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Machine learning is a useful tool for identifying radio pulses from cosmic-ray air showers and for cleaning such pulses from radio background. This can lower the detection threshold and increase the accuracy for the pulse time and…

Given the current limited knowledge of meteor plasma micro-physics and its interaction with the surrounding atmosphere and ionosphere, meteors are a highly interesting observational target for high-resolution wide-field astronomical…

We investigate the observation of meteors with video cameras in stratospheric balloons, overcoming tropospheric handicaps like weather and extinction. We have studied the practical implementation of the idea, designed and tested…

Context. The mirror tracking system of the Canadian Automated Meteor Observatory (CAMO) can track meteors in real time, providing an effective angular resolution of 1 arc second and a temporal resolution of 100 frames per second. Aims. We…

Context. Several authors predicted an outburst of the Draconid meteor shower in 2018, but with an uncertain level of activity. Aims. Optical meteor observations were used to derive the population and mass indices, flux, and radiant…

One of the most energetic bolide events in recent decades was detected by the US Government sensors (USGS) over remote areas of the Bering Sea on December 18, 2018, 23:48 UT. No ground-based optical observations exist. Using the satellite…

We advance the modeling capability of electron particle precipitation from the magnetosphere to the ionosphere through a new database and use of machine learning (ML) tools to gain utility from those data. We have compiled, curated,…

This paper presents an algorithm that relies on a series of dense and deep neural networks for passive microwave retrieval of precipitation. The neural networks learn from coincidences of brightness temperatures from the Global…

We present an application of Deep Learning for the image recognition of asteroid trails in single-exposure photos taken by the Hubble Space Telescope. Using algorithms based on multi-layered deep Convolutional Neural Networks, we report…

Small object detection via UAV (Unmanned Aerial Vehicle) images captured from drones and radar is a complex task with several formidable challenges. This domain encompasses numerous complexities that impede the accurate detection and…

We report high resolution multi-station observations of meteors by the Canadian Automated Meteor Observatory (CAMO) recorded from June 2009 to August 2010. Our survey has a limiting detection magnitude of +5 mag in R-band, equivalent to a…

The Canada-France-Hawaii Legacy Survey (CFHTLS) comprising about 25 000 MegaCam images was data mined to search for serendipitous encounters of known Near Earth Asteroids (NEAs) and Potentially Hazardous Asteroids (PHAs). A total of 143…

We report an instrumental observation of the very exceptional Geminid fireball which was observed in scope of the Czech part of the European Fireball Network (EN) on 13 December 2012 at 4h12m59.4s UT. The uniqueness of this Geminid fireball…

Drone light shows have emerged as a popular form of entertainment in recent years. However, several high-profile incidents involving large-scale drone failures -- where multiple drones simultaneously fall from the sky -- have raised safety…

Machine Learning (ML) is the branch of computer science that studies computer algorithms that can learn from data. It is mainly divided into supervised learning, where the computer is presented with examples of entries, and the goal is to…

We describe how meteors recorded at the Earth can be used to partly reconstruct the meteoroid environments of the planets if a large sample (i.e. millions of orbits at a minimum) is available. The process involves selecting from the…

An array of large observational programs using ground-based and space-borne telescopes is planned in the next decade. The forthcoming wide-field sky surveys are expected to deliver a sheer volume of data exceeding an exabyte. Processing the…

We present a data-driven and physics-informed algorithm for drilling accident forecasting. The core machine-learning algorithm uses the data from the drilling telemetry representing the time-series. We have developed a Bag-of-features…

We examine meteoroid orbits recorded by the Canadian Meteor Orbit Radar (CMOR) from 2012-2019, consisting of just over 11 million orbits in a search for potential interstellar meteoroids. Our 7.5 year survey consists of an integrated…

By using recent observations of the Dydimos-Dimorphos system from the Hubble Space Telescope, 37 boulders with a size of 4 to 7 meters ejected from the system during the impact with the DART spacecraft were identified. In this work, we…