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This paper introduces an audio encryption algorithm based on permutation of audio samples using discrete modified Henon map followed by substitution operation with keystream generated from the modified Lorenz-Hyperchaotic system. In this work, the audio file is initially compressed by Fast Walsh Hadamard Transform (FWHT) for removing the residual intelligibility in the transform domain. The resulting file is then encrypted in two phases. In the first phase permutation operation is carried out using modified discrete Henon map to weaken the correlation between adjacent samples. In the second phase it utilizes modified-Lorenz hyperchaotic system for substitution operation to fill the silent periods within the speech conversation. Dynamic keystream generation mechanism is also introduced to enhance the correlation between plaintext and encrypted text. Various quality metrics analysis such as correlation, signal to noise ratio (SNR), differential attacks, spectral entropy, histogram analysis, keyspace and key sensitivity are carried out to evaluate the quality of the proposed algorithm. The simulation results and numerical analyses demonstrate that the proposed algorithm has excellent security performance and robust against various cryptographic attacks.

The purpose of this paper is to examine the structural and computational potentials of a powerful class of neural networks (NNs), called multiple-valued logic neural networks (MVLNN), for predicting the behavior of phenomenological systems with highly nonlinear dynamics. MVLNNs are constructed based on the integration of a number of neurons working based on the principle of multiple-valued logics. MVLNNs possess some particular features, namely complex-valued weights, input, and outputs coded by kth roots of unity, and a continuous activation as a mean for transferring numbers from complex spaces to trigonometric spaces, which distinguish them from most of the existing NNs.

The presented study can be categorized into three sections. At the first part, the authors attempt at providing the mathematical formulations required for the implementation of ARX-based MVLNN (AMVLNN). In this context, it is indicated that how the concept of ARX can be used to revise the structure of MVLNN for online applications. Besides, the stepwise formulation for the simulation of Chua’s oscillatory map and multiple-valued logic-based BP are given. Through an analysis, some interesting characteristics of the Chua’s map, including a number of possible attractors of the state and sequences generated as a function of time, are given.

Based on a throughout simulation as well as a comprehensive numerical comparative study, some important features of AMVLNN are demonstrated. The simulation results indicate that AMVLNN can be employed as a tool for the online identification of highly nonlinear dynamic systems. Furthermore, the results show the compatibility of the Chua’s oscillatory system with BP for an effective tuning of the synaptic weights. The results also unveil the potentials of AMVLNN as a fast, robust, and efficient control-oriented model at the heart of NMPC control schemes.

This study presents two innovative propositions. First, the structure of MVLNN is modified based on the concept of ARX system identification programming to suit the base structure for coping with chaotic and highly nonlinear systems. Second, the authors share the findings about the learning characteristics of MVLNNs. Through an exhaustive comparative study and considering different rival methodologies, a novel and efficient double-stage learning strategy is proposed which remarkably improves the performance of MVLNNs. Finally, the authors describe the outline of a novel formulation which prepares the proposed AMVLNN for applications in NMPC controllers for dynamic systems.

The purpose of this paper is to investigate the performance of chaotic gravitational search algorithm (CGSA) in solving mechanical engineering design frameworks including welded beam design (WBD), compression spring design (CSD) and pressure vessel design (PVD).

In this study, ten chaotic maps were combined with gravitational constant to increase the exploitation power of gravitational search algorithm (GSA). Also, CGSA has been used for maintaining the adaptive capability of gravitational constant. Furthermore, chaotic maps were used for overcoming premature convergence and stagnation in local minima problems of standard GSA.

The chaotic maps have shown efficient performance for WBD and PVD problems. Further, they have depicted competitive results for CSD framework. Moreover, the experimental results indicate that CGSA shows efficient performance in terms of convergence speed, cost function minimization, design variable optimization and successful constraint handling as compared to other participating algorithms.

The use of chaotic maps in standard GSA is a new beginning for research in GSA particularly convergence and time complexity analysis. Moreover, CGSA can be used for solving the infinite impulsive response (IIR) parameter tuning and economic load dispatch problems in electrical sciences.

The hybridization of chaotic maps and evolutionary algorithms for solving practical engineering problems is an emerging topic in metaheuristics. In the literature, it can be seen that researchers have used some chaotic maps such as a logistic map, Gauss map and a sinusoidal map more rigorously than other maps. However, this work uses ten different chaotic maps for engineering design optimization. In addition, non-parametric statistical test, namely, Wilcoxon rank-sum test, was carried out at 5% significance level to statistically validate the simulation results. Besides, 11 state-of-the-art metaheuristic algorithms were used for comparative analysis of the experimental results to further raise the authenticity of the experimental setup.

It has been well known that the quantum zero‐point energy (ZPE) cannot be conserved in simulations of atoms and molecules dynamics based on classical mechanics. The purpose of this paper is to examine fundamental issues related to the treatment of quantum ZPE constraint in simulations of atoms and molecules dynamics.

The ZPE is well known to be a quantum mechanical expectation value that is equivalent to an ensemble average when this value is interpreted to classical mechanics. An important point is that the ensemble‐averaged energies on simulations are expected to obey the ZPE criteria rather than those of individual simulation. The point is elucidated using quasiclassical trajectory calculations with a popular hydrogen atom‐diatom direct collision process incorporating a potential energy surface of a triatomic hydrogen system.

The results obtained by using standard classical trajectory calculations agree well with the quantum calculations. Using them, the author found that the classical results remain valid even if some trajectory calculations have vibrational energies that are less than the ZPE.

It is found that the ensemble‐average of each trajectory calculation can provide results that are consistent with quantum mechanical ones that obey the ZPE criteria, without the introduction of any additional constraint conditions for atoms and simulation algorithms.

The results of five experiments on design of work stations are discussed. The first two experiments investigated the effects of work surface height on performance, the third investigated eye‐hand coordination at two heights and directions of movement, the fourth investigated both height and direction of movement, and the fifth studied the effect of angle and direction (in versus out) of movement. It was found that the optimum height is about one inch below the elbow. The effect of angle at a height is important: the best moves for a right‐hand movement are at 45 degrees.

Barriers, especially non‐tariff barriers (NTBs), have been shown to have an important impact upon international trade in services. Foreign direct investment and market entry strategy theory do not adequately address the importance of NTBs in the decision‐making process. Previous studies indicate that service firms need to establish local presence to be successful in a foreign market. Where firms are unable to enter a market because it is blocked by trade barriers, some researchers suggest managers engage in specific entry strategies or strategic actions to overcome barriers. This study, based on in‐depth interviews with insurance executives, shows that trade barriers are one of several factors managers evaluate when deciding whether to enter a market. However, barriers can become a critical factor if they create prohibitive costs or difficulties. Based on the findings, this study proposes a new model of market entry decision making which hypothesizes that barriers can become a go/no‐go decision factor.