基于几何剪切图和GPU的渲染地形新方法

大规模地形渲染技术一直是计算机图形学研究的热点问题之一。在总结现有算法的基础上,提出了一种基于现代GPU和Geometry Clipmap的地形渲染算法。应用了类似于几何剪切图的数据结构来提高算法的运行速度,改进了视相关裁剪和法线混合方法,同时用棱锥纹理解决大块纹理不能一次载入内存的问题。实验结果表明了改进方法的可行性和有效性。

结合有限元和非刚体运动估计的左心室应变分析

提出一种直观地分析左心室在心脏收缩期的应变情况的方法.首先利用心脏核磁共振图像数据对左心室进行三维实体建模,再进行有限元单元划分;然后,使用非刚体运动估计算法——单位法线及高斯曲率混合算法,在左心室收缩期相邻时刻的有限元模型表面上寻找最相似单元结点作为对应单元结点,计算各对应结点间的位移,并用α剪枝平均对位移过大的可疑结点进行处理;最后,利用弹塑性力学中应变与位移间的几何关系求解左心室表面各单元结点的应变,获得位移和应变的彩色云图.实验结果表明,该方法能直观、有效地反映左心室表面在整个心脏收缩期的形变情况和应变分布.

IMPLEMENTATION OF THE HYBRID GMRES ALGORITHM USING HOUSEHOLDER TRANSFORMATIONS

The standard implementation of the hybrid GMRES algorithm for solving large nonsymmetric linear systems involves a Gram-Schmidt process which is a potential source of significant numerical error. An alternative implementation is outlined here in which orthogonalization by Householder transformations replaces the Gram-Schmidt process. Numerical experiments show that the new implementation is more stable.

A robust statistical procedure to discover expression biomarkers using microarray genomic expression data

Microarray has become increasingly popular biotechnology in biological and medical researches, and has been widely applied in classification of treatment subtypes using expression patterns of biomarkers. We developed a statistical procedure to identify expression biomarkers for treatment subtype classification by constructing an F-statistic based on Henderson method Ⅲ. Monte Carlo simulations were conducted to examine the robustness and efficiency of the proposed method. Simulation results showed that our method could provide satisfying power of identifying differentially expressed genes （DEGs） with false discovery rate （FDR） lower than the given type I error rate. In addition, we analyzed a leukemia dataset collected from 38 leukemia patients with 27 samples diagnosed as acute lymphoblastic leukemia （ALL） and 11 samples as acute myeloid leukemia （AML）. We compared our results with those from the methods of significance analysis of microarray （SAM） and microarray analysis of variance （MAANOVA）. Among these three methods, only expression biomarkers identified by our method can precisely identify the three human acute leukemia subtypes.

Modeling and Optimization for Short-term Scheduling of Multipurpose Batch Plants

In the past two decades, short-term scheduling of multipurpose batch plants has received significant attention. Most scheduling problems are modeled using either state-task-network or resource-task-network(RTN) process representation. In this paper, an improved mixed integer linear programming model for short-term schedul-ing of multipurpose batch plants under maximization of profit is proposed based on RTN representation and unit-specific events. To solve the model, a hybrid algorithm based on line-up competition algorithm and linear programming is presented. The proposed model and hybrid algorithm are applied to two benchmark examples in literature. The simulation results show that the proposed model and hybrid algorithm are effective for short-term scheduling of multipurpose batch plants.

Multi-objective Evolutionary Algorithms for MILP and MINLP in Process Synthesis

Steady-state non-dominated sorting genetic algorithm (SNSGA), a new form of multi-objective genetic algorithm, is implemented by combining the steady-state idea in steady-state genetic algorithms (SSGA) and the fitness assignment strategy of non-dominated sorting genetic algorithm (NSGA). The fitness assignment strategy is improved and a new self-adjustment scheme of is proposed. This algorithm is proved to be very efficient both computationally and in terms of the quality of the Pareto fronts produced with five test problems including GA difficult problem and GA deceptive one. Finally, SNSGA is introduced to solve multi-objective mixed integer linear programming (MILP) and mixed integer non-linear programming (MINLP) problems in process synthesis.

Analytical Algorithms for the Blend Ratios by Fibre-bundle Tensile Curves Part I: Typical Tensile Curve and the Strength and Work Methods

The blend ratio and tensile properties are vital important characteristics of blended fibre bundles. Fibre-bundle tensile behaviour has been measured by means of the Sirolan-Tensor in order to derive a typical specific stress — extension curve. According to the typical tensile curve, the relationships between the blend ratio and the tensile parameters are discussed and established. Two new algorithms, so-called the strength method and the work method, have been developed for the blend-ratio estimation of blended fibre bundles. The relevant blend-ratios and calculations of the two methods are defined in detail. Also, the characteristics have been explained for every calculation and compared to each others. The experimental results show that the blend ratios estimated from the theoretical methods are high coincidence with the measured results. Meanwhile, the specific stress — extension curve of blended fibre bundles depends directly on the blend ratios of the fibre bundles.

Hybrid control based on inverse Prandtl-Ishlinskii model for magnetic shape memory alloy actuator

The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memory alloy actuator. Based on the proposed Prandtl-Ishlinskii model, the inverse Prandtl-Ishlinskii model was established as a feedforward controller to compensate the hysteresis of the magnetic shape memory alloy actuator. For further improving of the positioning precision of the magnetic shape memory alloy actuator, a hybrid control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with inverse Prandtl-Ishlinskii model and a feedback loop with neural network controller. To validate the validity of the proposed control method, a series of simulations and experiments were researched. The simulation and experimental results demonstrate that the maximum error rate of open loop controller based on inverse PI model is 1.72%, the maximum error rate of the hybrid controller based on inverse PI model is 1.37%.

A linear programming model for long-term mine planning in the presence of grade uncertainty and a stockpile

The complexity of an open pit production scheduling problem is increased by grade uncertainty. A method is presented to calculate the cost of uncertainty in a production schedule based on deviations from the target production. A mixed integer linear programming algorithm is formulated to find the min- ing sequence of blocks from a predefined pit shell and their respective destinations, with two objectives： to maximize the net present value of the operation and to minimize the cost of uncertainty. An efficient clustering technique reduces the number of var/ables to make the problem tractable. Also, the parameters that control the importance of uncertainty in the optimization problem are studied. The minimum annual mining capacity in presence of grade uncertainty is assessed. The method is illustrated with an oil sand deposit in northern Alberta.

Mapping Soil Organic Carbon Stocks of Northeastern China Using Expert Knowledge and GIS-based Methods

The main aim of this paper was to calculate soil organic carbon stock(SOCS) with consideration of the pedogenetic horizons using expert knowledge and GIS-based methods in northeastern China.A novel prediction process was presented and was referred to as model-then-calculate with respect to the variable thicknesses of soil horizons(MCV).The model-then-calculate with fixed-thickness(MCF),soil profile statistics(SPS),pedological professional knowledge-based(PKB) and vegetation type-based(Veg) methods were carried out for comparison.With respect to the similar pedological information,nine common layers from topsoil to bedrock were grouped in the MCV.Validation results suggested that the MCV method generated better performance than the other methods considered.For the comparison of polygon based approaches,the Veg method generated better accuracy than both SPS and PKB,as limited soil data were incorporated.Additional prediction of the pedogenetic horizons within MCV benefitted the regional SOCS estimation and provided information for future soil classification and understanding of soil functions.The intermediate product,that is,horizon thickness maps were fluctuant enough and reflected many details in space.The linear mixed model indicated that mean annual air temperature(MAAT) was the most important predictor for the SOCS simulation.The minimal residual of the linear mixed models was achieved in the vegetation type-based model,whereas the maximal residual was fitted in the soil type-based model.About 95% of SOCS could be found in Argosols,Cambosols and Isohumosols.The largest SOCS was found in the croplands with vegetation of Triticum aestivum L.,Sorghum bicolor(L.) Moench,Glycine max(L.) Merr.,Zea mays L.and Setaria italica(L.) P.Beauv.

A scenario relaxation algorithm for finite scenario based robust assembly line balancing

A balancing problem for a mixed model assembly line with uncertain task processmg Ume anO daily model mixed changes is considered, and the objective is to minimize the work variances between stations in the line. For the balancing problem for the scenario-based robust assembly line with a finitely large number of potential scenarios, the direct solution methodology considering all potential scenarios is quite time-consuming. A scenario relaxation algorithm that embeds genetic al- gorithm is developed. This new algorithm guarantees termination at an optimal robust solution with relatively short running time, and makes it possible to solve robust problems with large quantities of potential scenarios. Extensive computational results are reported to show the efficiency and effectiveness of the proposed algorithm.

Estimation of catalytic activity using an unscented Kalman filtering in condensation reaction

The catalytic activity of cation exchange resins will be continuously reduced with its use time in a condensation reaction for bisphenol A(BPA).For online estimation of the catalytic activity,a catalytic deactivation model is studied for a production plant of BPA,state equation and observation equation are proposed based on the axial temperature distribution of the reactor and the acetone concentration at reactor entrance.A hybrid model of state equation is constructed for improving estimation precision.The unknown parameters in observation equation are calculated with sample data.The unscented Kalman filtering algorithm is then used for on-line estimation of the catalytic activity.The simulation results show that this hybrid model has higher estimation accuracy than the mechanism model and the model is effective for production process of BPA.

SYNTHESIS AND CHARACTERIZATION OF NOVEL SOL-GEL DOPED ORGANIC/INORGANIC HYBRID NONLINEAR OPTICAL MATERIALS

hydroxy-4-nitro azobenzene (NHA) and 4-amino-4-nitro azobenzene (DO3) were prepared respectively from p-nitrophenylamine as a precursor compound. Two kinds of doped organic/inorganic hybrid nonlinear optical (NLO) materials containing NHA and DO3 were synthesized by Sol-Gel process. The preparation and properties of two NLO materials were studied and characterized by FTIR, 1H-NMR, UV-VIS, SEM, DSC and SHG measurements. The results show that the maximum doping amounts of NHA and DO3 in two doped hybrid NLO materials are 7.2(wt)% and 11.3(wt)% respectively, and the corresponding second-order NLO coefficients (d33 values) are 2.91×10 8esu and 6.14×10 8esu. Two doped NLO materials have relatively good RT stability, after 90 days at RT the d33 values can maintain about 85% of their initial values, but after 10h at 100℃ can only maintain about 50% of their initial values. In this report, the reasons for high-temperature instability of doped materials were discussed, and the possible improvements were also suggested.

A modified BFGS algorithm based on a hybrid secant equation

By making a convex combination of the modified secant equations proposed by Yuan and Wei et al., a hybrid secant equation and also, a modified BFGS algorithm is proposed. The hybridization parameter is effectively computed using the available information of recent iterations. Under proper conditions, it is shown that the proposed algorithm is globally, locally and superlinearly convergent. By using the performance profile introduced by Dolan and Mor6, a comparison between the implementations of the proposed algorithm and two efficient modified BFGS algorithms proposed by Yuan and Wei et al., on a set of unconstrained optimization test problems from the CUTEr collection, is done. Numerical results demonstrating the efficiency of the proposed modified BFGS algorithm are reported.

GENERATING EXACT NONLINEAR RANKING FUNCTIONS BY SYMBOLIC-NUMERIC HYBRID METHOD

This paper presents a hybrid symbolic-numeric algorithm to compute ranking functions for establishing the termination of loop programs with polynomial guards and polynomial assignments.The authors first transform the problem into a parameterized polynomial optimization problem,and obtain a numerical ranking function using polynomial sum-of-squares relaxation via semidefinite programming(SDP).A rational vector recovery algorithm is deployed to recover a rational polynomial from the numerical ranking function,and some symbolic computation techniques are used to certify that this polynomial is an exact ranking function of the loop programs.At last,the authors demonstrate on some polynomial loop programs from the literature that our algorithm successfully yields nonlinear ranking functions with rational coefficients.

Statistical and Geometrical Way of Model Selection for a Family of Subdivision Schemes

The objective of this article is to introduce a generalized algorithm to produce the m-point n-ary approximating subdivision schemes(for any integer m, n ≥ 2). The proposed algorithm has been derived from uniform B-spline blending functions. In particular, we study statistical and geometrical/traditional methods for the model selection and assessment for selecting a subdivision curve from the proposed family of schemes to model noisy and noisy free data. Moreover, we also discuss the deviation of subdivision curves generated by proposed family of schemes from convex polygonal curve. Furthermore, visual performances of the schemes have been presented to compare numerically the Gibbs oscillations with the existing family of schemes.

A Spectral Method for the Electrohydrodynamic Flow in a Circular Cylindrical Conduit

This paper presents a combination of the hybrid spectral collocation technique and the spectral homotopy analysis method(SHAM for short) for solving the nonlinear boundary value problem(BVP for short) for the electrohydrodynamic flow of a fluid in an ion drag configuration in a circular cylindrical conduit. The accuracy of the present solution is found to be in excellent agreement with the previously published solution. The authors use an averaged residual error to find the optimal convergence-control parameters. Comparisons are made between SHAM generated results, results from literature and Matlab ode45 generated results, and good agreement is observed.

A defect-correction method for unsteady conduction convection problems Ⅰ:spatial discretization

In this paper, a semi-discrete defect-correction mixed finite element method (MFEM) for solving the non-stationary conduction-convection problems in two dimension is presented. In this method, we solve the nonlinear equations with an added artificial viscosity term on a finite element grid and correct this solutions on the same grid using a linearized defect-correction technique. The stability and the error analysis are derived. The theory analysis shows that our method is stable and has a good convergence property.

Iterative Algorithm with Mixed Errors for Solving a New System of Generalized Nonlinear Variational-Like Inclusions and Fixed Point Problems in Banach Spaces

A new system of generalized nonlinear variational-like inclusions involving A- maximal m-relaxed η-accretive （so-called, （A, η）-accretive in [36]） mappings in q-uniformly smooth Banach spaces is introduced, and then, by using the resolvent operator technique associated with A-maximal m-relaxed ~/-accretive mappings due to Lan et al., the exis- tence and uniqueness of a solution to the aforementioned system is established. Applying two nearly uniformly Lipschitzian mappings 81 and 82 and using the resolvent operator technique associated with A-maximal m-relaxed ~？-accretive mappings, we shall construct a new perturbed N-step iterative algorithm with mixed errors for finding an element of the set of the fixed points of the nearly uniformly Lipschitzian mapping Q = （S1, S2） which is the unique solution of the aforesaid system. We also prove the convergence and stability of the iterative sequence generated by the suggested perturbed iterative algorithm under some suitable conditions, The results presented in this paper extend and improve some known results in the literature.

Mixed nonlinear dynamic voltage phasor tracing method based on WAMS/SCADA

By considering the static voltage characteristic of the load, we propose a WAMS/SCADA mixed nonlinear method to estimate the voltage of unobservable buses caused by topology change or phasor measurement unit (PMU) malfunction in a power system. By modeling the load characteristic with data from SCADA, we employed the Gauss-Seidel method to solve the nonlinear equations and estimate the voltage of unobservable buses with the high precision voltages of neighboring buses measured by a PMU. Simulations were carried out on the IEEE 39-bus system, and the results show that this novel method can dynamically and accurately trace the variation of the voltage phasor of the unobservable buses.