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All Outputs (161)

Federated Learning for Short-term Residential Load Forecasting (2022)
Journal Article
Briggs, C., Fan, Z., & Andras, P. (2022). Federated Learning for Short-term Residential Load Forecasting. IEEE Open Access Journal of Power and Energy, 9, 573-583. https://doi.org/10.1109/oajpe.2022.3206220

Load forecasting is an essential task performed within the energy industry to help balance supply with demand and maintain a stable load on the electricity grid. As supply transitions towards less reliable renewable energy generation, smart meters wi... Read More about Federated Learning for Short-term Residential Load Forecasting.

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, M. Crişan-Vida, E. Zoulias, & O. Sorina Chirila (Eds.), Public Health and Informatics (504-505). IOS Press. https://doi.org/10.3233/SHTI210216

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.

Compounding barriers to fairness in the digital technology ecosystem (2021)
Presentation / Conference Contribution
Woolley, S. I., Collins, T., Andras, P., Gardner, A., Ortolani, M., & Pitt, J. (2021, October). Compounding barriers to fairness in the digital technology ecosystem. Presented at 2021 IEEE International Symposium on Technology and Society (ISTAS), Waterloo, ON, Canada

A growing sense of unfairness permeates our quasi-digital society. Despite drivers supporting and motivating ethical practice in the digital technology ecosystem, there are compounding barriers to fairness that, at every level, impact technology inno... Read More about Compounding barriers to fairness in the digital technology ecosystem.

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). Springer. https://doi.org/10.1007/978-3-030-70604-3_2

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.

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?.

Federated Learning for Short-term Residential Energy Demand Forecasting (2021)
Preprint / Working Paper
Briggs, C., Fan, Z., & Andras, P. (2021). Federated Learning for Short-term Residential Energy Demand Forecasting

Energy demand forecasting is an essential task performed within the energy industry to help balance supply with demand and maintain a stable load on the electricity grid. As supply transitions towards less reliable renewable energy generation, smart... Read More about Federated Learning for Short-term Residential Energy Demand Forecasting.

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.

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, July). Federated learning with hierarchical clustering of local updates to improve training on non-IID data. Presented at 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow

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.

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.

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.

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.

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.

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.

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.

Measuring and testing the scalability of cloud-based software services (2019)
Presentation / Conference Contribution
Al-Said Ahmad, A., & Andras, P. (2018, October). Measuring and testing the scalability of cloud-based software services. Presented at 2018 Fifth International Symposium on Innovation in Information and Communication Technology (ISIICT), Amman, Jordan

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.

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.

Social learning and cultural evolution in artificial life (2018)
Journal Article
Marriott, C., Borg, J. M., Andras, P., & Smaldino, P. E. (2018). Social learning and cultural evolution in artificial life. Artificial Life, 24(1), 5-9. https://doi.org/10.1162/ARTL_a_00250

We describe the questions and discussions raised at the First Workshop on Social Learning and Cultural Evolution held at theArtificial Life Conference 2016 in Cancún, Mexico in July 2016. The purpose of the workshop was to assemble artificial life re... Read More about Social learning and cultural evolution in artificial life.

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.

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.

Reproducibility in machine Learning-Based studies: An example of text mining (2017)
Presentation / Conference Contribution
Olorisade, B. K., Brereton, P., & Andras, P. (2017). Reproducibility in machine Learning-Based studies: An example of text mining. In ICML 2017 RML Workshop: Reproducibility in Machine Learning

Reproducibility is an essential requirement for computational studies including those based on machine learning techniques. However, many machine learning studies are either not reproducible or are difficult to reproduce. In this paper, we consider... Read More about Reproducibility in machine Learning-Based studies: An example of text mining.