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L. Han, T. Saengngam, and J. van Hemert, Accelerating Data-Intensive Applications: a Cloud Computing Approach Image Pattern Recognition Tasks, in The Fourth International Conference on Advanced Engineering Computing and Applications in Sciences, 2010.
N. P. Chue Hong, M. Antonioletti, K. A. Karasavvas, and M. Atkinson, Accessing Data in Grids Using OGSA-DAI, in Knowledge and Data Management in Grids, 2007.
J. Eggermont, A. E. Eiben, and J. I. van Hemert, Adapting the Fitness Function in GP for Data Mining, in Springer Lecture Notes on Computer Science, 1999, p. 195--204.
R. Filgueira, D. E. Singh, A. Calderón, F. G. Carballeira, and J. Carretero, Adaptive CoMPI: Enhancing MPI based applications performance and scalability by using adaptive compression., International Journal of High Performance Computing and Applications, 2010. Sage, no. 25 (3), 2010.
J. Eggermont and J. I. van Hemert, Adaptive Genetic Programming Applied to New and Existing Simple Regression Problems, in Springer Lecture Notes on Computer Science, 2001, p. 23--35.
R. Filgueira, A. Nuñez, J. Fernandez, and M. Atkinson, An adaptive, scalable, and portable technique for speeding up MPI-based applications, in International European Conference on Parallel and Distributed Computing, Europar-2012, 2012.
P. Brezany, I. Janciak, A. Woehrer, C. B. Aranda, M. Atkinson, and J. van Hemert, ADMIRE D1.5 – Report defining an iteration of the model and language: PM3 and DL3. ADMIRE project, 2009.
A. Voss et al., Adoption of e-Infrastructure Services: inhibitors, enablers and opportunities, in 5th International Conference on e-Social Science, Maternushaus, Cologne, 2009.
M. Atkinson et al., Advanced Data Mining and Integration Research for Europe, in All Hands Meeting 2009, Oxford, 2009.
L. Han, Application of the methodology combined formal method with Object-Oriented technology in E-commerce, Journal of Computer Engineering, vol. 29, no. z1, p. 65~67 , 2002.
S. Prammanee and K. Moessner, The Architectural Design of Multi Interface-Device Binding (MID-B) System, in The 3rd Workshop on Context Awareness for Proactive Systems, Guildford, UK, 2007.
R. Upadhyay et al., An Architecture for an Integrated Fire Emergency Response System for the Built Environment, in 9th Symposium of the International Association for Fire Safety Science (IAFSS), Karlsruhe, GERMANY, 2008.
A. O. Maghraby, Automatic Agent Protocol Generation from Argumentation, in 13th European Agent Systems Summer Schoo, 2011.
L. Han, J. van Hemert, and R. Baldock, Automatically Identifying and Annotating Mouse Embryo Gene Expression Patterns, Bioinformatics, vol. 27, pp. 1101–1107, 2011.
L. Han, J. van Hemert, R. Baldock, and M. P. Atkinson, Automating Gene Expression Annotation for Mouse Embryo, in Lecture Notes in Computer Science (Advanced Data Mining and Applications, 5th International Conference), 2009, vol. LNAI 5678, pp. 469-478.
C
L. Han and C. Suo, The characterizing network traffic based on the wavelet technique, Journal of Mini-Micro Computer System, vol. 22, no. 9, p. 1110~ 1114, 2001.
A. Barker, J. Weissman, and J. I. van Hemert, The Circulate Architecture: Avoiding Workflow Bottlenecks Caused By Centralised Orchestration, Cluster Computing, vol. 12, p. 221--235, 2009.
S. Aitken and Y. Chen, COBrA and COBrA-CT: Ontology Engineering Tools, in Anatomy Ontologies for Bioinformatics: Principles and Practice, A. Burger, D. Davidson, and R. Baldock Springer, 2007.
J. I. van Hemert, Comparing Classical Methods for Solving Binary Constraint Satisfaction Problems with State of the Art Evolutionary Computation, in Springer Lecture Notes on Computer Science, 2002, p. 81--90.
M. Cuggia, P. Besana, and D. Glasspool., Comparing Clinical Decision Support Systems for Recruitment in Clinical Trials, Journal of Medical Informatics, 2010.
B. G. W. Craenen, A. E. Eiben, and J. I. van Hemert, Comparing Evolutionary Algorithms on Binary Constraint Satisfaction Problems, IEEE Transactions on Evolutionary Computation, vol. 7, p. 424--444, 2003.
J. Eggermont, A. E. Eiben, and J. I. van Hemert, Comparing genetic programming variants for data classification, in Proceedings of the Eleventh Belgium/Netherlands Conference on Artificial Intelligence (BNAIC'99), 1999, p. 253--254.
J. Eggermont, A. E. Eiben, and J. I. van Hemert, A comparison of genetic programming variants for data classification, in Springer Lecture Notes on Computer Science, 1999, p. 281--290.

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