34040250
Connected domination critical graphs
Abstract A dominating set in a graph G is a connected dominating set of G if it induces a connected subgraph of G . The minimum number of vertices in a connected dominating set of G is called the connected domination number of G , and is denoted by γ c ( G ). The purpose of this paper is to initiate an investigation of those graphs which are critical in the following sense: for each υ, μ ϵ V (G) with υ not adjacent to u , γ c ( G + υ u ) c ( G ). Thus, G is k -γ c -critical if γ c ( G ) = k and for each edge e ∉ E ( G ), γ c ( G + e ) k . First we discuss whether some particular classes of graphs are γ c -critical. Then 2-γ c -critical graphs are characterized. Finally, the properties of the 3-γ c -critical graphs are studied.
41168099
A note on Roman domination in graphs
Let G=(V,E) be a simple graph. A subset [email protected]?V is a dominating set of G, if for any vertex [email protected]?V-S, there exists a vertex [email protected]?S such that [email protected]?E. The domination number of G, @c(G), equals the minimum cardinality of a dominating set. A Roman dominating function on graph G=(V,E) is a function f:V->{0,1,2} satisfying the condition that every vertex v for which f(v)=0 is adjacent to at least one vertex u for which f(u)=2. The weight of a Roman dominating function is the value f(V)[email protected]?"v"@?"Vf(v). The Roman domination number of a graph G, denoted by @c"R(G), equals the minimum weight of a Roman dominating function on G. In this paper, for any integer k(2=
960732
Computing the Assignment of Orthologous Genes via Genome Rearrangement
The assignment of orthologous genes between a pair of genomes is a fundamental and challenging problem in comparative genomics. Existing methods that assign orthologs based on the similarity between DNA or protein sequences may make erroneous assignments when sequence similarity does not clearly delineate the evolutionary relationship among genes of the same families. In this paper, we present a new approach to ortholog assignment that takes into account both sequence similarity and evolutionary events at genome level, where orthologous genes are assumed to correspond to each other in the most parsimonious evolving scenario under genome rearrangement. It is then formulated as a problem of computing the signed reversal distance with duplicates between two genomes of interest, for which an efcient heuristic algorithm was given by introducing two new optimization problems, minimum common partition and maximum cycle decomposition. Following this approach, we have implemented a high-throughput system for assigning orthologs on a genome scale, called SOAR, and tested it on both simulated data and real genome sequence data. Compared to a recent ortholog assignment method based entirely on homology search (called INPARANOID), SOAR shows a marginally better performance in terms of sensitivity on the real data set because it was able to identify several correct orthologous pairs that were missed by INPARANOID. The simulation results demonstrate that SOAR in general performs better than the iterated exemplar algorithm in terms of computing the reversal distance and assigning correct orthologs.
7672318
Fusion of Infrared and Range Data: Multi-modal Face Images
Infrared and range imagery are intriguing sensing modalities for face recognition systems. They may offer better performance than other modalities due to their robustness to environmental effects and deliberate attempts to obscure identity. Furthermore, a combination of these modalities may offer additional discrimination power. Toward this end, we present a semi-automatic system that captures range and infrared data of a human subject’s face, registers and integrates multiple 3D views into one model, and applies the infrared measurements as a registered texture map.
761547
Finite Element Surface Fitting for Bridge Management
We propose a new finite element surface fitting method which can handle very large databases. This method uses finite element discretization to find an approximation of a smooth function which minimizes a sum of data residuals and second derivatives under some constraints on data. The finite element discretization derives a large scale constrained quadratic program, which can be reformulated as a system of piecewise linear equations. We develop a preconditioned Newton method to solve the system efficiently. We apply this method to form surfaces over Aomori Region in Japan by geographic databases, such that every bridge became associated with environmental information.
8954904
Modification of the AdaBoost-based Detector for Partially Occluded Faces
While face detection seems a solved problem under general conditions, most state-of-the-art systems degrade rapidly when faces are partially occluded by other objects. This paper presents a solution to detect partially occluded faces by reasonably modifying the AdaBoost-based face detector. Our basic idea is that the weak classifiers in the AdaBoost-based face detector, each corresponding to a Haar-like feature, are inherently a patch-based model. Therefore, one can divide the whole face region into multiple patches, and map those weak classifiers to the patches. The weak classifiers belonging to each patch are re-formed to be a new classifier to determine if it is a valid face patch - without occlusion. Finally, we combine all of the valid face patches by assigning the patches with different weights to make the final decision whether the input subwindow is a face. The experimental results show that the proposed method is promising for the detection of occluded faces
3223686
Personalized Knowledge Discovery: Mining Novel Association Rules from Text
This paper presents a methodology for personalized knowledge discovery from text. It derives a user’s background knowledge from his/her background documents, and exploits such knowledge to evaluate the novelty of discovered knowledge in the form of association rules by measuring the semantic distance between the antecedent and the consequent of a rule in the background knowledge. The experiment results show that the proposed user-oriented novelty measure is highly correlated with the human subjective rule novelty and usefulness ratings. It outperforms seven major objective interestingness measures and the WordNet novelty measure for identifying novel and useful rules.