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Data acquired from multi-channel sensors is a highly valuable asset to interpret the environment for a variety of remote sensing applications. However, low spatial resolution is a critical limitation for previous sensors and the constituent…
We have developed and characterized an imaging instrument to measure the spatial properties of the diffuse near-infrared extragalactic background light in a search for fluctuations from z > 6 galaxies during the epoch of reionization. The…
Understanding the neutron background is essential for determining the neutron yield from nuclear reactions. In the analysis presented here, the shadow bars are placed in front of neutron detectors to determine the energy dependent neutron…
Received signal strength based radio tomographic imaging is a popular device-free indoor localization method which reconstructs the spatial loss field of the environment using measurements from a dense wireless network. Existing methods…
This paper introduces the Adaptive Base Representation (ABR) Theorem and proposes a novel number system that offers a structured alternative to the binary number system for digital computers. The ABR number system enables each decimal…
In this paper, we exploit the spiked covariance structure of the clutter plus noise covariance matrix for radar signal processing. Using state-of-the-art techniques high dimensional statistics, we propose a nonlinear shrinkage-based…
We present a new algorithm, Robust Automated Assignment of Rigid Rotors (RAARR), for assigning rotational spectra of asymmetric tops. The RAARR algorithm can automatically assign experimental spectra under a broad range of conditions,…
An important task when processing sensor data is to distinguish relevant from irrelevant data. This paper describes a method for an iterative singular value decomposition that maintains a model of the background via singular vectors…
A recursive scheme for the design of scatterers acting simultaneously as emitters and absorbers, such as lasers and coherent perfect absorbers in optics, at multiple prescribed frequencies is proposed. The approach is based on the assembly…
Absolute spectrophotometric measurements of diffuse radiation at 1 \mu m to 2 \mu m are crucial to our understanding of the radiative content of the Universe from nucleosynthesis since the epoch of reionization, the composition and…
The Neutrino Experiment with a Xenon Time-Projection Chamber (NEXT) experiment intends to investigate the neutrinoless double beta decay of 136Xe, and therefore requires a severe suppression of potential backgrounds. An extensive material…
We present a cost-effective new approach for generating denser depth maps for Autonomous Driving (AD) and Autonomous Vehicles (AVs) by integrating the images obtained from deep neural network (DNN) 4D radar detectors with conventional…
Access to the neutron orbital degree of freedom has been enabled by the recent actualization of methods to prepare and characterize neutron helical waves carrying orbital angular momentum (OAM) at small-angle neutron scattering (SANS)…
Conventional LIDAR systems require hundreds or thousands of photon detections to form accurate depth and reflectivity images. Recent photon-efficient computational imaging methods are remarkably effective with only 1.0 to 3.0 detected…
Spectrum cartography reconstructs spatial radio fields from sparse and heterogeneous wireless measurements, underpinning many sensing and optimization tasks in wireless networks. Attention mechanisms have recently enabled adaptive…
Even after decades of research, dynamic scene background reconstruction and foreground object segmentation are still considered as open problems due various challenges such as illumination changes, camera movements, or background noise…
We consider tomography of the Earth's interior using the neutrino pair beam which has recently been proposed. The beam produces a large amount of neutrino and antineutrino pairs from the circulating partially stripped ions and provides the…
The photon spectrum in macrocoherent atomic de-excitation via radiative emission of neutrino pairs (RENP) has been proposed as a sensitive probe of the neutrino mass spectrum, capable of competing with conventional neutrino experiments. In…
We present a novel methodology of augmenting the scattering data measured by small angle neutron scattering via an emerging deep convolutional neural network (CNN) that is widely used in artificial intelligence (AI). Data collection time is…
Some inverse problems in high-energy physics, neutron diffraction and NMR spectroscopy are discussed. To solve them, the Fourier integrated transformation method and the Maximum Entropy Technique (MENT) were used. The integrated images of…