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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.

Unsupervised one-class learning for anomaly detection on home IoT network devices (2021)
Conference Proceeding
White, J., & Legg, P. (in press). Unsupervised one-class learning for anomaly detection on home IoT network devices. In 2021 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA)https://doi.org/10.1109/CyberSA52016.2021.9478248

In this paper we study anomaly detection methods for home IoT devices. Specifically, we address unsupervised one-class learning methods due to their ability to learn deviations from a single normal class. In a home IoT environment, this consideration... Read More about Unsupervised one-class learning for anomaly detection on home IoT network devices.

Proceedings of the 22nd Engineering Applications of Neural Networks Conference: EANN 2021 (2021)
Book
Iliadis, L., Macintyre, J., Jayne, C., & Pimenidis, E. (Eds.). (2021). Proceedings of the 22nd Engineering Applications of Neural Networks Conference: EANN 2021. Springer. https://doi.org/10.1007/978-3-030-80568-5

This book contains the proceedings of the 22nd EANN “Engineering Applications of Neural Networks” 2021 that comprise of research papers on both theoretical foundations and cutting-edge applications of artificial intelligence. Based on the discussed r... Read More about Proceedings of the 22nd Engineering Applications of Neural Networks Conference: EANN 2021.

Federated blockchained supply chain management: A cybersecurity and privacy framework (2021)
Conference Proceeding
Demertzis, K., Iliadis, L., Pimenidis, E., Tziritas, N., Koziri, M., Kikiras, P., & Tonkin, M. (2021). Federated blockchained supply chain management: A cybersecurity and privacy framework. In Artificial Intelligence Applications and Innovations https://doi.org/10.1007/978-3-030-79150-6_60

The complete transformation of the supply chain in a truly integrated and fully automated process, presupposes the continuous and endless collection of digital information from every stage of the production scale. The aim is not only to investigate t... Read More about Federated blockchained supply chain management: A cybersecurity and privacy framework.

Geo-AI to aid disaster response by memory-augmented deep reservoir computing (2021)
Journal Article
Demertzis, K., Iliadis, L., & Pimenidis, E. (in press). Geo-AI to aid disaster response by memory-augmented deep reservoir computing. Integrated Computer-Aided Engineering, https://doi.org/10.3233/ICA-210657

It is a fact that natural disasters often cause severe damage both to ecosystems and humans. Moreover, man-made disasters can have enormous moral and economic consequences for people. A typical example is the large deadly and catastrophic explosion i... Read More about Geo-AI to aid disaster response by memory-augmented deep reservoir computing.

Genre analysis of movies using a topic model of plot summaries (2021)
Journal Article
Matthews, P., & Glitre, K. (in press). Genre analysis of movies using a topic model of plot summaries. Journal of the Association for Information Science and Technology, https://doi.org/10.1002/asi.24525

Genre plays an important role in the description, navigation, and discovery of movies, but it is rarely studied at large scale using quantitative methods. This allows an analysis of how genre labels are applied, how genres are composed and how these... Read More about Genre analysis of movies using a topic model of plot summaries.

Blockchain and artificial intelligence -Managing a secure and sustainable supply chain (2021)
Conference Proceeding
Pimenidis, E., Patsavellas, J., & Tonkin, M. (2021). Blockchain and artificial intelligence -Managing a secure and sustainable supply chain. In Cybersecurity, Privacy and Freedom Protection in the Connected World (367-377). https://doi.org/10.1007/978-3-030-68534-8_23

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

Autoencoding with a classifier system (2021)
Journal Article
Preen, R. J., Wilson, S. W., & Bull, L. (in press). Autoencoding with a classifier system. IEEE Transactions on Evolutionary Computation, https://doi.org/10.1109/TEVC.2021.3079320

Autoencoders are data-specific compression algorithms learned automatically from examples. The predominant approach has been to construct single large global models that cover the domain. However, training and evaluating models of increasing size com... Read More about Autoencoding with a classifier system.

Evolving Boolean regulatory networks with variable gene expression times (2021)
Book Chapter
Bull, L. (in press). Evolving Boolean regulatory networks with variable gene expression times. In Handbook of Unconventional Computing (246-258). Springer

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.

Blockchained Αdaptive Federated Auto Meta Learning Big Data and DevOps CyberSecurity Architecture in Industry 4.0 (2021)
Conference Proceeding
Kikiras, P., Koziri, M., Tziritas, N., Pimenidis, E., Iliadis, L., & Demertzis, K. (in press). Blockchained Αdaptive Federated Auto Meta Learning Big Data and DevOps CyberSecurity Architecture in Industry 4.0

Maximizing the production process in modern industry, as proposed by Industry 4.0, requires extensive use of Cyber-Physical Systems (CbPS). Artificial intelligence technologies, through CbPS, allow monitoring of natural processes , making autonomous,... Read More about Blockchained Αdaptive Federated Auto Meta Learning Big Data and DevOps CyberSecurity Architecture in Industry 4.0.

Recommender systems algorithm selection using machine learning (2021)
Conference Proceeding
Pimenidis, E., Kapetanakis, S., & Polatidis, N. (in press). Recommender systems algorithm selection using machine learning

This article delivers a methodology for recommender system algorithm selection using a machine learning classifier. Initially, statistical data from real collaborative filtering recommender systems have been collected to form the basis for a syntheti... Read More about Recommender systems algorithm selection using machine learning.

"Hacking an IoT Home": New opportunities for cyber security education combining remote learning with cyber-physical systems (2021)
Conference Proceeding
Johnson, I., White, J., Spruhan, P., Higgs, T., & Legg, P. (in press). "Hacking an IoT Home": New opportunities for cyber security education combining remote learning with cyber-physical systems

In March 2020, the COVID-19 pandemic led to a dramatic shift in educational practice, whereby home-schooling and remote working became the norm. Many typical schools outreach projects to encourage uptake of learning cyber security skills therefore we... Read More about "Hacking an IoT Home": New opportunities for cyber security education combining remote learning with cyber-physical systems.

Protein structured reservoir computing for spike-based pattern recognition (2021)
Journal Article
Adamatzky, A., Smith, J., Sirakoulis, G. C., & Tsakalos, K. A. (in press). Protein structured reservoir computing for spike-based pattern recognition. IEEE Transactions on Parallel and Distributed Systems, XX, https://doi.org/10.1109/TPDS.2021.3068826

Nowadays we witness a miniaturisation trend in the semiconductor industry backed up by groundbreaking discoveries and designs in nanoscale characterisation and fabrication. To facilitate the trend and produce ever smaller, faster and cheaper computin... Read More about Protein structured reservoir computing for spike-based pattern recognition.

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

Audio Anywhere with Faust (2020)
Conference Proceeding
Gaster, B. R., & Cole, M. (2020). Audio Anywhere with Faust

This paper introduces \emph{Audio Anywhere} (\emph{AA}), a framework for working with audio plugins that are compiled once and run anywhere. At the heart of Audio Anywhere is an audio engine whose Digital Signal Processing (DSP) components are writte... Read More about Audio Anywhere with Faust.

The natural connectivity of autonomous systems (2020)
Journal Article
Battle, S. (2020). The natural connectivity of autonomous systems. Rivista Italiana di Filosofia del Linguaggio, 14(2), 1-16. https://doi.org/10.4396/AISB201901

The principle of biological autonomy, introduced by Francisco J. Varela, addresses the dilemma of Cartesian mind-body dualism by re-casting mind and body, or subject and object, observer and observed, not as irreconcilable categories, but as compleme... Read More about The natural connectivity of autonomous systems.

Using active learning to understand the videoconference experience: A case study (2020)
Conference Proceeding
Llewellyn, S., Simons, C., & Smith, J. (2020). Using active learning to understand the videoconference experience: A case study. https://doi.org/10.1007/978-3-030-63799-6_30

Videoconferencing is becoming ubiquitous, especially so during the COVID-19 pandemic. However, user experience of a videoconference call can be variable. To better understand and classify the performance of videoconference call systems, this paper re... Read More about Using active learning to understand the videoconference experience: A case study.

PlayShell: A low-cost, fun audio experience for heritage centres (2020)
Conference Proceeding
Goddard, P., & Gaster, B. R. (2020). PlayShell: A low-cost, fun audio experience for heritage centres. In Proceedings of the 15th International Conference on Audio Mostly. , (237-240). https://doi.org/10.1145/3411109.3411132

Various barriers prevent blind and visually impaired people accessing the rich multisensory experiences available at heritage centres. These barriers include large bodies of text and items in glass cases, which are difficult to see. Feedback from the... Read More about PlayShell: A low-cost, fun audio experience for heritage centres.

Cardiff University at SemEval-2020 Task 6: Fine-tuning BERT for Domain-Specific Definition Classification (2020)
Conference Proceeding
Jeawak, S. S., Espinosa-Anke, L., & Schockaert, S. (2020). Cardiff University at SemEval-2020 Task 6: Fine-tuning BERT for Domain-Specific Definition Classification. In Proceedings of the Fourteenth Workshop on Semantic Evaluation. , (361-366)

We describe the system submitted to SemEval-2020 Task 6, Subtask 1. The aim of this subtask is to predict whether a given sentence contains a definition or not. Unsurprisingly, we found that strong results can be achieved by fine-tuning a pre-trained... Read More about Cardiff University at SemEval-2020 Task 6: Fine-tuning BERT for Domain-Specific Definition Classification.

Automated screening of patients for dietician referral (2020)
Conference Proceeding
Soomro, K., & Pimenidis, E. (2020). Automated screening of patients for dietician referral. In L. Iliadis, P. Angelov, C. Jayne, & E. Pimenidis (Eds.), Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference. https://doi.org/10.1007/978-3-030-48791-1_24

Critical Care Units (CCU) in a hospital treat the severely sick patients that need constant monitoring and close medical attention. Feeding patients, enteral feeding in particular, is a critical and continuous process. Monitoring patients, managing t... Read More about Automated screening of patients for dietician referral.