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Although several existing and upcoming telescopes have imaging as their primary mode, they also have a sensitive phased-array mode with a multiple-beam forming capability enabling high time resolution studies of several types of objects,…
The identification and removal of systematic errors in object detectors can be a prerequisite for their deployment in safety-critical applications like automated driving and robotics. Such systematic errors can for instance occur under very…
The initial demonstrations over the last several years of the use of optical diffraction radiation (ODR) as non-intercepting electron-beam-parameter monitors are reviewed. Developments in both far-field imaging and near-field imaging are…
We study generalized dark-field imaging systems. These are a subset of linear shift-invariant optical imaging systems, that exhibit arbitrary aberrations, and for which normally-incident plane-wave input yields zero output. We write down…
GARR optical network is composed of two separate optical network domains at the national level. With the aim to integrate them we implemented alien wavelengths to deliver high-performance services improving the overall network efficiency.…
The LOw Frequency ARray (LOFAR) is capable of imaging spectroscopy of the Sun in the 10-240 MHz frequency range, with high spectral, temporal, and spatial resolution. However, the complex and rapidly varying nature of solar radio emission -…
Radio astronomy is entering a new era with new and future radio observatories such as the Low Frequency Array and the Square Kilometer Array. We describe in detail an automated flagging pipeline and evaluate its performance. With only a…
Network-wide traffic analytics are often needed for various network monitoring tasks. These measurements are often performed by collecting samples at network switches, which are then sent to the controller for aggregation. However,…
Due to the lack of a large-scale reflection removal dataset with diverse real-world scenes, many existing reflection removal methods are trained on synthetic data plus a small amount of real-world data, which makes it difficult to evaluate…
We describe the data flow in the operation of the VEGA/CHARA instrument. After a brief summary of the main characteristics and scientific objectives of the VEGA instrument, we explain the standard procedure from the scientific idea up to…
In the period 2003-2009 in the Frank Laboratory of Neutron Physics, JINR, the total modernization of the IBR-2 pulsed reactor which is mainly used for investigations in condensed matter physics using thermal neutron scattering will be…
The reduction of integral field spectroscopy (IFS) data requires several stages and many repetitive operations to convert raw data into, typically, a large number of spectra. Instead there are several semiautomatic data reduction tools and…
We introduce DataCI, a comprehensive open-source platform designed specifically for data-centric AI in dynamic streaming data settings. DataCI provides 1) an infrastructure with rich APIs for seamless streaming dataset management,…
The Son-Of-XShooter (SOXS) is a single object spectrograph (UV-VIS & NIR) and acquisition camera scheduled to be mounted on the ESO 3.58-m New Technology Telescope at the La Silla Observatory. Although the underlying data reduction…
The rapid development in ubiquitous computing has enabled the use of microcontrollers as edge devices. These devices are used to develop truly distributed IoT-based mechanisms where machine learning (ML) models are utilized. However,…
The introduction of infrared arrays for lunar occultations (LO) work and the improvement of predictions based on new deep IR catalogues have resulted in a large increase in the number of observable occultations. We provide the means for an…
The DIRC, a novel type of Cherenkov ring imaging device, is the primary hadronic particle identification system for the BaBar detector at the asymmetric B-factory Pep-II at SLAC. It is based on total internal reflection and uses long,…
IoT and edge-based inference systems require unique solutions to overcome resource limitations and unpredictable environments. In this paper, we propose an environment-aware dynamic pruning system that handles the unpredictability of edge…
We present the first public version of SImMER, an open-source Python reduction pipeline for astronomical images of point sources. Current capabilities include dark-subtraction, flat-fielding, sky-subtraction, image registration, FWHM…
Modeling high-dimensional dependencies while keeping likelihoods tractable remains challenging. Classical vine-copula pipelines are interpretable but can be expensive, while many neural estimators are flexible but less structured. In this…