Electrical Eng. & Systems
This report presents our solutions to the QoMEX 2026 Grand Challenge on Video Quality Assessment for Asymmetric Encoded Videos, comprising a full-reference (FR) model, CompressedVQA-AEV-FR, and a no-reference (NR) model,…
Home Energy Management Systems (HEMS) can reduce residential electricity costs and support demand response, but adoption is limited by the difficulty of translating household preferences into technical scheduling constraints. This paper…
Water electrolysis plants, hyperscale data centers, and aluminum potlines represent gigawatts of demand-side flexibility for bulk power system balancing, operational planning, and procurement services. Such loads are scheduled through…
Hyperscale data centers and other large concentrated loads can impose substantial new demand on existing transmission networks. If import corridors lack sufficient transfer capability, operators may need to curtail load, delay…
The modulating function method is an algebraic framework that, thus far, has been used for state and parameter estimation, as well as fault detection, of linear, fractional-order, distributed, and some nonlinear systems. At the core of the…
Linear spatial filters (beamformers) enable robust, generalizable and interpretable speech enhancement with performance guarantees under ideal parameterization. Modern beamformers are often parameterized by deep neural networks, whose…
Non-invasive blood glucose estimation from wearable physiological signals remains difficult because longitudinal photoplethysmography (PPG) data are subject to distribution drift, whereas reference capillary blood glucose labels are sparse…
Power-constrained 25kV AC railway sections, particularly under degraded feeding, are protected today by blunt, section-wide power limits that penalise every train irrespective of whether it contributes to the binding condition. This paper…
Low-Earth-orbit (LEO) relay networks deliver finite objects -- sensing tiles, telemetry blocks, model updates, and checkpoints -- over intermittent inter-satellite and space-to-ground contact plans. Partial delivery is insufficient when the…
Binary change detection in remote sensing requires both complete changed-region localization and accurate boundary delineation. We present MambaRefine-CD, a region-boundary temporal refinement framework built on a shared MambaVision…
Explainable AI (XAI) is important for deploying machine learning systems in domains where stakes are very high and where transparency, trust and accountability are critical. Although black box models like deep neural networks often perform…
Volterra series feedback linearizes a class of nonlinear hyperbolic PDEs but produces a controller that, even after truncation, demands solving a tower of plant-specific kernel PDEs and evaluating nested integrals. We prove the truncated…
Backstepping for nonlinear PDEs yields exact feedback linearizing laws in the form of infinite Volterra series -- elegant in theory, but with challenges for implementation. This paper shows that even very low-order truncations of such…
The dominant trend in voice anti-spoofing fuses self-supervised (SSL) backbones (e.g., WavLM) with handcrafted features, yet such fusion typically lacks transparency in cue-to-layer interactions, and simple concatenation limits cross-modal…
We develop a unified, certified lower bound on the time-to-boundary margin M for transient stability of interconnected dissipative systems under slow parameter drift. The companion work establishes M as the first-passage time of the joint…
Artificial intelligence (AI) and machine learning (ML)-based channel estimators silently degrade when propagation conditions drift from their training distributions. This letter proposes a model-agnostic cognitive digital twin (CDT)…
With the development of low altitude intelligent systems, multiple unmanned aerial vehicles (UAVs) can collaboratively execute more complex tasks. Conventional task allocation methods usually regard tasks and UAVs as isolated entities,…
AI-RAN aims to unify artificial intelligence and radio access network workloads on a shared compute substrate. While this paradigm has so far been demonstrated primarily on Graphics Processing Units (GPUs), it remains unclear whether Neural…
In MRI, dense receiver coil arrays with a high number of coil elements are used to efficiently detect and encode the signal. Further increasing the number of coils is hampered by electrical cabling and massive electronics that introduce…
Neural speech codec has attracted extensive attention for high-quality reconstruction at low-bitrate. However, real-world noise severely degrades its performance and hinders high-quality clean speech reconstruction. To tackle this problem,…