Aeronáutica y espacio

A Modern Large-Scale Memory Characterization Laboratory

- Real memory chip characterization yields insights into fundamental operational characteristics of modern memory, enabling new mechanisms that improve memory performance, robustness, security, and...

Enhancing Energy and Spectral Efficiency in IoT-Cellular Networks via Active SIM-Equipped LEO Satellites

- This paper investigates a low Earth orbit (LEO) satellite communication system enhanced by an active stacked intelligent metasurface (ASIM), mounted on the backplate of the satellite solar panels to...

ReSCom: A Reconfigurable Spiking Neural Network Accelerator Using Stochastic Computing

- Spiking Neural Networks (SNNs) provide an attractive framework for energy-efficient inference due to their event-driven computation and biologically inspired dynamics. However, efficient hardware...

SupraSNN: Exploiting Synapse-Level Parallelism in Spiking Neural Network Accelerators through Co-Optimized Mapping and Scheduling

- Spiking Neural Networks (SNNs) offer a brain-inspired path toward highly efficient computation, but their practical deployment is constrained by the challenge of managing and executing their massive...

Optimizing Appliance Scheduling for Solar Energy Management Using Metaheuristic Algorithms

- Renewable energy is essential for meeting future energy demands; however, solar energy generation, which occurs only during daylight hours often does not align with household consumption patterns....

Multi-Phase Optimization of Shared Charging Infrastructure for Freight Electrification

- The transition to heavy-duty battery electric vehicles requires an efficient and cost-effective deployment of the charging infrastructure, particularly when multiple operators share resources. This...

LongSpike: Fractional Order Spiking State Space Models for Efficient Long Sequence Learning

- Spiking Neural Networks (SNNs) are well-regarded for their biological plausibility and energy efficiency in processing sequential data. However, dominant SNN architectures typically rely on...

Scaling Demand-Side Flexibility Through Dynamic Tariffs

- The ongoing electrification and integration of renewable energy sources in Denmark's distribution grids pose significant operational challenges, including insufficient reserve capacity, component...

BenDi: An Energy-Efficient Quasi-Stochastic Systolic Architecture for Edge Bioelectronics

- Continuous long-term monitoring and diagnosis of biomedical signals, such as electrocardiograms (ECGs), can help mitigate an increasing threat to public health. Artificial Intelligence (AI) models,...

Performance Analysis of YOLOv11 and YOLOv8 for Mixed Traffic Object Detection under Adverse Weather Conditions in Developing Countries

- In modern vehicular systems, robust performance under harsh conditions has become a critical problem of autonomous driving. Our study delivers a comprehensive evaluation of the newest iteration of...

A Fast Locality Simulator for GEMM Design-Space Exploration on Multi-Chiplet GPUs

- Multi-chiplet GPUs split memory into local and remote HBM regions across a silicon interposer, and reducing the remote HBM traffic is crucial for the performance and energy efficiency of...

Making Locality-aware GEMM Compatible with Page-Granularity Placement on Chiplet GPUs

- Multi-chiplet GPUs scale compute throughput and high-bandwidth memory (HBM) capacity, but their non-uniform memory system makes locality between chiplets and their data critical to the GPU's...

Violation-Informed Spatio-Temporal Adaptive Targeting Framework for EV-Driven Distribution System Expansion Planning

- The rapid adoption of electric vehicles (EVs) can cause severe voltage drops and line current overloads in distribution networks, creating an urgent need for scalable expansion planning methods. This...

Probabilistic Repair Logistics Modeling for Utility-Scale PV Inverter Fleets Using Event-Driven Simulation

- As renewable energy systems expand, inverter availability becomes increasingly important for grid reliability and economics, yet photovoltaic inverter repair logistics remain under-modeled. This...

TileFuse: A Fused Mixed-Precision Kernel Library for Efficient Quantized LLM Inference on AMD NPUs

- With the growing demand for on-device LLM inference, edge SoCs increasingly integrate NPUs to improve performance and energy efficiency under tight power and thermal budgets. However, practical LLM...

A2SG:Adaptive and Asymmetric Surrogate Gradients for Training Deep Spiking Neural Networks

- Training deep spiking neural networks (SNNs) remains challenging due to sharp loss landscapes and temporal inconsistency caused by surrogate gradients. To address these challenges, we propose a...

IMPACT: Learning Internal-Model Predictive Control for Forceful Robotic Manipulation

- Real-world robotic manipulation tasks often involve forceful interactions with the environment, such as using tools of varying weights, transporting objects with different masses, and performing...

Dynamic Optimization of Virtual Inertia and Damping in Converter-Based Power Systems

- The transition towards a sustainable power system is enabled by the replacement of conventional synchronous generators with converter-interfaced renewable energy sources. However, the resulting loss...

HydraCIL: Decoupled Class-Incremental Learning through Prototype-Guided Multi-Head Classifiers

- We present HydraCIL, a decoupled continual learning model based on prototype-guided multi-head classifiers, targeting sustainable deployment in embedded and resource-constrained environments. While...

SPARX: Secure and Privacy-Aware Approximate CNN Acceleration with Edge RISC-V SoC

- Edge-AI systems increasingly require real-time CNN inference under strict energy, performance, security, and privacy constraints. Approximate computing improves hardware efficiency by exploiting the...

Retraction Note: Artificial intelligence-augmented smart grid architecture for cyber intrusion detection and mitigation in electric vehicle charging infrastructure