All Outputs (135)

A collaboratively-derived research agenda for e-assessment in undergraduate mathematics (2022)
Journal Article
Kinnear, G., Jones, I., Sangwin, C., Alarfaj, M., Davies, B., Fearn, S., …Wong, T. (in press). A collaboratively-derived research agenda for e-assessment in undergraduate mathematics. International Journal of Research in Undergraduate Mathematics Education, https://doi.org/10.1007/s40753-022-00189-6

This paper describes the collaborative development of an agenda for research on e-assessment in undergraduate mathematics. We built on an established approach to develop the agenda from the contributions of 22 mathematics education researchers, unive... Read More about A collaboratively-derived research agenda for e-assessment in undergraduate mathematics.

Testing lifecourse theories characterising associations between maternal depression and offspring depression in emerging adulthood: The Avon Longitudinal Study of Parents and Children (2022)
Journal Article
Lacey, R. E., Gondek, D., Smith, B. J., Smith, A. D., Dunn, E. C., & Sacker, A. (2023). Testing lifecourse theories characterising associations between maternal depression and offspring depression in emerging adulthood: The Avon Longitudinal Study of Parents and Children. Journal of Child Psychology and Psychiatry, 64(8), 1149-1158. https://doi.org/10.1111/jcpp.13699

Background: Maternal depression is a major determinant of offspring mental health. Yet, little is understood about how the duration and timing of maternal depression shapes youth risk for depressive symptoms, which if understood could inform when bes... Read More about Testing lifecourse theories characterising associations between maternal depression and offspring depression in emerging adulthood: The Avon Longitudinal Study of Parents and Children.

Analysing the predictivity of features to characterise the search space (2022)
Conference Proceeding
Durgut, R., Aydin, M. E., Ihshaish, H., & Rakib, A. (2022). Analysing the predictivity of features to characterise the search space. In E. Pimenidis, P. Angelov, C. Jayne, A. Papaleonidas, & M. Aydin (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2022 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings; Part IV (1-13). https://doi.org/10.1007/978-3-031-15937-4_1

Exploring search spaces is one of the most unpredictable challenges that has attracted the interest of researchers for decades. One way to handle unpredictability is to characterise the search spaces and take actions accordingly. A well-characterised... Read More about Analysing the predictivity of features to characterise the search space.

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.

Rank and wormhole attack detection model for RPL-based Internet of Things using machine learning (2022)
Journal Article
Zahra, F., Jhanjhi, N. Z., Brohi, S. N., Khan, N., Masud, M., & AlZain, M. A. (2022). Rank and wormhole attack detection model for RPL-based Internet of Things using machine learning. Sensors, 22(18), 1 - 17. https://doi.org/10.3390/s22186765

The proliferation of the internet of things (IoT) technology has led to numerous challenges in various life domains, such as healthcare, smart systems, and mission-critical applications. The most critical issue is the security of IoT nodes, networks,... Read More about Rank and wormhole attack detection model for RPL-based Internet of Things using machine learning.

Rethinking living matter: Animate behaviours of fungal composites (2022)
Presentation / Conference
Nikolaidou, A., & Adamatzky, A. (2022, September). Rethinking living matter: Animate behaviours of fungal composites. Paper presented at SEEDS International Conference 2022, University of West of England, Bristol

Smart materials integrating conventional soft electronics e.g. sensors and actuators, are widely used in the building and wearable industries, contributing to the depletion of natural resources and having a vast environmental impact. In this paper, a... Read More about Rethinking living matter: Animate behaviours of fungal composites.

Correct for the wrong reason: Why we should know more about mathematical common student errors in e-assessment questions (2022)
Presentation / Conference
Sikurajapathi, I., Henderson, K., & Gwynllyw, R. (2022, September). Correct for the wrong reason: Why we should know more about mathematical common student errors in e-assessment questions. Presented at Continuing Excellence in Teaching and Learning in Mathematics, Statistics and Operational Research conference (CETL-MSOR-2022), Abertay University, Dundee , Scotland

Students may arrive at an incorrect answer when answering a mathematical question due to several reasons, such as random errors, calculation errors or misreading the question. Such errors are sometimes referred to as Common Student Errors (CSEs). Se... Read More about Correct for the wrong reason: Why we should know more about mathematical common student errors in e-assessment questions.

Integrating wind variability to modelling wind-ramp events using a non-binary ramp function and deep learning models (2022)
Presentation / Conference
Sharp, R., Ihshaish, H., & Deza, J. I. (2022, August). Integrating wind variability to modelling wind-ramp events using a non-binary ramp function and deep learning models. Paper presented at International Conference for Sustainable Ecological Engineering Design for Society, SEEDS 22, UWE Bristol and online

The forecasting of large ramps in wind power output known as ramp events is crucial for the incorporation of large volumes of wind energy into national electricity grids. Large variations in wind power supply must be compensated by ancillary energy s... Read More about Integrating wind variability to modelling wind-ramp events using a non-binary ramp function and deep learning models.

Gathering and compiling mathematical common student errors in e-assessment questions with taxonomical classification (2022)
Journal Article
Sikurajapathi, I., Henderson, K., & Gwynllyw, R. (2022). Gathering and compiling mathematical common student errors in e-assessment questions with taxonomical classification. MSOR Connections, 20(3), 55-71. https://doi.org/10.21100/msor.v20i3.1345

This article gives an overview of the interactive book called ‘Collection of Taxonomically Classified Mathematical Common Student Errors in e-Assessments (CSE Book)’ which has been produced as a result of the Common Student Errors Project (CSE Projec... Read More about Gathering and compiling mathematical common student errors in e-assessment questions with taxonomical classification.

Reflecting on the benefits and challenges of online learning during the COVID-19 Pandemic (2022)
Presentation / Conference
West, H., Hill, J., Abzhaparova, A., Cox, W., & Alexander, A. (2022, August). Reflecting on the benefits and challenges of online learning during the COVID-19 Pandemic. Presented at Royal Geographical Society Annual International Conference, Newcastle

The COVID-19 pandemic resulted in profound disruption to geography higher education. A pivot to online teaching required staff to rapidly adapt their practices to novel learning environments and digital spaces. Whilst many studies have reported the d... Read More about Reflecting on the benefits and challenges of online learning during the COVID-19 Pandemic.

Molecular collective response and dynamical symmetry properties in biopotentials of superior plants: Experimental observations and quantum field theory modeling (2022)
Journal Article
Chiolerio, A., Dehshibi, M. M., Vitiello, G., & Adamatzky, A. (2022). Molecular collective response and dynamical symmetry properties in biopotentials of superior plants: Experimental observations and quantum field theory modeling. Symmetry, 14(9), e1792. https://doi.org/10.3390/sym14091792

Trees employ impulses of electrical activity to coordinate actions of their bodies and long-distance communication. There are indications that the vascular system might act as a network of pathways for traveling electrical impulses. A question arises... Read More about Molecular collective response and dynamical symmetry properties in biopotentials of superior plants: Experimental observations and quantum field theory modeling.

Neuromorphic liquids, colloids and gels: A review (2022)
Journal Article
Raeisi Kheirabadi, N. R., Chiolerio, A., Szacilowski, K., & Adamatzky, A. (in press). Neuromorphic liquids, colloids and gels: A review. ChemPhysChem, https://doi.org/10.1002/cphc.202200390

Advances in flexible electronic devices and robotic software require that sensors and controllers be virtually devoid of traditional electronic components, be deformable and stretch-resistant. Liquid electronic devices that mimic biological synapses... Read More about Neuromorphic liquids, colloids and gels: A review.

The impact of data sonification in virtual reality robot teleoperation (2022)
Journal Article
Bremner, P., Mitchell, T. J., & McIntosh, V. (2022). The impact of data sonification in virtual reality robot teleoperation. Frontiers in Virtual Reality, 3, 904720. https://doi.org/10.3389/frvir.2022.904720

Virtual Reality (VR) is being increasingly used to provide a more intuitive and embodied approach to robotic teleoperation, giving operators a sense of presence in the remote environment. Prior research has shown that presence can be enhanced when ad... Read More about The impact of data sonification in virtual reality robot teleoperation.

Deep learning for estimating sleeping sensor’s values in sustainable IoT applications (2022)
Conference Proceeding
Djenouri, D., Laidi, R., & Djenouri, Y. (2022). Deep learning for estimating sleeping sensor’s values in sustainable IoT applications. In 2022 International Balkan Conference on Communications and Networking (BalkanCom) (147-151). https://doi.org/10.1109/BalkanCom55633.2022.9900817

The aim of this work is to develop a deep learning model that uses spatial correlation to enable turning turn off a subset of sensors while predicting their readings. This considerably saves the energy that would be consumed by those sensors both for... Read More about Deep learning for estimating sleeping sensor’s values in sustainable IoT applications.

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.

Acceptability of Lycra arm sleeve in people with sub-acute stroke: Patients', carers' and clinicians' perspectives (2022)
Journal Article
Kumar, P., Jones, R., Cramp, M., Greenwood, R., White, P., & Turton, A. (2023). Acceptability of Lycra arm sleeve in people with sub-acute stroke: Patients', carers' and clinicians' perspectives. Physiotherapy, 118, 31-38. https://doi.org/10.1016/j.physio.2022.08.002

Background: Previous studies found that the Lycra sleeve has potential to reduce glenohumeral subluxation in people with stroke. The primary aim of this study was to explore the acceptability of the Lycra sleeve from patients’, carers’ and staff perc... Read More about Acceptability of Lycra arm sleeve in people with sub-acute stroke: Patients', carers' and clinicians' perspectives.

OGMA: Visualisation for software container security analysis and automated remediation (2022)
Conference Proceeding
Mills, A., White, J., & Legg, P. (2022). OGMA: Visualisation for software container security analysis and automated remediation. In 2022 IEEE International Conference on Cyber Security and Resilience (CSR) (76-81). https://doi.org/10.1109/CSR54599.2022.9850335

The use of software containerisation has rapidly increased in academia and industry which has lead to the production of several container security scanning tools for assessing the security posture and threat of a container image. The variability betw... Read More about OGMA: Visualisation for software container security analysis and automated remediation.

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.

A strategy-based algorithm for moving targets in an environment with multiple agents (2022)
Journal Article
Afzalov, A., Lotfi, A., Inden, B., & Aydin, M. E. (2022). A strategy-based algorithm for moving targets in an environment with multiple agents. SN Computer Science, 3(6), 435. https://doi.org/10.1007/s42979-022-01302-x

Most studies in the field of search algorithms have only focused on pursuing agents, while comparatively less attention has been paid to target algorithms that employ strategies to evade multiple pursuing agents. In this study, a state-of-the-art tar... Read More about A strategy-based algorithm for moving targets in an environment with multiple agents.