Electrical Eng. & Systems
This letter investigates the problem of energy efficient collaborative strategy for mobile embodied artificial intelligence network (MEAN) over wireless communication. In the considered model, the agents execute the tasks through…
Data assimilation (DA) estimates the state of an evolving dynamical system from noisy, partial observations, and is widely used in scientific simulation as well as weather and climate science. In practice, filtering methods rely on…
This paper presents a flexible energy management system (EMS) for an electric bus charging station (EBCS) that integrates renewable generation, energy storage, and electric bus (EB) charging while accounting for uncertainties in solar PV…
Connected and autonomous vehicles and smart mobility services increasingly use digital route guidance as an operational input to traffic network management. When this information becomes unreliable or adversarial, day-to-day traffic models…
Grid-forming (GFM) inverters are essential for enhancing stability in modern power systems with high penetration of inverter-based resources (IBRs). However, their performance highly depends on control parameters tuning, particularly the…
Feature sharing via split inference offers a lightweight alternative to federated learning for resource-constrained hospitals, but transmitted features still leak patient identity information and lack practical mechanisms for controlled…
This paper studies the synthesis of control policies for heterogeneous and interconnected multi-agent systems that collaborate through data exchange over a communication network to minimize a collective cost. We propose a distributed…
Uncrewed aerial vehicles (UAVs) are gaining increasing attention in wireless systems, providing new opportunities to expand the reach and improve the quality of wireless services. Despite their versatility, UAVs are limited by available…
Emerging connect-and-manage interconnection practices allow gigawatt-scale artificial intelligence data centers (AIDCs) to connect to the transmission network without prior network upgrades, at the cost of real-time curtailment during grid…
Emerging connect-and-manage practices allow new transmission-connected mega-loads to connect while enforcing time-varying admissible power exchange limits at the point of common coupling (PCC) in real time. Hyperscale artificial…
Coordinating growing grid flexibility under uncertainty is becoming increasingly important for efficient and reliable power-system operation. A core computational requirement is the efficient large-scale batched evaluation of AC power flow…
Power system restoration following blackouts must ensure frequency stability throughout the recovery process. This paper proposes a frequency-constrained mixed-integer linear programming (MILP) framework for black-start restoration planning…
Deceptive path planning enables autonomous agents to obscure their true goals from observers by deviating from an expected optimal path. Prior work largely solves full-horizon, end-to-end optimization for single agents, which is expensive…
Early-stage Parkinson's disease (EarlyPD) detection from speech is clinically meaningful yet underexplored, and published results are hard to compare because studies differ in datasets, languages, tasks, evaluation protocols, and EarlyPD…
The rapid growth of variable renewable energy has increased the need for flexible and efficiently coordinated energy resources. In this context, hybrid resources that combine renewable generation and battery storage within a single…
Frequency-modulated continuous-wave (FMCW) lidar conventionally estimates distance and velocity from constant beat frequencies generated through interferometry. Existing FMCW implementations emphasize simple signal processing -- e.g., beat…
Stain variation across hospitals degrades histopathology models at deployment. Existing augmentation methods perturb color spaces with arbitrary hyperparameters, lacking both a principled budget and coverage guarantees for unseen centers.…
While U-Net architectures remain the gold standard for medical image segmentation, their deployment in resource-constrained environments demands aggressive model compression. However, finding an optimally efficient configuration is…
We propose a novel extremum seeking control (ESC) method that operates in a lifted Koopman state space to minimize the filtered RMS energy in the dominant subspace. The lifted representation provides linear embeddings of nonlinear dynamics,…
Computational constraints permeate the controller design process, and yet are rarely treated as explicit design constraints. Towards addressing this gap, we propose a quantitative framework that captures the effects of common design…