Towards danger theory based artificial APC model: novel metaphor for danger susceptible data codons
Danger Theory (DT) sets significant shift in viewpoint about the main goal of human immune system (HIS). This viewpoint, though controversial among immunologists, may enable artificial immune systems (AIS) researchers to extract benefits of the theory for designing their systems and solving problems...
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2004
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my.utm.121222017-10-02T06:50:04Z http://eprints.utm.my/id/eprint/12122/ Towards danger theory based artificial APC model: novel metaphor for danger susceptible data codons Iqbal, Anjum Maarof, Mohd. Aizani QA75 Electronic computers. Computer science Danger Theory (DT) sets significant shift in viewpoint about the main goal of human immune system (HIS). This viewpoint, though controversial among immunologists, may enable artificial immune systems (AIS) researchers to extract benefits of the theory for designing their systems and solving problems confronting with the conventional approach of self-nonself discrimination. Furthering recent pioneering concepts in the field, this paper aims to gain a distinct look for the data that DT based AIS processes. The proposed concept introduces a novel biological metaphor, DASTON, for observing danger susceptible data chunks/points combinations. Preliminary analysis for DASTON identification gives hope for exciting future of the idea. It is an initial effort towards Artificial Antigen Presenting Cell (AAPC) modeling. The concept may initiate an argument that might contribute significantly for the body of knowledge in AIS research. Springer-Verlag Berlin Nicosia, Giuseppe Cutello, Vincenzo J. Bentley, Peter Timmis, Jon 2004-09-13 Book Section PeerReviewed Iqbal, Anjum and Maarof, Mohd. Aizani (2004) Towards danger theory based artificial APC model: novel metaphor for danger susceptible data codons. In: Proceedings Artificial Immune Systems. Lecture Notes In Computer Science, 3239 . Springer-Verlag Berlin, Germany, pp. 161-174. ISBN 3-540-23097-1 http://dx.doi.org/10.1007/978-3-540-30220-9_13 doi:10.1007/978-3-540-30220-9_13 |
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QA75 Electronic computers. Computer science Iqbal, Anjum Maarof, Mohd. Aizani Towards danger theory based artificial APC model: novel metaphor for danger susceptible data codons |
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Danger Theory (DT) sets significant shift in viewpoint about the main goal of human immune system (HIS). This viewpoint, though controversial among immunologists, may enable artificial immune systems (AIS) researchers to extract benefits of the theory for designing their systems and solving problems confronting with the conventional approach of self-nonself discrimination. Furthering recent pioneering concepts in the field, this paper aims to gain a distinct look for the data that DT based AIS processes. The proposed concept introduces a novel biological metaphor, DASTON, for observing danger susceptible data chunks/points combinations. Preliminary analysis for DASTON identification gives hope for exciting future of the idea. It is an initial effort towards Artificial Antigen Presenting Cell (AAPC) modeling. The concept may initiate an argument that might contribute significantly for the body of knowledge in AIS research. |
author2 |
Nicosia, Giuseppe |
author_facet |
Nicosia, Giuseppe Iqbal, Anjum Maarof, Mohd. Aizani |
format |
Book Section |
author |
Iqbal, Anjum Maarof, Mohd. Aizani |
author_sort |
Iqbal, Anjum |
title |
Towards danger theory based artificial APC model: novel metaphor for danger susceptible data codons |
title_short |
Towards danger theory based artificial APC model: novel metaphor for danger susceptible data codons |
title_full |
Towards danger theory based artificial APC model: novel metaphor for danger susceptible data codons |
title_fullStr |
Towards danger theory based artificial APC model: novel metaphor for danger susceptible data codons |
title_full_unstemmed |
Towards danger theory based artificial APC model: novel metaphor for danger susceptible data codons |
title_sort |
towards danger theory based artificial apc model: novel metaphor for danger susceptible data codons |
publisher |
Springer-Verlag Berlin |
publishDate |
2004 |
url |
http://eprints.utm.my/id/eprint/12122/ http://dx.doi.org/10.1007/978-3-540-30220-9_13 |
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