Applying artificial intelligence in healthcare: lessons from the COVID-19 pandemic (2023)
Journal Article
Balasubramanian, S., Shukla, V., Islam, N., Upadhyay, A., & Duong, L. (in press). Applying artificial intelligence in healthcare: lessons from the COVID-19 pandemic. International Journal of Production Research, https://doi.org/10.1080/00207543.2023.2263102

The COVID-19 pandemic exposed vulnerabilities in global healthcare systems and highlighted the need for innovative, technology-driven solutions like Artificial Intelligence (AI). However, previous research on the topic has been limited and fragmented... Read More about Applying artificial intelligence in healthcare: lessons from the COVID-19 pandemic.

SACRO: Semi-Automated Checking Of Research Outputs (2023)
Presentation / Conference
Smith, J., Preen, R., Albashir, M., Ritchie, F., Green, E., Davy, S., …Bacon, S. (2023, September). SACRO: Semi-Automated Checking Of Research Outputs. Paper presented at UNECE Expert meeting on Statistical Data Confidentiality, Wiesbaden, Germany

Output checking can require significant resources, acting as a barrier to scaling up the research use of confidential data. We report on a project, SACRO, that is developing a general-purpose, semi-automatic output checking systems that works across... Read More about SACRO: Semi-Automated Checking Of Research Outputs.

A method to enable automatic extraction of cost and quantity data from hierarchical construction information documents to enable rapid digital comparison and analysis (2023)
Journal Article
Adanza Dopazo, D., Mahdjoubi, L., & Gething, B. (2023). A method to enable automatic extraction of cost and quantity data from hierarchical construction information documents to enable rapid digital comparison and analysis. Buildings, 13(9), Article 2286. https://doi.org/10.3390/buildings13092286

Context: Despite the effort put into developing standards for structuring construction costs and the strong interest in the field, most construction companies still perform the process of data gathering and processing manually. This provokes inconsis... Read More about A method to enable automatic extraction of cost and quantity data from hierarchical construction information documents to enable rapid digital comparison and analysis.

Child safeguarding and immersive technologies - An outline of the risks (2023)
Report
McIntosh, V. (2023). Child safeguarding and immersive technologies - An outline of the risks. London: NSPCC

Given the rapid growth of new technologies, including immersive environments, the current generation of extended reality products – Virtual Reality (VR) and Augmented Reality (AR) – and the clear shift towards the development of the metaverse, resear... Read More about Child safeguarding and immersive technologies - An outline of the risks.

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.

Deep learning-based multi-target regression for traffic-related air pollution forecasting (2023)
Journal Article
Akinosho, T. D., Bilal, M., Hayes, E. T., Ajayi, A., Ahmed, A., & Khan, Z. (2023). Deep learning-based multi-target regression for traffic-related air pollution forecasting. Machine Learning with Applications, 12, Article 100474. https://doi.org/10.1016/j.mlwa.2023.100474

Traffic-related air pollution (TRAP) remains one of the main contributors to urban pollution and its impact on climate change cannot be overemphasised. Experts in developed countries strive to make optimal use of traffic and air qua... Read More about Deep learning-based multi-target regression for traffic-related air pollution forecasting.

Near neighbours: Artificial intelligence and anti-racism as an activating pursuit in archival moving image practice (2023)
Presentation / Conference
Egbe, A. (2023, June). Near neighbours: Artificial intelligence and anti-racism as an activating pursuit in archival moving image practice. Paper presented at Eye International Conference 2023 Activating the Archive Audiovisual Collections and Civic Engagement, Global Collaboration and Societal Change, Eye Filmmuseum, Amsterdam

Artificial intelligence (AI) is increasingly being utilized in various fields including the film industry and archives. The use of AI as a film analysis tool has the potential to develop the way we understand and critique cinema. AI systems can be tr... Read More about Near neighbours: Artificial intelligence and anti-racism as an activating pursuit in archival moving image practice.

Artificial life as controlled disequilibrium (2023)
Conference Proceeding
Battle, S. (2023). Artificial life as controlled disequilibrium. In B. Muller (Ed.),

Artificial Life can be modeled using simulated au-topoiesis. Liquid Automata are used to define simulated chemical reaction systems; particle systems with rules governing how particles are transformed on collision with each other. Unlike cellular aut... Read More about Artificial life as controlled disequilibrium.

Blurred lines (2023)
Journal Article
Goodman, B. (2023). Blurred lines. Multiples, 58, 10-11

In the age of rapid advancements in Generative Artificial Intelligence and machine learning, the creative landscape is witnessing a profound transformation. In this context, this article by Ben Goodman (under the pseudonym 'I Am Not A Robot') explore... Read More about Blurred lines.

Values, emotions and beliefs within generative AI arts practice patterns in practice: Values, beliefs and emotions within arts practitioners' engagements with machine learning and data mining (2023)
Presentation / Conference
Fratczak, M., Ochu, E., Medina-Perea, I., Bates, J., & Kennedy, H. (2023, April). Values, emotions and beliefs within generative AI arts practice patterns in practice: Values, beliefs and emotions within arts practitioners' engagements with machine learning and data mining. Paper presented at CHI Generative AI Workshop, Online

Patterns in Practice (PIP) is a qualitative study investigating how practitioners' beliefs, values and emotions shape their interaction and engagement with the use of machine learning (ML) and data mining across three contrasting domains-science, edu... Read More about Values, emotions and beliefs within generative AI arts practice patterns in practice: Values, beliefs and emotions within arts practitioners' engagements with machine learning and data mining.

Co-creating anti-racist datasets in AI workflows utilising films as data (2023)
Presentation / Conference
Egbe, A. (2023, April). Co-creating anti-racist datasets in AI workflows utilising films as data. Presented at AI and Archives: Explorations, Possibilities and Challenges, University of Sussex

Considering the concern for racial bias within AI algorithms, could creative responses within moving image archival practice and critical film theory foreground possibilities for intersectional approaches. This paper stems from artist practices with... Read More about Co-creating anti-racist datasets in AI workflows utilising films as data.

Disclosure control of machine learning models from trusted research environments (TRE): New challenges and opportunities (2023)
Journal Article
Mansouri-Benssassi, E., Rogers, S., Reel, S., Malone, M., Smith, J., Ritchie, F., & Jefferson, E. (2023). Disclosure control of machine learning models from trusted research environments (TRE): New challenges and opportunities. Heliyon, 9(4), Article e15143. https://doi.org/10.1016/j.heliyon.2023.e15143

Introduction: Artificial intelligence (AI) applications in healthcare and medicine have increased in recent years. To enable access to personal data, Trusted Research Environments (TREs) (otherwise known as Safe Havens) provide safe and secure enviro... Read More about Disclosure control of machine learning models from trusted research environments (TRE): New challenges and opportunities.

Error-type -A novel set of software metrics for software fault prediction (2023)
Journal Article
Phung, K., Ogunshile, E., & Aydin, M. (2023). Error-type -A novel set of software metrics for software fault prediction. IEEE Access, 11, 30562-30574. https://doi.org/10.1109/ACCESS.2023.3262411

In software development, identifying software faults is an important task. The presence of faults not only reduces the quality of the software, but also increases the cost of development life cycle. Fault identification can be performed by analysing... Read More about Error-type -A novel set of software metrics for software fault prediction.

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.

Chatbot in E-learning (2023)
Conference Proceeding
Hussain, S., Al-Hashmi, S. H., Malik, M. H., & Ali Kazmi, S. I. (2023). Chatbot in E-learning. In SHS Web of Conferences: International Conference on Teaching and Learning – Digital Transformation of Education and Employability (ICTL 2022). https://doi.org/10.1051/shsconf/202315601002

In many modern apps, especially those that provide the user intelligence help, the usage of chatbots is quite common. In reality, these systems frequently have chatbots that can read user inquiries and give the appropriate replies quickly and accurat... Read More about Chatbot in E-learning.

Dis-automation: Creative making with automation and AI (2022)
Journal Article
Crogan, P. (2022). Dis-automation: Creative making with automation and AI. Media Theory, 6(2), 25-54

This essay considers the nature and stakes of creative making with computational automation technologies. I will argue that Bernard Stiegler’s organological approach to the human as “technical life” takes care of the question of the nature of creativ... Read More about Dis-automation: Creative making with automation and AI.

AI and Society: Behind AI Systems (2022)
Presentation / Conference
Ochu, E., & Aneja, U. (2022, October). AI and Society: Behind AI Systems. Presented at Behind AI Systems, Online

Artificial Intelligence, algorithmic systems and machine decision making are being embedded in many areas of society – policing, justice, finance, banking, shopping and navigation just to name a few. These systems are affecting people’s lives in ways... Read More about AI and Society: Behind AI 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.

A spiking neural network model of rodent head direction calibrated with landmark free learning (2022)
Journal Article
Stentiford, R., Knowles, T. C., & Pearson, M. J. (2022). A spiking neural network model of rodent head direction calibrated with landmark free learning. Frontiers in Neurorobotics, 16, -. https://doi.org/10.3389/fnbot.2022.867019

Maintaining a stable estimate of head direction requires both self-motion (idiothetic) information and environmental (allothetic) anchoring. In unfamiliar or dark environments idiothetic drive can maintain a rough estimate of heading but is subject t... Read More about A spiking neural network model of rodent head direction calibrated with landmark free learning.

Deep learning-based networks for automated recognition and classification of awkward working postures in construction using wearable insole sensor data (2022)
Journal Article
Antwi-Afari, M. F., Qarout, Y., Herzallah, R., Anwer, S., Umer, W., Zhang, Y., & Manu, P. (2022). Deep learning-based networks for automated recognition and classification of awkward working postures in construction using wearable insole sensor data. Automation in Construction, 136, Article 104181. https://doi.org/10.1016/j.autcon.2022.104181

Among the numerous work-related risk factors, construction workers are often exposed to awkward working postures that may lead them to develop work-related musculoskeletal disorders (WMSDs). To mitigate WMSDs among construction workers, awkward worki... Read More about Deep learning-based networks for automated recognition and classification of awkward working postures in construction using wearable insole sensor data.