Tootfinder

Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT
Ioannis Panopoulos, Maria-Lamprini A. Bartsioka, Sokratis Nikolaidis, Stylianos I. Venieris, Dimitra I. Kaklamani, Iakovos S. Venieris
https://arxiv.org/abs/2506.18114

Dynamic Temporal Positional Encodings for Early Intrusion Detection in IoT
The rapid expansion of the Internet of Things (IoT) has introduced significant security challenges, necessitating efficient and adaptive Intrusion Detection Systems (IDS). Traditional IDS models often overlook the temporal characteristics of network traffic, limiting their effectiveness in early threat detection. We propose a Transformer-based Early Intrusion Detection System (EIDS) that incorporates dynamic temporal positional encodings to enhance detection accuracy while maintaining computati…

CFTel: A Practical Architecture for Robust and Scalable Telerobotics with Cloud-Fog Automation
Thien Tran, Jonathan Kua, Minh Tran, Honghao Lyu, Thuong Hoang, Jiong Jin
https://arxiv.org/abs/2506.17991

CFTel: A Practical Architecture for Robust and Scalable Telerobotics with Cloud-Fog Automation
Telerobotics is a key foundation in autonomous Industrial Cyber-Physical Systems (ICPS), enabling remote operations across various domains. However, conventional cloud-based telerobotics suffers from latency, reliability, scalability, and resilience issues, hindering real-time performance in critical applications. Cloud-Fog Telerobotics (CFTel) builds on the Cloud-Fog Automation (CFA) paradigm to address these limitations by leveraging a distributed Cloud-Edge-Robotics computing architecture, e…

Bias vs Bias -- Dawn of Justice: A Fair Fight in Recommendation Systems
Tahsin Alamgir Kheya, Mohamed Reda Bouadjenek, Sunil Aryal
https://arxiv.org/abs/2506.18327

Bias vs Bias -- Dawn of Justice: A Fair Fight in Recommendation Systems
Recommendation systems play a crucial role in our daily lives by impacting user experience across various domains, including e-commerce, job advertisements, entertainment, etc. Given the vital role of such systems in our lives, practitioners must ensure they do not produce unfair and imbalanced recommendations. Previous work addressing bias in recommendations overlooked bias in certain item categories, potentially leaving some biases unaddressed. Additionally, most previous work on fair re-rank…

fao_trade: FAO Multiplex Trade Network
Multiplex network representing trade relationships between countries from the Food and Agricultural Organization of the United Nations. Countries are nodes and edge types represent import/export of varying products. Data hosted by Manlio De Domenico.
This network has 214 nodes and 318346 edges.
Tags: Economic, Trade, Weighted, Multilayer

Supporting Deterministic Traffic on Standard NICs
Chuanyu Xue, Tianyu Zhang, Andrew Loveless, Song Han
https://arxiv.org/abs/2506.17877 https://

Supporting Deterministic Traffic on Standard NICs
Networked mission-critical applications (e.g., avionic control and industrial automation systems) require deterministic packet transmissions to support a range of sensing and control tasks with stringent timing constraints. While specialized network infrastructure (e.g., time-sensitive networking (TSN) switches) provides deterministic data transport across the network, achieving strict end-to-end timing guarantees requires equally capable end devices to support deterministic traffic. These end …

Enhancing Few-shot Keyword Spotting Performance through Pre-Trained Self-supervised Speech Models
Alican Gok, Oguzhan Buyuksolak, Osman Erman Okman, Murat Saraclar
https://arxiv.org/abs/2506.17686

Enhancing Few-shot Keyword Spotting Performance through Pre-Trained Self-supervised Speech Models
Keyword Spotting plays a critical role in enabling hands-free interaction for battery-powered edge devices. Few-Shot Keyword Spotting (FS-KWS) addresses the scalability and adaptability challenges of traditional systems by enabling recognition of custom keywords with only a few examples. However, existing FS-KWS systems achieve subpar accuracy at desirable false acceptance rates, particularly in resource-constrained edge environments. To address these issues, we propose a training scheme that l…

The DECam MAGIC Survey: Spectroscopic Follow-up of the Most Metal-Poor Stars in the Distant Milky Way Halo
Vinicius M. Placco, Guilherme Limberg, Anirudh Chiti, Deepthi S. Prabhu, Alexander P. Ji, Fabr\'icia O. Barbosa, William Cerny, Andrew B. Pace, Guy S. Stringfellow, David J. Sand, Clara E. Mart\'inez-V\'azquez, Alexander H. Riley, Silvia Rossi, Noelia E. D. No\"el, A. Katherina Vivas, Gustavo E. Medina, Alex Drlica-Wagner, Joanna D. Sakowska, Bur\c{c}in Mutlu-Pakd…

The DECam MAGIC Survey: Spectroscopic Follow-up of the Most Metal-Poor Stars in the Distant Milky Way Halo
In this work, we present high-resolution spectroscopic observations for six metal-poor stars with [Fe/H]<-3 (including one with [Fe/H]<-4), selected using narrow-band Ca II HK photometry from the DECam MAGIC Survey. The spectroscopic data confirms the accuracy of the photometric metallicities and allows for the determination of chemical abundances for 16 elements, from carbon to barium. The program stars have chemical abundances consistent with this metallicity range. A kinematic/dynamical anal…

Probing d-wave superconducting gap of high-$T_\mathrm{c}$ cuprate $\mathrm{Bi}_2\mathrm{Sr}_2\mathrm{Ca}_2\mathrm{Cu}_3\mathrm{O}_{10 \delta}$ by resonant inelastic X-ray scattering
Kunhao Li, Qizhi Li, Changwei Zou, Jaewon Choi, Chaohui Yin, Mirian Garcia-Fernandez, Stefano Agrestini, Shilong Zhang, Chengtian Lin, Xingjiang Zhou, Ke-Jin Zhou, Yi Lu, Yingying Peng

Probing d-wave superconducting gap of high-$T_\mathrm{c}$ cuprate $\mathrm{Bi}_2\mathrm{Sr}_2\mathrm{Ca}_2\mathrm{Cu}_3\mathrm{O}_{10+δ}$ by resonant inelastic X-ray scattering
The superconducting gap is a characteristic feature of high-T$_c$ superconductors and provides crucial information on the pairing mechanism underlying high-temperature superconductivity. Here, we employ high-resolution resonant inelastic X-ray scattering (RIXS) at the Cu $L_3$-edge to investigate the superconducting gap in the overdoped cuprate $\mathrm{Bi}_2\mathrm{Sr}_2\mathrm{Ca}_2\mathrm{Cu}_3\mathrm{O}_{10+δ}$ ($T_\mathrm{c}$ = 107 K). By analyzing antisymmetrized, temperature-dependent R…

Solar Transient Recognition Using Deep Learning (STRUDL) for heliospheric imager data
Maike Bauer, Justin Le Lou\"edec, Tanja Amerstorfer, Luke Barnard, David Barnes, Helmut Lammer
https://arxiv.org/abs/2506.16194

Solar Transient Recognition Using Deep Learning (STRUDL) for heliospheric imager data
Coronal Mass Ejections (CMEs) are space weather phenomena capable of causing significant disruptions to both space- and ground-based infrastructure. The timely and accurate detection and prediction of CMEs is a crucial steps towards implementing strategies to minimize the impacts of such events. CMEs are commonly observed using coronagraphs and heliospheric imagers (HIs), with some forecasting methods relying on manually tracking CMEs across successive images in order to provide an estimate of …

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees
Anders E. Kal{\o}r, Tomoaki Ohtsuki
https://arxiv.org/abs/2506.11391 https…

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees
Edge artificial intelligence (AI) will be a central part of 6G, with powerful edge servers supporting devices in performing machine learning (ML) inference. However, it is challenging to deliver the latency and accuracy guarantees required by 6G applications, such as automated driving and robotics. This stems from the black-box nature of ML models, the complexities of the tasks, and the interplay between transmitted data quality, chosen inference model, and the random wireless channel. This pap…