Results 221 to 230 of about 835,716 (334)
This study presents a tensegrity joint with pneumatic artificial muscles integrated directly into its tensile network. Inspired by tensegrity spine structures, the joint's topology is developed and further optimized through an evolutionary algorithm, taking into account fabrication constraints and target applications.
Jan Petrš+5 more
wiley +1 more source
Judicial review, rights and national security: the balancing act [PDF]
Lisa Hepplewhite
openalex +1 more source
GA: MCFFS method architecture. Pathological images are processed by the multi‐level feature information fusion (MLFF) method and the multi‐scale feature map fusion strategy to achieve the recognition result of cell nuclei. The MLFF module contains convolution blocks, spatial self‐attention, and atrous spatial pyramid pooling.
Yingqing Lu+3 more
wiley +1 more source
Judicial Review of Labor Agreements: Lessons From the Sports Industry [PDF]
Weistart, John C.
core +3 more sources
Losing Faith: America without Judicial Review?
Erwin Chemerinsky, Mark Tushnet
openalex +2 more sources
Speaking up: A Model of Judicial Dissent and Discretionary Review [PDF]
Andrew F. Daughety+1 more
openalex +1 more source
The study presents a low‐cost, noninvasive system for real‐time neonatal respiratory monitoring. A flexible, screen‐printed sensor patch captures chest movements with high sensitivity and minimal drift. Combined with machine learning, the system accurately detects breathing patterns and offers a practical solution for neonatal care in low‐resource ...
Gitansh Verma+3 more
wiley +1 more source
Judicial review in an age of legal realism: The debate over judicial activism
F. L. Morton
openalex +2 more sources
Editorial: The art of reducing futile biomedical research. [PDF]
Sisa I, Izurieta R, Llerena A, Teran E.
europepmc +1 more source
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