Accelerated Manhattan hashing via bit-remapping with location information

Multimedia Tools and Applications - Hashing is a binary-code encoding method which tries to preserve the neighborhood structures in the original feature space, in order to realize efficient...     

Visual topic discovering,tracking and summarization from social media streams

Multimedia Tools and Applications - Nowadays, microblogging has become popular, with hundreds of millions of short messages being posted and shared every minute on a variety of topics in social...     

High-fidelity lossless data hiding based on predictors selection

Multimedia Tools and Applications - Reversible data hiding based on prediction methods is a data hiding technique wherein secret bits can be efficiently hidden into cover images. In this paper, we...     

Highly non-rigid video object tracking using segment-based object candidates

Multimedia Tools and Applications - A novel scheme for non-rigid video object tracking using segment-based object candidates is proposed in this paper. Rather than using a conventional bounding...     

Efficient simplex computation for fixture layout design

Fixture, to hold an object by making multiple contacts, is a fundamental tool in manufacturing. A fixture layout is an arrangement of contacts on an object’s surface. Designing a fixture layout of an object can be reduced to computing the largest simplex and the resulting simplex is classified using the radius of the largest inscribed ball centered at the origin. We present three different algorithms to compute such a simplex: a simple randomized algorithm, an interchange algorithm, and a branch-and-bound algorithm. We also present methods to combine different algorithms to improve the performance and highlight their performance on complex 3D models consisting of thousands of triangles. Our randomized algorithm computes a feasible fixture layout in linear time and is well-suited for real-time applications. The interchange algorithm computes an optimal simplex in linear time such that no single vertex can be changed to enlarge the simplex, and it provides a practical method for complex 3D objects. The branch-and-bound algorithm computes the largest simplex by using lower and upper bounds on the radius of the inscribed ball, by which the computation time is reduced by a factor of five in comparison with the brute-force search.     

Group path covering and distance two labeling of graphs

For a positive integer d, an L(d,1)-labeling f of a graph G is an assignment of integers to the vertices of G such that |f(u)−f(v)|?d if uv∈E(G), and |f(u)−f(v)|?1 if u and u are at distance two. The span of an L(d,1)-labeling f of a graph is the absolute difference between the maximum and minimum integers used by f. The L(d,1)-labeling number of G, denoted by λd,1(G), is the minimum span over all L(d,1)-labelings of G. An L^′(d,1)-labeling of a graph G is an L(d,1)-labeling of G which assigns different labels to different vertices. Denote by the L^′(d,1)-labeling number of G. Georges et al. [Discrete Math. 135 (1994) 103-111] established relationship between the L(2,1)-labeling number of a graph G and the path covering number of Gc, the complement of G. In this paper we first generalize the concept of the path covering of a graph to the t-group path covering. Then we establish the relationship between the L^′(d,1)-labeling number of a graph G and the (d−1)-group path covering number of Gc. Using this result, we prove that and for bipartite graphs G can be computed in polynomial time.     

Evolutionary level set method for structural topology optimization

This paper proposes an evolutionary accelerated computational level set algorithm for structure topology optimization. It integrates the merits of evolutionary structure optimization (ESO) and level set method (LSM). Traditional LSM algorithm is largely dependent on the initial guess topology. The proposed method combines the merits of ESO techniques with those of LSM algorithm, while allowing new holes to be automatically generated in low strain energy within the nodal neighboring region during optimization. The validity and robustness of the new algorithm are supported by some widely used benchmark examples in topology optimization. Numerical computations show that optimization convergence is accelerated effectively.     

Sensitivity analysis and optimization of vehicle–bridge systems based on combined PEM–PIM strategy

This paper presents a new optimization method for coupled vehicle–bridge systems subjected to uneven road surface excitation. The vehicle system is simplified as a multiple rigid-body model and the single-span bridge is modeled as a simply supported Bernoulli–Euler beam. The pseudo-excitation method transforms the random surface roughness into the superposition of a series of deterministic pseudo-harmonic excitations, which enables convenient and accurate computation of first and second order sensitivity information. The precise integration method is used to compute the vertical random vibrations for both the vehicle and the bridge. The sensitivities are used to find the optimal solution, with vehicle ride comfort taken as the objective function. Optimization efficiency and computational accuracy are demonstrated numerically.     

Comparison of multiple linear regression and artificial neural network in developing the objective functions of the orthopaedic screws

Optimizing the orthopaedic screws can greatly improve their biomechanical performances. However, a methodical design optimization approach requires a long time to search the best design. Thus, the surrogate objective functions of the orthopaedic screws should be accurately developed. To our knowledge, there is no study to evaluate the strengths and limitations of the surrogate methods in developing the objective functions of the orthopaedic screws. Three-dimensional finite element models for both the tibial locking screws and the spinal pedicle screws were constructed and analyzed. Then, the learning data were prepared according to the arrangement of the Taguchi orthogonal array, and the verification data were selected with use of a randomized selection. Finally, the surrogate objective functions were developed by using either the multiple linear regression or the artificial neural network. The applicability and accuracy of those surrogate methods were evaluated and discussed. The multiple linear regression method could successfully construct the objective function of the tibial locking screws, but it failed to develop the objective function of the spinal pedicle screws. The artificial neural network method showed a greater capacity of prediction in developing the objective functions for the tibial locking screws and the spinal pedicle screws than the multiple linear regression method. The artificial neural network method may be a useful option for developing the objective functions of the orthopaedic screws with a greater structural complexity. The surrogate objective functions of the orthopaedic screws could effectively decrease the time and effort required for the design optimization process.     

LTE上行DFT/IDFT的一种设计实现

根据3GPP协议规定,提出一种适于FPGA实现的解决方案。采用分而治之和WFTA的算式分解,最大限度地减少DFT的运算量;采用块浮点动态截取多余位宽,减少系统面积;运用4个双端口RAM读写,使系统能运行在流水线结构;采用对称结构存储每一级的旋转因子,最大化共享因子。