Results 71 to 80 of about 2,675,626 (288)

On the Convergence, Bias and Degeneracy Properties of Iterative Multiple Disturbance Particle Filtering

open access: yesIEEE Access
The interest of this paper is the design of Bayesian particle filters for nonlinear state estimation (target tracking) applications. Particle filters employ a point mass representation of the probability densities using a set of weighted particles, in ...
Deepthi Kattula   +2 more
doaj   +1 more source

Importance sampling for metastable and multiscale dynamical systems

open access: yes, 2017
In this article, we address the issues that come up in the design of importance sampling schemes for rare events associated to stochastic dynamical systems. We focus on the issue of metastability and on the effect of multiple scales.
Spiliopoulos, Konstantinos
core   +1 more source

Novel Genetic Risk Factor Identified for L‐Asparaginase‐Induced Pancreatitis in Pediatric Patients With Cancer

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background L‐asparaginase is a critical component in treatment protocols for pediatric acute lymphoblastic leukemia. Acute pancreatitis reactions can necessitate delays and, in some cases, discontinuation of L‐asparaginase, which compromises outcomes.
Edward J. Raack   +39 more
wiley   +1 more source

An Adaptive Clustering-Based Active Learning Kriging Method Combining With Importance Sampling for Structural Reliability Analysis With Multiple Failure Regions

open access: yesIEEE Access
Reliability analysis of structures characterized by multiple failure regions remains a challenging task, especially when the computationally intensive numerical models are used to predict the system response. In order to address this problem, an adaptive
Guofeng Xue, Xuetao Lyu
doaj   +1 more source

Efficient tracking of spatially correlated signals in wireless sensor fields: A weighted stochastic gradient approach

open access: yesIET Wireless Sensor Systems, 2021
A weighted stochastic gradient algorithm is proposed for cost‐efficient tracking of unknown, correlated spatial signals from randomly distributed sensor observations in localized wireless sensor field.
Hadi Alasti
doaj   +1 more source

Ensemble Transport Adaptive Importance Sampling [PDF]

open access: yesSIAM/ASA Journal on Uncertainty Quantification, 2019
Markov chain Monte Carlo methods are a powerful and commonly used family of numerical methods for sampling from complex probability distributions. As applications of these methods increase in size and complexity, the need for efficient methods increases. In this paper, we present a particle ensemble algorithm.
Colin Cotter, Simon Cotter, Paul Russell
openaire   +6 more sources

MYCN Amplification in RB1‐Inactivated Retinoblastoma: Association With High‐Risk Features

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background MYCN amplification occurs in a subset of retinoblastoma cases, both with and without RB1 inactivation. It has been suggested that retinoblastomas with MYCN amplification represent a distinct entity with more aggressive clinical behavior.
Kyriaki Papaioannou   +9 more
wiley   +1 more source

Glucose sampling: importance of citrate [PDF]

open access: yesAnnals of Clinical Biochemistry: International Journal of Laboratory Medicine, 2016
We found that samples in which blood was acidified by citrate produced higher percentages of results within the desirable goal for bias compared with those collected into sodium fluoride. This confirms the findings of other studies. We also found that applying the multiplication factor suggested by Dimeski et al. (1.10) produced more results within the
Carta, Mariarosa   +3 more
openaire   +3 more sources

Revealing the structure of land plant photosystem II: the journey from negative‐stain EM to cryo‐EM

open access: yesFEBS Letters, EarlyView.
Advances in cryo‐EM have revealed the detailed structure of Photosystem II, a key protein complex driving photosynthesis. This review traces the journey from early low‐resolution images to high‐resolution models, highlighting how these discoveries deepen our understanding of light harvesting and energy conversion in plants.
Roman Kouřil
wiley   +1 more source

Dynamic importance sampling for queueing networks

open access: yes, 2007
Importance sampling is a technique that is commonly used to speed up Monte Carlo simulation of rare events. However, little is known regarding the design of efficient importance sampling algorithms in the context of queueing networks.
Dupuis, Paul   +2 more
core   +1 more source

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