Results 51 to 60 of about 25,758 (195)
Saliency Detection Method Using Hypergraphs on Adaptive Multiscales
IEEE Access, 2018 Saliency detection plays an important role in the fields of image processing and computer vision. We present an improved saliency detection method by means of hypergraphs on adaptive multi-scales (HAM).
Feilin Han, Aili Han, Jing Hao
doaj +1 more source
Discrete Mathematics, 2012 The aim of this paper is to generalize the notion of the coloring complex of a graph to hypergraphs. We present three different interpretations of those complexes -- a purely combinatorial one and two geometric ones. It is shown, that most of the properties, which are known to be true for coloring complexes of graphs, break down in this more general ...
Breuer, Felix +2 more
openaire +4 more sources
Advanced Intelligent Discovery, EarlyView.This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
Complement Reducible Uniform Hypergraphs
AxiomsWe investigate a generalization of complement reducible graphs, called co-graphs, for r-uniform hypergraphs. The operations of r-co-hypergraphs are the disjoint union of two given r-co-hypergraphs and the join operation, which inserts all hyperedges of ...
Frank Gurski, Jochen Rethmann
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On Tight Tree‐Complete Hypergraph Ramsey Numbers
Journal of Graph Theory, EarlyView.ABSTRACT Chvátal showed that for any tree T $T$ with k $k$ edges, the Ramsey number R ( T , n ) = k ( n − 1 ) + 1 $R(T,n)=k(n-1)+1$. For r = 3 $r=3$ or 4, we show that, if T $T$ is an r $r$‐uniform nontrivial tight tree, then the hypergraph Ramsey number R ( T , n ) = Θ ( n r − 1 ) $R(T,n)={\rm{\Theta }}({n}^{r-1})$.
Jiaxi Nie
wiley +1 more source
Niche Hypergraphs of Products of Digraphs
Discussiones Mathematicae Graph Theory, 2020 If D = (V, A) is a digraph, its niche hypergraph Nℋ(D) = (V, ℰ) has the edge set ℰ={e⊆V||e|≥2∧∃ υ∈V:e=ND−(υ)∨e=ND+(υ)}{\cal E} = \{ {e \subseteq V| | e | \ge 2 \wedge \exists \, \upsilon \in V:e = N_D^ - ( \upsilon ) \vee e = N_D^ + ( \upsilon ...
Sonntag Martin, Teichert Hanns-Martin
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A Dynamic Correlation‐Information‐Fusion‐Based Spatiotemporal Network for Traffic Flow Forecasting
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Traffic Flow Forecasting (TFF) is a foundational task in the development of Intelligent Transport Systems (ITSs). The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal correlations of the road network, unveiling the long‐term evolutionary traffic trends.
Dawen Xia +6 more
wiley +1 more source
, 2011 A support of a hypergraph H is a graph with the same vertex set as H in which each hyperedge induces a connected subgraph. We show how to test in polynomial time whether a given hypergraph has a cactus support, i.e. a support that is a tree of edges and cycles.
Brandes, Ulrik +3 more
openaire +3 more sources
The dynamics of criminal collaboration: Multiplex ties in mafia networks
Criminology, EarlyView.Abstract This study examines how social embeddedness and multiplex relationships shape criminal collaboration within organized crime networks. Drawing on data from three major investigations into the ‘Ndrangheta, we analyze how kinship, clan affiliation, leadership, and prior interactions influence participation in meetings and phone calls.
Francesco Calderoni +2 more
wiley +1 more source
Strong Jumps and Lagrangians of Non-Uniform Hypergraphs [PDF]
, 2014 The hypergraph jump problem and the study of Lagrangians of uniform hypergraphs are two classical areas of study in the extremal graph theory. In this paper, we refine the concept of jumps to strong jumps and consider the analogous problems over non ...
Johnston, Travis, Lu, Linyuan
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