All Outputs (601)

A little about the verification of a lot (EN 14358) (2022)
Presentation / Conference Contribution
Ridley-Ellis, D. (2022, September). A little about the verification of a lot (EN 14358). Paper presented at Northern European Network for Wood Science and Engineering (WSE) 2022, Goettingen, Germany

Sometimes it is necessary to estimate the mean and/or percentile of a certain population by limited sampling, in order to compare with target values. Done properly, the method should account for random chance in the sampling so that the two risks can... Read More about A little about the verification of a lot (EN 14358).

Dynamic noise filtering for multi-class classification of beehive audio data (2022)
Journal Article
Várkonyi, D. T., Seixas Junior, J. L., & Horváth, T. (2023). Dynamic noise filtering for multi-class classification of beehive audio data. Expert Systems with Applications, 213(Part A), Article 118850. https://doi.org/10.1016/j.eswa.2022.118850

Honeybees are the most specialized insect pollinators and are critical not only for honey production but, also, for keeping the environmental balance by pollinating the flowers of a wide variety of crops. Recording and analyzing bee sounds became... Read More about Dynamic noise filtering for multi-class classification of beehive audio data.

Who is More Likely (Not) to Make Home-Based Work Trips during the COVID-19 Pandemic? The Case of Scotland (2022)
Journal Article
Semple, T., Fountas, G., & Fonzone, A. (2023). Who is More Likely (Not) to Make Home-Based Work Trips during the COVID-19 Pandemic? The Case of Scotland. Transportation research record, 2677(4), 904-916. https://doi.org/10.1177/03611981221119192

In this study, we use survey data (n=6,000) to investigate the work trip patterns of Scottish residents at various points of the COVID-19 pandemic. We focus specifically on the reported patterns of weekly work trips made during the government-enforce... Read More about Who is More Likely (Not) to Make Home-Based Work Trips during the COVID-19 Pandemic? The Case of Scotland.

DSMAC: Privacy-Aware Decentralized Self-Management of Data Access Control Based on Blockchain for Health Data (2022)
Journal Article
Saidi, H., Labraoui, N., Ari, A. A. A., Maglaras, L. A., & Emati, J. H. M. (2022). DSMAC: Privacy-Aware Decentralized Self-Management of Data Access Control Based on Blockchain for Health Data. IEEE Access, 10, 101011-101028. https://doi.org/10.1109/acces

In recent years, the interest in using wireless communication technologies and mobile devices in the healthcare environment has increased. However, despite increased attention to the security of electronic health records, patient privacy is still at... Read More about DSMAC: Privacy-Aware Decentralized Self-Management of Data Access Control Based on Blockchain for Health Data.

Eight-Element Antenna Array with Improved Radiation Performances for 5G Hand-Portable Devices (2022)
Journal Article
Ullah, A., Ojaroudi Parchin, N., Amar, A. S. I., & Abd-Alhameed, R. A. (2022). Eight-Element Antenna Array with Improved Radiation Performances for 5G Hand-Portable Devices. Electronics, 11(18), Article 2962. https://doi.org/10.3390/electronics11182962

This study aims to introduce a new phased array design with improved radiation properties for future cellular networks. The procedure of the array design is simple and has been accomplished on a low-cost substrate material while offering several inte... Read More about Eight-Element Antenna Array with Improved Radiation Performances for 5G Hand-Portable Devices.

RCT: Random consistency training for semi-supervised sound event detection (2022)
Presentation / Conference Contribution
Shao, N., Loweimi, E., & Li, X. (2022, September). RCT: Random consistency training for semi-supervised sound event detection. Paper presented at Interspeech 2022, Incheon, Korea

Sound event detection (SED), as a core module of acoustic environmental analysis, suffers from the problem of data deficiency. The integration of semi-supervised learning (SSL) largely mitigates such problem. This paper researches on several core mod... Read More about RCT: Random consistency training for semi-supervised sound event detection.

Dysarthric Speech Recognition From Raw Waveform with Parametric CNNs (2022)
Presentation / Conference Contribution
Yue, Z., Loweimi, E., Christensen, H., Barker, J., & Cvetkovic, Z. (2022, September). Dysarthric Speech Recognition From Raw Waveform with Parametric CNNs. Paper presented at Interspeech 2022, Incheon, Korea

Raw waveform acoustic modelling has recently received increasing attention. Compared with the task-blind hand-crafted features which may discard useful information, representations directly learned from the raw waveform are task-specific and potentia... Read More about Dysarthric Speech Recognition From Raw Waveform with Parametric CNNs.

Developing a hybrid risk assessment method for prioritizing the critical risks of temporary accommodation sites after destructive earthquakes (2022)
Journal Article
Dabiri, M., Sarvari, H., Chan, D. W., & Olawumi, T. O. (2022). Developing a hybrid risk assessment method for prioritizing the critical risks of temporary accommodation sites after destructive earthquakes. Habitat International, 128, Article 102667. https

One of the most critical challenges in preventive planning and disaster management is the multitudinous uncertainties involved in decision-making. Previous studies showed the usefulness of intuitionistic fuzzy sets for considering uncertainties in de... Read More about Developing a hybrid risk assessment method for prioritizing the critical risks of temporary accommodation sites after destructive earthquakes.

DPb-MOPSO: A Dynamic Pareto bi-level Multi-objective Particle Swarm Optimization Algorithm (2022)
Journal Article
Aboud, A., Rokbani, N., Fdhila, R., Qahtani, A. M., Almutiry, O., Dhahri, H., …Alimi, A. M. (2022). DPb-MOPSO: A Dynamic Pareto bi-level Multi-objective Particle Swarm Optimization Algorithm. Applied Soft Computing, 129, Article 109622. https://doi.org/

Particle Swarm Optimization (PSO) system based on the distributed architecture over multiple sub-swarms is very efficient for static multi-objective optimization but has not been considered for solving dynamic multi-objective problems (DMOPs). Tracki... Read More about DPb-MOPSO: A Dynamic Pareto bi-level Multi-objective Particle Swarm Optimization Algorithm.

Joint Effect of Heavy Vehicles and Diminished Light Conditions on Paediatric Pedestrian Injuries in Backover Crashes: A UK Population-Based Study (2022)
Journal Article
Wiratama, B. S., Hsu, L., Yeh, Y., Chen, C., Saleh, W., Liu, Y., & Pai, C. (2022). Joint Effect of Heavy Vehicles and Diminished Light Conditions on Paediatric Pedestrian Injuries in Backover Crashes: A UK Population-Based Study. International Journal of

Backover crashes cause considerable injuries especially among young children. Prior research on backover crashes has not assessed the joint effect of heavy vehicles and diminished light conditions on injuries. By analysing the United Kingdom STATS19... Read More about Joint Effect of Heavy Vehicles and Diminished Light Conditions on Paediatric Pedestrian Injuries in Backover Crashes: A UK Population-Based Study.

A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling (2022)
Journal Article
Comminiello, D., Nezamdoust, A., Scardapane, S., Scarpiniti, M., Hussain, A., & Uncini, A. (2023). A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling. IEEE Transactions on Systems, Man and Cybernetics: Systems, 53(3), 1384-1396. https

Nonlinear models are known to provide excellent performance in real-world applications that often operate in nonideal conditions. However, such applications often require online processing to be performed with limited computational resources. To addr... Read More about A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling.

Comparison of machine learning models for early depression detection from users’ posts (2022)
Book Chapter
Mothe, J., Ramiandrisoa, F., & Ullah, M. Z. (2022). Comparison of machine learning models for early depression detection from users’ posts. In F. Crestani, D. E. Losada, & J. Parapar (Eds.), Early Detection of Mental Health Disorders by Social Media Mon

With around 300 millions people worldwide suffering from depression, the detection of this disorder is crucial and a challenge for individual and public health. As with many diseases, early detection means better medical management; the use of social... Read More about Comparison of machine learning models for early depression detection from users’ posts.

Correction of Evanescent Wave Influence on the Flexural Wave Velocity and Wavelength Estimation Based on a Mode Shape Function (2022)
Journal Article
Pantelić, F., Šumarac Pavlović, D., Mijić, M., & Ridley-Ellis, D. (2022). Correction of Evanescent Wave Influence on the Flexural Wave Velocity and Wavelength Estimation Based on a Mode Shape Function. Archives of Acoustics, 47(4), 539-546. https://do

The aim of this research is to use a simple acoustic method of a very near field recording, which enables measurement and display of oscillation modes, to estimate the velocity of flexural waves, based on the wavelengths of standing waves measured on... Read More about Correction of Evanescent Wave Influence on the Flexural Wave Velocity and Wavelength Estimation Based on a Mode Shape Function.

A Few-Shot Learning Method for SAR Images Based on Weighted Distance and Feature Fusion (2022)
Journal Article
Gao, F., Xu, J., Lang, R., Wang, J., Hussain, A., & Zhou, H. (2022). A Few-Shot Learning Method for SAR Images Based on Weighted Distance and Feature Fusion. Remote Sensing, 14(18), Article 4583. https://doi.org/10.3390/rs14184583

Convolutional Neural Network (CNN) has been widely applied in the field of synthetic aperture radar (SAR) image recognition. Nevertheless, CNN-based recognition methods usually encounter the problem of poor feature representation ability due to insuf... Read More about A Few-Shot Learning Method for SAR Images Based on Weighted Distance and Feature Fusion.

Classification of Skin Cancer Lesions Using Explainable Deep Learning (2022)
Journal Article
Zia Ur Rehman, M., Ahmed, F., Alsuhibany, S. A., Jamal, S. S., Zulfiqar Ali, M., & Ahmad, J. (2022). Classification of Skin Cancer Lesions Using Explainable Deep Learning. Sensors, 22(18), Article 6915. https://doi.org/10.3390/s22186915

Skin cancer is among the most prevalent and life-threatening forms of cancer that occur worldwide. Traditional methods of skin cancer detection need an in-depth physical examination by a medical professional, which is time-consuming in some cases. Re... Read More about Classification of Skin Cancer Lesions Using Explainable Deep Learning.

The creative use of digitised archives: case study of Lorna Lloyd’s ‘Diary of the War’ podcast series (2022)
Presentation / Conference Contribution
Ryan, B., Hall, H., Wilson, M., & Berger, J. (2022, September). The creative use of digitised archives: case study of Lorna Lloyd’s ‘Diary of the War’ podcast series. Presented at The BBC at 100 Symposium, National Science and Media Museum, Bradford

The roundtable discussion is concerned with the creative use of digitised archives in the work undertaken for the AHRC Creative Informatics funded Platform to Platform project. This centres on the exploitation, augmentation, and exhibition of a set o... Read More about The creative use of digitised archives: case study of Lorna Lloyd’s ‘Diary of the War’ podcast series.

Federated Learning for Short-term Residential Load Forecasting (2022)
Journal Article
Briggs, C., Fan, Z., & Andras, P. (2022). Federated Learning for Short-term Residential Load Forecasting. IEEE Open Access Journal of Power and Energy, 9, 573-583. https://doi.org/10.1109/oajpe.2022.3206220

Load forecasting is an essential task performed within the energy industry to help balance supply with demand and maintain a stable load on the electricity grid. As supply transitions towards less reliable renewable energy generation, smart meters wi... Read More about Federated Learning for Short-term Residential Load Forecasting.

Dynamic Behaviour of a Geotechnical Seismic Isolation System with Rubber-Sand Mixtures to Enhance Seismic Protection (2022)
Presentation / Conference Contribution
Bernal-Sanchez, J., McDougall, J., Miranda-Manzanares, M., & Barreto, D. (2022, September). Dynamic Behaviour of a Geotechnical Seismic Isolation System with Rubber-Sand Mixtures to Enhance Seismic Protection. Presented at 3rd European Conference on Earth

A Geotechnical Seismic Isolation (GSI) system is proposed in this study based on the use of Rubber-Soil mixtures (RSm) to facilitate the benefits of dynamic soil-foundation structure interaction. The latter is possible due to the lower stiffness and... Read More about Dynamic Behaviour of a Geotechnical Seismic Isolation System with Rubber-Sand Mixtures to Enhance Seismic Protection.

Multimodal audio-visual information fusion using canonical-correlated Graph Neural Network for energy-efficient speech enhancement (2022)
Journal Article
Passos, L. A., Papa, J. P., Del Ser, J., Hussain, A., & Adeel, A. (2023). Multimodal audio-visual information fusion using canonical-correlated Graph Neural Network for energy-efficient speech enhancement. Information Fusion, 90, 1-11. https://doi.org/10.

This paper proposes a novel multimodal self-supervised architecture for energy-efficient audio-visual (AV) speech enhancement that integrates Graph Neural Networks with canonical correlation analysis (CCA-GNN). The proposed approach lays its foundati... Read More about Multimodal audio-visual information fusion using canonical-correlated Graph Neural Network for energy-efficient speech enhancement.

Narrative modelling: A comparison of high and low mass dwelling solutions in Afghanistan and Peru (2022)
Journal Article
Eltaweel, A., Kuchai, N., Albadra, D., Coley, D., Hart, J., Acevedo-De-los-Ríos, A., & Rondinel-Oviedo, D. R. (2023). Narrative modelling: A comparison of high and low mass dwelling solutions in Afghanistan and Peru. Building Services Engineering Researc

Displaced populations are housed in various constructions, including lightweight predesigned structures. Theoretically, self-built heavyweight structures should ensure better temperatures and be closer to cultural norms. To examine this directly for... Read More about Narrative modelling: A comparison of high and low mass dwelling solutions in Afghanistan and Peru.