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All Outputs (45)

Electric Vehicle Battery Pack Design for Mitigating Thermal Runaway Propagation (2022)
Conference Proceeding
Copsey, E., Sun, H., & Jiang, J. (2022). Electric Vehicle Battery Pack Design for Mitigating Thermal Runaway Propagation. . https://doi.org/10.1109/vtc2022-fall57202.2022.10012777

The production of electric vehicle battery packs with ever-increasing energy densities has accelerated the electrification of the world’s automotive industry. With increased attention on the electric vehicle markets, it is vital to increase the safet... Read More about Electric Vehicle Battery Pack Design for Mitigating Thermal Runaway Propagation.

Digital Twins for Smart Cities: Case Study and Visualisation via Mixed Reality (2022)
Conference Proceeding
Piper, W., Sun, H., & Jiang, J. (2022). Digital Twins for Smart Cities: Case Study and Visualisation via Mixed Reality. . https://doi.org/10.1109/vtc2022-fall57202.2022.10012753

Digital twins is an increasingly valuable technology for realising smart cities worldwide. Visualising this technology using mixed reality creates unprecedented opportunities to easily access relevant data and information. In this paper, a digital tw... Read More about Digital Twins for Smart Cities: Case Study and Visualisation via Mixed Reality.

UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery (2022)
Conference Proceeding
Organisciak, D., Poyser, M., Alsehaim, A., Hu, S., Isaac-Medina, B. K., Breckon, T. P., & Shum, H. P. (2022). UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery. . https://doi.org/10.5220/0010836600003124

As unmanned aerial vehicles (UAV) become more accessible with a growing range of applications, the risk of UAV disruption increases. Recent development in deep learning allows vision-based counter-UAV systems to detect and track UAVs with a single ca... Read More about UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery.

Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery (2022)
Conference Proceeding
Bhowmik, N., & Breckon, T. (2022). Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery.

X-ray baggage security screening is in widespread use and crucial to maintaining transport security for threat/anomaly detection tasks. The automatic detection of anomaly, which is concealed within cluttered and complex electronics/electrical items,... Read More about Joint Sub-component Level Segmentation and Classification for Anomaly Detection within Dual-Energy X-Ray Security Imagery.

Performance comparison of Probabilistic and Artificial Neural Network Models for Long-sequence Generation of Wind Speed Forecasts (2022)
Conference Proceeding
Pina-Gongora, D. C., Kazemtabrizi, B., & Crabtree, C. (2022). Performance comparison of Probabilistic and Artificial Neural Network Models for Long-sequence Generation of Wind Speed Forecasts. . https://doi.org/10.1049/icp.2022.2777

This paper presents a new method for generating long-sequence wind speed time-series forecasts for purposes of offshore wind farm asset and operations planning. Our goal is to develop a planning decision support tool with which wind farm planners and... Read More about Performance comparison of Probabilistic and Artificial Neural Network Models for Long-sequence Generation of Wind Speed Forecasts.

EMI Shielding for 5G IOT devices with MXene Metamaterial Absorber (2022)
Conference Proceeding
Ullah, Z., Hasan, M. A., & Ben Mabrouk, I. (2022). EMI Shielding for 5G IOT devices with MXene Metamaterial Absorber. . https://doi.org/10.1109/iotsms58070.2022.10062134

In this article, we proposed a metamaterial with 2D MXene as a resonating element to reduce electromagnetic interference (EMI) at the sub-6 GHz frequency range. The shielding metamaterial is comprised of two miniaturized MXene resonator loops support... Read More about EMI Shielding for 5G IOT devices with MXene Metamaterial Absorber.

Demand side management considering household appliances and EV (2022)
Conference Proceeding
Dong, Z., Jiang, J., Qian, H., & Sun, H. (2022). Demand side management considering household appliances and EV. . https://doi.org/10.1109/icsgsc56353.2022.9963032

Combination of the information technology and the power engineering is the feature of next-generation grid. Depending on bidirectional communications, demand side management (DSM) aims at optimizing the electricity usage pattern of customers to impro... Read More about Demand side management considering household appliances and EV.

A Microgrid Management System Based on Metaheuristics Particle Swarm Optimization (2022)
Conference Proceeding
Deng, H., Jiang, J., Qian, H., & Sun, H. (2022). A Microgrid Management System Based on Metaheuristics Particle Swarm Optimization. . https://doi.org/10.1109/icsgsc56353.2022.9963000

Microgrid is playing an increasingly important role in making the utility grid more intelligent and efficient, since it can make better use of the renewable energy resources to simultaneously relieve the grid supply pressure and reduce carbon emissio... Read More about A Microgrid Management System Based on Metaheuristics Particle Swarm Optimization.

Protecting privacy in microgrids using federated learning and deep reinforcement learning (2022)
Conference Proceeding
Chen, W., Sun, H., Jiang, J., You, M., & Piper, W. (2022). Protecting privacy in microgrids using federated learning and deep reinforcement learning. . https://doi.org/10.1049/icp.2023.0100

This paper aims to improve the energy management efficiency of home microgrids while preserving privacy. The proposed microgrid model includes energy storage systems, PV panels, loads, and the connection to the main grid. A federated multi-objective... Read More about Protecting privacy in microgrids using federated learning and deep reinforcement learning.

Appliance Scheduling Optimisation Method Using Historical Data in Households with RES Generation and Battery Storage Systems (2022)
Conference Proceeding
Correa-Delval, M., Sun, H., Matthews, P. C., & Chiu, W. (2022). Appliance Scheduling Optimisation Method Using Historical Data in Households with RES Generation and Battery Storage Systems. . https://doi.org/10.1109/repe55559.2022.9949497

In recent years, the importance of reducing carbon dioxide (CO2) emissions has increased. With the use of technologies such as artificial intelligence, we can improve the way households manage their energy use to decrease cost and carbon emissions. I... Read More about Appliance Scheduling Optimisation Method Using Historical Data in Households with RES Generation and Battery Storage Systems.

VID-Trans-ReID: Enhanced Video Transformers for Person Re-identification (2022)
Conference Proceeding
Alsehaim, A., & Breckon, T. (2022). VID-Trans-ReID: Enhanced Video Transformers for Person Re-identification.

Video-based person Re-identification (Re-ID) has received increasing attention recently due to its important role within surveillance video analysis. Video-based Re- ID expands upon earlier image-based methods by extracting person features temporally... Read More about VID-Trans-ReID: Enhanced Video Transformers for Person Re-identification.

Does lossy image compression affect racial bias within face recognition? (2022)
Conference Proceeding
Yucer, S., Poyser, M., Al Moubayed, N., & Breckon, T. (2022). Does lossy image compression affect racial bias within face recognition?.

This study investigates the impact of commonplace lossy image compression on face recognition algorithms with regard to the racial characteristics of the subject. We adopt a recently proposed racial phenotype-based bias analysis methodology to measur... Read More about Does lossy image compression affect racial bias within face recognition?.

Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes (2022)
Conference Proceeding
Bond-Taylor, S., Hessey, P., Sasaki, H., Breckon, T., & Willcocks, C. (2022). Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes. In ECCV 2022: Computer Vision – ECCV 2022 (170-188)

Whilst diffusion probabilistic models can generate high quality image content, key limitations remain in terms of both generating high-resolution imagery and their associated high computational requirements. Recent Vector-Quantized image models have... Read More about Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes.

Investigation of Doubly-fed Induction Generator Controller Signals under Variable Speed Operating Conditions (2022)
Conference Proceeding
Sarma, N. (2022). Investigation of Doubly-fed Induction Generator Controller Signals under Variable Speed Operating Conditions. In 2022 11th International Conference on Renewable Energy Research and Application (ICRERA). https://doi.org/10.1109/icrera55966.2022.9922900

The analysis of the controller signals of a doublyfed induction generator under variable speed operating conditions with and without generator faults is presented in the time domain in order to more accurately investigate the conditions presently exp... Read More about Investigation of Doubly-fed Induction Generator Controller Signals under Variable Speed Operating Conditions.

Design of a Circular Dielectric Resonator Antenna for Vehicle-to-Everything Communication (2022)
Conference Proceeding
Sanders, B., Iqbal, A., Denidni, T., & Mabrouk, I. B. (2022). Design of a Circular Dielectric Resonator Antenna for Vehicle-to-Everything Communication. . https://doi.org/10.1109/ap-s/usnc-ursi47032.2022.9886586

Advanced vehicle-to-everything (V2X) communication is expected to require very large data rates, ultra high reliability, and low latency. This motivates the design of antennas able to operate in the mmWave spectrum with sufficient bandwidth and high... Read More about Design of a Circular Dielectric Resonator Antenna for Vehicle-to-Everything Communication.

A Miniaturized Implantable Antenna for ISM band Biomedical Application (2022)
Conference Proceeding
Alshammari, A., Iqbal, A., Denidni, T. A., & ben Mabrouk, I. (2022). A Miniaturized Implantable Antenna for ISM band Biomedical Application. . https://doi.org/10.1109/ap-s/usnc-ursi47032.2022.9886752

In this paper, an implantable antenna with two co-centric rectangular complementary split-ring elements with slots added between the rings are proposed. The slots, on the other hand, are utilized to fine-tune the frequency. This antenna design works... Read More about A Miniaturized Implantable Antenna for ISM band Biomedical Application.