We introduce HammerDrive, a novel architecture for task-aware visual attention prediction in driving. The proposed architecture is learnable from data and can reliably infer the current focus of attention of the driver in real-time, while only requiring limited and easy-to-access telemetry data from the vehicle. We build the proposed architecture o...
The paper contributes to improving the computational performance of controls of distributed energy resources (DERs) in distribution grids for efficient real-time control and short-term scheduling. The considered setting is a distribution grid with heterogeneous DERs controlled with model predictive control (MPC) to track a dispatch plan at its grid...
The design of cyber–physical systems (CPSs) is facing the explosion of new functionalities requiring increased computation capacities and, thus, the introduction of multi-core processors. Moreover, some functionalities may impose precedence constraints between the programs implementing these new functionalities. While important effort has been dedi...
Widespread adoption of mobile augmented reality (AR) and virtual reality (VR) applications depends on their smoothness and immersiveness. Modern AR applications applying computationally intensive computer vision algorithms can burden today's mobile devices, and cause high energy consumption and/or poor performance. To tackle this challenge, it is p...
Pedestrian detection is an important branch of computer vision, and it has important applications in the fields of autonomous driving, artificial intelligence and video surveillance.With the rapid development of deep learning and the proposal of large-scale datasets, pedestrian detection has reached a new stage and achieves better performance. Howe...
Automotive and industrial embedded systems are increasingly dependent on real-time capabilities. TSN aims to offer flexibility of the traffic by providing Ethernet with hard and soft real-time capabilities which allows for integration with other protocols in legacy systems. TSN requires the network to be fully synchronized to achieve high performan...
Railways are a well-recognized sustainable transportation mode that helps to satisfy the continuously growing mobility demand. However, the management of railway traffic in large-scale networks is a challenging task, especially when both a major disruption and various disturbances occur simultaneously. We propose an automatic rescheduling algorithm...
Co-simulation techniques are gaining popularity amongst the power system research community to analyse future scalable Smart Grid solutions. However, complications such as multiple communication protocols, uncertainty in latencies are holding up the widespread usage of these techniques for power system analysis. These issues are even further exacer...
This work addresses an innovative processing strategy to improve the classification of Steady-State Visually Evoked Potentials (SSVEPs). This strategy resorts to the combined use of fast Fourier transform and Canonical Correlation Analysis in time domain, and manages to outperform by over 5% previous results obtained for highly wearable, single-cha...
IEEENetwork reconfiguration (NR) has attracted much attention due to its ability to convert conventional distribution networks (DNs) into self-healing grids. This paper proposes a new strategy for real-time voltage regulation (VR) in a reconfigurable DN, whereby optimal feedforward control of distributed generators (DGs) is achieved in coordination...
