Outputs (248)

Stability Analysis of a Quantum Network with Max-Weight Scheduling (2021)
Other
Vasantam, T., & Towsley, D. (2021). Stability Analysis of a Quantum Network with Max-Weight Scheduling

Reward-Reinforced Reinforcement Learning for Multi-agent Systems (2021)
Journal Article
Zheng, C., Yang, S., Ullauri, J. M. P., García-Domínguez, A., & Bencomo, N. (2021). Reward-Reinforced Reinforcement Learning for Multi-agent Systems

Prospective on Technical Considerations for Edge–Cloud Cooperation Using Software-Defined Networking (2021)
Book Chapter
Singh, A., Bali, R. S., & Aujla, G. S. (2021). Prospective on Technical Considerations for Edge–Cloud Cooperation Using Software-Defined Networking. In Software Defined Internet of Everything (147-176). (1). Springer, Cham. https://doi.org/10.1007/978-3-030-89328-6_9

Semantics-STGCNN: A Semantics-guided Spatial-Temporal Graph Convolutional Network for Multi-class Trajectory Prediction (2021)
Presentation / Conference Contribution
Rainbow, B. A., Men, Q., & Shum, H. P. (2021). Semantics-STGCNN: A Semantics-guided Spatial-Temporal Graph Convolutional Network for Multi-class Trajectory Prediction. . https://doi.org/10.1109/smc52423.2021.9658781

Predicting the movement trajectories of multiple classes of road users in real-world scenarios is a challenging task due to the diverse trajectory patterns. While recent works of pedestrian trajectory prediction successfully modelled the influence of... Read More about Semantics-STGCNN: A Semantics-guided Spatial-Temporal Graph Convolutional Network for Multi-class Trajectory Prediction.

Evidence for Teaching Practices that Broaden Participation for Women in Computing (2021)
Presentation / Conference Contribution
Morrison, B. B., Quinn, B. A., Bradley, S., Buffardi, K., Harrington, B., Hu, H. H., …Waite, J. (2021). Evidence for Teaching Practices that Broaden Participation for Women in Computing. In ITiCSE-WGR '21: Proceedings of the 2021 Working Group Reports on Innovation and Technology in Computer Science Education (57-131). https://doi.org/10.1145/3502870.3506568

Computing has, for many years, been one of the least demographically diverse STEM fields, particularly in terms of women's participation [12, 36]. The last decade has seen a proliferation of research exploring new teaching techniques and their effect... Read More about Evidence for Teaching Practices that Broaden Participation for Women in Computing.

Gamified and Self-Adaptive Applications for the Common Good: Research Challenges Ahead (2021)
Presentation / Conference Contribution
Bucchiarone, A., Cicchetti, A., Bencomo, N., Loria, E., & Marconi, A. (2021). Gamified and Self-Adaptive Applications for the Common Good: Research Challenges Ahead. . https://doi.org/10.1109/seams51251.2021.00028

Towards Technology Acceptance: a Bayesian Network of soft requirements, the case of the NHS COVID-19 Test and Trace App (2021)
Presentation / Conference Contribution
Paucar, L. H. G., Bencomo, N., Sutcliffe, A. G., Yue, T., & Mirakhorli, M. (2021). Towards Technology Acceptance: a Bayesian Network of soft requirements, the case of the NHS COVID-19 Test and Trace App. In T. Yue, & M. Mirakhorli (Eds.), . https://doi.org/10.1109/rew53955.2021.00026

DurLAR: A High-Fidelity 128-Channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-Modal Autonomous Driving Applications (2021)
Presentation / Conference Contribution
Li, L., Ismail, K. N., Shum, H. P., & Breckon, T. P. (2021). DurLAR: A High-Fidelity 128-Channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-Modal Autonomous Driving Applications. . https://doi.org/10.1109/3dv53792.2021.00130

We present DurLAR, a high-fidelity 128-channel 3D LiDAR dataset with panoramic ambient (near infrared) and reflectivity imagery, as well as a sample benchmark task using depth estimation for autonomous driving applications. Our driving platform is eq... Read More about DurLAR: A High-Fidelity 128-Channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-Modal Autonomous Driving Applications.

RDMSim: An Exemplar for Evaluation and Comparison of Decision-Making Techniques for Self-Adaptation (2021)
Presentation / Conference Contribution
Samin, H., Paucar, L. H. G., Bencomo, N., Hurtado, C. M. C., & Fredericks, E. M. (2021). RDMSim: An Exemplar for Evaluation and Comparison of Decision-Making Techniques for Self-Adaptation. . https://doi.org/10.1109/seams51251.2021.00039

Leveraging Blockchain for Secure Drone-to-Everything Communications (2021)
Journal Article
Aujla, G. S., Vashisht, S., Garg, S., Kumar, N., & Kaddoum, G. (2021). Leveraging Blockchain for Secure Drone-to-Everything Communications. IEEE Communications Standards Magazine, 5(4), 80-87. https://doi.org/10.1109/mcomstd.0001.2100012

The popularity of drones has increased their deployment in a wide range of applications like commercial delivery, industrial systems, monitoring, surveillance, and surveys. The facility of fast deployment and cost effectiveness make drones a potentia... Read More about Leveraging Blockchain for Secure Drone-to-Everything Communications.