Related papers: Real-Time Thermospheric Density Estimation Via Two…
A novel multiphysics-decision tree learning algorithm is presented for (1) estimating transport properties in the variably saturated subsurface governed by explicitly coupled equations for water, heat, and solute transport; and (2)…
Kernel density estimation (KDE) has become a popular method for visual analysis in various fields, such as financial risk forecasting, crime clustering, and traffic monitoring. KDE can identify high-density areas from discrete datasets.…
Since the late 1950s, when the first artificial satellite was launched, the number of Resident Space Objects has steadily increased. It is estimated that around one million objects larger than one cm are currently orbiting the Earth, with…
We present a general parametrization for energy density of a quintessence field, a minimally coupled canonical scalar field which rolls down slowly during the late time. This parametrization can mimic all classes of quintessence dynamics,…
Diagnostic diagrams of forbidden lines have been a useful tool for observers in astrophysics for many decades now. They are used to obtain information on the basic physical properties of thin gaseous nebulae. Some diagnostic diagrams are in…
We perform molecular dynamics simulations to model density as a function of temperature for 74 alkanes with 5 to 10 carbon atoms and non-equilibrium molecular dynamics simulations in the NVT ensemble to model kinematic viscosity of 10…
Deep learning models frequently make incorrect predictions with high confidence when presented with test examples that are not well represented in their training dataset. We propose a novel and straightforward approach to estimate…
In dynamic and crowded environments, realistic pedestrian trajectory prediction remains a challenging task due to the complex nature of human motion and the mutual influences among individuals. Deep learning models have recently achieved…
Estimating the temperature and metal abundance of the intracluster and the intragroup media is crucial to determine their global metal content and to determine fundamental cosmological parameters. When a spatially resolved temperature or…
The helium I line intensity ratio (LIR) method is used to measure the electron density ($n_e$) and temperature ($T_e$) of fusion-relevant plasmas. Although the collisional-radiative model (CRM) has been used to predict $n_e$ and $T_e$,…
In-time and accurate assessments of on-road vehicle emissions play a central role in urban air quality and health policymaking. However, official insight is hampered by the Inspection/Maintenance (I/M) procedure conducted in the laboratory…
Climate change and the rapid growth of urban populations are intensifying environmental stresses within cities, making the behavior of urban atmospheric flows a critical factor in public health, energy use, and overall livability. This…
We describe a self-consistent spectrum analysis technique employing non-LTE line formation, which allows precise atmospheric parameters of massive stars to be derived: 1sigma-uncertainties as low as ~1% in effective temperature and…
In this report we analyze the feasibility of ionospheric monitoring using GNSS technology. The focus will be on the use of LEO GNSS data, exploiting GNSS Reflections, Navigation and Occultation TEC measurements. In order to attack this…
Accurate estimation of wildlife density is vital for effective ecological monitoring, conservation, and management. Line transect sampling, a central technique in distance sampling, relies on selecting an appropriate detection function to…
In this paper we develop a kernel density estimation (KDE) approach to modeling and forecasting recurrent trajectories on a compact manifold. For the purposes of this paper, a trajectory is a sequence of coordinates in a phase space defined…
The increasingly populated cities of the 21st Century face the challenge of being sustainable and resilient spaces for their inhabitants. However, climate change, among other problems, makes these objectives difficult to achieve. The Urban…
We consider inhomogeneous spherically symmetric models based on the Lema\^{i}tre-Tolman-Bondi (LTB) metric, assuming as its source an interactive mixture of ordinary baryonic matter, cold dark matter and dark energy with a coupling term…
Multithreshold Entropy Linear Classifier (MELC) is a density based model which searches for a linear projection maximizing the Cauchy-Schwarz Divergence of dataset kernel density estimation. Despite its good empirical results, one of its…
Water (H2O) ice is an important solid constituent of many astrophysical environments. To comprehend the role of such ices in the chemistry and evolution of dense molecular clouds and comets, it is necessary to understand the freeze-out,…