Three-Dimensional Space Interpolation of Grey / Depth Image Sequence-A New Technique of Computer Graphics Synthesis

This paper advances a three-dimensional space interpolation method of grey / depth image sequence, which breaks free from the limit of original practical photographing route. Pictures can cruise at will in space. By using space sparse sampling, great memorial capacity can be saved and reproduced scenes can be controlled. To solve time consuming and complex computations in three-dimensional interpolation algorithm, we have studied a fast and practical algorithm of scattered space lattice and that of 'Warp' algorithm with proper depth. By several simple aspects of three dimensional space interpolation, we succeed in developing some simple and practical algorithms. Some results of simulated experiments with computers have shown that the new method is absolutely feasible.

APPLICATION OF COMPUTER GRAPHICS IN MARTENSITIC TRANSFORMATION

This paper discuss the stereographic method of martensitic transformation (MT)in the view of computer graphics (CG) and programs are programmed to realize this method. Habit plane resulting from the programs agrees with that of numerical analysis in terms of the lattice parameters of austenite and martensite and shear mechanism supposed in Fe-22%Ni-0.8%C alloy, so does orientation relationships.

Identification of Lubricating Oil Additives Using XGBoost and Ant Colony Optimization Algorithms

To address the problem of identifying multiple types of additives in lubricating oil,a method based on midinfrared spectral band selection using the eXtreme Gradient Boosting(XGBoost)algorithm combined with the ant colony optimization(ACO)algorithm is proposed.The XGBoost algorithm was used to train and test three additives,T534(alkyl diphenylamine),T308(isooctyl acid thiophospholipid octadecylamine),and T306(trimethylphenol phosphate),separately,in order to screen for the optimal combination of spectral bands for each additive.The ACO algorithm was used to optimize the parameters of the XGBoost algorithm to improve the identification accuracy.During this process,the support vector machine(SVM)and hybrid bat algorithms(HBA)were included as a comparison,generating four models:ACO-XGBoost,ACO-SVM,HBA-XGboost,and HBA-SVM.The results showed that all four models could identify the three additives efficiently,with the ACO-XGBoost model achieving 100%recognition of all three additives.In addition,the generalizability of the ACO-XGBoost model was further demonstrated by predicting a lubricating oil containing the three additives prepared in our laboratory and a collected sample of commercial oil currently in use。

Power Quality Disturbance Classification Method Based on Wavelet Transform and SVM Multi-class Algorithms

The accurate identification and classification of various power quality disturbances are keys to ensuring high-quality electrical energy. In this study, the statistical characteristics of the disturbance signal of wavelet transform coefficients and wavelet transform energy distribution constitute feature vectors. These vectors are then trained and tested using SVM multi-class algorithms. Experimental results demonstrate that the SVM multi-class algorithms, which use the Gaussian radial basis function, exponential radial basis function, and hyperbolic tangent function as basis functions, are suitable methods for power quality disturbance classification.

Multi-Label Chinese Comments Categorization: Comparison of Multi-Label Learning Algorithms

Multi-label text categorization refers to the problem of categorizing text througha multi-label learning algorithm. Text classification for Asian languages such as Chinese isdifferent from work for other languages such as English which use spaces to separate words.Before classifying text, it is necessary to perform a word segmentation operation to converta continuous language into a list of separate words and then convert it into a vector of acertain dimension. Generally, multi-label learning algorithms can be divided into twocategories, problem transformation methods and adapted algorithms. This work will usecustomer's comments about some hotels as a training data set, which contains labels for allaspects of the hotel evaluation, aiming to analyze and compare the performance of variousmulti-label learning algorithms on Chinese text classification. The experiment involves threebasic methods of problem transformation methods: Support Vector Machine, Random Forest,k-Nearest-Neighbor;and one adapted algorithm of Convolutional Neural Network. Theexperimental results show that the Support Vector Machine has better performance.

Graphical model construction based on evolutionary algorithms

Using Bayesian networks to model promising solutions from the current population of the evolutionary algorithms can ensure efficiency and intelligence search for the optimum. However, to construct a Bayesian network that fits a given dataset is a NP-hard problem, and it also needs consuming mass computational resources. This paper develops a methodology for constructing a graphical model based on Bayesian Dirichlet metric. Our approach is derived from a set of propositions and theorems by researching the local metric relationship of networks matching dataset. This paper presents the algorithm to construct a tree model from a set of potential solutions using above approach. This method is important not only for evolutionary algorithms based on graphical models, but also for machine learning and data mining. The experimental results show that the exact theoretical results and the approximations match very well.

Comparison of fast discrete wavelet transform algorithms

This paper presents an analysis on and experimental comparison of several typical fast algorithms for discrete wavelet transform (DWT) and their implementation in image compression, particularly the Mallat algorithm, FFT-based algorithm, Short- length based algorithm and Lifting algorithm. The principles, structures and computational complexity of these algorithms are explored in details respectively. The results of the experiments for comparison are consistent to those simulated by MATLAB. It is found that there are limitations in the implementation of DWT. Some algorithms are workable only for special wavelet transform, lacking in generality. Above all, the speed of wavelet transform, as the governing element to the speed of image processing, is in fact the retarding factor for real-time image processing.

A-E equation of potential field transformations in the wavenumber domain and its application

A shift sampling theory established by author （1997a） is a generalization of Fourier transform computation theory. Based on this theory, I develop an Algorithm-Error （A-E） equation of potential field transformations in the wavenumber domain, which not only gives a more flexible algorithm of potential field transformations, but also reveals the law of error of potential field transformations in the wavenumber domain. The DFT0η η（0.5, 0.5） reduction-to-pole （RTP） technique derived from the A-E equation significantly improves the resolution and accuracy of RTP anomalies at low magnetic latitudes, including the magnetic equator. The law （origin, form mechanism, and essential properties） of the edge oscillation revealed by the A-E equation points out theoretically a way of improving the effect of existing padding methods in high-pass transformations in the wavenumber domain.

Electromagnetic Model and Image Reconstruction Algorithms Based on EIT System

An intuitive 2D model of circular electrical impedance tomography （EIT） sensor with small size electrodes is established based on the theory of analytic functions. The validation of the model is proved using the result from the solution of Laplace equation. Suggestions on to electrode optimization and explanation to the ill-condition property of the sensitivity matrix are provided based on the model, which takes electrode distance into account and can be generalized to the sensor with any simple connected region through a conformal transformation. Image reconstruction algorithms based on the model are implemented to show feasibility of the model using experimental data collected from the EIT system developed in Tianjin University. In the simulation with a human chestlike configuration, electrical conductivity distributions are reconstructed using equi-potential backprojection （EBP） and Tikhonov regularization （TR） based on a conformal transformation of the model. The algorithms based on the model are suitable for online image reconstruction and the reconstructed results are aood both in size and position.

TWO TYPES OF NEW ALGORITHMS FOR FINDING EXPLICIT ANALYTICAL SOLUTIONS OF NONLINEAR DIFFERENTIAL EQUATIONS

The idea of AC = BD was applied to solve the nonlinear differential equations. Suppose that Au = 0 is a given equation to he solved and Dv = 0 is an equation to be easily solved. If the transformation u = Cv is obtained so that v satisfies Dv = 0, then the solutions for Au = 0 can be found. In order to illustrate this approach, several examples about the transformation C are given.

SPLIT-RADIX ALGORITHMS FOR LENGTH-p^m DHT

The split-radix 2/4 algorithm for discrete Hartley transform(DHT)of length-2~m isnow very popular.In this paper,the split-radix approach is generalized to length-p^m DHT.It isshown that the radix-p/p^2 algorithm is superior to both the radix-p and the radix-p^2 algorithmsin the number of multiplications.As an example,a radix-3/9 fast algorithm for length-3~m DHTis developed.And its diagram of butterfly operation is given.

Several Algorithms for Manipulating Compressed Images in JPEG

Currently,in multimedia and image processing technologies, implementing special kinds of image manipulation operations by dealing directly with the compressed image is a work worthy to be concerned with. Theoretical analysis and experiment haVe indicated that some kinds of image processing works can be done very well by dealing with compressed image. In Ans paper, we give some efficient image manipulation operation algorithms operating on the compressed image data. These algorithms have advantages in computing complexity, storage space retirement and image quality.

Implementation of Control Algorithms in Small Embedded Systems

This work describes how a control algorithm can be implemented in a small (8-bit) microcontroller for the main purpose of merging embedded systems and control theory in electrical engineering undergraduate classes. Two different methods for discretizing the control expression are compared: Euler transformation and bilinear transformation. The sampling rate’s impact on the algorithm is discussed and theoretical results are verified by an application to a temperature control system in a heating plant. Four control algorithms are compared: PID and PI algorithms discretized with Euler and bilinear transformation, respectively. It is shown that for the heating plant used in this work, a bilinear PI algorithm implemented in a small 8-bit microcontroller outperforms a commercial controller from Panasonic. It is also demonstrated that all the derived algorithms can be implemented using integer calculations only, obviating the need for expensive and time-consuming floating-point calculations. This work bridges the gap between control theory equations and the implementation of control systems in small embedded systems with no inherent floating-point processing power.

Performance characterization of illumination algorithms for reconfigurable graphics processor

Graphics processing is an increasing important application domain with the demand of real-time rendering,video streaming,virtual reality,and so on.Illumination is a critical module in graphics rendering and is typically compute-bound,memory-bound,and power-bound in different application cases.It is crucial to decide how to schedule different illumination algorithms with different features according to the practical requirements in reconfigurable graphics hardware.This paper analyze the performance characteristics of four main-stream lighting algorithms,Lambert illumination algorithm,Phong illumination algorithm,Blinn-Phong illumination algorithm,and Cook-Torrance illumination algorithm,using hardware performance counters on x86 processor platform KabyLake(KBL).The data movement,computation,power consumption,and memory accessing are evaluated over a range of application scenarios.Further,by analyzing the system-level behavior of these illumination algorithms,obtains the cons and pros of these specific algorithms were obtained.The associated relationship between performance/energy and the evaluated metrics was analyzed through Pearson correlation coefficient(PCC)analysis.According to these performance characterization data,this paper presents some reconfiguration suggestions in reconfigurable graphics processor.

Local MFS Matrix Decomposition Algorithms for Elliptic BVPs in Annuli

We apply the local method of fundamental solutions(LMFS)to boundary value problems(BVPs)for the Laplace and homogeneous biharmonic equations in annuli.By appropriately choosing the collocation points,the LMFS discretization yields sparse block circulant system matrices.As a result,matrix decomposition algorithms(MDAs)and fast Fourier transforms(FFTs)can be used for the solution of the systems resulting in considerable savings in both computational time and storage requirements.The accuracy of the method and its ability to solve large scale problems are demonstrated by applying it to several numerical experiments.

Nonlinear Equations Solving with Intelligent Optimization Algorithms: A Survey

Nonlinear Equations(NEs),which may usually have multiple roots,are ubiquitous in diverse fields.One of the main purposes of solving NEs is to locate as many roots as possible simultaneously in a single run,however,it is a difficult and challenging task in numerical computation.In recent years,Intelligent Optimization Algorithms(IOAs)have shown to be particularly effective in solving NEs.This paper provides a comprehensive survey on IOAs that have been exploited to locate multiple roots of NEs.This paper first revisits the fundamental definition of NEs and reviews the most recent development of the transformation techniques.Then,solving NEs with IOAs is reviewed,followed by the benchmark functions and the performance comparison of several state-of-the-art algorithms.Finally,this paper points out the challenges and some possible open issues for solving NEs.

基于智能优化深度网络的档案数据分析方法

为提高档案管理的效率和准确性,提出了一种基于智能优化深度网络的档案数据分析方法。该方法结合了Transformer网络的特征提取能力和灰狼优化算法(Grey Wolf Optimizer,GWO)的参数优化能力,显著提高了档案管理的效率和准确性。将提出的方法运用到档案数据的多分类任务中,实验结果表明,通过GWO算法优化后的Transformer-GWO模型在与xgboost分类模型结合时取得了最佳性能,其宏观精确度、宏观召回率和宏观F1分数分别达到0.893、0.878以及0.885,提出的方法有效提升了档案管理的智能化水平。

Local RBF Algorithms for Elliptic Boundary Value Problems in Annular Domains

A local radial basis function method(LRBF)is applied for the solution of boundary value problems in annular domains governed by the Poisson equation,the inhomogeneous biharmonic equation and the inhomogeneous Cauchy-Navier equations of elasticity.By appropriately choosing the collocation points we obtain linear systems in which the coefficient matrices possess block sparse circulant structures and which can be solved efficiently using matrix decomposition algorithms(MDAs)and fast Fourier transforms(FFTs).The MDAs used are appropriately modified to take into account the sparsity of the arrays involved in the discretization.The leave-one-out cross validation(LOOCV)algorithm is employed to obtain a suitable value for the shape parameter in the radial basis functions(RBFs)used.The selection of the nearest centres for each local influence domain is carried out using a modification of the kdtree algorithm.In several numerical experiments,it is demonstrated that the proposed algorithm is both accurate and capable of solving large scale problems.

平面近场测量中一种极化探头补偿算法研究

为研究天线特性,该研究采用近场测量技术计算天线的远场方向图,该技术具有成本低、速度快的优势。考虑到平面近场测量中探头参数对远场方向图的影响,该研究基于平面近远场变换算法,引入探头补偿技术和极化补偿技术。利用HFSS仿真得到待测天线远场仿真方向图,通过计算机算法构建,将近远场变换算法所得方向图与实际测得的远场方向图进行比较,验证算法的准确性。进一步结合极化补偿算法与探头补偿算法,与未修正的结果及远场方向图进行对比。结果显示,极化探头补偿算法能有效修正探头对远场方向图的影响,其不确定度超过近远场变换算法1.4295 dB,超过极化补偿算法0.9062 dB,确保了研究的客观性和独立性。

Graphical representations and worm algorithms for the O(N) spin model

We present a family of graphical representations for the O(N)spin model,where N≥1 represents the spin dimension,and N=1,2,3 corresponds to the Ising,XY and Heisenberg models,respectively.With an integer parameter 0≤ℓ≤N/2,each configuration is the coupling of ℓ copies of subgraphs consisting of directed flows and N−2ℓ copies of subgraphs constructed by undirected loops,which we call the XY and Ising subgraphs,respectively.On each lattice site,the XY subgraphs satisfy the Kirchhoff flow-conservation law and the Ising subgraphs obey the Eulerian bond condition.Then,we formulate worm-type algorithms and simulate the O(N)model on the simple-cubic lattice for N from 2 to 6 at all possibleℓ.It is observed that the worm algorithm has much higher efficiency than the Metropolis method,and,for a given N,the efficiency is an increasing function ofℓ.Besides Monte Carlo simulations,we expect that these graphical representations would provide a convenient basis for the study of the O(N)spin model by other state-of-the-art methods like the tensor network renormalization.