Outputs (492)

Timetabling the classes of an entire university with an evolutionary algorithm. (1998)
Presentation / Conference Contribution
Paechter, B., Rankin, B., Cumming, A., & Fogarty, T. C. (1998, September). Timetabling the classes of an entire university with an evolutionary algorithm. Presented at 5th International Conference Parallel Problem Solving from Nature — PPSN V, Amsterdam

This paper describes extensions to an evolutionary algorithm that timetables classes for an entire University. A new method of dealing with multi-objectives is described along with a user interface designed for it. New results are given concerning re... Read More about Timetabling the classes of an entire university with an evolutionary algorithm..

A Conceptual Framework for Establishing Trust in Real World Intelligent Systems (2021)
Journal Article
Guckert, M., Gumpfer, N., Hannig, J., Keller, T., & Urquhart, N. (2021). A Conceptual Framework for Establishing Trust in Real World Intelligent Systems. Cognitive Systems Research, 68, 143-155. https://doi.org/10.1016/j.cogsys.2021.04.001

Intelligent information systems that contain emergent elements often encounter trust problems because results do not get sufficiently explained and the procedure itself can not be fully retraced. This is caused by a control flow depending either on s... Read More about A Conceptual Framework for Establishing Trust in Real World Intelligent Systems.

Real Time Optimisation of Traffic Signals to Prioritise Public Transport (2021)
Presentation / Conference Contribution
Plötz, P., Wittpohl, M., & Urquhart, N. (2021, April). Real Time Optimisation of Traffic Signals to Prioritise Public Transport. Presented at EvoApplications 2021, Online

This paper examines the optimisation of traffic signals to prioritise public transportation (busses) in real time. A novel representation for the traffic signal prioritisation problem is introduced. Through the novel representation a creative evoluti... Read More about Real Time Optimisation of Traffic Signals to Prioritise Public Transport.

WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets (2021)
Presentation / Conference Contribution
Pitt, J., Burth Kurka, D., Hart, E., & Cardoso, R. P. (2021, April). WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets. Presented at 24th European Conference, EvoApplications 2021, Online

In order to address scalability issues, which can be a challenge for Deep Learning methods, we propose Wide Learning of Diverse Architectures-a model that scales horizontally rather than vertically, enabling distributed learning. We propose a distrib... Read More about WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets.

A fully connected deep learning approach to upper limb gesture recognition in a secure FES rehabilitation environment (2021)
Journal Article
Liu, Q., Wu, X., Jiang, Y., Liu, X., Zhang, Y., Xu, X., & Qi, L. (2021). A fully connected deep learning approach to upper limb gesture recognition in a secure FES rehabilitation environment. International Journal of Intelligent Systems, 36(5), 2387-2411. https://doi.org/10.1002/int.22383

Stroke is one of the leading causes of death and disability in the world. The rehabilitation of Patients' limb functions has great medical value, for example, the therapy of functional electrical stimulation (FES) systems, but suffers from effective... Read More about A fully connected deep learning approach to upper limb gesture recognition in a secure FES rehabilitation environment.

Extensions to a memetic timetabling system. (1996)
Presentation / Conference Contribution
Paechter, B., Cumming, A., Norman, M. G., & Luchian, H. (1996). Extensions to a memetic timetabling system. In R. Burke (Ed.), Practice and Theory of Automated Timetabling (251-265). https://doi.org/10.1007/3-540-61794-9_64

This paper describes work in progress to increase the performance of a memetic timetabling system. The features looked at are two directed mutation operators, targeted mutation and a structured population that facilitates parallel implementation. Exp... Read More about Extensions to a memetic timetabling system..

The use of local search suggestion lists for improving the solution of timetable problems with evolutionary algorithms. (1995)
Presentation / Conference Contribution
Paechter, B., Cumming, A., & Luchian, H. (1995). The use of local search suggestion lists for improving the solution of timetable problems with evolutionary algorithms. In Evolutionary Computing (86-93). https://doi.org/10.1007/3-540-60469-3_27

This paper presents a new genetic representation for timetabling with evolutionary algorithms. The representation involves the use of suggestion lists for the placement of events into timeslots. A set of recombination operators is defined for the new... Read More about The use of local search suggestion lists for improving the solution of timetable problems with evolutionary algorithms..

A renewable energy forecasting and control approach to secured edge-level efficiency in a distributed micro-grid (2021)
Journal Article
Anaadumba, R., Liu, Q., Marah, B. D., Nakoty, F. M., Liu, X., & Zhang, Y. (2021). A renewable energy forecasting and control approach to secured edge-level efficiency in a distributed micro-grid. Cybersecurity, 4, Article 1 (2021). https://doi.org/10.1186/s42400-020-00065-3

Energy forecasting using Renewable energy sources (RESs) is gradually gaining weight in the research field due to the benefits it presents to the modern-day environment. Not only does energy forecasting using renewable energy sources help mitigate th... Read More about A renewable energy forecasting and control approach to secured edge-level efficiency in a distributed micro-grid.

An evolutionary approach to the general timetable problem. (1993)
Book Chapter
Paechter, B., Luchian, H., & Cumming, A. (1993). An evolutionary approach to the general timetable problem. In The Scientific Annals of the "Al. I. Cuza" University of Iasi, special issue for the ROSYCS symposium 1993. Alexandru Ioan Cuza University Press

Commonsense-enhanced Natural Language Generation for Human-Robot Interaction (2020)
Presentation / Conference Contribution
Gkatzia, D. (2020, December). Commonsense-enhanced Natural Language Generation for Human-Robot Interaction. Presented at 2nd Workshop on Natural Language Generation for Human-Robot Interaction (HRI 2020), Online

Commonsense is vital for human communication, as it allows us to make inferences without explicitly mentioning the context. Equipping robots with commonsense knowledge would lead to better communication between humans and robots and will allow robots... Read More about Commonsense-enhanced Natural Language Generation for Human-Robot Interaction.

Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation (2020)
Presentation / Conference Contribution
Hoffmann, B., Urquhart, N., Chalmers, K., & Guckert, M. (2020, February). Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation. Presented at Modelling 2020, Vienna

Multi-agent systems may be considered appropriate tools for simulating complex systems such as those based around traffic and transportation networks. Modelling traffic participants as agents can reveal relevant patterns of traffic flow. Upsurging tr... Read More about Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation.

Evolution of Diverse, Manufacturable Robot Body Plans (2020)
Presentation / Conference Contribution
Buchanan, E., Le Goff, L., Hart, E., Eiben, A. E., De Carlo, M., Li, W., Hale, M. F., Angus, M., Woolley, R., Winfield, A. F., Timmis, J., & Tyrrell, A. M. (2020, December). Evolution of Diverse, Manufacturable Robot Body Plans. Presented at International Conference on Evolvable Systems (ICES), Canberra, Australia

Advances in rapid prototyping have opened up new avenues of research within Evolutionary Robotics in which not only controllers but also the body plans (morphologies) of robots can evolve in real-time and real-space. However, this also introduces new... Read More about Evolution of Diverse, Manufacturable Robot Body Plans.

Hardware Design for Autonomous Robot Evolution (2020)
Presentation / Conference Contribution
Hale, M. F., Angus, M., Buchanan, E., Li, W., Woolley, R., Le Goff, L. K., De Carlo, M., Timmis, J., Winfield, A. F., Hart, E., Eiben, A. E., & Tyrrell, A. M. (2020, December). Hardware Design for Autonomous Robot Evolution. Presented at International Conference on Evolvable Hardware, Canberra Australia

The long term goal of the Autonomous Robot Evolution (ARE) project is to create populations of physical robots, in which both the controllers and body plans are evolved. The transition for evolutionary designs from purely simulation environments into... Read More about Hardware Design for Autonomous Robot Evolution.

A Fast Classification Approach to Upper-Limb Posture Recognition (2020)
Presentation / Conference Contribution
Wu, X., Jiang, Y., Liu, Q., Wu, H., & Liu, X. (2020, November). A Fast Classification Approach to Upper-Limb Posture Recognition. Presented at IEEE International Conferences on Cyber, Physical and Social Computing (CPSCom2020), Rhodes, Greece

Improving VIP viewer Gaze Estimation and Engagement Using Adaptive Dynamic Anamorphosis (2020)
Journal Article
Pan, Y., & Mitchell, K. (2021). Improving VIP viewer Gaze Estimation and Engagement Using Adaptive Dynamic Anamorphosis. International Journal of Human-Computer Studies, 147, Article 102563. https://doi.org/10.1016/j.ijhcs.2020.102563

Anamorphosis for 2D displays can provide viewer centric perspective viewing, enabling 3D appearance, eye contact and engagement, by adapting dynamically in real time to a single moving viewer’s viewpoint, but at the cost of distorted viewing for othe... Read More about Improving VIP viewer Gaze Estimation and Engagement Using Adaptive Dynamic Anamorphosis.

Visual Encodings for Networks with Multiple Edge Types (2020)
Presentation / Conference Contribution
Vogogias, T., Archambault, D. W., Bach, B., & Kennedy, J. (2020, October). Visual Encodings for Networks with Multiple Edge Types. Presented at International Conference on Advanced Visual Interfaces, Napkes, Italy

This paper reports on a formal user study on visual encodings of networks with multiple edge types in adjacency matrices. Our tasks and conditions were inspired by real problems in computational biology. We focus on encodings in adjacency matrices, s... Read More about Visual Encodings for Networks with Multiple Edge Types.

A Sensory Similarities Approach to Load Disaggregation of Charging Stations in Internet of Electric Vehicles (2020)
Journal Article
Liu, Q., Kamoto, K. M., Liu, X., Zhang, Y., Yang, Z., Khosravi, M. R., Xu, Y., & Qi, L. (2021). A Sensory Similarities Approach to Load Disaggregation of Charging Stations in Internet of Electric Vehicles. IEEE Sensors Journal, 21(14), 15895-15903. https://doi.org/10.1109/jsen.2020.3027684

Intelligent transportation systems (ITSs) have become popular in recent years as an essential requirement for safer and more efficient transportation systems. Internet of Electric vehicles (IoEV) as well as their hybrid forms provide an ideal means o... Read More about A Sensory Similarities Approach to Load Disaggregation of Charging Stations in Internet of Electric Vehicles.

Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples (2020)
Presentation / Conference Contribution
Babaagba, K., Tan, Z., & Hart, E. (2020, July). Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples. Presented at The 2020 IEEE Congress on Evolutionary Computation (IEEE CEC 2020), Glasgow, UK

Detecting metamorphic malware provides a challenge to machine-learning models as trained models might not generalise to future mutant variants of the malware. To address this, we explore whether machine-learning models can be improved by augmenting t... Read More about Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples.

A secure edge monitoring approach to unsupervised energy disaggregation using mean shift algorithm in residential buildings (2020)
Journal Article
Liu, Q., Nakoty, F. M., Wu, X., Anaadumba, R., Liu, X., Zhang, Y., & Qi, L. (2020). A secure edge monitoring approach to unsupervised energy disaggregation using mean shift algorithm in residential buildings. Computer Communications, 162, 187-195. https://doi.org/10.1016/j.comcom.2020.08.024

Compared to Intrusive Load Monitoring which uses smart power meters at each level to be monitored, Non-Intrusive Load Monitoring (NILM) is an ingenious way that relies on signal readings at a single point to deduce the share of the devices that have... Read More about A secure edge monitoring approach to unsupervised energy disaggregation using mean shift algorithm in residential buildings.

Exploratory Navigation for Runners Through Geographic Area Classification with Crowd-Sourced Data (2015)
Presentation / Conference Contribution
McGookin, D., Gkatzia, D., & Hastie, H. (2015, August). Exploratory Navigation for Runners Through Geographic Area Classification with Crowd-Sourced Data. Presented at 17th International Conference on Human-Computer Interaction with Mobile Devices and Services, Copenhagen, Denmark

Navigation when running is exploratory, characterised by both starting and ending in the same location, and iteratively foraging the environment to find areas with the most suitable running conditions. Runners do not wish to be explicitly directed, o... Read More about Exploratory Navigation for Runners Through Geographic Area Classification with Crowd-Sourced Data.