Results 61 to 70 of about 20,859 (261)

Fault Classification of a Blade Pitch System in a Floating Wind Turbine Based on a Recurrent Neural Network

한국해양공학회지, 2021
This paper describes a recurrent neural network (RNN) for the fault classification of a blade pitch system of a spar-type floating wind turbine. An artificial neural network (ANN) can effectively recognize multiple faults of a system and build a training
Seongpil Cho, Jongseo Park, Minjoo Choi
doaj   +1 more source

Beyond Visual Scoring: Computational CT‐analysis for HRCT based quantification of Interstitial Lung Disease in Inflammatory Rheumatic Disease

Arthritis Care &Research, Accepted Article.
Interstitial lung disease (IRD‐ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRD). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the non‐invasive assessment of ILD; however, its interpretation is constrained by substantial inter‐observer variability and ...
Alexander Pfeil, Tobias Hoffmann, Ulf Teichgräber, Diane Renz, Denise Beckmann, Gunter Wolf, Nicole Schadewaldt, Bianca Lassen‐Schmidt   +7 more
wiley   +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

Uncertainty quantification-based framework for predicting degradation trends of proton exchange membrane fuel cell

Green Energy and Intelligent Transportation
Accurately predicting the degradation trends of proton exchange membrane fuel cells (PEMFCs) can provide a solid basis for optimizing the control of vehicles and stations based on PEMFCs.
Bingxin Guo, Changjun Xie, Wenchao Zhu, Yang Yang, Hao Li, Yang Li, Hangyu Wu   +6 more
doaj   +1 more source

Short-Term Load Forecasting Based on Adabelief Optimized Temporal Convolutional Network and Gated Recurrent Unit Hybrid Neural Network

IEEE Access, 2021
To fully mine the relationship between temporal features in load data, improve the accuracy and efficiency of short-term load forecasting and overcome the difficulties caused by load nonlinearity and volatility in accurate load forecasting. In this paper,
Hanhong Shi, Lei Wang, Rafal Scherer, Marcin Wozniak, Pengchao Zhang, Wei Wei   +5 more
doaj   +1 more source

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

Simplified minimal gated unit variations for recurrent neural networks [PDF]

2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS), 2017
5 pages, 3 Figures, 5 ...
Joel C. Heck, Fathi M. Salem
openaire   +2 more sources

Automated Image Captioning with Multi-layer Gated Recurrent Unit

2022 30th European Signal Processing Conference (EUSIPCO), 2022
Describing the semantic content of an image via natural language, known as image captioning, has recently attracted substantial interest in computer vision and language processing communities. Current image captioning approaches are mainly based on an encoder-decoder framework in which visual information is extracted by an image encoder and captions ...
Moral, Ozge Taylan, Kilic, Volkan, Onan, Aytug, Wang, Wenwu   +3 more
openaire   +3 more sources

Dual-Gated Graph Convolutional Recurrent Unit with Integrated Graph Learning (DG3L): A Novel Recurrent Network Architecture with Dynamic Graph Learning for Spatio-Temporal Predictions

Entropy
Spatio-temporal prediction is crucial in intelligent transportation systems (ITS) to enhance operational efficiency and safety. Although Transformer-based models have significantly advanced spatio-temporal prediction performance, recent research ...
Yuxuan Wang, Zhouyuan Zhang, Shu Pi, Haishan Zhang, Jiatian Pi   +4 more
doaj   +1 more source

An Attention Encoder-Decoder Dual Graph Convolutional Network with Time Series Correlation for Multi-Step Traffic Flow Prediction

Journal of Advanced Transportation, 2022
Accurate traffic prediction is a powerful factor of intelligent transportation systems to make assisted decisions. However, existing methods are deficient in modeling long series spatio-temporal characteristics. Due to the complex and nonlinear nature of
Shanchun Zhao, Xu Li
doaj   +1 more source