Outputs (154)

Modeling of uncertain nonlinear system with Z-numbers (2021)
Book Chapter
Jafari, R., Razvarz, S., Gegov, A., & Paul, S. (2021). Modeling of uncertain nonlinear system with Z-numbers. In Encyclopedia of Information Science and Technology (290-314). IGI Global. https://doi.org/10.4018/978-1-7998-3479-3.ch022

In order to model the fuzzy nonlinear systems, fuzzy equations with Z-number coefficients are used in this chapter. The modeling of fuzzy nonlinear systems is to obtain the Z-number coefficients of fuzzy equations. In this work, the neural network ap... Read More about Modeling of uncertain nonlinear system with Z-numbers.

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.

Vision based semantic runway segmentation from simulation with deep convolutional neural networks (2021)
Conference Proceeding
Quessy, A. D., Richardson, T. S., & Hansen, M. (2022). Vision based semantic runway segmentation from simulation with deep convolutional neural networks. https://doi.org/10.2514/6.2022-0680

Manned flight crew rely upon optical imagery to make sense of the world and carry out high level guidance, navigation & control tasks. To advance autonomous aircraft’s capabilities and safety, programmes need to be developed that aim to achieve pilot... Read More about Vision based semantic runway segmentation from simulation with deep convolutional neural networks.

Incremental motor skill learning and generalization from human dynamic reactions based on dynamic movement primitives and fuzzy logic system (2021)
Journal Article
Lu, Z., Wang, N., Li, M., & Yang, C. (2022). Incremental motor skill learning and generalization from human dynamic reactions based on dynamic movement primitives and fuzzy logic system. IEEE Transactions on Fuzzy Systems, 30(6), 1506-1515. https://doi.org/10.1109/tfuzz.2021.3136933

Different from previous work on single skill learning from human demonstrations, an incremental motor skill learning, generalization and control method based on dynamic movement primitives (DMP) and broad learning system (BLS) is proposed for extract... Read More about Incremental motor skill learning and generalization from human dynamic reactions based on dynamic movement primitives and fuzzy logic system.

Passive impedance sensing using a SAW resonator-coupled biosensor for zero-power wearable applications (2021)
Journal Article
Yue, X., Kiely, J., Luxton, R., Chen, B., McLeod, C. N., & Drakakis, E. M. (2022). Passive impedance sensing using a SAW resonator-coupled biosensor for zero-power wearable applications. IEEE Sensors Journal, 22(3), 2347-2357. https://doi.org/10.1109/JSEN.2021.3136705

A bio-sensing scheme, which acquires impedance information of a capacitive biosensor by using the reflected RF signal from a surface acoustic wave (SAW) resonator connected to the biosensor, is proposed. This technique requires no power to be supplie... Read More about Passive impedance sensing using a SAW resonator-coupled biosensor for zero-power wearable applications.

A hybrid artificial neural network and wavelet packet transform approach for fault location in hybrid transmission lines (2021)
Journal Article
Rezaee Ravesh, N., Ramezani, N., Ahmadi, I., & Nouri, H. (2022). A hybrid artificial neural network and wavelet packet transform approach for fault location in hybrid transmission lines. Electric Power Systems Research, 204, Article 107721. https://doi.org/10.1016/j.epsr.2021.107721

This paper presents a single-ended traveling-wave-based fault location (F.L.) method in a hybrid transmission line (HTL) with an overhead section combined with a cable section. For this, the software has been developed in a MATLAB programming environ... Read More about A hybrid artificial neural network and wavelet packet transform approach for fault location in hybrid transmission lines.

A novel curved gaussian mixture model and its application in motion skill encoding (2021)
Conference Proceeding
Chen, D., Li, G., Zhou, D., & Ju, Z. (2021). A novel curved gaussian mixture model and its application in motion skill encoding. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (7813-7818). https://doi.org/10.1109/IROS51168.2021.9636121

The purpose of this paper is to present a novel curved Gaussian Mixture Model (CGMM) and to study the application of it in motion skill encoding. Primarily, Gaussian mixture model (GMM) has been widely applied on many occasions when a probability den... Read More about A novel curved gaussian mixture model and its application in motion skill encoding.

Microbial fuel cell scale-up options: Performance evaluation of membrane (c-MFC) and membrane-less (s-MFC) systems under different feeding regimes (2021)
Journal Article
Walter, X. A., Madrid, E., Gajda, I., Greenman, J., & Ieropoulos, I. (2022). Microbial fuel cell scale-up options: Performance evaluation of membrane (c-MFC) and membrane-less (s-MFC) systems under different feeding regimes. Journal of Power Sources, 520, 230875. https://doi.org/10.1016/j.jpowsour.2021.230875

In recent years, bioelectrochemical systems have advanced towards upscaling applications and tested during field trials, primarily for wastewater treatment. Amongst reported trials, two designs of urine-fed microbial fuel cells (MFCs) were tested suc... Read More about Microbial fuel cell scale-up options: Performance evaluation of membrane (c-MFC) and membrane-less (s-MFC) systems under different feeding regimes.

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.

Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding (2021)
Journal Article
Pearson, M. J., Dora, S., Struckmeier, O., Knowles, T. C., Mitchinson, B., Tiwari, K., …Pennartz, C. M. (2021). Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding. Frontiers in Robotics and AI, 8, Article 732023. https://doi.org/10.3389/frobt.2021.732023

Recognising familiar places is a competence required in many engineering applications that interact with the real world such as robot navigation. Combining information from different sensory sources promotes robustness and accuracy of place recogniti... Read More about Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding.