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Energy savings and emissions reduction of BEVs at an isolated complex intersection
Reddy, Radha; Almeida, Luis; Santos, Pedro Miguel; Kurunathan, Harrison; Tovar, EduardoImproving urban dwellers quality of life requires mitigating traffic congestion, minimizing waiting delays, and reducing fuel wastage and associated toxic air pollutants. Battery-electric vehicles (BEVs) are envisioned as the best option, thanks to zero exhaust emissions and regenerative braking. BEVs can be human-driven or autonomous and will co-exist with internal combustion engine vehicles (ICEVs) for years....
DynaVLC 13 towards dynamic GTS allocation in VLC networks
Kurunathan, John Harrison; Gutiérrez Gaitán, Miguel; Sámano-Robles, Ramiro; Tovar, EduardoEnvisioned to deliver superior Quality of Service (QoS) by offering faster data rates and reduced latency in 6G communication scenarios, pioneering communication protocols like the IEEE 802.15.7 are poised to facilitate emerging application trends (e.g. metaverse). The IEEE 802.15.7 standard that supports visible light communication (VLC) provides determinism for time-critical reliable communication through its...
Fusion flow-enhanced graph pooling residual networks for unmanned aerial vehicl...
Noor, Alam; Li, Kai; Tovar, Eduardo; Zhang, Pei; Wei, BoRecognizing unauthorized Unmanned Aerial Vehicles (UAVs) within designated no-fly zones throughout the day and night is of paramount importance, where the unauthorized UAVs pose a substantial threat to both civil and military aviation safety. However, recognizing UAVs day and night with dual-vision cameras is nontrivial, since red-green-blue (RGB) images suffer from a low detection rate under an insufficient li...
Improved memory contention analysis for the 3-Phase task model
Arora, Jatin; Rashid, Syed Aftab; Nelissen, Geoffrey; Maia, Cláudio; Tovar, EduardoIn multiprocessor-based real-time systems, main memory is identified as a major bottleneck in the worst-case timing analysis of tasks. Phased execution models such as the 3-phase task model, i.e., that divides the execution of tasks into distinct computation and memory phases, have shown to be a good candidate to tackle the memory contention problem. The 3-phase execution model in particular has gained much att...
MARS: Safely instrumenting runtime monitors in real-time resource-constrained d...
Nandi, Giann; Pereira, David; Proenca, José; Tovar, EduardoAdvancements in the energy efficiency and computational power of embedded devices allow developers to equip resource-constrained systems with a greater number of features and more complex behavior. As complexity of a system grows, so does the difficulty in demonstrating its overall correctness. Formal methods have been successfully applied in a variety of verification and validation scenarios, but their wide ad...
Poisoning federated learning with graph neural networks in Internet of Drones
Li, Kai; NOOR, ALAM; Ni, Wei; Tovar, Eduardo; Fu, Xiaoming; Akan, Ozgur B.Internet of Drones (IoD) is an innovative technology that integrates mobile computing capabilities with drones, enabling them to process data at or near the location where it is collected. Federated learning can significantly enhance the efficiency and effectiveness of data processing and decision-making in IoD. Since federated learning relies on aggregating updates from multiple drones, a malicious drone can g...
Reducing the gap between theory and practice in real-time systems with MARS
Spilere Nandi, Giann; Pereira, David; Proença, José; Tovar, Eduardo; Nogueira, LuísA significant number of dependable systems rely on scheduling algorithms to achieve temporal correctness. Despite their relevance in real-world applications, only a narrow subset of the works in the literature of real-time systems are readily available to be reproduced in real-world hardware platforms. This lack of support not only hinders the reproducibility of research results, but also reduces the opportunit...
Sheep health behavior analysis in machine learning: A short comprehensive survey
Noor, Alam; Corke, Murray J.; Tovar, EduardoSheep management and production enhancement are difficult for farmers due to the lack of dynamic response and poor welfare of the sheep. Poor welfare needs to be mitigated, and each farm must receive an expert-level assessment of critical importance. To mitigate poor welfare, researchers have conducted machine learning-based studies to automate the sheep health behavior monitoring process instead of using manua...
Memory Contention Analysis for 3-Phase Tasks
Arora, Jatin; Rashid, Syed Aftab; Nelissen, Geoffrey; Maia, Cláudio; Tovar, EduardoIn multiprocessor-based real-time systems, the main memory is identified as the main source of shared resource contention. Phased execution models such as the 3-phase task execution model has shown to be a good candidate to tackle the memory contention problem. It divides the execution of tasks into computation and memory phases that enable a fine-grained memory contention analysis. However, the existing work t...
RosDrive: An Open-Source ROS-Based Vehicular Simulator for STEM Control Systems...
Vasconcelos Filho, Ênio; Yudi, Jones; Abdelkader, Mohamed; Koubaa, Anis; Tovar, EduardoThe study of control systems in the engineering courses is quite complex, given the difficulty of some teachers in exemplifying and allowing the student to understand how such systems affect the environment. In this context, the STEM methodologies aim to fill this gap between the traditional classes and the student comprehension of the topic through the active learning process. Realistic open-source simulators ...