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In complex plasmas, the behavior of freely floating micrometer sized particles is studied. The particles can be directly visualized and recorded by digital video cameras. To analyze the dynamics of single particles, reliable algorithms are…
We propose an analytical framework based on stochastic geometry (SG) formulations to estimate a radar's detection performance under generalized discrete clutter conditions. We model the spatial distribution of discrete clutter scatterers as…
Initial State Radiation (ISR) effect is implemented in Madgraph using photon structure functions. Detailed examinations are performed against other generators including Whizard, BabayagaNLO and KKMC, for various physics processes at linear…
We propose a Gaussian mixture model for background subtraction in infrared imagery. Following a Bayesian approach, our method automatically estimates the number of Gaussian components as well as their parameters, while simultaneously it…
We model the annihilation of relic positrons produced in a gamma-ray burst (GRB) after its afterglow has faded. We find that the annihilation signal from at least one GRB remnant in the Milky Way galaxy should be observable with future…
A novel gaseous two-dimensional imaging detector "Micro Pixel Chamber (micro-PIC)" has been developed. This detector is based on double sided printed circuit board (PCB). We have developed large area (10cm x 10cm) micro-PICs with 65536…
We devise a fast and optimal estimator for the amplitude of the bispectrum of clustered Infrared (IR) point-sources. We show how this estimator can account for the cases of partial sky coverage and inhomogeneous noise. Expected detection…
The aim of our work is to analyze size distributions of particles and their agglomerates in imagery from astrophysical microgravity experiments. The data acquired in these experiments are given by sequences consisting of several hundred…
Most detection algorithms in spatial modulation (SM) are formulated as linear regression via the regularized least-squares (RLS) method. In this method, the transmit signal is estimated by minimizing the residual sum of squares penalized…
This paper presents a new Bayesian spectral unmixing algorithm to analyse remote scenes sensed via sparse multispectral Lidar measurements. To a first approximation, in the presence of a target, each Lidar waveform consists of a main peak,…
Microplastics (MPs) are ubiquitous in all ecosystems, affecting wildlife and, ultimately, human health. The complexity of natural samples plus the unspecificity of their treatments to isolate polymers renders the characterization of…
The realization that GRBs are narrowly beamed implied that the actual rate of GRBs is much larger than the observed one. There are 500 unobserved GRBs for each observed one. The lack of a clear trigger makes it hard to detect these…
Detection of sparse signals arises in a wide range of modern scientific studies. The focus so far has been mainly on Gaussian mixture models. In this paper, we consider the detection problem under a general sparse mixture model and obtain…
We present the observational results of our search for emission-line galaxies (ELG) towards nearby voids. In order to find ELG, we started a survey using the IIIa-J objective prism plates from the Hamburg QSO Survey. The plates are…
We report on the result of an extensive search for X-ray counterparts to Gamma Ray Bursts (GRB) using data acquired with the Imaging Proportional Counter (IPC) on-board the Einstein Observatory. We examine background sky fields from all…
There is a high demand for fully automated methods for the analysis of primary particle size distributions of agglomerated, sintered or occluded primary particles, due to their impact on material properties. Therefore, a novel, deep…
We analyze the statistical problem of recovering an atomic signal, modeled as a discrete uniform distribution $\mu$, from a binned Poisson convolution model. This question is motivated, among others, by super-resolution laser microscopy…
This paper introduces Bayesian supervised and unsupervised segmentation algorithms aimed at oceanic segmentation of SAR images. The data term, \emph{i.e}., the density of the observed backscattered signal given the region, is modeled by a…
A Bayesian approach is presented for detecting and characterising the signal from discrete objects embedded in a diffuse background. The approach centres around the evaluation of the posterior distribution for the parameters of the discrete…
Models of gravitational waveforms play a critical role in detecting and characterizing the gravitational waves (GWs) from compact binary coalescences. Waveforms from numerical relativity (NR), while highly accurate, are too computationally…