An efficient rendering method for large vector data on large terrain models

This paper presents an efficient way to render large-scale vector maps on level-of-detail(LOD) digital elevation models(DEMs).By using the frame buffer and Voronoi diagram,we achieve a rapid simplification of large-scale vector maps while keeping their original topological relationships.With the simplified maps,we establish level-of-detail vector map models.In the detailed level,we use the stencil shadow volume approach to render the map accurately,and in the coarse level we use substitute techniques to ren...     

An efficient large deformation method using domain decomposition

Efficiently simulating large deformations of flexible objects is a challenging problem in computer graphics. In this paper, we present a physically based approach to this problem, using the linear elasticity model and a finite elements method. To handle large deformations in the linear elasticity model, we exploit the domain decomposition method, based on the observation that each sub-domain undergoes a relatively small local deformation, involving a global rigid transformation. In order to efficiently solve the deformation at each simulation time step, we pre-compute the object responses in terms of displacement accelerations to the forces acting on each node, yielding a force–displacement matrix. However, the force–displacement matrix could be too large to handle for densely tessellated objects. To address this problem, we present two methods. The first method exploits spatial coherence to compress the force-displacement matrix using the clustered principal component analysis method; and the second method pre-computes only the force–displacement vectors for the boundary vertices of the sub-domains and resorts to the Cholesky factorization to solve the acceleration for the internal vertices of the sub-domains. Finally, we present some experimental results to show the large deformation effects and fast performance on complex large scale objects under interactive user manipulations.     

An efficient method for unconstrained optimization problems ofnonlinear large mesh-interconnected systems

Presents an efficient method for solving unconstrained optimization problems for nonlinear large mesh-interconnected systems. This method combines an approximate scaled gradient method with a block Gauss-Seidel with line search method which is used to obtain an approximate solution of the unconstrained quadratic programming subproblem. The authors prove that their method is globally convergent and demonstrate by several numerical examples its superior efficiency compared to a sparse matrix technique based method. In an example of a system of more than 200 variables, the authors observe that their method is 3.45 times faster than the sparse matrix technique based Newton-like method and about 50 times faster than the Newton-like method without the sparse matrix technique     

An efficient method for computing leading eigenvalues and eigenvectors of large asymmetric matrices

An efficient method for computing a given number of leading eigenvalues (i.e., having largest real parts) and the corresponding eigenvectors of a large asymmetric matrixM is presented. The method consists of three main steps. The first is a filtering process in which the equationx = Mx is solved for an arbitrary initial conditionx(0) yielding:x(t)=e ^Mt x(0). The second step is the construction of (n+1) linearly independent vectorsv _m =M ^m x, 0mn orv _m =e ^mMt x ( being a short time interval). By construction, the vectorsv _m are combinations of only a small number of leading eigenvectors ofM. The third step consists of an analysis of the vectors {v _m } that yields the eigenvalues and eigenvectors. The proposed method has been successfully tested on several systems. Here we present results pertaining to the Orr-Sommerfeld equation. The method should be useful for many computations in which present methods are too slow or necessitate excessive memory. In particular, we believe it is well suited for hydrodynamic and mechanical stability investigations.     

An efficient lattice-based phonetic search method for accelerating keyword spotting in large speech databases

This paper describes an algorithm for the reduction of computational complexity in phonetic search KeyWord Spotting (KWS). This reduction is particularly important when searching for keywords within very large speech databases and aiming for rapid response time. The suggested algorithm consists of an anchor-based phoneme search that reduces the search space by generating hypotheses only around phonemes recognized with high reliability. Three databases have been used for the evaluation: IBM Voicemail I and Voicemail II, consisting of long spontaneous utterances and the Wall Street Journal portion of the MACROPHONE database, consisting of read speech utterances. The results indicated a significant reduction of nearly 90 % in the computational complexity of the search while improving the false alarm rate, with only a small decrease in the detection rate in both databases. Search space reduction, as well as, performance gain or loss can be controlled according to the user preferences via the suggested algorithm parameters and thresholds.     

An efficient method for constructing an ILU preconditioner for solving large sparse nonsymmetric linear systems by the GMRES method

The main idea of this paper is in determination of the pattern of nonzero elements of the LU factors of a given matrix A. The idea is based on taking the powers of the Boolean matrix derived from A. This powers of a Boolean matrix strategy (PBS) is an efficient, effective, and inexpensive approach. Construction of an ILU preconditioner using PBS is described and used in solving large nonsymmetric sparse linear systems. Effectiveness of the proposed ILU preconditioner in solving large nonsymmetric sparse linear systems by the GMRES method is also shown. Numerical experiments are performed which show that it is possible to considerably reduce the number of GMRES iterations when the ILU preconditioner constructed here is used. In numerical examples, the influence of k, the dimension of the Krylov subspace, on the performance of the GMRES method using an ILU preconditioner is tested. For all the tests carried out, the best value for k is found to be 10.     

An efficient naturalness-preserving image-recoloring method for dichromats

We present an efficient and automatic image-recoloring technique for dichromats that highlights important visual details that would otherwise be unnoticed by these individuals. While previous techniques approach this problem by potentially changing all colors of the original image, causing their results to look unnatural to color vision deficients, our approach preserves, as much as possible, the image's original colors. Our approach is about three orders of magnitude faster than previous ones. The results of a paired-comparison evaluation carried out with fourteen color-vision deficients (CVDs) indicated the preference of our technique over the state-of-the-art automatic recoloring technique for dichromats. When considering information visualization examples, the subjects tend to prefer our results over the original images. An extension of our technique that exaggerates color contrast tends to be preferred when CVDs compared pairs of scientific visualization images. These results provide valuable information for guiding the design of visualizations for color-vision deficients.     

Discovering target groups in social networking sites: An effective method for maximizing joint influential power

With the tremendous popularity of social networking sites in this era of Web 2.0, increasingly more users are contributing their comments and opinions about products, people, organizations, and many other entities. These online comments often have direct influence on consumers’ buying decisions and the public’s impressions of enterprises. As a result, enterprises have begun to explore the feasibility of using social networking sites as platforms to conduct targeted marking and enterprise reputation management for e-commerce and e-business. As indicated from recent marketing research, the joint influential power of a small group of active users could have considerable impact on a large number of consumers’ buying decisions and the public’s perception of the capabilities of enterprises. This paper illustrates a novel method that can effectively discover the most influential users from social networking sites (SNS). In particular, the general method of mining the influence network from SNS and the computational models of mathematical programming for discovering the user groups with max joint influential power are proposed. The empirical evaluation with real data extracted from social networking sites shows that the proposed method can effectively identify the most influential groups when compared to the benchmark methods. This study opens the door to effectively conducting targeted marketing and enterprise reputation management on social networking sites.     

A communication–computation efficient group key algorithm for large and dynamic groups

The management of secure communication among groups of participants requires a set of secure and efficient operations. In this paper we extend existing work to present a Communication–Computation Efficient Group Key Algorithm (CCEGK) designed to provide both efficient communication and computation, addressing performance, security and authentication issues of CCEGK. Additionally, we compare CCEGK with three other leading group key algorithms, EGK, TGDH, and STR. An analytical comparison of all algorithms revealed eight similar methods: add, remove, merge, split, mass add, mass remove, initialize, and key refresh. Comparing the cost in terms of communication and computation, we found CCEGK to be more efficient across the board.     

An efficient exact algorithm for triangle listing in large graphs

This paper presents a new efficient exact algorithm for listing triangles in a large graph. While the problem of listing triangles in a graph has been considered before, dealing with large graphs continues to be a challenge. Although previous research has attempted to tackle the challenge, this is the first contribution that addresses this problem on a compressed copy of the input graph. In fact, the proposed solution lists the triangles without decompressing the graph. This yields interesting improvements in both storage requirement of the graphs and their time processing.     

An efficient scheme for simulating large,passive microstrip layouts

An efficient algorithm is presented here for simulating large, passive, microstrip layouts using a circle of influence approach with a full-wave/integral-equation-based numerical solver. The procedure involves dividing the circuit into standard subcomponents or blocks and assigning a circle of influence for each block. Reiving on physical intuition, the computation of the couplings between blocks is then limited to those that fall within the circle. By adjusting the circle size, different orders of parasitic coupling can be included in the simulation process. Local junction effects from the individual blocks and the parasitic couplings between blocks that are in close physical proximity can always be taken into account. Aided by a newly developed graphical user interface, the tradeoff between computational efficiency and accuracy is examined by varying the diameter of the circle of influence. Data are presented to illustrate the effectiveness of this new approach. © 1992 John Wiley & Sons, Inc.     

An efficient spatial anti-aliasing method for deferred shading

In recent years, image-based anti-aliasing techniques have been widely investigated in real-time computer graphics. Compared to traditional routine of anti-aliasing, image-based methods, which combined with deferred shading, can efficiently decouple anti-aliasing step from standard graphics pipeline. However, most of the existing image-based methods consume video memory, bandwidth and computation resources heavily. In this paper, we propose an optimized anti-aliasing method, which can efficiently reduce the multi-sampling rate by a multi-sampling mask. We carefully designed the rendering system to avoid serial execution on branch divergence, by utilizing both modern GPU's features and latest shader model. Experimental results demonstrate that our method can achieve high-quality synthesized image with real-time performance.     

An efficient iterated method for mathematical biology model

The purpose of this study is to introduce an efficient iterated homotopy perturbation transform method (IHPTM) for solving a mathematical model of HIV infection of CD4+ T cells. The equations are Laplace transformed, and the nonlinear terms are represented by He’s polynomials. The solutions are obtained in the form of rapidly convergent series with elegantly computable terms. This approach, in contrast to classical perturbation techniques, is valid even for systems without any small/large parameters and therefore can be applied more widely than traditional perturbation techniques, especially when there do not exist any small/large quantities. A good agreement of the novel method solution with the existing solutions is presented graphically and in tabulated forms to study the efficiency and accuracy of IHPTM. This study demonstrates the general validity and the great potential of the IHPTM for solving strongly nonlinear problems.     

An efficient search method for job-shop scheduling problems

We present an efficient search method for job-shop scheduling problems. Our technique is based on an innovative way of relaxing and subsequently reimposing the capacity constraints on some critical operations. We integrate this technique into a fast tabu search algorithm. Our computational results on benchmark problems show that this approach is very effective. Upper bounds for 11 well-known test problems are thus improved. Through the work presented We hope to move a step closer to the ultimate vision of an automated system for generating optimal or near-optimal production schedules. The peripheral conditions for such a system are ripe with the increasingly widespread adoption of enterprise information systems and plant floor tracking systems based on bar code or wireless technologies. One of the remaining obstacles, however, is the fact that scheduling problems arising from many production environments, including job-shops, are extremely difficult to solve. Motivated by recent success of local search methods in solving the job-shop scheduling problem, we propose a new diversification technique based on relaxing and subsequently reimposing the capacity constraints on some critical operations. We integrate this technique into a fast tabu search algorithm and are able to demonstrate its effectiveness through extensive computational experiments. In future research, we will consider other diversification techniques that are not restricted to critical operations.     

An efficient raster evaluation method for univariate polynomials

An evaluation algorithm for univariate polynomials is presented which yields the function values for a sequence of equidistant points. The method is based on a formula which relates the forward differences with step size λh (λ a positive integer) to forward differences with step sizeh. The new method needs about half as many essential operations as Horner's applied to each point separately. It is also compared with a third method from literature which is faster yet less accurate.     

An efficient continuation method for quadratic assignment problems

In this article, we propose a Lagrangian smoothing algorithm for quadratic assignment problems, where the continuation subproblems are solved by the truncated Frank–Wolfe algorithm. We establish practical stopping criteria and show the algorithm finitely terminates at a KKT point of a continuation subproblem. The quality of the returned solution is studied in detail. Finally, limited numerical results are provided.     

An efficient signature computation method

A signature generation algorithm for linear-feedback shift register (LFSR)-based compactors used in fault simulation of built-in self-test digital circuits is presented. The algorithm uses small- to medium-size lookup tables to generate signatures for internal as well as external exclusive-OR LFSRs of any length. The basic concept can be extended to general linear compactors. Algorithms that convert signatures from one form of LFSR to the other are also presented     

An efficient method for maintaining data cubes incrementally

The data cube operator computes group-bys for all possible combinations of a set of dimension attributes. Since computing a data cube typically incurs a considerable cost, the data cube is often precomputed and stored as materialized views in data warehouses. A materialized data cube needs to be updated when the source relations are changed. The incremental maintenance of a data cube is to compute and propagate only its changes, rather than recompute the entire data cube from scratch. For n dimension attributes, the data cube consists of 2ⁿ group-bys, each of which is called a cuboid. To incrementally maintain a data cube with 2ⁿ cuboids, the conventional methods compute 2ⁿdelta cuboids, each of which represents the change of a cuboid. In this paper, we propose an efficient incremental maintenance method that can maintain a data cube using only a subset of 2ⁿ delta cuboids. We formulate an optimization problem to find the optimal subset of 2ⁿ delta cuboids that minimizes the total maintenance cost, and propose a heuristic solution that allows us to maintain a data cube using only delta cuboids. As a result, the cost of maintaining a data cube is substantially reduced. Through various experiments, we show the performance advantages of the proposed method over the conventional methods. We also extend the proposed method to handle partially materialized cubes and dimension hierarchies.     

An efficient method for computing dynamic program slices

We propose an efficient method for computing dynamic slices of programs. Our method is based on construction of data dependence edges of program dependence graph at run-time. We introduce the concept of compact dynamic dependence graphs (CDDGs) of programs. We show computation of dynamic slices using CDDGs to be more efficient than existing methods.