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How Can Big Data Analytics Improve Outbound Logistics in The UK Retail Sector? A Qualitative Study (2023)
Journal Article
Ali, M., & Essien, A. (2023). How Can Big Data Analytics Improve Outbound Logistics in The UK Retail Sector? A Qualitative Study. Journal of Enterprise Information Management, https://doi.org/10.1108/JEIM-08-2022-0282

Purpose – The purpose of this study is to explore how big data analytics (BDA) as a potential information technology (IT) innovation can facilitate the retail logistics supply chain (SC) from the perspective of outbound logistics operations in the Un... Read More about How Can Big Data Analytics Improve Outbound Logistics in The UK Retail Sector? A Qualitative Study.

Environmental, health and safety assessment of nanoparticle application in drilling mud – review (2023)
Journal Article
Martin, C., Nourian, A., Babaie, M., & Nasr, G. (in press). Environmental, health and safety assessment of nanoparticle application in drilling mud – review. Journal of Petroleum Science and Engineering, 226, https://doi.org/10.1016/j.geoen.2023.211767

The rapid increase in the use of engineered nanoparticles in different industrial applications makes risk assessment on human health, ecosystem and the environment necessary. Health, safety and environmental (HSE) risks of a technology are an insep... Read More about Environmental, health and safety assessment of nanoparticle application in drilling mud – review.

Closed-form analytical approach for calculating noise contours of directive aircraft noise sources (2023)
Journal Article
of directive aircraft noise sources. AIAA journal, https://doi.org/10.2514/1.J062033

This paper extends the simplified airport noise model Rapid Aviation Noise Evaluator (RANE) [Torija et al., Journal of the Acoustical Society of America, Vol. 141, No. 2, 2017, pp. 981–995], adding capability of including fully nonisotropic noise sou... Read More about Closed-form analytical approach for calculating noise contours of directive aircraft noise sources.

A comparison between the high-frequency Boundary Element Method and Surface-Based Geometrical Acoustics (2023)
Journal Article
Hargreaves, J. (2023). A comparison between the high-frequency Boundary Element Method and Surface-Based Geometrical Acoustics. https://doi.org/10.3397/in_2022_1005

The audible frequency range covers many octaves in which the wavelength changes from being large with respect to dominant features of a space to being comparatively much smaller. This makes numerical prediction of a space's acoustic response, e.g. fo... Read More about A comparison between the high-frequency Boundary Element Method and Surface-Based Geometrical Acoustics.

Can acoustic design accommodate aural diversity? (2023)
Journal Article
Davies, W. (2023). Can acoustic design accommodate aural diversity?. NOISE-CON proceedings, 8, 5064-5071. https://doi.org/10.3397/IN_2022_0732

Up to now, the acoustic design of almost everything has assumed a typical listener with "normal" hearing. This includes the physical environment (homes, workplaces, public space), products that make sound (transport, appliances, loudspeakers), and sy... Read More about Can acoustic design accommodate aural diversity?.

An optimisation of a chordwise slot to enhance lateral flow control on a UCAV (2022)
Journal Article
Ali, U., Chadwick, E., & Sugar-Gabor, O. (2022). An optimisation of a chordwise slot to enhance lateral flow control on a UCAV. Incas Bulletin, 14(4), 3-17. https://doi.org/10.13111/2066-8201.2022.14.4.1

This research aims to optimise a chordwise slot so that lateral flow control of a flying wing configuration can be enhanced. This was achieved by maximising the airflow rate over the trailing edge control surfaces of the wing. A higher rate of airf... Read More about An optimisation of a chordwise slot to enhance lateral flow control on a UCAV.

DeepClean : a robust deep learning technique for autonomous vehicle camera data privacy (2022)
Journal Article
Adeboye, O., Dargahi, T., Babaie, M., Saraee, M., & Yu, C. (2022). DeepClean : a robust deep learning technique for autonomous vehicle camera data privacy. IEEE Access, https://doi.org/10.1109/ACCESS.2022.3222834

Autonomous Vehicles (AVs) are equipped with several sensors which produce various forms of data, such as geo-location, distance, and camera data. The volume and utility of these data, especially camera data, have contributed to the advancement of h... Read More about DeepClean : a robust deep learning technique for autonomous vehicle camera data privacy.

An experimental study of granular material using recycled concrete waste for pavement roadbed construction (2022)
Journal Article
concrete waste for pavement roadbed construction. Buildings, 12(11), 1926. https://doi.org/10.3390/buildings12111926

Rapid worldwide urbanization and drastic population growth have increased the demand for new road construction, which will cause a substantial amount of natural resources such as aggregates to be consumed. The use of recycled concrete aggregate could... Read More about An experimental study of granular material using recycled concrete waste for pavement roadbed construction.

Experimental study of temperature effect on the mechanical tensile fatigue of hydrated lime modified asphalt concrete and case application for the analysis of climatic effect on constructed pavement (2022)
Journal Article
constructed pavement. Case studies in construction materials, 17, https://doi.org/10.1016/j.cscm.2022.e01622

Previous experimental studies have suggested that hot mixed asphalt (HMA) concrete using hydrated lime (HL) to partially replace the conventional limestone dust filler at 2.5% by the total weight of all aggregates showed an optimum improvement on sev... Read More about Experimental study of temperature effect on the mechanical tensile fatigue of hydrated lime modified asphalt concrete and case application for the analysis of climatic effect on constructed pavement.

Sonic enhancement of virtual exhibits (2022)
Journal Article
Al-Taie, I., Di Franco, P., Tymkiw, M., Williams, D., & Daly, I. (2022). Sonic enhancement of virtual exhibits. PLoS ONE, 17(8), https://doi.org/10.1371/journal.pone.0269370

Museums have widely embraced virtual exhibits. However, relatively little attention is paid to how sound may create a more engaging experience for audiences. To begin addressing this lacuna, we conducted an online experiment to explore how sound infl... Read More about Sonic enhancement of virtual exhibits.

Text line segmentation from struck-out handwritten document images (2022)
Journal Article
Shivakumara, P., Jain, T., Pal, U., Surana, N., Antonacopoulos, A., & Lu, T. (2022). Text line segmentation from struck-out handwritten document images. Expert systems with applications, 210, 118266. https://doi.org/10.1016/j.eswa.2022.118266

In the case of freestyle everyday handwritten documents, writing, erasing, striking out, and overwriting are common behaviors of the writers. This not cleanly-written text poses significant challenges for text line segmentation. Accurate text line se... Read More about Text line segmentation from struck-out handwritten document images.

Cloud-based AI for automatic audio production for personalized immersive XR experiences (2022)
Journal Article
Oldfield, R., Walley, M., Shirley, B., & Williams, D. (2022). Cloud-based AI for automatic audio production for personalized immersive XR experiences. SMPTE motion imaging journal, 131(7), 6-16. https://doi.org/10.5594/JMI.2022.3184849

In this article, we focus on the machine-learning approach developed for automatic audio source recognition and mixing for the U.K. Government Department of Culture Media and Sport (DCMS) funded collaborative project called 5G Edge-XR. Leveraging gra... Read More about Cloud-based AI for automatic audio production for personalized immersive XR experiences.

Requirements for drone operations to minimise community noise impact (2022)
Journal Article
Ramos Romero, C., Green, N., Roberts, S., Clark, C., & Torija Martinez, A. (2022). Requirements for drone operations to minimise community noise impact. International Journal of Environmental Research and Public Health, 19(15), https://doi.org/10.3390/ijerph19159299

The number of applications for drones under R&D have growth significantly during the 12 last few years, however the wider adoption of these technologies requires ensuring public trust and 13 acceptance. Noise has been identified as one of the key c... Read More about Requirements for drone operations to minimise community noise impact.

Optimal controllers and configurations of 100% PV and energy Storage systems for a microgrid : the case study of a small town in Jordan (2022)
Journal Article
Alasali, F., Salameh, M., Semrin, A., Nusair, K., El-Naily, N., & Holderbaum, W. (2022). Optimal controllers and configurations of 100% PV and energy Storage systems for a microgrid : the case study of a small town in Jordan. Sustainability, 14(13), 8124. https://doi.org/10.3390/su14138124

Renewable energy systems such as Photovoltaic (PV) have become one of the best options for supplying electricity at the distribution network level. This is mainly because the PV system is sustainable, environmentally friendly, and is a low-cost form... Read More about Optimal controllers and configurations of 100% PV and energy Storage systems for a microgrid : the case study of a small town in Jordan.

Thermal properties of hydrated lime-modified asphalt concrete and modelling evaluation for their effect on the constructed pavements in service (2022)
Journal Article
Al Ashaibi, A., Wang, Y., Albayati, A., Byzyka, J., Scholz, M., & Weekes, L. (2022). Thermal properties of hydrated lime-modified asphalt concrete and modelling evaluation for their effect on the constructed pavements in service. Sustainability, 14(13),

Flexible pavements are subjected to three main distress types: fatigue crack, thermal crack, and permanent deformation. Under severe climate conditions, thermal cracking particularly contributes largely to a considerable scale of premature deteriora... Read More about Thermal properties of hydrated lime-modified asphalt concrete and modelling evaluation for their effect on the constructed pavements in service.

A deep explainable model for fault prediction using IoT sensors (2022)
Journal Article
Mansouri, T., & Vadera, S. (2022). A deep explainable model for fault prediction using IoT sensors. IEEE Access, https://doi.org/10.1109/ACCESS.2022.3184693

IoT sensors and deep learning models can widely be applied for fault prediction. Although deep learning models are considerably more potent than many conventional machine learning models, they are not transparent. This paper first examines differen... Read More about A deep explainable model for fault prediction using IoT sensors.

A heuristic approach on predictive maintenance techniques : limitations and scope (2022)
Journal Article
Shukla, K., Nefti-Meziani, S., & Davis, S. (2022). A heuristic approach on predictive maintenance techniques : limitations and scope. Advances in Mechanical Engineering, 14(6), https://doi.org/10.1177/16878132221101009

In view of the trend towards Industry 4.0, intelligent predictive monitoring and decision-making processes have become a crucial requirement in today’s manufacturing industries to safeguard data exchange and industrial assets from damage that would t... Read More about A heuristic approach on predictive maintenance techniques : limitations and scope.

Methods for pruning deep neural networks (2022)
Journal Article
Vadera, S., & Ameen, S. (2022). Methods for pruning deep neural networks. IEEE Access, 63280- 63300. https://doi.org/10.1109/ACCESS.2022.3182659

This paper presents a survey of methods for pruning deep neural networks. It begins by categorising over 150 studies based on the underlying approach used and then focuses on three categories: methods that use magnitude based pruning, methods that... Read More about Methods for pruning deep neural networks.