Results 151 to 160 of about 6,813,126 (333)

Does a Morphotropic Phase Boundary Exist in ZrxHf1‐xO2‐Based Thin Films?

Advanced Functional Materials, EarlyView.
This study investigates 6 nm zirconium‐rich hafnium‐zirconium oxide thin–film metal–insulator–metal capacitors using a combination of experimental methods and machine learning–based molecular dynamics simulations to provide insight into the physical mechanisms that enhance the dielectric constant near 0 V and attribute it to the field‐induced ...
Pramoda Vishnumurthy, Richard Ganser, Dong‐Gyu Kim, Intak Jeon, Chang Hwa Jung, Hanjin Lim, Thomas Mikolajick, Susan Trolier‐McKinstry, Alfred Kersch, Uwe Schroeder   +9 more
wiley   +1 more source

Q-learning Based Meta-Heuristics for Scheduling Bi-Objective Surgery Problems with Setup Time

Complex System Modeling and Simulation
Since the increasing demand for surgeries in hospitals, the surgery scheduling problems have attracted extensive attention. This study focuses on solving a surgery scheduling problem with setup time. First, a mathematical model is created to minimize the
Ruixue Zhang, Hui Yu, Adam Slowik, Kaizhou Gao   +3 more
doaj   +1 more source

EEG Signal in Emotion Detection Feature Extraction and Classification using Fuzzy Based Feature Search Algorithm and Deep Q Neural Network in Deep Learning Architectures [PDF]

, 2023
Shailaja Kotte, J. R. K. Kumar Dabbakuti
openalex   +1 more source

Rational Design of Printable Carbon Nanotube Transparent Conductive Films via Data‐Driven and Mechanistic Insights

Advanced Functional Materials, EarlyView.
A machine learning and simulation‐guided strategy is demonstrated for gentle, non‐sonication dispersion of carbon nanotubes, preserving structural integrity and performance. This approach enables transparent conductive films with low sheet resistance, high transmittance, and sub‐20 µm printability.
Ying Zhou, Ken‐ichi Nomura, Shun Muroga, Makoto Yoneya, Don N. Futaba, Takeo Yamada, Reiko Azumi, Kenji Hata   +7 more
wiley   +1 more source

Exploration design for Q-learning-based adaptive linear quadratic optimal regulators under stochastic disturbances

SICE Journal of Control, Measurement, and System Integration
This study considers a discrete-time, linear state feedback control strategy rooted in Q-learning, one of the Reinforcement Learning (RL) approaches, to address an adaptive Linear Quadratic (LQ) problem under stochastic disturbances. Q-learning optimizes
Vina Putri Virgiani, Shiro Masuda
doaj   +1 more source

Context Aware Task Orchestration With Deep Reinforcement Learning in Real Time Fog Computing Simulation Environment

IEEE Access
In the ever-evolving landscape of cloud computing, fog and edge computing have become more prominent because of their natural property of proximity to demanding parts.
Alp Gokhan Hossucu, Suat Ozdemir
doaj   +1 more source

Cross Learning in Deep Q-Networks [PDF]

, 2020
Xing Wang, Alexander Vinel
openalex   +1 more source

PRELIVE: A Framework for Predicting Lipid Nanoparticles In Vivo Efficacy and Reducing Reliance on Animal Testing

Advanced Functional Materials, EarlyView.
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy, Chuan‐En Lu, Kai Liu, Audrey Gallud   +3 more
wiley   +1 more source

Data-Driven Self-Learning Controller Design Approach for Power-Aware IoT Devices based on Double Q-Learning Strategy

, 2023
Paterova Tereza, Michal Prauzek, Jaromír Konecny   +2 more
openalex   +1 more source

Designing Asymmetric Memristive Behavior in Proton Mixed Conductors for Neuromorphic Applications

Advanced Functional Materials, EarlyView.
Protonic devices that couple ionic and electronic transport are demonstrated as bioinspired neuromorphic elements. The devices exhibit rubber‐like asymmetric memristive behavior with slow voltage‐driven conductance increase and rapid relaxation, enabling simplified read–write operation.
Nada H. A. Besisa, Masaki Tsuji, Yoshihiro Furue, Yifan Geng, Satya P. Pati, Satoshi Hamasuna, Takeaki Yajima   +6 more
wiley   +1 more source