Electrical spiking activity of proteinoids-ZnO colloids (2024)
Journal Article
Mougkogiannis, P., Raeisi Kheirabadi, N., Cholerio, A., & Adamatzky, A. (2024). Electrical spiking activity of proteinoids-ZnO colloids. Neuromorphic Computing and Engineering, 4(1), Article 014007. https://doi.org/10.1088/2634-4386/ad2afb

We are studying the remarkable electrical properties of Proteinoids-ZnO microspheres with the aim of exploring their potential for a new form of computing. Our research has revealed that these microspheres exhibit behavior similar to neurons, generat... Read More about Electrical spiking activity of proteinoids-ZnO colloids.

Reproducing "Show, attend and tell: Neural image caption generation with visual attention" (2023)
Journal Article
Liu, H., & Brailsford, T. (2023). Reproducing "Show, attend and tell: Neural image caption generation with visual attention". Journal of Physics: Conference Series, 2589(1), Article 012012. https://doi.org/10.1088/1742-6596/2589/1/012012

This paper replicates the experiment presented in the work of Xu et al. [1], and examines errors in the generated captions. The analysis of the identified errors aims to provide deeper insight into the underlying causes. This study also encompass... Read More about Reproducing "Show, attend and tell: Neural image caption generation with visual attention".

No ultrasounds detected from fungi when dehydrated (2023)
Journal Article
Phillips, N., Remedios, S. W., Nikolaidou, A., Baracskai, Z., & Adamatzky, A. (2023). No ultrasounds detected from fungi when dehydrated. Ultrasonics, 135, Article 107111. https://doi.org/10.1016/j.ultras.2023.107111

Many organisms (including certain plant species) can be observed to emit sounds, potentially signifying threat alerts. Sensitivity to such sounds and vibrations may also play an important role in the lives of fungi. In this work, we explore the poten... Read More about No ultrasounds detected from fungi when dehydrated.

Computer vision and IoT research landscape for health and safety management on construction sites (2023)
Journal Article
Arshad, S., Akinade, O., Bello, S., & Bilal, M. (2023). Computer vision and IoT research landscape for health and safety management on construction sites. Journal of Building Engineering, 76, Article 107049. https://doi.org/10.1016/j.jobe.2023.107049

Aims: Perform a systematic review of current literature to evaluate and summarise the health and safety hazards on construction sites. Methods: Science Direct, SCOPUS and web of science databases were searched for research articles published from 201... Read More about Computer vision and IoT research landscape for health and safety management on construction sites.

Error-type -A novel set of software metrics for software fault prediction (2023)
Journal Article
Phung, K., Ogunshile, E., & Aydin, M. (2023). Error-type -A novel set of software metrics for software fault prediction. IEEE Access, 11, 30562-30574. https://doi.org/10.1109/ACCESS.2023.3262411

In software development, identifying software faults is an important task. The presence of faults not only reduces the quality of the software, but also increases the cost of development life cycle. Fault identification can be performed by analysing... Read More about Error-type -A novel set of software metrics for software fault prediction.

Personalised learning through context-based adaptation in the serious games with gating mechanism (2023)
Journal Article
Shum, L. C., Rosunally, Y., Scarle, S., & Munir, K. (2023). Personalised learning through context-based adaptation in the serious games with gating mechanism. Education and Information Technologies, 28(10), 13077-13108. https://doi.org/10.1007/s10639-023-11695-8

When the traditional "one size fits all" approach is used in designing educational games, the game context is usually arranged in a fixed sequence. However, the designated content may not effectively support the diversity of players. The player's abi... Read More about Personalised learning through context-based adaptation in the serious games with gating mechanism.

The nonequilibrium potential today: A short review (2022)
Journal Article
Wio, H. S., Deza, J. I., Sánchez, A. D., García-García, R., Gallego, R., Revelli, J. A., & Deza, R. R. (2022). The nonequilibrium potential today: A short review. Chaos, Solitons and Fractals, 165(Part 1), 112778. https://doi.org/10.1016/j.chaos.2022.112778

A brief review is made of the birth and evolution of the “nonequilibrium potential” (NEP) concept. As if providing a landscape for qualitative reasoning were not helpful enough, the NEP adds a quantitative dimension to the qualitative theory of diffe... Read More about The nonequilibrium potential today: A short review.

An energy-aware and Q-learning-based area coverage for oil pipeline monitoring systems using sensors and Internet of Things (2022)
Journal Article
Rahmani, A. M., Ali, S., Malik, M. H., Yousefpoor, E., Yousefpoor, M. S., Mousavi, A., …Hosseinzadeh, M. (2022). An energy-aware and Q-learning-based area coverage for oil pipeline monitoring systems using sensors and Internet of Things. Scientific Reports, 12(1), https://doi.org/10.1038/s41598-022-12181-w

Pipelines are the safest tools for transporting oil and gas. However, the environmental effects and sabotage of hostile people cause corrosion and decay of pipelines, which bring financial and environmental damages. Today, new technologies such as th... Read More about An energy-aware and Q-learning-based area coverage for oil pipeline monitoring systems using sensors and Internet of Things.

Chlorella sensors in liquid marbles and droplets (2022)
Journal Article
Phillips, N., Mayne, R., & Adamatzky, A. (2022). Chlorella sensors in liquid marbles and droplets. Sensing and Bio-Sensing Research, 36, Article 100491. https://doi.org/10.1016/j.sbsr.2022.100491

The use of live organisms in electrically-coupled sensing devices has been suggested as an alternative low-cost, low-environmental footprint and robust technology for continuous monitoring and sensing applications. The utility of Chlorella vulgaris a... Read More about Chlorella sensors in liquid marbles and droplets.

Variational restricted Boltzmann machines to automated anomaly detection (2022)
Journal Article
Demertzis, K., Iliadis, L., Pimenidis, E., & Kikiras, P. (2022). Variational restricted Boltzmann machines to automated anomaly detection. Neural Computing and Applications, 34, 15207–15220. https://doi.org/10.1007/s00521-022-07060-4

Data-driven methods are implemented using particularly complex scenarios that reflect in-depth perennial knowledge and research. Hence, the available intelligent algorithms are completely dependent on the quality of the available data. This is not po... Read More about Variational restricted Boltzmann machines to automated anomaly detection.

Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue (2022)
Journal Article
Duran, N., Battle, S., & Smith, J. (2022). Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue. Communication Methods and Measures, 16(3), 182-214. https://doi.org/10.1080/19312458.2021.2020229

We present the Conversation Analysis Modeling Schema (CAMS), a novel dialogue labeling schema that combines the Conversation Analysis concept of Adjacency Pairs, with Dialogue Acts. The aim is to capture both the semantic and syntactic structure of d... Read More about Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue.

Marimo actuated rover systems (2022)
Journal Article
Phillips, N., Draper, T. C., Mayne, R., Reynolds, D. M., & Adamatzky, A. (2022). Marimo actuated rover systems. Journal of Biological Engineering, 16(1), Article 3. https://doi.org/10.1186/s13036-021-00279-0

Background: The potential to directly harness photosynthesis to make actuators, biosensors and bioprocessors has been previously demonstrated in the literature. Herein, this capability has been expanded to more advanced systems — Marimo Actuated Rove... Read More about Marimo actuated rover systems.

Machine learning activation energies of chemical reactions (2021)
Journal Article
Lewis-Atwell, T., Townsend, P. A., & Grayson, M. N. (2022). Machine learning activation energies of chemical reactions. Wiley Interdisciplinary Reviews: Computational Molecular Science, 12(4), e1593. https://doi.org/10.1002/wcms.1593

Application of machine learning (ML) to the prediction of reaction activation barriers is a new and exciting field for these algorithms. The works covered here are specifically those in which ML is trained to predict the activation energies of homoge... Read More about Machine learning activation energies of chemical reactions.

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.

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.

Precision fibre angle inspection for carbon fibre composite structures using polarisation vision (2021)
Journal Article
Atkinson, G., O'Hara Nash, S., & Smith, L. (2021). Precision fibre angle inspection for carbon fibre composite structures using polarisation vision. Electronics, 10(22), Article 2765. https://doi.org/10.3390/electronics10222765

This paper evaluates the precision of polarisation imaging technology for the inspection of carbon fibre composite components. Specifically, it assesses the feasibility of the technology for fibre orientation measurements based on the premise that li... Read More about Precision fibre angle inspection for carbon fibre composite structures using polarisation vision.

Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting (2021)
Journal Article
Barrera Animas, A., Oladayo Oyedele, L., Bilal, M., Dolapo Akinosho, T., Davila Delgado, J. M., & Adewale Akanbi, L. (2022). Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting. Machine Learning with Applications, 7, Article 100204. https://doi.org/10.1016/j.mlwa.2021.100204

Rainfall forecasting has gained utmost research relevance in recent times due to its complexities and persistent applications such as flood forecasting and monitoring of pollutant concentration levels, among others. Existing models use complex statis... Read More about Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting.

Sentence encoding for dialogue act classification (2021)
Journal Article
Duran, N., Battle, S., & Smith, J. (2023). Sentence encoding for dialogue act classification. Natural Language Engineering, 29(3), 794-823. https://doi.org/10.1017/S1351324921000310

In this study, we investigate the process of generating single-sentence representations for the purpose of Dialogue Act (DA) classification, including several aspects of text pre-processing and input representation which are often overlooked or under... Read More about Sentence encoding for dialogue act classification.

Adaptive operator selection with reinforcement learning (2021)
Journal Article
Durgut, R., Aydin, M. E., & Atli, I. (2021). Adaptive operator selection with reinforcement learning. Information Sciences, 581, 773-790. https://doi.org/10.1016/j.ins.2021.10.025

Operator selection plays a crucial role in the efficiency of heuristic-based problem solving algorithms, especially, when a pool of operators is used to let algorithms dynamically select operators to produce new candidate solutions. A sequence of sel... Read More about Adaptive operator selection with reinforcement learning.