205875547
The hamiltonicity of bipartite graphs involving neighborhood unions
Let G = (X,Y) be a 2-connected balanced bipartite graph with |X| = |Y| = n. In this paper, we prove that if |N(x1) ∪ N(x2)| + |N(y1) ∪ N(y2)| ≥ n+2 for any {x1, x2} ⊆ X and {y1, y2} ⊆ Y, then G is hamiltonian except when G is a special graph on 8 or on 12 vertices.
3788531
Degree-Light-Free Graphs and Hamiltonian Cycles
Abstract. Let G and H be graphs. G is said to be degree-light H-free if G is either H-free or, for every induced subgraph K of G with K≅H, and every {u,v}⊆K, distK(u,v)=2 implies max {d(u),d(v)}≥|V(G)|/2. In this paper, we will show that every 2-connected graph with either degree-light {K1,3, P6}-free or degree-light {K1,3, Z}-free is hamiltonian (with three exceptional graphs), where P6 is a path of order 6 and Z is obtained from P6 by adding an edge between the first and the third vertex of P6 (see Figure 1).
29730920
Translating update operations from relational to object-oriented databases
Abstract In migrating a legacy relational database system to the object-oriented (OO) platform, when database migration completes, application modules are to be migrated, where embedded relational database operations are mapped into their OO correspondents. In this paper we study mapping relational update operations to their OO equivalents, which include UPDATE 1 , INSERT and DELETE operations. Relational update operation translation from relational to OO faces the touchy problem of transformation from a value-based relationship model to a reference-based model and maintaining the relational integrity constraints. Moreover, with a relational database where inheritance is expressed as attribute value subset relationship, changing of some attribute values may lead to the change of the position of an object in the class inheritance hierarchy, which we call object migration. Considering all these aspects, algorithms are given mapping relational UPDATE, INSERT and DELETE operations to their OO correspondents. Our work emphasize in examining the differences in the representation of the source schema's semantics resulting from the translation process, as well as differences in the inherent semantics of the two models.
15047459
Disjoint Triangles of a Cubic Line Graph
Abstract.In this paper, we prove that a cubic line graph G on n vertices rather than the complete graph K4 has vertex-disjoint triangles and the vertex independence number . Moreover, the equitable chromatic number, acyclic chromatic number and bipartite density of G are respectively.
9689230
Doubly stochastic matrices of trees
Abstract In this paper, we obtain sharp upper and lower bounds for the smallest entries of doubly stochastic matrices of trees and characterize all extreme graphs which attain the bounds. We also present a counterexample to Merris’ conjecture on relations between the smallest entry of the doubly stochastic matrix and the algebraic connectivity of a graph in [R. Merris, Doubly stochastic graph matrices II, Linear Multilinear Algebr. 45 (1998) 275–285].
17218997
Profiling program behavior for anomaly intrusion detection based on the transition and frequency property of computer audit data
Intrusion detection is an important technique in the defense-in-depth network security framework. In recent years, it has been a widely studied topic in computer network security. In this paper, we present two methods, namely, the Hidden Markov Models (HMM) method and the Self Organizing Maps (SOM) method, to profile normal program behavior for anomaly intrusion detection based on computer audit data. The HMM method utilizes the transition property of events while SOM method relies on the frequency property of events. Two data sets, CERT synthetic Sendmail system call data collected in the University of New Mexico (UNM) and Live FTP system call data collected in the CNSIS lab of Xi'an Jiaotong University, were used to assess the two methods. Testing results show that the HMM method using the transition property of events produces good detection performance while high computational expense is required both for training and detection. The HMM method is better than other two methods reported previously in terms of detection accuracy for the same data set. The SOM method considering the frequency property of events, on the other hand, is suitable for real-time intrusion detection because of its capability of processing a large amount of data with low computational overhead.
17630030
Prediction of Protein Complexes Based on Protein Interaction Data and Functional Annotation Data Using Kernel Methods
Prediction of protein complexes is a crucial problem in computational biology. The increasing amount of available genomic data can enhance the identification of protein complexes. Here we describe an approach for predicting protein complexes based on integration of protein-protein interaction (PPI) data and protein functional annotation data. The basic idea is that proteins in protein complexes often interact with each other and protein complexes exhibit high functional consistency/even multiple functional consistency. We create a protein-protein relationship network (PPRN) via a kernel-based integration of these two genomic data. Then we apply the MCODE algorithm on PPRN to detect network clusters as numerically determined protein complexes. We present the results of the approach to yeast Sacchromyces cerevisiae. Comparison with well-known experimentally derived complexes and results of other methods verifies the effectiveness of our approach.