Scheme for Generation of <Emphasis Type="Italic">W</Emphasis> and <Emphasis Type="Italic">W</Emphasis>-like States of Nonidentical Particles and their Application in Teleportation

In this paper, a scheme is proposed for the preparation of the tripartite W state or W-like state of nonidentical particles. In our scheme, our required resources include two atoms and one cavity field, which makes our system become simple. Because each party included by W state has its own two possible states, and is not identical each other, one can easily distinguish them. Furthermore, we teleportate an unknown state of cavity field by using this W state as quantum channels. Our scheme of preparation employing a single high-Q superconducting cavity turns out to be attractive to realize based on present or future cavity QED techniques. Partially supported by Natural Science Foundation of Jiangxi, China, under Grant No. 0612006 and by the Scientific Research Foundation of Jiangxi Provincial Department of Education, China, under Grant No. [2007]191.     

A geometric approach for shared secrets, a refinement

A refinement to the (k,n) threshold scheme proposed by Wu and He [1] is presented. It has been found that usable primes p need not be confined to the form p ≡ ±3 (mod 8) as suggested originally. Our constructive proof also lead to a different algorithm for implementation. This implementation dispenses with the directory file suggested in [1] which can be prohibitively large when the scheme is implemented with large p using the original proposal.     

H ∞ robust control of DC-AC interfaced microsource in microgrids

This paper focuses on the direct current-alternating current (DC-AC) interfaced microsource based H∞ robust control strategies in microgrids. It presents detail of a DC-AC interfaced microsource model which is connected to the power grid through a controllable switch. A double loop current-regulated voltage control scheme for the DC-AC interface is designed. In the case of the load disturbance and the model uncertainties, the inner voltage and current loop are produced based on the H∞ robust control strategies. The outer power loop uses the droop characteristic controller. Finally, the scheme is simulated using the Matlab/Simulink. The simulation results demonstrate that DC-AC interfaced microsource system can supply high quality power. Also, the proposed control scheme can make the system switch smoothly between the isolated mode and grid-connected mode.     

IEEE 802.11支持QoS区分服务的性能优化

基于IEEE 802。11 p-persistent协议模型的研究,对一种近似优化条件在多优先级业务网络条件下的适用性进行了证明。应用该近似优化条件,提出了一种适用于IEEE 802。11 QoS区分服务支持的自适应优化算法QATC (QoS-supporting adaptive transmission control)。算法利用信道侦听信息实时优化调整各优先级业务的发送概率,更新相应的协议参数,实现信道利用率的提高和系统性能的增强。QATC算法不需要估计各优先级业务的节点数量,并且拥有     

A residual-based compact scheme of optimal order for hyperbolic problems

A new fourth-order dissipative scheme on a compact 3 × 3 stencil is presented for solving 2D hyperbolic problems. It belongs to the family of previously developed residual-based compact schemes and can be considered as optimal since it offers the maximum achievable order of accuracy on the 3 × 3-point stencil. The computation of 2D scalar problems demonstrates the excellent accuracy and efficiency properties offered by this new RBC scheme with respect to existing second- and third-order versions.     

An A Posteriori Error Estimate for the Local Discontinuous Galerkin Method

In this work an a posteriori global error estimate for the Local Discontinuous Galerkin (LDG) applied to a linear second order elliptic problem is analyzed. Using a mixed formulation, an upper bound of the error in the primal variable is derived from explicit computations. Finally, a local adaptive scheme based on explicit error estimators is studied numerically using one dimensional problems.This revised version was published online in July 2005 with corrected volume and issue numbers.     

Selecting the Numerical Flux in Discontinuous Galerkin Methods for Diffusion Problems

In this paper we present numerical investigations of four different formulations of the discontinuous Galerkin method for diffusion problems. Our focus is to determine, through numerical experimentation, practical guidelines as to which numerical flux choice should be used when applying discontinuous Galerkin methods to such problems. We examine first an inconsistent and weakly unstable scheme analyzed in Zhang and Shu, Math. Models Meth. Appl. Sci. (M ³ AS) 13, 395–413 (2003), and then proceed to examine three consistent and stable schemes: the Bassi–Rebay scheme (J. Comput. Phys. 131, 267 (1997)), the local discontinuous Galerkin scheme (SIAM J. Numer. Anal. 35, 2440–2463 (1998)) and the Baumann–Oden scheme (Comput. Math. Appl. Mech. Eng. 175, 311–341 (1999)). For an one-dimensional model problem, we examine the stencil width, h-convergence properties, p-convergence properties, eigenspectra and system conditioning when different flux choices are applied. We also examine the ramifications of adding stabilization to these schemes. We conclude by providing the pros and cons of the different flux choices based upon our numerical experiments.This revised version was published online in July 2005 with corrected volume and issue numbers.     

结合调整差值变换的(K,N)有意义图像分存方案

目的 针对传统有意义分存方法存在的像素扩张和分发掩体图像视觉质量不高等问题,提出一种结合调整差值变换的(K,N)有意义图像分存方案,该方案可用于与掩体等大且同为自然图像的密图分存.方法 在分存阶段,首先用调整差值变换将密图转换为差值图和位置图;其次将差值图和位置图进行(K,N)分存,分别嵌入到掩体图像中,并使用密钥确定位置图分存信息的嵌入位置和根据位置图中不同的差值类型选择不同的差值嵌入方法;再次对密钥进行(K,N)分存,将子密钥和分发掩体对应的MD5值公布到第3方公信方作为认证码;最后将子密钥和分发掩体分发给参与者进行保管.在恢复阶段,首先核对参与者的子密钥和分发掩体对应的MD5值,若认证通过的人数小于K,则恢复失败;否则,使用认证通过的子密钥还原出密钥,然后根据密钥提取并恢复出位置图;其次根据位置图中的差值类型来提取和恢复出差值图;最后使用逆调整差值变换还原出最终密图.结果 同现有方法相比,所提策略不存在像素扩张且分发掩体图像视觉质量较高,具有较强的恶意参与者检测能力.结论 本文方法的掩体图像与密图等大且同为自然图像,同经典有意义图像分存方案相比,克服了像素扩张问题,嵌入信息后的掩体图像具有较高的视觉质量,使用第3方公信方存储的MD5值作为认证码,具有较强的恶意参与者识别能力.     

Hierarchical parallel processing of large scale data clustering on a PC cluster with GPU co-processing

This paper presents an effective scheme for clustering a huge data set using a PC cluster system, in which each PC is equipped with a commodity programmable graphics processing unit (GPU). The proposed scheme is devised to achieve three-level hierarchical parallel processing of massive data clustering. The divide-and-conquer approach to parallel data clustering is employed to perform the coarse-grain parallel processing by multiple PCs with a message passing mechanism. By taking advantage of the GPU’s parallel processing capability, moreover, the proposed scheme can exploit two types of the fine-grain data parallelism at the different levels in the nearest neighbor search, which is the most computationally-intensive part of the data-clustering process. The performance of our scheme is discussed in comparison with that of the implementation entirely running on CPU. Experimental results clearly show that the proposed hierarchial parallel processing can remarkably accelerate the data clustering task. Especially, GPU co-processing is quite effective to improve the computational efficiency of parallel data clustering on a PC cluster. Although data-transfer from GPU to CPU is generally costly, acceleration by GPU co-processing is significant to save the total execution time of data-clustering.     

Convergence of the generalized-α scheme for constrained mechanical systems

A variant of the generalized-α scheme is proposed for constrained mechanical systems represented by index-3 DAEs. Based on the analogy with linear multistep methods, an elegant convergence analysis is developed for this algorithm. Second-order convergence is demonstrated both for the generalized coordinates and the Lagrange multipliers, and those theoretical results are illustrated by numerical tests.     

Generalised influential rule search scheme for fuzzy function approximation

The present paper is a humble attempt to develop a fuzzy function approximator which can completely self-generate its fuzzy rule base and input-output membership functions from an input-output data set. The fuzzy system can be further adapted to modify its rule base and output membership functions to provide satisfactory performance. This proposed scheme, called generalised influential rule search scheme, has been successfully implemented to develop pure fuzzy function approximators as well as fuzzy logic controllers. The satisfactory performance of the proposed scheme is amply demonstrated by implementing it to develop different major components in a process control loop. The versatility of the algorithm is further proved by implementing it for a benchmark nonlinear function approximation problem.     

An HLLC Scheme to Solve The <Emphasis Type="Italic">M</Emphasis><Subscript>1</Subscript> Model of Radiative Transfer in Two Space Dimensions

The M ₁ radiative transfer model is considered in the present work in order to simulate the radiative fields and their interactions with the matter. The model is governed by an hyperbolic system of conservation laws supplemented by relaxation source terms. Several difficulties arise when approximating the solutions of the model; namely the positiveness of the energy, the flux limitation and and the limit diffusion behavior have to be satisfied. An HLLC scheme is exhibited and it is shown to satisfy all the required properties. A particular attention is payed concerning the approximate extreme waves. These approximations are crucial to obtain an accurate scheme. The extension to the full 2D problem is proposed. It satisfies, once again, all the expected properties. Numerical experiments are proposed. They show that the considered scheme is actually less diffusive than the currently used numerical methods.      

Evolutionary Optimization of Machining Processes

Optimization of machining processes plays a key role in meeting the demands for high precision and productivity. The primary challenge for machining process optimization often stems from the fact that the procedure is typically highly constrained and highly non-linear, involving mixed-integer-discrete-continuous design variables. Additionally, machining process models are likely discontinuous, non-explicit, or not analytically differentiable with the design variables. Traditional non-linear optimization techniques are mostly gradient-based, posing many limitations upon application to today’s complex machining models. Genetic Algorithms (GAs) has distinguished itself as a method with the potential for solving highly non-linear, ill-behaved complex machining optimization problems. Unlike traditional optimization techniques, GAs start with a population of different designs and use direct search methods stochastically and deterministically toward optimal and feasible direction. However, GAs still has its own drawbacks when it is applied to machining process optimization, including the lack of efficiency due to its binary representation scheme for continuous design variables, a lack of local fine-tuning capabilities, a lack of a self-adaptation mechanism, and a lack of an effective constraint handling method. A novel and systematic evolutionary algorithm based on GAs is presented in this paper in the areas of problem representation; selection scheme; genetic operators for integer, discrete, and continuous variables; constraint handling method; and population initialization to overcome the underlying drawbacks. The proposed scheme has been applied to two machining problems to demonstrate its superior performance.     

Queuing system evolution in a diffusion approximation scheme

An asymptotic diffusion approximation scheme is investigated as applied to the requirement evolution in semi-Markov queuing systems. In proving the diffusion approximation theorem, the compensating operator of the corresponding extended Markov process is used. This problem is solved with the help of a phase merging procedure. Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 136–145, May–June 2009. Original article submitted August 19, 2008.     

On a Rational Linear Approximation of Fourier Series for Smooth Functions

The Fourier series of a smooth function on a compact interval usually has slow convergence due to the Gibbs phenomena. A class of Fourier-Pade approximations is introduced and studied for performing a boundary correction. Additional acceleration is achieved by applying Fourier–Bernoulli scheme.     

Approximation of satisfactory bisection problems

The Satisfactory Bisection problem means to decide whether a given graph has a partition of its vertex set into two parts of the same cardinality such that each vertex has at least as many neighbors in its part as in the other part. A related variant of this problem, called Co-Satisfactory Bisection, requires that each vertex has at most as many neighbors in its part as in the other part. A vertex satisfying the degree constraint above in a partition is called ‘satisfied’ or ‘co-satisfied,’ respectively. After stating the NP-completeness of both problems, we study approximation results in two directions. We prove that maximizing the number of (co-)satisfied vertices in a bisection has no polynomial-time approximation scheme (unless P=NP), whereas constant approximation algorithms can be obtained in polynomial time. Moreover, minimizing the difference of the cardinalities of vertex classes in a bipartition that (co-)satisfies all vertices has no polynomial-time approximation scheme either.     

Classification of weld flaws with imbalanced class data

This paper presents research results of our investigation of the imbalanced data problem in the classification of different types of weld flaws, a multi-class classification problem. The one-against-all scheme is adopted to carry out multi-class classification and three algorithms including minimum distance, nearest neighbors, and fuzzy nearest neighbors are employed as the classifiers. The effectiveness of 22 data preprocessing methods for dealing with imbalanced data is evaluated in terms of eight evaluation criteria to determine whether any method would emerge to dominate the others. The test results indicate that: (1) nearest neighbor classifiers outperform the minimum distance classifier; (2) some data preprocessing methods do not improve any criterion and they vary from one classifier to another; (3) the combination of using the AHC_KM data preprocessing method with the 1-NN classifier is the best because they together produce the best performance in six of eight evaluation criteria; and (4) the most difficult weld flaw type to recognize is crack.     

Noisy Image Decomposition: A New Structure,Texture and Noise Model Based on Local Adaptivity

These last few years, image decomposition algorithms have been proposed to split an image into two parts: the structures and the textures. These algorithms are not adapted to the case of noisy images because the textures are corrupted by noise. In this paper, we propose a new model which decomposes an image into three parts (structures, textures and noise) based on a local regularization scheme. We compare our results with the recent work of Aujol and Chambolle. We finish by giving another model which combines the advantages of the two previous ones.     

面向缺失数据的数据匿名方法

在数据发布过程中,为了防止隐私泄露,需要对数据的准标识符属性进行匿名化,以降低链接攻击风险,实现对数据所有者敏感属性的匿名保护.现有数据匿名方法都建立在数据无缺失的假设基础上,在数据存在缺失的情况下会直接丢弃相关的记录,造成了匿名化前后数据特性不一致.针对缺失数据匿名方法进行研究,基于k-匿名模型提出面向缺失数据的数据匿名方法KAIM(k-anonymity for incomplete mircrodata),在保留包含缺失记录的前提下,使在同一属性上缺失的记录尽量被分配到同一分组参与泛化.该方法将分组泛化前后的信息熵变化作为距离,基于改进的k-member 算法对数据进行聚类分组,最后通过基于泛化层次的局部泛化算法对组内数据进行泛化.实际数据集的大量实验结果表明,KAIM 造成信息缺损仅为现有算法的43.8%,可以最大程度地保障匿名化前后数据特性不变.     

Inverting and noninverting H∞ controllers

It is well known that two-block S/KS/T H_∞ problems in which the plant is weighted at the output tend to invert the plant in the controller. This paper shows that even four-block S/KS/T problems in which the plant is weighted at the input result in controllers which invert the plant. However, if a GS/T weighting scheme is used where the weight for the sensitivity includes the plant, the inversion is avoided. This GS/T scheme therefore is especially suited for ill-conditioned plants. An example confirms these results.