Results 161 to 170 of about 792,416 (284)

Trajectories of Physical Function in Canadian Children with Juvenile Idiopathic Arthritis

Arthritis Care &Research, Accepted Article.
Objectives We describe trajectories of physical function in children newly diagnosed with juvenile idiopathic arthritis (JIA) and identify trajectories with persisting functional impairments and associated baseline characteristics. Methods We included patients enrolled in the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry ...
Clare Cunningham, Meghan McPherson, Lillian Lim, Roberta A. Berard, Matthew Berkowitz, Jean‐Philippe Proulx‐Gauthier, Brian M. Feldman, Nicole Johnson, Dax G. Rumsey, Heinrike Schmeling, Lori B. Tucker, Thomas Loughin, Kristin M. Houghton, Jaime Guzman, The CAPRI Registry Investigators   +14 more
wiley   +1 more source

Prediction of skin disease using a new cytological taxonomy based on cytology and pathology with deep residual learning method. [PDF]

Sci Rep, 2021
Bu J, Lin Y, Qing LQ, Hu G, Jiang P, Hu HF, Shen EX.   +6 more
europepmc   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

Deep residual learning with product units

We propose a deep product-unit residual neural network (PURe) that integrates product units into residual blocks to improve the expressiveness and parameter efficiency of deep convolutional networks. Unlike standard summation neurons, product units enable multiplicative feature interactions, potentially offering a more powerful representation of ...
Li, Ziyuan, Jaekel, Uwe, Dellen, Babette
openaire   +2 more sources

An Adaptive Human Pilot Model With Reaction Time Delay for Enhanced Adaptive Control in Piloted Systems

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces an adaptive human pilot model that captures pilot time‐delay effects in adaptive control systems. The model enables the prediction of pilot–controller interactions, facilitating safer integration and improved design of adaptive controllers for piloted applications.
Abdullah Habboush, Yildiray Yildiz
wiley   +1 more source

A Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller

International Journal of Adaptive Control and Signal Processing, EarlyView.
Block Diagram of the Robust Adaptive One‐Sample‐Ahead Preview Super‐Twisting Sliding Mode Controller. ABSTRACT This article introduces a discrete‐time robust adaptive one‐sample‐ahead preview super‐twisting sliding mode controller. A stability analysis of the controller by Lyapunov criteria is developed to demonstrate its robustness in handling both ...
Guilherme Vieira Hollweg, Paulo Jefferson Dias de Oliveira Evald, Shivam Chaturvedi, Hilton Abilio Gründling, Rodrigo Varella Tambara, Wencong Su   +5 more
wiley   +1 more source

Mechanistically guided residual learning for battery state monitoring throughout life. [PDF]

Nat Commun
Che Y, Zheng Y, Rhyu J, Guo J, Wang S, Teodorescu R, Braatz RD.   +6 more
europepmc   +1 more source

Retinal Vessel Segmentation by Deep Residual Learning with Wide Activation. [PDF]

Comput Intell Neurosci, 2020
Ma Y, Li X, Duan X, Peng Y, Zhang Y.
europepmc   +1 more source

Reconstruction of Compressed-sensing MR Imaging Using Deep Residual Learning in the Image Domain. [PDF]

Magn Reson Med Sci, 2021
Ouchi S, Ito S.
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source