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Outputs (42)

Users’ experiences of enhancing underwater images: An empirical study (2021)
Journal Article
Emberton, S., & Simons, C. (2021). Users’ experiences of enhancing underwater images: An empirical study. Quality and User Experience, 7(1), Article 1. https://doi.org/10.1007/s41233-021-00048-3

Within the worldwide diving community, underwater photography is becoming increasingly popular. However, the marine environment presents certain challenges for image capture, with resulting imagery often suffering from colour distortions, low contras... Read More about Users’ experiences of enhancing underwater images: An empirical study.

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.

A metaheuristic search framework to derive Cancer Care Services from business process models (2019)
Conference Proceeding
Aljawawdeh, H., Odeh, M., Simons, C., & Lebzo, N. (2019). A metaheuristic search framework to derive Cancer Care Services from business process models. In Proceedings - 2018 1st International Conference on Cancer Care Informatics (CCI) (142-151). https://doi.org/10.1109/CANCERCARE.2018.8618153

Cancer Care involves not only handling patients' medical or physical needs but also other services to facilitate patient needs which are underpinned by appropriate software systems that assist in patient care processes. The Service-Oriented Architect... Read More about A metaheuristic search framework to derive Cancer Care Services from business process models.

Beneficial role of humans and AI in a machine learning age of the Telco ecosystem (2018)
Presentation / Conference
Cassidy, S., Perrett, J., & Simons, C. (2018, May). Beneficial role of humans and AI in a machine learning age of the Telco ecosystem. Paper presented at TM Forum Digital Transformation World, Nice, France

The adoption of new technology in the telecommunications industry raises challenges, particularly when exploiting advances in artificial intelligence (AI) (e.g. dynamic optimisation and machine learning). Indeed, opinions have been expressed that AI... Read More about Beneficial role of humans and AI in a machine learning age of the Telco ecosystem.

Simply the best: Optimising with an evolutionary computing framework (2018)
Presentation / Conference
Buontempo, F., & Simons, C. (2018, April). Simply the best: Optimising with an evolutionary computing framework. Presented at Annual Conference of Association of C and C++ Users 2018 (ACCU 2018), Bristol, UK

These are the slides of the interactive programming workshop on optimising with an evolutionary computing framework at ACCU 2018. Java Class Library for Evolutionary Computing (JCLEC) is used as the example framework. Example optimisation problems in... Read More about Simply the best: Optimising with an evolutionary computing framework.

A systematic review of interaction in search-based software engineering (2018)
Journal Article
Ramirez, A., Romero, J. R., & Simons, C. (2019). A systematic review of interaction in search-based software engineering. IEEE Transactions on Software Engineering, 45(8), 760-781. https://doi.org/10.1109/TSE.2018.2803055

IEEE Search-Based Software Engineering (SBSE) has been successfully applied to automate a wide range of software development activities. Nevertheless, in those software engineering problems where human evaluation and preference are crucial, such insi... Read More about A systematic review of interaction in search-based software engineering.

Evolutionary computing frameworks for optimisation (2017)
Journal Article
Simons, C., & Ramirez, A. (2017). Evolutionary computing frameworks for optimisation

Evolutionary algorithms can find optimal solutions to problems. This article gives an overview of some programming frameworks available to solve optimisation problems.

Metaheuristic design patterns - new perspectives for larger-scale search architectures (2017)
Book Chapter
Krawiec, K., Simons, C., Swan, J., & Woodward, J. (2017). Metaheuristic design patterns - new perspectives for larger-scale search architectures. In P. Vasant, S. Z. Alparslan-Gok, & G. Weber (Eds.), Handbook of Research on Emergent Applications of Optimization Algorithms (1-36). IGI Global Publishing. https://doi.org/10.4018/978-1-5225-2990-3.ch001

Design patterns capture the essentials of recurring best practice in an abstract form. Their merits are well established in domains as diverse as architecture and software development. They offer significant benefits, not least a common conceptual... Read More about Metaheuristic design patterns - new perspectives for larger-scale search architectures.

Evolutionary computing frameworks for optimisation (2017)
Presentation / Conference
Ramirez, A., & Simons, C. (2017, September). Evolutionary computing frameworks for optimisation. Presented at Meeting of Bristol Branch of the Association of C and C++ Users (ACCU), Bristol, UK

Presentation on frameworks for optimisation using evolutionary computing.