Efficient processing of shortest path queries in evolving graph sequences

In many applications, information is best represented as graphs. In a dynamic world, information changes and so the graphs representing the information evolve with time. We propose that historical graph-structured data be maintained for analytical processing. We call a historical evolving graph sequence an EGS. We observe that in many applications, graphs of an EGS are large and numerous, and they often exhibit much redundancy among them. We study the problem of efficient shortest path query processing on an EGS and put forward a solution framework called FVF. Two algorithms, namely, FVF-F and FVF-H, are proposed. While the FVF-F algorithm works on a sequence of flat graph clusters, the FVF-H algorithm works on a hierarchy of such clusters. Through extensive experiments on both real and synthetic datasets, we show that our FVF framework is highly efficient in shortest query processing on EGSs. Comparing FVF-F and FVF-H, the latter gives a larger speedup, is more flexible in terms of memory requirements, and is far less sensitive to parameter values.     

Efficient preconditioning for image reconstruction with radial basis functions

Radial basis functions are a popular basis for interpolating scattered data during the image reconstruction process in graphic analysis. In this context, the solution of a linear system of equations represents the most time-consuming operation. In this paper an efficient preconditioning technique is proposed to solve these linear systems of equations. This algorithm consists of an iterative method which enforces at each iteration a projection of the residual onto a suitable subspace called coarse space. This constraint is ensured by solving an auxiliary problem at each iteration without regularisation. As increasing the number of the coarse space basis functions increases the computational cost of the algorithm, correct selection of coarse space basis is addressed in the paper. Numerical results illustrate the convergence properties of the proposed method with wavelet-like basis functions and regular distributed radial basis functions for image reconstruction.     

Efficient computation of Morse-Smale complexes for three-dimensional scalar functions

The Morse-Smale complex is an efficient representation of the gradient behavior of a scalar function, and critical points paired by the complex identify topological features and their importance. We present an algorithm that constructs the Morse-Smale complex in a series of sweeps through the data, identifying various components of the complex in a consistent manner. All components of the complex, both geometric and topological, are computed, providing a complete decomposition of the domain. Efficiency is maintained by representing the geometry of the complex in terms of point sets.     

A comprehensive evaluation of the methods for evolving a cooperative team

This article focuses on the techniques of evolutionary computation for generating players performing tasks cooperatively. However, in using evolutionary computation for generating players performing tasks cooperatively, one faces fundamental and difficult decisions, including the one regarding the so-called credit assignment problem. We believe that there are some correlations among design decisions, and therefore a comprehensive evaluation of them is essential. We first list three fundamental decisions and possible options in each decision in designing methods for evolving a cooperative team. We find that there are 18 typical combinations available. Then we describe the ultimately simplified soccer game played on a one-dimensional field as a testbed for a comprehensive evaluation for these 18 candidate methods. It has been shown that some methods perform well, while there are complex correlations among design decisions. Also, further analysis has shown that cooperative behavior can be evolved, and is a necessary requirement for the teams to perform well even in such a simple game. This work was presented in part at the 10th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2005     

Genetic evolving ant direction HDE for OPF with non-smooth cost functions and statistical analysis

This paper proposes an evolving ant direction hybrid differential evolution (EADHDE) algorithm for solving the optimal power flow problem with non-smooth and non-convex generator fuel cost characteristics. The EADHDE employs ant colony search to find a suitable mutation operator for hybrid differential evolution (HDE) where as the ant colony parameters are evolved using genetic algorithm approach. The Newton–Raphson method solves the power flow problem. The feasibility of the proposed approach was tested on IEEE 30-bus system with three different cost characteristics. Several cases were investigated to test and validate the robustness of the proposed method in finding optimal solution. Simulation results demonstrate that the EADHDE provides very remarkable results compared to classical HDE and other methods reported in the literature recently. An innovative statistical analysis based on central tendency measures and dispersion measures was carried out on the bus voltage profiles and voltage stability indices.     

Efficient data partitioning for the GPU computation of moment functions

In our previous work, we have provided tools for an efficient characterization of biomedical images using Legendre and Zernike moments, showing their relevance as biomarkers for classifying image tiles coming from bone tissue regeneration studies (Ujaldón, 2009) [24]. As part of our research quest for efficiency, we developed methods for accelerating those computations on GPUs (Martín-Requena and Ujaldón, 2011)  and . This new stage of our work focuses on the efficient data partitioning to optimize the execution on many-cores and clusters of GPUs to attain gains up to three orders of magnitude when compared to the execution on multi-core CPUs of similar age and cost using 1 Mpixel images. We deploy a successive and successful chain of optimizations which exploit symmetries in trigonometric functions and access patterns to image pixels which are effectively combined with massive data parallelism on GPUs to enable (1) real-time processing for our set of input biomedical images, and (2) the use of high-resolution images in clinical practice.     

Expert-driven genetic algorithms for simulating evaluation functions

In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an appropriate expert (or mentor), we can evolve a program that is on par with top tournament-playing chess programs, outperforming a two-time World Computer Chess Champion. This performance gain is achieved by evolving a program that mimics the behavior of a superior expert. The resulting evaluation function of the evolved program consists of a much smaller number of parameters than the expert’s. The extended experimental results provided in this paper include a report on our successful participation in the 2008 World Computer Chess Championship. In principle, our expert-driven approach could be used in a wide range of problems for which appropriate experts are available.     

Efficient evaluation of splines

An algorithm is presented to compute the Taylor expansion of a polynomial B-spline function from its de Boor points. It is shown to be more efficient than existing methods and has the additional advantage of being reversible.     

有效的安卓应用软件可信性评估方法

为保障安卓应用环境中智能终端用户的信息安全,利用支持向量机(support vector machine,SVM),结合证据理论,提出一种面向安卓应用软件的可信性评估方法.该方法分为训练阶段和评估阶段实现,在前阶段,对应用软件样本的属性进行度量,即形成属性证据;利用属性证据对各关联SVM进行训练以确定分类模型.在后阶段...     

Efficient traffic loss evaluation for transport backbone networks

The resilience and survivability of transport backbone networks are vital for the economy and security. Modern backbone networks use a mesh of fiber optic cables, which are, due to their ubiquitous deployment, prone to failures. The goal of this paper is to develop efficient computational methods for assessing the expected traffic loss in such networks. We present both analytical and simulation approaches for this problem. Our analytical approach is based on the cut set enumeration technique, while our simulation approach is based on Monte Carlo sampling techniques. To facilitate the computational process, we employ artificial intelligence methods based on genetic algorithms.     

Efficient evaluation for a subset of recursive queries

We consider the efficient evaluation of recursive queries in logic databases where the queries are expressed using a Datalog program (function-free Horn-clause program) that contains only regularly or linearly recursive predicates. Using well-known results on graph traversal, we develop an efficient algorithm for evaluating relations defined by a binary-chain program. We also present a transformation by which the evaluation of a subset of queries involving nonbinary relations can be reduced to the evaluation of binary-chain queries. This transformation is guided by the choice of bound arguments in the query, and the bindings are propagated through the program so that in the evaluation of the transformed program the bindings will be used to restrict the set of database facts consulted.     

一种面向FPGA的指/对数函数求值算法

CORDIC算法常用于高效地实现多种超越函数求值,但算法的通用性使其无法针对具体函数进行优化。提出一种统一的指数/对数函数迭代求值算法LnE,实现方式与CORDIC算法类似,每次迭代同样只需进行移位、加法和简单的判断操作,拥有线性收敛速度,但LnE算法具备更多优势：只需x、y两条通路;每次迭代均进行加法操作,不需根据迭代系数[di]选择加法/减法,控制简单;不需进行扩展因子补偿;不需重复某些迭代以保证收敛。因此LnE算法的迭代次数和每次迭代的开销均小于CORDIC算法,相对于CORDIC算法可节省1/3以上的面积开销。     

Efficient evaluation of multivariate polynomials

In CAGD applications, the usual way to store a polynomial defined over a triangle is in the Bernstein-Bézier form, and the accepted way to evaluate it at a given point in the triangle is by the de Casteljau algorithm. In this paper we present an algorithm for evaluating Berstein-Bézier type polynomials which is significantly faster than de Casteljau. This suggests that a modified form of Bernstein-Bézier may be preferable for CAGD applications (as well as in applications of piecewise polynomials in data fitting and numerical solution of boundary-value problems).     

投资项目多目标协同经济评价研究

在传统项目经济评价中,评价主体在详细说明和明确规定的环境下进行效益“最大化”投资决策。然而在现实生活中,评价主体的理性是有局限性的,评价维度呈现多元化,且最终的投资选择需要各维度的协同。从有限理性理论视角,引入功效系数,分别计算确定性信息、风险信息和完全不确定信息三个维度有限理性经济评价协同度,并建立了对互斥型以及独立型投资项目组合经济评价协调度模型;最后应用微粒群算法,以独立项目组合经济评价为例,介绍了有限理性项目多目标协同模型的求解,对传统项目经济评价理论作了有意义的探索和改进。     

Optimal sequential arrangement of evaluation trees for boolean functions

Let F be a disjunction of boolean functions of pairwise disjoint variables. Suppose an evaluation tree is given for each such function. We consider the problem of finding an optimal sequential order of scanning the trees for evaluation of F. A necessary and sufficient condition is given.A more general arrangement—a tree—structured arrangement of the trees is considered. It is shown to give no improvement.     

An algorithm for direct evaluation of network transfer functions

A method is proposed for computing the network transfer functions by direct evaluation of the determinant and the appropriate cofactors of the node-admittance matrix of the network using rules governed by topological formulae but without actually generating trees of the corresponding graph. This method suggests a quick analysis (and eventually design) of networks avoiding any matrix analysis or matrix inversion techniques, as in usual practice.     

LoI: Efficient relevance evaluation and filtering for distributed simulation

In large-scale distributed simulation, thousands of objects keep moving and interacting in a virtual environment, which produces a mass of messages. High level architecture (HLA) is the prevailing standard for modeling and simulation. It specifies two publish-subscribe mechanisms for message filtering: class-based and value-based. However, the two mechanisms can only judge whether a message is relevant to a subscriber or not. Lacking of the ability to evaluate the relevance, all relevant messages are delivered with the same priority even when congestion occurs. It significantly limits the scalability and performance of distributed simulation. Aiming to solve the relevance evaluation problem, speed up message filtering, and filter more unnecessary messages, a new relevance evaluation mechanism Layer of Interest (LoI) was proposed by this paper. LoI defines a relevance classifier based on the impact of spatial distance on receiving attributes and attribute values. An adaptive publish-subscribe scheme was built on the basis of LoI. This scheme can abandon most irrelevant messages directly. Run-time infrastructure (RTI) can also apply congestion control by reducing the frequency of sending or receiving object messages based on each objects’ LoI. The experiment results verify the efficiency of message filtering and RTI congestion control. Supported by the National Basic Research Program of China (Grant No. 2009CB320805), the National Natural Science Foundation of China (Grant No. 60603084), and the National High-Tech Research & Development Program of China (Grant No. 2006AA01Z331)