Results 31 to 40 of about 1,666 (170)

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Enhancing data consistency in decision matrix: Adapting Hadamard model to mitigate judgment contradiction

, 2014
Cardinal and ordinal inconsistencies are important and popular research topics in the study of decision making with pair-wise comparison matrices (PCMs).
Ergu, Daji, Shang, Jennifer, Kou, Gang
core   +1 more source

A goodness‐of‐fit test for regression models with discrete outcomes

Canadian Journal of Statistics, EarlyView.
Abstract Regression models are often used to analyze discrete outcomes, but classical goodness‐of‐fit tests such as those based on the deviance or Pearson's statistic can be misleading or have little power in this context. To address this issue, we propose a new test, inspired by the work of Czado et al.
Lu Yang, Christian Genest, Johanna G. Nešlehová   +2 more
wiley   +1 more source

Time Driven Activity‐Based Costing and Social Life Cycle Assessment: An Integrated Framework for Social Sustainability Accounting

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Integrating sustainability not only into corporate strategy and product design is essential to address pressing global challenges. This study proposes a framework that integrates social life cycle assessment (S‐LCA) into time‐driven activity‐based costing (TD‐ABC) to manage both social and economic issues by assessing social impacts across ...
Widiene Essouid, Ghada Bouillass, Stéphane Trébucq, Philippe Loubet, Guido Sonnemann   +4 more
wiley   +1 more source

Quenching the Hubbard Model: Comparison of Nonequilibrium Green's Function Methods

Contributions to Plasma Physics, EarlyView.
ABSTRACT We benchmark nonequilibrium Green's function (NEGF) approaches for interaction quenches in the half‐filled Fermi–Hubbard model in one and two dimensions. We compare fully self‐consistent two‐time Kadanoff–Baym equations (KBE), the generalized Kadanoff–Baym ansatz (GKBA), and the recently developed NEGF‐based quantum fluctuations approach (NEGF‐
Jan‐Philip Joost, Christopher Makait, Alexander Osterkorn, Erik Schroedter   +3 more
wiley   +1 more source

The Hadamard decomposition problem

Publisher Copyright: © The Author(s) 2024.We introduce the Hadamard decomposition problem in the context of data analysis. The problem is to represent exactly or approximately a given matrix as the Hadamard (or element-wise) product of two or more low ...
Mannila, Heikki, Ciaperoni, Martino, Gionis, Aristides   +2 more
core   +1 more source

Boolean invertible matrices identified from two permutations and their corresponding Haar-type matrices

, 2011
We construct a class Rm of m×m boolean invertible matrices whose elements satisfy the following property: when we perform the Hadamard product operation Ri⊙Rj on the set of row vectors {R1,…,Rm} of an element R∈Rm we produce either the row Rmax{i,j} or ...
Atreas, Nikolaos, Nikolaos Atreas, Costas Karanikas, Karanikas, Costas   +3 more
core   +1 more source