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Read  full  paper  at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=52971#.VK8qbMnQrzE Author(s)   Luigi Maxmilian Caligiuri 1,2*   Affiliation(s) 1 University of Calabria, Arcavacata di Rende, Italy . 2 Foundation of Physics Research Center (FoPRC), Cosenza, Italy . ABSTRACT Living organisms are high ordered and organized systems accumulating and successively using low entropy energy to support all the processes needed for life. This low level of entropy is a required condition in order to make possible the use of endogenous energy for producing, for example, mechanical work. The commonly accepted picture of condensed matter physics, exclusively considering the perturbative coupling between QED Zero-Point-Field also known as “Quantum Vacuum” and the matter system, is unable to thoroughly explain the true origin of this low entropy energy reservoir and its dynamics. Recent researches instead suggested that energy and ...

Read  full  paper  at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=52902#.VKyUgcnQrzE Author(s) M. Divari , D. Vivona Affiliation(s) Department of Basic and Applied Sciences for Engineering, Faculty of Civil and Industrial Engineering, “Sapienza” University of Rome, Roma, Italy . ABSTRACT In this paper, by axiomatic way, a form of information entropy will be presented on crisp and fuzzy setting. Information entropy is the unavailability of information about a crisp or fuzzy event. It will use measure of information defined without any probability or fuzzy measure: for this reason it is called general information .   KEYWORDS Information , Entropy , Functional Equations , Fuzzy Sets Cite this paper Divari, M. and Vivona, D. (2014) A Form of Information Entropy. Natural Science , 6 , 1282-1285. doi: 10.4236/ns.2014.617118 .   References [ 1 ] Shannon, C. and Weaver, W. (1949) The Mathematical Theor...

Read full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=50204#.VDH94lfHRK0 Author(s)     Daniel Kovach 1* Affiliation(s) 1 Kovach Technologies, San Jose, CA, USA . ABSTRACT This paper presents an information theoretic approach to the concept of intelligence in the computational sense. We introduce a probabilistic framework from which computation alintelligence is shown to be an entropy minimizing process at the local level. Using this new scheme, we develop a simple data driven clustering example and discuss its applications. KEYWORDS Machine Learning , Artificial Intelligence , Entropy , Computer Science , Intelligence ...