Results 151 to 160 of about 168,042 (312)
Asymptotic Properties of Error Density Estimators in the Two-Phase Linear Regression Model
StatsThis paper investigates kernel estimation of the error density function for the two-phase linear regression model. We derive the asymptotic distributions of residual-based kernel density estimators.
Fuxia Cheng, Lixia Wang
doaj +1 more source
Cross Kingdom Metabolic Engineering Paradigm Elevating Sustainable Protein Production
Advanced Science, EarlyView.ABSTRACT Confronting the dual crisis of escalating global protein demand and unsustainable agriculture necessitates transformative solutions. Here, we pioneer evolutionary insights from maize nitrogen optimization via asparagine synthetase (ASNS) to rewire metabolism in Pichia pastoris.
Yuanyuan Du +4 more
wiley +1 more source
Target tracking based on non-linear kernel density estimation and Kalman filter
, 2015 This paper chooses Mean Shift algorithm to track target based on non-linear kernel density estimation and Kalman filter. Kernel density estimation is a probability density estimation method, which is used to detect moving target and update the target ...
Zhang YC(张宜弛) +2 more
core
Protein subnuclear localization based on a new effective representation and intelligent kernel linear discriminant analysis by dichotomous greedy genetic algorithm. [PDF]
PLoS One, 2018 Wang S, Yue Y.
europepmc +1 more source
On Determination Method for Resolution of Secondary Electron Images in Scanning Electron Microscopy
Advanced Science, EarlyView.An idealized SEM, termed Rayleigh's microscope, is constructed by Monte Carlo simulation to represent imaging conditions that just satisfy the Rayleigh criterion. Based on this physically defined model, sharpness–resolution conversion curves are established and combined with the Rose criterion, enabling automated resolution evaluation from practical ...
Tongfang Yang, Yanbo Zou, Zejun Ding
wiley +1 more source
Nonparametric Density Estimation for Positive Time Series [PDF]
The Gaussian kernel density estimator is known to have substantial problems for bounded random variables with high density at the boundaries. For i.i.d. data several solutions have been put forward to solve this boundary problem. In this paper we propose
Jeroen V.K. Rombouts, Taoufik Bouezmarni
core
Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI
Advanced Science, EarlyView.ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia +7 more
wiley +1 more source
On the Eigenspectrum of the Gram matrix and the generalisation error of kernel PCA
, 2004 In this paper we analyze the relationships between the eigenvalues of the m x m Gram matrix K for a kernel k(.,.) corresponding to a sample x1,...,xm drawn from a density p(x) and the eigenvalues of the corresponding continuous eigenproblem. We bound the
Shawe-Taylor, John +3 more
core
Advanced Science, EarlyView.A biotin‐modified artificial insertion peptide functionalized three‐dimensional high‐curvature‐TiO2 nano‐interface was engineered in a microfluidic chip to improve the isolation efficiency of small extracellular vesicles (sEVs). This chip balanced affinity, releasability, and extendibility, enabling high‐throughput recovery of sEVs for downstream ...
Le Wang +7 more
wiley +1 more source
Multiple Locally Linear Kernel Machines
CoRRIn this paper we propose a new non-linear classifier based on a combination of locally linear classifiers. A well known optimization formulation is given as we cast the problem in a $\ell_1$ Multiple Kernel Learning (MKL) problem using many locally linear kernels.
openaire +2 more sources