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Articles 2131 - 2160 of 291657
Full-Text Articles in Physical Sciences and Mathematics
Towards Efficient Continual Learning: From Memory Optimization To Foundation Models, Zilin Luo
Towards Efficient Continual Learning: From Memory Optimization To Foundation Models, Zilin Luo
Dissertations and Theses Collection (Open Access)
Continual learning, also termed lifelong learning, enables machine learning models to incrementally acquire new knowledge while mitigating the degradation of previously learned information—a capability essential for adapting to dynamic, real-world data environments. This dissertation investigates the core challenges of continual learning and extends its application to enhancing training efficiency in the era of foundation models. The first part of this dissertation addresses the constraints of few-shot exemplar storage with a novel compression framework. While leveraging class activation maps to downsample non-discriminative pixels, we introduce an adaptive masking model, optimized through bilevel optimization, to store more exemplars efficiently. The second part …
Constraints On Axion-Like Particles From Ultra-High-Energy Observations Of M87 With The Hawc Observatory, R. Alfaro, C. Alvarez, A. Andrés, E. Anita-Rangel, M. Araya, J. C. Arteaga-Velázquez, N. Ghosh, M. Najafi, Et Al.
Constraints On Axion-Like Particles From Ultra-High-Energy Observations Of M87 With The Hawc Observatory, R. Alfaro, C. Alvarez, A. Andrés, E. Anita-Rangel, M. Araya, J. C. Arteaga-Velázquez, N. Ghosh, M. Najafi, Et Al.
Michigan Tech Publications
In this work, we perform an indirect search for axion-like particles (ALPs) through their hypothesized mixing with photons in the presence of magnetic fields. ALPs are a well-motivated dark-matter candidate class, and the photon-ALP conversion mechanism provides a unique channel to constrain their mass and coupling constant using very-high-energy gamma-ray observations. The photon-ALP mixing could alter the observed gamma-ray spectrum from extragalactic sources by effectively reducing the apparent attenuation due to extragalactic-background-light absorption. We analyze 7.5 years of data from the High Altitude Water Cherenkov (HAWC) Observatory, targeting the nearby radio galaxy M87. This source is located within the Virgo …
What's The Big Picture? Capturing All The Companions To The Lowest-Mass Stars, Eliot Vrijmoet, K. Ward-Duong, Susan Niu, Alette Matthews, Todd Henry, Lucy Williams
What's The Big Picture? Capturing All The Companions To The Lowest-Mass Stars, Eliot Vrijmoet, K. Ward-Duong, Susan Niu, Alette Matthews, Todd Henry, Lucy Williams
Astronomy: Faculty Publications
The M dwarfs are frequently orbited by low-mass stars and terrestrial planets, yet rarely by the brown dwarfs and Jovian planets between those mass regimes. The collective orbital architectures of those unusual substellar companions thus present a valuable opportunity to learn about those objects' formation, dynamical evolution, and original circumstellar environments. Accessing those parameter spaces, however, requires complementary observing techniques to truly map orbits and thoroughly assess the masses and mass ratios that occur. Here we present our pilot study of five M dwarfs with strong evidence of potentially substellar companions, combining 20+ years of astrometric monitoring from RECONS with …
Measuring And Modeling The Circumplanetary Dust Disk Around The Planetary-Mass Companion Sr 12 C, Nathaniel Kerman, Kimberly Ward-Duong, Mickael Bonnefoy, Kj Soto Villarreal, Nicole Arulanantham, Benoît Tabone, Catherine Dougados, Laurent Pueyo, Mathilde Mâlin, Claire Finley, Et Al
Measuring And Modeling The Circumplanetary Dust Disk Around The Planetary-Mass Companion Sr 12 C, Nathaniel Kerman, Kimberly Ward-Duong, Mickael Bonnefoy, Kj Soto Villarreal, Nicole Arulanantham, Benoît Tabone, Catherine Dougados, Laurent Pueyo, Mathilde Mâlin, Claire Finley, Et Al
Astronomy: Faculty Publications
SR 12 c, a planetary mass companion in a ~1000 au orbit around its binary host, is one of only three planetary mass objects surrounded by an ALMA-detected circumplanetary disk (CPD). CPDs with different masses and orbits provide crucial laboratories to study substellar formation: the structure and mass of CPDs govern planet formation timescales and may distinguish between formation mechanisms, while dust composition and grain sizes ultimately affect atmospheric metallicity and satellites. CPD properties can also be compared against better-understood brown dwarf and low-mass star disks to test how disk properties scale with central object mass at the low-mass extreme. …
Real-Time Simulation Of Bio-Luminescent Light Propagation Using Compute Shaders Within Unreal Engine, Jaden D. Halevi
Real-Time Simulation Of Bio-Luminescent Light Propagation Using Compute Shaders Within Unreal Engine, Jaden D. Halevi
Computer Science Senior Theses
Presented in this paper is a GPU-native approach to interactive fluid simulation within Unreal Engine 5. The system, BioFluidSim, implements an incompressible Navier-Stokes solver using Unreal’s Niagara Grid2D compute shader pipeline, with a modular biological emission output stage parameterized from experimentally measured Lingulodinium polyedrum bioluminescence behavior. The system is evaluated against FluidNinja Live, a commercially available fragment shader fluid implementation, as a performance baseline. Beyond performance, BioFluidSim offers greater physical fidelity than the fragment shader baseline. Helmholtz–Hodge pressure projection enforces a divergence-free velocity field at runtime, a physical constraint approximated but not enforced by fragment shader approaches. The biological emission …
Mgrre_Thinsections_Mgrre-101_6, Mgrre
Mgrre_Thinsections_Mgrre-101_20, Mgrre
Mgrre_Thinsections_Mgrre-101_22, Mgrre
Mgrre_Thinsections_Mgrre-101_24, Mgrre
Mgrre_Thinsections_Mgrre-101_20, Mgrre
Mgrre_Thinsections_Mgrre-102_1, Mgrre
A Systematic Review Of Intrusion Detection Systems For Internet Of Medical Things: Performance, Efficiency, Explainability, And Generalization, Oswald Adohinzin, Youssef Harrath
A Systematic Review Of Intrusion Detection Systems For Internet Of Medical Things: Performance, Efficiency, Explainability, And Generalization, Oswald Adohinzin, Youssef Harrath
Research & Publications
The Internet of Medical Things (IoMT) has transformed health care delivery through medical devices, remote patient monitoring, and real-time clinical decision support. However, the proliferation of IoMT devices introduces security vulnerabilities that put patient safety and data privacy at risk. Intrusion Detection Systems (IDS) have emerged as essential components for protecting IoMT networks from cyberattacks. This article presents a systematic review of IoMT-IDS research, analyzing 53 high-quality papers published between 2020 and 2025, identified through database searches spanning 2016–2025 across IEEE Xplore, Springer, ScienceDirect, and ACM Digital Library. We organize the literature through a comprehensive taxonomy spanning classical machine learning …
A Machine Learning Framework For Residential District Cooling: Forecasting Consumption, Explaining Drivers, And Evaluating Decarbonization Pathways, Kadhim Hayawi, Husna Maliakkal, Neethu Venugopal, Thanveer Musthafa Hussain, Gomathi Bhavani Rajagopalan
A Machine Learning Framework For Residential District Cooling: Forecasting Consumption, Explaining Drivers, And Evaluating Decarbonization Pathways, Kadhim Hayawi, Husna Maliakkal, Neethu Venugopal, Thanveer Musthafa Hussain, Gomathi Bhavani Rajagopalan
All Works
District Cooling Systems (DCS) in the Middle East, while energy-efficient, are significant contributors to carbon emissions. This study introduces a novel framework to decarbonize DCS operations by integrating predictive machine learning, explainable AI (XAI), and renewable energy planning, all grounded in extensive real-world data. Leveraging a unique dataset from 59 residential buildings in the UAE—including energy consumption, climate variables, and building features—we developed a high-fidelity cooling load forecasting model. Following a rigorous chronological validation methodology, the Random Forest model was identified as the most robust, achieving a strong performance (R2 = 0.8256, RMSE = 11,668.31). Outdoor temperature was confirmed …
Mgrre_Thinsections_Mgrre-101_3, Mgrre
Mgrre_Thinsections_Mgrre-101_4, Mgrre
Mgrre_Thinsections_Mgrre-101_5, Mgrre
Mgrre_Thinsections_Mgrre-101_7, Mgrre
Mgrre_Thinsections_Mgrre-101_9, Mgrre
Mgrre_Thinsections_Mgrre-101_10, Mgrre
Mgrre_Thinsections_Mgrre-101_14, Mgrre
Mgrre_Thinsections_Mgrre-101_15, Mgrre
Mgrre_Thinsections_Mgrre-101_13, Mgrre
Mgrre_Thinsections_Mgrre-101_19, Mgrre
Mgrre_Thinsections_Mgrre-101_17, Mgrre
Mgrre_Thinsections_Mgrre-101_21, Mgrre
Mgrre_Thinsections_Mgrre-101_25, Mgrre
Mgrre_Thinsections_Mgrre-101_2, Mgrre
Mgrre_Thinsections_Mgrre-101_3, Mgrre