arXiv subjects

Michael Smith

Publications and source records attributed to Michael Smith.

At least 19 recordsLinked to original sources

arXiv2026

Bridging the Gap: A Longitudinal Analysis of Extended Identifiers in the Post-Cookie Era

As third-party cookies fade because of browser restrictions, the online advertising ecosystem is turning to extended identifiers (EIDs) as an alternative. EIDs are persistent user identifiers, such as hashed email addresses, that are employed to link users across domains and devices. This paper presents a 41-month longitudinal study examining EID usage in over 145 million HTTP header bidding requests sent to six major supply-side platforms (SSPs) from 616,539 websites. Our findings show that EIDs are widely used and are becoming increasingly prevalent in the digital advertising ecosystem, reaching 83.76% of studied websites by May 2025. Our analysis of the 18 popular EID providers that account for 99.42% of all transmitted EIDs in our dataset raises concerns about the readiness of EIDs as an alternative to third-party cookie tracking. In terms of accuracy, only one identity provider consistently recognizes and identifies that the visitor is a self-identified bot crawler, and many providers regularly transmit multiple EIDs for the same visitor. We also identify privacy concerns with EIDs, as 12 of the providers create persistent EIDs that can identify the same user across visits, websites, devices, and months. Finally, we found that 16 providers transmit EIDs on EU websites without user consent.

cs.NI↗

arXiv2026

Monophonic Audio Synthesizer Using FPGAs

Signal synthesis is used in every aspect of the electronics world, where sinusoidal waveforms are used to perform functions such as clocking, signal transmission, feedback controls, and other applications. Digital synthesis is the method of approximating sinusoidal waveforms using digital logic, where the waveform is approximated to an accurate degree at a specific frequency which can be either implemented digitally or converted into the analog domain for use elsewhere. This project details the creation of a digital synthesizer commonly used for professional audio applications through the implementation of hardware in an FPGA.

cs.AR↗

arXiv2026

U-SEG: Uncertainty in SEGmentation -- A systematic multi-variable exploration

In this study, we explore in depth a few under-studied topics at the intersection of uncertainty estimation and segmentation. Prior work has shown that the quality of uncertainty estimates can be very sensitive to a range of variables. As one of the main uses of uncertainty estimation is to help identify and deal with prediction errors in practical scenarios, any factors that affect this must be clearly identified. For example, do more challenging domains or different datasets and architectures result in worse performance when using uncertainty estimates? Can prior frames in a video sequence in fact provide useful uncertainty estimates comparable to other approaches? Is it possible to combine uncertainty estimation approaches, taking advantage of sample diversity, to get better estimates? Finally, when might it make sense to use an ensemble-based uncertainty estimate over a deterministic network? We address these questions by creating a framework for and executing a large scale study across many variables such as datasets, backbones, and downstream tasks, for both semantic and panoptic segmentation. We find that a) the more challenging task of panoptic segmentation usually results in worse performance while high performance variance between datasets and backbones indicates that generalization is not guaranteed, b) time series samples can be useful for specific configurations, but in many cases are not worth the cost, c) sample diversity shows the most promise in the downstream task of calibration, but otherwise fails to beat simpler alternatives, d) a deterministic approach is adequate for some downstream tasks, but ensembles allow for significant improvements if the right conditions can be achieved in deployment.

cs.CV↗

arXiv2026

Inconsistencies in Classification of Online News Articles: A Call for Common Standards in Brand Safety Services

This study examines inconsistencies in the brand safety classifications of online news articles by analyzing ratings from three leading brand safety providers, DoubleVerify, Integral Ad Science, and Oracle. We focus on news content because of its central role in public discourse and the significant financial consequences of unsafe classifications in a sector that is already underserved by digital ad spending. By collecting data from 4,352 news articles on 51 domains, our analysis shows that brand safety services often produce conflicting classifications, with significant discrepancies between providers. These inconsistencies can have harmful consequences for both advertisers and publishers, leading to misplaced advertising spending and revenue losses. This research provides critical insights into the shortcomings of the current brand safety landscape. We argue for a standardized and transparent brand safety system to mitigate the harmful effects of the current system on the digital advertising ecosystem.

cs.CY↗

arXiv2025

Using Salient Object Detection to Identify Manipulative Cookie Banners that Circumvent GDPR

The main goal of this paper is to study how often cookie banners that comply with the General Data Protection Regulation (GDPR) contain aesthetic manipulation, a design tactic to draw users' attention to the button that permits personal data sharing. As a byproduct of this goal, we also evaluate how frequently the banners comply with GDPR and the recommendations of national data protection authorities regarding banner designs. We visited 2,579 websites and identified the type of cookie banner implemented. Although 45% of the relevant websites have fully compliant banners, we found aesthetic manipulation on 38% of the compliant banners. Unlike prior studies of aesthetic manipulation, we use a computer vision model for salient object detection to measure how salient (i.e., attention-drawing) each banner element is. This enables the discovery of new types of aesthetic manipulation (e.g., button placement), and leads us to conclude that aesthetic manipulation is more common than previously reported (38% vs 27% of banners). To study the effects of user and/or website location on cookie banner design, we include websites within the European Union (EU), where privacy regulation enforcement is more stringent, and websites outside the EU. We visited websites from IP addresses in the EU and from IP addresses in the United States (US). We find that 13.9% of EU websites change their banner design when the user is from the US, and EU websites are roughly 48.3% more likely to use aesthetic manipulation than non-EU websites, highlighting their innovative responses to privacy regulation.

cs.CY↗

arXiv2025

Observation of the Axion quasiparticle in 2D MnBi$_2$Te$_4$

In 1978, Wilczek and Weinberg theoretically discovered a new boson-the Axion-which is the coherent oscillation of the $\theta$ field in QCD. Its existence can solve multiple fundamental questions including the strong CP problem of QCD and the dark matter. However, its detection is challenging because it has almost no interaction with existing particles. Similar $\theta$ has been introduced to condensed matter and so far studied as a static, quantized value to characterize topology of materials. But the coherent oscillation of $\theta$ in condensed matter is proposed to lead to new physics directly analogous to the high-energy Axion particle, the dynamical Axion quasiparticle (DAQ). In this paper, we present the direct observation of the DAQ. By combining 2D electronic device with ultrafast pump-probe optics, we manage to measure the magnetoelectric coupling $\theta$ ($\theta\propto\alpha$) of 2D MnBi$_2$Te$_4$ with sub-picosecond time-resolution. This allows us to directly observe the DAQ by seeing a coherent oscillation of $\theta$ at ~44 GHz in real time, which is uniquely induced by the out-of-phase antiferromagnetic magnon. Interestingly, in 2D MnBi$_2$Te$_4$, the DAQ arises from the magnon-induced coherent modulation of Berry curvature. Such ultrafast control of quantum wavefunction can be generalized to manipulate Berry curvature and quantum metric of other materials in ultrafast time-scale. Moreover, the DAQ enables novel quantum physics such as Axion polariton and electric control of ultrafast spin polarization, implying applications in unconventional light-matter interaction and coherent antiferromagnetic spintronics. Beyond condensed matter, the DAQ can serve as a detector of the dark matter Axion particle. We estimate the detection frequency range and sensitivity in the critically-lacking meV regime, contributing to one of the most challenging questions in fundamental physics.

cond-mat.mes-hall↗

arXiv2024

The BRAVO Semantic Segmentation Challenge Results in UNCV2024

We propose the unified BRAVO challenge to benchmark the reliability of semantic segmentation models under realistic perturbations and unknown out-of-distribution (OOD) scenarios. We define two categories of reliability: (1) semantic reliability, which reflects the model's accuracy and calibration when exposed to various perturbations; and (2) OOD reliability, which measures the model's ability to detect object classes that are unknown during training. The challenge attracted nearly 100 submissions from international teams representing notable research institutions. The results reveal interesting insights into the importance of large-scale pre-training and minimal architectural design in developing robust and reliable semantic segmentation models.

cs.CV↗

arXiv2023

Uncertainty estimation in Deep Learning for Panoptic segmentation

As deep learning-based computer vision algorithms continue to advance the state of the art, their robustness to real-world data continues to be an issue, making it difficult to bring an algorithm from the lab to the real world. Ensemble-based uncertainty estimation approaches such as Monte Carlo Dropout have been successfully used in many applications in an attempt to address this robustness issue. Unfortunately, it is not always clear if such ensemble-based approaches can be applied to a new problem domain. This is the case with panoptic segmentation, where the structure of the problem and architectures designed to solve it means that unlike image classification or even semantic segmentation, the typical solution of using a mean across samples cannot be directly applied. In this paper, we demonstrate how ensemble-based uncertainty estimation approaches such as Monte Carlo Dropout can be used in the panoptic segmentation domain with no changes to an existing network, providing both improved performance and more importantly a better measure of uncertainty for predictions made by the network. Results are demonstrated quantitatively and qualitatively on the COCO, KITTI-STEP and VIPER datasets.

cs.CV↗

arXiv2023

Current-Induced Spin Accumulation and Magnetoresistance in Chiral Semimetals

Weyl fermions possess the property of spin-momentum locking: the expectation value of the spin is parallel or antiparallel to the momentum at any given point in the Brillouin zone in the vicinity of a Weyl node. This is a direct consequence of the fact that Weyl nodes are monopoles of the Berry curvature, and in this sense an expression of the nontrivial Weyl electronic structure topology. Thanks to this property, an isolated Weyl node produces a large spin accumulation in response to a charge current, $\hbar/2$ per electron, similar to surface states of time-reversal invariant topological insulators. However, in bulk Weyl semimetals, the nodes must occur in pairs of opposite chirality and, when the nodes are at the same energy, the effect cancels out. Here we show that this cancellation is avoided in chiral semimetals, in which Weyl nodes of opposite chirality occur at different energies due to broken mirror symmetry. We find that the spin accumulation is maximized when the Fermi energy coincides with one of the nodes in a pair and reaches the same value as for an isolated node in this case. Moreover, we demonstrate the existence of a distinct magnetoresistance mechanism, closely related to this current-induced spin accumulation.

cond-mat.mes-hall↗

arXiv2022

XMM-Newton

The X-ray Multi-mirror Mission (XMM-Newton) provides simultaneous non-dispersive spectroscopic X-ray imaging and timing, medium resolution dispersive X-ray spectroscopy and optical/UV imaging, spectroscopy and timing. In combination, the imaging cameras offer an effective area over the energy range from 150 eV to 12 keV of up to 2500 cm$^2$ at 1.5 keV and $\sim$1800 cm$^2$ at 5 keV. The gratings cover an energy range from 0.4 keV to 2.2 keV with a combined effective area of up to 120 cm$^2$ at 0.8 keV. XMM-Newton offers unique opportunities for a wide variety of sensitive X-ray observations accompanied by simultaneous optical/UV measurements. The majority of XMM-Newton's observing time is made available to the astronomical community by peer-reviewed Announcements of Opportunity. The scientific exploitation of XMM-Newton data is aided by an observatory-class X-ray facility which provides analysis software, pipeline processing, calibration and catalogue generation. Around 380 refereed papers based on XMM-Newton data are published each year with a high fraction of papers reporting transformative scientific results.

astro-ph.IM↗

arXiv2022

Adjoint-aided inference of Gaussian process driven differential equations

Linear systems occur throughout engineering and the sciences, most notably as differential equations. In many cases the forcing function for the system is unknown, and interest lies in using noisy observations of the system to infer the forcing, as well as other unknown parameters. In differential equations, the forcing function is an unknown function of the independent variables (typically time and space), and can be modelled as a Gaussian process (GP). In this paper we show how the adjoint of a linear system can be used to efficiently infer forcing functions modelled as GPs, using a truncated basis expansion of the GP kernel. We show how exact conjugate Bayesian inference for the truncated GP can be achieved, in many cases with substantially lower computation than would be required using MCMC methods. We demonstrate the approach on systems of both ordinary and partial differential equations, and show that the basis expansion approach approximates well the true forcing with a modest number of basis vectors. Finally, we show how to infer point estimates for the non-linear model parameters, such as the kernel length-scales, using Bayesian optimisation.

stat.ML↗

arXiv2022

Blocked or Broken? Automatically Detecting When Privacy Interventions Break Websites

A core problem in the development and maintenance of crowd-sourced filter lists is that their maintainers cannot confidently predict whether (and where) a new filter list rule will break websites. This is a result of enormity of the Web, which prevents filter list authors from broadly understanding the impact of a new blocking rule before they ship it to millions of users. The inability of filter list authors to evaluate the Web compatibility impact of a new rule before shipping it severely reduces the benefits of filter-list-based content blocking: filter lists are both overly-conservative (i.e. rules are tailored narrowly to reduce the risk of breaking things) and error-prone (i.e. blocking tools still break large numbers of sites). To scale to the size and scope of the Web, filter list authors need an automated system to detect when a new filter rule breaks websites, before that breakage has a chance to make it to end users. In this work, we design and implement the first automated system for predicting when a filter list rule breaks a website. We build a classifier, trained on a dataset generated by a combination of compatibility data from the EasyList project and novel browser instrumentation, and find it is accurate to practical levels (AUC 0.88). Our open source system requires no human interaction when assessing the compatibility risk of a proposed privacy intervention. We also present the 40 page behaviors that most predict breakage in observed websites.

cs.CR↗

arXiv2021

Informal Science Education and Career Advancement

This document supports a proposed APS statement that encourages academic, research, and other institutions to add the participation in informal science education activities to the criteria they use for hiring and career advancement decisions. There is a prevalent attitude that the time spent by a researcher on these activities takes time away from research efforts that are more valued by their peers and their institution. To change this mindset, we enumerate the many benefits of informal science education activities to the public, to researchers, to their institutions, and to the field of physics. We also suggest aspects of these activities that may be considered by institutions in evaluating informal educational efforts for recruitment and career advancement decisions.

physics.soc-ph↗

arXiv2021

Observation of coexisting weak localization and superconducting fluctuations in strained Sn1-xInxTe thin films

Topological superconductors have attracted tremendous excitement as they are predicted to host Majorana zero modes that can be utilized for topological quantum computing. Candidate topological superconductor Sn1-xInxTe thin films (0<x<0.3) grown by molecular beam epitaxy and strained in the (111) plane are shown to host three coexisting quantum effects: localization, antilocalization and superconducting fluctuations above the critical temperature Tc. An analysis of the normal state magnetoresistance reveals these effects. Weak localization is consistently observed in superconducting samples, indicating that superconductivity originates dominantly from trivial valence band states that may be strongly spin-orbit split. A large enhancement of the conductivity is observed above Tc, indicating that quantum coherent quasiparticle effects coexist with superconducting fluctuations. Our results motivate a re-examination of the debated pairing symmetry of this material when subjected to quantum confinement and lattice strain.

cond-mat.supr-con↗

arXiv2019

Numerical simulations of wind-driven protoplanetary nebulae. I. near-infrared emission

To understand how the circumstellar environments of post-AGB stars develop into planetary nebulae, we initiate a systematic study of 2D axisymmetric hydrodynamic simulations of protoplanetary nebula (pPN) with a modified ZEUS code. The aim of this first work is to compare the structure of prolate ellipsoidal winds into a stationary ambient medium where both media can be either atomic or molecular. We specifically model the early twin-shock phase which generates a decelerating shell. A thick deformed and turbulent shell grows when an atomic wind expands into an atomic medium. In all other cases, the interaction shell region fragments into radial protrusions due to molecular cooling and chemistry. The resulting fingers eliminate any global slip parallel to the shell surface. This rough surface implies that weak shocks are prominent in the excitation of the gas despite the fast speed of advance. This may explain why low excitation molecular hydrogen is found towards the front of elliptical pPN. We constrain molecular dissociative fractions and timescales of fast $\mathrm H_2$ winds and the pPN lifetime with wind densities $\mathrm{\sim10^{5}cm^{-3}}$ and shock speeds of $\mathrm{80\sim200\,km\,s^{-1}}$. We identify a variety of stages associated with thermal excitation of H$_2$ near-infrared emission. Generated line emission maps and position-velocity diagrams enable a comparison and distinction with post-AGB survey results. The $\mathrm{1\to0 \, S(1)}$ $\&$ $\mathrm{2\to1 \, S(1)}$ lines are lobe-dominated bows rather than bipolar shells.

astro-ph.SR↗

arXiv2019

Numerical simulations of wind-driven protoplanetary nebulae. II. signatures of atomic emission

We follow up on our systematic study of axisymmetric hydrodynamic simulations of protoplanetary nebula. The aim of this work is to generate the atomic analogues of the $\mathrm H_2$ near-infrared models of Paper I with the ZEUS code modified to include molecular and atomic cooling routines. We investigate stages associated with strong $\mathrm {[Fe II]}$ 1.64 $\mathrm {μm}$ and $\mathrm {[S II]}$ 6716 Å forbidden lines, the $\mathrm {[O I]}$ 6300 Å airglow line, and H$\mathrm α\, 6563$ Å emission. We simulate ($\mathrm{80\sim200\,km\,s^{-1}}$) dense ($\mathrm{\sim10^{5}\,cm^{-3}}$) outflows expanding into a stationary ambient medium. In the case of an atomic wind interacting with an atomic medium, a decelerating advancing turbulent shell thickens with time. This contrasts with all other cases where a shell fragments into a multitude of cometary-shaped protrusions with weak oblique shocks as the main source of gas excitation. We find that the atomic wind-ambient simulation leads to considerably higher excitation, stronger peak and integrated atomic emission as the nebula expands. The weaker emission when one component is molecular is due to the shell fragmentation into fingers so that the shock surface area is increased and oblique shocks are prevalent. Position-velocity diagrams indicate that the atomic-wind model may be most easy to distinguish with more emission at higher radial velocities. With post-AGB winds and shells often highly obscured and the multitude of configurations that are observed, this study suggests and motivates selection criteria for new surveys.

astro-ph.SR↗

arXiv2018

Amanuensis: The Programmer's Apprentice

This document provides an overview of the material covered in a course taught at Stanford in the spring quarter of 2018. The course draws upon insight from cognitive and systems neuroscience to implement hybrid connectionist and symbolic reasoning systems that leverage and extend the state of the art in machine learning by integrating human and machine intelligence. As a concrete example we focus on digital assistants that learn from continuous dialog with an expert software engineer while providing initial value as powerful analytical, computational and mathematical savants. Over time these savants learn cognitive strategies (domain-relevant problem solving skills) and develop intuitions (heuristics and the experience necessary for applying them) by learning from their expert associates. By doing so these savants elevate their innate analytical skills allowing them to partner on an equal footing as versatile collaborators - effectively serving as cognitive extensions and digital prostheses, thereby amplifying and emulating their human partner's conceptually-flexible thinking patterns and enabling improved access to and control over powerful computing resources.

q-bio.NC↗

arXiv2018

The WIYN One Degree Imager in 2018: An Extended 30-Detector Focal Plane

We report on the upgraded One Degree Imager (ODI) at the WIYN 3.5 meter telescope at the Kitt Peak Observatory after the focal plane was expanded by an additional seventeen detectors in spring 2015. The now thirty Orthogonal Transfer Array CCD detectors provide a total field of view of 40' x 48' on the sky. The newly added detectors underwent a design revision to mitigate reduced charge transfer efficiency under low light conditions. We discuss the performance of the focal plane and challenges in the photometric calibration of the wide field of view, helped by the addition of telescope baffles. In a parallel project, we upgraded the instrument's three filter arm mechanisms, where a degrading worm-gear mechanism was replaced by a chain drive that is operating faster and with high reliability. Three more filters, a u' band and two narrow band filters were added to the instrument's complement, with two additional narrow band filters currently in procurement (including an H-alpha filter). We review the lessons learned during nearly three years of operating the instrument in the observatory environment and discuss infrastructure upgrades that were driven by ODI's needs.

astro-ph.IM↗