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Outputs (99)

An Entity Ontology-Based Knowledge Graph Embedding Approach to News Credibility Assessment (2024)
Journal Article
Liu, Q., Jin, Y., Cao, X., Liu, X., Zhou, X., Zhang, Y., Xu, X., & Qi, L. (online). An Entity Ontology-Based Knowledge Graph Embedding Approach to News Credibility Assessment. IEEE Transactions on Computational Social Systems, https://doi.org/10.1109/TCSS

Fake news is a prevalent issue in modern society, leading to misinformation and societal harm. News credibility assessment is a crucial approach for evaluating the accuracy and authenticity of news. It plays a significant role in enhancing public awa... Read More about An Entity Ontology-Based Knowledge Graph Embedding Approach to News Credibility Assessment.

Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms (2024)
Journal Article
Mantovani, R. G., Horváth, T., Rossi, A. L. D., Cerri, R., Barbon Junior, S., Vanschoren, J., & de Carvalho, A. C. P. L. F. (2024). Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms. Data Minin

Machine learning algorithms often contain many hyperparameters whose values affect the predictive performance of the induced models in intricate ways. Due to the high number of possibilities for these hyperparameter configurations and their complex i... Read More about Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms.

Extending AGADE Traffic To Simulate Auctions In Shared Mobility Services (2023)
Presentation / Conference Contribution
Nguyen, J., Powers, S., Urquhart, N., Eckerle, D., Farrenkopf, T., & Guckert, M. (2023, June). Extending AGADE Traffic To Simulate Auctions In Shared Mobility Services. Presented at 37th ECMS International Conference on Modelling and Simulation, Florence,

With the number of individual vehicles meeting the capacity limit of urban road infrastructure, the deployment of new mobility services may help to achieve more efficient use of available resources and prevent critical overload. It may be observed th... Read More about Extending AGADE Traffic To Simulate Auctions In Shared Mobility Services.

Towards individualised speech enhancement: An SNR preference learning system for multi-modal hearing aids (2023)
Presentation / Conference Contribution
Kirton-Wingate, J., Ahmed, S., Gogate, M., Tsao, Y., & Hussain, A. (2023, June). Towards individualised speech enhancement: An SNR preference learning system for multi-modal hearing aids. Presented at 2023 IEEE International Conference on Acoustics, Speec

Since the advent of deep learning (DL), speech enhancement (SE) models have performed well under a variety of noise conditions. However, such systems may still introduce sonic artefacts, sound unnatural, and restrict the ability for a user to hear am... Read More about Towards individualised speech enhancement: An SNR preference learning system for multi-modal hearing aids.

A review of privacy-preserving federated learning for the Internet-of-Things (2021)
Book Chapter
Briggs, C., Fan, Z., & Andras, P. (2021). A review of privacy-preserving federated learning for the Internet-of-Things. In M. Habib ur Rehman, & M. Medhat Gaber (Eds.), Federated Learning Systems: Towards Next-Generation AI (21-50). Cham: Springer. https:

The Internet-of-Things (IoT) generates vast quantities of data. Much of this data is attributable to human activities and behavior. Collecting personal data and executing machine learning tasks on this data in a central location presents a significan... Read More about A review of privacy-preserving federated learning for the Internet-of-Things.

Scalability analysis comparisons of cloud-based software services (2019)
Journal Article
Ahmad, A. A., & Andras, P. (2019). Scalability analysis comparisons of cloud-based software services. Journal of cloud computing: advances, systems and applications, 8, Article 10. https://doi.org/10.1186/s13677-019-0134-y

Performance and scalability testing and measurements of cloud-based software services are necessary for future optimizations and growth of cloud computing. Scalability, elasticity, and efficiency are interrelated aspects of cloud-based software servi... Read More about Scalability analysis comparisons of cloud-based software services.

Cooperation in Repeated Rock-Paper-Scissors Games in Uncertain Environments (2018)
Presentation / Conference Contribution
Andras, P. (2018). Cooperation in Repeated Rock-Paper-Scissors Games in Uncertain Environments. In ALIFE 2018: The 2018 Conference on Artificial Life (404-411). https://doi.org/10.1162/isal_a_00078

Cooperation among selfish individuals provides the fundamentals for social organization among animals and humans. Cooperation games capture this behavior at an abstract level and provide the tools for the analysis of the evolution of cooperation. Her... Read More about Cooperation in Repeated Rock-Paper-Scissors Games in Uncertain Environments.

Cloud-based software services delivery from the perspective of scalability (2019)
Journal Article
Al-Said Ahmad, A., & Andras, P. (2021). Cloud-based software services delivery from the perspective of scalability. International Journal of Parallel, Emergent and Distributed Systems, 36(2), 53-68. https://doi.org/10.1080/17445760.2019.1617864

Measuring and testing the scalability and performance of cloud-based software services is critical for the delivery of such services, and the development of cloud computing. There are three interconnected Cloud-based software services’ performance as... Read More about Cloud-based software services delivery from the perspective of scalability.

Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters (2020)
Presentation / Conference Contribution
Briggs, C., Fan, Z., & Andras, P. (2020). Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters. In NeurIPS 2020 Workshop: Tackling Climate Change with Machine Learning

In this proposal paper we highlight the need for privacy preserving energy demand forecasting to allay a major concern consumers have about smart meter installations. High resolution smart meter data can expose many private aspects of a consumer’s ho... Read More about Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters.

User perception of Bitcoin usability and security across novice users (2019)
Journal Article
Alshamsi, A., & Andras, P. (2019). User perception of Bitcoin usability and security across novice users. International Journal of Human-Computer Studies, 126, 94-110. https://doi.org/10.1016/j.ijhcs.2019.02.004

This paper investigates users’ perceptions and experiences of an anonymous digital payment system (Bitcoin) and its influence on users in terms of usability and security in comparison to other non-anonymous payment systems such as credit/debit cards.... Read More about User perception of Bitcoin usability and security across novice users.

Where do successful populations originate from? (2021)
Journal Article
Andras, P., & Stanton, A. (2021). Where do successful populations originate from?. Journal of Theoretical Biology, 524, Article 110734. https://doi.org/10.1016/j.jtbi.2021.110734

In order to understand the dynamics of emergence and spreading of socio-technical innovations and population moves it is important to determine the place of origin of these populations. Here we focus on the role of geographical factors, such as land... Read More about Where do successful populations originate from?.

The use of bibliography enriched features for automatic citation screening (2019)
Journal Article
Olorisade, B. K., Brereton, P., & Andras, P. (2019). The use of bibliography enriched features for automatic citation screening. Journal of Biomedical Informatics, 94, Article 103202. https://doi.org/10.1016/j.jbi.2019.103202

Context Citation screening (also called study selection) is a phase of systematic review process that has attracted a growing interest on the use of text mining (TM) methods to support it to reduce time and effort. Search results are usually imbalan... Read More about The use of bibliography enriched features for automatic citation screening.

Leveraging the Cloud for Large-Scale Software Testing: A Case Study ‑ Google Chrome on Amazon (2014)
Book Chapter
Pakhira, A., & Andras, P. (2014). Leveraging the Cloud for Large-Scale Software Testing: A Case Study ‑ Google Chrome on Amazon. In Cloud Technology: Concepts, Methodologies, Tools, and Applications. IGI Global. https://doi.org/10.4018/978-1-4666-6539-

Testing is a critical phase in the software life-cycle. While small-scale component-wise testing is done routinely as part of development and maintenance of large-scale software, the system level testing of the whole software is much more problematic... Read More about Leveraging the Cloud for Large-Scale Software Testing: A Case Study ‑ Google Chrome on Amazon.

Social learning in repeated cooperation games in uncertain environments (2018)
Journal Article
Andras, P. (2018). Social learning in repeated cooperation games in uncertain environments. Cognitive Systems Research, 51, 24-39. https://doi.org/10.1016/j.cogsys.2018.04.013

Cooperation and social learning are fundamental mechanisms that maintain social organisation among animals and humans. Social institutions can be conceptualised abstractly as cooperation games with social learning. In some cases potential cooperation... Read More about Social learning in repeated cooperation games in uncertain environments.

Measuring and testing the scalability of cloud-based software services (2019)
Presentation / Conference Contribution
Al-Said Ahmad, A., & Andras, P. (2019). Measuring and testing the scalability of cloud-based software services. In 2018 Fifth International Symposium on Innovation in Information and Communication Technology (ISIICT) (67-74). https://doi.org/10.1109/ISII

Performance and scalability testing and measurements of cloud-based software services are critically important in the context of rapid growth of cloud computing and supporting the delivery of these services. Cloud-based software services performance... Read More about Measuring and testing the scalability of cloud-based software services.

Environmental Harshness and Fitness Improving Innovations (2019)
Presentation / Conference Contribution
Andras, P. (2019). Environmental Harshness and Fitness Improving Innovations. In Artificial Life Conference Proceedings (300-307). https://doi.org/10.1162/isal_a_00179

Fitness improving innovations occur in populations of organisms as genetic changes (mutations) that allow better fit with the environmental niche of the organisms. Similarly, fitness improving innovations may occur in the context of human communities... Read More about Environmental Harshness and Fitness Improving Innovations.

Random projection neural network approximation (2018)
Presentation / Conference Contribution
Andras, P. (2018). Random projection neural network approximation. In 2018 International Joint Conference on Neural Networks (IJCNN) (1-8). https://doi.org/10.1109/IJCNN.2018.8489215

Neural networks are often used to approximate functions defined over high-dimensional data spaces (e.g. text data, genomic data, multi-sensor data). Such approximation tasks are usually difficult due to the curse of dimensionality and improved method... Read More about Random projection neural network approximation.

Composition of Games as a Model for the Evolution of Social Institutions (2020)
Presentation / Conference Contribution
Andras, P. (2020). Composition of Games as a Model for the Evolution of Social Institutions. In Artificial Life Conference Proceedings (171-179). https://doi.org/10.1162/isal_a_00264

The evolution of social institutions (e.g. institutions of political decision making or joint resource administration) is an important question in the context of understanding of how societies develop and evolve. In principle, social institutions can... Read More about Composition of Games as a Model for the Evolution of Social Institutions.

Federated learning with hierarchical clustering of local updates to improve training on non-IID data (2020)
Presentation / Conference Contribution
Briggs, C., Fan, Z., & Andras, P. (2020). Federated learning with hierarchical clustering of local updates to improve training on non-IID data. In 2020 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/IJCNN48605.2020.920

Federated learning (FL) is a well established method for performing machine learning tasks over massively distributed data. However in settings where data is distributed in a non-iid (not independent and identically distributed) fashion - as is typic... Read More about Federated learning with hierarchical clustering of local updates to improve training on non-IID data.

A Preliminary Scoping Study of Federated Learning for the Internet of Medical Things (2021)
Book Chapter
Farhad, A., Woolley, S. I., & Andras, P. (2021). A Preliminary Scoping Study of Federated Learning for the Internet of Medical Things. In J. Mantas, L. Stoicu-Tivadar, C. Chronaki, A. Hasman, P. Weber, P. Gallos, …O. Sorina Chirila (Eds.), Public Health

This paper presents a scoping review of federated learning for the Internet of Medical Things (IoMT) and demonstrates the limited amount of research work in an area which has potential to improve patient care. Federated Learning and IoMT – as standal... Read More about A Preliminary Scoping Study of Federated Learning for the Internet of Medical Things.