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Signal artefacts due to Radio Frequency Interference (RFI) are a common nuisance in radio astronomy. Conventionally, the RFI-affected data are tagged by an expert data analyst in order to warrant data quality. In view of the increasing data…
Improving the retrieval relevance on noisy datasets is an emerging need for the curation of a large-scale clean dataset in the medical domain. While existing methods can be applied for class-wise retrieval (aka. inter-class), they cannot…
The MeerKAT Large Area Synoptic Survey (MeerKLASS) is designed to map large areas of the Southern sky for cosmology using the single-dish HI intensity mapping (IM) technique, while simultaneously delivering a wide, high angular-resolution…
Stellar intensity interferometry (SII) is based on the correlation of the light intensity fluctuations of a star detected at two or more telescopes, with no need to combine the collected photons directly. A measurement of the correlation in…
Sub-milliarcsecond imaging of nearby main sequence stars and binary systems can provide critical information on stellar phenomena such as rotational deformation, accretion effects, and the universality of starspot (sunspot) cycles.…
Effective labeled data collection plays a critical role in developing and fine-tuning robust streaming analytics systems. However, continuously labeling documents to filter relevant information poses significant challenges like limited…
We report the implemented architecture for monitoring the health and the quality of the Son Of X-Shooter (SOXS) spectrograph for the New Technology Telescope in La Silla at the European Southern Observatory. Briefly, we report on the…
Low-altitude wireless networks (LAWNs) have become effective solutions for collecting data from low-power Internet-of-Things devices (IoTDs) in remote areas with limited communication infrastructure. However, some outdoor IoTDs deployed in…
Neural architecture search (NAS) approaches aim at automatically finding novel CNN architectures that fit computational constraints while maintaining a good performance on the target platform. We introduce a novel efficient one-shot NAS…
The flourishing low-Earth orbit (LEO) constellation communication network provides a promising solution for seamless coverage services to Internet-of-Things (IoT) terminals. However, confronted with massive connectivity and rapid variation…
A new architecture is presented for a Networked Signal Processing System (NSPS) suitable for handling the real-time signal processing of multi-element radio telescopes. In this system, a multi-element radio telescope is viewed as an…
Current optimization of ground-based Cherenkov telescopes arrays, also called Imaging Air Cherenkov Telescope (IACT) arrays, relies on brute-force human-driven approaches based on large simulations requiring both high amount of storage and…
We present a project to implement a national common strategy for the mitigation of the steadily deteriorating Radio Frequency Interference (RFI) situation at the Italian radio telescopes. The project involves the Medicina, Noto, and…
The Cherenkov Telescope Array (CTA) is the next-generation stereoscopic system of Imaging Atmospheric Cherenkov Telescopes (IACTs). In IACTs, the atmosphere is used as a calorimeter to measure the energy of extensive air showers induced by…
GAW (Gamma Air Watch) is a pathfinder experiment in the TeV range to test the feasibility of a new generation of Imaging Atmospheric Cherenkov Telescopes (IACT). It combines high flux sensitivity with large field-of-view (FoV=24deg x 24deg)…
Gamma-ray astronomy holds a great potential for Astrophysics, Particle Physics and Cosmology. The CTA is an inter- national initiative to build the next generation of ground-based gamma-ray observatories, which will represent a factor of…
Our Galaxy is filled with cosmic-ray particles and more than 98% of them are atomic nuclei. In order to clarify their origin and acceleration mechanism, chemical composition measurements of these cosmic rays with wide energy coverage play…
The online monitoring data in distribution networks contain rich information on the running states of the networks. By leveraging the data, this paper proposes a spatio-temporal correlation analysis approach for anomaly detection and…
Analysts and scientists are interested in querying streams of video, audio, and text to extract quantitative insights. For example, an urban planner may wish to measure congestion by querying the live feed from a traffic camera. Prior work…
We sought to develop a quantitative tool to quickly determine relative differences in MRI volumes both within and between large MR imaging cohorts (such as available in The Cancer Imaging Archive (TCIA)), in order to help determine the…