Results 261 to 270 of about 386,074 (314)

Method for transmission error prediction and optimization of RV reducer based on ensemble learning

Youcheng Wang, Zhenyu Lv, Ling Zhu, Jiazhen Mao, Le Chang   +4 more
openalex   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Machine Learning Accelerated Computational Design of Bio‐Inspired Catalysts in the Nitrogen Reduction Reaction

Advanced Materials, EarlyView.
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano, Zihan You, Haoran Chen, Qifan Zhong, Rong‐Zhen Liao, Shaoqi Zhan   +5 more
wiley   +1 more source

An AI-driven fire risk forecasting framework for urban villages using IGWO-optimized LSTM with incremental learning. [PDF]

PLoS One
Tian J, Li H, Lv S.
europepmc   +1 more source

Deep Learning Inverse Design of Phase‐Change Reconfigurable Terahertz Metadevices for Multidimensional Secure Communication

Advanced Materials, EarlyView.
A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong, Xieyu Chen, Aarthy Nagarajan, Yi Yang, Zhihao Wang, Rui Yu, Chuang Zheng, Chunmei Ouyang, Xueqian Zhang, Tun Cao, Ranjan Singh, Zhen Tian   +11 more
wiley   +1 more source

Individual Differences in Detecting and Correcting Logical Errors in Mathematical Texts. [PDF]

Behav Sci (Basel)
Luo Z, Yang X, Zhang Y, Xiong B.
europepmc   +1 more source

The dysconnection hypothesis of schizophrenia: a 30-year update. [PDF]

World Psychiatry
Friston K.
europepmc   +1 more source

Axial Load Capacity Prediction of Concrete-Filled Steel Tubes Using Machine Learning: A Comparative Study. [PDF]

Materials (Basel)
Chen B, He W, Huang L, Shi X.
europepmc   +1 more source

Machine-Learning Predictions of Photoluminescence in Molecules Exhibiting Thermally Activated Delayed Fluorescence with Implicit Experimental Validation. [PDF]

J Chem Inf Model
Huang D, Cole JM.
europepmc   +1 more source

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Ring Learning with Errors Cryptography

2020
In this chapter, we will discuss Ring-Learning with Errors cryptography (RLWE) as one of the most powerful and challenging approaches for developing professional and complex applications and systems.
Marius Iulian Mihailescu, Stefania Loredana Nita   +1 more
openaire   +1 more source