13477825
A HYBRID GENETIC ALGORITHM FOR OPTICAL ORTHOGONAL CODE CONSTRUCTION
Optical orthogonal codes (OOCs) are used to uniquely identify stations within an optical code division multiple access (CDMA) local area network (LAN). Previous efforts in constructing OOCs have focused on the use of deterministic techniques, which relied heavily on the use of Galois fields. These techniques severely restrict the availability of the resulting OOCs. This paper considers an evolutionary approach by proposing a hybrid genetic algorithm (hGA) as a flexible technique to construct OOCs. This hGA uses the simulated annealing (SA) method to generate its initial population. The effectiveness of the proposed hGA for OOC construction is demonstrated in two stages. First, we show that the SA-generated initial population is better than the randomly generated initial population in terms of fitness. Due to this, the hGA is able to converge on average two times faster compared to the use of the GA-only scheme. Second, we compare the code availability and performance of the hGA-constructed OOCs (hGA OOCs) against that of three other OOCs. Through these comparisons, we show why the proposed hGA is a more flexible technique for constructing OOCs with higher availability and better performance.
30879352
An Ant Colony Optimization Approach to the Degree-Constrained Minimum Spanning Tree Problem
This paper presents the application of an Ant Colony Optimization (ACO) algorithm approach for communications networks design problem. We explore the use of ACO’s for solving a network optimization problem, the degree-constrained minimum spanning tree problem (d-MST), which is a NP-Hard problem. The effectiveness of the proposed algorithm is demonstrated through two kinds of data set: structured hard (SHRD) complete graphs and misleading (M-graph) complete graphs. Empirical results show that ACO performs competitively with other approaches based on evolutionary algorithm (EA) on certain instance set problem.
3127403
An efficient parallel strategy for computing K-terminal reliability and finding most vital edge in 2-trees and partial 2-trees
The authors develop a parallel strategy to compute K-terminal reliability in 2-trees and partial 2-trees. They also solve the problem of finding the most vital edge with respect to K-terminal reliability in partial 2-trees. The algorithms take O(log n) time with C(m,n) processors on a CRCW PRAM, where C(m,n) is the number of processors required to find connected components of a graph with m edges and n vertices in logarithmic time.
12331697
The Clio project: managing heterogeneity
Clio is a system for managing and facilitating the complex tasks of heterogeneous data transformation and integration. In Clio, we have collected together a powerful set of data management techniques that have proven invaluable in tackling these difficult problems. In this paper, we present the underlying themes of our approach and present a brief case study.
1980858
Edge and Node Searching Problems on Trees
In this paper, we show that there is a natural correspondence between a tree's edge-search strategy and its node-search strategy. By doing so, we simplify the previous linear time algorithm for determining the edge-search number of a tree, and improve the running time of a previous algorithm for constructing an edge-search strategy (or plan) for a tree containing n vertices from O(n log n) to O(n) time.
5342850
A Parallel Algorithm for Solving Sparse Triangular Systems
A fast parallel algorithm, which is generalized from the parallel algorithms for solving banded linear systems, is proposed to solve sparse triangular systems. The original problem is transformed into a directed graph. The solving procedure then consists of eliminating edges in this graph. The worst-case time-complexity of this parallel algorithm is O(log/sup 2/n) where n is the size of the coefficient matrix. When the coefficient matrix is a triangular banded matrix with bandwidth m, then the time-complexity of the algorithm is O(log(m)*log(n)). >
40059378
Wavelet-Based Off-Line Handwritten Signature Verification
In this paper, a wavelet-based off-line handwritten signature verification system is proposed. The proposed system can automatically identify useful and common features which consistently exist within different signatures of the same person and, based on these features, verify whether a signature is a forgery or not. The system starts with a closed-contour tracing algorithm. The curvature data of the traced closed contours are decomposed into multiresolutional signals using wavelet transforms. Then the zero-crossings corresponding to the curvature data are extracted as features for matching. Moreover, a statistical measurement is devised to decide systematically which closed contours and their associated frequency data of a writer are most stable and discriminating. Based on these data, the optimal threshold value which controls the accuracy of the feature extraction process is calculated. The proposed approach can be applied to both on-line and off-line signature verification systems. Experimental results show that the average success rates for English signatures and Chinese signatures are 92.57% and 93.68%, respectively.