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Visual analytics for collaborative human-machine confidence in human-centric active learning tasks (2019)
Journal Article
Legg, P., Smith, J., & Downing, A. (2019). Visual analytics for collaborative human-machine confidence in human-centric active learning tasks. Human-Centric Computing and Information Sciences, 9, https://doi.org/10.1186/s13673-019-0167-8

Active machine learning is a human-centric paradigm that leverages a small labelled dataset to build an initial weak classifier, that can then be improved over time through human-machine collaboration. As new unlabelled samples are observed, the mach... Read More about Visual analytics for collaborative human-machine confidence in human-centric active learning tasks.

Evolutionary n-level hypergraph partitioning with adaptive coarsening (2019)
Journal Article
Preen, R., & Smith, J. (2019). Evolutionary n-level hypergraph partitioning with adaptive coarsening. IEEE Transactions on Evolutionary Computation, 23(6), 962-971. https://doi.org/10.1109/TEVC.2019.2896951

Hypergraph partitioning is an NP-hard problem that occurs in many computer science applications where it is necessary to reduce large problems into a number of smaller, computationally tractable sub-problems. Current techniques use a multilevel appro... Read More about Evolutionary n-level hypergraph partitioning with adaptive coarsening.

Confidentiality and linked data (2018)
Book Chapter
Ritchie, F., & Smith, J. Confidentiality and linked data. In G. Roarson (Ed.), Privacy and Data Confidentiality Methods – a National Statistician’s Quality Review, 1-34. Office for National Statistics

This chapter considers the confidentiality issues around linked data. It notes that the use and availability of secondary (adminstrative or social media) data, allied to powerful processing and machine learning techniques, in theory means that re-ide... Read More about Confidentiality and linked data.

E-assessment of computer programming (2018)
Presentation / Conference
Gwynllyw, R., & Smith, J. (2018, September). E-assessment of computer programming. Paper presented at 12th International Symposium on Advances in Technology Education Nurturing Professionals for Smart Cities: Way Forward for Technology Education

This paper demonstrates how we have used Dewis, an algorithmic open source e-assessment system, to automatically assess programming skills, in particular, in the C programming language. Teaching and assessing programming skills is challenging; prior... Read More about E-assessment of computer programming.

Predicting user confidence during visual decision making (2018)
Journal Article
Smith, J., Legg, P., Kinsey, K., & Matovis, M. (2018). Predicting user confidence during visual decision making. ACM Transactions on Interactive Intelligent Systems, 8(2), https://doi.org/10.1145/3185524

© 2018 ACM People are not infallible consistent “oracles”: their confidence in decision-making may vary significantly between tasks and over time. We have previously reported the benefits of using an interface and algorithms that explicitly captured... Read More about Predicting user confidence during visual decision making.

The Internet of Flying Things (2018)
Book
Pigatto, D. F., Rodrigues, M., de Carvalho Fontes, J. V., Pinto, A. S. R., Smith, J., & Branco, K. R. L. J. C. (2018). The Internet of Flying Things. John Wiley & Sons, Inc. https://doi.org/10.1002/9781119456735.ch19

Popularly known as drones, unmanned aerial vehicles (UAVs) have been applied in several fields, usually operating in cooperative and collaborative swarms to enable the execution of more dynamic missions. Thus, the new Flying Ad Hoc Networks (FANETs)... Read More about The Internet of Flying Things.

Predicting the occurrence of world news events using recurrent neural networks and auto-regressive moving average models (2017)
Book Chapter
Smith, E. M., Smith, J., Legg, P., & Francis, S. (2017). Predicting the occurrence of world news events using recurrent neural networks and auto-regressive moving average models. In F. Chao, S. Schockaert, & Q. Zhang (Eds.), Advances in Computational Intelligence Systems: UKCI 2017, 191-202. Springer Cham

The ability to predict future states is fundamental for a wide variety of applications, from weather forecasting to stock market analysis. Understanding the related data attributes that can influence changes in time series is a challenging task that... Read More about Predicting the occurrence of world news events using recurrent neural networks and auto-regressive moving average models.

Exploiting diverse distance metrics for surrogate-based optimisation of ordering problems (2016)
Presentation / Conference
Smith, J., Stone, C., & Serpell, M. (2016, July). Exploiting diverse distance metrics for surrogate-based optimisation of ordering problems. Paper presented at ACM-SIGEVO Genetic and Evolutionary Computation Conference, GECCO ’16

Surrogate-assisted optimisation has proven success in the continuous domain, but only recently begun to be explored for other representations, in particular permutations. The use of Gaussian kernel-based models has been proposed, but only tested on s... Read More about Exploiting diverse distance metrics for surrogate-based optimisation of ordering problems.

Exploiting antipheromone in ant colony optimisation for interactive search-based software design and refactoring (2016)
Presentation / Conference
Simons, C., & Smith, J. (2016, July). Exploiting antipheromone in ant colony optimisation for interactive search-based software design and refactoring. Poster presented at ACM-SIGEVO Genetic and Evolutionary Computation Conference, GECCO ’16

Preventing user-fatigue in interactive meta-heuristic search places as great an emphasis on efficiency as it does on ef- fectiveness. Engagement may also be boosted if the system provides a sense of “responsiveness” - for example, avoiding unpopular... Read More about Exploiting antipheromone in ant colony optimisation for interactive search-based software design and refactoring.

Evolving atomic aesthetics and dynamics (2016)
Journal Article
Davies, E., Tew, P., Glowacki, D., Smith, J., & Mitchell, T. (2016). Evolving atomic aesthetics and dynamics. Lecture Notes in Artificial Intelligence, 9596, 17-33. https://doi.org/10.1007/978-3-319-31008-4_2

© Springer International Publishing Switzerland 2016. The depiction of atoms and molecules in scientific literature owes as much to the creative imagination of scientists as it does to scientific theory and experimentation. danceroom Spectroscopy (dS... Read More about Evolving atomic aesthetics and dynamics.

Sphere: A novel platform for increasing safety & security on unmanned systems (2015)
Presentation / Conference
Pigatto, D., Smith, J., & Branco, K. (2015, June). Sphere: A novel platform for increasing safety & security on unmanned systems. Paper presented at 2015 International Conference on Unmanned Aircraft Systems (ICUAS)

The Healthy, Mobility and Security-based Data Communication Architecture, also known as HAMSTER, is provided with a special platform for safety & security: Sphere. It concentrates all the safety & security aspects of the main ar- chitecture and all d... Read More about Sphere: A novel platform for increasing safety & security on unmanned systems.

From evolutionary computation to the evolution of things (2015)
Journal Article
Eiben, A. E., & Smith, J. (2015). From evolutionary computation to the evolution of things. Nature, 521(7553), 476-482. https://doi.org/10.1038/nature14544

Evolution has provided a source of inspiration for algorithm designers since the birth of computers. The resulting field, evolutionary computation, has been successful in solving engineering tasks ranging in outlook from the molecular to the astronom... Read More about From evolutionary computation to the evolution of things.

The influence of search components and problem characteristics in early life cycle class modelling (2014)
Journal Article
Smith, J., & Simons, C. (2015). The influence of search components and problem characteristics in early life cycle class modelling. Journal of Systems and Software, 103, 440-451. https://doi.org/10.1016/j.jss.2014.11.034

© 2014 Elsevier Inc. All rights reserved. This paper examines the factors affecting the quality of solution found by meta-heuristic search when optimising object-oriented software class models. From the algorithmic perspective, we examine the effect... Read More about The influence of search components and problem characteristics in early life cycle class modelling.

Using evolutionary computation to shed light on the effect of scale and complexity on object-orientedsoftware design (2014)
Presentation / Conference
Simons, C., & Smith, J. (2014, October). Using evolutionary computation to shed light on the effect of scale and complexity on object-orientedsoftware design. Paper presented at 2014 IEEE International Conference on Systems, Man, and Cybernetics, San Diego, CA, USA

Early lifecycle software design is an intensely human activity in which design scale and complexity can place a high cognitive load on the software designer. Recently, the use of evolutionary search has been suggested to yield insights in the natur... Read More about Using evolutionary computation to shed light on the effect of scale and complexity on object-orientedsoftware design.

The Baldwin effect hinders self-adaptation (2014)
Book Chapter
Smith, J. (2014). The Baldwin effect hinders self-adaptation. In J. Branke, B. Filipic, J. Smith, & T. Bartz-Beielstein (Eds.), Parallel Problem Solving from Nature – PPSN XIII, 120-129. Springer. https://doi.org/10.1007/978-3-319-10762-2_12

The “end-game” of evolutionary optimisation is often largely governed by the efficiency and effectiveness of searching regions of space known to contain high quality solutions. In a traditional EA this role is done via mutation, which creates a tensi... Read More about The Baldwin effect hinders self-adaptation.

Interactive ant colony optimization (iACO) for early lifecycle software design (2014)
Journal Article
Simons, C., Smith, J., & White, P. (2014). Interactive ant colony optimization (iACO) for early lifecycle software design. Swarm Intelligence, 8(2), 139-157. https://doi.org/10.1007/s11721-014-0094-2

Finding good designs in the early stages of the software development lifecycle is a demanding multi-objective problem that is crucial to success. Previously, both interactive and non-interactive techniques based on evolutionary algorithms (EAs) have... Read More about Interactive ant colony optimization (iACO) for early lifecycle software design.

A genetic algorithm for the one-dimensional cutting stock problem with setups (2014)
Journal Article
de Araujo, S. A., Poldi, K. C., & Smith, J. (2014). A genetic algorithm for the one-dimensional cutting stock problem with setups. Pesquisa Operacional, 34(2), 165-187. https://doi.org/10.1590/0101-7438.2014.034.02.0165

This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the conce... Read More about A genetic algorithm for the one-dimensional cutting stock problem with setups.

A comparison of meta-heuristic search for interactive software design (2013)
Journal Article
Smith, J. E., Simons, C. L., Simons, C., & Smith, J. (2013). A comparison of meta-heuristic search for interactive software design. Soft Computing, 17(11), 2147-2162. https://doi.org/10.1007/s00500-013-1039-1

Advances in processing capacity, coupled with the desire to tackle problems where a human subjective judgment plays an important role in determining the value of a proposed solution, has led to a dramatic rise in the number of applications of Interac... Read More about A comparison of meta-heuristic search for interactive software design.


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