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Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization (2024)
Journal Article
Zeng, L., Liu, Q., Shen, S., & Liu, X. (2024). Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization. Tsinghua Science and Technology, 29(3), 806 - 817. https://doi.org/10.26599/TST.2023.9010058

Edge computing nodes undertake more and more tasks as business density grows. How to efficiently allocate large-scale and dynamic workloads to edge computing resources has become a critical challenge. An edge task scheduling approach based on an impr... Read More about Improved Double Deep Q Network-Based Task Scheduling Algorithm in Edge Computing for Makespan Optimization.

DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences (2024)
Conference Proceeding
Koniaris, B., Sinclair, D., & Mitchell, K. (in press). DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences.

DanceMark is an open telemetry framework designed for latency-sensitive real-time networked immersive experiences, focusing on online dancing in virtual reality within the DanceGraph platform. The goal is to minimize end-to-end latency and enhance us... Read More about DanceMark: An open telemetry framework for latency sensitive real-time networked immersive experiences.

Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP (2023)
Conference Proceeding
Datta, S., Ganguly, D., Mothe, J., & Ullah, M. Z. (2023). Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP. In Proceedings of the The QPP++ 2023: Query Performance Prediction and Its Evaluation in New Tasks Workshop co-located with The 45th European Conference on Information Retrieval (ECIR) (7-12)

In information retrieval, query performance prediction aims to predict whether a search engine is likely to succeed in retrieving potentially relevant documents to a user's query. This problem is usually cast into a regression problem where a machine... Read More about Combining Word Embedding Interactions and LETOR Feature Evidences for Supervised QPP.

Expressive Talking Avatars (2023)
Journal Article
Pan, Y., Tan, S., Cheng, S., Lin, Q., Zeng, Z., & Mitchell, K. (in press). Expressive Talking Avatars. IEEE Transactions on Visualization and Computer Graphics,

Stylized avatars are common virtual representations used in VR to support interaction and communication between remote collaborators. However, explicit expressions are notoriously difficult to create, mainly because most current methods rely on geome... Read More about Expressive Talking Avatars.

Real-time Facial Animation for 3D Stylized Character with Emotion Dynamics (2023)
Conference Proceeding
Pan, Y., Zhang, R., Wang, J., Ding, Y., & Mitchell, K. (2023). Real-time Facial Animation for 3D Stylized Character with Emotion Dynamics. In MM '23: Proceedings of the 31st ACM International Conference on Multimedia (6851-6859). https://doi.org/10.1145/3581783.3613803

Our aim is to improve animation production techniques' efficiency and effectiveness. We present two real-time solutions which drive character expressions in a geometrically consistent and perceptually valid way. Our first solution combines keyframe a... Read More about Real-time Facial Animation for 3D Stylized Character with Emotion Dynamics.

Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements, and Challenges (2023)
Journal Article
Liu, Q., Yang, Z., Ji, R., Zhang, Y., Bilal, M., Liu, X., …Xu, X. (2023). Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements, and Challenges. IEEE Systems, Man, and Cybernetics Magazine, 9(4), 4-12. https://doi.org/10.1109/msmc.2022.3216943

Radars are widely used to obtain echo information for effective prediction, such as precipitation nowcasting. In this article, recent relevant scientific investigation and practical efforts using deep learning (DL) models for weather radar data analy... Read More about Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements, and Challenges.

Responsible Design & Evaluation of a Conversational Agent for a National Careers Service (2023)
Conference Proceeding
Wilson, M., Cruickshank, P., Gkatzia, D., & Robertson, P. (in press). Responsible Design & Evaluation of a Conversational Agent for a National Careers Service.

This PhD project applies a research-through-design approach to the development of a conversational agent for a national career service for young people. This includes addressing practical, interactional and ethical aspects of the system. For each asp... Read More about Responsible Design & Evaluation of a Conversational Agent for a National Careers Service.

Towards Improving Accessibility of Web Auditing with Google Lighthouse (2023)
Conference Proceeding
McGill, T., Bamgboye, O., Liu, X., & Kalutharage, C. S. (2023). Towards Improving Accessibility of Web Auditing with Google Lighthouse. In H. Shahriar, Y. Teranishi, A. Cuzzocrea, M. Sharmin, D. Towey, A. Jahangir Alam Majumder, …S. Iqbal Ahamed (Eds.), 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC) (1594-1599). https://doi.org/10.1109/COMPSAC57700.2023.00246

Google Lighthouse is a tool made by Google for auditing web pages performance, accessibility, SEO, and best practices with the intention of improving the quality of the websites. This allows software developers to understand areas of improvement with... Read More about Towards Improving Accessibility of Web Auditing with Google Lighthouse.

A cloud-based Bi-directional LSTM approach to grid-connected solar PV energy forecasting for multi-energy systems (2023)
Journal Article
Liu, Q., Darteh, O. F., Bilal, M., Huang, X., Attique, M., Liu, X., & Acakpovi, A. (2023). A cloud-based Bi-directional LSTM approach to grid-connected solar PV energy forecasting for multi-energy systems. Sustainable Computing, 40, Article 100892. https://doi.org/10.1016/j.suscom.2023.100892

The drive for smarter, greener, and more livable cities has led to research towards more effective solar energy forecasting techniques and their integration into traditional power systems. However, the availability of real-time data, data storage, an... Read More about A cloud-based Bi-directional LSTM approach to grid-connected solar PV energy forecasting for multi-energy systems.

Editorial: Games May Host the First Rightful AI Citizens (2023)
Journal Article
Mitchell, K. (2023). Editorial: Games May Host the First Rightful AI Citizens. Games: Research and Practice, 1(2), 1-7. https://doi.org/10.1145/3606834

GAMES creatively take place in imaginative worlds informed by, but often not limited by, real-world challenges, and this advantageously provides an accelerated environment for innovation, where concepts and ideas can be explored unencumbered by physi... Read More about Editorial: Games May Host the First Rightful AI Citizens.

A Multi-Swarm PSO Approach to Large-Scale Task Scheduling in a Sustainable Supply Chain Datacenter (2023)
Journal Article
Liu, Q., Zeng, L., Bilal, M., Song, H., Liu, X., Zhang, Y., & Cao, X. (2023). A Multi-Swarm PSO Approach to Large-Scale Task Scheduling in a Sustainable Supply Chain Datacenter. IEEE Transactions on Green Communications and Networking, 7(4), 1667 - 1677. https://doi.org/10.1109/tgcn.2023.3283509

Supply chain management is a vital part of ensuring service quality and production efficiency in industrial applications. With the development of cloud computing and data intelligence in modern industries, datacenters have become an important basic s... Read More about A Multi-Swarm PSO Approach to Large-Scale Task Scheduling in a Sustainable Supply Chain Datacenter.

DanceGraph: A Complementary Architecture for Synchronous Dancing Online (2023)
Presentation / Conference
Sinclair, D., Ademola, A. V., Koniaris, B., & Mitchell, K. (2023, May). DanceGraph: A Complementary Architecture for Synchronous Dancing Online. Paper presented at 36th International Computer Animation & Social Agents (CASA) 2023, Limassol, Cyprus

DanceGraph is an architecture for synchronized online dancing overcoming the latency of net-worked body pose sharing. We break down this challenge by developing a real-time bandwidth-efficient architecture to minimize lag and reduce the timeframe of... Read More about DanceGraph: A Complementary Architecture for Synchronous Dancing Online.

To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features (2023)
Conference Proceeding
Vermetten, D., Wang, H., Sim, K., & Hart, E. (2023). To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features. In J. Correia, S. Smith, & R. Qaddoura (Eds.), Applications of Evolutionary Computation: 26th International Conference, EvoApplications 2023 (335-350). https://doi.org/10.1007/978-3-031-30229-9_22

Dynamic algorithm selection aims to exploit the complementarity of multiple optimization algorithms by switching between them during the search. While these kinds of dynamic algorithms have been shown to have potential to outperform their component a... Read More about To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features.

A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms (2023)
Conference Proceeding
Montague, K., Hart, E., Paechter, B., & Nitschke, G. (2023). A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms. In J. Correia, S. Smith, & R. Qaddoura (Eds.), Applications of Evolutionary Computation: 26th European Conference, EvoApplications 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings (145-160). https://doi.org/10.1007/978-3-031-30229-9_10

Designing controllers for a swarm of robots such that collabo-rative behaviour emerges at the swarm level is known to be challenging. Evolutionary approaches have proved promising, with attention turning more recently to evolving repertoires of dive... Read More about A Quality-Diversity Approach to Evolving a Repertoire of Diverse Behaviour-Trees in Robot Swarms.

Improving the size and quality of MAP-Elites containers via multiple emitters and decoders for urban logistics (2023)
Conference Proceeding
Urquhart, N., & Hart, E. (2023). Improving the size and quality of MAP-Elites containers via multiple emitters and decoders for urban logistics. In Applications of Evolutionary Computation – 26th International Conference, EvoApplications 2023 (35-52). https://doi.org/10.1007/978-3-031-30229-9

Quality-diversity (QD) methods such as MAP-Elites have been demonstrated to be useful in the domain of combinatorial optimisation due to their ability to generate a large set of solutions to a single-objective problem that are diverse with respect to... Read More about Improving the size and quality of MAP-Elites containers via multiple emitters and decoders for urban logistics.

DIGNEA: A tool to generate diverse and discriminatory instance suites for optimisation domains (2023)
Journal Article
Marrero, A., Segredo, E., León, C., & Hart, E. (2023). DIGNEA: A tool to generate diverse and discriminatory instance suites for optimisation domains. SoftwareX, 22, Article 101355. https://doi.org/10.1016/j.softx.2023.101355

To advance research in the development of optimisation algorithms, it is crucial to have access to large test-beds of diverse and discriminatory instances from a domain that can highlight strengths and weaknesses of different algorithms. The DIGNEA t... Read More about DIGNEA: A tool to generate diverse and discriminatory instance suites for optimisation domains.

CFNet: An Eigenvalue Preserved Approach to Multiscale Building Segmentation in High-Resolution Remote Sensing Images (2023)
Journal Article
Liu, Q., Li, Y., Bilal, M., Liu, X., Zhang, Y., Wang, H., & Xu, X. (2023). CFNet: An Eigenvalue Preserved Approach to Multiscale Building Segmentation in High-Resolution Remote Sensing Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 2481-2491. https://doi.org/10.1109/jstars.2023.3244336

In recent years, AI and Deep Learning (DL) methods have been widely used for object classification, recognition, and segmentation of high-resolution multispectral remote sensing images. These DL-based solutions perform better compare to traditional s... Read More about CFNet: An Eigenvalue Preserved Approach to Multiscale Building Segmentation in High-Resolution Remote Sensing Images.

Explainable AI-Based DDOS Attack Identification Method for IoT Networks (2023)
Journal Article
Kalutharage, C. S., Liu, X., Chrysoulas, C., Pitropakis, N., & Papadopoulos, P. (2023). Explainable AI-Based DDOS Attack Identification Method for IoT Networks. Computers, 12(2), Article 32. https://doi.org/10.3390/computers12020032

The modern digitized world is mainly dependent on online services. The availability of online systems continues to be seriously challenged by distributed denial of service (DDoS) attacks. The challenge in mitigating attacks is not limited to identify... Read More about Explainable AI-Based DDOS Attack Identification Method for IoT Networks.

Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches (2023)
Journal Article
Alissa, M., Sim, K., & Hart, E. (2023). Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches. Journal of Heuristics, 29(1), 1-38. https://doi.org/10.1007/s10732-022-09505-4

We propose a novel technique for algorithm-selection, applicable to optimisation domains in which there is implicit sequential information encapsulated in the data, e.g., in online bin-packing. Specifically we train two types of recurrent neural netw... Read More about Automated Algorithm Selection: from Feature-Based to Feature-Free Approaches.