Results 71 to 80 of about 27,799 (321)

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Oscillation of generalized differences of H\"older and Zygmund functions

, 2016
In this paper we analyze the oscillation of functions having derivatives in the H\"older or Zygmund class in terms of generalized differences and prove that its growth is governed by a version of the classical Kolmogorov's Law of the Iterated Logarithm ...
Castro, Alejandro J., Llorente, José G., Nicolau, Artur   +2 more
core   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Iterated-logarithm laws for convex hulls of random walks with drift [PDF]

, 2023
Wojciech Cygan, Nikola Sandrić, Stjepan Šebek, Andrew R. Wade   +3 more
openalex   +1 more source

Enhanced Switching Performance in Single‐Crystalline PbTiO3 Ferroelectric Memristors for Replicating Synaptic Plasticity

Advanced Functional Materials, EarlyView.
This study demonstrated single‐crystalline PbTiO3‐based memristors with atomically sharp interfaces, well‐ordered lattices, and minimal lattice mismatch. The devices exhibited an ON/OFF ratio exceeding 105, high stability, and rich resistance‐state modulation.
Haining Li, Zhiqiang Liao, Risa Kataoka, Md Sarker Shamim, Takeshi Kijima, Hiroyasu Yamahara, Hitoshi Tabata, Munetoshi Seki   +7 more
wiley   +1 more source

Patterns in Sinai's walk

, 2013
Sinai's random walk in random environment shows interesting patterns on the exponential time scale. We characterize the patterns that appear on infinitely many time scales after appropriate rescaling (a functional law of iterated logarithm).
Cheliotis, Dimitris, Virág, Bálint
core   +1 more source

An Ultra‐Robust Memristor Based on Vertically Aligned Nanocomposite with Highly Defective Vertical Channels for Neuromorphic Computing

Advanced Functional Materials, EarlyView.
An ultra‐robust memristor based on SrTiO3‐CeO2 (S‐C) vertically aligned nanocomposite (VAN) achieving exceptional endurance of 1012 switching cycles via interface engineering. Artificial neural networks (ANNs) integrated with S‐C VAN memristors exhibit high training accuracy across multiple datasets.
Zedong Hu, Hongyi Dou, Jeremy B. Gan, Cun Li, Xuanyu Sheng, Juanjuan Lu, Abhijeet Choudhury, Jialong Huang, Yizhi Zhang, Zhongxia Shang, Ye Cao, Xinghang Zhang, Haiyan Wang   +12 more
wiley   +1 more source

Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables [PDF]

Journal of Sciences, Islamic Republic of Iran, 2005
In this paper, we obtain the upper exponential bounds for the tail probabilities of the quadratic forms for negatively dependent subgaussian random variables.
doaj  

A general law of the iterated logarithm for non-additive probabilities

Results in Applied Mathematics
Motivated by some interesting problems in mathematical economics, quantum mechanics and finance, non-additive probabilities have been used to describe the phenomena which are generally non-additive. In this paper, we further study the law of the iterated
Zhaojun Zong, Miaomiao Gao, Feng Hu
doaj   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source