Tootfinder

Tourists Stranded After Kangaroo Crash Receive 23 Days of ‘Unforgettable’ Help from Loving Locals https://www.goodnewsnetwork.org/tourists-stranded-after-kangaroo-crash-receive-23-days-of-unforgettable-help…

Tourists Stranded After Kangaroo Crash Receive 23 Days of 'Unforgettable' Help from Loving Locals
Melina Gitton and Florian Crepinior were about 135 miles south of Perth when they hit the kangaroo in the dark, leaving it undrivable.

MGPRL: Distributed Multi-Gaussian Processes for Wi-Fi-based Multi-Robot Relative Localization in Large Indoor Environments
Sai Krishna Ghanta, Ramviyas Parasuraman
https://arxiv.org/abs/2506.23514

MGPRL: Distributed Multi-Gaussian Processes for Wi-Fi-based Multi-Robot Relative Localization in Large Indoor Environments
Relative localization is a crucial capability for multi-robot systems operating in GPS-denied environments. Existing approaches for multi-robot relative localization often depend on costly or short-range sensors like cameras and LiDARs. Consequently, these approaches face challenges such as high computational overhead (e.g., map merging) and difficulties in disjoint environments. To address this limitation, this paper introduces MGPRL, a novel distributed framework for multi-robot relative loca…

Towards Scalable and Robust White Matter Lesion Localization via Multimodal Deep Learning
Julia Machnio, Sebastian N{\o}rgaard Llambias, Mads Nielsen, Mostafa Mehdipour Ghazi
https://arxiv.org/abs/2506.22041

Towards Scalable and Robust White Matter Lesion Localization via Multimodal Deep Learning
White matter hyperintensities (WMH) are radiological markers of small vessel disease and neurodegeneration, whose accurate segmentation and spatial localization are crucial for diagnosis and monitoring. While multimodal MRI offers complementary contrasts for detecting and contextualizing WM lesions, existing approaches often lack flexibility in handling missing modalities and fail to integrate anatomical localization efficiently. We propose a deep learning framework for WM lesion segmentation a…

Golden Ratio Assisted Localization for Wireless Sensor Network
Hitesh Mohapatra
https://arxiv.org/abs/2506.22464 https://arxiv.org/pd…

Golden Ratio Assisted Localization for Wireless Sensor Network
This paper presents a novel localization algorithm for wireless sensor networks (WSNs) called Golden Ratio Localization (GRL), which leverages the mathematical properties of the golden ratio (phi 1.618) to optimize both node placement and communication range. GRL introduces phi-based anchor node deployment and hop-sensitive weighting using phi-exponents to improve localization accuracy while minimizing energy consumption. Through extensive simulations conducted on a 100 m * 100 m sensor field w…

Hyperbolic localization in Donaldson-Thomas theory
Pierre Descombes
https://arxiv.org/abs/2506.22400 https://arxiv.org/pdf/2506.22400…

Hyperbolic localization in Donaldson-Thomas theory
In this paper we prove a toric localization formula in the cohomological Donaldson-Thomas theory. Consider a (-1)-shifted symplectic algebraic space with a $\mathbb{G}_m$-action leaving the (-1)-shifted symplectic form invariant (typical examples are the moduli space of stable sheaves or complexes of sheaves on a Calabi-Yau threefold with a $\mathbb{G}_m$-invariant Calabi-Yau form or the intersection of two $\mathbb{G}_m$-invariant Lagrangians in a symplectic space with a $\mathbb{G}_m$-invaria…

heise | Digitaler Garten: Mit Notion einfach Wissen sammeln
Der "digitale Garten" bietet Platz für persönliches Wissen, das nachhaltig wächst. Wer bequem loslegen möchte, nutzt einfach Notion. Wir zeigen, wie es geht.
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Sensing for Free: Learn to Localize More Sources than Antennas without Pilots
Wentao Yu, Khaled B. Letaief, Lizhong Zheng
https://arxiv.org/abs/2506.23525 …

Sensing for Free: Learn to Localize More Sources than Antennas without Pilots
Integrated sensing and communication (ISAC) represents a key paradigm for future wireless networks. However, existing approaches require waveform modifications, dedicated pilots, or overhead that complicates standards integration. We propose sensing for free - performing multi-source localization without pilots by reusing uplink data symbols, making sensing occur during transmission and directly compatible with 3GPP 5G NR and 6G specifications. With ever-increasing devices in dense 6G networks,…

Change Point Localization and Inference in Dynamic Multilayer Networks
Fan Wang, Kyle Ritscher, Yik Lun Kei, Xin Ma, Oscar Hernan Madrid Padilla
https://arxiv.org/abs/2506.21878

Change Point Localization and Inference in Dynamic Multilayer Networks
We study offline change point localization and inference in dynamic multilayer random dot product graphs (D-MRDPGs), where at each time point, a multilayer network is observed with shared node latent positions and time-varying, layer-specific connectivity patterns. We propose a novel two-stage algorithm that combines seeded binary segmentation with low-rank tensor estimation, and establish its consistency in estimating both the number and locations of change points. Furthermore, we derive the l…

genetic_multiplex: Multiplex genetic interactions (2014)
Multiplex networks representing different types of genetic interactions, for different organisms. Layers represent (i) physical, (ii) association, (iii) co-localization, (iv) direct, and (v) suppressive, (vi) additive or synthetic genetic interaction. Edge direction (i,j) indicates gene i interacting with gene j.
This network has 155 nodes and 188 edges.
Tags: Biological, Gene regulation, Protein interactions, Unweigh…

Adaptive Multipath-Based SLAM for Distributed MIMO Systems
Xuhong Li, Benjamin J. B. Deutschmann, Erik Leitinger, Florian Meyer
https://arxiv.org/abs/2506.21798

Adaptive Multipath-Based SLAM for Distributed MIMO Systems
Localizing users and mapping the environment using radio signals is a key task in emerging applications such as reliable communications, location-aware security, and safety critical navigation. Recently introduced multipath-based simultaneous localization and mapping (MP-SLAM) can jointly localize a mobile agent and the reflective surfaces in radio frequency (RF) environments. Most existing MP-SLAM methods assume that map features and their corresponding RF propagation paths are statistically i…