridge branches in stator network, to enhance the calculating accuracy of both saturated and unsaturated armature inductances. Finally, the predicted results from the four magnetic network models are validated by both 2D finite element analysis(FEA) and experimental measurements on a machine prototype. Overall, comparisons indicate that the model with bypass-bridge branches between stator teeth and back irons exhibits best performances.