Results 111 to 120 of about 3,095,070 (339)
Arc-Disjoint Hamiltonian Cycles in Round Decomposable Locally Semicomplete Digraphs
Discussiones Mathematicae Graph Theory, 2018 Let D = (V,A) be a digraph; if there is at least one arc between every pair of distinct vertices of D, then D is a semicomplete digraph. A digraph D is locally semicomplete if for every vertex x, the out-neighbours of x induce a semicomplete digraph and ...
Li Ruijuan, Han Tingting
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On pre-Hamiltonian Cycles in Hamiltonian Digraphs
, 2014 Let $D$ be a strongly connected directed graph of order $n\geq 4$. In \cite{[14]} (J. of Graph Theory, Vol.16, No. 5, 51-59, 1992) Y. Manoussakis proved the following theorem: Suppose that $D$ satisfies the following condition for every triple $x,y,z$ of vertices such that $x$ and $y$ are non-adjacent: If there is no arc from $x$ to $z$, then $d(x)+d(y)
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Small cycles in Hamiltonian graphs
Discrete Applied Mathematics, 1997 AbstractWe prove that if a graph G on n ⩾ 32 vertices is hamiltonian and has two nonadjacent vertices u and v with d(u) + d(v) ⩾ n + z where z = 0 if n is odd and z = 1 if n is even, then G contains all cycles of length m where 3 ⩽ m ⩽ 15(n + 13).
Ingo Schiermeyer, Uwe Schelten
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Advanced Energy and Sustainability Research, EarlyView.An aqueous potassium‐ion battery using vanadium hexacyanoferrate (VHCF) as the cathode and graphite as the anode is presented. During charge/discharge, K+ ions shuttle between electrodes through the electrolyte, enabling energy storage. The VHCF material demonstrates high capacity (≈121 mAh g−1), fast kinetics, and eco‐friendliness, making it a ...
Nilasha Maiti +10 more
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Energy Conditions for Hamiltonicity of Graphs
Discrete Dynamics in Nature and Society, 2014 Let G be an undirected simple graph of order n. Let A(G) be the adjacency matrix of G, and let μ1(G)≤μ2(G)≤⋯≤μn(G) be its eigenvalues. The energy of G is defined as ℰ(G)=∑i=1n|μi(G)|. Denote by GBPT a bipartite graph.
Guidong Yu +3 more
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Designing Memristive Materials for Artificial Dynamic Intelligence
Advanced Intelligent Discovery, EarlyView.Key characteristics required of memristors for realizing next‐generation computing, along with modeling approaches employed to analyze their underlying mechanisms. These modeling techniques span from the atomic scale to the array scale and cover temporal scales ranging from picoseconds to microseconds. Hardware architectures inspired by neural networks
Youngmin Kim, Ho Won Jang
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Lower Bound on the Number of Hamiltonian Cycles of Generalized Petersen Graphs
Discussiones Mathematicae Graph Theory, 2020 In this paper, we investigate the number of Hamiltonian cycles of a generalized Petersen graph P (N, k) and prove that Ψ(P(N,3))⩾N⋅αN,\Psi ( {P ( {N,3} )} ) \ge N \cdot {\alpha _N}, where Ψ(P(N, 3)) is the number of Hamiltonian cycles of P(N, 3) and αN ...
Lu Weihua, Yang Chao, Ren Han
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Applied Artificial Intelligence in Materials Science and Material Design
Advanced Intelligent Systems, EarlyView.AI‐driven methods are transforming materials science by accelerating material discovery, design, and analysis, leveraging large datasets to enhance predictive modeling and streamline experimental techniques. This review highlights advancements in AI applications across spectroscopy, microscopy, and molecular design, enabling efficient material ...
Emigdio Chávez‐Angel +7 more
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Solving SAT and Hamiltonian Cycle Problem Using Asynchronous P Systems
IEICE Trans. Inf. Syst., 2012 In the present paper, we consider fully asynchronous parallelism in membrane computing, and propose two asynchronous P systems for the satisfiability (SAT) and Hamiltonian cycle problem.
Hirofumi Tagawa, A. Fujiwara
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Energy‐Efficient Knapsack Optimization Using Probabilistic Memristor Crossbars
Advanced Intelligent Systems, EarlyView.The knapsack problem, a nondeterministic polynomial‐time (NP)‐hard combinatorial optimization problem, is solved energy‐efficiently. This work presents an algorithm‐hardware co‐design and implementation for practical (non‐ideal) NP‐hard problems with destabilizing self‐feedback (non‐zero diagonal) and non‐binary Hamiltonian representations under analog
Jinzhan Li, Suhas Kumar, Su‐in Yi
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