Contesting Regulatory Capacity: Exploring Doctrines in the Regulatory State
ABSTRACT The contemporary literature on regulation and development has emphasised the importance of low discretion devices for achieving desired policy objectives. At the same time, there has been a growing recognition that state capacity in general, and regulatory capacity more specifically, are essential for achieving development goals in a world of ...
Bruno Queiroz Cunha, Martin Lodge
wiley +1 more source
Improved deformation reconstruction of composite material structures based on optical fiber sensing. [PDF]
Huang J +8 more
europepmc +1 more source
PID‐Like Robust Control of Non‐Minimum Phase Robotic Manipulators
ABSTRACT This paper proposes an output‐feedback tracking controller for non‐minimum phase nonlinear systems with unknown uncertainties and external disturbances, where not all states are measurable, and the zero dynamics are unstable. The approach combines a backstepping‐based stabilizing state‐feedback law with a cascade extended high‐gain observer ...
Mohammad Al Saaideh +2 more
wiley +1 more source
Machine Learning-based Radiomic Model for Early Diagnosis of Male Urethral Injury in Pelvic Fracture Patients. [PDF]
Pan Y +7 more
europepmc +1 more source
Optimal Gain Selection for the Arbitrary‐Order Homogeneous Differentiator
ABSTRACT Differentiation of noisy signals is a relevant and challenging task. Widespread approaches are the linear high‐gain observer acting as a differentiator and Levant's robust exact differentiator with a discontinuous right‐hand side. We consider the family of arbitrary‐order homogeneous differentiators, which includes these special cases.
Benjamin Calmbach +2 more
wiley +1 more source
Prognostic value of tumor microenvironment-based molecular subtypes in hepatocellular carcinoma patients undergoing surgery for spinal metastases: refining conventional scoring systems. [PDF]
Liang B, Hu A, Zhou J, Li J, Dong J.
europepmc +1 more source
ABSTRACT Data‐based learning of system dynamics allows model‐based control approaches to be applied to systems with partially unknown dynamics. Gaussian process regression is a preferred approach that outputs not only the learned system model but also the variance of the model, which can be seen as a measure of uncertainty.
Daniel Landgraf +2 more
wiley +1 more source
AiM: urban air quality forecasting with grid-embedded recurrent MLP model. [PDF]
Chatterjee K +9 more
europepmc +1 more source
ABSTRACT This work proposes a new framework for stabilizing uncertain linear systems and for determining robust periodic invariant sets and their associated control laws for constrained uncertain linear systems. Necessary and sufficient conditions for stabilizability by periodic controllers are stated and proven using finite step Lyapunov functions for
Yehia Abdelsalam +2 more
wiley +1 more source
MRI-based habitat analysis for differentiating benign and malignant vertebral compression fractures. [PDF]
Liu X +7 more
europepmc +1 more source

