Results 121 to 130 of about 87,618 (263)

Grain Refinement During Severe Plastic Deformation and Similitude of Subgrain Formation: A Molecular Dynamics Study

Advanced Engineering Materials, EarlyView.
Molecular dynamics is used to investigate structure refinement during severe plastic deformation. The results show similitude with experimental data. Molecular dynamics simulations of severe plastic deformation of monocrystalline and polycrystalline samples by multiaxial compression of aluminum are carried out.
Roberto B. Figueiredo
wiley   +1 more source

Antenna Q-Factor Topology Optimization With Auxiliary Edge Resistivities

IEEE Open Journal of Antennas and Propagation
This paper presents a novel bi-level topology optimization strategy within the method-of-moments paradigm. The proposed approach utilizes an auxiliary variables called edge resistivities related to the Rao–Wilton–Glisson method-of-moments ...
Stepan Bosak, Miloslav Capek, Jiri Matas
doaj   +1 more source

Deep Learning for Automatic Differentiation of Mucinous versus Non-Mucinous Pancreatic Cystic Lesions: A Pilot Study. [PDF]

Diagnostics (Basel), 2022
Vilas-Boas F, Ribeiro T, Afonso J, Cardoso H, Lopes S, Moutinho-Ribeiro P, Ferreira J, Mascarenhas-Saraiva M, Macedo G.   +8 more
europepmc   +1 more source

Stretching the Printability Metric in Direct‐Ink Writing with Highly Extensible Yield‐Stress Fluids

Advanced Functional Materials, EarlyView.
This study introduces “drawability” as a new metric for assessing printability in direct‐ink writing, focusing on gap‐spanning performance and speed robustness. By designing yield‐stress fluids with high extensibility, we demonstrate that extensional strain‐to‐break significantly enhances printability.
Chaimongkol Saengow, Samya Sen, Joaquin Yus, Eliza E. Lovrich, Amanda G. Hoika, Kelly M. Chang, Arielle A. Pfeil, Nellie Haug, Amy J. Wagoner Johnson, Randy H. Ewoldt   +9 more
wiley   +1 more source

SHIFT PARAMETER ESTIMATION FOR IMPLICIT NEURAL REPRESENTATIONS OF IMAGES

Компютерні системи та інформаційні технології
Неявні нейронні репрезентації моделюють зображення як неперервні функції координат, що дає змогу виконувати обробку сигналів без дискретизації. Водночас перевірка того, чи відрізняються два зображення лише паралельним зсувом, як  правило  здійснюється ...
Ганна БЕДРАТЮК
doaj   +1 more source

MimIrADe: Automatic Differentiation in MimIR

Proceedings of the 34th ACM SIGPLAN International Conference on Compiler Construction
# Artifacts for MimIrADe: Automatic Differentiation in MimIR We present the code to replicate the experiments from the paper "MimIrADe: Automatic Differentiation in MimIR" submitted at the "International Conference on Compiler Construction" (CC) 2025.
Marcel Ullrich, Sebastian Hack, Roland Leißa   +2 more
openaire   +3 more sources

Printed Integrated Logic Circuits Based on Chitosan‐Gated Organic Transistors for Future Edible Systems

Advanced Functional Materials, EarlyView.
Edible electronics needs integrated logic circuits for computation and control. This work presents a potentially edible printed chitosan‐gated transistor with a design optimized for integration in circuits. Its implementation in integrated logic gates and circuits operating at low voltage (0.7 V) is demonstrated, as well as the compatibility with an ...
Giulia Coco, Valerio Francesco Annese, Valerio Galli, Ilaria Penna, Debora Russo, Marina Veronesi, Rita Scarpelli, Stefania Sabella, Mario Caironi   +8 more
wiley   +1 more source

Understanding the Flows of Signals and Gradients: A Tutorial on Algorithms Needed to Implement a Deep Neural Network from Scratch

Applied Sciences
Theano, TensorFlow, Keras, Torch, PyTorch, and other software frameworks have remarkably stimulated the popularity of deep learning (DL). Apart from all the good they achieve, the danger of such frameworks is that they unintentionally spur a black-box ...
Przemysław Klęsk
doaj   +1 more source

Automatic differentiation of thyroid scintigram by deep convolutional neural network: a dual center study. [PDF]

BMC Med Imaging, 2021
Yang P, Pi Y, He T, Sun J, Wei J, Xiang Y, Jiang L, Li L, Yi Z, Zhao Z, Cai H.   +10 more
europepmc   +1 more source

Automatic differentiation of ODE integration

CoRR, 2018
We discuss the calculation of the derivatives of ODE systems with the automatic differentiation tool ADiMat. Using the well-known Lotka-Volterra equations and the ode23 ODE solver as examples we show the analytic derivatives and detail how to differentiate a top-level function that calls ode23 somewhere with ADiMat.
openaire   +2 more sources