Tootfinder

If you are a US citizen holding a #HamRadio license, please add your name to #AmateurRadio antennas with bills in both the house and senate,…

Robust Small Methane Plume Segmentation in Satellite Imagery
Khai Duc Minh Tran, Hoa Van Nguyen, Aimuni Binti Muhammad Rawi, Hareeshrao Athinarayanarao, Ba-Ngu Vo
https://arxiv.org/abs/2508.16282

Robust Small Methane Plume Segmentation in Satellite Imagery
This paper tackles the challenging problem of detecting methane plumes, a potent greenhouse gas, using Sentinel-2 imagery. This contributes to the mitigation of rapid climate change. We propose a novel deep learning solution based on U-Net with a ResNet34 encoder, integrating dual spectral enhancement techniques (Varon ratio and Sanchez regression) to optimise input features for heightened sensitivity. A key achievement is the ability to detect small plumes down to 400 m2 (i.e., for a single pi…

Does Embodiment Matter to Biomechanics and Function? A Comparative Analysis of Head-Mounted and Hand-Held Assistive Devices for Individuals with Blindness and Low Vision
Gaurav Seth, Hoa Pham, Giles Hamilton-Fletcher, Charles Leclercq, John-Ross Rizzo
https://arxiv.org/abs/2509.18391

Does Embodiment Matter to Biomechanics and Function? A Comparative Analysis of Head-Mounted and Hand-Held Assistive Devices for Individuals with Blindness and Low Vision
Visual assistive technologies, such as Microsoft Seeing AI, can improve access to environmental information for persons with blindness or low vision (pBLV). Yet, the physical and functional implications of different device embodiments remain unclear. In this study, 11 pBLV participants used Seeing AI on a hand-held smartphone and on a head-mounted ARx Vision system to perform six activities of daily living, while their movements were captured with Xsens motion capture. Functional outcomes inclu…

Vacuum birefringence in the polarized X-ray emission of a radio magnetar
Rachael E. Stewart, Hoa Dinh Thi, George Younes, Marcus E. Lower, Matthew G. Baring, Michela Negro, Fernando Camilo, Joel B. Coley, Alice K. Harding, Wynn C. G. Ho, Chin-Ping Hu, Philip Kaaret, Paul Scholz, Alex Van Kooten, Zorawar Wadiasingh
https://arxiv.org/abs/250…

Vacuum birefringence in the polarized X-ray emission of a radio magnetar
The quantum electrodynamics (QED) theory predicts that the quantum vacuum becomes birefringent in the presence of ultra-strong magnetic fields -- a fundamental effect yet to be directly observed. Magnetars, isolated neutron stars with surface fields exceeding $10^{14}$~G, provide unique astrophysical laboratories to probe this elusive prediction. Here, we report phase- and energy-resolved X-ray polarization measurements of the radio-emitting magnetar 1E 1547.0-5408 obtained with the Imaging X-r…

DX Engineering invited John Robert Stratton N5AUS, ARRL West Gulf Director, to give more details about why this new attempt to give #HamRadio similar rights already given for broadcast antennas (the FCC's Over-the-Air Reception Devices, or "OTARD", rule) has a real chance to pass this time.
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An LLM-based multi-agent framework for agile effort estimation
Thanh-Long Bui, Hoa Khanh Dam, Rashina Hoda
https://arxiv.org/abs/2509.14483 https://arxiv.o…

An LLM-based multi-agent framework for agile effort estimation
Effort estimation is a crucial activity in agile software development, where teams collaboratively review, discuss, and estimate the effort required to complete user stories in a product backlog. Current practices in agile effort estimation heavily rely on subjective assessments, leading to inaccuracies and inconsistencies in the estimates. While recent machine learning-based methods show promising accuracy, they cannot explain or justify their estimates and lack the capability to interact with…

You know if you want to gatekeep and cosplay HOA on Mastodon, just make your own server and then pull the Ethernet plug

An internet hoaxer claims responsibility for creating fake freelance journalist Margaux Blanchard, whose AI-generated articles were published by six outlets (Charlotte Tobitt/Press Gazette)
https://pressgazette.co.uk/news/ai-hoaxer-a-fake-x-accou…

AI hoaxer, a fake X account and the case of Margaux Blanchard
Who is Margaux Blanchard? Her true identity remains unclear despite the emergence of an AI hoaxer claiming responsibility.

Today:
⁃ New interview video promo for our rapper finished, uploaded and distributed
⁃ Rough cut of the Beach Boys set we played with Matt Jardine completed and uploaded to everyone
⁃ Marketing call with clients for an upcoming gig to determine what I can create for them
⁃ Had an HOA legal matter rescheduled *by the court days out* because *they are exepecting widespread civil unrest*
⁃ Actually practiced guitar for half an hour
⁃ Watched a Dann Huff video 😎

MobilityDuck: Mobility Data Management with DuckDB
Nhu Ngoc Hoang, Ngoc Hoa Pham, Viet Phuong Hoang, Esteban Zim\'anyi
https://arxiv.org/abs/2510.07963 https://

MobilityDuck: Mobility Data Management with DuckDB
The analytics of spatiotemporal data is increasingly important for mobility analytics. Despite extensive research on moving object databases (MODs), few systems are ready on production or lightweight enough for analytics. MobilityDB is a notable system that extends PostgreSQL with spatiotemporal data, but it inherits complexity of the architecture as well. In this paper, we present MobilityDuck, a DuckDB extension that integrates the MEOS library to provide support spatiotemporal and other temp…

BoMGene: Integrating Boruta-mRMR feature selection for enhanced Gene expression classification
Bich-Chung Phan, Thanh Ma, Huu-Hoa Nguyen, Thanh-Nghi Do
https://arxiv.org/abs/2510.00907

BoMGene: Integrating Boruta-mRMR feature selection for enhanced Gene expression classification
Feature selection is a crucial step in analyzing gene expression data, enhancing classification performance, and reducing computational costs for high-dimensional datasets. This paper proposes BoMGene, a hybrid feature selection method that effectively integrates two popular techniques: Boruta and Minimum Redundancy Maximum Relevance (mRMR). The method aims to optimize the feature space and enhance classification accuracy. Experiments were conducted on 25 publicly available gene expression data…

Deep Learning Reconstruction of Tropical Cyclogenesis in the Western North Pacific from Climate Reanalysis Dataset
Duc-Trong Le, Tran-Binh Dang, Anh-Duc Hoang Gia, Duc-Hai Nguyen, Minh-Hoa Tien, Xuan-Truong Ngo, Quang-Trung Luu, Quang-Lap Luu, Tai-Hung Nguyen, Thanh T. N. Nguyen, Chanh Kieu
https://arxiv.org/abs/2510.06118

Deep Learning Reconstruction of Tropical Cyclogenesis in the Western North Pacific from Climate Reanalysis Dataset
This study presents a deep learning (DL) architecture based on residual convolutional neural networks (ResNet) to reconstruct the climatology of tropical cyclogenesis (TCG) in the Western North Pacific (WNP) basin from climate reanalysis datasets. Using different TCG data labeling strategies and data enrichment windows for the NASA Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA2) dataset during the 1980-2020 period, we demonstrate that ResNet can reasonably rep…

Replaced article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- A locking-free isogeometric thin shell formulation based on higher order accurate diagonalized st...
Thi-Hoa Nguyen, Ren\'e R. Hiemstra, Dominik Schillinger

Smart Contract Adoption in Derivative Markets under Bounded Risk: An Optimization Approach
Jinho Cha, Long Pham, Thi Le Hoa Vo, Jaeyoung Cho, Jaejin Lee
https://arxiv.org/abs/2510.07006

Smart Contract Adoption in Derivative Markets under Bounded Risk: An Optimization Approach
This study develops and analyzes an optimization model of smart contract adoption under bounded risk, linking structural theory with simulation and real-world validation. We examine how adoption intensity alpha is structurally pinned at a boundary solution, invariant to variance and heterogeneity, while profitability and service outcomes are variance-fragile, eroding under volatility and heavy-tailed demand. A sharp threshold in the fixed cost parameter A3 triggers discontinuous adoption collap…

Monte Carlo Simulations of Polarized Radiative Transfer in Neutron Star Atmospheres
Hoa Dinh Thi, Matthew G. Baring, Kun Hu, Alice K. Harding, Joseph A. Barchas
https://arxiv.org/abs/2508.00225

Monte Carlo Simulations of Polarized Radiative Transfer in Neutron Star Atmospheres
Soft X-ray emission from neutron stars affords powerful diagnostic tools for uncovering their surface and interior properties, as well as their geometric configurations. In the atmospheres of neutron stars, the presence of magnetic fields alters the photon-electron scattering cross sections, resulting in non-trivial angular dependence of intensity and polarization of the emergent signals. This paper presents recent developments of our Monte Carlo simulation, MAGTHOMSCATT, which tracks the compl…

Inverse Portfolio Optimization with Synthetic Investor Data: Recovering Risk Preferences under Uncertainty
Jinho Cha, Long Pham, Thi Le Hoa Vo, Jaeyoung Cho, Jaejin Lee
https://arxiv.org/abs/2510.06986

Inverse Portfolio Optimization with Synthetic Investor Data: Recovering Risk Preferences under Uncertainty
This study develops an inverse portfolio optimization framework for recovering latent investor preferences including risk aversion, transaction cost sensitivity, and ESG orientation from observed portfolio allocations. Using controlled synthetic data, we assess the estimator's statistical properties such as consistency, coverage, and dynamic regret. The model integrates robust optimization and regret-based inference to quantify welfare losses under preference misspecification and market shocks.…