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A chaotic orbit generated by a nonlinear system is irregular, aperiodic, unpredictable and has sensitive dependence on initial conditions. However, the chaotic trajectory is still not well enough to be a crypto system in digital secure communication. Therefore, we propose a Modified Logistic Map (MLM) and give a theoretical proof to show that the MLM is a chaotic map according to Devaney's definition. Based on the MLMs, we establish a Modified Logistic Hyper-Chaotic System (MLHCS) and apply MLHCS to develop a symmetric cryptography algorithm, Asymptotic Synchronization of Modified Logistic Hyper-Chaotic System (ASMLHCS). [ABSTRACT FROM AUTHOR]

Performance results for finding the best genetic algorithm for the complex real problem of optimal machinery equipment operation and predictive maintenance are presented. A genetic algorithm is a stochastic computational model that seeks the optimal solution to an objective function. A methodology calculation is based on the idea of measuring the increase of fitness and fitness quality evaluation with chaos theory principles applying within genetic algorithm environment. Fuzzy neural networks principles are effectively applied in solved manufacturing problems mostly where multisensor integration, real - timeness, robustness and learning abilities are needed. A modified Mamdani neuro-fuzzy system improves the interpretability of used domain knowledge. [ABSTRACT FROM AUTHOR]

There is a lot of literature announcing the advent of Information Society; in the meantime, though, we are living in a transitional period that has been labeled as Risk Society (RS). One of the specific traits of RS is the spreading of this perception of risk and the growing wish for higher security. However, this paper argues that risk is poorly treated nowadays and that a new approach is in demand. Futures Studies (FS) can provide this perspective, but only as long as it is able to integrate the inputs of other disciplines such as Chaos Theory, Evolutionary Theory and Kondratieff Waves (KW). KW can have a key role in this endeavor as they can offer ways to surpass one of FS shortcomings, their difficulty to incorporate in a solid way human variables in systemic methods. On the other hand, FS can help KW in several aspects: to improve their capacity to work with inputs from diverse sources, to assimilate with greater ease the normative aspects inherent to risk researches and, finally, a way to get around the not-so-appealing determinism implicit in KW. [ABSTRACT FROM AUTHOR]