1 citations · 2 across the 6 of their papers we have counts for
6 papers
Increasing Determinism of All-vs-all Orbital Evolution Simulators
Enrico M. Zucchelli, Daniel Jang, Richard Linares
All-vs-all orbital evolutionary simulations for the low Earth orbit (LEO) simulate the long term evolution of the LEO environment. Although these simulations typically offer the hi…
PixLift: Accelerating Web Browsing via AI Upscaling
Yonas Atinafu, Sarthak Malla, HyunSeok Daniel Jang +3
Accessing the internet in regions with expensive data plans and limited connectivity poses significant challenges, restricting information access and economic growth. Images, as a…
Simulating the Evolution of Lethal Non-Trackable Population and its Effect on LEO Sustainability
Daniel Jang, Richard Linares
The vast majority of the orbital population today is unobservable and untracked because of their small size. These lethal non-trackable objects will only become more numerous as mo…
Threat Level Estimation From Possible Break-Up Events In LEO
Simone Servadio, Daniel Jang, Richard Linares
The NASA Standard Break-Up Model models collisions and explosions in space, which identifies the future distribution of debris. Given a possible break-up event, this work analyses…
A New Monte-Carlo Model for the Space Environment
Daniel Jang, Davide Gusmini, Peng Mun Siew +4
This paper introduces a novel Monte Carlo (MC) method to simulate the evolution of the low-earth orbit environment, enhancing the MIT Orbital Capacity Analysis Tool (MOCAT). In rec…
Towards a Machine Learning-Based Approach to Predict Space Object Density Distributions
Victor Rodriguez-Fernandez, Sumiyajav Sarangerel, Peng Mun Siew +3
With the rapid increase in the number of Anthropogenic Space Objects (ASOs), Low Earth Orbit (LEO) is facing significant congestion, thereby posing challenges to space operators an…