8097819
Model Management Through Graph Transformation
Model management offers a higher level interface than current techniques for metadata management, and generic operators drastically reduce amount of programming for metadata applications. The interactive nature of generic model management operators inevitably demands an intuitive representation. This paper proposes a visual representation for model management operators based on graph transformation. Graph transformation formalisms, as the theoretic foundation of many visual programming languages, can formally represent model management operators by visual and intuitive expressions. By using graphical representations, users can easily comprehend and manipulate the operators and desired outputs
7869643
Fast parallel algorithms for the unit cost editing distance between trees
We present three algorithms to find the distance. The first algorithm is a simple dynamic programming algorithm based on a postorder traversal whose complexity improves upon the best previously published algorithm due to Tai (T79 in JACM). The second and third algorithms are parallel algorithms based on the application of suffix trees to the comparison problem. The cost of executing these algorithms is a monotonic increasing function of the distance between the two trees. Results Let trees T I and T2 have numbers of levels L i and L 2 respectively. Let k be the actual distance between T 1 and T2. Let N be rain (IT11, IT2 ]). The asymptotic running times (assuming a concurrentread concurrent-write parallel random access machine) are:
52799334
On the Editing Distance Between Undirected Acyclic Graphs
We consider the problem of comparing CUAL graphs (Connected, Undirected, Acyclic graphs with nodes being Labeled). This problem is motivated by the study of information retrieval for bio-chemical and molecular databases. Suppose we define the distance between two CUAL graphs G1 and G2 to be the weighted number of edit operations (insert node, delete node and relabel node) to transform G1 to G2. By reduction from exact cover by 3-sets, one can show that finding the distance between two CUAL graphs is NP-complete. In view of the hardness of the problem, we propose a constrained distance metric, called the degree-2 distance, by requiring that any node to be inserted (deleted) have no more than 2 neighbors. With this metric, we present an efficient algorithm to solve the problem. The algorithm runs in time O(N1N2D2) for general weighting edit operations and in time for integral weighting edit operations, where Ni, i=1, 2, is the number of nodes in Gi, D=min{d1, d2} and di is the maximum degree of Gi.
13281459
Software Defect Fractal Description
5672527
Complementary cycles containing a fixed arc in diregular bipartite tournaments
Abstract Let ( x , y ) be a specified arc in a k -regular bipartite tournament B . We prove that there exists a cycle C of length four through ( x , y ) in B such that B − C is hamiltonian.
29387350
Efficient and robust feature extraction by maximum margin criterion
In pattern recognition, feature extraction techniques are widely employed to reduce the dimensionality of data and to enhance the discriminatory information. Principal component analysis (PCA) and linear discriminant analysis (LDA) are the two most popular linear dimensionality reduction methods. However, PCA is not very effective for the extraction of the most discriminant features, and LDA is not stable due to the small sample size problem . In this paper, we propose some new (linear and nonlinear) feature extractors based on maximum margin criterion (MMC). Geometrically, feature extractors based on MMC maximize the (average) margin between classes after dimensionality reduction. It is shown that MMC can represent class separability better than PCA. As a connection to LDA, we may also derive LDA from MMC by incorporating some constraints. By using some other constraints, we establish a new linear feature extractor that does not suffer from the small sample size problem, which is known to cause serious stability problems for LDA. The kernelized (nonlinear) counterpart of this linear feature extractor is also established in the paper. Our extensive experiments demonstrate that the new feature extractors are effective, stable, and efficient.
13354529
Edge-pancyclicity of coupled graphs
The coupled graph c(G) of a plane graph G is the graph defined on the vertex set V(G)∪F(G) so that two vertices in c(G) are joined by an edge if and only if they are adjacent or incident in G. We prove that the coupled graph of a 2-connected plane graph is edge-pancyclic. However, there exists a 2-edge-connected plane graph G such that c(G) is not Hamiltonian.
6145819
HapBlock: haplotype block partitioning and tag SNP selection software using a set of dynamic programming algorithms
UNLABELLED
Recent studies have revealed that linkage disequilibrium (LD) patterns vary across the human genome with some regions of high LD interspersed with regions of low LD. Such LD patterns make it possible to select a set of single nucleotide polymorphism (SNPs; tag SNPs) for genome-wide association studies. We have developed a suite of computer programs to analyze the block-like LD patterns and to select the corresponding tag SNPs. Compared to other programs for haplotype block partitioning and tag SNP selection, our program has several notable features. First, the dynamic programming algorithms implemented are guaranteed to find the block partition with minimum number of tag SNPs for the given criteria of blocks and tag SNPs. Second, both haplotype data and genotype data from unrelated individuals and/or from general pedigrees can be analyzed. Third, several existing measures/criteria for haplotype block partitioning and tag SNP selection have been implemented in the program. Finally, the programs provide flexibility to include specific SNPs (e.g. non-synonymous SNPs) as tag SNPs.


AVAILABILITY
The HapBlock program and its supplemental documents can be downloaded from the website http://www.cmb.usc.edu/~msms/HapBlock.