Class resource: ERCIM

posted Nov 9, 2011, 7:58 PM by Francis Cabarle   [ updated Nov 9, 2011, 7:58 PM by Nestine Hope Hernandez ]
The European Research Consortium for Informatics and Mathematics makes available for free downloads their past as well as current issues. One recent issue of particular interest is the April 2011 issue for Unconventional Computing Paradigms downloadable here. A preview for this issue is as follows:

ERCIM News 85

Image ERCIM News 85 cover page

April 2011
Special theme: 
Unconventional Computing Paradigms
This issue in pdf
(64 pages; 7 Mb)

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fet11fet11, Budapest, 4-6 May 2006 
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January 2011

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Evolving Software

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ERCIM News 85

Unconventional Computation


Susan Stepneyby Susan Stepney

The mathematician Stanislaw Ulam is famously quoted as saying that using a term like nonlinear science is like referring to the bulk of zoology as the study of non-elephant animals (Campbell, Farmer, Crutchfield, Jen. "Experimental Mathematics: the role of computation in nonlinear science". Comms.ACM 28(4):374-84, 1985). Unconventional, or non-classical, computation is a similar term: the study of non-Turing computation. But how big is its associated field? Whereas zoology has the advantage of studying many kinds of non-elephants, non-classical computer scientists are currently restricted to studying a few relatively primitive, or dimly seen, or merely hypothesised, devices.


Introduction to the Special theme - Quantum Computing

Special Theme

by Jiri Vala

We are living at the beginning of a quantum revolution which will no doubt have a profound impact on all aspects of our lives. Quantum systems, which were once restricted to academic research, are now becoming a technological reality. This inevitable evolution is particularly well documented in the context of information and communication technologies where the first quantum devices are becoming available commercially.


Introduction to the Special theme - Molecular and Cellular Computing

Special Theme

by Giancarlo Mauri
In 1994, a pioneering experiment by Leonard Adleman showed that DNA could be used to solve mathematical problems by exploiting its capability to store and process information and using molecular biology tools to perform arithmetic or logic operations on the encoded data. Since then, the interest of researchers in the area of (bio-)molecular computing has been growing continuously, taking the discipline well beyond the original idea of using biological molecules as fundamental components of computing devices.