Results 101 to 110 of about 1,421,625 (273)

word2vec Parameter Learning Explained

open access: yes, 2014
The word2vec model and application by Mikolov et al. have attracted a great amount of attention in recent two years. The vector representations of words learned by word2vec models have been shown to carry semantic meanings and are useful in various NLP tasks.
openaire   +2 more sources

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

open access: yesArthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos   +2 more
wiley   +1 more source

Clinical, histological, and serological predictors of renal function loss in lupus nephritis.

open access: yesArthritis Care &Research, Accepted Article.
Objective Kidney survival is the ultimate goal in lupus nephritis (LN) management, but long‐term predictors remain inadequately studied, requiring long‐term follow‐up. This study aimed to identify baseline and early longitudinal predictors of kidney survival in the Accelerating Medicines Partnership LN longitudinal cohort.
Shangzhu Zhang   +21 more
wiley   +1 more source

Adaptive Mission Abort Planning Integrating Bayesian Parameter Learning

open access: yesMathematics
Failure of a safety-critical system during mission execution can result in significant financial losses. Implementing mission abort policies is an effective strategy to mitigate the system failure risk.
Yuhan Ma   +4 more
doaj   +1 more source

Iterative Learning Control for MIMO Singular Distributed Parameter Systems

open access: yesIEEE Access, 2017
This paper deals with the iterative learning control issue for multi-input multi-output singular distributed parameter systems (SDPSs) with parabolic and hyperbolic type, which described by coupled partial differential equations with singular matrix ...
Xi-Sheng Dai   +3 more
doaj   +1 more source

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

open access: yesInternational 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   +2 more
wiley   +1 more source

Parameter optimised iterative learning control algorithm for multi-batch reactor

open access: yesThe Journal of Engineering, 2019
A two-dimensional iterative learning PID control algorithm with Markov tuning method for batch reaction process is presented in this study. The learning algorithm with parameters tuned by Markov method can be explicitly tackling the repetitiveness of ...
Shida Gao   +4 more
doaj   +1 more source

Lifted generative parameter learning

open access: yes, 2013
Statistical relational learning (SRL) augments probabilistic models with relational representations and facilitates reasoning over sets of objects. When learning the probabilistic parameters for SRL models, however, one often resorts to reasoning over individual objects.
Van den Broeck, Guy   +2 more
openaire   +1 more source

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

open access: yesInternational 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   +5 more
wiley   +1 more source

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

open access: yesAdvanced 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   +8 more
wiley   +1 more source

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