Ontology-Driven Automated Generation of Data Entry Interfaces to Databases
Conference Proceeding
Cannon, A., Kennedy, J. B., Paterson, T., & Watson, M. F. (2004)
Ontology-Driven Automated Generation of Data Entry Interfaces to Databases. In H. Williams, & L. Mackinnon (Eds.), Key Technologies for Data Management; Lecture Notes in Computer Science, 150-164. doi:10.1007/978-3-540-27811-5_15
This paper discusses an ontology based approach for the automatic generation of data entry interfaces to databases. An existing domain ontology is mapped to a system domain mo...
DEEPC: Dynamic Energy Profiling of Components
Conference Proceeding
Liu, X., Chinenyeze, S. J., & Al-Dubai, A. (2016)
DEEPC: Dynamic Energy Profiling of Components. In 2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC)https://doi.org/10.1109/COMPSAC.2016.90
Many software projects are built using reusable components (i.e. reusable objects - as per component and connectors in software architectures). During component selection in C...
An Optimized Speculative Execution Strategy Based on Local Data Prediction in a Heterogeneous Hadoop Environment
Conference Proceeding
Liu, X., & Liu, Q. (2017)
An Optimized Speculative Execution Strategy Based on Local Data Prediction in a Heterogeneous Hadoop Environment. In Proceedings of 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC), (128-131). https://doi.org/10.1109/cse-euc.2017.208
Hadoop is a famous distributed computing framework that is applied to process large-scale data. "Straggling tasks" have a serious impact on Hadoop performance due to imbalance...
Clustering Moving Data with a Modified Immune Algorithm
Conference Proceeding
Hart, E., & Ross, P. (2001)
Clustering Moving Data with a Modified Immune Algorithm. In E. Boers (Ed.), Applications of Evolutionary Computing, 394-403. https://doi.org/10.1007/3-540-45365-2_41
In this paper we present a prototype of a new model for performing clustering in large, non-static databases. Although many machine learning algorithms for data clustering hav...
Evaluation of a genetic representation for outline shapes
Conference Proceeding
Lapok, P., Lawson, A., & Paechter, B. (2017)
Evaluation of a genetic representation for outline shapes. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference Companion, (1419-1422). https://doi.org/10.1145/3067695.3082501
This work in progress focuses on the evaluation of a genetic representation for outline shapes for planar mechanical levers which addresses the first stage of the complex real...
Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems
Conference Proceeding
Segredo, E., Paechter, B., Hart, E., & Gonz´alez-Vila, C. I. (2016)
Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems. In 2016 IEEE Congress on Evolutionary Computation (CEC)https://doi.org/10.1109/CEC.2016.7743969
In order to address the difficult issue of parameter setting within a diversity-based Multi-objective Evolutionary Algorithm (MOEA), we recently proposed a hybrid control sche...
Finding Fair Negotiation Algorithms to Reduce Peak Electricity Consumption in Micro Grids
Conference Proceeding
Powers, S. T., Meanwell, O., & Cai, Z. (2019)
Finding Fair Negotiation Algorithms to Reduce Peak Electricity Consumption in Micro Grids. In PAAMS 2019: Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection, 269-272. https://doi.org/10.1007/978-3-030-24209-1_28
Reducing peak electricity consumption is important to maximise use of renewable energy sources, and reduce the total amount of capacity required on a grid. Most approaches use...
Towards Modelling and Reasoning about Uncertain Data of Sensor Measurements for Decision Support in Smart Spaces.
Conference Proceeding
Bamgboye, O., Liu, X., & Cruickshank, P. (2018)
Towards Modelling and Reasoning about Uncertain Data of Sensor Measurements for Decision Support in Smart Spaces. In 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC)https://doi.org/10.1109/COMPSAC.2018.10330
Smart Spaces currently benefits from Internet of Things (IoT) infrastructures in order to realise its objectives. In many cases, it demonstrates this through certain automated...
Developing a core ontology for taxonomic data.
Conference Proceeding
Kennedy, J., Gales, R., Hyam, R., Kukla, R., Wieczorek, J., Hagedorn, G., …Vieglais, D. (2006)
Developing a core ontology for taxonomic data. In L. Belbin, A. Rissoné, & A. Weitzman (Eds.), Proceedings of TDWG (2006), St Louis, MI
Over recent years several sub-groups within the Taxonomic Databases Working Group (TDWG) have developed models and exchange standards to facilitate data sharing within the tax...
A Cooperative Learning Approach for the Quadratic Knapsack Problem
Conference Proceeding
Lalla-Ruiz, E., Segredo, E., & Voß, S. (2018)
A Cooperative Learning Approach for the Quadratic Knapsack Problem. In Learning and Intelligent Optimization Conference (LION12). , (31-35). https://doi.org/10.1007/978-3-030-05348-2_3
The Quadratic Knapsack Problem (QKP) is a well-known optimization problem aimed to maximize a quadratic objective function subject to linear capacity constraints. It has sever...