Results 11 to 20 of about 173,823 (304)

Fast Error Propagation Probability Estimates by Answer Set Programming and Approximate Model Counting

IEEE Access, 2022
We present a method employing Answer Set Programming in combination with Approximate Model Counting for fast and accurate calculation of error propagation probabilities in digital circuits.
Anselm Breitenreiter, Marko Andjelkovic, Oliver Schrape, Milos Krstic   +3 more
doaj   +1 more source

Using Conventional Cameras as Sensors for Estimating Confidence Intervals for the Speed of Vessels from Single Images

Sensors, 2022
In this paper, we describe an image-based approach for estimating the speed of a moving vessel using the wakes that remain on the surface of water after the vessel has passed.
Jose L. Huillca, Leandro A. F. Fernandes
doaj   +1 more source

Simultaneous Measurement of Strain and Temperature Distributions Using Optical Fibers with Different GeO₂ and B₂O₃ Doping

Sensors, 2023
Compensating for the effects of temperature is a crucial issue in structural health monitoring when using optical fiber sensors. This study focused on the change in sensitivity due to differences in GeO2 and B2O3 doping and then verified the accuracy ...
Shinsaku Hisada, Utanori Kodakamine, Daichi Wada, Hideaki Murayama, Hirotaka Igawa   +4 more
doaj   +1 more source

On the uncertainty of stream networks derived from elevation data: the error propagation approach [PDF]

, 2010
DEM error propagation methodology is extended to the derivation of vector-based objects (stream networks) using geostatistical simulations. First, point sampled elevations are used to fit a variogram model.
Heuvelink, G.B.M., van Loon, E.E.; id_orcid, Loon, E.E., van, Hengl, T.   +3 more
core   +1 more source

Reduced Sampling Overhead for Probabilistic Error Cancellation by Pauli Error Propagation [PDF]

Quantum
Quantum error mitigation is regarded as a possible path to near-term quantum utility. The methods under the quantum error mitigation umbrella term, such as probabilistic error cancellation (PEC), zero-noise extrapolation (ZNE) or Clifford data regression
Timon Scheiber, Paul Haubenwallner, Matthias Heller   +2 more
doaj   +1 more source

Accounting for Training Data Error in Machine Learning Applied to Earth Observations

Remote Sensing, 2020
Remote sensing, or Earth Observation (EO), is increasingly used to understand Earth system dynamics and create continuous and categorical maps of biophysical properties and land cover, especially based on recent advances in machine learning (ML).
Arthur Elmes, Hamed Alemohammad, Ryan Avery, Kelly Caylor, J. Ronald Eastman, Lewis Fishgold, Mark A. Friedl, Meha Jain, Divyani Kohli, Juan Carlos Laso Bayas, Dalton Lunga, Jessica L. McCarty, Robert Gilmore Pontius, Andrew B. Reinmann, John Rogan, Lei Song, Hristiana Stoynova, Su Ye, Zhuang-Fang Yi, Lyndon Estes   +19 more
doaj   +1 more source

Error Propagation in Monocular Navigation for Zinf Compared to Eightpoint Algorithm [PDF]

, 2013
Efficient visual pose estimation plays an important role for a variety of applications. To improve the quality, the measurements from different sensors can be fused.
Elmar Mair, Michael Suppa, Mair, Elmar, Darius Burschka, Suppa, Michael, Burschka, Darius   +5 more
core   +1 more source

Propagation of Error from Registration Parameters to Transformed Data [PDF]

, 2016
Methods to register two sets of data have existed for quite some time. However, these sets of data are rarely error-free. Consequently, any registration based on this data will be affected by the error.
Shah, Mili; Franaszek, Marek; Cheok, Geraldine
core   +1 more source

Error Propagation on a Hybrid Evaporator Model

Chemical Engineering Transactions, 2011
preview not available - see full-text PDF article.
D. Colorado, X. Ding, J.A. Hernandez, J. Andaverde, D. Juarez   +4 more
doaj   +1 more source

Índices de capacidade de relações funcionais lineares e não-lineares Capability index for linear and non-linear functions

Production, 2004
São apresentados métodos para determinação dos índices de capacidade tais como Cp e Cpk aplicados no "design for six sigma" (DFSS) quando a característica de qualidade é não-observável e dada por Y = f(X1, X2, X3,....Xk), onde Xi são variáveis aleatórias
Edivaldo Antonio Bulba, Linda Lee Ho
doaj   +1 more source