All Outputs (4095)

Decentralised Privacy: A Distributed Ledger Approach (2021)
Book Chapter
Papadopoulos, P., Pitropakis, N., & Buchanan, W. J. (2021). Decentralised Privacy: A Distributed Ledger Approach. In C. Mustansar Hussain, & P. Di Sia (Eds.), Handbook of Smart Materials, Technologies, and Devices (1-26). Springer. https://doi.org/10.1007/978-3-030-58675-1_58-1

Our world due to the technological progress became fast-paced and is constantly evolving, thus changing every single day. Consequently, the most valuable asset on earth is not gold or oil anymore but data. Big data companies try to take advantage of... Read More about Decentralised Privacy: A Distributed Ledger Approach.

An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction (2021)
Presentation / Conference Contribution
Kanwal, S., Rashid, J., Kim, J., Nisar, M. W., Hussain, A., Batool, S., & Kanwal, R. (2021, November). An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction. Presented at 2021 International Conference on Innovative Computing (ICIC), Lahore, Pakistan

One of the most challenging problems in the telecommunications industry is predicting customer churn (CCP). Decision-makers and business experts stressed that acquiring new clients is more expensive than maintaining current ones. From current churn d... Read More about An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction.

Guest Editorial: Special Issue on "Advance in Mobile Edge Computing" (2021)
Journal Article
Yang, X., Tan, Z., & Xu, Y. (2021). Guest Editorial: Special Issue on "Advance in Mobile Edge Computing". Journal of Internet Technology, 22(5),

Cloud computing has a problem for communication-intensive applications, which need to meet the delay requirements. The problem becomes more intense with the huge application of the Internet of Things. Mobile Edge Computing processes data at the neare... Read More about Guest Editorial: Special Issue on "Advance in Mobile Edge Computing".

Underreporting of errors in NLG output, and what to do about it (2021)
Presentation / Conference Contribution
van Miltenburg, E., Clinciu, M.-A., Dušek, O., Gkatzia, D., Inglis, S., Leppänen, L., Mahamood, S., Manning, E., Schoch, S., Thomson, C., & Wen, L. (2021, September). Underreporting of errors in NLG output, and what to do about it. Presented at 14th International Conference on Natural Language Generation, Aberdeen, UK

We observe a severe under-reporting of the different kinds of errors that Natural Language Generation systems make. This is a problem, because mistakes are an important indicator of where systems should still be improved. If authors only report overa... Read More about Underreporting of errors in NLG output, and what to do about it.

VNWTS: A Virtual Water Chlorination Process for Cybersecurity Analysis of Industrial Control Systems (2021)
Presentation / Conference Contribution
Robles Durazno, A., Moradpoor, N., McWhinnie, J., & Porcel-Bustamante, J. (2021, December). VNWTS: A Virtual Water Chlorination Process for Cybersecurity Analysis of Industrial Control Systems. Presented at SINCONF 2021: 14th International Conference on Security of Information and Networks, Edinburgh (Online)

The rapid development of technology during the last decades has led to the integration of the network capabilities in the devices that are essential in the operation of Industrial Control Systems (ICS). Consequently, the attack surface of these asset... Read More about VNWTS: A Virtual Water Chlorination Process for Cybersecurity Analysis of Industrial Control Systems.

Degree Apprentices’ Lockdown Survey: Reflections on working and studying from home (2021)
Presentation / Conference Contribution
Taylor-Smith, E., & Fabian, K. (2021, December). Degree Apprentices’ Lockdown Survey: Reflections on working and studying from home. Presented at SRHE International Conference on Research into Higher Education, Online

During the first UK lockdown period, degree apprentices in two universities in Scotland were invited to complete a short qualitative survey with their reflections on starting to work and study from home. They were encouraged to complete the survey o... Read More about Degree Apprentices’ Lockdown Survey: Reflections on working and studying from home.

Lost in translation: Qualitative data collecting and translating challenges in multilingual settings in information systems research (2021)
Journal Article
Demeke, W., & Ryan, B. (2021). Lost in translation: Qualitative data collecting and translating challenges in multilingual settings in information systems research. University of Dar es Salaam Library Journal, 16(2), 105-118

In this paper under-researched methodological issues in information systems research of multilingual interview data collection and translation using translators explored. Observations field notes were collected during the study of the role of ICT for... Read More about Lost in translation: Qualitative data collecting and translating challenges in multilingual settings in information systems research.

Transfer learning-based method for detection of COVID-19 using X-Ray Images (2021)
Presentation / Conference Contribution
Rehman, A., Tariq, Z., Jan, S. U., Aziz, S., Khan, M. U., & Chaudry, H. N. (2021, October). Transfer learning-based method for detection of COVID-19 using X-Ray Images. Presented at 2021 International Conference on Robotics and Automation in Industry (ICRAI), Rawalpindi, Pakistan

In this paper, we have performed transfer learning using different pre-trained convolutional neural networks for binary classification of X-ray images into COVID-19 disease and normal. The dataset is gathered from two open sources. Our dataset is con... Read More about Transfer learning-based method for detection of COVID-19 using X-Ray Images.

An Integrated Approach for Cancer Survival Prediction Using Data Mining Techniques (2021)
Journal Article
Kaur, I., Doja, M. N., Ahmad, T., Ahmad, M., Hussain, A., Nadeem, A., & Abd El-Latif, A. A. (2021). An Integrated Approach for Cancer Survival Prediction Using Data Mining Techniques. Computational Intelligence and Neuroscience, 2021, Article 6342226. https://doi.org/10.1155/2021/6342226

Ovarian cancer is the third most common gynecologic cancers worldwide. Advanced ovarian cancer patients bear a significant mortality rate. Survival estimation is essential for clinicians and patients to understand better and tolerate future outcomes.... Read More about An Integrated Approach for Cancer Survival Prediction Using Data Mining Techniques.

Improving wireless indoor non-intrusive load disaggregation using attention-based deep learning networks (2021)
Journal Article
Liu, Q., Zhang, J., Liu, X., Zhang, Y., Xu, X., Khosravi, M., & Bilal, M. (2022). Improving wireless indoor non-intrusive load disaggregation using attention-based deep learning networks. Physical Communication, 51, Article 101584. https://doi.org/10.1016/j.phycom.2021.101584

The intensification of the greenhouse effect is driving the implementation of energy saving and emission reduction policies, which lead to a wide variety of energy saving solutions benefiting from the advancement of emerging technologies such as Wire... Read More about Improving wireless indoor non-intrusive load disaggregation using attention-based deep learning networks.

A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls (2021)
Journal Article
Varone, G., Boulila, W., Lo Giudice, M., Benjdira, B., Mammone, N., Ieracitano, C., Dashtipour, K., Neri, S., Gasparini, S., Morabito, F. C., Hussain, A., & Aguglia, U. (2022). A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls. Sensors, 22(1), Article 129. https://doi.org/10.3390/s22010129

Until now, clinicians are not able to evaluate the Psychogenic Non-Epileptic Seizures (PNES) from the rest-electroencephalography (EEG) readout. No EEG marker can help differentiate PNES cases from healthy subjects. In this paper, we have investigate... Read More about A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls.

A journey that motivates: Exploring the Associate Students Transition Framework (2021)
Presentation / Conference Contribution
Meharg, D., Varey, A., & Cairncross, S. (2021, October). A journey that motivates: Exploring the Associate Students Transition Framework. Presented at 2021 IEEE Frontiers in Education Conference (FIE), Lincoln, Nebraska, USA

This research to practice full paper presents empirical work exploring the transition experiences of transfer students into computing degrees in Scotland. Students on this journey face transitional barriers as they adapt to the change in culture, com... Read More about A journey that motivates: Exploring the Associate Students Transition Framework.

Event-driven Temporal Models for Explanations - ETeMoX: Explaining Reinforcement Learning (2021)
Journal Article
Parra-Ullauri, J. M., Garcoa-Dominguez, A., Bencomo, N., Zheng, C., Zhen, C., Boubeta-Puig, J., Ortiz, G., & Yang, S. (2022). Event-driven Temporal Models for Explanations - ETeMoX: Explaining Reinforcement Learning. Software and Systems Modeling, 21, 1091-1113. https://doi.org/10.1007/s10270-021-00952-4

Modern software systems are increasingly expected to show higher degrees of autonomy and self-management to cope with uncertain and diverse situations. As a consequence, autonomous systems can exhibit unexpected and surprising behaviours. This is... Read More about Event-driven Temporal Models for Explanations - ETeMoX: Explaining Reinforcement Learning .

An Edge-Assisted Cloud Framework Using a Residual Concatenate FCN Approach to Beam Correction in the Internet of Weather Radars (2021)
Journal Article
Wu, H., Liu, Q., Liu, X., Zhang, Y., & Yang, Z. (2022). An Edge-Assisted Cloud Framework Using a Residual Concatenate FCN Approach to Beam Correction in the Internet of Weather Radars. World Wide Web, 25, 1923-1949. https://doi.org/10.1007/s11280-021-00988-y

Internet of Things (IoT) has been rapidly developed in recent years, being well applied in the fields of Environmental Surveillance, Smart Grid, Intelligent Transportation, and so on. As one of the typical earth-based meteorological observation metho... Read More about An Edge-Assisted Cloud Framework Using a Residual Concatenate FCN Approach to Beam Correction in the Internet of Weather Radars.

Recorded performance as digital content: Perspectives from Fringe 2020 (2021)
Book Chapter
Elsden, C., Yu, D., Piccio, B., Helgason, I., & Terras, M. (2021). Recorded performance as digital content: Perspectives from Fringe 2020. In L. Bissell, & L. Weir (Eds.), Performance in a Pandemic. Routledge. https://doi.org/10.4324/9781003165644

Within days of performance venues being forced to close their doors in 2020, the National Theatre began broadcasting high-quality recordings of the best of London’s West End. Few other companies could dream of having such rich recorded archives to dr... Read More about Recorded performance as digital content: Perspectives from Fringe 2020.

Artificial evolution of robot bodies and control: on the interaction between evolution, individual and cultural learning (2021)
Journal Article
Hart, E., & Le Goff, L. K. (2022). Artificial evolution of robot bodies and control: on the interaction between evolution, individual and cultural learning. Philosophical Transactions B: Biological Sciences, 377(1843), https://doi.org/10.1098/rstb.2021.0117

We survey and reflect on evolutionary approaches to the joint optimisation of the body and control of a robot, in scenarios where a the goal is to find a design that maximises performance on a specified task. The review is grounded in a general frame... Read More about Artificial evolution of robot bodies and control: on the interaction between evolution, individual and cultural learning.

FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning (2021)
Journal Article
Spinelli, I., Scardapane, S., Hussain, A., & Uncini, A. (2022). FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning. IEEE Transactions on Artificial Intelligence, 3(3), 344-354. https://doi.org/10.1109/tai.2021.3133818

Graph representation learning has become a ubiquitous component in many scenarios, ranging from social network analysis to energy forecasting in smart grids. In several applications, ensuring the fairness of the node (or graph) representations with r... Read More about FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning.

Developing Visualisations to Enhance an Insider Threat Product: A Case Study (2021)
Presentation / Conference Contribution
Graham, M., Kukla, R., Mandrychenko, O., Hart, D., & Kennedy, J. (2021, October). Developing Visualisations to Enhance an Insider Threat Product: A Case Study. Presented at 2021 IEEE Symposium on Visualization for Cyber Security (VizSec), New Orleans, USA

This paper describes the process of developing data visualisations to enhance a commercial software platform for combating insider threat, whose existing UI, while perfectly functional, was limited in its ability to allow analysts to easily spot the... Read More about Developing Visualisations to Enhance an Insider Threat Product: A Case Study.

Compounding barriers to fairness in the digital technology ecosystem (2021)
Presentation / Conference Contribution
Woolley, S. I., Collins, T., Andras, P., Gardner, A., Ortolani, M., & Pitt, J. (2021, October). Compounding barriers to fairness in the digital technology ecosystem. Presented at 2021 IEEE International Symposium on Technology and Society (ISTAS), Waterloo, ON, Canada

A growing sense of unfairness permeates our quasi-digital society. Despite drivers supporting and motivating ethical practice in the digital technology ecosystem, there are compounding barriers to fairness that, at every level, impact technology inno... Read More about Compounding barriers to fairness in the digital technology ecosystem.

Wireless Sensor Networks (WSN) in Oil and Gas Industry: Applications, Requirements and Existing Solutions (2021)
Presentation / Conference Contribution
Wadhaj, I., Ghaleb, B., & Thomson, C. (2021, June). Wireless Sensor Networks (WSN) in Oil and Gas Industry: Applications, Requirements and Existing Solutions. Presented at International Conference on Emerging Technologies and Intelligent Systems (ICETIS 2021), Online

Effective measurement and monitoring of certain parameters (temperature, pressure, flow etc.) is crucial for the safety and optimization of processes in the Oil and Gas Industry. Wired sensors have been extensively utilized for this purpose but are c... Read More about Wireless Sensor Networks (WSN) in Oil and Gas Industry: Applications, Requirements and Existing Solutions.