Results 71 to 80 of about 9,352 (255)

Narrowband Radar Micromotion Targets Recognition Strategy Based on Graph Fusion Network Constructed by Cross-Modal Attention Mechanism

Remote Sensing
In the domain of micromotion target recognition, target characteristics can be extracted through either broadband or narrowband radar echoes. However, due to technical limitations and cost constraints in acquiring broadband radar waveform data ...
Yuanjie Zhang, Ting Gao, Hongtu Xie, Haozong Liu, Mengfan Ge, Bin Xu, Nannan Zhu, Zheng Lu   +7 more
doaj   +1 more source

Large Language Model‐Informed Dual‐Track AI Framework for the Synergistic Design of Crack‐Free and High‐Strength Superalloys

Advanced Science, EarlyView.
This paper illustrates a knowledge‐augmented dual‐track AI framework for advanced superalloy design. First, Large Language Models translate metallurgical heuristics into explicit rules to rapidly prune a vast compositional search space. Subsequently, LLM‐distilled priors safely guide a reinforcement learning agent during autonomous process optimization,
Jian Yao, Junkang Wu, Jie Su, Fuzhu Wang, Zi Wang, Li Wang, Liming Tan, Lan Huang, Feng Liu, Yong Liu   +9 more
wiley   +1 more source

Small Sample Target Recognition Based on Radar HRRP and SDAE-WACGAN

IEEE Access
The high resolution range profile (HRRP) of radar targets is commonly used for target recognition, and the recognition of non-cooperative targets is one of the urgent problems to be solved in radar target recognition. In order to address the noise impact
Jianguo Yin, Wen Sheng, He Jiang
doaj   +1 more source

Polarimetric radar target recognition framework based on LSTM

The Journal of Engineering, 2019
Polarimetric information is of great importance for radar target recognition. Conventional polarimetric features are hand-designed based on scattering mechanism.
Wei Chen, Liang Zhang, Jia Song, Yanhua Wang, Yang Li   +4 more
doaj   +1 more source

Circulating Amino Acid Network Remodeling Reveals Systemic Metabolic Reprogramming Predictive of Colorectal Cancer Recurrence and Metastasis

Advanced Science, EarlyView.
Blood‐based amino acid patterns measured by 19F NMR reveal hidden metabolic changes in colorectal cancer. By analyzing how these amino acids interact as a network, machine learning models identify patients at higher risk of recurrence and metastasis.
Ji‐Yeon Lee, Jumi Kim, Taehan Yoon, So Hyun Kwon, Su Chan Park, Dohyun Chun, Dohyeong Kim, Eun Jung Park, Hyunwoo Kim, Ji Min Lee   +9 more
wiley   +1 more source

Soft Segmented Randomization: Enhancing Domain Generalization in SAR ATR for Synthetic-to-Measured

IEEE Access
Synthetic aperture radar technology is crucial for high-resolution imaging under various conditions; however, the acquisition of real-world synthetic aperture radar data for deep learning-based automatic target recognition remains challenging due to high
Minjun Kim, Ohtae Jang, Haekang Song, Heesub Shin, Jaewoo Ok, Minyoung Back, Jaehyuk Youn, Sungho Kim   +7 more
doaj   +1 more source

Bridged h‐BN Nanosheets Coatings: Simultaneous Shielding Atomic‐Oxygen Irradiation and Achieving Superior Friction Performance

Advanced Science, EarlyView.
ABSTRACT To confront extreme space environments, a combination of inorganic and organic coatings can provide a pathway for offering highly durable radiation resistance and anti‐friction simultaneously. Herein, a strong interfacial 3D hydrogen‐bonding network is designed to create robust hexagonal boron nitride (h‐BN) based polymer coatings with ...
Zhuoyi Li, Changning Bai, Xingkai Zhang, Yusheng Liang, Wei Wu, Dingrui Zhou, Tao Du, Chunjin Wang   +7 more
wiley   +1 more source

CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning

Advanced Science, EarlyView.
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang, Zexi Chen, Yuanxiang Miao, Zuolin Shen, Deyu Cai, Shijie Tang, Yun Xue, Weifeng Guo, Hongbin Ji, Jian Liu, Kazuyuki Aihara, Luonan Chen   +11 more
wiley   +1 more source

Controllable Carbon Shell Encapsulation via Rapid Joule Heating Calcination for High‐Performance Asymmetric Supercapacitor With Suppressed Self‐Discharge and Robust Cycling Stability

Advanced Science, EarlyView.
The H‐Fe3O4@C negative electrode and H‐NiCo2S4@C positive electrode are designed through a controllable carbon shell encapsulation strategy. The as‐constructed asymmetric supercapacitor presents robust cycling stability with 93.7% capacity retention after 25 000 cycles.
Qiang Zhou, Zheng Yang, Zhen Cao, Xulan Zheng, Xiao Yan, Yunsong Li, Xinsheng Zhao, Yuxiao Lin, Xiaoxiao Li   +8 more
wiley   +1 more source

Physics-Informed Semantic Prompt Learning for Few-Shot Low-Altitude Radar Target Recognition in Remote Sensing

Remote Sensing
Low-altitude radar target recognition is important for intelligent airspace monitoring, unmanned aerial vehicle (UAV) supervision, airport bird-strike prevention, and low-altitude remote sensing.
Junrong Tu, Jihui Tu, Wenqing Feng, Zhaoyang Liu   +3 more
doaj   +1 more source