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Aims. The derivation of spectroscopic parameters for M dwarf stars is very important in the fields of stellar and exoplanet characterization. The goal of this work is the creation of an automatic computational tool, able to derive quickly…

Solar and Stellar Astrophysics · Physics 2020-04-08 A. Antoniadis-Karnavas , S. G. Sousa , E. Delgado-Mena , N. C. Santos , G. D. C. Teixeira , V. Neves

The current availability of soil moisture data over large areas comes from satellite remote sensing technologies (i.e., radar-based systems), but these data have coarse resolution and often exhibit large spatial information gaps. Where data…

Machine Learning · Computer Science 2019-05-22 Danny Rorabaugh , Mario Guevara , Ricardo Llamas , Joy Kitson , Rodrigo Vargas , Michela Taufer

We examine the selection characteristics of infrared and sub-mm surveys with IRAS, Spitzer, BLAST, Herschel and SCUBA and identify the range of dust temperatures these surveys are sensitive to, for galaxies in the ULIRG luminosity range…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-20 M. Symeonidis , M. J. Page , N. Seymour

M dwarfs are the most abundant stars in the Solar Neighborhood and they are prime targets for searching for rocky planets in habitable zones. Consequently, a detailed characterization of these stars is in demand. The spectral sub-type is…

Instrumentation and Methods for Astrophysics · Physics 2023-04-28 Sirinrat Sithajan , Sukanya Meethong

The present research investigates how to improve Network Intrusion Detection Systems (NIDS) by combining Machine Learning (ML) and Deep Learning (DL) techniques, addressing the growing challenge of cybersecurity threats. A thorough process…

Cryptography and Security · Computer Science 2024-08-16 Surasit Songma , Watcharakorn Netharn , Siriluck Lorpunmanee

The LiDAR-inertial odometry (LIO) and the ultra-wideband (UWB) have been integrated together to achieve driftless positioning in global navigation satellite system (GNSS)-denied environments. However, the UWB may be affected by systematic…

Robotics · Computer Science 2025-05-29 Tisheng Zhang , Man Yuan , Linfu Wei , Yan Wang , Hailiang Tang , Xiaoji Niu

A covariant energy density functional is calibrated using a principled Bayesian statistical framework informed by experimental binding energies and charge radii of several magic and semi-magic nuclei. The Bayesian sampling required for the…

Nuclear Theory · Physics 2022-09-28 Pablo Giuliani , Kyle Godbey , Edgard Bonilla , Frederi Viens , Jorge Piekarewicz

A new dataset of summed neutral N2 and O number density profiles, spanning altitudes between 150 and 400 km, and observed during Northern Winter from 2010 through 2016 is presented. The neutral density profiles are derived from solar…

Earth and Planetary Astrophysics · Physics 2018-02-14 E. M. B. Thiemann , M. Dominique , M. D. Pilinski , F. G. Eparvier

In this study we extract the deep features and investigate the compression of the Mg II k spectral line profiles observed in quiet Sun regions by NASA's IRIS satellite. The data set of line profiles used for the analysis was obtained on…

Unmanned Aircraft Systems (UAS) and satellites are key data sources for precision agriculture, yet each presents trade-offs. Satellite data offer broad spatial, temporal, and spectral coverage but lack the resolution needed for many…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Arif Masrur , Peder A. Olsen , Paul R. Adler , Carlan Jackson , Matthew W. Myers , Nathan Sedghi , Ray R. Weil

The Medium-Resolution Spectrometer (MRS) provides one of the four operating modes of the Mid-Infrared Instrument (MIRI) on board the James Webb Space Telescope (JWST). The MRS is an integral field spectrometer, measuring the spatial and…

Here we present a new method of estimating global variations in outdoor PM$_{2.5}$ concentrations using satellite images combined with ground-level measurements and deep convolutional neural networks. Specifically, new deep learning models…

Image and Video Processing · Electrical Eng. & Systems 2019-06-11 Kris Y. Hong , Pedro O. Pinheiro , Scott Weichenthal

Seasonal forecasting is a crucial task when it comes to detecting the extreme heat and colds that occur due to climate change. Confidence in the predictions should be reliable since a small increase in the temperatures in a year has a big…

Machine Learning · Computer Science 2024-04-05 Busra Asan , Abdullah Akgül , Alper Unal , Melih Kandemir , Gozde Unal

Uncertainty is inherent in modern engineered systems, including cyber-physical systems, autonomous systems, and large-scale software-intensive infrastructures (such as microservice-based systems) operating in dynamic and partially…

Software Engineering · Computer Science 2026-02-26 Man Zhang , Yunyang Li , Tao Yue

Mutual coupling is increasingly important in reconfigurable intelligent surface (RIS)-aided communications, particularly when RIS elements are densely integrated in applications such as holographic communications. This paper experimentally…

Signal Processing · Electrical Eng. & Systems 2024-07-02 Pinjun Zheng , Ruiqi Wang , Atif Shamim , Tareq Y. Al-Naffouri

Millimeter wave (mmWave) radars have attracted significant attention from both academia and industry due to their capability to operate in extreme weather conditions. However, they face challenges in terms of sparsity and noise…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Ruibin Zhang , Donglai Xue , Yuhan Wang , Ruixu Geng , Fei Gao

In this work, we investigate neutron stars (NSs) in the strong field regime within the framework of symmetric teleparallel $f(Q)$ gravity, considering three representative models: linear, logarithmic, and exponential. While Bayesian studies…

General Relativity and Quantum Cosmology · Physics 2026-02-19 Sneha Pradhan , N. K. Patra , Kai Zhou , P. K. Sahoo

Full-complexity Earth system models (ESMs) are computationally very expensive, limiting their use in exploring the climate outcomes of multiple emission pathways. More efficient emulators that approximate ESMs can directly map emissions…

Machine Learning · Computer Science 2025-10-01 Björn Lütjens , Raffaele Ferrari , Duncan Watson-Parris , Noelle Selin

A comparison of two thermodynamic models is presented using the water-cesium nitrate system as case study. Both models were able to model the thermodynamic properties such as the osmotic coefficient, vapor pressure, mean activity…

Soft Condensed Matter · Physics 2024-01-22 Mouad Arrad , Kaj Thomsen , Simon Müller , Irina Smirnova
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