All Outputs (41)

Incremental growth on Compositional Pattern Producing Networks based optimization of biohybrid actuators (2024)
Conference Proceeding
Tsompanas, M. A. (2024). Incremental growth on Compositional Pattern Producing Networks based optimization of biohybrid actuators. In Applications of Evolutionary Computation (275-289). https://doi.org/10.1007/978-3-031-56855-8_17

One of the training methods of Artificial Neural Networks is Neuroevolution (NE) or the application of Evolutionary Optimization on the architecture and weights of networks to fit the target behaviour. In order to provide competitive results, three k... Read More about Incremental growth on Compositional Pattern Producing Networks based optimization of biohybrid actuators.

Cyber Funfair: Creating immersive and educational experiences for teaching Cyber Physical Systems Security (2024)
Conference Proceeding
Mills, A., White, J., & Legg, P. (2024). Cyber Funfair: Creating immersive and educational experiences for teaching Cyber Physical Systems Security. In SIGCSE 2024: Proceedings of the 55th ACM Technical Symposium on Computer Science Education (847-852). https://doi.org/10.1145/3626252.3630820

Delivering meaningful and inspiring cyber security education for younger audiences can often be a challenge due to limited expertise and resources. Key to any outreach activity is that it both develops a learner's curiosity, as well as providing educ... Read More about Cyber Funfair: Creating immersive and educational experiences for teaching Cyber Physical Systems Security.

Explainable NLP model for predicting patient admissions at emergency department using triage notes (2024)
Conference Proceeding
Arnaud, E., Elbattah, M., Moreno-Sánchez, P. A., Dequen, G., & Ghazali, D. A. (2024). Explainable NLP model for predicting patient admissions at emergency department using triage notes. In 2023 IEEE International Conference on Big Data (BigData) (4843-4847). https://doi.org/10.1109/bigdata59044.2023.10386753

Explainable Artificial Intelligence (XAI) has the potential to revolutionize healthcare by providing more transparent, trustworthy, and understandable predictions made by AI models. To this end, the present study aims to develop an explainable NLP mo... Read More about Explainable NLP model for predicting patient admissions at emergency department using triage notes.

Obmaaq: Ontology-based model for automated assessment of short-answer questions (2024)
Conference Proceeding
Ramnarain-Seetohul, V., Bassoo, V., & Rosunally, Y. (in press). Obmaaq: Ontology-based model for automated assessment of short-answer questions. In 2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI). https://doi.org/10.1109/ICAEECI58247.2023.10370992

Automated scoring of short answers is becoming increasingly important nowadays, as more classes are taking place online due to COVID-19 outbreaks. Over the past 50 years, different techniques have been applied to develop ways of assessing short answe... Read More about Obmaaq: Ontology-based model for automated assessment of short-answer questions.

Electrical properties of proteinoids for unconventional computing architectures (2023)
Conference Proceeding
Mougkogiannis, P., & Adamatzky, A. (2023). Electrical properties of proteinoids for unconventional computing architectures. In NANOARCH '23: Proceedings of the 18th ACM International Symposium on Nanoscale Architectures (1-4). https://doi.org/10.1145/3611315.3633264

Proteinoids are peptide-like molecules that arise from the combination of amino acids in pre-biotic environments. Recent studies have revealed distinctive electrical characteristics of proteinoids, such as the presence of voltage-gated ion channels,... Read More about Electrical properties of proteinoids for unconventional computing architectures.

A decision-making architecture for human-robot collaboration: Model transferability (2023)
Conference Proceeding
Sobhani, M., Smith, J., Pipe, A., & Peer, A. (2023). A decision-making architecture for human-robot collaboration: Model transferability. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1 (719-726). https://doi.org/10.5220/0012210600003543

In this paper, we aim to demonstrate the potential for wider-ranging capabilities and ease of transferability of our recently developed decision-making architecture for human-robot collaboration. To this end, a somewhat related but different applicat... Read More about A decision-making architecture for human-robot collaboration: Model transferability.

Development and evaluation of a mobile app to support reading education (2023)
Conference Proceeding
Mthethwa, L. C., & Matthews, P. (2023). Development and evaluation of a mobile app to support reading education. In AfriCHI '23: Proceedings of the 4th African Human Computer Interaction Conference (58-63). https://doi.org/10.1145/3628096.3628751

We report on the design, development and evaluation of an app to support teachers in the teaching of reading at primary level. The app was developed with two main features: book levelling, where a book photograph, OCR and a simple machine learning mo... Read More about Development and evaluation of a mobile app to support reading education.

Improving search space analysis of fuzzing mutators using cryptographic structures (2023)
Conference Proceeding
Chafjiri, S. B., Legg, P., Tsompanas, M., & Hong, J. (in press). Improving search space analysis of fuzzing mutators using cryptographic structures. In Lecture Notes in Network Security

This paper introduces a novel approach to enhance the performance of software fuzzing mutator tools, by leveraging cryptographic structures known as substitution-permutation networks and Feistel networks. By integrating these structures into the exis... Read More about Improving search space analysis of fuzzing mutators using cryptographic structures.

Predicting social trust from implicit feedback (2023)
Conference Proceeding
Oshodin, E. (2023). Predicting social trust from implicit feedback. In Artificial Intelligence XL (228-233). https://doi.org/10.1007/978-3-031-47994-6_20

Element of trust exists in every network structure of diverse fields, but suitable computational methods for evaluating the trust remain a problem since there are different definitions of trust in diverse fields where several entities interact with e... Read More about Predicting social trust from implicit feedback.

DPFTT: Distributed particle filter for target tracking in the Internet of Things (2023)
Conference Proceeding
Boulkaboul, S., Djenouri, D., & Bagaa, M. (2023). DPFTT: Distributed particle filter for target tracking in the Internet of Things. In 2023 12th IFIP/IEEE International Conference on Performance Evaluation and Modeling in Wired and Wireless Networks (PEMWN). https://doi.org/10.23919/PEMWN58813.2023.10304926

A novel distributed particle filter algorithm for target tracking is proposed in this paper. It uses new metrics and addresses the measurement uncertainty problem by adapting the particle filter to environmental changes and estimating the kinematic (... Read More about DPFTT: Distributed particle filter for target tracking in the Internet of Things.

Evaluating data distribution strategies in federated learning: A trade-off analysis between privacy and performance for IoT security (2023)
Conference Proceeding
White, J., & Legg, P. (in press). Evaluating data distribution strategies in federated learning: A trade-off analysis between privacy and performance for IoT security.

Federated learning is an effective approach for training a global machine learning model. It uses locally acquired data without having to share local data with the centralised server. This method provides a machine learning model beneficial for all p... Read More about Evaluating data distribution strategies in federated learning: A trade-off analysis between privacy and performance for IoT security.

Generating event sensor readings using spatial correlations and a graph sensor adversarial model for energy saving in IoT: GSAVES (2023)
Conference Proceeding
Laidi, R., Djenouri, D., Bagaa, M., Khelladi, L., & Djenouri, Y. (2023). Generating event sensor readings using spatial correlations and a graph sensor adversarial model for energy saving in IoT: GSAVES. In 2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). https://doi.org/10.1109/pimrc56721.2023.10293922

This work targets a comprehensive model enabling energy-constrained IoT (Internet of Things) sensor devices to be inactive for extended periods while estimating their readings of real-time events. Although events seem semantically uncoupled, they are... Read More about Generating event sensor readings using spatial correlations and a graph sensor adversarial model for energy saving in IoT: GSAVES.

What will make misinformation spread: An XAI perspective (2023)
Conference Proceeding
Bo, H., Wu, Y., You, Z., McConville, R., Hong, J., & Liu, W. (2023). What will make misinformation spread: An XAI perspective. In L. Longo (Ed.), Explainable Artificial Intelligence (321-337). https://doi.org/10.1007/978-3-031-44067-0_17

Explainable Artificial Intelligence (XAI) techniques can provide explanations of how AI systems or models make decisions, or what factors AI considers when making the decisions. Online social networks have a problem with misinformation which is known... Read More about What will make misinformation spread: An XAI perspective.

The effect of parameters on the success of heuristic algorithms in personalized personnel scheduling (2023)
Conference Proceeding
Gülmez, E., Urgancı, K. B., Koruca, H. İ., & Aydin, M. E. (2023). The effect of parameters on the success of heuristic algorithms in personalized personnel scheduling. In Advances in Intelligent Manufacturing and Service System Informatics (600-611). https://doi.org/10.1007/978-981-99-6062-0_55

Work-life balance is an approach that aims to enable employees to balance their work, family, and private lives. It is seen that the factors in the work-life balance are not relevant to work and family, considering the activities that one wishes for... Read More about The effect of parameters on the success of heuristic algorithms in personalized personnel scheduling.

Knowledge guided deep learning for general-purpose computer vision applications (2023)
Conference Proceeding
Djenouri, Y., Belbachir, A. N., Jhaveri, R. H., & Djenouri, D. (2023). Knowledge guided deep learning for general-purpose computer vision applications. In Computer Analysis of Images and Patterns (185-194). https://doi.org/10.1007/978-3-031-44237-7_18

This research targets general-purpose smart computer vision that eliminates reliance on domain-specific knowledge to reach adaptable generic models for flexible applications. It proposes a novel approach in which several deep learning models are trai... Read More about Knowledge guided deep learning for general-purpose computer vision applications.

Understanding people's perceptions of their liveable neighbourhoods: A case study of East Bristol (2023)
Conference Proceeding
Covato, E., & Jeawak, S. (2023). Understanding people's perceptions of their liveable neighbourhoods: A case study of East Bristol. . https://doi.org/10.4230/LIPIcs.GIScience.2023.24

Liveable neighbourhoods are urban planning initiatives that aim to improve the quality of residential areas. In this paper, we focus on the East Bristol Liveable Neighbourhood (EBLN) to understand people’s perceptions of their neighbourhood’s urban r... Read More about Understanding people's perceptions of their liveable neighbourhoods: A case study of East Bristol.

A systematic review of reverberation and accessibility for B/blind users in virtual environments (2023)
Conference Proceeding
Child, L., Mitchell, T., & Ford, N. (2023). A systematic review of reverberation and accessibility for B/blind users in virtual environments.

Reverberation is often used in linear and non-linear media to convey the acoustic characteristics of a space. This information is presented alongside visual stimuli to create a multi-modal experience, assisting participants in developing visual and a... Read More about A systematic review of reverberation and accessibility for B/blind users in virtual environments.

Maintenance automation using deep learning methods: A case study from the aerospace industry (2023)
Conference Proceeding
Mayhew, P. J., Ihshaish, H., Deza, I., & Del Amo, A. (2023). Maintenance automation using deep learning methods: A case study from the aerospace industry. In Artificial Neural Networks and Machine Learning – ICANN 2023 (295-307). https://doi.org/10.1007/978-3-031-44204-9_25

In this study, state-of-the-art AI models are employed to classify aerospace maintenance records into categories based on the fault descriptions of avionic components. The classification is performed using short natural language text descriptions pro... Read More about Maintenance automation using deep learning methods: A case study from the aerospace industry.

Enhancing software fault prediction with deep neural networks: An empirical analysis of error-type metrics (2023)
Conference Proceeding
Phung, K., Ogunshile, E., & Aydin, M. E. (in press). Enhancing software fault prediction with deep neural networks: An empirical analysis of error-type metrics.

In the context of software quality assurance, Software Fault Prediction (SFP) serves as a critical technique to optimise costs and efforts by classifying software modules as faulty or not, using pertinent project characteristics. Despite considerable... Read More about Enhancing software fault prediction with deep neural networks: An empirical analysis of error-type metrics.

Feel the force, see the force: Exploring visual-tactile associations of deformable surfaces with colours and shapes (2023)
Conference Proceeding
Steer, C., Dinca, T., Jicol, C., Proulx, M. J., & Alexander, J. (2023). Feel the force, see the force: Exploring visual-tactile associations of deformable surfaces with colours and shapes. In CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (1-13). https://doi.org/10.1145/3544548.3580830

Deformable interfaces provide unique interaction potential for force input, for example, when users physically push into a soft display surface. However, there remains limited understanding of which visual-tactile design elements signify the presence... Read More about Feel the force, see the force: Exploring visual-tactile associations of deformable surfaces with colours and shapes.