Results 101 to 110 of about 12,115,560 (297)

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

A Fast Single-Key Two-Level Universal Hash Function

IACR Transactions on Symmetric Cryptology, 2017
Universal hash functions based on univariate polynomials are well known, e.g. Poly1305 and GHASH. Using Horner’s rule to evaluate such hash functionsrequire l − 1 field multiplications for hashing a message consisting of l blocks where each block is one ...
Debrup Chakraborty, Sebati Ghosh, Palash Sarkar   +2 more
doaj   +1 more source

Enumeration of Special Sets of Polynomials over Finite Fields [PDF]

, 1999
In this paper we consider squarefree polynomials over finite fields whose gcd with their reciprocal and Frobenius conjugate polynomial is trivial, respectively.
Reifegerste, Astrid
core   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

On the Cycle Structure of Permutation Polynomials of Finite Fields [PDF]

, 2007
Any permutation of a finite field Fq can be represented by a polynomial Pn(x)=(⋯+((a0x+a1)q−2+a2)q−2+⋯+an)q−2+an+1, for some n⩾0. P0 is linear and the cycle structure of P1 is known.
Meidl, Wilfried, Topuzoğlu, Alev, Çeşmelioğlu, Ayça   +2 more
core   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

Polynomials over base 2 finite fields with evenly distributed values [PDF]

, 2005
Few nontrivial results about the value sets of polynomials over finite fields are known. This paper uses results from the theory of crosscorrelation of binary m-sequences to find five kinds of polynomials f(x) defined over finite fields GF(2n) such that ...
Cusick, Thomas W.
core   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

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

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

A circuit area optimization of MK-3 S-box

Cybersecurity
In MILCOM 2015, Kelly et al. proposed the authentication encryption algorithm MK-3, which applied the 16-bit S-box. This paper aims to implement the 16-bit S-box with less circuit area. First, we classified the irreducible polynomials over $$\mathbb {F}_{
Yanjun Li, Weiguo Zhang, Yiping Lin, Jian Zou, Jian Liu   +4 more
doaj   +1 more source