39024705
The Linear 2-Arboricity of Planar Graphs
Abstract. Let G be a planar graph with maximum degree Δ and girth g. The linear 2-arboricity la2(G) of G is the least integer k such that G can be partitioned into k edge-disjoint forests, whose component trees are paths of length at most 2. We prove that (1) la2(G)≤⌈(Δ+1)/2⌉+12; (2) la2(G)≤⌈(Δ+1)/2⌉+6 if g≥4; (3) la2(G)≤⌈(Δ+1)/2⌉+2 if g≥5; (4) la2(G)≤⌈(Δ+1)/2⌉+1 if g≥7.
26709203
The Linear 2-Arboricity of Outerplanar Graphs
11186519
Edge-partitions of graphs of nonnegative characteristic and their game coloring numbers
Let G be a graph of nonnegative characteristic and let g(G) and @D(G) be its girth and maximum degree, respectively. We show that G has an edge-partition into a forest and a subgraph H so that (1) @D(H)= =11; (2) @D(H)= =7; (3) @D(H)= =5 or G does not contain 4-cycles and 5-cycles; (4) @D(H)= =11; (2) col"g(G)= =7; (3) col"g(G)= =5 or G contains no 4-cycles and 5-cycles; (4) col"g(G)=<10 if G does not contain 4-cycles.
9810371
The edge-face choosability of plane graphs
A plane graph G is said to be k-edge-face choosable if, for every list L of colors satisfying |L(x)|=k for every edge and face x, there exists a coloring which assigns to each edge and each face a color from its list so that any adjacent or incident elements receive different colors. We prove that every plane graph G with maximum degree Δ(G) is (Δ(G)+3)-edge-face choosable.
1003852
Upper Bounds of Entire Chromatic Number of Plane Graphs
The entire chromatic number χvef (G) of a plane graph G is the least number of colors assigned to the vertices, edges and faces so that every two adjacent or incident pair of them receive different colors. Kronk and Mitchem (1973) conjectured that χvef (G) ≤ 1 + 4 for every plane graph G. In this paper we prove the conjecture for a plane graph G having χ ′(G) = 1 and give a upper bound χvef (G) ≤ 1+ 5 for all plane graphs, where χ ′(G) and 1 are the chromatic index and the maximum degree of G, respectively.
6853966
Total chromatic number of planar graphs with maximum degree ten
16657065
Collaborative Web caching based on proxy affinities
With the exponential growth of hosts and traffic workloads on the Internet, collaborative web caching has been recognized as an efficient solution to alleviate web page server bottlenecks and reduce traffic. However, cache discovery, i.e., locating where a page is cached, is a challenging problem, especially in the fast growing World Wide Web environment, where the number of participating proxies can be very large. In this paper, we propose a new scheme which employs proxy affinities to maintain a dynamic distributed collaborative caching infrastructure. Web pages are partitioned into clusters according to proxy reference patterns. All proxies which frequently access some page(s) in the same web page cluster form an “information group”. When web pages belonging to a web page cluster are deleted from or added into a proxy's cache, only proxies in the associated information group are notified. This scheme can be shown to greatly reduce the number of messages and other overhead on individual proxies while maintaining a high cache hit rate. Finally, we employ trace driven simulation to evaluate our web caching scheme using three web access trace logs to verify that our caching structure can provide significant benefits on real workloads.
10774024
Accurate Classification of Protein Structural Families Using Coherent Subgraph Analysis
Protein structural annotation and classification is an important problem in bioinformatics. We report on the development of an efficient subgraph mining technique and its application to finding characteristic substructural patterns within protein structural families. In our method, protein structures are represented by graphs where the nodes are residues and the edges connect residues found within certain distance from each other. Application of subgraph mining to proteins is challenging for a number reasons: (1) protein graphs are large and complex, (2) current protein databases are large and continue to grow rapidly, and (3) only a small fraction of the frequent subgraphs among the huge pool of all possible subgraphs could be significant in the context of protein classification. To address these challenges, we have developed an information theoretic model called coherent subgraph mining. From information theory, the entropy of a random variable X measures the information content carried by X and the Mutual Information (MI) between two random variables X and Y measures the correlation between X and Y. We define a subgraph X as coherent if it is strongly correlated with every sufficiently large sub-subgraph Y embedded in it. Based on the MI metric, we have designed a search scheme that only reports coherent subgraphs. To determine the significance of coherent protein subgraphs, we have conducted an experimental study in which all coherent subgraphs were identified in several protein structural families annotated in the SCOP database (Murzin et al, 1995). The Support Vector Machine algorithm was used to classify proteins from different families under the binary classification scheme. We find that this approach identifies spatial motifs unique to individual SCOP families and affords excellent discrimination between families.
33629250
Robust Visual Tracking Via Incremental Maximum Margin Criterion
Robust visual object tracking is one of the key problems in computer vision. Subspace based tracking method is a promising approach in handling appearance variability. Linear Discriminant Analysis(LDA) has been applied to this problem, but LDA is not a stable algorithm especially for visual tracking. Maximum Margin Criterion(MMC) is a recently proposed discriminant criterion. Its promising specialities make it a better choice for the tracking problem. In this paper, we present a novel subspace tracking algorithm based on MMC. We also proposed an incremental version of the corresponding algorithm so that the tracker can update in realtime. Experiments show our tracking algorithm is able to track objects well under large lighting, pose and expression variation.
15242556
AFOPT: An Efficient Implementation of Pattern Growth Approach
In this paper, we revisit the frequent itemset mining (FIM) problem and focus on studying the pattern growth approach. Existing pattern growth algorithms differ in several dimensions: (1) item search order; (2) conditional database representation; (3) conditional database construction strategy; and (4) tree traversal strategy. They adopted different strategies on these dimensions. Several adaptive algorithms were proposed to try to find good strategies for general situations. In this paper, we described the implementation techniques of an adaptive pattern growth algorithm, called AFOPT, which demonstrated good performance on all tested datasets. We also extended the algorithm to mine closed and maximal frequent itemsets. Comprehensive experiments were conducted to demonstrate the efficiency of the proposed algorithms.
11609470
Interpolating Polyhedral Models Using Intrinsic Shape Parameters
Metamorphosis, or morphing, is the gradual transformation of one shape into another. It generally consists of two subproblems: the correspondence problem and the interpolation problem. This paper presents a solution to the interpolation problem of transforming one polyhedral model into another. It is an extension of the intrinsic shape interpolation scheme (T. W. Sederberg, P. Gao, G. Wang and H. Mu, ‘2-D shape blending: an intrinsic solution to the vertex path problem, SIGGRAPH ’93, pp. 15–18.) for 2D polygons. Rather than considering a polyhedron as a set of independent points or faces, our solution treats a polyhedron as a graph representing the interrelations between faces. Intrinsic shape parameters, such as dihedral angles and edge lengths that interrelate the vertices and faces in the two graphs, are used for interpolation. This approach produces more satisfactory results than the linear or cubic curve paths would, and is translation and rotation invariant.  1997 by John Wiley & Sons, Ltd.