Aeronáutica y espacio

Real-World Evaluation of Protocol-Compliant Denial-of-Service Attacks on C-V2X-based Forward Collision Warning Systems

- Cellular Vehicle-to-Everything (C-V2X) technology enables low-latency, reliable communications essential for safety applications such as a Forward Collision Warning (FCW) system. C-V2X deployments...

ReSim: Reliable World Simulation for Autonomous Driving

- How can we reliably simulate future driving scenarios under a wide range of ego driving behaviors? Recent driving world models, developed exclusively on real-world driving data composed mainly of...

Risk-Aware Aerocapture Guidance Through a Probabilistic Indicator Function

- Aerocapture is sensitive to trajectory errors, particularly for low-cost missions with imprecise navigation. For such missions, considering the probability of each failure mode when computing...

Reinforcement Learning for Testing Interdependent Requirements in Autonomous Vehicles: An Empirical Study

- Autonomous vehicles (AVs) make driving decisions without humans, making dependability assurance critical. Scenario-based testing is widely used to evaluate AVs under diverse conditions, with...

AIDOVECL: AI-generated Dataset of Outpainted Vehicles for Eye-level Classification and Localization

- Image labeling is a critical bottleneck in the development of computer vision technologies, often constraining machine learning performance due to the time-intensive nature of manual annotations....

BEVal: A Cross-dataset Evaluation Study of BEV Segmentation Models for Autonomous Driving

- Current research in semantic bird's-eye view segmentation for autonomous driving focuses solely on optimizing neural network models using a single dataset, typically nuScenes. This practice leads...

Quantum-Inspired Robust and Scalable SAR Object Classification

- SAR image classification naturally has to deal with huge noise and a high dynamic range particularly requiring robust classification models. Additionally, the deployment of these models on edge...

Adaptive Meta-Learning Stochastic Gradient Hamiltonian Monte Carlo Simulation for Bayesian Updating of Structural Dynamic Models

- In the last few decades, Markov chain Monte Carlo (MCMC) methods have been widely applied to Bayesian updating of structural dynamic models in the field of structural health monitoring. Recently,...

Bridging the Indoor-Outdoor Gap: Cross-Technology Ranging for Seamless Robot Navigation

- Mobile robots that move between outdoor and indoor environments still struggle with consistent positioning. Satellite-based and terrestrial ranging each work well in their home domains, but combining...

Make Any Collection Navigable: Methods for Constructing and Evaluating Hypergraph of Text

- One reason the Web is more useful than a simple collection of documents is that the structure created by hyperlinks enables flexible navigation from one web page to another. However, hyperlinks are...

Carbon-Taxed Transformers: A Green Compression Pipeline for Overgrown Language Models

- The accelerating adoption of Large Language Models (LLMs) in software engineering (SE) has brought with it a silent crisis: unsustainable computational cost. While these models demonstrate remarkable...

At the Edge of the Heart: ULP FPGA-Based CNN for On-Device Cardiac Feature Extraction in Smart Health Sensors for Astronauts

- The convergence of accelerating human spaceflight ambitions and critical terrestrial health monitoring demands is driving unprecedented requirements for reliable, real-time feature extraction on...

EOS-Bench: A Comprehensive Benchmark for Earth Observation Satellite Scheduling

- Earth observation satellite imaging scheduling is a challenging NP-hard combinatorial optimisation problem central to space mission operations. While next-generation agile Earth observation...

Learning-Based Dynamics Modeling and Robust Control for Tendon-Driven Continuum Robots

- Tendon-Driven Continuum Robots (TDCRs) pose significant modeling and control challenges due to complex nonlinearities, such as frictional hysteresis and transmission compliance. This paper proposes a...

Control Your Queries: Heterogeneous Query Interaction for Camera-Radar Fusion

- In autonomous driving, camera-radar fusion offers complementary sensing and low deployment cost. Existing methods perform fusion through input mixing, feature map mixing, or query-based feature...

AI as Consumer and Participant: A Co-Design Agenda for MBSE Substrates and Methodology

- AI tools are being deployed over MBSE models today, and those models were not designed for this kind of consumption. The problem is not simply that tools hallucinate: well-prompted frontier models...

Economical and ecological impact of sector coupling applied to computing clusters

- The rising share of abundant renewable energy inevitably increases volatility in the electricity production. The concept of sector coupling means that the volatility of electricity production to a...

Medoid Prototype Alignment for Cross-Plant Unknown Attack Detection in Industrial Control Systems

- Deploying an intrusion detector trained in one industrial plant to another remains difficult because Industrial Control System (ICS) traffic is highly site-dependent, labels are scarce, and unseen...

GS-Playground: A High-Throughput Photorealistic Simulator for Vision-Informed Robot Learning

- Embodied AI research is undergoing a shift toward vision-centric perceptual paradigms. While massively parallel simulators have catalyzed breakthroughs in proprioception-based locomotion, their...

FED-FSTQ: Fisher-Guided Token Quantization for Communication-Efficient Federated Fine-Tuning of LLMs on Edge Devices

- Federated fine-tuning provides a practical route to adapt large language models (LLMs) on edge devices without centralizing private data, yet in mobile deployments the training wall-clock is often...

SARU: A Shadow-Aware and Removal Unified Framework for Remote Sensing Images with New Benchmarks

- Shadows are a prevalent problem in remote sensing imagery (RSI), degrading visual quality and severely limiting the performance of downstream tasks like object detection and semantic segmentation....