Tootfinder

🇺🇦 Auf radioeins läuft...
Katy J Pearson:
🎵 Those Goodbyes
#NowPlaying #KatyJPearson
https://katyjpearson.bandcamp.com/track/those-goodbyes
https://open.spotify.com/track/5aDqrsPqasMR2gdtYYMnbH

Here's a Thinking Machines-inspired text animation for your terminal https://gist.githubusercontent.com/zeroeth/c0b83e7a856d01c9db46ee6d414a1654/raw/12ed0182b1d469a9ee861fb269ff6c02c7d3cee6/mode5.c

Higher-Order Graph Databases
Maciej Besta, Shriram Chandran, Jakub Cudak, Patrick Iff, Marcin Copik, Robert Gerstenberger, Tomasz Szydlo, J\"urgen M\"uller, Torsten Hoefler
https://arxiv.org/abs/2506.19661

Higher-Order Graph Databases
Recent advances in graph databases (GDBs) have been driving interest in large-scale analytics, yet current systems fail to support higher-order (HO) interactions beyond first-order (one-hop) relations, which are crucial for tasks such as subgraph counting, polyadic modeling, and HO graph learning. We address this by introducing a new class of systems, higher-order graph databases (HO-GDBs) that use lifting and lowering paradigms to seamlessly extend traditional GDBs with HO. We provide a theore…

Revisiting R: Statistical Envelope Analysis for Lightweight RF Modulation Classification
Srinivas Rahul Sapireddy, Mostafizur Rahman
https://arxiv.org/abs/2506.19956

Revisiting R: Statistical Envelope Analysis for Lightweight RF Modulation Classification
Modulation classification plays a crucial role in wireless communication systems, enabling applications such as cognitive radio, spectrum monitoring, and electronic warfare. Conventional techniques often involve deep learning or complex feature extraction, which, while effective, require substantial computational resources and memory. An early approach by Chan and Gadbois in 1985 introduced a theoretical method for modulation classification using a mathematically derived parameter called R. The…

🇺🇦 Auf radioeins läuft...
The Black Keys:
🎵 Lonely Boy
#NowPlaying #TheBlackKeys
https://blackonblues.bandcamp.com/track/lonely-boy
https://open.spotify.com/track/5G1sTBGbZT5o4PNRc75RKI

A look at the lack of consensus in the tech industry on what AGI is, whether LLMs are the best path to it, and what AGI might look like if or when it arrives (Melissa Heikkilä/Financial Times)

Why Big Tech cannot agree on artificial general intelligence
It has been tipped as the next big breakthrough out of Silicon Valley, but is it a scientific goal — or a marketing buzzword?

Uh-oh. Did someone try Vibe Ops?
https://www.githubstatus.com

Exact Hull Reformulation for Quadratically Constrained Generalized Disjunctive Programs
Sergey Gusev, David E. Bernal Neira
https://arxiv.org/abs/2508.16093 https://

Exact Hull Reformulation for Quadratically Constrained Generalized Disjunctive Programs
Generalized Disjunctive Programming (GDP) is a framework for optimization problems involving discrete decisions and nonlinear constraints. The widely used Hull Reformulation transforms GDPs into Mixed-Integer Nonlinear Programming (MINLP) problems with tighter continuous relaxations. However, it typically employs an epsilon approximation of the closure of the perspective function for nonlinear constraints, which can lead to numerical instability and a weaker continuous relaxation. We present …

Views: A Hardware-friendly Graph Database Model For Storing Semantic Information
Yanjun Yang, Adrian Wheeldon, Yihan Pan, Alex Serb
https://arxiv.org/abs/2508.18123 https://

Views: A Hardware-friendly Graph Database Model For Storing Semantic Information
The graph database (GDB) is an increasingly common storage model for data involving relationships between entries. Beyond its widespread usage in database industries, the advantages of GDBs indicate a strong potential in constructing symbolic artificial intelligences (AIs) and retrieval-augmented generation (RAG), where knowledge of data inter-relationships takes a critical role in implementation. However, current GDB models are not optimised for hardware acceleration, leading to bottlenecks in…

Innovative Distributed Maintenance Concept: From the design to cost optimisation
Maria Di Mascolo (G-SCOP, G-SCOP\_DOME2S), Zineb Simeu-Abazi (G-SCOP, G-SCOP\_DOME2S), Rony Ars\`ene Djeunang Mezafack (G-SCOP, G-SCOP\_DOME2S)
https://arxiv.org/abs/2508.16160

Innovative Distributed Maintenance Concept: From the design to cost optimisation
This study proposes an integrated heuristic framework for the strategic optimization of distributed maintenance operations in geo-distributed production systems (GDPS). It introduces a dual-entity maintenance structure comprising a Centralized Maintenance Workshop (CMW) and a Mobile Maintenance Workshop (MMW), aimed at minimizing total long-term maintenance costs. The cost function incorporates transport, operations, and downtime penalties, optimized via a two-stage algorithmic approach: a Main…