Entropy

2443 KiB

Open AccessArticle

A Soft Parameter Function Penalized Normalized Maximum Correntropy Criterion Algorithm for Sparse System Identification

by Yingsong Li, Yanyan Wang, Rui Yang and Felix Albu

Entropy 2017, 19(1), 45; https://doi.org/10.3390/e19010045 - 23 Jan 2017

Cited by 63 | Viewed by 5983

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 [...] Read more.

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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985 KiB

Open AccessArticle

Crane Safety Assessment Method Based on Entropy and Cumulative Prospect Theory

by Aihua Li and Zhangyan Zhao

Entropy 2017, 19(1), 44; https://doi.org/10.3390/e19010044 - 21 Jan 2017

Cited by 16 | Viewed by 5903

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 [...] Read more.

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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7459 KiB

Open AccessArticle

Radiative Entropy Production along the Paludification Gradient in the Southern Taiga

by Olga Kuricheva, Vadim Mamkin, Robert Sandlersky, Juriy Puzachenko, Andrej Varlagin and Juliya Kurbatova

Entropy 2017, 19(1), 43; https://doi.org/10.3390/e19010043 - 21 Jan 2017

Cited by 12 | Viewed by 5227

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 [...] Read more.

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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940 KiB

Open AccessArticle

Intermittent Motion, Nonlinear Diffusion Equation and Tsallis Formalism

by Ervin K. Lenzi, Luciano R. Da Silva, Marcelo K. Lenzi, Maike A. F. Dos Santos, Haroldo V. Ribeiro and Luiz R. Evangelista

Entropy 2017, 19(1), 42; https://doi.org/10.3390/e19010042 - 21 Jan 2017

Cited by 11 | Viewed by 4665

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

(This article belongs to the Special Issue Entropic Aspects of Nonlinear Partial Differential Equations: Classical and Quantum Mechanical Perspectives)

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1615 KiB

Open AccessReview

Nonlinear q-Generalizations of Quantum Equations: Homogeneous and Nonhomogeneous Cases—An Overview

by Fernando D. Nobre, Marco Aurélio Rego-Monteiro and Constantino Tsallis

Entropy 2017, 19(1), 39; https://doi.org/10.3390/e19010039 - 21 Jan 2017

Cited by 10 | Viewed by 4052

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 [...] Read more.

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 \to 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 (\vec{x}, t)

, a new field

Φ (\vec{x}, t)

must be introduced; this latter field becomes

Ψ^{*} (\vec{x}, t)

only when

q \to 1

. A class of linear nonhomogeneous Schroedinger equations, characterized by position-dependent masses, for which the extra field

Φ (\vec{x}, t)

becomes necessary, is also investigated. In this case, an appropriate transformation connecting

Ψ (\vec{x}, t)

and

Φ (\vec{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

(This article belongs to the Special Issue Entropic Aspects of Nonlinear Partial Differential Equations: Classical and Quantum Mechanical Perspectives)

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515 KiB

Open AccessArticle

Transfer Learning for SSVEP Electroencephalography Based Brain–Computer Interfaces Using Learn++.NSE and Mutual Information

by Matthew Sybeldon, Lukas Schmit and Murat Akcakaya

Entropy 2017, 19(1), 41; https://doi.org/10.3390/e19010041 - 19 Jan 2017

Cited by 7 | Viewed by 5206

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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1228 KiB

Open AccessReview

Nonequilibrium Thermodynamics of Ion Flux through Membrane Channels

by Chi-Pan Hsieh

Entropy 2017, 19(1), 40; https://doi.org/10.3390/e19010040 - 19 Jan 2017

Cited by 3 | Viewed by 6328

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 [...] Read more.

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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641 KiB

Open AccessArticle

Distributed Rateless Codes with Unequal Error Protection Property for Space Information Networks

by Jian Jiao, Yi Yang, Bowen Feng, Shaohua Wu, Yonghui Li and Qinyu Zhang

Entropy 2017, 19(1), 38; https://doi.org/10.3390/e19010038 - 18 Jan 2017

Cited by 14 | Viewed by 4023

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 [...] Read more.

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, Probability and Statistics)

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4260 KiB

Open AccessArticle

Evaluation Model of Aluminum Alloy Welded Joint Low-Cycle Fatigue Data Based on Information Entropy

by Yaliang Liu, Li Zou, Yibo Sun and Xinhua Yang

Entropy 2017, 19(1), 37; https://doi.org/10.3390/e19010037 - 18 Jan 2017

Cited by 8 | Viewed by 4863

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. [...] Read more.

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, Probability and Statistics)

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2124 KiB

Open AccessArticle

Exploitation of the Maximum Entropy Principle in Mathematical Modeling of Charge Transport in Semiconductors

by Giovanni Mascali and Vittorio Romano

Entropy 2017, 19(1), 36; https://doi.org/10.3390/e19010036 - 18 Jan 2017

Cited by 28 | Viewed by 4506

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 [...] Read more.

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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390 KiB

Open AccessArticle

Spacetime Topology and the Laws of Black Hole-Soliton Mechanics

by Hari K. Kunduri

Entropy 2017, 19(1), 35; https://doi.org/10.3390/e19010035 - 17 Jan 2017

Viewed by 3543

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, [...] Read more.

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)

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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

by Saleh S. Baakeem, Jamel Orfi, Shaker Alaqel and Hany Al-Ansary

Entropy 2017, 19(1), 32; https://doi.org/10.3390/e19010032 - 17 Jan 2017

Cited by 12 | Viewed by 5326

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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446 KiB

Open AccessArticle

A Probabilistic Damage Identification Method for Shear Structure Components Based on Cross-Entropy Optimizations

by Xuefei Guan, Yongxiang Wang and Jingjing He

Entropy 2017, 19(1), 27; https://doi.org/10.3390/e19010027 - 17 Jan 2017

Cited by 13 | Viewed by 3623

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 [...] Read more.

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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8181 KiB

Open AccessArticle

Implementing Demons and Ratchets

by Peter M. Orem and Frank M. Orem

Entropy 2017, 19(1), 34; https://doi.org/10.3390/e19010034 - 14 Jan 2017

Cited by 3 | Viewed by 6928

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 [...] Read more.

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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29008 KiB

Open AccessArticle

by Lei Zhang, Weilin Zhuge, Yangjun Zhang and Tao Chen

Entropy 2017, 19(1), 25; https://doi.org/10.3390/e19010025 - 14 Jan 2017

Cited by 12 | Viewed by 7274

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 [...] Read more.

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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934 KiB

Open AccessArticle

Heuristic Approach to Understanding the Accumulation Process in Hydrothermal Pores

by Doreen Niether and Simone Wiegand

Entropy 2017, 19(1), 33; https://doi.org/10.3390/e19010033 - 13 Jan 2017

Cited by 10 | Viewed by 4979

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. [...] Read more.

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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2566 KiB

Open AccessArticle

Univariate and Multivariate Generalized Multiscale Entropy to Characterise EEG Signals in Alzheimer’s Disease

by Hamed Azami, Daniel Abásolo, Samantha Simons and Javier Escudero

Entropy 2017, 19(1), 31; https://doi.org/10.3390/e19010031 - 12 Jan 2017

Cited by 45 | Viewed by 7013

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 (MSE_σ²) to multichannel signals, termed multivariate MSE_σ² (mvMSE_σ²), to take into account both the spatial and time domains of time series. Then, we investigate the mvMSE_σ² 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 (MSE_µ), multivariate MSE_µ (mvMSE_µ), and MSE_σ², 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. MSE_σ² and mvMSE_σ² results, showing a loss of complexity in AD signals, led to smaller p-values in comparison with MSE_µ and mvMSE_µ 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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5553 KiB

Open AccessTechnical Note

Comparing Relational and Ontological Triple Stores in Healthcare Domain

by Ozgu Can, Emine Sezer, Okan Bursa and Murat Osman Unalir

Entropy 2017, 19(1), 30; https://doi.org/10.3390/e19010030 - 11 Jan 2017

Cited by 16 | Viewed by 6803

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 [...] Read more.

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, Probability and Statistics)

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Open AccessArticle

Local Entropy Generation in Compressible Flow through a High Pressure Turbine with Delayed Detached Eddy Simulation

by Dun Lin, Xin Yuan and Xinrong Su

Entropy 2017, 19(1), 29; https://doi.org/10.3390/e19010029 - 11 Jan 2017

Cited by 40 | Viewed by 7117

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 [...] Read more.

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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217 KiB

Open AccessEditorial

Acknowledgement to Reviewers of Entropy in 2016

by Entropy Editorial Office

Entropy 2017, 19(1), 28; https://doi.org/10.3390/e19010028 - 11 Jan 2017

Viewed by 4587

Abstract

The editors of Entropy would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2016.[...] Full article

5467 KiB

Open AccessArticle

Face Detection Based on Skin Color Segmentation Using Fuzzy Entropy

by Francisco A. Pujol, Mar Pujol, Antonio Jimeno-Morenilla and María José Pujol

Entropy 2017, 19(1), 26; https://doi.org/10.3390/e19010026 - 11 Jan 2017

Cited by 29 | Viewed by 8929

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 [...] Read more.

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, Probability and Statistics)

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Open AccessArticle

Research Entropy Complexity about the Nonlinear Dynamic Delay Game Model

by Xueli Zhan, Junhai Ma and Wenbo Ren

Entropy 2017, 19(1), 22; https://doi.org/10.3390/e19010022 - 09 Jan 2017

Cited by 5 | Viewed by 4470

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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418 KiB

Open AccessArticle

Use of Information Measures and Their Approximations to Detect Predictive Gene-Gene Interaction

by Jan Mielniczuk and Marcin Rdzanowski

Entropy 2017, 19(1), 23; https://doi.org/10.3390/e19010023 - 07 Jan 2017

Cited by 5 | Viewed by 5417

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 [...] Read more.

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

Constructing a Measurement Method of Differences in Group Preferences Based on Relative Entropy

by Shiyu Zhang, Wenzhi Liu, Qin He and Xuguang Hao

Entropy 2017, 19(1), 24; https://doi.org/10.3390/e19010024 - 06 Jan 2017

Cited by 2 | Viewed by 3935

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 [...] Read more.

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

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Open AccessArticle

Misalignment Fault Diagnosis of DFWT Based on IEMD Energy Entropy and PSO-SVM

by Yancai Xiao, Na Kang, Yi Hong and Guangjian Zhang

Entropy 2017, 19(1), 6; https://doi.org/10.3390/e19010006 - 01 Jan 2017

Cited by 49 | Viewed by 6734

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

Perturbative Treatment of the Non-Linear q-Schrödinger and q-Klein–Gordon Equations

by Javier Zamora, Mario C. Rocca, Angelo Plastino and Gustavo L. Ferri

Entropy 2017, 19(1), 21; https://doi.org/10.3390/e19010021 - 31 Dec 2016

Cited by 4 | Viewed by 3920

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 \sim 1

instance via a perturbative analysis of the NRT equations. Full article

(This article belongs to the Special Issue Entropic Aspects of Nonlinear Partial Differential Equations: Classical and Quantum Mechanical Perspectives)

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Open AccessArticle

Nonlinear Relaxation Phenomena in Metastable Condensed Matter Systems

by Bernardo Spagnolo, Claudio Guarcello, Luca Magazzù, Angelo Carollo, Dominique Persano Adorno and Davide Valenti

Entropy 2017, 19(1), 20; https://doi.org/10.3390/e19010020 - 31 Dec 2016

Cited by 98 | Viewed by 6078

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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6481 KiB

Open AccessArticle

Thermal Conductivity of Suspension of Aggregating Nanometric Rods

by Amine Ammar, Francisco Chinesta and Rodolphe Heyd

Entropy 2017, 19(1), 19; https://doi.org/10.3390/e19010019 - 31 Dec 2016

Cited by 5 | Viewed by 4289

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 [...] Read more.

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 AccessEditorial

Information and Self-Organization

by Hermann Haken and Juval Portugali

Entropy 2017, 19(1), 18; https://doi.org/10.3390/e19010018 - 31 Dec 2016

Cited by 23 | Viewed by 7973

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)

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Open AccessArticle

A New Feature Extraction Method Based on EEMD and Multi-Scale Fuzzy Entropy for Motor Bearing

by Huimin Zhao, Meng Sun, Wu Deng and Xinhua Yang

Entropy 2017, 19(1), 14; https://doi.org/10.3390/e19010014 - 31 Dec 2016

Cited by 190 | Viewed by 8981

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 [...] Read more.

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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