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All Outputs (130)

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.

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.

Blockchain and artificial intelligence – Managing a secure and sustainable supply chain (2021)
Book Chapter
Pimenidis, E., Patsavellas, J., & Tonkin, M. (2021). Blockchain and artificial intelligence – Managing a secure and sustainable supply chain. In H. Jahankhani, A. Jamal, & S. Lawson (Eds.), Cybersecurity, Privacy and Freedom Protection in the Connected World. (1). Springer. https://doi.org/10.1007/978-3-030-68534-8

Supply chain management is often the most challenging part of any business that manufactures, sells goods, or provides services. Regardless of whether the operations are mostly physical or online, managing supply chains largely relies on being able t... Read More about Blockchain and artificial intelligence – Managing a secure and sustainable supply chain.

Bespoke anywhere (2021)
Conference Proceeding
Gaster, B., & Challinor, R. (2021). Bespoke anywhere.

This paper reports on a project aimed to break away from the portability concerns of native DSP code between different platforms, thus freeing the instrument designer from the burden of porting new Digital Musical Instruments (DMIs) to different arch... Read More about Bespoke anywhere.

Automatic for the people: Crowd-driven generative scores using Manhattan and machine vision (2021)
Conference Proceeding
Nash, C. (2021). Automatic for the people: Crowd-driven generative scores using Manhattan and machine vision.

This paper details a workshop and optional public installation based on the development of situational scores that combine music notation, AI, and code to create dynamic interactive art driven by the realtime movements of objects and people in a live... Read More about Automatic for the people: Crowd-driven generative scores using Manhattan and machine vision.

Evolving Boolean regulatory networks with variable gene expression times (2021)
Book Chapter
Bull, L. (2021). Evolving Boolean regulatory networks with variable gene expression times. In Handbook of Unconventional Computing (247-259). World Scientific Publishing. https://doi.org/10.1142/9789811235726_0007

The time taken for gene expression varies not least because proteins vary in length considerably. This paper uses an abstract, tuneable Boolean regulatory network model to explore gene expression time variation. In particular, it is shown how non-uni... Read More about Evolving Boolean regulatory networks with variable gene expression times.

Analysing the effect of food supply chain traceability on product waste (2021)
Conference Proceeding
Glew, M. R., Perez Hernandez, M., & McFarlane, D. (2021). Analysing the effect of food supply chain traceability on product waste. In M. Fakhimi, T. Boness, & D. Robertson (Eds.), Proceedings of the Operational Research Society Simulation Workshop 2021 (SW21) (145-154)

This paper presents initial results from an agent-based simulation study into the impact of supply chain traceability information sharing on food waste reduction in the fresh food supply chain. Based on data collected during a 2019 study of a multi-t... Read More about Analysing the effect of food supply chain traceability on product waste.

Pandemic management with social media analytics (2021)
Book Chapter
Sabuncu, I., & Aydin, M. E. (2021). Pandemic management with social media analytics. In Data Science Advancements in Pandemic and Outbreak Management (78-107). IGI Global. https://doi.org/10.4018/978-1-7998-6736-4.ch005

Social media analytics appears as one of recently developing disciplines that helps understand public perception, reaction, and emerging developments. Particularly, pandemics are one of overwhelming phenomena that push public concerns and necessitate... Read More about Pandemic management with social media analytics.

The role of text analytics in healthcare: A review of recent developments and applications (2021)
Conference Proceeding
Elbattah, M., Arnaud, É., Gignon, M., & Dequen, G. (2021). The role of text analytics in healthcare: A review of recent developments and applications. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (825-832). https://doi.org/10.5220/0010414508250832

The implementation of Data Analytics has achieved a significant momentum across a very wide range of domains. Part of that progress is directly linked to the implementation of Text Analytics solutions. Organisations increasingly seek to harness the p... Read More about The role of text analytics in healthcare: A review of recent developments and applications.

Computer aided collaborative learning using cloud computing: Challenges and opportunities (2021)
Book Chapter
Malik, M., Sid Ahmed, A., & Hosseini, A. (2021). Computer aided collaborative learning using cloud computing: Challenges and opportunities. In S. L. Gupta, N. Kishor, N. Mishra, S. Mathur, & U. Gupta (Eds.), Digitalization of Higher Education using Cloud Computing. Taylor & Francis

This chapter discusses and explores computer aided collaborative learning, starting with an introduction to its method and theories. Bloom’s taxonomy and benefits to individuals and organisations are discussed. The study considers the available compu... Read More about Computer aided collaborative learning using cloud computing: Challenges and opportunities.

Modeling diseases with Stream X Machine (2021)
Conference Proceeding
Jayatilake, S., Ogunshile, E., Aydin, M., & Phung, K. (2021). Modeling diseases with Stream X Machine. In 2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT) (61-68). https://doi.org/10.1109/CONISOFT52520.2021.00020

At present the world is moving towards alternative medicine and behavioural alteration for treating, managing, and preventing chronical diseases. With the individuality of the human beings has added more complexity in a domain where very high accurac... Read More about Modeling diseases with Stream X Machine.

A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning (2021)
Conference Proceeding
Phung, K., Ogunshile, E., & Aydin, M. (2021). A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning. In 2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT) (168-179). https://doi.org/10.1109/CONISOFT52520.2021.00032

Software fault prediction makes software quality assurance process more efficient and economic. Most of the works related to software fault prediction have mainly focused on classifying software modules as faulty or not, which does not produce suffic... Read More about A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning.

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.

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.

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.

Fungal architectures (2021)
Exhibition / Performance
Nikolaidou, A., Adamatzky, A., Phillips, N., Roberts, N., & Petrova, I. Fungal architectures. [Installations, Prints]. 13 December 2021 - 19 December 2021. (Unpublished)

"Fungal architectures" arts exhibition presents works inspired by protocognition of fungi and slime moulds and fungal materials. Fungal Architectures is a new cross-disciplinary research project that seeks to develop a fully integrated structural and... Read More about Fungal architectures.