Results 221 to 230 of about 54,052 (304)

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Analysis of the impact of non-real-time frequency sampling and damping coefficient on the dynamic frequency support response of grid-forming type renewable energy. [PDF]

Sci Rep
Tao X, Zhang S, He H, Xiong J, He W, Zeng W.   +5 more
europepmc   +1 more source

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

Consistency control of grid-connected substation voltage regulation based on photovoltaic inverter power coordination. [PDF]

Sci Rep
Liu J, Yang F, Lu B, Ren L.
europepmc   +1 more source

Cryogenic Neuromorphic Synaptic Behavior in 180 nm Silicon Transistors for Emerging Computing Systems

Advanced Intelligent Systems, EarlyView.
This study investigates the neuromorphic plasticity behavior of 180 nm bulk complementary metal oxide semiconductor (CMOS) transistors at cryogenic temperatures. The observed hysteresis data reveal a signature of synaptic behavior in CMOS transistors at 4 K.
Fiheon Imroze, Bhavani Yalagala, Naveen Kumar, Mostafa Elsayed, Meraj Ahmad, Robert Graham, Vihar Georgiev, Hadi Heidari, Martin Weides   +8 more
wiley   +1 more source

Development of a solar-integrated energy management system for grid-to-vehicle and vehicle-to-grid power exchange. [PDF]

Sci Rep
Rao NVK, Krishna KB.
europepmc   +1 more source

Multitarget Recognition of Flower Images Based on Lightweight Deep Neural Network and Transfer Learning

Advanced Intelligent Systems, EarlyView.
This article proposes a lightweight YOLOv4‐based detection model using MobileNetV3 or CSPDarknet53_tiny, achieving 30+ FPS and higher mAP. It also presents a ShuffleNet‐based classification model with transfer learning and GAN‐augmented images, improving generalization and accuracy.
Qingyang Liu, Yanrong Hu, Hongjiu Liu
wiley   +1 more source

A reduced sensor-based efficient and robust MPPT nonlinear controller for grid-integrated photovoltaic energy systems operating under rapidly changing climatic conditions. [PDF]

Sci Rep
Almalaq A, Annuk A, Jin T, Mohamed MA.
europepmc   +1 more source

Fault Models of Inverter-Interfaced Distributed Generators: Experimental Verification and Application to Fault Analysis

, 2011
Brucoli, M, Green, TC, McDonald, JDF, Plet, CA   +3 more
core   +1 more source

Design Challenges to Expand the Functionality of Drones: Deformable Rotorcraft and Nature‐Inspired Flapping Drones

Advanced Intelligent Systems, EarlyView.
This review systematically analyzes deformable drones, including extendable, foldable, and tilting configurations, along with nature‐inspired flapping rotorcraft. By classifying deformation principles and structural mechanisms, design trade‐offs, functional capabilities, and future development potential are highlighted.
Ju‐Hee Lee, Sumin Jung, Jinwoo Jang, Yeji Han, Minchae Kang, Jihun Seong, Suyeon Seo, Eunsol Park, Haesol Kwak, Min‐Woo Han   +9 more
wiley   +1 more source