Abstract: In this second part of our inquiry into the emergence and evolution of meaning, the category of meaning is explored from the manifestation of reality in its corresponding level of interaction towards the interpretation of such reality (the first part deals correspondingly with an appropriate top-down approach). Based on the physical constraints of manifestation through electromagnetic waves, which constitutes the base of animal vision, we analyze the limits of the meaning-offer of such a manifestation, which allows us, on the one hand, to compare the efficiency of natural evolution in the reception of such meaning-offers; on the other hand, to analyze the conditions of developing agency able to acknowledge the reality underlying its manifestation. Regarding the complexity of such an agency and its related pragmatic response, we distinguish different levels, which allow the development of the General Definition of Information (GDI) properly, with respect to interpretation, as advanced in the first part, throughout nature. As we show at the end, our approach provides new grounds for the Unified Theory of Information (UTI) Program, as well as the possibility for bridging other approaches in the converging fields of information, meaning, computation, and communication.
Abstract: Jensen-Shannon, J-divergence and Arithmetic-Geometric mean divergences are three classical divergence measures known in the information theory and statistics literature. These three divergence measures bear interesting inequality among the three non-logarithmic measures known as triangular discrimination, Hellingar’s divergence and symmetric chi-square divergence. However, in 2003, Eve studied seven means from a geometrical point of view, which are Harmonic, Geometric, Arithmetic, Heronian, Contra-harmonic, Root-mean square and Centroidal. In this paper, we have obtained new inequalities among non-negative differences arising from these seven means. Correlations with generalized triangular discrimination and some new generating measures with their exponential representations are also presented.
Abstract: In order to promote the core competitive power for telecom operating enterprises to face market fine operation, this article compares the ECTA mode (Extension Case Transmission Mode) and the LCA mode (Loosen Couple Mode), both of which are promoted by WfMC. By comparing these two modes, the suitable situations for these two modes are determined. We also carry out empirical analysis based on the customization mode of mobile phones between China telecom and mobile phone manufacturers and to expound the ascension effect of mechanism based on the agile telecom loose coupling workflow with positive feedback to the telecom enterprises. Finally, on the basis of positive feedback system, the task complexity and information transparency of LCA mode are improved, so that the semantics of public flow mode is kept unchanged and the sub workflow is optimized when modifying the sub workflow.
Abstract: It has been found in a variety of face-to-face networks that diffusion of information, behaviors and sentiments extend up to two to four degrees of distance from the original source. This regularity has been popularized as the three degrees of influence phenomenon. Prior works have suggested a number of possible explanations to this pattern. In this paper, we study it in the context of an online network. We find similar results in this online setting to those already found offline. However, our approach suggests that two of the previously proposed explanations (increasing instability of connections at greater distances from the source and simple information decay) should not be central to explain the pattern.
Abstract: The following paragraphs are reproduced from the website of the publisher [1]. At the dawn of the information age, a proper understanding of information and how it relates to matter and energy is of utmost importance for the survival of civilisation. Yet, attempts to reconcile information concepts underlying science and technology with those en vogue in social science, humanities, and arts are rather rare. This book offers a new approach, departing from fragmented information concepts.
Abstract: Evolutionary information theory is a constructive approach that studies information in the context of evolutionary processes, which are ubiquitous in nature and society. In this paper, we develop foundations of evolutionary information theory, building several measures of evolutionary information and obtaining their properties. These measures are based on mathematical models of evolutionary computations, machines and automata. To measure evolutionary information in an invariant form, we construct and study universal evolutionary machines and automata, which form the base for evolutionary information theory. The first class of measures introduced and studied in this paper is evolutionary information size of symbolic objects relative to classes of automata or machines. In particular, it is proved that there is an invariant and optimal evolutionary information size relative to different classes of evolutionary machines. As a rule, different classes of algorithms or automata determine different information size for the same object. The more powerful classes of algorithms or automata decrease the information size of an object in comparison with the information size of an object relative to weaker4 classes of algorithms or machines. The second class of measures for evolutionary information in symbolic objects is studied by introduction of the quantity of evolutionary information about symbolic objects relative to a class of automata or machines. To give an example of applications, we briefly describe a possibility of modeling physical evolution with evolutionary machines to demonstrate applicability of evolutionary information theory to all material processes. At the end of the paper, directions for future research are suggested.
