Tootfinder

Here's a good chunk of the assigned books for my grad seminar on Canadian history - a few golden oldies, but mostly newer stuff. I've got a good group and am looking forward to a fine term.
#histodons

🍆 A Hermetic, Transparent Soft Growing Vine Robot System for Pipe Inspection
#robots #machine

A Hermetic, Transparent Soft Growing Vine Robot System for Pipe Inspection
Rehabilitation of aging pipes requires accurate condition assessment and mapping far into the pipe interiors. Soft growing vine robot systems are particularly promising for navigating confined, sinuous paths such as in pipes, but are currently limited by complex subsystems and a lack of validation in real-world industrial settings. In this paper, we introduce the concept and implementation of a hermetic and transparent vine robot system for visual condition assessment and mapping within non-bra…

IVEBench: Modern Benchmark Suite for Instruction-Guided Video Editing Assessment
Yinan Chen, Jiangning Zhang, Teng Hu, Yuxiang Zeng, Zhucun Xue, Qingdong He, Chengjie Wang, Yong Liu, Xiaobin Hu, Shuicheng Yan
https://arxiv.org/abs/2510.11647

IVEBench: Modern Benchmark Suite for Instruction-Guided Video Editing Assessment
Instruction-guided video editing has emerged as a rapidly advancing research direction, offering new opportunities for intuitive content transformation while also posing significant challenges for systematic evaluation. Existing video editing benchmarks fail to support the evaluation of instruction-guided video editing adequately and further suffer from limited source diversity, narrow task coverage and incomplete evaluation metrics. To address the above limitations, we introduce IVEBench, a mo…

How to Get Actual Privacy and Utility from Privacy Models: the k-Anonymity and Differential Privacy Families
Josep Domingo-Ferrer, David S\'anchez
https://arxiv.org/abs/2510.11299

How to Get Actual Privacy and Utility from Privacy Models: the k-Anonymity and Differential Privacy Families
Privacy models were introduced in privacy-preserving data publishing and statistical disclosure control with the promise to end the need for costly empirical assessment of disclosure risk. We examine how well this promise is kept by the main privacy models. We find they may fail to provide adequate protection guarantees because of problems in their definition or incur unacceptable trade-offs between privacy protection and utility preservation. Specifically, k-anonymity may not entirely exclude …