Skip to main content

Research Repository

Advanced Search

All Outputs (4204)

High Gain/Bandwidth Off-Chip Antenna Loaded with Metamaterial Unit-Cell Impedance Matching Circuit for Sub-Terahertz Near-Field Electronic Systems (2022)
Journal Article
Alibakhshikenari, M., Virdee, B. S., Mariyanayagam, D., Vadalà, V., Naser-Moghadasi, M., See, C. H., Dayoub, I., Aïssa, S., Livreri, P., Burokur, S. N., Pietrenko-Dabrowska, A., Falcone, F., Koziel, S., & Limiti, E. (2022). High Gain/Bandwidth Off-Chip Antenna Loaded with Metamaterial Unit-Cell Impedance Matching Circuit for Sub-Terahertz Near-Field Electronic Systems. Scientific Reports, 12(1), 17893. https://doi.org/10.1038/s41598-022-22828-3

An innovative off-chip antenna (OCA) is presented that exhibits high gain and efficiency performance at the terahertz (THz) band and has a wide operational bandwidth. The proposed OCA is implemented on stacked silicon layers and consists of an open c... Read More about High Gain/Bandwidth Off-Chip Antenna Loaded with Metamaterial Unit-Cell Impedance Matching Circuit for Sub-Terahertz Near-Field Electronic Systems.

Design of a Tri-Band Wearable Antenna for Millimeter-Wave 5G Applications (2022)
Journal Article
Ahmad, S., Boubakar, H., Naseer, S., Alim, M. E., Sheikh, Y. A., Ghaffar, A., …Parchin, N. O. (2022). Design of a Tri-Band Wearable Antenna for Millimeter-Wave 5G Applications. Sensors, 22(20), Article 8012. https://doi.org/10.3390/s22208012

A printed monopole antenna for millimeter-wave applications in the 5G frequency region is described in this research. As a result, the proposed antenna resonates in three frequency bands that are designated for 5G communication systems, including 28... Read More about Design of a Tri-Band Wearable Antenna for Millimeter-Wave 5G Applications.

Multi-Objective Evolutionary Optimisation for Prototype-Based Fuzzy Classifiers (2022)
Journal Article
Gu, X., Li, M., Shen, L., Tang, G., Ni, Q., Peng, T., & Shen, Q. (2023). Multi-Objective Evolutionary Optimisation for Prototype-Based Fuzzy Classifiers. IEEE Transactions on Fuzzy Systems, 31(5), 1703-1715. https://doi.org/10.1109/tfuzz.2022.3214241

Evolving intelligent systems (EISs), particularly, the zero-order ones have demonstrated strong performance on many real-world problems concerning data stream classification, while offering high model transparency and interpretability thanks to their... Read More about Multi-Objective Evolutionary Optimisation for Prototype-Based Fuzzy Classifiers.

A Deployable and Cost-Effective Kirigami Antenna for Sub-6 GHz MIMO Applications (2022)
Journal Article
Kiani, S. H., Marey, M., Rafique, U., Shah, S. I. H., Bashir, M. A., Mostafa, H., Wong, S., & Parchin, N. O. (2022). A Deployable and Cost-Effective Kirigami Antenna for Sub-6 GHz MIMO Applications. Micromachines, 13(10), Article 1735. https://doi.org/10.3390/mi13101735

In this work, a low-cost, deployable, integratable, and easy-to-fabricate multiple-input multiple-output (MIMO) Kirigami antenna is proposed for sub-6 GHz applications. The proposed MIMO antenna is inspired by Kirigami art, which consists of four rad... Read More about A Deployable and Cost-Effective Kirigami Antenna for Sub-6 GHz MIMO Applications.

A Quantitative Field Study of a Persuasive Security Technology in the Wild (2022)
Presentation / Conference Contribution
Vargheese, J. P., Collinson, M., & Masthoff, J. (2022, October). A Quantitative Field Study of a Persuasive Security Technology in the Wild. Presented at SocInfo'22: International Conference on Social Informatics 2022, Glasgow, UK

Persuasive techniques and persuasive technologies have been suggested as a means to improve user cybersecurity behaviour, but there have been few quantitative studies in this area. In this paper, we present a large scale evaluation of persuasive mess... Read More about A Quantitative Field Study of a Persuasive Security Technology in the Wild.

A brain atlas of synapse protein lifetime across the mouse lifespan (2022)
Journal Article
Bulovaite, E., Qiu, Z., Kratschke, M., Zgraj, A., Fricker, D. G., Tuck, E. J., …Grant, S. G. (2022). A brain atlas of synapse protein lifetime across the mouse lifespan. Neuron, 110(24), 4057-4073. https://doi.org/10.1016/j.neuron.2022.09.009

The lifetime of proteins in synapses is important for their signaling, maintenance, and remodeling, and for memory duration. We quantified the lifetime of endogenous PSD95, an abundant postsynaptic protein in excitatory synapses, at single-synapse re... Read More about A brain atlas of synapse protein lifetime across the mouse lifespan.

Detection of Signals in MC–CDMA Using a Novel Iterative Block Decision Feedback Equalizer (2022)
Journal Article
Bagadi, K., Ravikumar, C., Sathish, K., Alibakhshikenari, M., Virdee, B. S., Kouhalvandi, L., Olan-Nuñez, . K. N., Pau, G., See, C. H., Dayoub, I., Livreri, . P., Aïssa, S., Falcone, F., & Limiti, E. (2022). Detection of Signals in MC–CDMA Using a Novel Iterative Block Decision Feedback Equalizer. IEEE Access, 10, 105674-105684. https://doi.org/10.1109/ACCESS.2022.3211392

This paper presents a technique to mitigate multiple access interference (MAI) in multicarrier code division multiple access (MC-CDMA) wireless communications systems. Although under normal circumstances the MC-CDMA system can achieve high spectral e... Read More about Detection of Signals in MC–CDMA Using a Novel Iterative Block Decision Feedback Equalizer.

Special Issue on Adversarial AI to IoT Security and Privacy Protection: Attacks and Defenses (2022)
Journal Article
Gao, H., & Tan, Z. (2022). Special Issue on Adversarial AI to IoT Security and Privacy Protection: Attacks and Defenses. Computer Journal, 65(11), 2847-2848. https://doi.org/10.1093/comjnl/bxac128

The prosperity of social IoT data brings revolutionary changes to our daily lives and greatly increases the existing data volume. But IoT data are vulnerable due to security and privacy issues. Over the past few years, malicious adversaries exploited... Read More about Special Issue on Adversarial AI to IoT Security and Privacy Protection: Attacks and Defenses.

Manipulating Foley Footsteps and Character Realism to Influence Audience Perceptions of a 3D Animated Walk Cycle (2022)
Presentation / Conference Contribution
Cunningham, S., & Mcgregor, I. (2022, September). Manipulating Foley Footsteps and Character Realism to Influence Audience Perceptions of a 3D Animated Walk Cycle. Presented at Audio Mostly 2022, St. Pölten University of Applied Sciences, Austria

Foley artistry is an essential part of the audio post-production process for film, television, games, and animation. By extension, it is as crucial in emergent media such as virtual, mixed, and augmented reality. Footsteps are a core activity that a... Read More about Manipulating Foley Footsteps and Character Realism to Influence Audience Perceptions of a 3D Animated Walk Cycle.

AI-driven lightweight real-time SDR sensing system for anomalous respiration identification using ensemble learning (2022)
Journal Article
Saeed, U., Abbasi, Q. H., & Shah, S. A. (2022). AI-driven lightweight real-time SDR sensing system for anomalous respiration identification using ensemble learning. CCF Transactions on Pervasive Computing and Interaction, 4(4), 381-392. https://doi.org/10.1007/s42486-022-00113-6

In less than three years, more than six million fatalities have been reported worldwide due to the coronavirus pandemic. COVID-19 has been contained within a broad range due to restrictions and effective vaccinations. However, there is a greater risk... Read More about AI-driven lightweight real-time SDR sensing system for anomalous respiration identification using ensemble learning.

Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform (2022)
Journal Article
Ali, H., Ahmad, J., Jaroucheh, Z., Papadopoulos, P., Pitropakis, N., Lo, O., Abramson, W., & Buchanan, W. J. (2022). Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform. Entropy, 24(10), Article 1379. https://doi.org/10.3390/e24101379

Historically, threat information sharing has relied on manual modelling and centralised network systems, which can be inefficient, insecure, and prone to errors. Alternatively, private blockchains are now widely used to address these issues and impro... Read More about Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform.

An enduring in vitro wound healing phase recipient by bioactive glass-graphene oxide nanocomposites (2022)
Journal Article
Nandhakumar, M., Thangaian, D. T., Sundaram, S., Roy, A., & Subramanian, B. (2022). An enduring in vitro wound healing phase recipient by bioactive glass-graphene oxide nanocomposites. Scientific Reports, 12(1), Article 16162. https://doi.org/10.1038/s41598-022-20575-z

Bioactive glass (BG) is an interesting topic in soft tissue engineering because of its biocompatibility and bonding potential to increase fibroblast cell proliferation, synthesize growth factors, and stimulate granulation tissue development. The prop... Read More about An enduring in vitro wound healing phase recipient by bioactive glass-graphene oxide nanocomposites.

Investigating Machine Learning Attacks on Financial Time Series Models (2022)
Journal Article
Gallagher, M., Pitropakis, N., Chrysoulas, C., Papadopoulos, P., Mylonas, A., & Katsikas, S. (2022). Investigating Machine Learning Attacks on Financial Time Series Models. Computers and Security, 123, https://doi.org/10.1016/j.cose.2022.102933

Machine learning and Artificial Intelligence (AI) already support human decision-making and complement professional roles, and are expected in the future to be sufficiently trusted to make autonomous decisions. To trust AI systems with such tasks, a... Read More about Investigating Machine Learning Attacks on Financial Time Series Models.

IoT for Sustainability (2022)
Book Chapter
Davison, B. (2022). IoT for Sustainability. In R. Buyya, L. Garg, G. Fortino, & S. Misra (Eds.), New Frontiers in Cloud Computing and Internet of Things (253-286). Cham: Springer. https://doi.org/10.1007/978-3-031-05528-7_10

The Internet of Things (IoT) comprises a set of complementary technologies which offer unprecedented opportunities for interacting with the physical environment. Faced with multiple pressures on our physical wellbeing such as climate change, habitat... Read More about IoT for Sustainability.

Detection of Ethanol Concentration in Liquid Using a Double-Layered Resonator Operating at 5G-mm-Wave Frequencies (2022)
Journal Article
Qureshi, S. A., Abidin, Z. Z., Majid, H. A., Ashyap, A. Y. I., & See, C. H. (2022). Detection of Ethanol Concentration in Liquid Using a Double-Layered Resonator Operating at 5G-mm-Wave Frequencies. Journal of Electronic Materials, 51, 7028-7036. https://doi.org/10.1007/s11664-022-09932-w

A new sensing technique for rapidly detecting ethanol concentration in aqueous solutions based on electromagnetic resonance is discussed. The sensor has two substrate layers and operates at 5G-mm-wave frequencies. An experimental study of the new res... Read More about Detection of Ethanol Concentration in Liquid Using a Double-Layered Resonator Operating at 5G-mm-Wave Frequencies.

Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures (2022)
Presentation / Conference Contribution
Zheng, C., Zhen, C., Xie, H., & Yang, S. (2022, June). Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures. Presented at 2022 IEEE Conference on Dependable and Secure Computing (DSC), Edinburgh, United Kingdom

Reinforcement Learning (RL) is one of the most popular methods for solving complex sequential decision-making problems. Deep RL needs careful sensing of the environment, selecting algorithms as well as hyper-parameters via soft agents, and simultaneo... Read More about Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures.

A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling (2022)
Presentation / Conference Contribution
Turnbull, L., Tan, Z., & Babaagba, K. (2022, June). A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling. Presented at The 2022 5th IEEE Conference on Dependable and Secure Computing (IEEE DSC 2022), Edinburgh [Online]

Malicious software trends show a persistent yearly increase in volume and cost impact. More than 350,000 new malicious or unwanted programs that target various technologies were registered daily over the past year. Metamorphic malware is a specifical... Read More about A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling.

Comprehensive review on the feasibility of developing wave energy as a renewable energy resource in Australia (2022)
Journal Article
Wimalaratna, Y. P., Hassan, A., Afrouzi, H. N., Mehranzamir, K., Ahmed, J., Siddique, B. M., & Liew, S. C. (2022). Comprehensive review on the feasibility of developing wave energy as a renewable energy resource in Australia. Cleaner Energy Systems, 3, Article 100021. https://doi.org/10.1016/j.cles.2022.100021

The facts are that increasing energy demand, depletion of fossil fuel, and greenhouse gas emissions have increased the world's interest in renewable energy. Out of all RE options, Wave Energy (WE) is the least harnessed one despite the availability o... Read More about Comprehensive review on the feasibility of developing wave energy as a renewable energy resource in Australia.

An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos (2022)
Journal Article
Hoffmann, B., Urquhart, N., Chalmers, K., & Guckert, M. (2022). An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos. Empirical Software Engineering, 27(7), Article 180. https://doi.org/10.1007/s10664-022-10210-w

Domain-specific languages (DSLs) are a popular approach among software engineers who demand for a tailored development interface. A DSL-based approach allows to encapsulate the intricacies of the target platform in transformations that turn DSL model... Read More about An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos.