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Outputs (387)

Decision Making for Self-adaptation based on Partially Observable Satisfaction of Non-Functional Requirements (2024)
Journal Article
Garcia, L., Samin, H., & Bencomo, N. (2024). Decision Making for Self-adaptation based on Partially Observable Satisfaction of Non-Functional Requirements. ACM Transactions on Autonomous and Adaptive Systems, 19(2), 1-44. https://doi.org/10.1145/3643889

Approaches that support the decision-making of self-adaptive and autonomous systems (SAS) often consider an idealized situation where (i) the system’s state is treated as fully observable by the monitoring infrastructure, and (ii) adaptation actions... Read More about Decision Making for Self-adaptation based on Partially Observable Satisfaction of Non-Functional Requirements.

Innovative haptic-based system for upper limb rehabilitation in visually impaired individuals: a multilayer approach (2023)
Journal Article
Albusac, J., Herrera, V., Schez-Sobrino, S., Grande, R., Vallejo, D., & Monekosso, D. (2024). Innovative haptic-based system for upper limb rehabilitation in visually impaired individuals: a multilayer approach. Multimedia Tools and Applications, 83(21), 60537-60563. https://doi.org/10.1007/s11042-023-17892-4

The integration of technology in healthcare has revolutionized physical rehabilitation of patients affected by neurological conditions, such as spinal cord injuries and strokes. However, a significant gap remains in addressing the needs of the visual... Read More about Innovative haptic-based system for upper limb rehabilitation in visually impaired individuals: a multilayer approach.

Using deep learning to analyze the psychological effects of COVID-19 (2023)
Journal Article
Almeqren, M. A., Almegren, M., Alhayan, F., Cristea, A. I., & Pennington, D. R. (2023). Using deep learning to analyze the psychological effects of COVID-19. Frontiers in Psychology, 14, Article 962854. https://doi.org/10.3389/fpsyg.2023.962854

Problem: Sentiment Analysis (SA) automates the classification of the sentiment of people’s attitudes, feelings or reviews employing natural language processing (NLP) and computational approaches. Deep learning has recently demonstrated remarkable suc... Read More about Using deep learning to analyze the psychological effects of COVID-19.

The engage taxonomy: SDT-based measurable engagement indicators for MOOCs and their evaluation (2023)
Journal Article
Cristea, A. I., Alamri, A., Alshehri, M., Dwan Pereira, F., Toda, A. M., Harada T. de Oliveira, E., & Stewart, C. (2024). The engage taxonomy: SDT-based measurable engagement indicators for MOOCs and their evaluation. User Modeling and User-Adapted Interaction, 34(2), 323-374. https://doi.org/10.1007/s11257-023-09374-x

Massive Online Open Course (MOOC) platforms are considered a distinctive way to deliver a modern educational experience, open to a worldwide public. However, student engagement in MOOCs is a less explored area, although it is known that MOOCs suffer... Read More about The engage taxonomy: SDT-based measurable engagement indicators for MOOCs and their evaluation.

An Interactional Account of Empathy in Human-Machine Communication (2023)
Journal Article
Concannon, S., Roberts, I., & Tomalin, M. (2023). An Interactional Account of Empathy in Human-Machine Communication. Human-machine communication journal, 6, 87-116. https://doi.org/10.30658/hmc.6.6

Efforts to develop empathetic agents, or systems capable of responding appropriately to emotional content, have increased as the deployment of such systems in socially complex scenarios becomes more commonplace. In the context of human-machine commun... Read More about An Interactional Account of Empathy in Human-Machine Communication.

Deep learning for Crack Detection on Masonry Façades using Limited Data and Transfer Learning (2023)
Journal Article
Katsigiannis, S., Seyedzadeh, S., Agapiou, A., & Ramzan, N. (2023). Deep learning for Crack Detection on Masonry Façades using Limited Data and Transfer Learning. Journal of Building Engineering, 76, Article 107105. https://doi.org/10.1016/j.jobe.2023.107105

Crack detection in masonry façades is a crucial task for ensuring the safety and longevity of buildings. However, traditional methods are often time-consuming, expensive, and labour-intensive. In recent years, deep learning techniques have been appli... Read More about Deep learning for Crack Detection on Masonry Façades using Limited Data and Transfer Learning.

Toward Automatic Tutoring of Math Word Problems in Intelligent Tutoring Systems (2023)
Journal Article
Arnau-González, P., Serrano-Mamolar, A., Katsigiannis, S., Althobaiti, T., & Arevalillo-Herráez, M. (2023). Toward Automatic Tutoring of Math Word Problems in Intelligent Tutoring Systems. IEEE Access, 11, 67030-67039. https://doi.org/10.1109/access.2023.3290478

Math Word Problem (MWP) solving, which involves solving math problems in natural language, is a prevalent approach employed by Intelligent Tutoring Systems (ITS) for teaching mathematics. However, one major drawback of ITS is the complexity of encodi... Read More about Toward Automatic Tutoring of Math Word Problems in Intelligent Tutoring Systems.

Language as a latent sequence: Deep latent variable models for semi-supervised paraphrase generation (2023)
Journal Article
Yu, J., Cristea, A. I., Harit, A., Sun, Z., Aduragba, O. T., Shi, L., & Al Moubayed, N. (2023). Language as a latent sequence: Deep latent variable models for semi-supervised paraphrase generation. AI open, 4, 19-32. https://doi.org/10.1016/j.aiopen.2023.05.001

This paper explores deep latent variable models for semi-supervised paraphrase generation, where the missing target pair for unlabelled data is modelled as a latent paraphrase sequence. We present a novel unsupervised model named variational sequence... Read More about Language as a latent sequence: Deep latent variable models for semi-supervised paraphrase generation.

Exploring Time-Coded Comments on YouTube Music Videos of ‘Top 40’ Pop 2000–20 (2023)
Book Chapter
Bell, E. (2023). Exploring Time-Coded Comments on YouTube Music Videos of ‘Top 40’ Pop 2000–20. In H. Rogers, J. Freitas, & J. F. Porfírio (Eds.), YouTube and Music: Online Culture and Everyday Life (255-276). Bloomsbury. https://doi.org/10.5040/9781501387302.0024

As part of a larger project to understand the way that structural features of the design and implementation of radio technology influences its audiences – calling this the medium’s ‘physiognomy’ – Theodor Adorno opened the mailbags of the radio stati... Read More about Exploring Time-Coded Comments on YouTube Music Videos of ‘Top 40’ Pop 2000–20.

Confronting ethical and social issues related to the genetics of musicality (2023)
Journal Article
Gordon, R. L., Martschenko, D. O., Nayak, S., Niarchou, M., Morrison, M. D., Bell, E., …Davis, L. K. (2023). Confronting ethical and social issues related to the genetics of musicality. Annals of the New York Academy of Sciences, 1522(1), https://doi.org/10.1111/nyas.14972

New interdisciplinary research into genetic influences on musicality raises a number of ethical and social issues for future avenues of research and public engagement. The historical intersection of music cognition and eugenics heightens the need to... Read More about Confronting ethical and social issues related to the genetics of musicality.

Toward Supporting CS1 Instructors and Learners With Fine-Grained Topic Detection in Online Judges (2023)
Journal Article
Pereira, F. D., Fonseca, S. C., Wiktor, S., Oliveira, D. B., Cristea, A. I., Benedict, A., …Oliveira, E. H. (2023). Toward Supporting CS1 Instructors and Learners With Fine-Grained Topic Detection in Online Judges. IEEE Access, 11, https://doi.org/10.1109/access.2023.3247189

Online judges (OJ) are a popular tool to support programming learning. However, one major issue with OJs is that problems are often put together without any associated meta-information that could, for example, be used to help classify problems. This... Read More about Toward Supporting CS1 Instructors and Learners With Fine-Grained Topic Detection in Online Judges.

How Personalization Affects Motivation in Gamified Review Assessments (2023)
Journal Article
Rodrigues, L., Palomino, P. T., Toda, A. M., Klock, A. C., Pessoa, M., Pereira, F. D., …Isotani, S. (2023). How Personalization Affects Motivation in Gamified Review Assessments. International Journal of Artificial Intelligence in Education, https://doi.org/10.1007/s40593-022-00326-x

Personalized gamification aims to address shortcomings of the one-size-fits-all (OSFA) approach in improving students’ motivations throughout the learning process. However, studies still focus on personalizing to a single user dimension, ignoring mul... Read More about How Personalization Affects Motivation in Gamified Review Assessments.

COVID-19 and Science Advice on the ‘Grand Stage’: The Metadata and Linguistic Choices in a Scientific Advisory Groups’ Meeting Minutes. (2022)
Journal Article
Baker, H., Concannon, S., Meller, M., Cohen, K., Millington, A., Ward, S., & So, E. (2022). COVID-19 and Science Advice on the ‘Grand Stage’: The Metadata and Linguistic Choices in a Scientific Advisory Groups’ Meeting Minutes. Humanities and Social Sciences Communications, 9, Article 465. https://doi.org/10.1057/s41599-022-01403-1

Automated Detection of Substance-Use Status and Related Information from Clinical Text (2022)
Journal Article
Alzubi, R., Alzoubi, H., Katsigiannis, S., West, D., & Ramzan, N. (2022). Automated Detection of Substance-Use Status and Related Information from Clinical Text. Sensors, 22(24), Article 9609. https://doi.org/10.3390/s22249609

This study aims to develop and evaluate an automated system for extracting information related to patient substance use (smoking, alcohol, and drugs) from unstructured clinical text (medical discharge records). The authors propose a four-stage system... Read More about Automated Detection of Substance-Use Status and Related Information from Clinical Text.

Insights from impacts of the digital divide on children in five majority world countries during the COVID-19 pandemic (2022)
Journal Article
Law, E. L.-C., Vostanis, P., & O’Reilly, M. J. (2023). Insights from impacts of the digital divide on children in five majority world countries during the COVID-19 pandemic. Behaviour and Information Technology, 42(15), 2696-2715. https://doi.org/10.1080/0144929x.2022.2141136

The digital divide is especially pertinent in Majority World Countries (MWCs), and this was exacerbated greatly by the pandemic. Tackling the digital divide underpins the work of Human–Computer Interaction for Development (HCI4D) and remains an impor... Read More about Insights from impacts of the digital divide on children in five majority world countries during the COVID-19 pandemic.

IEViT: An Enhanced Vision Transformer Architecture for Chest X-ray Image Classification (2022)
Journal Article
Okolo, G. I., Katsigiannis, S., & Ramzan, N. (2022). IEViT: An Enhanced Vision Transformer Architecture for Chest X-ray Image Classification. Computer Methods and Programs in Biomedicine, 226, Article 107141. https://doi.org/10.1016/j.cmpb.2022.107141

Background and Objective: Chest X-ray imaging is a relatively cheap and accessible diagnostic tool that can assist in the diagnosis of various conditions, including pneumonia, tuberculosis, COVID-19, and others. However, the requirement for expert ra... Read More about IEViT: An Enhanced Vision Transformer Architecture for Chest X-ray Image Classification.