All Outputs (238)

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.

Haptic User Experience Evaluation for Virtual Reality (2022)
Presentation / Conference Contribution
Aldhous, J., Sobolewska, E., & Webster, G. (2022). Haptic User Experience Evaluation for Virtual Reality. In Proceedings of the 35th British HCI and Doctoral Consortium 2022, UK. https://doi.org/10.14236/ewic/hci2022.59

Hapticians (engineers, researchers or designers) are developing 'haptic displays' to replicate the complexity of sensations and interactivity accommodated by the hand. Haptic displays hold potential in allowing users to interact with each other and m... Read More about Haptic User Experience Evaluation for Virtual Reality.

Data-Driven Innovation for Sustainable Creative Practice (2022)
Presentation / Conference Contribution
Lechelt, S., Panneels, I., & Helgason, I. (2022). Data-Driven Innovation for Sustainable Creative Practice. In Proceedings of the 35th British HCI and Doctoral Consortium 2022, UK. https://doi.org/10.14236/ewic/HCI2022.51

We present a film exhibiting eight case studies of projects dealing with the intersections of environmental sustainability, data and technology, which have all been led by and rooted in the creative industries in Scotland. The film highlights how the... Read More about Data-Driven Innovation for Sustainable Creative Practice.

Digi-Mapping: Creative Placemaking with Psychogeography (2022)
Presentation / Conference Contribution
Grandison, T., Flint, T., & Jamieson, K. (2022). Digi-Mapping: Creative Placemaking with Psychogeography. In Proceedings of the 35th British HCI and Doctoral Consortium 2022, UK. https://doi.org/10.14236/ewic/HCI2022.44

This exhibit consists of four large (2m x 1.5 m) tactile talking maps that were co-created with primary school children in Wester Hailes Edinburgh, UK. In a collaborative partnership with local arts organisation WHALE Arts, the Digi-Mapping project s... Read More about Digi-Mapping: Creative Placemaking with Psychogeography.

Emotional Data Visualised - EDV (2022)
Presentation / Conference Contribution
Flint, T., & Shore, L. (2022). Emotional Data Visualised - EDV. In Proceedings of the 35th British HCI and Doctoral Consortium 2022, UK. https://doi.org/10.14236/ewic/HCI2022.45

This installation is an attempt to reflect the emotional state of a population of people. Emotional Data Visualised (EDV) poses the question: In a post-pandemic digital world how can we be expressive in a subtle yet personal way? EDV reflects the obs... Read More about Emotional Data Visualised - EDV.

Blended Experience Narratives (2022)
Presentation / Conference Contribution
Flint, T., O'Keefe, B., Mastermaker, M., Sturdee, M., & Benyon, D. (2022). Blended Experience Narratives. In Proceedings of the 35th British HCI and Doctoral Consortium 2022, UK. https://doi.org/10.14236/ewic/HCI2022.9

Our work employs conceptual integration, otherwise known as blending, as a tool for designing interactions that work across and between the digital/physical divide. Theoretical approaches to blends can be difficult to navigate and a hard subject to g... Read More about Blended Experience Narratives.

A novel security and authentication method for infrared medical image with discrete time chaotic systems (2022)
Journal Article
Boyraz, O. F., Guleryuz, E., Akgul, A., Yildiz, M. Z., Kiran, H. E., & Ahmad, J. (2022). A novel security and authentication method for infrared medical image with discrete time chaotic systems. Optik, 267, Article 169717. https://doi.org/10.1016/j.ijleo.2022.169717

Objective:
Hand vein images have become important biometric signs used for identification systems. Also, dorsal hand vein images have noteworthy advantages in terms of reliability and contactless procedure. Surgically changing the vascular pattern u... Read More about A novel security and authentication method for infrared medical image with discrete time chaotic systems.

Arabic sentiment analysis using dependency-based rules and deep neural networks (2022)
Journal Article
Diwali, A., Dashtipour, K., Saeedi, K., Gogate, M., Cambria, E., & Hussain, A. (2022). Arabic sentiment analysis using dependency-based rules and deep neural networks. Applied Soft Computing, 127, Article 109377. https://doi.org/10.1016/j.asoc.2022.109377

With the growth of social platforms in recent years and the rapid increase in the means of communication through these platforms, a significant amount of textual data is available that contains an abundance of individuals’ opinions. Sentiment analysi... Read More about Arabic sentiment analysis using dependency-based rules and deep neural networks.

Ensemble learning-based IDS for sensors telemetry data in IoT networks (2022)
Journal Article
Naz, N., Khan, M. A., Alsuhibany, S. A., Diyan, M., Tan, Z., Khan, M. A., & Ahmad, J. (2022). Ensemble learning-based IDS for sensors telemetry data in IoT networks. Mathematical Biosciences and Engineering, 19(10), 10550-10580. https://doi.org/10.3934/mbe.2022493

The Internet of Things (IoT) is a paradigm that connects a range of physical smart devices to provide ubiquitous services to individuals and automate their daily tasks. IoT devices collect data from the surrounding environment and communicate with ot... Read More about Ensemble learning-based IDS for sensors telemetry data in IoT networks.

Minimising line segments in linear diagrams is NP-hard (2022)
Journal Article
Chapman, P., Sim, K., & Hao Chen, H. (2022). Minimising line segments in linear diagrams is NP-hard. Journal of Computer Languages, 71, Article 101136. https://doi.org/10.1016/j.cola.2022.101136

Linear diagrams have been shown to be an effective method of representing set-based data. Moreover, a number of guidelines have been proven to improve the efficacy of linear diagrams. One of these guidelines is to minimise the number of line segments... Read More about Minimising line segments in linear diagrams is NP-hard.

A novel multiple kernel fuzzy topic modeling technique for biomedical data (2022)
Journal Article
Rashid, J., Kim, J., Hussain, A., Naseem, U., & Juneja, S. (2022). A novel multiple kernel fuzzy topic modeling technique for biomedical data. BMC Bioinformatics, 23(1), Article 275. https://doi.org/10.1186/s12859-022-04780-1

Background: Text mining in the biomedical field has received much attention and regarded as the important research area since a lot of biomedical data is in text format. Topic modeling is one of the popular methods among text mining techniques used t... Read More about A novel multiple kernel fuzzy topic modeling technique for biomedical data.

Evaluation Mechanism for Decentralised Collaborative Pattern Learning in Heterogeneous Vehicular Networks (2022)
Journal Article
Qiao, C., Qiu, J., Tan, Z., Min, G., Zomaya, A. Y., & Tian, Z. (2023). Evaluation Mechanism for Decentralised Collaborative Pattern Learning in Heterogeneous Vehicular Networks. IEEE Transactions on Intelligent Transportation Systems, 24(11), 13123 - 13132. https://doi.org/10.1109/TITS.2022.3186630

Collaborative machine learning, especially Feder-ated Learning (FL), is widely used to build high-quality Machine Learning (ML) models in the Internet of Vehicles (IoV). In this paper, we study the performance evaluation problem in an inherently hete... Read More about Evaluation Mechanism for Decentralised Collaborative Pattern Learning in Heterogeneous Vehicular Networks.

Novel single and multi-layer echo-state recurrent autoencoders for representation learning (2022)
Journal Article
Chouikhi, N., Ammar, B., Hussain, A., & Alimi, A. M. (2022). Novel single and multi-layer echo-state recurrent autoencoders for representation learning. Engineering Applications of Artificial Intelligence, 114, Article 105051. https://doi.org/10.1016/j.engappai.2022.105051

Representation learning impacts the performance of Machine Learning (ML) models. Feature extraction-based methods such as Auto-Encoders (AEs) are used to find new, more accurate data representations from original ones. They perform efficiently on a s... Read More about Novel single and multi-layer echo-state recurrent autoencoders for representation learning.

Educational data mining to predict students' academic performance: A survey study (2022)
Journal Article
Batool, S., Rashid, J., Nisar, M. W., Kim, J., Kwon, H., & Hussain, A. (2023). Educational data mining to predict students' academic performance: A survey study. Education and Information Technologies, 28(1), 905-971. https://doi.org/10.1007/s10639-022-11152-y

Educational data mining is an emerging interdisciplinary research area involving both education and informatics. It has become an imperative research area due to many advantages that educational institutions can achieve. Along these lines, various da... Read More about Educational data mining to predict students' academic performance: A survey study.