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Practical Aspects of Localization Microscopy
Published in Guy Cox, Fundamentals of Fluorescence Imaging, 2019
Mark B. Cannell, Christian Soeller, David Baddeley
The principal argument for centroid-based methods is their speed, but we can perform real-time analysis of both 2D and 3D data using fitting methods, on fairly modest computing hardware. 2D fitting can be performed in real time on a single workstation class machine (Xeon E5620, 2.4 GHz, 4 cores, HT) at 50 Hz acquisition frame rates—specifics depend on the typical number of events per frame, but we can typically analyse 70–100 frames per second. In connection with this point, we find that the bottleneck in our implementation of 2D fitting is often the initial event detection step, a step that also has to be performed prior to the application of centroid-based localization methods, rather than the fitting itself. Fitting 3D data is a bit slower and may require a small distributed cluster of 2–3 machines to allow analysis in real time. Our “cluster” is implemented by running a standard program on participating office PCs (which are present in the typical research laboratory setting) and we dynamically recruit additional PCs until the analysis keeps up with data acquisition. Given that the intrinsically more reliable fitting methods can be performed in real time, we feel that using a centroid estimator for its superior speed is an unnecessary compromise. Centroid-based estimation does, however, have a useful role in estimating start parameters for fitting-based methods, improving their speed and convergence. We use a bias-reduced derivative of the Quick-PALM algorithm [50] for this purpose when fitting astigmatic PSFs.
Graphene-based anti-corrosion coatings on magnesium alloys: a review
Published in Surface Engineering, 2023
Yan Zhou, Qian Li, Andrej Atrens, Liang Wu
The degree of oxidation of the graphene and the type of oxygen-containing groups influences the value of its electron gap, and consequently the conductivity of the GO. Moreover, graphene with different degrees of oxidation can has different energy gaps and structural deformations, resulting in different chemical properties [81]. Reduced graphene oxide (rGO), a reduced derivative of GO that is electrically conductive, contains fewer oxygen radicals, and maintains the better the original structure of graphene [60,82].
On the combination of kernel principal component analysis and neural networks for process indirect control
Published in Mathematical and Computer Modelling of Dynamical Systems, 2020
A. Errachdi, S. Slama, M. Benrejeb
In this paper, the scheme of indirect adaptive control is used based on a neural network. First, the used neural network is based on an adaptive learning rate and a reduced derivative of the activation function. Even better, the weights of the neural network model and neural network controller are updated based on the identification error and the control error and used to generate the appropriate control.
Adaptative regularization parameter for Poisson noise with a bilevel approach: application to spectral computerized tomography
Published in Inverse Problems in Science and Engineering, 2021
(3) Compute the reduced derivative and the reduced gradient and 19. A gradient descent is performed with a Armijo line search. The stopping criterion used is .