Electrical Eng. & Systems
This paper proposes a scenario-based framework for predictive maintenance scheduling under uncertainty in a finite planning horizon. The considered setting involves multiple assets for which maintenance decisions are informed by three…
Large-scale offshore Wind Farms (WFs) are considered key assets towards realizing a sustainable power system. These systems are often configured as offshore AC islands and their integration largely depends on the High-Voltage-Direct-Current…
Preload loss in bolted joints results in alterations of the stiffness, damping, and nonlinearity of the structure, but existing monitoring techniques for rail-vehicle systems are often not capable of combining controlled shaker tests and…
AI-driven respiratory sound classification (RSC) is promising for automated pulmonary disease detection, yet multi-site deployment is hindered by inter-stethoscope variability. We introduce a federated domain generalization (FedDG)…
Recent speech language models rely on encoders that are optimized separately from autoregressive models. Since these encoders are unaware of the downstream objectives, the extracted representations may not be optimal for downstream tasks.…
Machine learning (ML) is increasingly used for data-driven modeling of buildings to enable downstream tasks such as fault detection and diagnosis, and energy-efficient control. While recent work improves generalization across building…
This paper presents a distributed nonlinear model predictive control that uses alternating direction method of mul tipliers for district heating networks. Exploiting a graph-based modeling of the thermal dynamics, our controller optimizes…
This article discusses the concept of an Operational Design Domain (ODD) designed specifically for teleoperated road vehicles. For this purpose, the ODD concept designed for automated driving is adapted for teleoperation. As teleoperation…
This work presents a high-resolution X-ray microtomography system that uses commercial off-the-shelf (COTS) CMOS image sensors as direct detectors, relying on the sensor s intrinsic resolution to achieve tomographic reconstructions without…
A deep denoising based channel estimation framework is proposed for orthogonal time frequency space (OTFS) modulated systems, wherein channel state information (CSI) recovery is formulated as an image restoration problem. A salient…
Dual-energy CT (DECT) enables virtual monochromatic imaging (VMI) and improved contrast resolution, but its clinical adoption is limited by hardware complexity and cost. In this work, we propose a unified deep learning framework that…
While LLM-based Automatic Speech Recognition (ASR) achieves high accuracy, its speed is limited by sequential autoregressive decoding. Diffusion Language Models (DLMs) offer a parallel alternative, yet their decoding strategies remain…
Understanding what governs collective robustness and how it can be enhanced remains a central pursuit in network science. This paper investigates the robustness of multi-agent consensus networks, quantified by the $H_2$ performance metric,…
The demands for high data rates in 6G networks have driven the transition toward higher frequencies and larger antenna apertures, giving rise to the near-field communications. In the near-field region, spherical waves enable beam focusing…
In millimeter wave (mmWave) massive MIMO systems, existing alternating minimization (AltMin) based hybrid digital-analog precoding algorithms can achieve near-optimal spectral efficiency (SE) of the fully-digital precoding. However, this…
Task-based assessment of image quality (IQ) is critically important for the design and optimization of medical imaging systems. Ideal observers, including the Bayesian Ideal Observer (IO) and the ideal linear observer, i.e., the Hotelling…
This paper presents the real-time retargeting guidance policy developed for the Chandrayaan-3 lunar landing mission. The baseline guidance generates approximate fuel-optimal descent trajectories, while a high-level policy enables safe…
Chandrayaan-3 mission achieved a historic milestone with its successful soft landing near the lunar south pole, highlighting the critical role of the navigation, guidance, and control (NGC) system. Navigation provided vehicle state…
This paper studies closed-loop identification of linear periodically time-varying (LPTV) plants, with emphasis on open-loop unstable plants for which open-loop experiments are not practically available. The central contribution is an exact…
Ongoing demand for radio spectrum by commercial wireless services has steadily increased pressure on the frequency bands traditionally reserved for radar. This paper addresses the joint problem of designing non-contiguous radar transmission…