Results 81 to 90 of about 145,710 (264)

Neural Network‐Based Permittivity Engineering of Magnetic Absorbers for Customizable Microwave Absorption

Advanced Science, EarlyView.
A neural network‐enabled permittivity engineering paradigm is introduced, transcending traditional trial‐and‐error design. By decoupling electromagnetic parameters and screening a high‐throughput feature space, an ultrathin (1.0 mm) magnetic absorber is inversely designed, experimentally achieving a superior and customizable 5.1 GHz bandwidth and ...
Chenxi Liu, Jinzhe Li, Sen Li, Zhongqiu Guo, Yao Chen, Tian Li, Renchi Qin, Jiaxu Sun, Yongxi Lu, Fanbin Meng   +9 more
wiley   +1 more source

Quantitative Assessment of Brix in Grafted Melon Cultivars: A Machine Learning and Regression-Based Approach

Foods
The article demonstrates the Brix content of melon fruits grafted with different varieties of rootstock using Support Vector Regression (SVR) and Multiple Linear Regression (MLR) model approaches.
Uğur Ercan, Ilker Sonmez, Aylin Kabaş, Onder Kabas, Buşra Calık Zyambo, Muharrem Gölükcü, Gigel Paraschiv   +6 more
doaj   +1 more source

Lattice Genome Framework for Regionally Tailored Component‐Level Multi‐Objective Design in Additive Manufacturing

Advanced Science, EarlyView.
A Lattice Genome framework links geometric and process “genes” to lattice “phenotypes” via correction‐calibrated high‐throughput simulations and a growing performance database. Genome‐driven retrieval and recombination of unit cells enables component‐level, regionally tailored multi‐objective design: stress fields are programmed under constant relative
Haoyuan Deng, Yufan Zhao, Mingyang Cao, Haiou Yang, Pan Wang, Hongze Wang, Hao Wang, Akihiko Chiba, Xin Lin   +8 more
wiley   +1 more source

Design and Optimization of Full‐Stokes Hyperspectro‐Polarimetric Encoding Metasurfaces Based on Conditional Multi‐Task Deep Learning

Advanced Science, EarlyView.
A conditional multi‐task deep learning framework is developed for designing and optimizing Full‐Stokes Hyperspectro‐Polarimetric Encoding Metasurfaces (FHPEMs). This framework achieves joint spectro‐polarimetric learning and unified forward–inverse design.
Chenjie Gong, Haodong Shi, Qi Wang, Yingchao Li, Hongyu Sun, Jiayu Wang, Guanlin Li, Jian Zhang, Qiang Fu, Huilin Jiang   +9 more
wiley   +1 more source

Kernel Methods for Small Sample and Asymptotic Tail Inference for Dependent, Heterogeneous Data [PDF]

This paper considers tail shape inference techniques robust to substantial degrees of serial dependence and heterogeneity. We detail a new kernel estimator of the asymptotic variance and the exact small sample mean-squared-error, and a simple ...
Jonathan Hill
core  

Robust transceiver design for MIMO relay systems with tomlinson harashima precoding [PDF]

, 2012
In this paper we consider a robust transceiver design for two hop non-regenerative multiple-input multiple-output (MIMO) relay networks with imperfect channel state information (CSI).
Millar, Andrew Paul, Stewart, Robert, Weiss, Stephan   +2 more
core  

Discovering Interpretable Semantics from Radio Signals for Contactless Cardiac Monitoring

Advanced Science, EarlyView.
This study presents a semantic representation framework for clinically interpretable cardiac monitoring from contactless radio signals. It formulates radio semantic learning as an information‐bottleneck problem and approximates the objective via intra‐modal compression and cross‐modal alignment, structuring radio measurements into meaningful semantic ...
Jinbo Chen, Haoyu Wang, Guixin Xu, Yuqin Yuan, Xinmeng Cai, Zhengwu Wei, Dongheng Zhang, Qibin Sun, Tianwei Zhang, Cuntai Guan, Yan Chen   +10 more
wiley   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Transforming oil market analysis: A novel GAN + LSTM predictive framework

Next Energy
A novel method of predicting the crude oil WTI futures prices based on a data set covering April 12, 2009 through January 7, 2024. To capture complex market dynamics more precisely, it incorporates key market factors such as open, high, and low price ...
Prity Kumari, G.Y. Chandan, Satish Kumar M   +2 more
doaj   +1 more source

AP‐Lab: An AI‐Driven Autonomous Pilot‐Scale Platform Bridging Materials Discovery and Industrial Manufacturing

Advanced Science, EarlyView.
AP‐Lab bridges materials discovery and industrial manufacturing by coupling proprietary datasets with an application benchmark (PCR Ct). A closed‐loop optimization workflow integrates ML, LLM, and autonomous synthesis/testing to refine magnetic nanoparticles–based nucleic‐acid extraction systems.
Zhan‐Long Wang, Zhifen Ma, Wenxing Song, Guolai Jiang, Boshi Jiang, Mingyang Jiang, Weiliang Shu, Bing Wang, Zhiyuan Wan, Shengyong Geng, Zhen Zhao, Wenhua Zhou, Xue‐Feng Yu   +12 more
wiley   +1 more source