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.

The nonequilibrium potential today: A short review (2022)
Journal Article
Wio, H. S., Deza, J. I., Sánchez, A. D., García-García, R., Gallego, R., Revelli, J. A., & Deza, R. R. (2022). The nonequilibrium potential today: A short review. Chaos, Solitons and Fractals, 165(Part 1), 112778. https://doi.org/10.1016/j.chaos.2022.112778

A brief review is made of the birth and evolution of the “nonequilibrium potential” (NEP) concept. As if providing a landscape for qualitative reasoning were not helpful enough, the NEP adds a quantitative dimension to the qualitative theory of diffe... Read More about The nonequilibrium potential today: A short review.

Developing concept system for robotics open heart surgery (2022)
Digital Artefact
Farzadnia, F., D’Agnano, F., & Jorgensen, T. (in press). Developing concept system for robotics open heart surgery. [Website article]

Research interests in the healthcare field have for some time been growing within CFPR. A connection with Dr Muhammad Bilal from UWE’s Big Data Enterprise and Artificial Intelligence Lab is, in particular, developing some promising healthcare researc... Read More about Developing concept system for robotics open heart surgery.

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.

An energy-aware and Q-learning-based area coverage for oil pipeline monitoring systems using sensors and Internet of Things (2022)
Journal Article
Rahmani, A. M., Ali, S., Malik, M. H., Yousefpoor, E., Yousefpoor, M. S., Mousavi, A., …Hosseinzadeh, M. (2022). An energy-aware and Q-learning-based area coverage for oil pipeline monitoring systems using sensors and Internet of Things. Scientific Reports, 12(1), https://doi.org/10.1038/s41598-022-12181-w

Pipelines are the safest tools for transporting oil and gas. However, the environmental effects and sabotage of hostile people cause corrosion and decay of pipelines, which bring financial and environmental damages. Today, new technologies such as th... Read More about An energy-aware and Q-learning-based area coverage for oil pipeline monitoring systems using sensors and Internet of Things.

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.

Chlorella sensors in liquid marbles and droplets (2022)
Journal Article
Phillips, N., Mayne, R., & Adamatzky, A. (2022). Chlorella sensors in liquid marbles and droplets. Sensing and Bio-Sensing Research, 36, Article 100491. https://doi.org/10.1016/j.sbsr.2022.100491

The use of live organisms in electrically-coupled sensing devices has been suggested as an alternative low-cost, low-environmental footprint and robust technology for continuous monitoring and sensing applications. The utility of Chlorella vulgaris a... Read More about Chlorella sensors in liquid marbles and droplets.

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.

Automatic report-based labelling of clinical EEGs for classifier training (2022)
Conference Proceeding
Western, D., Weber, T., Kandasamy, R., May, F., Taylor, S., Zhu, Y., & Canham, L. (2022). Automatic report-based labelling of clinical EEGs for classifier training. In 2021 IEEE Signal Processing in Medicine and Biology Symposium (SPMB). https://doi.org/10.1109/SPMB52430.2021.9672295

Machine learning classifiers for detection of abnormal clinical electroencephalography (EEG) signals have advanced signficantly in recent years, largely supported by the carefully curated Temple University Hospital Abnormal EEG Corpus (TUAB). Further... Read More about Automatic report-based labelling of clinical EEGs for classifier training.

Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue (2022)
Journal Article
Duran, N., Battle, S., & Smith, J. (2022). Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue. Communication Methods and Measures, 16(3), 182-214. https://doi.org/10.1080/19312458.2021.2020229

We present the Conversation Analysis Modeling Schema (CAMS), a novel dialogue labeling schema that combines the Conversation Analysis concept of Adjacency Pairs, with Dialogue Acts. The aim is to capture both the semantic and syntactic structure of d... Read More about Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue.

Marimo actuated rover systems (2022)
Journal Article
Phillips, N., Draper, T. C., Mayne, R., Reynolds, D. M., & Adamatzky, A. (2022). Marimo actuated rover systems. Journal of Biological Engineering, 16(1), Article 3. https://doi.org/10.1186/s13036-021-00279-0

Background: The potential to directly harness photosynthesis to make actuators, biosensors and bioprocessors has been previously demonstrated in the literature. Herein, this capability has been expanded to more advanced systems — Marimo Actuated Rove... Read More about Marimo actuated rover systems.

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.

Automatic for the people: Crowd-driven generative scores using Manhattan and machine vision (2021)
Conference Proceeding
Nash, C. (2021). Automatic for the people: Crowd-driven generative scores using Manhattan and machine vision.

This paper details a workshop and optional public installation based on the development of situational scores that combine music notation, AI, and code to create dynamic interactive art driven by the realtime movements of objects and people in a live... Read More about Automatic for the people: Crowd-driven generative scores using Manhattan and machine vision.

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.

Machine learning activation energies of chemical reactions (2021)
Journal Article
Lewis-Atwell, T., Townsend, P. A., & Grayson, M. N. (2022). Machine learning activation energies of chemical reactions. Wiley Interdisciplinary Reviews: Computational Molecular Science, 12(4), e1593. https://doi.org/10.1002/wcms.1593

Application of machine learning (ML) to the prediction of reaction activation barriers is a new and exciting field for these algorithms. The works covered here are specifically those in which ML is trained to predict the activation energies of homoge... Read More about Machine learning activation energies of chemical reactions.