Tootfinder

Die ePetition 179095 an den Bundestag aus dem Bereich Allgemeine Rüstungsangelegenheiten mit dem Titel
Beschaffung und Betrieb von Waffensystemen
kann bis zum Dienstag 15. Juli 2025 01:00 UTC mitgezeichnet werden und lautet
Mit der Petition wird gefordert, dass alle Waffensysteme, die für die Bundeswehr zukünftig beschafft werden, so ausgelegt sein müssen, dass sie von Deutschland ohne Unterstützung von Aussen betrieben, gewartet und mit Munition versorgt werden können. Bes…

today's "I can't believe I wasted half a hour on this" computer issue: whether Wireshark validates the Ethernet checksum in packets depends on the capture format you're using
.snoop: nope, and ignores all settings including "always check FCS"
.pcap: yep
saving a .snoop file as a .pcap file makes it immediately check all FCS

Also just been watching a kōtare out the window. I startled it by walking past the window and then saw it sitting on a nearby street light. It then flew down and ate a few things off the rain slick road... worms, I'm guessing. Gorgeous to see its blue and gold highlights flitting around.

omg. so because my new modem has a router I can't use my existing router? REALLY? I feel like I should be able to have another router with it's own settings.

Extended c-differential distinguishers of full 9 and reduced-round Kuznyechik cipher
Pantelimon Stanica, Ranit Dutta, Bimal Mandal
https://arxiv.org/abs/2507.02181

Extended c-differential distinguishers of full 9 and reduced-round Kuznyechik cipher
This paper introduces {\em truncated inner $c$-differential cryptanalysis}, a novel technique that for the first time enables the practical application of $c$-differential uniformity to block ciphers. While Ellingsen et al. (IEEE Trans. Inf. Theory, 2020) established the notion of $c$-differential uniformity using $(F(x\oplus a), cF(x))$, a key challenge remained: multiplication by $c$ disrupts the structural properties essential for block cipher analysis, particularly key addition. We resolv…

Numerical methods for fully nonlinear degenerate diffusions
Edgard A. Pimentel, Erc\'ilia Sousa
https://arxiv.org/abs/2506.02595 https://

Numerical methods for fully nonlinear degenerate diffusions
We propose finite difference methods for degenerate fully nonlinear elliptic equations and prove the convergence of the schemes. Our focus is on the pure equation and a related free boundary problem of transmission type. The cornerstone of our argument is a regularisation procedure. It decouples the degeneracy term from the elliptic operator driving the diffusion process. In the free boundary setting, the absence of degenerate ellipticity entails new, genuine difficulties. To bypass them, we re…

Standing Tall: Robust Fall Prediction for Bipedal Robots
Gokul Prabhakaran, Jessy W. Grizzle, M. Eva Mungai
https://arxiv.org/abs/2506.01141 https://

Standing Tall: Robust Fall Prediction for Bipedal Robots
This paper extends the fall prediction algorithm from Mungai et al.(2024) to a real-time/online setting, implemented in both hardware and simulation. This yields results comparable to the offline version, maintaining a zero false positive rate, sufficient lead time, and accurate lead time prediction. Additionally, it achieves a high recovery rate. The paper also evaluates the fall prediction algorithm against omnidirectional faults and introduces an improved algorithm capable of reliably predic…

This https://arxiv.org/abs/2409.04108 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

An Extension of the Adversarial Threat Model in Quantitative Information Flow
In this paper, we propose an extended framework for quantitative information flow (QIF), aligned with the previously proposed core-concave generalization of entropy measures, to include adversaries that use Kolmogorov-Nagumo $f$-mean to infer secrets in a private system. Specifically, in our setting, an adversary uses Kolmogorov-Nagumo $f$-mean to compute its best actions before and after observing the system's randomized outputs. This leads to generalized notions of prior and posterior vulnera…

This https://arxiv.org/abs/2410.11470 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDS_…

Almost Optimal Fully Dynamic $k$-Center Clustering with Recourse
In this paper, we consider the \emph{metric $k$-center} problem in the fully dynamic setting, where we are given a metric space $(V,d)$ evolving via a sequence of point insertions and deletions and our task is to maintain a subset $S \subseteq V$ of at most $k$ points that minimizes the objective $\max_{x \in V} \min_{y \in S}d(x, y)$. We want to design our algorithm so that we minimize its \emph{approximation ratio}, \emph{recourse} (the number of changes it makes to the solution $S$), and \em…