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Outputs (75)

Fungal electronics (2021)
Journal Article
Adamatzky, A., Ayres, P., Beasley, A. E., Chiolerio, A., Dehshibi, M. M., Gandia, A., …Wösten, H. A. (2022). Fungal electronics. BioSystems, 212, Article 104588. https://doi.org/10.1016/j.biosystems.2021.104588

Fungal electronics is a family of living electronic devices made of mycelium bound composites or pure mycelium. Fungal electronic devices are capable of changing their impedance and generating spikes of electrical potential in response to external co... Read More about Fungal electronics.

Deep learning based customer preferences analysis in industry 4.0 environment (2021)
Journal Article
Sun, Q., Feng, X., Zhao, S., Cao, H., Li, S., & Yao, Y. (2021). Deep learning based customer preferences analysis in industry 4.0 environment. Mobile Networks and Applications, 26, 2329–2340. https://doi.org/10.1007/s11036-021-01830-5

Customer preferences analysis and modelling using deep learning in edge computing environment are critical to enhance customer relationship management that focus on a dynamically changing market place. Existing forecasting methods work well with ofte... Read More about Deep learning based customer preferences analysis in industry 4.0 environment.

Exploring a web-based application to convert Tamil and Vietnamese speech to text without the effect of code- switching and code-mixing (2021)
Journal Article
Phung, K., Ramachandran, R., & Ogunshile, E. (2021). Exploring a web-based application to convert Tamil and Vietnamese speech to text without the effect of code- switching and code-mixing. Programming and Computer Software, 47(8), 757-764. https://doi.org/10.1134/S036176882108020X

This paper attempts to develop an application that converts Tamil and Vietnamese speech to text, with a view to encourage usage and indirectly ensure linguistic preservation of a classical language. The application converts spoken Tamil and Vietnames... Read More about Exploring a web-based application to convert Tamil and Vietnamese speech to text without the effect of code- switching and code-mixing.

A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach (2021)
Journal Article
Phung, K., Jayatilake, D., Ogunshile, E., & Aydin, M. (2021). A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach. Programming and Computer Software, 47(8), 765-777. https://doi.org/10.1134/S0361768821080211

In the biomedical domain, diagrammatical models have been extensively used to describe and understand the behaviour of biological organisms (biological agents) for decades. Although these models are simple and comprehensive, they can only offer a sta... Read More about A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach.

Application of region-based video surveillance in smart cities using deep learning (2021)
Journal Article
Zahra, A., Ghafoor, M., Munir, K., Ullah, A., & Ul Abideen, Z. (2021). Application of region-based video surveillance in smart cities using deep learning. Multimedia Tools and Applications, 2021, https://doi.org/10.1007/s11042-021-11468-w

Smart video surveillance helps to build more robust smart city environment. The varied angle cameras act as smart sensors and collect visual data from smart city environment and transmit it for further visual analysis. The transmitted visual data is... Read More about Application of region-based video surveillance in smart cities using deep learning.

Users’ experiences of enhancing underwater images: An empirical study (2021)
Journal Article
Emberton, S., & Simons, C. (2021). Users’ experiences of enhancing underwater images: An empirical study. Quality and User Experience, 7(1), Article 1. https://doi.org/10.1007/s41233-021-00048-3

Within the worldwide diving community, underwater photography is becoming increasingly popular. However, the marine environment presents certain challenges for image capture, with resulting imagery often suffering from colour distortions, low contras... Read More about Users’ experiences of enhancing underwater images: An empirical study.

Ensemble metropolis light transport (2021)
Journal Article
Bashford-Rogers, T., Paulo Santos, L., Marnerides, D., & Debattista, K. (2022). Ensemble metropolis light transport. ACM Transactions on Graphics, 41(1), Article 5. https://doi.org/10.1145/3472294

This article proposes a Markov Chain Monte Carlo (MCMC) rendering algorithm based on a family of guided transition kernels. The kernels exploit properties of ensembles of light transport paths, which are distributed according to the lighting in the s... Read More about Ensemble metropolis light transport.

Emergent deep learning for anomaly detection in internet of everything (2021)
Journal Article
Djenouri, Y., Djenouri, D., Belhadi, A., Srivastava, G., & Lin, J. C. W. (2023). Emergent deep learning for anomaly detection in internet of everything. IEEE Internet of Things, 10(4), 3206-3214. https://doi.org/10.1109/JIOT.2021.3134932

This research presents a new generic deep learning framework for anomaly detection in the Internet of Everything (IoE). It combines decomposition methods, deep neural networks, and evolutionary computation to better detect outliers in IoE environment... Read More about Emergent deep learning for anomaly detection in internet of everything.

E-learning development based on internet of things and blockchain technology during Covid-19 Pandemic (2021)
Journal Article
Rahmani, A. M., Naqvi, R., Malik, M., Malik, T. S., Sadrishojaei, M., Hosseinzadeh, M., & Al-Musawi, A. (2021). E-learning development based on internet of things and blockchain technology during Covid-19 Pandemic. Mathematics, 9(24), 3151. https://doi.org/10.3390/math9243151

The suspension of institutions around the world in early 2020 due to the COVID-19 virus did not stop the learning process. E-learning concepts and digital technologies enable students to learn from a safe distance while continuing their educational p... Read More about E-learning development based on internet of things and blockchain technology during Covid-19 Pandemic.