Results 91 to 100 of about 51,114 (288)
Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Graph Spectral Properties of Deterministic Finite Automata
, 2014 We prove that a minimal automaton has a minimal adjacency matrix rank and a minimal adjacency matrix nullity using equitable partition (from graph spectra theory) and Nerode partition (from automata theory). This result naturally introduces the notion of
A. Goldberg +5 more
core +1 more source
Advanced Intelligent Discovery, EarlyView.A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas +4 more
wiley +1 more source
COMPLETELY REACHABLE ALMOST GROUP AUTOMATA
Ural Mathematical JournalWe consider finite deterministic automata such that their alphabets consist of exactly one letter of defect 1 and a set of permutations of the state set. We study under which conditions such an automaton is completely reachable. We focus our attention on
David Fernando Casas Torres
doaj +1 more source
Multipass automata and group word problems
, 2014 We introduce the notion of multipass automata as a generalization of pushdown automata and study the classes of languages accepted by such machines. The class of languages accepted by deterministic multipass automata is exactly the Boolean closure of the
Ceccherini-Silberstein, Tullio +4 more
core +3 more sources
Advanced Intelligent Discovery, EarlyView.This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan +3 more
wiley +1 more source
, 2011 Minimal deterministic finite automata (DFAs) can be reduced further at the expense of a finite number of errors. Recently, such minimization algorithms have been improved to run in time O(n log n), where n is the number of states of the input DFA, by ...
Maletti, Andreas, Quernheim, Daniel
core +2 more sources
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker +2 more
wiley +1 more source
Half-Positional Objectives Recognized by Deterministic B\"uchi Automata [PDF]
Logical Methods in Computer ScienceIn two-player games on graphs, the simplest possible strategies are those that can be implemented without any memory. These are called positional strategies. In this paper, we characterize objectives recognizable by deterministic B\"uchi automata (a
Patricia Bouyer +3 more
doaj +1 more source
Exact and Approximate Determinization of Discounted-Sum Automata [PDF]
Logical Methods in Computer Science, 2014 A discounted-sum automaton (NDA) is a nondeterministic finite automaton with edge weights, valuing a run by the discounted sum of visited edge weights.
Udi Boker, Thomas A. Henzinger
doaj +1 more source