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Entropy, Volume 19, Issue 1 (January 2017)

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Description What are the chemical and physical conditions that make the emergence of life possible? One of the [...] Read more.
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Editorial

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Open AccessEditorial Information and Self-Organization
Entropy 2017, 19(1), 18; doi:10.3390/e19010018
Received: 22 December 2016 / Revised: 26 December 2016 / Accepted: 27 December 2016 / Published: 31 December 2016
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Abstract The process of “self-organization” takes place in open and complex systems that acquire spatio-temporal or functional structures without specific ordering instructions from the outside. [...] Full article
(This article belongs to the Special Issue Information and Self-Organization)
Open AccessEditorial Acknowledgement to Reviewers of Entropy in 2016
Entropy 2017, 19(1), 28; doi:10.3390/e19010028
Received: 11 January 2017 / Accepted: 11 January 2017 / Published: 11 January 2017
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Abstract The editors of Entropy would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2016.[...] Full article

Research

Jump to: Editorial, Review, Other

Open AccessArticle Entropy Generation in Magnetohydrodynamic Mixed Convection Flow over an Inclined Stretching Sheet
Entropy 2017, 19(1), 10; doi:10.3390/e19010010
Received: 5 July 2016 / Revised: 26 September 2016 / Accepted: 28 September 2016 / Published: 28 December 2016
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Abstract
This research focuses on entropy generation rate per unit volume in magneto-hydrodynamic (MHD) mixed convection boundary layer flow of a viscous fluid over an inclined stretching sheet. Analysis has been performed in the presence of viscous dissipation and non-isothermal boundary conditions. The governing
[...] Read more.
This research focuses on entropy generation rate per unit volume in magneto-hydrodynamic (MHD) mixed convection boundary layer flow of a viscous fluid over an inclined stretching sheet. Analysis has been performed in the presence of viscous dissipation and non-isothermal boundary conditions. The governing boundary layer equations are transformed into ordinary differential equations by an appropriate similarity transformation. The transformed coupled nonlinear ordinary differential equations are then solved numerically by a shooting technique along with the Runge-Kutta method. Expressions for entropy generation (Ns) and Bejan number (Be) in the form of dimensionless variables are also obtained. Impact of various physical parameters on the quantities of interest is seen. Full article
(This article belongs to the Special Issue Advances in Applied Thermodynamics II)
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Open AccessArticle Information Decomposition in Multivariate Systems: Definitions, Implementation and Application to Cardiovascular Networks
Entropy 2017, 19(1), 5; doi:10.3390/e19010005
Received: 21 November 2016 / Revised: 14 December 2016 / Accepted: 19 December 2016 / Published: 24 December 2016
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Abstract
The continuously growing framework of information dynamics encompasses a set of tools, rooted in information theory and statistical physics, which allow to quantify different aspects of the statistical structure of multivariate processes reflecting the temporal dynamics of complex networks. Building on the most
[...] Read more.
The continuously growing framework of information dynamics encompasses a set of tools, rooted in information theory and statistical physics, which allow to quantify different aspects of the statistical structure of multivariate processes reflecting the temporal dynamics of complex networks. Building on the most recent developments in this field, this work designs a complete approach to dissect the information carried by the target of a network of multiple interacting systems into the new information produced by the system, the information stored in the system, and the information transferred to it from the other systems; information storage and transfer are then further decomposed into amounts eliciting the specific contribution of assigned source systems to the target dynamics, and amounts reflecting information modification through the balance between redundant and synergetic interaction between systems. These decompositions are formulated quantifying information either as the variance or as the entropy of the investigated processes, and their exact computation for the case of linear Gaussian processes is presented. The theoretical properties of the resulting measures are first investigated in simulations of vector autoregressive processes. Then, the measures are applied to assess information dynamics in cardiovascular networks from the variability series of heart period, systolic arterial pressure and respiratory activity measured in healthy subjects during supine rest, orthostatic stress, and mental stress. Our results document the importance of combining the assessment of information storage, transfer and modification to investigate common and complementary aspects of network dynamics; suggest the higher specificity to alterations in the network properties of the measures derived from the decompositions; and indicate that measures of information transfer and information modification are better assessed, respectively, through entropy-based and variance-based implementations of the framework. Full article
(This article belongs to the Special Issue Multivariate Entropy Measures and Their Applications)
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Open AccessArticle A Sequence of Escort Distributions and Generalizations of Expectations on q-Exponential Family
Entropy 2017, 19(1), 7; doi:10.3390/e19010007
Received: 26 October 2016 / Revised: 16 December 2016 / Accepted: 19 December 2016 / Published: 25 December 2016
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Abstract
In the theory of complex systems, long tailed probability distributions are often discussed. For such a probability distribution, a deformed expectation with respect to an escort distribution is more useful than the standard expectation. In this paper, by generalizing such escort distributions, a
[...] Read more.
In the theory of complex systems, long tailed probability distributions are often discussed. For such a probability distribution, a deformed expectation with respect to an escort distribution is more useful than the standard expectation. In this paper, by generalizing such escort distributions, a sequence of escort distributions is introduced. As a consequence, it is shown that deformed expectations with respect to sequential escort distributions effectively work for anomalous statistics. In particular, it is shown that a Fisher metric on a q-exponential family can be obtained from the escort expectation with respect to the second escort distribution, and a cubic form (or an Amari–Chentsov tensor field, equivalently) is obtained from the escort expectation with respect to the third escort distribution. Full article
(This article belongs to the Special Issue Differential Geometrical Theory of Statistics)
Open AccessArticle Maximum Entropy Models for Quantum Systems
Entropy 2017, 19(1), 1; doi:10.3390/e19010001
Received: 28 October 2016 / Revised: 3 December 2016 / Accepted: 19 December 2016 / Published: 22 December 2016
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Abstract
We show that for a finite von Neumann algebra, the states that maximise Segal’s entropy with a given energy level are Gibbs states. This is a counterpart of the classical result for the algebra of all bounded linear operators on a Hilbert space
[...] Read more.
We show that for a finite von Neumann algebra, the states that maximise Segal’s entropy with a given energy level are Gibbs states. This is a counterpart of the classical result for the algebra of all bounded linear operators on a Hilbert space and von Neumann entropy. Full article
Open AccessArticle Nonlinear Relaxation Phenomena in Metastable Condensed Matter Systems
Entropy 2017, 19(1), 20; doi:10.3390/e19010020
Received: 12 November 2016 / Revised: 22 December 2016 / Accepted: 25 December 2016 / Published: 31 December 2016
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Abstract
Nonlinear relaxation phenomena in three different systems of condensed matter are investigated. (i) First, the phase dynamics in Josephson junctions is analyzed. Specifically, a superconductor-graphene-superconductor (SGS) system exhibits quantum metastable states, and the average escape time from these metastable states in the presence
[...] Read more.
Nonlinear relaxation phenomena in three different systems of condensed matter are investigated. (i) First, the phase dynamics in Josephson junctions is analyzed. Specifically, a superconductor-graphene-superconductor (SGS) system exhibits quantum metastable states, and the average escape time from these metastable states in the presence of Gaussian and correlated fluctuations is calculated, accounting for variations in the the noise source intensity and the bias frequency. Moreover, the transient dynamics of a long-overlap Josephson junction (JJ) subject to thermal fluctuations and non-Gaussian noise sources is investigated. Noise induced phenomena are observed, such as the noise enhanced stability and the stochastic resonant activation. (ii) Second, the electron spin relaxation process in a n-type GaAs bulk driven by a fluctuating electric field is investigated. In particular, by using a Monte Carlo approach, we study the influence of a random telegraph noise on the spin polarized transport. Our findings show the possibility to raise the spin relaxation length by increasing the amplitude of the external fluctuations. Moreover, we find that, crucially, depending on the value of the external field strength, the electron spin depolarization length versus the noise correlation time increases up to a plateau. (iii) Finally, the stabilization of quantum metastable states by dissipation is presented. Normally, quantum fluctuations enhance the escape from metastable states in the presence of dissipation. We show that dissipation can enhance the stability of a quantum metastable system, consisting of a particle moving in a strongly asymmetric double well potential, interacting with a thermal bath. We find that the escape time from the metastable region has a nonmonotonic behavior versus the system- bath coupling and the temperature, producing a stabilizing effect. Full article
(This article belongs to the Special Issue Nonequilibrium Phenomena in Confined Systems)
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Open AccessArticle A Multivariate Multiscale Fuzzy Entropy Algorithm with Application to Uterine EMG Complexity Analysis
Entropy 2017, 19(1), 2; doi:10.3390/e19010002
Received: 25 October 2016 / Revised: 15 December 2016 / Accepted: 19 December 2016 / Published: 22 December 2016
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Abstract
The recently introduced multivariate multiscale entropy (MMSE) has been successfully used to quantify structural complexity in terms of nonlinear within- and cross-channel correlations as well as to reveal complex dynamical couplings and various degrees of synchronization over multiple scales in real-world multichannel data.
[...] Read more.
The recently introduced multivariate multiscale entropy (MMSE) has been successfully used to quantify structural complexity in terms of nonlinear within- and cross-channel correlations as well as to reveal complex dynamical couplings and various degrees of synchronization over multiple scales in real-world multichannel data. However, the applicability of MMSE is limited by the coarse-graining process which defines scales, as it successively reduces the data length for each scale and thus yields inaccurate and undefined entropy estimates at higher scales and for short length data. To that cause, we propose the multivariate multiscale fuzzy entropy (MMFE) algorithm and demonstrate its superiority over the MMSE on both synthetic as well as real-world uterine electromyography (EMG) short duration signals. Based on MMFE features, an improvement in the classification accuracy of term-preterm deliveries was achieved, with a maximum area under the curve (AUC) value of 0.99. Full article
(This article belongs to the Special Issue Multivariate Entropy Measures and Their Applications)
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Open AccessArticle Misalignment Fault Diagnosis of DFWT Based on IEMD Energy Entropy and PSO-SVM
Entropy 2017, 19(1), 6; doi:10.3390/e19010006
Received: 27 September 2016 / Revised: 17 November 2016 / Accepted: 30 November 2016 / Published: 1 January 2017
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Abstract
Misalignment is an important cause for the early failure of large doubly-fed wind turbines (DFWT). For the non-stationary characteristics of the signals in the transmission system of DFWT and the reality that it is difficult to obtain a large number of fault samples,
[...] Read more.
Misalignment is an important cause for the early failure of large doubly-fed wind turbines (DFWT). For the non-stationary characteristics of the signals in the transmission system of DFWT and the reality that it is difficult to obtain a large number of fault samples, Solidworks and Adams are used to simulate the different operating conditions of the transmission system of the DFWT to obtain the corresponding characteristic signals. Improved empirical mode decomposition (IEMD), which improves the end effects of empirical mode decomposition (EMD) is used to decompose the signals to get intrinsic mode function (IMF), and the IEMD energy entropy reflecting the working state are extracted as the inputs of the support vector machine (SVM). Particle swarm optimization (PSO) is used to optimize the parameters of SVM to improve the classification performance. The results show that the proposed method can effectively and accurately identify the types of misalignment of the DFWT. Full article
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Open AccessArticle Active and Purely Dissipative Nambu Systems in General Thermostatistical Settings Described by Nonlinear Partial Differential Equations Involving Generalized Entropy Measures
Entropy 2017, 19(1), 8; doi:10.3390/e19010008
Received: 30 October 2016 / Revised: 16 December 2016 / Accepted: 22 December 2016 / Published: 27 December 2016
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Abstract
In physics, several attempts have been made to apply the concepts and tools of physics to the life sciences. In this context, a thermostatistic framework for active Nambu systems is proposed. The so-called free energy Fokker–Planck equation approach is used to describe stochastic
[...] Read more.
In physics, several attempts have been made to apply the concepts and tools of physics to the life sciences. In this context, a thermostatistic framework for active Nambu systems is proposed. The so-called free energy Fokker–Planck equation approach is used to describe stochastic aspects of active Nambu systems. Different thermostatistic settings are considered that are characterized by appropriately-defined entropy measures, such as the Boltzmann–Gibbs–Shannon entropy and the Tsallis entropy. In general, the free energy Fokker–Planck equations associated with these generalized entropy measures correspond to nonlinear partial differential equations. Irrespective of the entropy-related nonlinearities occurring in these nonlinear partial differential equations, it is shown that semi-analytical solutions for the stationary probability densities of the active Nambu systems can be obtained provided that the pumping mechanisms of the active systems assume the so-called canonical-dissipative form and depend explicitly only on Nambu invariants. Applications are presented both for purely-dissipative and for active systems illustrating that the proposed framework includes as a special case stochastic equilibrium systems. Full article
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Open AccessArticle Quantum Key Distribution in the Presence of the Intercept-Resend with Faked States Attack
Entropy 2017, 19(1), 4; doi:10.3390/e19010004
Received: 3 November 2016 / Revised: 15 December 2016 / Accepted: 19 December 2016 / Published: 23 December 2016
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Abstract
Despite the unconditionally secure theory of the Quantum Key Distribution (QKD), several attacks have been successfully implemented against commercial QKD systems. Those systems have exhibited some flaws, as the secret key rate of corresponding protocols remains unaltered,
[...] Read more.
Despite the unconditionally secure theory of the Quantum Key Distribution (Q K D), several attacks have been successfully implemented against commercial Q K D systems. Those systems have exhibited some flaws, as the secret key rate of corresponding protocols remains unaltered, while the eavesdropper obtains the entire secret key. We propose the negative acknowledgment state quantum key distribution protocol as a novel protocol capable of detecting the eavesdropping activity of the Intercept Resend with Faked Sates (I R F S) attack without requiring additional optical components different from the B B 84 protocol because the system can be implemented as a high software module. In this approach, the transmitter interleaves pairs of quantum states, referred to here as parallel and orthogonal states, while the receiver uses active basis selection. Full article
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Open AccessArticle Echo State Condition at the Critical Point
Entropy 2017, 19(1), 3; doi:10.3390/e19010003
Received: 29 October 2016 / Revised: 13 December 2016 / Accepted: 15 December 2016 / Published: 23 December 2016
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Abstract
Recurrent networks with transfer functions that fulfil the Lipschitz continuity with K=1 may be echo state networks if certain limitations on the recurrent connectivity are applied. It has been shown that it is sufficient if the largest singular value of the
[...] Read more.
Recurrent networks with transfer functions that fulfil the Lipschitz continuity with K = 1 may be echo state networks if certain limitations on the recurrent connectivity are applied. It has been shown that it is sufficient if the largest singular value of the recurrent connectivity is smaller than 1. The main achievement of this paper is a proof under which conditions the network is an echo state network even if the largest singular value is one. It turns out that in this critical case the exact shape of the transfer function plays a decisive role in determining whether the network still fulfills the echo state condition. In addition, several examples with one-neuron networks are outlined to illustrate effects of critical connectivity. Moreover, within the manuscript a mathematical definition for a critical echo state network is suggested. Full article
(This article belongs to the Special Issue Complexity, Criticality and Computation (C³))
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Open AccessArticle A Dissipation of Relative Entropy by Diffusion Flows
Entropy 2017, 19(1), 9; doi:10.3390/e19010009
Received: 5 October 2016 / Revised: 18 December 2016 / Accepted: 22 December 2016 / Published: 27 December 2016
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Abstract
Given a probability measure, we consider the diffusion flows of probability measures associated with the partial differential equation (PDE) of Fokker–Planck. Our flows of the probability measures are defined as the solution of the Fokker–Planck equation for the same strictly convex potential, which
[...] Read more.
Given a probability measure, we consider the diffusion flows of probability measures associated with the partial differential equation (PDE) of Fokker–Planck. Our flows of the probability measures are defined as the solution of the Fokker–Planck equation for the same strictly convex potential, which means that the flows have the same equilibrium. Then, we shall investigate the time derivative for the relative entropy in the case where the object and the reference measures are moving according to the above diffusion flows, from which we can obtain a certain dissipation formula and also an integral representation of the relative entropy. Full article
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Open AccessArticle Univariate and Multivariate Generalized Multiscale Entropy to Characterise EEG Signals in Alzheimer’s Disease
Entropy 2017, 19(1), 31; doi:10.3390/e19010031
Received: 29 October 2016 / Revised: 22 December 2016 / Accepted: 9 January 2017 / Published: 12 January 2017
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Abstract
Alzheimer’s disease (AD) is a degenerative brain disorder leading to memory loss and changes in other cognitive abilities. The complexity of electroencephalogram (EEG) signals may help to characterise AD. To this end, we propose an extension of multiscale entropy based on variance (MSE
[...] Read more.
Alzheimer’s disease (AD) is a degenerative brain disorder leading to memory loss and changes in other cognitive abilities. The complexity of electroencephalogram (EEG) signals may help to characterise AD. To this end, we propose an extension of multiscale entropy based on variance (MSEσ2) to multichannel signals, termed multivariate MSEσ2 (mvMSEσ2), to take into account both the spatial and time domains of time series. Then, we investigate the mvMSEσ2 of EEGs at different frequency bands, including the broadband signals filtered between 1 and 40 Hz, θ, α, and β bands, and compare it with the previously-proposed multiscale entropy based on mean (MSEµ), multivariate MSEµ (mvMSEµ), and MSEσ2, to distinguish different kinds of dynamical properties of the spread and the mean in the signals. Results from 11 AD patients and 11 age-matched controls suggest that the presence of broadband activity of EEGs is required for a proper evaluation of complexity. MSEσ2 and mvMSEσ2 results, showing a loss of complexity in AD signals, led to smaller p-values in comparison with MSEµ and mvMSEµ ones, suggesting that the variance-based MSE and mvMSE can characterise changes in EEGs as a result of AD in a more detailed way. The p-values for the slope values of the mvMSE curves were smaller than for MSE at large scale factors, also showing the possible usefulness of multivariate techniques. Full article
(This article belongs to the Special Issue Multivariate Entropy Measures and Their Applications)
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Open AccessArticle A Cloud Theory-Based Trust Computing Model in Social Networks
Entropy 2017, 19(1), 11; doi:10.3390/e19010011
Received: 4 November 2016 / Revised: 19 December 2016 / Accepted: 22 December 2016 / Published: 28 December 2016
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Abstract
How to develop a trust management model and then to efficiently control and manage nodes is an important issue in the scope of social network security. In this paper, a trust management model based on a cloud model is proposed. The cloud model
[...] Read more.
How to develop a trust management model and then to efficiently control and manage nodes is an important issue in the scope of social network security. In this paper, a trust management model based on a cloud model is proposed. The cloud model uses a specific computation operator to achieve the transformation from qualitative concepts to quantitative computation. Additionally, this can also be used to effectively express the fuzziness, randomness and the relationship between them of the subjective trust. The node trust is divided into reputation trust and transaction trust. In addition, evaluation methods are designed, respectively. Firstly, the two-dimension trust cloud evaluation model is designed based on node’s comprehensive and trading experience to determine the reputation trust. The expected value reflects the average trust status of nodes. Then, entropy and hyper-entropy are used to describe the uncertainty of trust. Secondly, the calculation methods of the proposed direct transaction trust and the recommendation transaction trust involve comprehensively computation of the transaction trust of each node. Then, the choosing strategies were designed for node to trade based on trust cloud. Finally, the results of a simulation experiment in P2P network file sharing on an experimental platform directly reflect the objectivity, accuracy and robustness of the proposed model, and could also effectively identify the malicious or unreliable service nodes in the system. In addition, this can be used to promote the service reliability of the nodes with high credibility, by which the stability of the whole network is improved. Full article
(This article belongs to the Section Information Theory)
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Open AccessArticle Perturbative Treatment of the Non-Linear q-Schrödinger and q-Klein–Gordon Equations
Entropy 2017, 19(1), 21; doi:10.3390/e19010021
Received: 5 November 2016 / Revised: 28 December 2016 / Accepted: 29 December 2016 / Published: 31 December 2016
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Abstract
Interesting non-linear generalization of both Schrödinger’s and Klein–Gordon’s equations have been recently advanced by Tsallis, Rego-Monteiro and Tsallis (NRT) in Nobre et al. (Phys. Rev. Lett. 2011, 106, 140601). There is much current activity going on in this area. The non-linearity is
[...] Read more.
Interesting non-linear generalization of both Schrödinger’s and Klein–Gordon’s equations have been recently advanced by Tsallis, Rego-Monteiro and Tsallis (NRT) in Nobre et al. (Phys. Rev. Lett. 2011, 106, 140601). There is much current activity going on in this area. The non-linearity is governed by a real parameter q. Empiric hints suggest that the ensuing non-linear q-Schrödinger and q-Klein–Gordon equations are a natural manifestations of very high energy phenomena, as verified by LHC-experiments. This happens for q values close to unity (Plastino et al. (Nucl. Phys. A 2016, 955, 16–26, Nucl. Phys. A 2016, 948, 19–27)). It might thus be difficult for q-values close to unity to ascertain whether one is dealing with solutions to the ordinary Schrödinger equation (whose free particle solutions are exponentials and for which q = 1 ) or with its NRT non-linear q-generalizations, whose free particle solutions are q-exponentials. In this work, we provide a careful analysis of the q 1 instance via a perturbative analysis of the NRT equations. Full article
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Open AccessArticle Transfer Learning for SSVEP Electroencephalography Based Brain–Computer Interfaces Using Learn++.NSE and Mutual Information
Entropy 2017, 19(1), 41; doi:10.3390/e19010041
Received: 30 November 2016 / Revised: 29 December 2016 / Accepted: 17 January 2017 / Published: 19 January 2017
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Abstract
Brain–Computer Interfaces (BCI) using Steady-State Visual Evoked Potentials (SSVEP) are sometimes used by injured patients seeking to use a computer. Canonical Correlation Analysis (CCA) is seen as state-of-the-art for SSVEP BCI systems. However, this assumes that the user has full control over their
[...] Read more.
Brain–Computer Interfaces (BCI) using Steady-State Visual Evoked Potentials (SSVEP) are sometimes used by injured patients seeking to use a computer. Canonical Correlation Analysis (CCA) is seen as state-of-the-art for SSVEP BCI systems. However, this assumes that the user has full control over their covert attention, which may not be the case. This introduces high calibration requirements when using other machine learning techniques. These may be circumvented by using transfer learning to utilize data from other participants. This paper proposes a combination of ensemble learning via Learn++ for Nonstationary Environments (Learn++.NSE)and similarity measures such as mutual information to identify ensembles of pre-existing data that result in higher classification. Results show that this approach performed worse than CCA in participants with typical SSVEP responses, but outperformed CCA in participants whose SSVEP responses violated CCA assumptions. This indicates that similarity measures and Learn++.NSE can introduce a transfer learning mechanism to bring SSVEP system accessibility to users unable to control their covert attention. Full article
(This article belongs to the Special Issue Entropy and Electroencephalography II)
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Open AccessArticle Intermittent Motion, Nonlinear Diffusion Equation and Tsallis Formalism
Entropy 2017, 19(1), 42; doi:10.3390/e19010042
Received: 25 November 2016 / Revised: 15 January 2017 / Accepted: 17 January 2017 / Published: 21 January 2017
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Abstract
We investigate an intermittent process obtained from the combination of a nonlinear diffusion equation and pauses. We consider the porous media equation with reaction terms related to the rate of switching the particles from the diffusive mode to the resting mode or switching
[...] Read more.
We investigate an intermittent process obtained from the combination of a nonlinear diffusion equation and pauses. We consider the porous media equation with reaction terms related to the rate of switching the particles from the diffusive mode to the resting mode or switching them from the resting to the movement. The results show that in the asymptotic limit of small and long times, the spreading of the system is essentially governed by the diffusive term. The behavior exhibited for intermediate times depends on the rates present in the reaction terms. In this scenario, we show that, in the asymptotic limits, the distributions for this process are given by in terms of power laws which may be related to the q-exponential present in the Tsallis statistics. Furthermore, we also analyze a situation characterized by different diffusive regimes, which emerges when the diffusive term is a mixing of linear and nonlinear terms. Full article
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Open AccessArticle An Urban Cellular Automata Model for Simulating Dynamic States on a Local Scale
Entropy 2017, 19(1), 12; doi:10.3390/e19010012
Received: 30 September 2016 / Revised: 13 December 2016 / Accepted: 20 December 2016 / Published: 28 December 2016
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Abstract
In complex systems, flexibility and adaptability to changes are crucial to the systems’ dynamic stability and evolution. Such resilience requires that the system is able to respond to disturbances by self-organizing, which implies a certain level of entropy within the system. Dynamic states
[...] Read more.
In complex systems, flexibility and adaptability to changes are crucial to the systems’ dynamic stability and evolution. Such resilience requires that the system is able to respond to disturbances by self-organizing, which implies a certain level of entropy within the system. Dynamic states (static, cyclical/periodic, complex, and chaotic) reflect this generative capacity, and correlate with the level of entropy. For planning complex cities, we need to develop methods to guide such autonomous progress in an optimal manner. A classical apparatus, cellular automaton (CA), provides such a tool. Applications of CA help us to study temporal dynamics in self-organizing urban systems. By exploring the dynamic states of the model’s dynamics resulting from different border conditions it is possible to discover favorable set(s) of rules conductive to the self-organizing dynamics and enable the system’s recovery at the time of crises. Level of entropy is a relevant measurement for evaluation of these dynamic states. The 2-D urban cellular automaton model studied here is based on the microeconomic principle that similar urban activities are attracted to each other, especially in certain self-organizing areas, and that the local dynamics of these enclaves affect the dynamics of the urban region by channeling flows of information, goods and people. The results of the modeling experiment indicate that the border conditions have a major impact on the model’s dynamics generating various dynamic states of the system. Most importantly, it seemed that the model could simulate a favorable, complex dynamic state with medium entropy level which may refer to the continuous self-organization of the system. The model provides a tool for exploring and understanding the effects of boundary conditions in the planning process as various scenarios are tested: resulting dynamics of the system can be explored with such “planning rules” prior to decisions, helping to identify planning guidelines that will support the future evolution of these areas. Full article
(This article belongs to the Special Issue Entropy for Sustainable and Resilient Urban Future)
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Open AccessArticle Research Entropy Complexity about the Nonlinear Dynamic Delay Game Model
Entropy 2017, 19(1), 22; doi:10.3390/e19010022
Received: 9 November 2016 / Revised: 15 December 2016 / Accepted: 22 December 2016 / Published: 9 January 2017
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Abstract
Based on the research of domestic and foreign scholars, this paper has improved and established a double oligopoly market model of renewable energy, and analyzed the complex dynamic characteristics of a system based on entropy theory and chaos theory, such as equilibrium point,
[...] Read more.
Based on the research of domestic and foreign scholars, this paper has improved and established a double oligopoly market model of renewable energy, and analyzed the complex dynamic characteristics of a system based on entropy theory and chaos theory, such as equilibrium point, stability, Hopf bifurcation conditions, etc. This paper also studied and simulated the effects of the natural growth rate of energy and the single delay decision on the renewable energy system by minimizing the entropy of the system and reducing the system instability to a minimum, so that the degree of disorder within the system was reduced. The results show that with the increase of the natural growth rate of energy, the stability of the system is not affected, but the market demand of the oligopoly 1 is gradually reducing and the market demand of the oligopoly 2 is gradually increasing. At the same time, a single oligopoly making the time delay decision will affect the stability of the two oligopolies. With the increase of delay, the time required to reach the stable state will grow, and the system will eventually enter the Hopf bifurcation, thus the system will have its entropy increased and fall into an unstable state. Therefore, in the actual market of renewable energy, oligopolies should pay attention to the natural growth rate of energy and time delay, ensuring the stability of the game process and the orderliness of the system. Full article
(This article belongs to the Special Issue Complex Systems and Fractional Dynamics)
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Open AccessArticle Impact of Ambient Conditions of Arab Gulf Countries on the Performance of Gas Turbines Using Energy and Exergy Analysis
Entropy 2017, 19(1), 32; doi:10.3390/e19010032
Received: 28 October 2016 / Revised: 5 January 2017 / Accepted: 6 January 2017 / Published: 17 January 2017
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Abstract
In this paper, energy and exergy analysis of typical gas turbines is performed using average hourly temperature and relative humidity for selected Gulf cities located in Saudi Arabia, Kuwait, United Arab Emirates, Oman, Bahrain and Qatar. A typical gas turbine unit of 42
[...] Read more.
In this paper, energy and exergy analysis of typical gas turbines is performed using average hourly temperature and relative humidity for selected Gulf cities located in Saudi Arabia, Kuwait, United Arab Emirates, Oman, Bahrain and Qatar. A typical gas turbine unit of 42 MW is considered in this study. The electricity production, thermal efficiency, fuel consumption differences between the ISO conditions and actual conditions are determined for each city. The exergy efficiency and exergy destruction rates for the gas turbine unit and its components are also evaluated taking ISO conditions as reference conditions. The results indicate that the electricity production losses occur in all cities during the year, except in Dammam and Kuwait for the period between November and March. During a typical day, the variation of the power production can reach 4 MW. The rate of exergy destruction under the combined effect of temperature and humidity is significant in hot months reaching a maximum of 12 MW in July. The presented results show also that adding inlet cooling systems to the existing gas turbine units could be justified in hot periods. Other aspects, such as the economic and environmental ones, should also be investigated. Full article
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Open AccessArticle Use of Information Measures and Their Approximations to Detect Predictive Gene-Gene Interaction
Entropy 2017, 19(1), 23; doi:10.3390/e19010023
Received: 7 November 2016 / Revised: 23 December 2016 / Accepted: 31 December 2016 / Published: 7 January 2017
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Abstract
We reconsider the properties and relationships of the interaction information and its modified versions in the context of detecting the interaction of two SNPs for the prediction of a binary outcome when interaction information is positive. This property is called predictive interaction, and
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We reconsider the properties and relationships of the interaction information and its modified versions in the context of detecting the interaction of two SNPs for the prediction of a binary outcome when interaction information is positive. This property is called predictive interaction, and we state some new sufficient conditions for it to hold true. We also study chi square approximations to these measures. It is argued that interaction information is a different and sometimes more natural measure of interaction than the logistic interaction parameter especially when SNPs are dependent. We introduce a novel measure of predictive interaction based on interaction information and its modified version. In numerical experiments, which use copulas to model dependence, we study examples when the logistic interaction parameter is zero or close to zero for which predictive interaction is detected by the new measure, while it remains undetected by the likelihood ratio test. Full article
(This article belongs to the Special Issue Transfer Entropy II)
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Open AccessArticle Radiative Entropy Production along the Paludification Gradient in the Southern Taiga
Entropy 2017, 19(1), 43; doi:10.3390/e19010043
Received: 24 November 2016 / Revised: 13 January 2017 / Accepted: 17 January 2017 / Published: 21 January 2017
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Abstract
Entropy production (σ) is a measure of ecosystem and landscape stability in a changing environment. We calculated the σ in the radiation balance for a well-drained spruce forest, a paludified spruce forest, and a bog in the southern taiga of the
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Entropy production (σ) is a measure of ecosystem and landscape stability in a changing environment. We calculated the σ in the radiation balance for a well-drained spruce forest, a paludified spruce forest, and a bog in the southern taiga of the European part of Russia using long-term meteorological data. Though radiative σ depends both on surface temperature and absorbed radiation, the radiation effect in boreal ecosystems is much more important than the temperature effect. The dynamic of the incoming solar radiation was the main driver of the diurnal, seasonal, and intra-annual courses of σ for all ecosystems; the difference in ecosystem albedo was the second most important factor, responsible for seven-eighths of the difference in σ between the bog and forest in a warm period. Despite the higher productivity and the complex structure of the well-drained forest, the dynamics and sums of σ in two forests were very similar. Summer droughts had no influence on the albedo and σ efficiency of forests, demonstrating high self-regulation of the taiga forest ecosystems. On the contrary, a decreasing water supply significantly elevated the albedo and lowered the σ in bog. Bogs, being non-steady ecosystems, demonstrate unique thermodynamic behavior, which is fluctuant and strongly dependent on the moisture supply. Paludification of territories may result in increasing instability of the energy balance and entropy production in the landscape of the southern taiga. Full article
(This article belongs to the Special Issue Entropy in Landscape Ecology)
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Open AccessArticle Heuristic Approach to Understanding the Accumulation Process in Hydrothermal Pores
Entropy 2017, 19(1), 33; doi:10.3390/e19010033
Received: 25 November 2016 / Revised: 10 January 2017 / Accepted: 11 January 2017 / Published: 13 January 2017
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Abstract
One of the central questions of humankind is: which chemical and physical conditions are necessary to make life possible? In this “origin-of-life” context, formamide plays an important role, because it has been demonstrated that prebiotic molecules can be synthesized from concentrated formamide solutions.
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One of the central questions of humankind is: which chemical and physical conditions are necessary to make life possible? In this “origin-of-life” context, formamide plays an important role, because it has been demonstrated that prebiotic molecules can be synthesized from concentrated formamide solutions. Recently, it could be shown, using finite-element calculations combining thermophoresis and convection processes in hydrothermal pores, that sufficiently high formamide concentrations could be accumulated to form prebiotic molecules (Niether et al. (2016)). Depending on the initial formamide concentration, the aspect ratio of the pores, and the ambient temperature, formamide concentrations up to 85 wt % could be reached. The stationary calculations show an effective accumulation, only if the aspect ratio is above a certain threshold, and the corresponding transient studies display a sudden increase of the accumulation after a certain time. Neither of the observations were explained. In this work, we derive a simple heuristic model, which explains both phenomena. The physical idea of the approach is a comparison of the time to reach the top of the pore with the time to cross from the convective upstream towards the convective downstream. If the time to reach the top of the pore is shorter than the crossing time, the formamide molecules are flushed out of the pore. If the time is long enough, the formamide molecules can reach the downstream and accumulate at the bottom of the pore. Analysing the optimal aspect ratio as function of concentration, we find that, at a weight fraction of w = 0 . 5 , a minimal pore height is required for effective accumulation. At the same concentration, the transient calculations show a maximum of the accumulation rate. Full article
(This article belongs to the Special Issue Nonequilibrium Phenomena in Confined Systems)
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Open AccessArticle A Comparative Study of Empirical Mode Decomposition-Based Filtering for Impact Signal
Entropy 2017, 19(1), 13; doi:10.3390/e19010013
Received: 14 October 2016 / Revised: 4 December 2016 / Accepted: 27 December 2016 / Published: 29 December 2016
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Abstract
The Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) has been used to propose a new method for filtering time series originating from nonlinear systems. The filtering method is based on fuzzy entropy and a new waveform. A new waveform is defined
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The Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) has been used to propose a new method for filtering time series originating from nonlinear systems. The filtering method is based on fuzzy entropy and a new waveform. A new waveform is defined wherein Intrinsic Mode Functions (IMFs)—which are obtained by CEEMDAN algorithm—are firstly sorted in ascending order (the sorted IMFs is symmetric about center point, because at any point, the mean value of the envelope line defined by the local maxima and the local minima is zero), and the energy of the sorted IMFs are calculated, respectively. Finally, the new waveform with axial symmetry can be obtained. The complexity of the new waveform can be quantified by fuzzy entropy. The relevant modes (noisy signal modes and useful signal modes) can be identified by the difference between the fuzzy entropy of the new waveform and the next adjacent new waveform. To evaluate the filter performance, CEEMDAN and sample entropy, Ensemble Empirical Mode Decomposition (EEMD) and fuzzy entropy, and EEMD and sample entropy were used to filter the synthesizing signals with various levels of input signal-to-noise ratio (SNRin). In particular, this approach is successful in filtering impact signal. The results of the filtering are evaluated by a de-trended fluctuation analysis (DFA) algorithm, revised mean square error (RMSE), and revised signal-to-noise ratio (RSNR), respectively. The filtering results of simulated and impact signal show that the filtering method based on CEEMDAN and fuzzy entropy outperforms other signal filtering methods. Full article
(This article belongs to the Section Information Theory)
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Open AccessArticle Implementing Demons and Ratchets
Entropy 2017, 19(1), 34; doi:10.3390/e19010034
Received: 30 November 2016 / Revised: 5 January 2017 / Accepted: 6 January 2017 / Published: 14 January 2017
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Abstract
Experimental results show that ratchets may be implemented in semiconductor and chemical systems, bypassing the second law and opening up huge gains in energy production. This paper summarizes or describes experiments and results on systems that effect demons and ratchets operating in chemical
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Experimental results show that ratchets may be implemented in semiconductor and chemical systems, bypassing the second law and opening up huge gains in energy production. This paper summarizes or describes experiments and results on systems that effect demons and ratchets operating in chemical or electrical domains. One creates temperature differences that can be harvested by a heat engine. A second produces light with only heat input. A third produces harvestable electrical potential directly. These systems share creating particles in one location, destroying them in another and moving them between locations by diffusion (Brownian motion). All absorb ambient heat as they produce other energy forms. None requires an external hot and cold side. The economic and social impacts of these conversions of ambient heat to work are, of course, well-understood and huge. The experimental results beg for serious work on the chance that they are valid. Full article
(This article belongs to the Special Issue Limits to the Second Law of Thermodynamics: Experiment and Theory)
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Open AccessArticle Constructing a Measurement Method of Differences in Group Preferences Based on Relative Entropy
Entropy 2017, 19(1), 24; doi:10.3390/e19010024
Received: 13 November 2016 / Revised: 29 December 2016 / Accepted: 3 January 2017 / Published: 6 January 2017
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Abstract
In the research and data analysis of the differences involved in group preferences, conventional statistical methods cannot reflect the integrity and preferences of human minds; in particular, it is difficult to exclude humans’ irrational factors. This paper introduces a preference amount model based
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In the research and data analysis of the differences involved in group preferences, conventional statistical methods cannot reflect the integrity and preferences of human minds; in particular, it is difficult to exclude humans’ irrational factors. This paper introduces a preference amount model based on relative entropy theory. A related expansion is made based on the characteristics of the questionnaire data, and we also construct the parameters to measure differences in the data distribution of different groups on the whole. In this paper, this parameter is called the center distance, and it effectively reflects the preferences of human minds. Using the survey data of securities market participants as an example, this paper analyzes differences in market participants’ attitudes toward the effectiveness of securities regulation. Based on this method, differences between groups that were overlooked by analysis of variance are found, and certain aspects obscured by general data characteristics are also found. Full article
Open AccessArticle A New Feature Extraction Method Based on EEMD and Multi-Scale Fuzzy Entropy for Motor Bearing
Entropy 2017, 19(1), 14; doi:10.3390/e19010014
Received: 23 September 2016 / Revised: 3 December 2016 / Accepted: 26 December 2016 / Published: 31 December 2016
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Abstract
Feature extraction is one of the most important, pivotal, and difficult problems in mechanical fault diagnosis, which directly relates to the accuracy of fault diagnosis and the reliability of early fault prediction. Therefore, a new fault feature extraction method, called the EDOMFE method
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Feature extraction is one of the most important, pivotal, and difficult problems in mechanical fault diagnosis, which directly relates to the accuracy of fault diagnosis and the reliability of early fault prediction. Therefore, a new fault feature extraction method, called the EDOMFE method based on integrating ensemble empirical mode decomposition (EEMD), mode selection, and multi-scale fuzzy entropy is proposed to accurately diagnose fault in this paper. The EEMD method is used to decompose the vibration signal into a series of intrinsic mode functions (IMFs) with a different physical significance. The correlation coefficient analysis method is used to calculate and determine three improved IMFs, which are close to the original signal. The multi-scale fuzzy entropy with the ability of effective distinguishing the complexity of different signals is used to calculate the entropy values of the selected three IMFs in order to form a feature vector with the complexity measure, which is regarded as the inputs of the support vector machine (SVM) model for training and constructing a SVM classifier (EOMSMFD based on EDOMFE and SVM) for fulfilling fault pattern recognition. Finally, the effectiveness of the proposed method is validated by real bearing vibration signals of the motor with different loads and fault severities. The experiment results show that the proposed EDOMFE method can effectively extract fault features from the vibration signal and that the proposed EOMSMFD method can accurately diagnose the fault types and fault severities for the inner race fault, the outer race fault, and rolling element fault of the motor bearing. Therefore, the proposed method provides a new fault diagnosis technology for rotating machinery. Full article
(This article belongs to the Special Issue Wavelets, Fractals and Information Theory II)
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Open AccessArticle Crane Safety Assessment Method Based on Entropy and Cumulative Prospect Theory
Entropy 2017, 19(1), 44; doi:10.3390/e19010044
Received: 22 November 2016 / Revised: 30 December 2016 / Accepted: 16 January 2017 / Published: 21 January 2017
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Abstract
Assessing the safety status of cranes is an important problem. To overcome the inaccuracies and misjudgments in such assessments, this work describes a safety assessment method for cranes that combines entropy and cumulative prospect theory. Firstly, the proposed method transforms the set of
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Assessing the safety status of cranes is an important problem. To overcome the inaccuracies and misjudgments in such assessments, this work describes a safety assessment method for cranes that combines entropy and cumulative prospect theory. Firstly, the proposed method transforms the set of evaluation indices into an evaluation vector. Secondly, a decision matrix is then constructed from the evaluation vectors and evaluation standards, and an entropy-based technique is applied to calculate the index weights. Thirdly, positive and negative prospect value matrices are established from reference points based on the positive and negative ideal solutions. Thus, this enables the crane safety grade to be determined according to the ranked comprehensive prospect values. Finally, the safety status of four general overhead traveling crane samples is evaluated to verify the rationality and feasibility of the proposed method. The results demonstrate that the method described in this paper can precisely and reasonably reflect the safety status of a crane. Full article
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Open AccessArticle Similarity Theory Based Radial Turbine Performance and Loss Mechanism Comparison between R245fa and Air for Heavy-Duty Diesel Engine Organic Rankine Cycles
Entropy 2017, 19(1), 25; doi:10.3390/e19010025
Received: 13 November 2016 / Revised: 27 December 2016 / Accepted: 5 January 2017 / Published: 14 January 2017
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Abstract
Organic Rankine Cycles using radial turbines as expanders are considered as one of the most efficient technologies to convert heavy-duty diesel engine waste heat into useful work. Turbine similarity design based on the existing air turbine profiles is time saving. Due to totally
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Organic Rankine Cycles using radial turbines as expanders are considered as one of the most efficient technologies to convert heavy-duty diesel engine waste heat into useful work. Turbine similarity design based on the existing air turbine profiles is time saving. Due to totally different thermodynamic properties between organic fluids and air, its influence on turbine performance and loss mechanisms need to be analyzed. This paper numerically simulated a radial turbine under similar conditions between R245fa and air, and compared the differences of the turbine performance and loss mechanisms. Larger specific heat ratio of air leads to air turbine operating at higher pressure ratios. As R245fa gas constant is only about one-fifth of air gas constant, reduced rotating speeds of R245fa turbine are only 0.4-fold of those of air turbine, and reduced mass flow rates are about twice of those of air turbine. When using R245fa as working fluid, the nozzle shock wave losses decrease but rotor suction surface separation vortex losses increase, and eventually leads that isentropic efficiencies of R245fa turbine in the commonly used velocity ratio range from 0.5 to 0.9 are 3%–4% lower than those of air turbine. Full article
(This article belongs to the Special Issue Advances in Applied Thermodynamics II)
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Open AccessArticle Humans Outperform Machines at the Bilingual Shannon Game
Entropy 2017, 19(1), 15; doi:10.3390/e19010015
Received: 3 October 2016 / Revised: 8 December 2016 / Accepted: 27 December 2016 / Published: 30 December 2016
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Abstract
We provide an upper bound for the amount of information a human translator adds to an original text, i.e., how many bits of information we need to store a translation, given the original. We do this by creating a Bilingual Shannon Game that
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We provide an upper bound for the amount of information a human translator adds to an original text, i.e., how many bits of information we need to store a translation, given the original. We do this by creating a Bilingual Shannon Game that elicits character guesses from human subjects, then developing models to estimate the entropy of those guess sequences. Full article
(This article belongs to the Section Information Theory)
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Open AccessArticle Spacetime Topology and the Laws of Black Hole-Soliton Mechanics
Entropy 2017, 19(1), 35; doi:10.3390/e19010035
Received: 28 October 2016 / Revised: 8 January 2017 / Accepted: 12 January 2017 / Published: 17 January 2017
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Abstract
The domain of outer communication of an asymptotically flat spactime must be simply connected. In five dimensions, this still allows for the possibility of an arbitrary number of 2-cycles supported by magnetic flux carried by Maxwell fields. As a result, stationary, asymptotically flat,
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The domain of outer communication of an asymptotically flat spactime must be simply connected. In five dimensions, this still allows for the possibility of an arbitrary number of 2-cycles supported by magnetic flux carried by Maxwell fields. As a result, stationary, asymptotically flat, horizonless solutions—“gravitational solitons”—may exist with non-vanishing mass, charge, and angular momenta. These gravitational solutions satisfy a Smarr-like relation, as well as a first law of mechanics. Furthermore, the presence of solitons leads to new terms in the well-known first law of black hole mechanics for spacetimes containing black hole horizons and non-trivial topology in the exterior region. I outline the derivation of these results and consider an explicit example in five-dimensional supergravity. Full article
(This article belongs to the Special Issue Black Hole Thermodynamics II)
Open AccessArticle A Soft Parameter Function Penalized Normalized Maximum Correntropy Criterion Algorithm for Sparse System Identification
Entropy 2017, 19(1), 45; doi:10.3390/e19010045
Received: 9 December 2016 / Revised: 15 January 2017 / Accepted: 20 January 2017 / Published: 23 January 2017
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Abstract
A soft parameter function penalized normalized maximum correntropy criterion (SPF-NMCC) algorithm is proposed for sparse system identification. The proposed SPF-NMCC algorithm is derived on the basis of the normalized adaptive filter theory, the maximum correntropy criterion (MCC) algorithm and zero-attracting techniques. A soft
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A soft parameter function penalized normalized maximum correntropy criterion (SPF-NMCC) algorithm is proposed for sparse system identification. The proposed SPF-NMCC algorithm is derived on the basis of the normalized adaptive filter theory, the maximum correntropy criterion (MCC) algorithm and zero-attracting techniques. A soft parameter function is incorporated into the cost function of the traditional normalized MCC (NMCC) algorithm to exploit the sparsity properties of the sparse signals. The proposed SPF-NMCC algorithm is mathematically derived in detail. As a result, the proposed SPF-NMCC algorithm can provide an efficient zero attractor term to effectively attract the zero taps and near-zero coefficients to zero, and, hence, it can speed up the convergence. Furthermore, the estimation behaviors are obtained by estimating a sparse system and a sparse acoustic echo channel. Computer simulation results indicate that the proposed SPF-NMCC algorithm can achieve a better performance in comparison with the MCC, NMCC, LMS (least mean square) algorithms and their zero attraction forms in terms of both convergence speed and steady-state performance. Full article
(This article belongs to the Special Issue Entropy in Signal Analysis)
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Open AccessArticle One-Parameter Fisher–Rényi Complexity: Notion and Hydrogenic Applications
Entropy 2017, 19(1), 16; doi:10.3390/e19010016
Received: 27 September 2016 / Revised: 14 December 2016 / Accepted: 25 December 2016 / Published: 30 December 2016
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Abstract
In this work, the one-parameter Fisher–Rényi measure of complexity for general d-dimensional probability distributions is introduced and its main analytic properties are discussed. Then, this quantity is determined for the hydrogenic systems in terms of the quantum numbers of the quantum states
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In this work, the one-parameter Fisher–Rényi measure of complexity for general d-dimensional probability distributions is introduced and its main analytic properties are discussed. Then, this quantity is determined for the hydrogenic systems in terms of the quantum numbers of the quantum states and the nuclear charge. Full article
(This article belongs to the Section Information Theory)
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Open AccessArticle Exploitation of the Maximum Entropy Principle in Mathematical Modeling of Charge Transport in Semiconductors
Entropy 2017, 19(1), 36; doi:10.3390/e19010036
Received: 7 November 2016 / Revised: 4 January 2017 / Accepted: 5 January 2017 / Published: 18 January 2017
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Abstract
In the last two decades, the Maximum Entropy Principle (MEP) has been successfully employed to construct macroscopic models able to describe the charge and heat transport in semiconductor devices. These models are obtained, starting from the Boltzmann transport equations, for the charge and
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In the last two decades, the Maximum Entropy Principle (MEP) has been successfully employed to construct macroscopic models able to describe the charge and heat transport in semiconductor devices. These models are obtained, starting from the Boltzmann transport equations, for the charge and the phonon distribution functions, by taking—as macroscopic variables—suitable moments of the distributions and exploiting MEP in order to close the evolution equations for the chosen moments. Important results have also been obtained for the description of charge transport in devices made both of elemental and compound semiconductors, in cases where charge confinement is present and the carrier flow is two- or one-dimensional. Full article
(This article belongs to the Special Issue Maximum Entropy Principle and Semiconductors)
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Open AccessArticle Face Detection Based on Skin Color Segmentation Using Fuzzy Entropy
Entropy 2017, 19(1), 26; doi:10.3390/e19010026
Received: 14 November 2016 / Revised: 15 December 2016 / Accepted: 22 December 2016 / Published: 11 January 2017
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Abstract
Face detection is the first step of any automated face recognition system. One of the most popular approaches to detect faces in color images is using a skin color segmentation scheme, which in many cases needs a proper representation of color spaces to
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Face detection is the first step of any automated face recognition system. One of the most popular approaches to detect faces in color images is using a skin color segmentation scheme, which in many cases needs a proper representation of color spaces to interpret image information. In this paper, we propose a fuzzy system for detecting skin in color images, so that each color tone is assumed to be a fuzzy set. The Red, Green, and Blue (RGB), the Hue, Saturation and Value (HSV), and the YCbCr (where Y is the luminance and Cb,Cr are the chroma components) color systems are used for the development of our fuzzy design. Thus, a fuzzy three-partition entropy approach is used to calculate all of the parameters needed for the fuzzy systems, and then, a face detection method is also developed to validate the segmentation results. The results of the experiments show a correct skin detection rate between 94% and 96% for our fuzzy segmentation methods, with a false positive rate of about 0.5% in all cases. Furthermore, the average correct face detection rate is above 93%, and even when working with heterogeneous backgrounds and different light conditions, it achieves almost 88% correct detections. Thus, our method leads to accurate face detection results with low false positive and false negative rates. Full article
(This article belongs to the Section Information Theory)
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Open AccessArticle Evaluation Model of Aluminum Alloy Welded Joint Low-Cycle Fatigue Data Based on Information Entropy
Entropy 2017, 19(1), 37; doi:10.3390/e19010037
Received: 8 December 2016 / Revised: 10 January 2017 / Accepted: 16 January 2017 / Published: 18 January 2017
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Abstract
An evaluation model of aluminum alloy welded joint low-cycle fatigue data based on information entropy is proposed. Through calculating and analyzing the information entropy of decision attributes, quantitative contribution of stress concentration, plate thickness, and loading mode to the fatigue destruction are researched.
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An evaluation model of aluminum alloy welded joint low-cycle fatigue data based on information entropy is proposed. Through calculating and analyzing the information entropy of decision attributes, quantitative contribution of stress concentration, plate thickness, and loading mode to the fatigue destruction are researched. Results reveal that the total information entropy of the fatigue data based on nominal stress, structural stress and equivalent structural stress are, respectively, 0.9702, 0.8881, and 0.8294. There is consistency between the reducing trend of the weight-based information entropy and the smaller and smaller standard deviation of the S-N curves. In the structural stress based S-N curve, total stress concentration factor is crucial for the distribution of the fatigue data and the weight based information entropy of membrane stress concentration factor is 0.6754, which illustrates that stress concentration is a key issue of welded structure to which ought to be attached great importance. Subsequently, in the equivalent structural stress-based S-N curve, the weight based information entropy of stress ratio is 0.5759, which plays an important role in the distribution of fatigue data. With the importance level of the attributes on the S-N curves investigated, the correction of R in the equivalent structural stress based master S-N curve method should be carried out to make the welding fatigue prediction much more accurate. Full article
(This article belongs to the Section Information Theory)
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Open AccessArticle The Information Recovery Problem
Entropy 2017, 19(1), 17; doi:10.3390/e19010017
Received: 19 September 2016 / Revised: 6 December 2016 / Accepted: 27 December 2016 / Published: 30 December 2016
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Abstract
The issue of unitary evolution during creation and evaporation of a black hole remains controversial. We argue that some prominent cures are more troubling than the disease, demonstrate that their central element—forming of the event horizon before the evaporation begins—is not necessarily true,
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The issue of unitary evolution during creation and evaporation of a black hole remains controversial. We argue that some prominent cures are more troubling than the disease, demonstrate that their central element—forming of the event horizon before the evaporation begins—is not necessarily true, and describe a fully coupled matter-gravity system which is manifestly unitary. Full article
(This article belongs to the Special Issue Quantum Information 2016)
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Open AccessArticle A Probabilistic Damage Identification Method for Shear Structure Components Based on Cross-Entropy Optimizations
Entropy 2017, 19(1), 27; doi:10.3390/e19010027
Received: 10 October 2016 / Revised: 4 January 2017 / Accepted: 6 January 2017 / Published: 17 January 2017
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Abstract
A probabilistic damage identification method for shear structure components is presented. The method uses the extracted modal frequencies from the measured dynamical responses in conjunction with a representative finite element model. The damage of each component is modeled using a stiffness multiplier in
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A probabilistic damage identification method for shear structure components is presented. The method uses the extracted modal frequencies from the measured dynamical responses in conjunction with a representative finite element model. The damage of each component is modeled using a stiffness multiplier in the finite element model. By coupling the extracted features and the probabilistic structural model, the damage identification problem is recast to an equivalent optimization problem, which is iteratively solved using the cross-entropy optimization technique. An application example is used to demonstrate the proposed method and validate its effectiveness. Influencing factors such as the location of damaged components, measurement location, measurement noise level, and damage severity are studied. The detection reliability under different measurement noise levels is also discussed in detail. Full article
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Open AccessArticle Distributed Rateless Codes with Unequal Error Protection Property for Space Information Networks
Entropy 2017, 19(1), 38; doi:10.3390/e19010038
Received: 26 November 2016 / Revised: 16 January 2017 / Accepted: 16 January 2017 / Published: 18 January 2017
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Abstract
In this paper, we propose a novel distributed unequal error protection (UEP) rateless coding scheme (DURC) for space information networks (SIN). We consider the multimedia data transmissions in a dual-hop SIN communication scenario, where multiple disjoint source nodes need to transmit their UEP
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In this paper, we propose a novel distributed unequal error protection (UEP) rateless coding scheme (DURC) for space information networks (SIN). We consider the multimedia data transmissions in a dual-hop SIN communication scenario, where multiple disjoint source nodes need to transmit their UEP rateless coded data to a destination via a dynamic relay. We formulate the optimization problems to provide optimal degree distributions on the direct links and the dynamic relay links to satisfy the required error protection levels. The optimization methods are based on the And–Or tree analysis and can be solved by multi-objective programming. In addition, we evaluate the performance of the optimal DURC scheme, and simulation results show that the proposed DURC scheme can effectively provide UEP property under a variety of error requirements. Full article
(This article belongs to the Section Information Theory)
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Open AccessArticle Thermal Conductivity of Suspension of Aggregating Nanometric Rods
Entropy 2017, 19(1), 19; doi:10.3390/e19010019
Received: 10 November 2016 / Revised: 14 December 2016 / Accepted: 24 December 2016 / Published: 31 December 2016
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Abstract
Enhancing thermal conductivity of simple fluids is of major interest in numerous applicative systems. One possibility of enhancing thermal properties consists of dispersing small conductive particles inside. However, in general, aggregation effects occur and then one must address systems composed of dispersed clusters
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Enhancing thermal conductivity of simple fluids is of major interest in numerous applicative systems. One possibility of enhancing thermal properties consists of dispersing small conductive particles inside. However, in general, aggregation effects occur and then one must address systems composed of dispersed clusters composed of particles as well as the ones related to percolated networks. This papers analyzes the conductivity enhancement of different microstructures scaling from clusters dispersed into a simple matrix to the ones related to percolated networks exhibiting a fractal morphology. Full article
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Open AccessArticle Local Entropy Generation in Compressible Flow through a High Pressure Turbine with Delayed Detached Eddy Simulation
Entropy 2017, 19(1), 29; doi:10.3390/e19010029
Received: 11 November 2016 / Revised: 3 January 2017 / Accepted: 9 January 2017 / Published: 11 January 2017
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Abstract
Gas turbines are important energy-converting equipment in many industries. The flow inside gas turbines is very complicated and the knowledge about the flow loss mechanism is critical to the advanced design. The current design system heavily relies on empirical formulas or Reynolds Averaged
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Gas turbines are important energy-converting equipment in many industries. The flow inside gas turbines is very complicated and the knowledge about the flow loss mechanism is critical to the advanced design. The current design system heavily relies on empirical formulas or Reynolds Averaged Navier–Stokes (RANS), which faces big challenges in dealing with highly unsteady complex flow and accurately predicting flow losses. Further improving the efficiency needs more insights into the loss generation in gas turbines. Conventional Unsteady Reynolds Averaged Simulation (URANS) methods have defects in modeling multi-frequency, multi-length, highly unsteady flow, especially when mixing or separation occurs, while Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) are too costly for the high-Reynolds number flow. In this work, the Delayed Detached Eddy Simulation (DDES) method is used with a low-dissipation numerical scheme to capture the detailed flow structures of the complicated flow in a high pressure turbine guide vane. DDES accurately predicts the wake vortex behavior and produces much more details than RANS and URANS. The experimental findings of the wake vortex length characteristics, which RANS and URANS fail to predict, are successfully captured by DDES. Accurate flow simulation builds up a solid foundation for accurate losses prediction. Based on the detailed DDES results, loss analysis in terms of entropy generation rate is conducted from two aspects. The first aspect is to apportion losses by its physical resources: viscous irreversibility and heat transfer irreversibility. The viscous irreversibility is found to be much stronger than the heat transfer irreversibility in the flow. The second aspect is weighing the contributions of steady effects and unsteady effects. Losses due to unsteady effects account for a large part of total losses. Effects of unsteadiness should not be neglected in the flow physics study and design process. Full article
(This article belongs to the Special Issue Entropy in Computational Fluid Dynamics)
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Open AccessReview Nonequilibrium Thermodynamics of Ion Flux through Membrane Channels
Entropy 2017, 19(1), 40; doi:10.3390/e19010040
Received: 30 November 2016 / Revised: 17 January 2017 / Accepted: 18 January 2017 / Published: 19 January 2017
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Abstract
Ion flux through membrane channels is passively driven by the electrochemical potential differences across the cell membrane. Nonequilibrium thermodynamics has been successful in explaining transport mechanisms, including the ion transport phenomenon. However, physiologists may not be familiar with biophysical concepts based on the
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Ion flux through membrane channels is passively driven by the electrochemical potential differences across the cell membrane. Nonequilibrium thermodynamics has been successful in explaining transport mechanisms, including the ion transport phenomenon. However, physiologists may not be familiar with biophysical concepts based on the view of entropy production. In this paper, I have reviewed the physical meanings and connections between nonequilibrium thermodynamics and the expressions commonly used in describing ion fluxes in membrane physiology. The fluctuation theorem can be applied to interpret the flux ratio in the small molecular systems. The multi-ion single-file feature of the ion channel facilitates the utilization of the natural tendency of electrochemical driving force to couple specific biophysical processes and biochemical reactions on the membrane. Full article
(This article belongs to the Special Issue Advances in Applied Thermodynamics II)
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Open AccessReview Nonlinear q-Generalizations of Quantum Equations: Homogeneous and Nonhomogeneous Cases—An Overview
Entropy 2017, 19(1), 39; doi:10.3390/e19010039
Received: 15 December 2016 / Revised: 12 January 2017 / Accepted: 16 January 2017 / Published: 21 January 2017
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Abstract
Recent developments on the generalizations of two important equations of quantum physics, namely the Schroedinger and Klein–Gordon equations, are reviewed. These generalizations present nonlinear terms, characterized by exponents depending on an index q, in such a way that the standard linear equations
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Recent developments on the generalizations of two important equations of quantum physics, namely the Schroedinger and Klein–Gordon equations, are reviewed. These generalizations present nonlinear terms, characterized by exponents depending on an index q, in such a way that the standard linear equations are recovered in the limit q 1 . Interestingly, these equations present a common, soliton-like, traveling solution, which is written in terms of the q-exponential function that naturally emerges within nonextensive statistical mechanics. In both cases, the corresponding well-known Einstein energy-momentum relations, as well as the Planck and the de Broglie ones, are preserved for arbitrary values of q. In order to deal appropriately with the continuity equation, a classical field theory has been developed, where besides the usual Ψ ( x , t ) , a new field Φ ( x , t ) must be introduced; this latter field becomes Ψ * ( x , t ) only when q 1 . A class of linear nonhomogeneous Schroedinger equations, characterized by position-dependent masses, for which the extra field Φ ( x , t ) becomes necessary, is also investigated. In this case, an appropriate transformation connecting Ψ ( x , t ) and Φ ( x , t ) is proposed, opening the possibility for finding a connection between these fields in the nonlinear cases. The solutions presented herein are potential candidates for applications to nonlinear excitations in plasma physics, nonlinear optics, in structures, such as those of graphene, as well as in shallow and deep water waves. Full article
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Open AccessTechnical Note Comparing Relational and Ontological Triple Stores in Healthcare Domain
Entropy 2017, 19(1), 30; doi:10.3390/e19010030
Received: 8 December 2016 / Revised: 5 January 2017 / Accepted: 9 January 2017 / Published: 11 January 2017
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Abstract
Today’s technological improvements have made ubiquitous healthcare systems that converge into smart healthcare applications in order to solve patients’ problems, to communicate effectively with patients, and to improve healthcare service quality. The first step of building a smart healthcare information system is representing
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Today’s technological improvements have made ubiquitous healthcare systems that converge into smart healthcare applications in order to solve patients’ problems, to communicate effectively with patients, and to improve healthcare service quality. The first step of building a smart healthcare information system is representing the healthcare data as connected, reachable, and sharable. In order to achieve this representation, ontologies are used to describe the healthcare data. Combining ontological healthcare data with the used and obtained data can be maintained by storing the entire health domain data inside big data stores that support both relational and graph-based ontological data. There are several big data stores and different types of big data sets in the healthcare domain. The goal of this paper is to determine the most applicable ontology data store for storing the big healthcare data. For this purpose, AllegroGraph and Oracle 12c data stores are compared based on their infrastructural capacity, loading time, and query response times. Hence, healthcare ontologies (GENE Ontology, Gene Expression Ontology (GEXO), Regulation of Transcription Ontology (RETO), Regulation of Gene Expression Ontology (REXO)) are used to measure the ontology loading time. Thereafter, various queries are constructed and executed for GENE ontology in order to measure the capacity and query response times for the performance comparison between AllegroGraph and Oracle 12c triple stores. Full article
(This article belongs to the Section Information Theory)
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