Hostname: page-component-cc8bf7c57-qfg88 Total loading time: 0 Render date: 2024-12-11T23:10:17.808Z Has data issue: false hasContentIssue false
  • English
  • Français

Intelligent computing in large-scale systems

Published online by Cambridge University Press:  25 March 2015

Joanna Kołodziej ,
Horacio González-Vélez ,
Fatos Xhafa  and
Leonard Barolli
Joanna Kołodziej
Affiliation:
Department of Computer Science, Cracow University of Technology, ul. Warszawska 24, 31-155 Cracow, Poland e-mail: [email protected]
Horacio González-Vélez
Affiliation:
School of Computing, National College of Ireland, Mayor Street, IFSC, Dublin 1, Ireland e-mail: [email protected]
Fatos Xhafa
Affiliation:
Departament de Ciéncies de la Computació, Universitat Politècnica de Catalunya Campus Nord, Ed. Omega, 08034 Barcelona, Spain e-mail: [email protected]
Leonard Barolli
Affiliation:
Department of Information and Communication Engineering, Fukuoka, Institute of Technology, 3-30-1 Wajiro-Higashi, Higashi-Ku, Fukuoka 811-0295, Japan e-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Intelligent computing in large-scale systems provides systematic methodologies and tools for building complex inferential systems, which are able to adapt, mine data sets, evolve, and act in a nimble manner within major distributed environments with diverse architectures featuring multiple cores, accelerators, and high-speed networks.

We believe that the papers presented in this special issue ought to serve as a reference for students, researchers, and industry practitioners interested in the evolving, interdisciplinary area of intelligent computing in large-scale systems. We very much hope that readers will find in this compendium new inspiration and ideas to enhance their own research.

Type
Articles
Information
The Knowledge Engineering Review , Volume 30 , Issue 2: Intelligent Computing in Large–Scale Systems , March 2015 , pp. 137 - 139
Copyright
© Cambridge University Press, 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Buchanan, F., Capanni, N. & González-Vélez, H. 2015. Distributed aggregation of heterogeneous web-based fine art information: enabling multi-source accessibility and curation. The Knowledge Engineering Review 30, 220–236.CrossRefGoogle Scholar
Byrski, A., Dreyzewski, R., Siwik, L. & Kisiel-Dorohinicki, M. 2015. Evolutionary multi-agent systems. The Knowledge Engineering Review 30, 171–186.CrossRefGoogle Scholar
Conti, V., Militello, C., Sorbello, F. & Vitabile, S. 2015. Biometric sensors rapid prototyping on FPGA. The Knowledge Engineering Review 30, 201–219.Google Scholar
Gateau, B., Ouedraogo, M., Feltus, C., Guemkam, G., Danoy, G., Seredynski, M., Khan, S. U., Khadraoui, D. & Bouvry, P. 2015. Adopting trust and assurance as indicators for the reassignment of responsibilities in multi-agent systems. The Knowledge Engineering Review 30, 187–200.Google Scholar
Irfan, R., King, C., Grages, D., Ewen, S., Khan, S. U., Madani, S., Kolodziej, J., Wang, L., Chen, D. & Rayes, A. 2015. A survey on text mining in social networks. The Knowledge Engineering Review 30, 157–170.Google Scholar
Moore, P. T. & Pham, H. V. 2015. Personalization and rule strategies in human-centric data intensive intelligent context-aware systems. The Knowledge Engineering Review 30, 140–156.Google Scholar