Conversation analysis for computational modelling of task-oriented dialogue (2023)
Thesis
Duran, N. Conversation analysis for computational modelling of task-oriented dialogue. (Thesis). University of the West of England. Retrieved from https://uwe-repository.worktribe.com/output/10021806

Current methods of dialogue modelling for Conversational AI (CAI) bear little resemblance to the manner in which humans organise conversational interactions. The way utterances are represented, interpreted, and generated are determined by the necessi... Read More about Conversation analysis for computational modelling of task-oriented dialogue.

Personalised learning through context-based adaptation in the serious games with gating mechanism (2023)
Journal Article
Shum, L. C., Rosunally, Y., Scarle, S., & Munir, K. (in press). Personalised learning through context-based adaptation in the serious games with gating mechanism. Education and Information Technologies,

When the traditional "one size fits all" approach is used in designing educational games, the game context is usually arranged in a fixed sequence. However, the designated content may not effectively support the diversity of players. The player's abi... Read More about Personalised learning through context-based adaptation in the serious games with gating mechanism.

Modelling interrelationship between diseases with communicating stream x-machines (2022)
Journal Article
Jayatilake, D., Phung, K., Ogunshile, E., & Aydin, M. (2022). Modelling interrelationship between diseases with communicating stream x-machines. Proceedings of the Institute for System Programming of the RAS, 34(6), 147-164. https://doi.org/10.15514/ispras-2022-34%286%29-11

The world is moving towards alternative medicine and behavioural alteration for treating, managing, and preventing chronical diseases. In the last few decades, diagrammatical models have been extensively used to describe and understand the behaviou... Read More about Modelling interrelationship between diseases with communicating stream x-machines.

Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification (2022)
Journal Article
McCarthy, A., Ghadafi, E., Andriotis, P., & Legg, P. (2023). Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification. Journal of Information Security and Applications, 72, Article 103398. https://doi.org/10.1016/j.jisa.2022.103398

Machine learning is key for automated detection of malicious network activity to ensure that computer networks and organizations are protected against cyber security attacks. Recently, there has been growing interest in the domain of adversarial mach... Read More about Defending against adversarial machine learning attacks using hierarchical learning: A case study on network traffic attack classification.

A generalised dropout mechanism for distributed systems (2022)
Journal Article
Bull, L., & Liu, H. (in press). A generalised dropout mechanism for distributed systems. Artificial Life, https://doi.org/10.1162/artl_a_00393

This letter uses a modified form of the NK model introduced to explore aspects of distributed control. In particular, a previous result suggesting the use of dynamically formed subgroups within the overall system can be more effective than global con... Read More about A generalised dropout mechanism for distributed systems.

Problem classification for tailored help desk auto replies (2022)
Conference Proceeding
Nicholls, R., Fellows, R., Battle, S., & Ihshaish, H. (2022). Problem classification for tailored help desk auto replies. In E. Pimenidis, P. Angelov, C. Jayne, A. Papaleonidas, & M. Aydin (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2022 (445-454). https://doi.org/10.1007/978-3-031-15937-4_37

IT helpdesks are charged with the task of responding quickly to user queries. To give the user confidence that their query matters, the helpdesk will auto-reply to the user with confirmation that their query has been received and logged. This auto-re... Read More about Problem classification for tailored help desk auto replies.

Development of communicating stream x-machine tool for modeling and generating test cases for automated teller machine (2022)
Presentation / Conference
Adewale Sanusi, B., Ogunshile, E., Aydin, M., Olatunde Olabiyisi, S., & Oyedepo Oyediran, M. (2022, August). Development of communicating stream x-machine tool for modeling and generating test cases for automated teller machine. Paper presented at 9th International Conference on Computer Science and Information Technology (CSIT 2022), Chennai, India

The improvement of this paper takes advantage of the existing formal method called Stream X-Machine by optimizing the theory and applying it to practice in a large-scale system. This optimized formal approach called Communicating Stream X-Machine (CS... Read More about Development of communicating stream x-machine tool for modeling and generating test cases for automated teller machine.

Cellular automata application on chemical computing logic circuits (2022)
Conference Proceeding
Tsompanas, M., Chatzinikolaou, T. P., & Sirakoulis, G. C. (2022). Cellular automata application on chemical computing logic circuits. In B. Chopard, S. Bandini, A. Dennunzio, & M. A. Haddad (Eds.), International Conference on Cellular Automata for Research and Industry: ACRI 2022: Cellular Automata (3-14). https://doi.org/10.1007/978-3-031-14926-9_1

Cellular Automata (CAs) have been proved to be a robust tool for mimicking a plethora of biological, physical and chemical systems. CAs can be used as an alternative to partial differential equations, in order to illustrate the evolution in time of t... Read More about Cellular automata application on chemical computing logic circuits.

A haploid-diploid evolutionary algorithm optimizing nanoparticle based cancer treatments (2022)
Book Chapter
Tsompanas, M., Bull, L., Adamatzky, A., & Balaz, I. (2022). A haploid-diploid evolutionary algorithm optimizing nanoparticle based cancer treatments. In I. Balaz, & A. Adamatzky (Eds.), Cancer, Complexity, Computation (237-251). Springer. https://doi.org/10.1007/978-3-031-04379-6_10

This paper uses a recent explanation for the fundamental haploid-diploid lifecycle of eukaryotic organisms to present a new evolutionary algorithm that differs from all previous known work using diploid representations. A form of the Baldwin effect h... Read More about A haploid-diploid evolutionary algorithm optimizing nanoparticle based cancer treatments.

Supporting patient nutrition in critical care units (2022)
Conference Proceeding
Soomro, K., Pimenidis, E., & McWilliams, C. (2022). Supporting patient nutrition in critical care units. In Engineering Applications of Neural Networks: EANN 2022: Engineering Applications of Neural Networks (128-136). https://doi.org/10.1007/978-3-031-08223-8_11

Critical Care Unit (CCU) patients often benefit from being referred to dietitians for various reasons. This can help improve recovery time, resulting in more effective utilisation of valuable resources within the NHS (National Health Service) in the... Read More about Supporting patient nutrition in critical care units.

HyperModels - A framework for GPU accelerated physical modelling sound synthesis (2022)
Conference Proceeding
Renney, H., Willemsen, S., Gaster, B. R., & Mitchell, T. J. (in press). HyperModels - A framework for GPU accelerated physical modelling sound synthesis. . https://doi.org/10.21428/92fbeb44.98a4210a

Physical modelling sound synthesis methods generate vast and intricate sound spaces that are navigated using meaningful parameters. Numerical based physical modelling nsynthesis methods provide authentic representations of the physics they model. Unf... Read More about HyperModels - A framework for GPU accelerated physical modelling sound synthesis.

Studying how digital luthiers choose their tools (2022)
Conference Proceeding
Renney, N., Renney, H., Mitchell, T. J., & Gaster, B. R. (2022). Studying how digital luthiers choose their tools. . https://doi.org/10.1145/3491102.3517656

Digital lutherie is a sub-domain of digital craft focused on creating digital musical instruments: high-performance devices for musical expression. It represents a nuanced and challenging area of human-computer interaction that is well established an... Read More about Studying how digital luthiers choose their tools.

Nonbinary representations in the NK and NKCS models (2022)
Journal Article
Bull, L. (2022). Nonbinary representations in the NK and NKCS models. Complex Systems -Champaign-, 31(1), 87-101. https://doi.org/10.25088/ComplexSystems.31.1.87

The NK model has been used widely to explore aspects of natural evolution and complex systems. Traditionally, the model has used a binary representation scheme. This paper introduces a modified form of the NK model through which to systematically exp... Read More about Nonbinary representations in the NK and NKCS models.

Fast and accurate evaluation of collaborative filtering recommendation algorithms (2022)
Conference Proceeding
Polatidis, N., Kapetanakis, S., Pimenidis, E., & ManolopouLos, Y. (in press). Fast and accurate evaluation of collaborative filtering recommendation algorithms.

Collaborative filtering are recommender systems algorithms that provide personalized recommendations to users in various online environments such as movies, music, books, jokes and others. There are many such recommendation algorithms and, regarding... Read More about Fast and accurate evaluation of collaborative filtering recommendation algorithms.

Variational restricted Boltzmann machines to automated anomaly detection (2022)
Journal Article
Demertzis, K., Iliadis, L., Pimenidis, E., & Kikiras, P. (2022). Variational restricted Boltzmann machines to automated anomaly detection. Neural Computing and Applications, 34, 15207–15220. https://doi.org/10.1007/s00521-022-07060-4

Data-driven methods are implemented using particularly complex scenarios that reflect in-depth perennial knowledge and research. Hence, the available intelligent algorithms are completely dependent on the quality of the available data. This is not po... Read More about Variational restricted Boltzmann machines to automated anomaly detection.

Memory-constrained context-aware reasoning (2022)
Conference Proceeding
Uddin, I., Rakib, A., Ali, M., & Vinh, P. C. (2022). Memory-constrained context-aware reasoning. In P. Cong Vinh, & A. Rakib (Eds.), Context-Aware Systems and Applications (133-146). https://doi.org/10.1007/978-3-030-93179-7_11

The context-aware computing paradigm introduces environments, known as smart spaces, which can unobtrusively and proactively assist their users. These systems are currently mostly implemented on mobile platforms considering various techniques, includ... Read More about Memory-constrained context-aware reasoning.

Evolving Boolean regulatory networks with variable gene expression times (2021)
Book Chapter
Bull, L. (2021). Evolving Boolean regulatory networks with variable gene expression times. In Handbook of Unconventional Computing (247-259). World Scientific Publishing. https://doi.org/10.1142/9789811235726_0007

The time taken for gene expression varies not least because proteins vary in length considerably. This paper uses an abstract, tuneable Boolean regulatory network model to explore gene expression time variation. In particular, it is shown how non-uni... Read More about Evolving Boolean regulatory networks with variable gene expression times.

Bespoke anywhere (2021)
Conference Proceeding
Gaster, B., & Challinor, R. (2021). Bespoke anywhere.

This paper reports on a project aimed to break away from the portability concerns of native DSP code between different platforms, thus freeing the instrument designer from the burden of porting new Digital Musical Instruments (DMIs) to different arch... Read More about Bespoke anywhere.

Blockchain and artificial intelligence – Managing a secure and sustainable supply chain (2021)
Book Chapter
Pimenidis, E., Patsavellas, J., & Tonkin, M. (2021). Blockchain and artificial intelligence – Managing a secure and sustainable supply chain. In H. Jahankhani, A. Jamal, & S. Lawson (Eds.), Cybersecurity, Privacy and Freedom Protection in the Connected World. (1). Springer. https://doi.org/10.1007/978-3-030-68534-8

Supply chain management is often the most challenging part of any business that manufactures, sells goods, or provides services. Regardless of whether the operations are mostly physical or online, managing supply chains largely relies on being able t... Read More about Blockchain and artificial intelligence – Managing a secure and sustainable supply chain.

A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach (2021)
Journal Article
Phung, K., Jayatilake, D., Ogunshile, E., & Aydin, M. (2021). A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach. Programming and Computer Software, 47(8), 765-777. https://doi.org/10.1134/S0361768821080211

In the biomedical domain, diagrammatical models have been extensively used to describe and understand the behaviour of biological organisms (biological agents) for decades. Although these models are simple and comprehensive, they can only offer a sta... Read More about A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach.