Tootfinder

The King's Lodge
(Not all kings built hunting lodges, even fewer built them on precipices like these, but some of Bavaria's last ones did and not just in one place... Not endorsing kings in any form, just admiring their choice of locations.... btw. the picture only shows the top half of the drop)
#MountainMonday

🇺🇦 #NowPlaying on KEXP's #MiddayShow
Preoccupations:
🎵 Retrograde
#Preoccupations
https://preoccupations.bandcamp.com/track/retrograde
https://open.spotify.com/track/24z9cQzLKCVmDdLm36vZyl

Aligning visual imagery to the operator improves geospatial situation awareness in a single-display 360-degree periscope concept https://cognitiveresearchjournal.springeropen.com/articles/10.1186/s41235-025-00646-1

Aligning visual imagery to the operator improves geospatial situation awareness in a single-display 360-degree periscope concept - Cognitive Research: Principles and Implications
Technological advances mean that it is now possible to represent the entire 360° view of the horizon to a submarine periscope operator simultaneously, in strips on a single display, as opposed to the restricted view offered through a conventional periscope aperture. Initial research showing performance improvements for such panoramic displays is promising. However, that research has yet to consider the importance of alignment between the visual representation of the environment on the periscop…

Impact of Hill coefficient and time delay on a perceptual decision-making model
Bart{\l}omiej Morawski, Anna Czartoszewska
https://arxiv.org/abs/2506.19853

Impact of Hill coefficient and time delay on a perceptual decision-making model
In this paper, a neural mass perceptual decision making model introduced by Piskała et al. is analyzed. The model describes activity of two neuron populations influenced by each other and external inputs. The groups' activities correspond to the process of making a perceptual binary decision. Existing results are generalized by investigating the impact of both a delay in self-inhibition and a generic Hill coefficient on solutions to the system of differential equations. Several versions of the…

Consensus-Driven Uncertainty for Robotic Grasping based on RGB Perception
Eric C. Joyce, Qianwen Zhao, Nathaniel Burgdorfer, Long Wang, Philippos Mordohai
https://arxiv.org/abs/2506.20045

Consensus-Driven Uncertainty for Robotic Grasping based on RGB Perception
Deep object pose estimators are notoriously overconfident. A grasping agent that both estimates the 6-DoF pose of a target object and predicts the uncertainty of its own estimate could avoid task failure by choosing not to act under high uncertainty. Even though object pose estimation improves and uncertainty quantification research continues to make strides, few studies have connected them to the downstream task of robotic grasping. We propose a method for training lightweight, deep networks t…

User Understanding of Privacy Permissions in Mobile Augmented Reality: Perceptions and Misconceptions
Viktorija Paneva, Verena Winterhalter, Franziska Augustinowski, Florian Alt
https://arxiv.org/abs/2506.20207

User Understanding of Privacy Permissions in Mobile Augmented Reality: Perceptions and Misconceptions
Mobile Augmented Reality (AR) applications leverage various sensors to provide immersive user experiences. However, their reliance on diverse data sources introduces significant privacy challenges. This paper investigates user perceptions and understanding of privacy permissions in mobile AR apps through an analysis of existing applications and an online survey of 120 participants. Findings reveal common misconceptions, including confusion about how permissions relate to specific AR functionali…

Robust Anomaly Detection in Network Traffic: Evaluating Machine Learning Models on CICIDS2017
Zhaoyang Xu, Yunbo Liu
https://arxiv.org/abs/2506.19877 https…

Robust Anomaly Detection in Network Traffic: Evaluating Machine Learning Models on CICIDS2017
Identifying suitable machine learning paradigms for intrusion detection remains critical for building effective and generalizable security solutions. In this study, we present a controlled comparison of four representative models - Multi-Layer Perceptron (MLP), 1D Convolutional Neural Network (CNN), One-Class Support Vector Machine (OCSVM) and Local Outlier Factor (LOF) - on the CICIDS2017 dataset under two scenarios: detecting known attack types and generalizing to previously unseen threats. O…

De Bruijn Tori Without Zeros: A Field-Theoretic Perspective
Ming Hsuan Kang, Yu Hsuan Hsieh
https://arxiv.org/abs/2506.19605 https://…

De Bruijn Tori Without Zeros: A Field-Theoretic Perspective
We present an algebraic construction of trace-based De Bruijn tori over finite fields, focusing on the nonzero variant that omits the all-zero pattern. The construction arranges nonzero field elements on a toroidal grid using two multiplicatively independent generators, with values obtained by applying a fixed linear map, typically the field trace. We characterize sampling patterns as subsets whose associated field elements form an \( \mathbb{F}_p \)-basis, and show that column structures cor…

Join our #Luanti server they said. A few days have passed and I built this. Now what?
Contemplating my life choices.

Bridging Compositional and Distributional Semantics: A Survey on Latent Semantic Geometry via AutoEncoder
Yingji Zhang, Danilo S. Carvalho, Andr\'e Freitas
https://arxiv.org/abs/2506.20083

Bridging Compositional and Distributional Semantics: A Survey on Latent Semantic Geometry via AutoEncoder
Integrating compositional and symbolic properties into current distributional semantic spaces can enhance the interpretability, controllability, compositionality, and generalisation capabilities of Transformer-based auto-regressive language models (LMs). In this survey, we offer a novel perspective on latent space geometry through the lens of compositional semantics, a direction we refer to as \textit{semantic representation learning}. This direction enables a bridge between symbolic and distri…