Outputs (249)

Donor Influence on the Optoelectronic Properties of N‐Substituted Tetraphenylimidazole Derivatives (2023)
Journal Article
Matulaitis, T., dos Santos, P. L., Tsuchiya, Y., Cordes, D. B., Slawin, A. M., Adachi, C., Samuel, I. D., & Zysman‐Colman, E. (2023). Donor Influence on the Optoelectronic Properties of N‐Substituted Tetraphenylimidazole Derivatives. ChemistrySelect, 8(9), https://doi.org/10.1002/slct.202300274

Three new 1,2,4,5-tetraphenylimidazole derivatives, 9,9-dimethyl-10-(4-(2,4,5-triphenyl-1H-imidazol-1-yl)phenyl)-9,10-dihydroacridine (DMAC-TPI), 10-(4-(2,4,5-triphenyl-1H-imidazol-1-yl)phenyl)-10H-phenoxazine (PXZ-TPI), and 10-(4-(2,4,5-triphenyl-1H... Read More about Donor Influence on the Optoelectronic Properties of N‐Substituted Tetraphenylimidazole Derivatives.

Diversity-Based Non-Coherent Signal Detector for Molecular Communication via Reaction-Diffusion (2023)
Journal Article
Lin, Z., Li, B., Wei, Z., Huang, Y., Guo, W., & Zhao, C. (2023). Diversity-Based Non-Coherent Signal Detector for Molecular Communication via Reaction-Diffusion. IEEE Transactions on Communications, 71(5), 2618-2631. https://doi.org/10.1109/tcomm.2023.3249785

Molecular communication is attractive to the emerging nano-scale communication systems. Traditionally, a detector recovers the information from only the concentration of single messenger molecule, while ignoring the variation of multiple participants... Read More about Diversity-Based Non-Coherent Signal Detector for Molecular Communication via Reaction-Diffusion.

Approaching STEP file analysis as a language processing task: A robust and scale-invariant solution for machining feature recognition (2023)
Journal Article
Miles, V., Giani, S., & Vogt, O. (2023). Approaching STEP file analysis as a language processing task: A robust and scale-invariant solution for machining feature recognition. Journal of Computational and Applied Mathematics, 427, Article 115166. https://doi.org/10.1016/j.cam.2023.115166

Machining feature recognition is a key task in the intelligent analysis of 3D CAD models as it represents a bridge between a part design and the manufacturing processes required for manufacture and can, therefore, increase automation in the manufactu... Read More about Approaching STEP file analysis as a language processing task: A robust and scale-invariant solution for machining feature recognition.

On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds (2023)
Journal Article
Wang, C.-X., You, X., Gao, X., Zhu, X., Li, Z., Zhang, C., Wang, H., Huang, Y., Chen, Y., Haas, H., Thompson, J. S., Larsson, E. G., Renzo, M. D., Tong, W., Zhu, P., Shen, X., Poor, H. V., & Hanzo, L. (2023). On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds. IEEE Communications Surveys and Tutorials, 25(2), 905 - 974. https://doi.org/10.1109/comst.2023.3249835

Fifth generation (5G) mobile communication systems have entered the stage of commercial development, providing users with new services and improved user experiences as well as offering a host of novel opportunities to various industries. However, 5G... Read More about On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds.

Revisiting Salvucci’s Semi-analytical Solution for Bare Soil Evaporation with New Consideration of Vapour Diffusion and Film Flow (2023)
Journal Article
Mathias, S. A., Sander, G. C., Leung, J., & Newall, S. R. (2023). Revisiting Salvucci’s Semi-analytical Solution for Bare Soil Evaporation with New Consideration of Vapour Diffusion and Film Flow. Transport in Porous Media, 147(2), 463-493. https://doi.org/10.1007/s11242-023-01917-5

Bare soil evaporation is controlled by a combination of capillary flow, vapour diffusion and film flow. Relevant analytical solutions mostly assume horizontal flow conditions and ignore gravitational effects. Salvucci (1997) provided a rare example o... Read More about Revisiting Salvucci’s Semi-analytical Solution for Bare Soil Evaporation with New Consideration of Vapour Diffusion and Film Flow.

Molecular insights informing factors affecting low temperature anaerobic applications: Diversity, collated core microbiomes and complexity stability relationships in LCFA-fed systems. (2023)
Journal Article
Singh, S., Keating, C., Ijaz, U. Z., & Hassard, F. (2023). Molecular insights informing factors affecting low temperature anaerobic applications: Diversity, collated core microbiomes and complexity stability relationships in LCFA-fed systems. Science of the Total Environment, 874, Article 162420

Probability embedded failure prediction of unidirectional composites under biaxial loadings combining machine learning and micromechanical modelling (2023)
Journal Article
Wan, L., Ullah, Z., Yang, D., & Falzon, B. G. (2023). Probability embedded failure prediction of unidirectional composites under biaxial loadings combining machine learning and micromechanical modelling. Composite Structures, 312, Article 116837. https://doi.org/10.1016/j.compstruct.2023.116837

This study presents a data-driven, probability embedded approach for the failure prediction of IM7/8552 unidirectional carbon fibre reinforced polymer (CFRP) composite materials under biaxial stress states based on micromechanical modelling and artif... Read More about Probability embedded failure prediction of unidirectional composites under biaxial loadings combining machine learning and micromechanical modelling.

Data Augmentation with norm-VAE and Selective Pseudo-Labelling for Unsupervised Domain Adaptation (2023)
Journal Article
Wang, Q., Meng, F., & Breckon, T. (2023). Data Augmentation with norm-VAE and Selective Pseudo-Labelling for Unsupervised Domain Adaptation. Neural Networks, 161, 614-625. https://doi.org/10.1016/j.neunet.2023.02.006

We address the Unsupervised Domain Adaptation (UDA) problem in image classification from a new perspective. In contrast to most existing works which either align the data distributions or learn domain-invariant features, we directly learn a unified c... Read More about Data Augmentation with norm-VAE and Selective Pseudo-Labelling for Unsupervised Domain Adaptation.

Diagnostic value of intereye difference metrics for optic neuritis in aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorders (2023)
Journal Article
Oertel, F. C., Zimmermann, H. G., Motamedi, S., Chien, C., Aktas, O., Albrecht, P., Ringelstein, M., Dcunha, A., Pandit, L., Martinez-Lapiscina, E. H., Sanchez-Dalmau, B., Villoslada, P., Palace, J., Roca-Fernández, A., Leite, M. I., Sharma, S. M., Leocani, L., Pisa, M., Radaelli, M., Lana-Peixoto, M. A., …Petzold, A. (2023). Diagnostic value of intereye difference metrics for optic neuritis in aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorders. Journal of Neurology, Neurosurgery and Psychiatry, 94(7), 560-566. https://doi.org/10.1136/jnnp-2022-330608

Background: The novel optic neuritis (ON) diagnostic criteria include intereye differences (IED) of optical coherence tomography (OCT) parameters. IED has proven valuable for ON diagnosis in multiple sclerosis but has not been evaluated in aquaporin-... Read More about Diagnostic value of intereye difference metrics for optic neuritis in aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorders.

Automatic Choroid Vascularity Index Calculation in Optical Coherence Tomography Images with Low-Contrast Sclerochoroidal Junction Using Deep Learning (2023)
Journal Article
Arian, R., Mahmoudi, T., Riazi-Esfahani, H., Faghihi, H., Mirshahi, A., Ghassemi, F., Khodabande, A., Kafieh, R., & Khalili Pour, E. (2023). Automatic Choroid Vascularity Index Calculation in Optical Coherence Tomography Images with Low-Contrast Sclerochoroidal Junction Using Deep Learning. Photonics, 10(3), Article 234. https://doi.org/10.3390/photonics10030234

The choroidal vascularity index (CVI) is a new biomarker defined for retinal optical coherence tomography (OCT) images for measuring and evaluating the choroidal vascular structure. The CVI is the ratio of the choroidal luminal area (LA) to the total... Read More about Automatic Choroid Vascularity Index Calculation in Optical Coherence Tomography Images with Low-Contrast Sclerochoroidal Junction Using Deep Learning.