Skip to main content

Research Repository

Advanced Search

All Outputs (4204)

Digital options: an assessment of audience engagement with a digitised archive set transformed from online text and images to audio format (2022)
Presentation / Conference Contribution
Ryan, B., Hall, H., & McGregor, I. (2022, August). Digital options: an assessment of audience engagement with a digitised archive set transformed from online text and images to audio format. Paper presented at Archives and Records Association Annual Conference 2022, Chester, UK

We report the findings of a research project funded by the AHRC, with support of the BBC, British Library, and a community museum. This exploits, augments, and exhibits a set of existing archive data by transforming a young woman’s personal testimony... Read More about Digital options: an assessment of audience engagement with a digitised archive set transformed from online text and images to audio format.

Information literacy impact framework: Final project report (2022)
Report
Cruickshank, P., Ryan, B., & Milosheva, M. (2022). Information literacy impact framework: Final project report

This report presents findings from a review of literature reporting on information literacy (IL) impact. It is intended to deliver considerations towards a framework for impactful IL interventions, including development of parameters to guide impact... Read More about Information literacy impact framework: Final project report.

A Multirobot Cooperative Area Coverage Search Algorithm Based on Bioinspired Neural Network in Unknown Environments (2022)
Journal Article
Chen, B., Zhang, W., Zhang, F., Liu, Y., & Yu, H. (2023). A Multirobot Cooperative Area Coverage Search Algorithm Based on Bioinspired Neural Network in Unknown Environments. IEEE Systems Journal, 17(2), 1995-2006. https://doi.org/10.1109/jsyst.2022.3198712

This article proposes a novel approach based on a bioinspired neural network (BIN) for multirobot area coverage search in unknown environments. We obtain the dynamic environment information in the search process of the multirobot by combining the BIN... Read More about A Multirobot Cooperative Area Coverage Search Algorithm Based on Bioinspired Neural Network in Unknown Environments.

Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique (2022)
Journal Article
Moezzi, S. A. R., Ghaedi, A., Rahmanian, M., Mousavi, S. Z., & Sami, A. (2023). Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique. Journal of Digital Imaging, 36(1), 80-90. https://doi.org/10.1007/s10278-022-00692-x

Since radiology reports needed for clinical practice and research are written and stored in free-text narrations, extraction of relative information for further analysis is difficult. In these circumstances, natural language processing (NLP) techniqu... Read More about Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique.

Semi-supervised Representative Learning for Measuring Epidermal Thickness in Human Subjects in Optical Coherence Tomography by Leveraging Datasets from Rodent Models (2022)
Journal Article
Ji, Y., Yang, S., Zhou, K., Lu, J., Wang, R., Rocliffe, H. R., Pellicoro, A., Cash, J. L., Li, C., & Huang, Z. (2022). Semi-supervised Representative Learning for Measuring Epidermal Thickness in Human Subjects in Optical Coherence Tomography by Leveraging Datasets from Rodent Models. Journal of Biomedical Optics, 27(8), Article 085002. https://doi.org/10.1117/1.JBO.27.8.085002

Aim: Morphological changes in the epidermis layer are critical for the diagnosis and assessment of various skin diseases. Due to its non-invasiveness, optical coherence tomography (OCT) is a good candidate for observing microstructural changes of ski... Read More about Semi-supervised Representative Learning for Measuring Epidermal Thickness in Human Subjects in Optical Coherence Tomography by Leveraging Datasets from Rodent Models.

A Testing Methodology for the Internet of Things Affordable IP Cameras (2022)
Book Chapter
Dzwigala, G., Ghaleb, B., Aldhaheri, T. A., Wadhaj, I., Thomson, C., & Al-Zidi, N. M. (2022). A Testing Methodology for the Internet of Things Affordable IP Cameras. In H. Sharma, V. Shrivastava, K. Kumari Bharti, & L. Wang (Eds.), . Springer. https://doi.org/10.1007/978-981-19-2130-8_37

IP cameras are becoming a cheaper and more convenient option for a lot of households, whether it being for outdoor, indoor security, or as baby or pet monitors. Their security, however, is often lacking, and there is currently no testbed that focuses... Read More about A Testing Methodology for the Internet of Things Affordable IP Cameras.

A Mixed Approach for Aggressive Political Discourse Analysis on Twitter (2022)
Journal Article
Torregrosa, J., D’Antonio-Maceiras, S., Villar-Rodríguez, G., Hussain, A., Cambria, E., & Camacho, D. (2023). A Mixed Approach for Aggressive Political Discourse Analysis on Twitter. Cognitive Computation, 15, 440-465. https://doi.org/10.1007/s12559-022-10048-w

Political tensions have grown throughout Europe since the beginning of the new century. The consecutive crises led to the rise of different social movements in several countries, in which the political status quo changed. These changes included an in... Read More about A Mixed Approach for Aggressive Political Discourse Analysis on Twitter.

A Novel Chaos-Based Privacy-Preserving Deep Learning Model for Cancer Diagnosis (2022)
Journal Article
Rehman, M. U., Shafique, A., Ghadi, Y. Y., Boulila, W., Jan, S. U., Gadekallu, T. R., Driss, M., & Ahmad, J. (2022). A Novel Chaos-Based Privacy-Preserving Deep Learning Model for Cancer Diagnosis. IEEE Transactions on Network Science and Engineering, 9(6), 4322-4337. https://doi.org/10.1109/tnse.2022.3199235

Early cancer identification is regarded as a challenging problem in cancer prevention for the healthcare community. In addition, ensuring privacy-preserving healthcare data becomes more difficult with the growing demand for sharing these data. This s... Read More about A Novel Chaos-Based Privacy-Preserving Deep Learning Model for Cancer Diagnosis.

Predicting Breast Cancer Leveraging Supervised Machine Learning Techniques (2022)
Journal Article
Aamir, S., Rahim, A., Aamir, Z., Abbasi, S. F., Khan, M. S., Alhaisoni, M., Khan, M. A., Khan, K., & Ahmad, J. (2022). Predicting Breast Cancer Leveraging Supervised Machine Learning Techniques. Computational and Mathematical Methods in Medicine, 2022, Article 5869529. https://doi.org/10.1155/2022/5869529

Breast cancer is one of the leading causes of increasing deaths in women worldwide. The complex nature (microcalcification and masses) of breast cancer cells makes it quite difficult for radiologists to diagnose it properly. Subsequently, various com... Read More about Predicting Breast Cancer Leveraging Supervised Machine Learning Techniques.

A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem (2022)
Presentation / Conference Contribution
Marrero, A., Segredo, E., León, C., & Hart, E. (2022, September). A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem. Presented at Parallel Problem Solving from Nature – PPSN XVII, 17th International Conference, Dortmund, Germany

We propose a new approach to generating synthetic instances in the knapsack domain in order to fill an instance-space. The method uses a novelty-search algorithm to search for instances that are diverse with respect to a feature-space but also elicit... Read More about A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem.

Evolutionary Approaches to Improving the Layouts of Instance-Spaces (2022)
Presentation / Conference Contribution
Sim, K., & Hart, E. (2022, September). Evolutionary Approaches to Improving the Layouts of Instance-Spaces. Presented at 17th International Conference, PPSN 2022, Dortmund, Germany

We propose two new methods for evolving the layout of an instance-space. Specifically we design three different fitness metrics that seek to: (i) reward layouts which place instances won by the same solver close in the space; (ii) reward layouts that... Read More about Evolutionary Approaches to Improving the Layouts of Instance-Spaces.

Transforming Points of Single Contact Data into Linked Data (2022)
Journal Article
Fragkou, P., & Maglaras, L. (2022). Transforming Points of Single Contact Data into Linked Data. Computers, 11(8), Article 122. https://doi.org/10.3390/computers11080122

Open data portals contain valuable information for citizens and business. However, searching for information can prove to be tiresome even in portals tackling domains similar information. A typical case is the information residing in the European Com... Read More about Transforming Points of Single Contact Data into Linked Data.

Electromagnetic Side-Channel Attack Resilience against PRESENT Lightweight Block Cipher (2022)
Presentation / Conference Contribution
Gunathilake, N. A., Al-Dubai, A., Buchanan, W. J., & Lo, O. (2022, January). Electromagnetic Side-Channel Attack Resilience against PRESENT Lightweight Block Cipher. Presented at 2022 IEEE 6th International Conference on Cryptography, Security and Privacy (CSP 2022), Tianjin, China

Lightweight cryptography is a novel diversion from conventional cryptography that targets internet-of-things (IoT) platform due to resource constraints. In comparison, it offers smaller cryptographic primitives such as shorter key sizes, block sizes... Read More about Electromagnetic Side-Channel Attack Resilience against PRESENT Lightweight Block Cipher.

Co-optimization method to improve lateral resolution in photoacoustic computed tomography (2022)
Journal Article
Zhang, Y., Yang, S., Xia, Z., Hou, R., Xu, B., Hou, L., Marsh, J. H., Jiangmin Hou, J., Mojtaba Rezaei Sani, S., Liu, X., & Xiong, J. (2022). Co-optimization method to improve lateral resolution in photoacoustic computed tomography. Biomedical Optics Express, 13(9), 4621-4636. https://doi.org/10.1364/BOE.469744

In biomedical imaging, photoacoustic computed tomography (PACT) has recently gained increased interest as this imaging technique has good optical contrast and depth of acoustic penetration. However, a spinning blur will be introduced during the image... Read More about Co-optimization method to improve lateral resolution in photoacoustic computed tomography.

Thermography for Disease Detection in Livestock: A Scoping Review (2022)
Journal Article
McManus, R., Boden, L., Weir, W., Viora, L., Barker, R., Kim, Y., …Yang, S. (2022). Thermography for Disease Detection in Livestock: A Scoping Review. Frontiers in Veterinary Science, 9, Article 965622. https://doi.org/10.3389/fvets.2022.965622

Infra-red thermography (IRT) offers potential opportunities as a tool for disease detection in livestock. Despite considerable research in this area, there are no common standards or protocols for managing IRT parameters in animal disease detection r... Read More about Thermography for Disease Detection in Livestock: A Scoping Review.

Footsteps in the fog: Certificateless fog-based access control (2022)
Journal Article
Frimpong, E., Michalas, A., & Ullah, A. (2022). Footsteps in the fog: Certificateless fog-based access control. Computers and Security, 121, Article 102866. https://doi.org/10.1016/j.cose.2022.102866

The proliferating adoption of the Internet of Things (IoT) paradigm has fuelled the need for more efficient and resilient access control solutions that aim to prevent unauthorized resource access. The majority of existing works in this field follow e... Read More about Footsteps in the fog: Certificateless fog-based access control.

Machine Learning-Based Prediction of Node Localization Accuracy in IIoT-Based MI-UWSNs and Design of a TD Coil for Omnidirectional Communication (2022)
Journal Article
Gang, Q., Muhammad, A., Khan, Z. U., Khan, M. S., Ahmed, F., & Ahmad, J. (2022). Machine Learning-Based Prediction of Node Localization Accuracy in IIoT-Based MI-UWSNs and Design of a TD Coil for Omnidirectional Communication. Sustainability, 14(15), Article 9683. https://doi.org/10.3390/su14159683

This study aims to realize Sustainable Development Goals (SDGs), i.e., SDG 9: Industry Innovation and Infrastructure and SDG 14: Life below Water, through the improvement of localization estimation accuracy in magneto-inductive underwater wireless se... Read More about Machine Learning-Based Prediction of Node Localization Accuracy in IIoT-Based MI-UWSNs and Design of a TD Coil for Omnidirectional Communication.

A Commonsense-Enhanced Document-Grounded Conversational Agent: A Case Study on Task-Based Dialogue (2022)
Book Chapter
Strathearn, C., & Gkatzia, D. (2023). A Commonsense-Enhanced Document-Grounded Conversational Agent: A Case Study on Task-Based Dialogue. In M. Abbas (Ed.), Analysis and Application of Natural Language and Speech Processing (123-144). Springer. https://doi.org/10.1007/978-3-031-11035-1_6

This paper argues that future dialogue systems must retrieve relevant information from multiple structured and unstructured data sources in order to generate natural and informative responses as well as exhibit commonsense capabilities and flexibilit... Read More about A Commonsense-Enhanced Document-Grounded Conversational Agent: A Case Study on Task-Based Dialogue.

DRaNN_PSO: A deep random neural network with particle swarm optimization for intrusion detection in the industrial internet of things (2022)
Journal Article
Ahmad, J., Shah, S. A., Latif, S., Ahmed, F., Zou, Z., & Pitropakis, N. (2022). DRaNN_PSO: A deep random neural network with particle swarm optimization for intrusion detection in the industrial internet of things. Journal of King Saud University (Computer and Information Sciences), 34(10), 8112-8121. https://doi.org/10.1016/j.jksuci.2022.07.023

The Industrial Internet of Things (IIoT) is a rapidly emerging technology that increases the efficiency and productivity of industrial environments by integrating smart sensors and devices with the internet. The advancements in communication technolo... Read More about DRaNN_PSO: A deep random neural network with particle swarm optimization for intrusion detection in the industrial internet of things.

Next Generation Cognition-Aware Hearing Aid Devices With Microwave Sensors: Opportunities and Challenges (2022)
Journal Article
Anwar, U., Arslan, T., Hussain, A., & Lomax, P. (2022). Next Generation Cognition-Aware Hearing Aid Devices With Microwave Sensors: Opportunities and Challenges. IEEE Access, 10, 82214-82235. https://doi.org/10.1109/access.2022.3195875

The strong association between hearing loss and cognitive decline has developed into a major health challenge that calls for early detection, diagnosis and prevention. Hearing loss usually results in severe health implications that include loss of mo... Read More about Next Generation Cognition-Aware Hearing Aid Devices With Microwave Sensors: Opportunities and Challenges.