Search results for "Names"
showing 10 items of 6843 documents
Influence Diagnostics for Meta-Analysis of Individual Patient Data Using Generalized Linear Mixed Models
2014
In meta-analysis, generalized linear mixed models (GLMMs) are usually used when heterogeneity is present and individual patient data (IPD) are available, while accepting binary, discrete as well as continuous response variables. In the present paper some measures of influence diagnostics based on log-likelihood are suggested and discussed. A known measure is approximated to get a simpler form, for which the information matrix is no more necessary. The performance of the proposed measure is assessed through a diagnostic analysis on simulated data reproducing a possible meta-analytical context of IPD with influential outliers. The proposed measure is showed to work well and to have a form sim…
Applicability of the Poisson distribution to model the data of the German Children's Cancer Registry.
1995
Since 1980 the German Children's Cancer Registry has documented all childhood malignancies in the Federal Republic of Germany. Various statistical procedures have been proposed to identify municipalities or other geographic units with increased numbers of malignancies. Usually the Poisson distribution, which requires the malignancies to be distributed homogeneously and uncorrelated, is applied. Other discrete statistical distributions (so-called cluster distributions) like the generalized or compound Poisson distributions are applicable more generally. In this paper we present a first explorative approach to the question of whether it is necessary to use one of these cluster distributions t…
PVAmpliconFinder: a workflow for the identification of human papillomaviruses from high-throughput amplicon sequencing
2019
Abstract Background The detection of known human papillomaviruses (PVs) from targeted wet-lab approaches has traditionally used PCR-based methods coupled with Sanger sequencing. With the introduction of next-generation sequencing (NGS), these approaches can be revisited to integrate the sequencing power of NGS. Although computational tools have been developed for metagenomic approaches to search for known or novel viruses in NGS data, no appropriate tool is available for the classification and identification of novel viral sequences from data produced by amplicon-based methods. Results We have developed PVAmpliconFinder, a data analysis workflow designed to rapidly identify and classify kno…
Ownership protection of plenoptic images by robust and reversible watermarking
2018
Abstract Plenoptic images are highly demanded for 3D representation of broad scenes. Contrary to the images captured by conventional cameras, plenoptic images carry a considerable amount of angular information, which is very appealing for 3D reconstruction and display of the scene. Plenoptic images are gaining increasing importance in areas like medical imaging, manufacturing control, metrology, or even entertainment business. Thus, the adaptation and refinement of watermarking techniques to plenoptic images is a matter of raising interest. In this paper a new method for plenoptic image watermarking is proposed. A secret key is used to specify the location of logo insertion. Employing discr…
Fake Nodes approximation for Magnetic Particle Imaging
2020
Accurately reconstructing functions with discontinuities is the key tool in many bio-imaging applications as, for instance, in Magnetic Particle Imaging (MPI). In this paper, we apply a method for scattered data interpolation, named mapped bases or Fake Nodes approach, which incorporates discontinuities via a suitable mapping function. This technique naturally mitigates the Gibbs phenomenon, as numerical evidence for reconstructing MPI images confirms.
Non-equilibrium Markov state modeling of periodically driven biomolecules
2019
Molecular dynamics simulations allow to study the structure and dynamics of single biomolecules in microscopic detail. However, many processes occur on time scales beyond the reach of fully atomistic simulations and require coarse-grained multiscale models. While systematic approaches to construct such models have become available, these typically rely on microscopic dynamics that obey detailed balance. In vivo, however, biomolecules are constantly driven away from equilibrium in order to perform specific functions and thus break detailed balance. Here we introduce a method to construct Markov state models for systems that are driven through periodically changing one (or several) external p…
Towards an Efficient Implementation of an Accurate SPH Method
2020
A modified version of the Smoothed Particle Hydrodynamics (SPH) method is considered in order to overcome the loss of accuracy of the standard formulation. The summation of Gaussian kernel functions is employed, using the Improved Fast Gauss Transform (IFGT) to reduce the computational cost, while tuning the desired accuracy in the SPH method. This technique, coupled with an algorithmic design for exploiting the performance of Graphics Processing Units (GPUs), makes the method promising, as shown by numerical experiments.
Enhancing the Resolution of the Spectrogram of Non-Stationary Mobile Radio Channels by Using Massive MIMO Techniques
2017
This paper is concerned with the enhancement of the resolution of the spectrogram of non-stationary mobile radio channels using massive multiple-input multiple-output (MIMO) techniques. By starting from a new generic geometrical model for a non-stationary MIMO channel, we derive the complex MIMO channel gains under the assumption that the mobile station (MS) moves with time-variant speed. Closed-form solutions are derived for the spectrogram of the complex MIMO channel gains by using a Gaussian window. It is shown that the window spread can be optimized subject to the MS's speed change. Furthermore, it is shown that the spectrogram can be split into an auto-term and a cross-term. The auto-t…
Filter Bank: a Directional Approach for Retinal Vessel Segmentation
2017
It is well known that retinal diseases are sometimes identified by tortuosity of the vessels, presence of exudates and hemorrhages while lesions of tissues are associated to diabetic retinopathy, retinopathy of prematurity and more general cerebrovascular problems. One of the main issues in this research field is detecting small curvilinear structures, thus the aim of this contribution is to introduce a non-supervised and automated methodology to detect features such as curvilinear structures in retinal images. The core of the proposed methodology consists in using an approach that resembles the “a trous” wavelet algorithm. With respect to the standard Gabor analysis our methodology is base…
Experimental validation for spectrum cartography using adaptive multi-kernels
2017
This paper validates the functionality of an algorithm for spectrum cartography, generating a radio environment map (REM) using adaptive radial basis functions (RBF) based on a limited number of measurements. The power at all locations is estimated as a linear combination of different RBFs without assuming any prior information about either power spectral densities (PSD) of the transmitters or their locations. The RBFs are represented as centroids at optimized locations, using machine learning to jointly optimize their positions, weights and Gaussian decaying parameters. Optimization is performed using expectation maximization with a least squares loss function and a quadratic regularizer. …