Remarks on Bousso's covariant entropy bound
Mayo, A E
2002-01-01
Bousso's covariant entropy bound is put to the test in the context of a non-singular cosmological solution of general relativity found by Bekenstein. Although the model complies with every assumption made in Bousso's original conjecture, the entropy bound is violated due to the occurrence of negative energy density associated with the interaction of some the matter components in the model. We demonstrate how this property allows for the test model to 'elude' a proof of Bousso's conjecture which was given recently by Flanagan, Marolf and Wald. This corroborates the view that the covariant entropy bound should be applied only to stable systems for which every matter component carries positive energy density.
An Entropy-Based Upper Bound Methodology for Robust Predictive Multi-Mode RCPSP Schedules
Directory of Open Access Journals (Sweden)
Angela Hsiang-Ling Chen
2014-09-01
Full Text Available Projects are an important part of our activities and regardless of their magnitude, scheduling is at the very core of every project. In an ideal world makespan minimization, which is the most commonly sought objective, would give us an advantage. However, every time we execute a project we have to deal with uncertainty; part of it coming from known sources and part remaining unknown until it affects us. For this reason, it is much more practical to focus on making our schedules robust, capable of handling uncertainty, and even to determine a range in which the project could be completed. In this paper we focus on an approach to determine such a range for the Multi-mode Resource Constrained Project Scheduling Problem (MRCPSP, a widely researched, NP-complete problem, but without adding any subjective considerations to its estimation. We do this by using a concept well known in the domain of thermodynamics, entropy and a three-stage approach. First we use Artificial Bee Colony (ABC—an effective and powerful meta-heuristic—to determine a schedule with minimized makespan which serves as a lower bound. The second stage defines buffer times and creates an upper bound makespan using an entropy function, with the advantage over other methods that it only considers elements which are inherent to the schedule itself and does not introduce any subjectivity to the buffer time generation. In the last stage, we use the ABC algorithm with an objective function that seeks to maximize robustness while staying within the makespan boundaries defined previously and in some cases even below the lower boundary. We evaluate our approach with two different benchmarks sets: when using the PSPLIB for the MRCPSP benchmark set, the computational results indicate that it is possible to generate robust schedules which generally result in an increase of less than 10% of the best known solutions while increasing the robustness in at least 20% for practically every
The covariant entropy bound in gravitational collapse
International Nuclear Information System (INIS)
Gao, Sijie; Lemos, Jose P. S.
2004-01-01
We study the covariant entropy bound in the context of gravitational collapse. First, we discuss critically the heuristic arguments advanced by Bousso. Then we solve the problem through an exact model: a Tolman-Bondi dust shell collapsing into a Schwarzschild black hole. After the collapse, a new black hole with a larger mass is formed. The horizon, L, of the old black hole then terminates at the singularity. We show that the entropy crossing L does not exceed a quarter of the area of the old horizon. Therefore, the covariant entropy bound is satisfied in this process. (author)
Braneworld black holes and entropy bounds
Directory of Open Access Journals (Sweden)
Y. Heydarzade
2018-01-01
Full Text Available The Bousso's D-bound entropy for the various possible black hole solutions on a 4-dimensional brane is checked. It is found that the D-bound entropy here is apparently different from that of obtained for the 4-dimensional black hole solutions. This difference is interpreted as the extra loss of information, associated to the extra dimension, when an extra-dimensional black hole is moved outward the observer's cosmological horizon. Also, it is discussed that N-bound entropy is hold for the possible solutions here. Finally, by adopting the recent Bohr-like approach to black hole quantum physics for the excited black holes, the obtained results are written also in terms of the black hole excited states.
Covariant entropy bound and loop quantum cosmology
International Nuclear Information System (INIS)
Ashtekar, Abhay; Wilson-Ewing, Edward
2008-01-01
We examine Bousso's covariant entropy bound conjecture in the context of radiation filled, spatially flat, Friedmann-Robertson-Walker models. The bound is violated near the big bang. However, the hope has been that quantum gravity effects would intervene and protect it. Loop quantum cosmology provides a near ideal setting for investigating this issue. For, on the one hand, quantum geometry effects resolve the singularity and, on the other hand, the wave function is sharply peaked at a quantum corrected but smooth geometry, which can supply the structure needed to test the bound. We find that the bound is respected. We suggest that the bound need not be an essential ingredient for a quantum gravity theory but may emerge from it under suitable circumstances.
Frenetic Bounds on the Entropy Production
Maes, Christian
2017-10-01
We give a systematic derivation of positive lower bounds for the expected entropy production (EP) rate in classical statistical mechanical systems obeying a dynamical large deviation principle. The logic is the same for the return to thermodynamic equilibrium as it is for steady nonequilibria working under the condition of local detailed balance. We recover there recently studied "uncertainty" relations for the EP, appearing in studies about the effectiveness of mesoscopic machines. In general our refinement of the positivity of the expected EP rate is obtained in terms of a positive and even function of the expected current(s) which measures the dynamical activity in the system, a time-symmetric estimate of the changes in the system's configuration. Also underdamped diffusions can be included in the analysis.
Entropy Bounds for Constrained Two-Dimensional Fields
DEFF Research Database (Denmark)
Forchhammer, Søren Otto; Justesen, Jørn
1999-01-01
The maximum entropy and thereby the capacity of 2-D fields given by certain constraints on configurations are considered. Upper and lower bounds are derived.......The maximum entropy and thereby the capacity of 2-D fields given by certain constraints on configurations are considered. Upper and lower bounds are derived....
Maximum and minimum entropy states yielding local continuity bounds
Hanson, Eric P.; Datta, Nilanjana
2018-04-01
Given an arbitrary quantum state (σ), we obtain an explicit construction of a state ρɛ * ( σ ) [respectively, ρ * , ɛ ( σ ) ] which has the maximum (respectively, minimum) entropy among all states which lie in a specified neighborhood (ɛ-ball) of σ. Computing the entropy of these states leads to a local strengthening of the continuity bound of the von Neumann entropy, i.e., the Audenaert-Fannes inequality. Our bound is local in the sense that it depends on the spectrum of σ. The states ρɛ * ( σ ) and ρ * , ɛ (σ) depend only on the geometry of the ɛ-ball and are in fact optimizers for a larger class of entropies. These include the Rényi entropy and the minimum- and maximum-entropies, providing explicit formulas for certain smoothed quantities. This allows us to obtain local continuity bounds for these quantities as well. In obtaining this bound, we first derive a more general result which may be of independent interest, namely, a necessary and sufficient condition under which a state maximizes a concave and Gâteaux-differentiable function in an ɛ-ball around a given state σ. Examples of such a function include the von Neumann entropy and the conditional entropy of bipartite states. Our proofs employ tools from the theory of convex optimization under non-differentiable constraints, in particular Fermat's rule, and majorization theory.
Upper bounds on the entropy of radiation systems
Institute of Scientific and Technical Information of China (English)
汪定雄
1997-01-01
The upper bounds on the entropy of a radiation system confined to a spherical box are calculated in six cases by using the equation of state of radiation in flat spacetime and the equation of state of radiation near black-hole horizon,which was derived by Li and Liu (hereafter the Li-Liu equation).It turns out that the Li-Liu equation does have unique advantage in dealing with the entropy bound of critical self-gravitating radiation systems,while the usual equation of state will result in entropy divergence.In the case of non-self-gravitating radiation systems and non-critical self-gravitating radiation systems,there is no difference in the entropy bounds derived by these two equations of state.
The question of an upper bound on entropy
International Nuclear Information System (INIS)
Qadir, A.
1982-08-01
We discuss the possibility, and significance, of an upper bound on entropy in the light of the arguments of Bekenstein and Unruh and Wald. We obtain a stricter bound than Bekenstein does, and point out some limitations with regard to its significance. (author)
Entropy lower bounds of quantum decision tree complexity
Shi, Yaoyun
2000-01-01
We prove a general lower bound of quantum decision tree complexity in terms of some entropy notion. We regard the computation as a communication process in which the oracle and the computer exchange several rounds of messages, each round consisting of O(log(n)) bits. Let E(f) be the Shannon entropy of the random variable f(X), where X is uniformly random in f's domain. Our main result is that it takes \\Omega(E(f)) queries to compute any \\emph{total} function f. It is interesting to contrast t...
Entropy methods for reaction-diffusion equations: slowly growing a-priori bounds
Desvillettes, Laurent; Fellner, Klemens
2008-01-01
In the continuation of [Desvillettes, L., Fellner, K.: Exponential Decay toward Equilibrium via Entropy Methods for Reaction-Diffusion Equations. J. Math. Anal. Appl. 319 (2006), no. 1, 157-176], we study reversible reaction-diffusion equations via entropy methods (based on the free energy functional) for a 1D system of four species. We improve the existing theory by getting 1) almost exponential convergence in L1 to the steady state via a precise entropy-entropy dissipation estimate, 2) an explicit global L∞ bound via interpolation of a polynomially growing H1 bound with the almost exponential L1 convergence, and 3), finally, explicit exponential convergence to the steady state in all Sobolev norms.
Computing a Non-trivial Lower Bound on the Joint Entropy between Two Images
Energy Technology Data Exchange (ETDEWEB)
Perumalla, Kalyan S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2017-03-01
In this report, a non-trivial lower bound on the joint entropy of two non-identical images is developed, which is greater than the individual entropies of the images. The lower bound is the least joint entropy possible among all pairs of images that have the same histograms as those of the given images. New algorithms are presented to compute the joint entropy lower bound with a computation time proportional to S log S where S is the number of histogram bins of the images. This is faster than the traditional methods of computing the exact joint entropy with a computation time that is quadratic in S .
Entropy bound and causality violation in higher curvature gravity
International Nuclear Information System (INIS)
Neupane, Ishwaree P; Dadhich, Naresh
2009-01-01
In any quantum theory of gravity we do expect corrections to Einstein gravity to occur. Yet, at a fundamental level, it is not apparent what the most relevant corrections are. We argue that the generic curvature square corrections present in the lower dimensional actions of various compactified string theories provide a natural passage between the classical and quantum realms of gravity. The Gauss-Bonnet and (Riemann) 2 gravities, in particular, provide concrete examples in which inconsistency of a theory, such as a violation of microcausality, and a classical limit on black hole entropy are correlated. In such theories the ratio of the shear viscosity to the entropy density, η/s, can be smaller than for a boundary conformal field theory with Einstein gravity dual. This result is interesting from the viewpoint that nuclear matter or quark-gluon plasma produced (such as at RHIC) under extreme densities and temperatures may violate the conjectured KSS bound η/s ≥ 1/4π, albeit marginally so.
Mouloudakis, K.; Kominis, I. K.
2017-02-01
Radical-ion-pair reactions, central for understanding the avian magnetic compass and spin transport in photosynthetic reaction centers, were recently shown to be a fruitful paradigm of the new synthesis of quantum information science with biological processes. We show here that the master equation so far constituting the theoretical foundation of spin chemistry violates fundamental bounds for the entropy of quantum systems, in particular the Ozawa bound. In contrast, a recently developed theory based on quantum measurements, quantum coherence measures, and quantum retrodiction, thus exemplifying the paradigm of quantum biology, satisfies the Ozawa bound as well as the Lanford-Robinson bound on information extraction. By considering Groenewold's information, the quantum information extracted during the reaction, we reproduce the known and unravel other magnetic-field effects not conveyed by reaction yields.
Mouloudakis, K; Kominis, I K
2017-02-01
Radical-ion-pair reactions, central for understanding the avian magnetic compass and spin transport in photosynthetic reaction centers, were recently shown to be a fruitful paradigm of the new synthesis of quantum information science with biological processes. We show here that the master equation so far constituting the theoretical foundation of spin chemistry violates fundamental bounds for the entropy of quantum systems, in particular the Ozawa bound. In contrast, a recently developed theory based on quantum measurements, quantum coherence measures, and quantum retrodiction, thus exemplifying the paradigm of quantum biology, satisfies the Ozawa bound as well as the Lanford-Robinson bound on information extraction. By considering Groenewold's information, the quantum information extracted during the reaction, we reproduce the known and unravel other magnetic-field effects not conveyed by reaction yields.
Bounds on the entanglement entropy of droplet states in the XXZ spin chain
Beaud, V.; Warzel, S.
2018-01-01
We consider a class of one-dimensional quantum spin systems on the finite lattice Λ ⊂Z , related to the XXZ spin chain in its Ising phase. It includes in particular the so-called droplet Hamiltonian. The entanglement entropy of energetically low-lying states over a bipartition Λ = B ∪ Bc is investigated and proven to satisfy a logarithmic bound in terms of min{n, |B|, |Bc|}, where n denotes the maximal number of down spins in the considered state. Upon addition of any (positive) random potential, the bound becomes uniformly constant on average, thereby establishing an area law. The proof is based on spectral methods: a deterministic bound on the local (many-body integrated) density of states is derived from an energetically motivated Combes-Thomas estimate.
An Upper Bound on the Entropy of Constrained 2d Fields
DEFF Research Database (Denmark)
Forchhammer, Søren; Justesen, Jørn
1998-01-01
An upper bound on the entropy of constrained 2D fields is presented. The constraints have to be symmetric in (at least) one of the two directions. The bound generalizes (in a weaker form) the bound of Calkin and Wilf (see SIAM Journal of Discrete Mathematics, vol.11, p.54-60, 1998) which is valid...
Minimization under entropy conditions, with applications in lower bound problems
International Nuclear Information System (INIS)
Toft, Joachim
2004-01-01
We minimize the functional f->∫ afdμ under the entropy condition E(f)=-∫ f log fdμ≥E, ∫ fdμ=1 and f≥0, where E is a member of R is fixed. We prove that the minimum is attained for f=e -sa /∫ e -sa dμ, where s is a member of R is chosen such that E(f)=E. We apply the result on minimizing problems in pseudodifferential calculus, where we minimize the harmonic oscillator
The optimal entropy bound and the self-energy of test objects in the vicinity of a black hole
Mayo, Avraham E.
1999-01-01
Recently Bekenstein and Mayo conjectured an entropy bound for charged rotating objects. On the basis of the No-Hair principle for black holes, they speculate that this bound cannot be improved generically based on knowledge of other ``quantum numbers'', e.g. baryon number, which may be borne by the object. Here we take a first step in the proof of this conjecture. The proof make use of a gedanken experiment in which a massive object endowed with a scalar charge is lowered adiabatically toward...
A Lower Bound on the Differential Entropy of Log-Concave Random Vectors with Applications
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Arnaud Marsiglietti
2018-03-01
Full Text Available We derive a lower bound on the differential entropy of a log-concave random variable X in terms of the p-th absolute moment of X. The new bound leads to a reverse entropy power inequality with an explicit constant, and to new bounds on the rate-distortion function and the channel capacity. Specifically, we study the rate-distortion function for log-concave sources and distortion measure d ( x , x ^ = | x − x ^ | r , with r ≥ 1 , and we establish that the difference between the rate-distortion function and the Shannon lower bound is at most log ( π e ≈ 1 . 5 bits, independently of r and the target distortion d. For mean-square error distortion, the difference is at most log ( π e 2 ≈ 1 bit, regardless of d. We also provide bounds on the capacity of memoryless additive noise channels when the noise is log-concave. We show that the difference between the capacity of such channels and the capacity of the Gaussian channel with the same noise power is at most log ( π e 2 ≈ 1 bit. Our results generalize to the case of a random vector X with possibly dependent coordinates. Our proof technique leverages tools from convex geometry.
Nonthreshold D-brane bound states and black holes with nonzero entropy
International Nuclear Information System (INIS)
Costa, M.S.; Cvetic, M.
1997-01-01
We start with Bogomol close-quote nyi-Prasad-Sommerfield- (BPS) saturated configurations of two (orthogonally) intersecting M-branes and use the electromagnetic duality or dimensional reduction along a boost, in order to obtain new p-brane bound states. In the first case the resulting configurations are interpreted as BPS-saturated nonthreshold bound states of intersecting p-branes, and in the second case as p-branes intersecting at angles and their duals. As a by-product we deduce the enhancement of supersymmetry as the angle approaches zero. We also comment on the D-brane theory describing these new bound states, and a connection between the angle and the world-volume gauge fields of the D-brane system. We use these configurations to find new embeddings of the four- and five-dimensional black holes with nonzero entropy, whose entropy now also depends on the angle and world-volume gauge fields. The corresponding D-brane configuration sheds light on the microscopic entropy of such black holes. copyright 1997 The American Physical Society
Entropy Evaluation Based on Value Validity
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Tarald O. Kvålseth
2014-09-01
Full Text Available Besides its importance in statistical physics and information theory, the Boltzmann-Shannon entropy S has become one of the most widely used and misused summary measures of various attributes (characteristics in diverse fields of study. It has also been the subject of extensive and perhaps excessive generalizations. This paper introduces the concept and criteria for value validity as a means of determining if an entropy takes on values that reasonably reflect the attribute being measured and that permit different types of comparisons to be made for different probability distributions. While neither S nor its relative entropy equivalent S* meet the value-validity conditions, certain power functions of S and S* do to a considerable extent. No parametric generalization offers any advantage over S in this regard. A measure based on Euclidean distances between probability distributions is introduced as a potential entropy that does comply fully with the value-validity requirements and its statistical inference procedure is discussed.
Entropy bound of horizons for accelerating, rotating and charged Plebanski–Demianski black hole
International Nuclear Information System (INIS)
Debnath, Ujjal
2016-01-01
We first review the accelerating, rotating and charged Plebanski–Demianski (PD) black hole, which includes the Kerr–Newman rotating black hole and the Taub-NUT spacetime. The main feature of this black hole is that it has 4 horizons like event horizon, Cauchy horizon and two accelerating horizons. In the non-extremal case, the surface area, entropy, surface gravity, temperature, angular velocity, Komar energy and irreducible mass on the event horizon and Cauchy horizon are presented for PD black hole. The entropy product, temperature product, Komar energy product and irreducible mass product have been found for event horizon and Cauchy horizon. Also their sums are found for both horizons. All these relations are dependent on the mass of the PD black hole and other parameters. So all the products are not universal for PD black hole. The entropy and area bounds for two horizons have been investigated. Also we found the Christodoulou–Ruffini mass for extremal PD black hole. Finally, using first law of thermodynamics, we also found the Smarr relation for PD black hole.
Entropy bound of horizons for accelerating, rotating and charged Plebanski–Demianski black hole
Energy Technology Data Exchange (ETDEWEB)
Debnath, Ujjal, E-mail: ujjaldebnath@yahoo.com
2016-09-15
We first review the accelerating, rotating and charged Plebanski–Demianski (PD) black hole, which includes the Kerr–Newman rotating black hole and the Taub-NUT spacetime. The main feature of this black hole is that it has 4 horizons like event horizon, Cauchy horizon and two accelerating horizons. In the non-extremal case, the surface area, entropy, surface gravity, temperature, angular velocity, Komar energy and irreducible mass on the event horizon and Cauchy horizon are presented for PD black hole. The entropy product, temperature product, Komar energy product and irreducible mass product have been found for event horizon and Cauchy horizon. Also their sums are found for both horizons. All these relations are dependent on the mass of the PD black hole and other parameters. So all the products are not universal for PD black hole. The entropy and area bounds for two horizons have been investigated. Also we found the Christodoulou–Ruffini mass for extremal PD black hole. Finally, using first law of thermodynamics, we also found the Smarr relation for PD black hole.
Coherence and entanglement measures based on Rényi relative entropies
International Nuclear Information System (INIS)
Zhu, Huangjun; Hayashi, Masahito; Chen, Lin
2017-01-01
We study systematically resource measures of coherence and entanglement based on Rényi relative entropies, which include the logarithmic robustness of coherence, geometric coherence, and conventional relative entropy of coherence together with their entanglement analogues. First, we show that each Rényi relative entropy of coherence is equal to the corresponding Rényi relative entropy of entanglement for any maximally correlated state. By virtue of this observation, we establish a simple operational connection between entanglement measures and coherence measures based on Rényi relative entropies. We then prove that all these coherence measures, including the logarithmic robustness of coherence, are additive. Accordingly, all these entanglement measures are additive for maximally correlated states. In addition, we derive analytical formulas for Rényi relative entropies of entanglement of maximally correlated states and bipartite pure states, which reproduce a number of classic results on the relative entropy of entanglement and logarithmic robustness of entanglement in a unified framework. Several nontrivial bounds for Rényi relative entropies of coherence (entanglement) are further derived, which improve over results known previously. Moreover, we determine all states whose relative entropy of coherence is equal to the logarithmic robustness of coherence. As an application, we provide an upper bound for the exact coherence distillation rate, which is saturated for pure states. (paper)
Energy Technology Data Exchange (ETDEWEB)
Goswami, Gurupada; Majee, Pradip; Bag, Bidhan Chandra [Department of Chemistry, Visva-Bharati, Santiniketan 731 235 (India); Barik, Debashis [Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700 032 (India)
2006-09-15
In this paper we have studied upper bound of time derivative of information entropy for colored cross-correlated noise driven open systems. The upper bound is calculated based on the Fokker-Planck equation and the Schwartz inequality principle. Our results consider the effect of the noise correlation strength and correlation time due to the correlation between additive and multiplicative white noises on the upper bound as well as relaxation time. The interplay of deterministic and random forces reveals extremal nature of the upper bound and its deviation from the time derivative of information entropy. (author)
Autonomous entropy-based intelligent experimental design
Malakar, Nabin Kumar
2011-07-01
The aim of this thesis is to explore the application of probability and information theory in experimental design, and to do so in a way that combines what we know about inference and inquiry in a comprehensive and consistent manner. Present day scientific frontiers involve data collection at an ever-increasing rate. This requires that we find a way to collect the most relevant data in an automated fashion. By following the logic of the scientific method, we couple an inference engine with an inquiry engine to automate the iterative process of scientific learning. The inference engine involves Bayesian machine learning techniques to estimate model parameters based upon both prior information and previously collected data, while the inquiry engine implements data-driven exploration. By choosing an experiment whose distribution of expected results has the maximum entropy, the inquiry engine selects the experiment that maximizes the expected information gain. The coupled inference and inquiry engines constitute an autonomous learning method for scientific exploration. We apply it to a robotic arm to demonstrate the efficacy of the method. Optimizing inquiry involves searching for an experiment that promises, on average, to be maximally informative. If the set of potential experiments is described by many parameters, the search involves a high-dimensional entropy space. In such cases, a brute force search method will be slow and computationally expensive. We develop an entropy-based search algorithm, called nested entropy sampling, to select the most informative experiment. This helps to reduce the number of computations necessary to find the optimal experiment. We also extended the method of maximizing entropy, and developed a method of maximizing joint entropy so that it could be used as a principle of collaboration between two robots. This is a major achievement of this thesis, as it allows the information-based collaboration between two robotic units towards a same
Entropy based fingerprint for local crystalline order
Piaggi, Pablo M.; Parrinello, Michele
2017-09-01
We introduce a new fingerprint that allows distinguishing between liquid-like and solid-like atomic environments. This fingerprint is based on an approximate expression for the entropy projected on individual atoms. When combined with local enthalpy, this fingerprint acquires an even finer resolution and it is capable of discriminating between different crystal structures.
A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy
Directory of Open Access Journals (Sweden)
Ge Jianjun
2017-12-01
Full Text Available Nowadays, the battlefield environment has become much more complex and variable. This paper presents a quantitative method and lower bound for the amount of target information acquired from multiple radar observations to adaptively and dynamically organize the detection of battlefield resources based on the principle of information entropy. Furthermore, for minimizing the given information entropy’s lower bound for target measurement at every moment, a method to dynamically and adaptively select radars with a high amount of information for target tracking is proposed. The simulation results indicate that the proposed method has higher tracking accuracy than that of tracking without adaptive radar selection based on entropy.
Entropy-based benchmarking methods
Temurshoev, Umed
2012-01-01
We argue that benchmarking sign-volatile series should be based on the principle of movement and sign preservation, which states that a bench-marked series should reproduce the movement and signs in the original series. We show that the widely used variants of Denton (1971) method and the growth
Fundamental limits on quantum dynamics based on entropy change
Das, Siddhartha; Khatri, Sumeet; Siopsis, George; Wilde, Mark M.
2018-01-01
It is well known in the realm of quantum mechanics and information theory that the entropy is non-decreasing for the class of unital physical processes. However, in general, the entropy does not exhibit monotonic behavior. This has restricted the use of entropy change in characterizing evolution processes. Recently, a lower bound on the entropy change was provided in the work of Buscemi, Das, and Wilde [Phys. Rev. A 93(6), 062314 (2016)]. We explore the limit that this bound places on the physical evolution of a quantum system and discuss how these limits can be used as witnesses to characterize quantum dynamics. In particular, we derive a lower limit on the rate of entropy change for memoryless quantum dynamics, and we argue that it provides a witness of non-unitality. This limit on the rate of entropy change leads to definitions of several witnesses for testing memory effects in quantum dynamics. Furthermore, from the aforementioned lower bound on entropy change, we obtain a measure of non-unitarity for unital evolutions.
International Nuclear Information System (INIS)
Zhang Min-Min; Mei Dong-Cheng; Wang Can-Jun
2011-01-01
The effects of the time delay on the upper bound of the time derivative of information entropy are investigated in a time-delayed dynamical system driven by correlated noise. Using the Markov approximation of the stochastic delay differential equations and the Schwartz inequality principle, we obtain an analytical expression for the upper bound U B (t) of the time derivative of the information entropy. The results show that there is a critical value of τ (delay time), and U B (t) presents opposite behaviours on difference sides of the critical value. For the case of the weak additive noise, τ can induce a reentrance transition. Delay time τ also causes a reversal behaviour in U B (t)-λ plot, where λ denotes the degree of the correlation between the two noises. (general)
Entropy-based financial asset pricing.
Directory of Open Access Journals (Sweden)
Mihály Ormos
Full Text Available We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return-entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy.
Entropy-based financial asset pricing.
Ormos, Mihály; Zibriczky, Dávid
2014-01-01
We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return-entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy.
Entropy-Based Algorithm for Supply-Chain Complexity Assessment
Directory of Open Access Journals (Sweden)
Boris Kriheli
2018-03-01
Full Text Available This paper considers a graph model of hierarchical supply chains. The goal is to measure the complexity of links between different components of the chain, for instance, between the principal equipment manufacturer (a root node and its suppliers (preceding supply nodes. The information entropy is used to serve as a measure of knowledge about the complexity of shortages and pitfalls in relationship between the supply chain components under uncertainty. The concept of conditional (relative entropy is introduced which is a generalization of the conventional (non-relative entropy. An entropy-based algorithm providing efficient assessment of the supply chain complexity as a function of the SC size is developed.
Jaeken, Laurent; Vasilievich Matveev, Vladimir
2012-01-01
Observations of coherent cellular behavior cannot be integrated into widely accepted membrane (pump) theory (MT) and its steady state energetics because of the thermal noise of assumed ordinary cell water and freely soluble cytoplasmic K(+). However, Ling disproved MT and proposed an alternative based on coherence, showing that rest (R) and action (A) are two different phases of protoplasm with different energy levels. The R-state is a coherent metastable low-entropy state as water and K(+) are bound to unfolded proteins. The A-state is the higher-entropy state because water and K(+) are free. The R-to-A phase transition is regarded as a mechanism to release energy for biological work, replacing the classical concept of high-energy bonds. Subsequent inactivation during the endergonic A-to-R phase transition needs an input of metabolic energy to restore the low entropy R-state. Matveev's native aggregation hypothesis allows to integrate the energetic details of globular proteins into this view.
Comment on ''Proof of the quantum bound on specific entropy for free fields''
International Nuclear Information System (INIS)
Unruh, W.G.
1990-01-01
The effect of zero modes on the arguments of Bekenstein and Schiffer are analyzed, and it is shown that, if a system has such zero modes, an arbitrarily large entropy can be stored in the system for any given cost in energy
Financial time series analysis based on effective phase transfer entropy
Yang, Pengbo; Shang, Pengjian; Lin, Aijing
2017-02-01
Transfer entropy is a powerful technique which is able to quantify the impact of one dynamic system on another system. In this paper, we propose the effective phase transfer entropy method based on the transfer entropy method. We use simulated data to test the performance of this method, and the experimental results confirm that the proposed approach is capable of detecting the information transfer between the systems. We also explore the relationship between effective phase transfer entropy and some variables, such as data size, coupling strength and noise. The effective phase transfer entropy is positively correlated with the data size and the coupling strength. Even in the presence of a large amount of noise, it can detect the information transfer between systems, and it is very robust to noise. Moreover, this measure is indeed able to accurately estimate the information flow between systems compared with phase transfer entropy. In order to reflect the application of this method in practice, we apply this method to financial time series and gain new insight into the interactions between systems. It is demonstrated that the effective phase transfer entropy can be used to detect some economic fluctuations in the financial market. To summarize, the effective phase transfer entropy method is a very efficient tool to estimate the information flow between systems.
A new entropy based method for computing software structural complexity
Roca, J L
2002-01-01
In this paper a new methodology for the evaluation of software structural complexity is described. It is based on the entropy evaluation of the random uniform response function associated with the so called software characteristic function SCF. The behavior of the SCF with the different software structures and their relationship with the number of inherent errors is investigated. It is also investigated how the entropy concept can be used to evaluate the complexity of a software structure considering the SCF as a canonical representation of the graph associated with the control flow diagram. The functions, parameters and algorithms that allow to carry out this evaluation are also introduced. After this analytic phase follows the experimental phase, verifying the consistency of the proposed metric and their boundary conditions. The conclusion is that the degree of software structural complexity can be measured as the entropy of the random uniform response function of the SCF. That entropy is in direct relation...
Upper bounds for reversible circuits based on Young subgroups
DEFF Research Database (Denmark)
Abdessaied, Nabila; Soeken, Mathias; Thomsen, Michael Kirkedal
2014-01-01
We present tighter upper bounds on the number of Toffoli gates needed in reversible circuits. Both multiple controlled Toffoli gates and mixed polarity Toffoli gates have been considered for this purpose. The calculation of the bounds is based on a synthesis approach based on Young subgroups...... that results in circuits using a more generalized gate library. Starting from an upper bound for this library we derive new bounds which improve the existing bound by around 77%....
Fractal Image Compression Based on High Entropy Values Technique
Directory of Open Access Journals (Sweden)
Douaa Younis Abbaas
2018-04-01
Full Text Available There are many attempts tried to improve the encoding stage of FIC because it consumed time. These attempts worked by reducing size of the search pool for pair range-domain matching but most of them led to get a bad quality, or a lower compression ratio of reconstructed image. This paper aims to present a method to improve performance of the full search algorithm by combining FIC (lossy compression and another lossless technique (in this case entropy coding is used. The entropy technique will reduce size of the domain pool (i. e., number of domain blocks based on the entropy value of each range block and domain block and then comparing the results of full search algorithm and proposed algorithm based on entropy technique to see each of which give best results (such as reduced the encoding time with acceptable values in both compression quali-ty parameters which are C. R (Compression Ratio and PSNR (Image Quality. The experimental results of the proposed algorithm proven that using the proposed entropy technique reduces the encoding time while keeping compression rates and reconstruction image quality good as soon as possible.
Entropy-Based Clutter Rejection for Intrawall Diagnostics
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Raffaele Solimene
2012-01-01
Full Text Available The intrawall diagnostic problem of detecting localized inhomogeneities possibly present within the wall is addressed. As well known, clutter arising from masonry structure can impair detection of embedded scatterers due to high amplitude reflections that wall front face introduces. Moreover, internal multiple reflections also can make it difficult ground penetrating radar images (radargramms interpretation. To counteract these drawbacks, a clutter rejection method, properly tailored on the wall features, is mandatory. To this end, here we employ a windowing strategy based on entropy measures of temporal traces “similarity.” Accordingly, instants of time for which radargramms exhibit entropy values greater than a prescribed threshold are “silenced.” Numerical results are presented in order to show the effectiveness of the entropy-based clutter rejection algorithm. Moreover, a comparison with the standard average trace subtraction is also included.
Directory of Open Access Journals (Sweden)
Leonid M. Martyushev
2015-06-01
Full Text Available The entropy production (inside the volume bounded by a photosphere of main-sequence stars, subgiants, giants, and supergiants is calculated based on B–V photometry data. A non-linear inverse relationship of thermodynamic fluxes and forces as well as an almost constant specific (per volume entropy production of main-sequence stars (for 95% of stars, this quantity lies within 0.5 to 2.2 of the corresponding solar magnitude is found. The obtained results are discussed from the perspective of known extreme principles related to entropy production.
Image coding based on maximum entropy partitioning for identifying ...
Indian Academy of Sciences (India)
A new coding scheme based on maximum entropy partitioning is proposed in our work, particularly to identify the improbable intensities related to different emotions. The improbable intensities when used as a mask decode the facial expression correctly, providing an effectiveplatform for future emotion categorization ...
Optimization and large scale computation of an entropy-based moment closure
Kristopher Garrett, C.; Hauck, Cory; Hill, Judith
2015-12-01
We present computational advances and results in the implementation of an entropy-based moment closure, MN, in the context of linear kinetic equations, with an emphasis on heterogeneous and large-scale computing platforms. Entropy-based closures are known in several cases to yield more accurate results than closures based on standard spectral approximations, such as PN, but the computational cost is generally much higher and often prohibitive. Several optimizations are introduced to improve the performance of entropy-based algorithms over previous implementations. These optimizations include the use of GPU acceleration and the exploitation of the mathematical properties of spherical harmonics, which are used as test functions in the moment formulation. To test the emerging high-performance computing paradigm of communication bound simulations, we present timing results at the largest computational scales currently available. These results show, in particular, load balancing issues in scaling the MN algorithm that do not appear for the PN algorithm. We also observe that in weak scaling tests, the ratio in time to solution of MN to PN decreases.
Epoch-based Entropy for Early Screening of Alzheimer's Disease.
Houmani, N; Dreyfus, G; Vialatte, F B
2015-12-01
In this paper, we introduce a novel entropy measure, termed epoch-based entropy. This measure quantifies disorder of EEG signals both at the time level and spatial level, using local density estimation by a Hidden Markov Model on inter-channel stationary epochs. The investigation is led on a multi-centric EEG database recorded from patients at an early stage of Alzheimer's disease (AD) and age-matched healthy subjects. We investigate the classification performances of this method, its robustness to noise, and its sensitivity to sampling frequency and to variations of hyperparameters. The measure is compared to two alternative complexity measures, Shannon's entropy and correlation dimension. The classification accuracies for the discrimination of AD patients from healthy subjects were estimated using a linear classifier designed on a development dataset, and subsequently tested on an independent test set. Epoch-based entropy reached a classification accuracy of 83% on the test dataset (specificity = 83.3%, sensitivity = 82.3%), outperforming the two other complexity measures. Furthermore, it was shown to be more stable to hyperparameter variations, and less sensitive to noise and sampling frequency disturbances than the other two complexity measures.
Entropy-Based Privacy against Profiling of User Mobility
Directory of Open Access Journals (Sweden)
Alicia Rodriguez-Carrion
2015-06-01
Full Text Available Location-based services (LBSs flood mobile phones nowadays, but their use poses an evident privacy risk. The locations accompanying the LBS queries can be exploited by the LBS provider to build the user profile of visited locations, which might disclose sensitive data, such as work or home locations. The classic concept of entropy is widely used to evaluate privacy in these scenarios, where the information is represented as a sequence of independent samples of categorized data. However, since the LBS queries might be sent very frequently, location profiles can be improved by adding temporal dependencies, thus becoming mobility profiles, where location samples are not independent anymore and might disclose the user’s mobility patterns. Since the time dimension is factored in, the classic entropy concept falls short of evaluating the real privacy level, which depends also on the time component. Therefore, we propose to extend the entropy-based privacy metric to the use of the entropy rate to evaluate mobility profiles. Then, two perturbative mechanisms are considered to preserve locations and mobility profiles under gradual utility constraints. We further use the proposed privacy metric and compare it to classic ones to evaluate both synthetic and real mobility profiles when the perturbative methods proposed are applied. The results prove the usefulness of the proposed metric for mobility profiles and the need for tailoring the perturbative methods to the features of mobility profiles in order to improve privacy without completely loosing utility.
A Method of Rotating Machinery Fault Diagnosis Based on the Close Degree of Information Entropy
Institute of Scientific and Technical Information of China (English)
GENG Jun-bao; HUANG Shu-hong; JIN Jia-shan; CHEN Fei; LIU Wei
2006-01-01
This paper presents a method of rotating machinery fault diagnosis based on the close degree of information entropy. In the view of the information entropy, we introduce four information entropy features of the rotating machinery, which describe the vibration condition of the machinery. The four features are, respectively, denominated as singular spectrum entropy, power spectrum entropy, wavelet space state feature entropy and wavelet power spectrum entropy. The value scopes of the four information entropy features of the rotating machinery in some typical fault conditions are gained by experiments, which can be acted as the standard features of fault diagnosis. According to the principle of the shorter distance between the more similar models, the decision-making method based on the close degree of information entropy is put forward to deal with the recognition of fault patterns. We demonstrate the effectiveness of this approach in an instance involving the fault pattern recognition of some rotating machinery.
A new entropy based method for computing software structural complexity
International Nuclear Information System (INIS)
Roca, Jose L.
2002-01-01
In this paper a new methodology for the evaluation of software structural complexity is described. It is based on the entropy evaluation of the random uniform response function associated with the so called software characteristic function SCF. The behavior of the SCF with the different software structures and their relationship with the number of inherent errors is investigated. It is also investigated how the entropy concept can be used to evaluate the complexity of a software structure considering the SCF as a canonical representation of the graph associated with the control flow diagram. The functions, parameters and algorithms that allow to carry out this evaluation are also introduced. After this analytic phase follows the experimental phase, verifying the consistency of the proposed metric and their boundary conditions. The conclusion is that the degree of software structural complexity can be measured as the entropy of the random uniform response function of the SCF. That entropy is in direct relationship with the number of inherent software errors and it implies a basic hazard failure rate for it, so that a minimum structure assures a certain stability and maturity of the program. This metric can be used, either to evaluate the product or the process of software development, as development tool or for monitoring the stability and the quality of the final product. (author)
An Entropy-Based Network Anomaly Detection Method
Directory of Open Access Journals (Sweden)
Przemysław Bereziński
2015-04-01
Full Text Available Data mining is an interdisciplinary subfield of computer science involving methods at the intersection of artificial intelligence, machine learning and statistics. One of the data mining tasks is anomaly detection which is the analysis of large quantities of data to identify items, events or observations which do not conform to an expected pattern. Anomaly detection is applicable in a variety of domains, e.g., fraud detection, fault detection, system health monitoring but this article focuses on application of anomaly detection in the field of network intrusion detection.The main goal of the article is to prove that an entropy-based approach is suitable to detect modern botnet-like malware based on anomalous patterns in network. This aim is achieved by realization of the following points: (i preparation of a concept of original entropy-based network anomaly detection method, (ii implementation of the method, (iii preparation of original dataset, (iv evaluation of the method.
Wu, Yue; Shang, Pengjian; Li, Yilong
2018-03-01
A modified multiscale sample entropy measure based on symbolic representation and similarity (MSEBSS) is proposed in this paper to research the complexity of stock markets. The modified algorithm reduces the probability of inducing undefined entropies and is confirmed to be robust to strong noise. Considering the validity and accuracy, MSEBSS is more reliable than Multiscale entropy (MSE) for time series mingled with much noise like financial time series. We apply MSEBSS to financial markets and results show American stock markets have the lowest complexity compared with European and Asian markets. There are exceptions to the regularity that stock markets show a decreasing complexity over the time scale, indicating a periodicity at certain scales. Based on MSEBSS, we introduce the modified multiscale cross-sample entropy measure based on symbolic representation and similarity (MCSEBSS) to consider the degree of the asynchrony between distinct time series. Stock markets from the same area have higher synchrony than those from different areas. And for stock markets having relative high synchrony, the entropy values will decrease with the increasing scale factor. While for stock markets having high asynchrony, the entropy values will not decrease with the increasing scale factor sometimes they tend to increase. So both MSEBSS and MCSEBSS are able to distinguish stock markets of different areas, and they are more helpful if used together for studying other features of financial time series.
Universal bounds on current fluctuations.
Pietzonka, Patrick; Barato, Andre C; Seifert, Udo
2016-05-01
For current fluctuations in nonequilibrium steady states of Markovian processes, we derive four different universal bounds valid beyond the Gaussian regime. Different variants of these bounds apply to either the entropy change or any individual current, e.g., the rate of substrate consumption in a chemical reaction or the electron current in an electronic device. The bounds vary with respect to their degree of universality and tightness. A universal parabolic bound on the generating function of an arbitrary current depends solely on the average entropy production. A second, stronger bound requires knowledge both of the thermodynamic forces that drive the system and of the topology of the network of states. These two bounds are conjectures based on extensive numerics. An exponential bound that depends only on the average entropy production and the average number of transitions per time is rigorously proved. This bound has no obvious relation to the parabolic bound but it is typically tighter further away from equilibrium. An asymptotic bound that depends on the specific transition rates and becomes tight for large fluctuations is also derived. This bound allows for the prediction of the asymptotic growth of the generating function. Even though our results are restricted to networks with a finite number of states, we show that the parabolic bound is also valid for three paradigmatic examples of driven diffusive systems for which the generating function can be calculated using the additivity principle. Our bounds provide a general class of constraints for nonequilibrium systems.
International Nuclear Information System (INIS)
Zhu, Qingjun; Song, Fengquan; Ren, Jie; Chen, Xueyong; Zhou, Bin
2014-01-01
To further expand the application of an artificial neural network in the field of neutron spectrometry, the criteria for choosing between an artificial neural network and the maximum entropy method for the purpose of unfolding neutron spectra was presented. The counts of the Bonner spheres for IAEA neutron spectra were used as a database, and the artificial neural network and the maximum entropy method were used to unfold neutron spectra; the mean squares of the spectra were defined as the differences between the desired and unfolded spectra. After the information entropy of each spectrum was calculated using information entropy theory, the relationship between the mean squares of the spectra and the information entropy was acquired. Useful information from the information entropy guided the selection of unfolding methods. Due to the importance of the information entropy, the method for predicting the information entropy using the Bonner spheres' counts was established. The criteria based on the information entropy theory can be used to choose between the artificial neural network and the maximum entropy method unfolding methods. The application of an artificial neural network to unfold neutron spectra was expanded. - Highlights: • Two neutron spectra unfolding methods, ANN and MEM, were compared. • The spectrum's entropy offers useful information for selecting unfolding methods. • For the spectrum with low entropy, the ANN was generally better than MEM. • The spectrum's entropy was predicted based on the Bonner spheres' counts
Distance-Based Configurational Entropy of Proteins from Molecular Dynamics Simulations.
Fogolari, Federico; Corazza, Alessandra; Fortuna, Sara; Soler, Miguel Angel; VanSchouwen, Bryan; Brancolini, Giorgia; Corni, Stefano; Melacini, Giuseppe; Esposito, Gennaro
2015-01-01
Estimation of configurational entropy from molecular dynamics trajectories is a difficult task which is often performed using quasi-harmonic or histogram analysis. An entirely different approach, proposed recently, estimates local density distribution around each conformational sample by measuring the distance from its nearest neighbors. In this work we show this theoretically well grounded the method can be easily applied to estimate the entropy from conformational sampling. We consider a set of systems that are representative of important biomolecular processes. In particular: reference entropies for amino acids in unfolded proteins are obtained from a database of residues not participating in secondary structure elements;the conformational entropy of folding of β2-microglobulin is computed from molecular dynamics simulations using reference entropies for the unfolded state;backbone conformational entropy is computed from molecular dynamics simulations of four different states of the EPAC protein and compared with order parameters (often used as a measure of entropy);the conformational and rototranslational entropy of binding is computed from simulations of 20 tripeptides bound to the peptide binding protein OppA and of β2-microglobulin bound to a citrate coated gold surface. This work shows the potential of the method in the most representative biological processes involving proteins, and provides a valuable alternative, principally in the shown cases, where other approaches are problematic.
Entropy Based Classifier Combination for Sentence Segmentation
2007-01-01
speaker diarization system to divide the audio data into hypothetical speakers [17...the prosodic feature also includes turn-based features which describe the position of a word in relation to diarization seg- mentation. The speaker ...ro- bust speaker segmentation: the ICSI-SRI fall 2004 diarization system,” in Proc. RT-04F Workshop, 2004. [18] “The rich transcription fall 2003,” http://nist.gov/speech/tests/rt/rt2003/fall/docs/rt03-fall-eval- plan-v9.pdf.
An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression
Weiss, Brandi A.; Dardick, William
2016-01-01
This article introduces an entropy-based measure of data-model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify…
2D Tsallis Entropy for Image Segmentation Based on Modified Chaotic Bat Algorithm
Directory of Open Access Journals (Sweden)
Zhiwei Ye
2018-03-01
Full Text Available Image segmentation is a significant step in image analysis and computer vision. Many entropy based approaches have been presented in this topic; among them, Tsallis entropy is one of the best performing methods. However, 1D Tsallis entropy does not consider make use of the spatial correlation information within the neighborhood results might be ruined by noise. Therefore, 2D Tsallis entropy is proposed to solve the problem, and results are compared with 1D Fisher, 1D maximum entropy, 1D cross entropy, 1D Tsallis entropy, fuzzy entropy, 2D Fisher, 2D maximum entropy and 2D cross entropy. On the other hand, due to the existence of huge computational costs, meta-heuristics algorithms like genetic algorithm (GA, particle swarm optimization (PSO, ant colony optimization algorithm (ACO and differential evolution algorithm (DE are used to accelerate the 2D Tsallis entropy thresholding method. In this paper, considering 2D Tsallis entropy as a constrained optimization problem, the optimal thresholds are acquired by maximizing the objective function using a modified chaotic Bat algorithm (MCBA. The proposed algorithm has been tested on some actual and infrared images. The results are compared with that of PSO, GA, ACO and DE and demonstrate that the proposed method outperforms other approaches involved in the paper, which is a feasible and effective option for image segmentation.
Entropy-based implied volatility and its information content
X. Xiao (Xiao); C. Zhou (Chen)
2016-01-01
markdownabstractThis paper investigates the maximum entropy approach on estimating implied volatility. The entropy approach also allows to measure option implied skewness and kurtosis nonparametrically, and to construct confidence intervals. Simulations show that the en- tropy approach outperforms
Inhomogeneity of epidemic spreading with entropy-based infected clusters.
Wen-Jie, Zhou; Xing-Yuan, Wang
2013-12-01
Considering the difference in the sizes of the infected clusters in the dynamic complex networks, the normalized entropy based on infected clusters (δ*) is proposed to characterize the inhomogeneity of epidemic spreading. δ* gives information on the variability of the infected clusters in the system. We investigate the variation in the inhomogeneity of the distribution of the epidemic with the absolute velocity v of moving agent, the infection density ρ, and the interaction radius r. By comparing δ* in the dynamic networks with δH* in homogeneous mode, the simulation experiments show that the inhomogeneity of epidemic spreading becomes smaller with the increase of v, ρ, r.
Towards an entropy-based detached-eddy simulation
Zhao, Rui; Yan, Chao; Li, XinLiang; Kong, WeiXuan
2013-10-01
A concept of entropy increment ratio ( s¯) is introduced for compressible turbulence simulation through a series of direct numerical simulations (DNS). s¯ represents the dissipation rate per unit mechanical energy with the benefit of independence of freestream Mach numbers. Based on this feature, we construct the shielding function f s to describe the boundary layer region and propose an entropy-based detached-eddy simulation method (SDES). This approach follows the spirit of delayed detached-eddy simulation (DDES) proposed by Spalart et al. in 2005, but it exhibits much better behavior after their performances are compared in the following flows, namely, pure attached flow with thick boundary layer (a supersonic flat-plate flow with high Reynolds number), fully separated flow (the supersonic base flow), and separated-reattached flow (the supersonic cavity-ramp flow). The Reynolds-averaged Navier-Stokes (RANS) resolved region is reliably preserved and the modeled stress depletion (MSD) phenomenon which is inherent in DES and DDES is partly alleviated. Moreover, this new hybrid strategy is simple and general, making it applicable to other models related to the boundary layer predictions.
Feedback structure based entropy approach for multiple-model estimation
Institute of Scientific and Technical Information of China (English)
Shen-tu Han; Xue Anke; Guo Yunfei
2013-01-01
The variable-structure multiple-model (VSMM) approach, one of the multiple-model (MM) methods, is a popular and effective approach in handling problems with mode uncertainties. The model sequence set adaptation (MSA) is the key to design a better VSMM. However, MSA methods in the literature have big room to improve both theoretically and practically. To this end, we propose a feedback structure based entropy approach that could find the model sequence sets with the smallest size under certain conditions. The filtered data are fed back in real time and can be used by the minimum entropy (ME) based VSMM algorithms, i.e., MEVSMM. Firstly, the full Markov chains are used to achieve optimal solutions. Secondly, the myopic method together with particle filter (PF) and the challenge match algorithm are also used to achieve sub-optimal solutions, a trade-off between practicability and optimality. The numerical results show that the proposed algorithm provides not only refined model sets but also a good robustness margin and very high accuracy.
Multiscale Permutation Entropy Based Rolling Bearing Fault Diagnosis
Directory of Open Access Journals (Sweden)
Jinde Zheng
2014-01-01
Full Text Available A new rolling bearing fault diagnosis approach based on multiscale permutation entropy (MPE, Laplacian score (LS, and support vector machines (SVMs is proposed in this paper. Permutation entropy (PE was recently proposed and defined to measure the randomicity and detect dynamical changes of time series. However, for the complexity of mechanical systems, the randomicity and dynamic changes of the vibration signal will exist in different scales. Thus, the definition of MPE is introduced and employed to extract the nonlinear fault characteristics from the bearing vibration signal in different scales. Besides, the SVM is utilized to accomplish the fault feature classification to fulfill diagnostic procedure automatically. Meanwhile, in order to avoid a high dimension of features, the Laplacian score (LS is used to refine the feature vector by ranking the features according to their importance and correlations with the main fault information. Finally, the rolling bearing fault diagnosis method based on MPE, LS, and SVM is proposed and applied to the experimental data. The experimental data analysis results indicate that the proposed method could identify the fault categories effectively.
Ensemble of classifiers based network intrusion detection system performance bound
CSIR Research Space (South Africa)
Mkuzangwe, Nenekazi NP
2017-11-01
Full Text Available This paper provides a performance bound of a network intrusion detection system (NIDS) that uses an ensemble of classifiers. Currently researchers rely on implementing the ensemble of classifiers based NIDS before they can determine the performance...
Cao, Yuzhen; Cai, Lihui; Wang, Jiang; Wang, Ruofan; Yu, Haitao; Cao, Yibin; Liu, Jing
2015-08-01
In this paper, experimental neurophysiologic recording and statistical analysis are combined to investigate the nonlinear characteristic and the cognitive function of the brain. Fuzzy approximate entropy and fuzzy sample entropy are applied to characterize the model-based simulated series and electroencephalograph (EEG) series of Alzheimer's disease (AD). The effectiveness and advantages of these two kinds of fuzzy entropy are first verified through the simulated EEG series generated by the alpha rhythm model, including stronger relative consistency and robustness. Furthermore, in order to detect the abnormality of irregularity and chaotic behavior in the AD brain, the complexity features based on these two fuzzy entropies are extracted in the delta, theta, alpha, and beta bands. It is demonstrated that, due to the introduction of fuzzy set theory, the fuzzy entropies could better distinguish EEG signals of AD from that of the normal than the approximate entropy and sample entropy. Moreover, the entropy values of AD are significantly decreased in the alpha band, particularly in the temporal brain region, such as electrode T3 and T4. In addition, fuzzy sample entropy could achieve higher group differences in different brain regions and higher average classification accuracy of 88.1% by support vector machine classifier. The obtained results prove that fuzzy sample entropy may be a powerful tool to characterize the complexity abnormalities of AD, which could be helpful in further understanding of the disease.
An Alternative to Chaid Segmentation Algorithm Based on Entropy.
Directory of Open Access Journals (Sweden)
María Purificación Galindo Villardón
2010-07-01
Full Text Available The CHAID (Chi-Squared Automatic Interaction Detection treebased segmentation technique has been found to be an effective approach for obtaining meaningful segments that are predictive of a K-category (nominal or ordinal criterion variable. CHAID was designed to detect, in an automatic way, the nteraction between several categorical or ordinal predictors in explaining a categorical response, but, this may not be true when Simpson’s paradox is present. This is due to the fact that CHAID is a forward selection algorithm based on the marginal counts. In this paper we propose a backwards elimination algorithm that starts with the full set of predictors (or full tree and eliminates predictors progressively. The elimination procedure is based on Conditional Independence contrasts using the concept of entropy. The proposed procedure is compared to CHAID.
Scale-invariant entropy-based theory for dynamic ordering
International Nuclear Information System (INIS)
Mahulikar, Shripad P.; Kumari, Priti
2014-01-01
Dynamically Ordered self-organized dissipative structure exists in various forms and at different scales. This investigation first introduces the concept of an isolated embedding system, which embeds an open system, e.g., dissipative structure and its mass and/or energy exchange with its surroundings. Thereafter, scale-invariant theoretical analysis is presented using thermodynamic principles for Order creation, existence, and destruction. The sustainability criterion for Order existence based on its structured mass and/or energy interactions with the surroundings is mathematically defined. This criterion forms the basis for the interrelationship of physical parameters during sustained existence of dynamic Order. It is shown that the sufficient condition for dynamic Order existence is approached if its sustainability criterion is met, i.e., its destruction path is blocked. This scale-invariant approach has the potential to unify the physical understanding of universal dynamic ordering based on entropy considerations
Some Comments on the Entropy-Based Criteria for Piping
Directory of Open Access Journals (Sweden)
Emöke Imre
2015-04-01
Full Text Available This paper is an extension of previous work which characterises soil behaviours using the grading entropy diagram. The present work looks at the piping process in granular soils, by considering some new data from flood-protection dikes. The piping process is divided into three parts here: particle movement at the micro scale to segregate free water; sand boil development (which is the initiation of the pipe, and pipe growth. In the first part of the process, which occurs during the rising flood, the increase in shear stress along the dike base may cause segregation of water into micro pipes if the subsoil in the dike base is relatively loose. This occurs at the maximum dike base shear stress level (ratio of shear stress and strength zone which is close to the toe. In the second part of the process, the shear strain increment causes a sudden, asymmetric slide and cracking of the dike leading to the localized excess pore pressure, liquefaction and the formation of a sand boil. In the third part of the process, the soil erosion initiated through the sand boil continues, and the pipe grows. The piping in the Hungarian dikes often occurs in a two-layer system; where the base layer is coarser with higher permeability and the cover layer is finer with lower permeability. The new data presented here show that the soils ejected from the sand boils are generally silty sands and sands, which are prone to both erosion (on the basis of the entropy criterion and liquefaction. They originate from the cover layer which is basically identical to the soil used in the Dutch backward erosion experiments.
IN-cross Entropy Based MAGDM Strategy under Interval Neutrosophic Set Environment
Directory of Open Access Journals (Sweden)
Shyamal Dalapati
2017-12-01
Full Text Available Cross entropy measure is one of the best way to calculate the divergence of any variable from the priori one variable. We define a new cross entropy measure under interval neutrosophic set (INS environment, which we call IN-cross entropy measure and prove its basic properties. We also develop weighted IN-cross entropy measure and investigats its basic properties. Based on the weighted IN-cross entropy measure, we develop a novel strategy for multi attribute group decision making (MAGDM strategy under interval neutrosophic environment. The proposed multi attribute group decision making strategy is compared with the existing cross entropy measure based strategy in the literature under interval neutrosophic set environment. Finally, an illustrative example of multi attribute group decision making problem is solved to show the feasibility, validity and efficiency of the proposed MAGDM strategy.
LIBOR troubles: Anomalous movements detection based on maximum entropy
Bariviera, Aurelio F.; Martín, María T.; Plastino, Angelo; Vampa, Victoria
2016-05-01
According to the definition of the London Interbank Offered Rate (LIBOR), contributing banks should give fair estimates of their own borrowing costs in the interbank market. Between 2007 and 2009, several banks made inappropriate submissions of LIBOR, sometimes motivated by profit-seeking from their trading positions. In 2012, several newspapers' articles began to cast doubt on LIBOR integrity, leading surveillance authorities to conduct investigations on banks' behavior. Such procedures resulted in severe fines imposed to involved banks, who recognized their financial inappropriate conduct. In this paper, we uncover such unfair behavior by using a forecasting method based on the Maximum Entropy principle. Our results are robust against changes in parameter settings and could be of great help for market surveillance.
Entropy-Based Block Processing for Satellite Image Registration
Directory of Open Access Journals (Sweden)
Ikhyun Lee
2012-11-01
Full Text Available Image registration is an important task in many computer vision applications such as fusion systems, 3D shape recovery and earth observation. Particularly, registering satellite images is challenging and time-consuming due to limited resources and large image size. In such scenario, state-of-the-art image registration methods such as scale-invariant feature transform (SIFT may not be suitable due to high processing time. In this paper, we propose an algorithm based on block processing via entropy to register satellite images. The performance of the proposed method is evaluated using different real images. The comparative analysis shows that it not only reduces the processing time but also enhances the accuracy.
Global sensitivity analysis for fuzzy inputs based on the decomposition of fuzzy output entropy
Shi, Yan; Lu, Zhenzhou; Zhou, Yicheng
2018-06-01
To analyse the component of fuzzy output entropy, a decomposition method of fuzzy output entropy is first presented. After the decomposition of fuzzy output entropy, the total fuzzy output entropy can be expressed as the sum of the component fuzzy entropy contributed by fuzzy inputs. Based on the decomposition of fuzzy output entropy, a new global sensitivity analysis model is established for measuring the effects of uncertainties of fuzzy inputs on the output. The global sensitivity analysis model can not only tell the importance of fuzzy inputs but also simultaneously reflect the structural composition of the response function to a certain degree. Several examples illustrate the validity of the proposed global sensitivity analysis, which is a significant reference in engineering design and optimization of structural systems.
Quantum key distribution with finite resources: Smooth Min entropy vs. Smooth Renyi entropy
Energy Technology Data Exchange (ETDEWEB)
Mertz, Markus; Abruzzo, Silvestre; Bratzik, Sylvia; Kampermann, Hermann; Bruss, Dagmar [Institut fuer Theoretische Physik III, Duesseldorf (Germany)
2010-07-01
We consider different entropy measures that play an important role in the analysis of the security of QKD with finite resources. The smooth min entropy leads to an optimal bound for the length of a secure key. Another bound on the secure key length was derived by using Renyi entropies. Unfortunately, it is very hard or even impossible to calculate these entropies for realistic QKD scenarios. To estimate the security rate it becomes important to find computable bounds on these entropies. Here, we compare a lower bound for the smooth min entropy with a bound using Renyi entropies. We compare these entropies for the six-state protocol with symmetric attacks.
Entropy-based critical reaction time for mixing-controlled reactive transport
DEFF Research Database (Denmark)
Chiogna, Gabriele; Rolle, Massimo
2017-01-01
Entropy-based metrics, such as the dilution index, have been proposed to quantify dilution and reactive mixing in solute transport problems. In this work, we derive the transient advection dispersion equation for the entropy density of a reactive plume. We restrict our analysis to the case where...... the concentration distribution of the transported species is Gaussian and we observe that, even in case of an instantaneous complete bimolecular reaction, dilution caused by dispersive processes dominates the entropy balance at early times and results in the net increase of the entropy density of a reactive species...
Multi-Level Wavelet Shannon Entropy-Based Method for Single-Sensor Fault Location
Directory of Open Access Journals (Sweden)
Qiaoning Yang
2015-10-01
Full Text Available In actual application, sensors are prone to failure because of harsh environments, battery drain, and sensor aging. Sensor fault location is an important step for follow-up sensor fault detection. In this paper, two new multi-level wavelet Shannon entropies (multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy are defined. They take full advantage of sensor fault frequency distribution and energy distribution across multi-subband in wavelet domain. Based on the multi-level wavelet Shannon entropy, a method is proposed for single sensor fault location. The method firstly uses a criterion of maximum energy-to-Shannon entropy ratio to select the appropriate wavelet base for signal analysis. Then multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy are used to locate the fault. The method is validated using practical chemical gas concentration data from a gas sensor array. Compared with wavelet time Shannon entropy and wavelet energy Shannon entropy, the experimental results demonstrate that the proposed method can achieve accurate location of a single sensor fault and has good anti-noise ability. The proposed method is feasible and effective for single-sensor fault location.
Dynamic Garment Simulation based on Hybrid Bounding Volume Hierarchy
Directory of Open Access Journals (Sweden)
Zhu Dongyong
2016-12-01
Full Text Available In order to solve the computing speed and efficiency problem of existing dynamic clothing simulation, this paper presents a dynamic garment simulation based on a hybrid bounding volume hierarchy. It firstly uses MCASG graph theory to do the primary segmentation for a given three-dimensional human body model. And then it applies K-means cluster to do the secondary segmentation to collect the human body’s upper arms, lower arms, upper legs, lower legs, trunk, hip and woman’s chest as the elementary units of dynamic clothing simulation. According to different shapes of these elementary units, it chooses the closest and most efficient hybrid bounding box to specify these units, such as cylinder bounding box and elliptic cylinder bounding box. During the process of constructing these bounding boxes, it uses the least squares method and slices of the human body to get the related parameters. This approach makes it possible to use the least amount of bounding boxes to create close collision detection regions for the appearance of the human body. A spring-mass model based on a triangular mesh of the clothing model is finally constructed for dynamic simulation. The simulation result shows the feasibility and superiority of the method described.
Parameters Tuning of Model Free Adaptive Control Based on Minimum Entropy
Institute of Scientific and Technical Information of China (English)
Chao Ji; Jing Wang; Liulin Cao; Qibing Jin
2014-01-01
Dynamic linearization based model free adaptive control(MFAC) algorithm has been widely used in practical systems, in which some parameters should be tuned before it is successfully applied to process industries. Considering the random noise existing in real processes, a parameter tuning method based on minimum entropy optimization is proposed,and the feature of entropy is used to accurately describe the system uncertainty. For cases of Gaussian stochastic noise and non-Gaussian stochastic noise, an entropy recursive optimization algorithm is derived based on approximate model or identified model. The extensive simulation results show the effectiveness of the minimum entropy optimization for the partial form dynamic linearization based MFAC. The parameters tuned by the minimum entropy optimization index shows stronger stability and more robustness than these tuned by other traditional index,such as integral of the squared error(ISE) or integral of timeweighted absolute error(ITAE), when the system stochastic noise exists.
Upper entropy axioms and lower entropy axioms
International Nuclear Information System (INIS)
Guo, Jin-Li; Suo, Qi
2015-01-01
The paper suggests the concepts of an upper entropy and a lower entropy. We propose a new axiomatic definition, namely, upper entropy axioms, inspired by axioms of metric spaces, and also formulate lower entropy axioms. We also develop weak upper entropy axioms and weak lower entropy axioms. Their conditions are weaker than those of Shannon–Khinchin axioms and Tsallis axioms, while these conditions are stronger than those of the axiomatics based on the first three Shannon–Khinchin axioms. The subadditivity and strong subadditivity of entropy are obtained in the new axiomatics. Tsallis statistics is a special case of satisfying our axioms. Moreover, different forms of information measures, such as Shannon entropy, Daroczy entropy, Tsallis entropy and other entropies, can be unified under the same axiomatics
Towards an entropy-based analysis of log variability
DEFF Research Database (Denmark)
Back, Christoffer Olling; Debois, Søren; Slaats, Tijs
2017-01-01
the development of hybrid miners: given a (sub-)log, can we determine a priori whether the log is best suited for imperative or declarative mining? We propose using the concept of entropy, commonly used in information theory. We consider different measures for entropy that could be applied and show through...... experimentation on both synthetic and real-life logs that these entropy measures do indeed give insights into the complexity of the log and can act as an indicator of which mining paradigm should be used....
Towards an Entropy-based Analysis of Log Variability
DEFF Research Database (Denmark)
Back, Christoffer Olling; Debois, Søren; Slaats, Tijs
2018-01-01
the development of hybrid miners: given a log, can we determine a priori whether the log is best suited for imperative or declarative mining? We propose using the concept of entropy, commonly used in information theory. We consider different measures for entropy that could be applied and show through...... experimentation on both synthetic and real-life logs that these entropy measures do indeed give insights into the complexity of the log and can act as an indicator of which mining paradigm should be used....
Symbolic transfer entropy-based premature signal analysis
International Nuclear Information System (INIS)
Wang Jun; Yu Zheng-Feng
2012-01-01
In this paper, we use symbolic transfer entropy to study the coupling strength between premature signals. Numerical experiments show that three types of signal couplings are in the same direction. Among them, normal signal coupling is the strongest, followed by that of premature ventricular contractions, and that of atrial premature beats is the weakest. The T test shows that the entropies of the three signals are distinct. Symbolic transfer entropy requires less data, can distinguish the three types of signals and has very good computational efficiency. (interdisciplinary physics and related areas of science and technology)
Calculating the Entropy of Solid and Liquid Metals, Based on Acoustic Data
Tekuchev, V. V.; Kalinkin, D. P.; Ivanova, I. V.
2018-05-01
The entropies of iron, cobalt, rhodium, and platinum are studied for the first time, based on acoustic data and using the Debye theory and rigid-sphere model, from 298 K up to the boiling point. A formula for the melting entropy of metals is validated. Good agreement between the research results and the literature data is obtained.
Damage detection in rotating machinery by means of entropy-based parameters
Tocarciuc, Alexandru; Bereteu, Liviu; ǎgǎnescu, Gheorghe Eugen, Dr
2014-11-01
The paper is proposing two new entropy-based parameters, namely Renyi Entropy Index (REI) and Sharma-Mittal Entropy Index (SMEI), for detecting the presence of failures (or damages) in rotating machinery, namely: belt structural damage, belt wheels misalignment, failure of the fixing bolt of the machine to its baseplate and eccentricities (i.e.: due to detaching a small piece of material or bad mounting of the rotating components of the machine). The algorithms to obtain the proposed entropy-based parameters are described and test data is used in order to assess their sensitivity. A vibration test bench is used for measuring the levels of vibration while artificially inducing damage. The deviation of the two entropy-based parameters is compared in two states of the vibration test bench: not damaged and damaged. At the end of the study, their sensitivity is compared to Shannon Entropic Index.
Entropy-Based Model for Interpreting Life Systems in Traditional Chinese Medicine
Directory of Open Access Journals (Sweden)
Guo-lian Kang
2008-01-01
Full Text Available Traditional Chinese medicine (TCM treats qi as the core of the human life systems. Starting with a hypothetical correlation between TCM qi and the entropy theory, we address in this article a holistic model for evaluating and unveiling the rule of TCM life systems. Several new concepts such as acquired life entropy (ALE, acquired life entropy flow (ALEF and acquired life entropy production (ALEP are propounded to interpret TCM life systems. Using the entropy theory, mathematical models are established for ALE, ALEF and ALEP, which reflect the evolution of life systems. Some criteria are given on physiological activities and pathological changes of the body in different stages of life. Moreover, a real data-based simulation shows life entropies of the human body with different ages, Cold and Hot constitutions and in different seasons in North China are coincided with the manifestations of qi as well as the life evolution in TCM descriptions. Especially, based on the comparative and quantitative analysis, the entropy-based model can nicely describe the evolution of life entropies in Cold and Hot individuals thereby fitting the Yin–Yang theory in TCM. Thus, this work establishes a novel approach to interpret the fundamental principles in TCM, and provides an alternative understanding for the complex life systems.
Application of entropy measurement technique in grey based ...
African Journals Online (AJOL)
For this study, four control variables are selected current, voltage, gas flow rate and ... Keywords: Metal Inert Gas (MIG) Welding, Grey-Taguchi Method, Entropy ...... of metal inert gas welding on the corrosion and mechanical behaviour of.
Sample Entropy-Based Approach to Evaluate the Stability of Double-Wire Pulsed MIG Welding
Directory of Open Access Journals (Sweden)
Ping Yao
2014-01-01
Full Text Available According to the sample entropy, this paper deals with a quantitative method to evaluate the current stability in double-wire pulsed MIG welding. Firstly, the sample entropy of current signals with different stability but the same parameters is calculated. The results show that the more stable the current, the smaller the value and the standard deviation of sample entropy. Secondly, four parameters, which are pulse width, peak current, base current, and frequency, are selected for four-level three-factor orthogonal experiment. The calculation and analysis of desired signals indicate that sample entropy values are affected by welding current parameters. Then, a quantitative method based on sample entropy is proposed. The experiment results show that the method can preferably quantify the welding current stability.
An entropy-based analysis of lane changing behavior: An interactive approach.
Kosun, Caglar; Ozdemir, Serhan
2017-05-19
As a novelty, this article proposes the nonadditive entropy framework for the description of driver behaviors during lane changing. The authors also state that this entropy framework governs the lane changing behavior in traffic flow in accordance with the long-range vehicular interactions and traffic safety. The nonadditive entropy framework is the new generalized theory of thermostatistical mechanics. Vehicular interactions during lane changing are considered within this framework. The interactive approach for the lane changing behavior of the drivers is presented in the traffic flow scenarios presented in the article. According to the traffic flow scenarios, 4 categories of traffic flow and driver behaviors are obtained. Through the scenarios, comparative analyses of nonadditive and additive entropy domains are also provided. Two quadrants of the categories belong to the nonadditive entropy; the rest are involved in the additive entropy domain. Driving behaviors are extracted and the scenarios depict that nonadditivity matches safe driving well, whereas additivity corresponds to unsafe driving. Furthermore, the cooperative traffic system is considered in nonadditivity where the long-range interactions are present. However, the uncooperative traffic system falls into the additivity domain. The analyses also state that there would be possible traffic flow transitions among the quadrants. This article shows that lane changing behavior could be generalized as nonadditive, with additivity as a special case, based on the given traffic conditions. The nearest and close neighbor models are well within the conventional additive entropy framework. In this article, both the long-range vehicular interactions and safe driving behavior in traffic are handled in the nonadditive entropy domain. It is also inferred that the Tsallis entropy region would correspond to mandatory lane changing behavior, whereas additive and either the extensive or nonextensive entropy region would
Entropy-based Probabilistic Fatigue Damage Prognosis and Algorithmic Performance Comparison
National Aeronautics and Space Administration — In this paper, a maximum entropy-based general framework for probabilistic fatigue damage prognosis is investigated. The proposed methodology is based on an...
Entropy-based probabilistic fatigue damage prognosis and algorithmic performance comparison
National Aeronautics and Space Administration — In this paper, a maximum entropy-based general framework for probabilistic fatigue damage prognosis is investigated. The proposed methodology is based on an...
Confidence bounds of recurrence-based complexity measures
International Nuclear Information System (INIS)
Schinkel, Stefan; Marwan, N.; Dimigen, O.; Kurths, J.
2009-01-01
In the recent past, recurrence quantification analysis (RQA) has gained an increasing interest in various research areas. The complexity measures the RQA provides have been useful in describing and analysing a broad range of data. It is known to be rather robust to noise and nonstationarities. Yet, one key question in empirical research concerns the confidence bounds of measured data. In the present Letter we suggest a method for estimating the confidence bounds of recurrence-based complexity measures. We study the applicability of the suggested method with model and real-life data.
International Nuclear Information System (INIS)
Luo Qiang; Schwarz, Bjoern; Mattern, Norbert; Eckert, Juergen
2010-01-01
We study the effects of amorphous structure and random anisotropy on the magnetic entropy change in a series of Tb-based amorphous alloys. The amorphous structure broadens the peak of magnetic entropy change and facilitates the adjustment of properties. The peak magnetic entropy change above the spin freezing temperature first depends on the average magnetic moment approximately linearly and second on the exchange interaction and random anisotropy. Large and broad reversible negative magnetic entropy changes are observed above the spin freezing temperature and giant positive irreversible magnetic entropy changes which associate with the internal entropy production are obtained well below.
Entropy-Based Economic Denial of Sustainability Detection
Directory of Open Access Journals (Sweden)
Marco Antonio Sotelo Monge
2017-11-01
Full Text Available In recent years, an important increase in the amount and impact of Distributed Denial of Service (DDoS threats has been reported by the different information security organizations. They typically target the depletion of the computational resources of the victims, hence drastically harming their operational capabilities. Inspired by these methods, Economic Denial of Sustainability (EDoS attacks pose a similar motivation, but adapted to Cloud computing environments, where the denial is achieved by damaging the economy of both suppliers and customers. Therefore, the most common EDoS approach is making the offered services unsustainable by exploiting their auto-scaling algorithms. In order to contribute to their mitigation, this paper introduces a novel EDoS detection method based on the study of entropy variations related with metrics taken into account when deciding auto-scaling actuations. Through the prediction and definition of adaptive thresholds, unexpected behaviors capable of fraudulently demand new resource hiring are distinguished. With the purpose of demonstrate the effectiveness of the proposal, an experimental scenario adapted to the singularities of the EDoS threats and the assumptions driven by their original definition is described in depth. The preliminary results proved high accuracy.
Entropy-based model for miRNA isoform analysis.
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Shengqin Wang
Full Text Available MiRNAs have been widely studied due to their important post-transcriptional regulatory roles in gene expression. Many reports have demonstrated the evidence of miRNA isoform products (isomiRs in high-throughput small RNA sequencing data. However, the biological function involved in these molecules is still not well investigated. Here, we developed a Shannon entropy-based model to estimate isomiR expression profiles of high-throughput small RNA sequencing data extracted from miRBase webserver. By using the Kolmogorov-Smirnov statistical test (KS test, we demonstrated that the 5p and 3p miRNAs present more variants than the single arm miRNAs. We also found that the isomiR variant, except the 3' isomiR variant, is strongly correlated with Minimum Free Energy (MFE of pre-miRNA, suggesting the intrinsic feature of pre-miRNA should be one of the important factors for the miRNA regulation. The functional enrichment analysis showed that the miRNAs with high variation, particularly the 5' end variation, are enriched in a set of critical functions, supporting these molecules should not be randomly produced. Our results provide a probabilistic framework for miRNA isoforms analysis, and give functional insights into pre-miRNA processing.
Entropy-Based Video Steganalysis of Motion Vectors
Directory of Open Access Journals (Sweden)
Elaheh Sadat Sadat
2018-04-01
Full Text Available In this paper, a new method is proposed for motion vector steganalysis using the entropy value and its combination with the features of the optimized motion vector. In this method, the entropy of blocks is calculated to determine their texture and the precision of their motion vectors. Then, by using a fuzzy cluster, the blocks are clustered into the blocks with high and low texture, while the membership function of each block to a high texture class indicates the texture of that block. These membership functions are used to weight the effective features that are extracted by reconstructing the motion estimation equations. Characteristics of the results indicate that the use of entropy and the irregularity of each block increases the precision of the final video classification into cover and stego classes.
Directory of Open Access Journals (Sweden)
Zhendong Mu
2017-02-01
Full Text Available Driver fatigue has become one of the major causes of traffic accidents, and is a complicated physiological process. However, there is no effective method to detect driving fatigue. Electroencephalography (EEG signals are complex, unstable, and non-linear; non-linear analysis methods, such as entropy, maybe more appropriate. This study evaluates a combined entropy-based processing method of EEG data to detect driver fatigue. In this paper, 12 subjects were selected to take part in an experiment, obeying driving training in a virtual environment under the instruction of the operator. Four types of enthrones (spectrum entropy, approximate entropy, sample entropy and fuzzy entropy were used to extract features for the purpose of driver fatigue detection. Electrode selection process and a support vector machine (SVM classification algorithm were also proposed. The average recognition accuracy was 98.75%. Retrospective analysis of the EEG showed that the extracted features from electrodes T5, TP7, TP8 and FP1 may yield better performance. SVM classification algorithm using radial basis function as kernel function obtained better results. A combined entropy-based method demonstrates good classification performance for studying driver fatigue detection.
Bias-based modeling and entropy analysis of PUFs
van den Berg, R.; Skoric, B.; Leest, van der V.
2013-01-01
Physical Unclonable Functions (PUFs) are increasingly becoming a well-known security primitive for secure key storage and anti-counterfeiting. For both applications it is imperative that PUFs provide enough entropy. The aim of this paper is to propose a new model for binary-output PUFs such as SRAM,
Sharmila, A; Aman Raj, Suman; Shashank, Pandey; Mahalakshmi, P
2018-01-01
In this work, we have used a time-frequency domain analysis method called discrete wavelet transform (DWT) technique. This method stand out compared to other proposed methods because of its algorithmic elegance and accuracy. A wavelet is a mathematical function based on time-frequency analysis in signal processing. It is useful particularly because it allows a weak signal to be recovered from a noisy signal without much distortion. A wavelet analysis works by analysing the image and converting it to mathematical function which is decoded by the receiver. Furthermore, we have used Shannon entropy and approximate entropy (ApEn) for extracting the complexities associated with electroencephalographic (EEG) signals. The ApEn is a suitable feature to characterise the EEGs because its value drops suddenly due to excessive synchronous discharge of neurons in the brain during epileptic activity in this study. EEG signals are decomposed into six EEG sub-bands namely D1-D5 and A5 using DWT technique. Non-linear features such as ApEn and Shannon entropy are calculated from these sub-bands and support vector machine classifiers are used for classification purpose. This scheme is tested using EEG data recorded from five healthy subjects and five epileptic patients during the inter-ictal and ictal periods. The data are acquired from University of Bonn, Germany. The proposed method is evaluated through 15 classification problems, and obtained high classification accuracy of 100% for two cases and it indicates the good classifying performance of the proposed method.
Entropy Viscosity and L1-based Approximations of PDEs: Exploiting Sparsity
2015-10-23
AFRL-AFOSR-VA-TR-2015-0337 Entropy Viscosity and L1-based Approximations of PDEs: Exploiting Sparsity Jean-Luc Guermond TEXAS A & M UNIVERSITY 750...REPORT DATE (DD-MM-YYYY) 09-05-2015 2. REPORT TYPE Final report 3. DATES COVERED (From - To) 01-07-2012 - 30-06-2015 4. TITLE AND SUBTITLE Entropy ...conservation equations can be stabilized by using the so-called entropy viscosity method and we proposed to to investigate this new technique. We
Towards an information extraction and knowledge formation framework based on Shannon entropy
Directory of Open Access Journals (Sweden)
Iliescu Dragoș
2017-01-01
Full Text Available Information quantity subject is approached in this paperwork, considering the specific domain of nonconforming product management as information source. This work represents a case study. Raw data were gathered from a heavy industrial works company, information extraction and knowledge formation being considered herein. Involved method for information quantity estimation is based on Shannon entropy formula. Information and entropy spectrum are decomposed and analysed for extraction of specific information and knowledge-that formation. The result of the entropy analysis point out the information needed to be acquired by the involved organisation, this being presented as a specific knowledge type.
Preimage entropy dimension of topological dynamical systems
Liu, Lei; Zhou, Xiaomin; Zhou, Xiaoyao
2014-01-01
We propose a new definition of preimage entropy dimension for continuous maps on compact metric spaces, investigate fundamental properties of the preimage entropy dimension, and compare the preimage entropy dimension with the topological entropy dimension. The defined preimage entropy dimension holds various basic properties of topological entropy dimension, for example, the preimage entropy dimension of a subsystem is bounded by that of the original system and topologically conjugated system...
Jiang, Quansheng; Shen, Yehu; Li, Hua; Xu, Fengyu
2018-01-24
Feature recognition and fault diagnosis plays an important role in equipment safety and stable operation of rotating machinery. In order to cope with the complexity problem of the vibration signal of rotating machinery, a feature fusion model based on information entropy and probabilistic neural network is proposed in this paper. The new method first uses information entropy theory to extract three kinds of characteristics entropy in vibration signals, namely, singular spectrum entropy, power spectrum entropy, and approximate entropy. Then the feature fusion model is constructed to classify and diagnose the fault signals. The proposed approach can combine comprehensive information from different aspects and is more sensitive to the fault features. The experimental results on simulated fault signals verified better performances of our proposed approach. In real two-span rotor data, the fault detection accuracy of the new method is more than 10% higher compared with the methods using three kinds of information entropy separately. The new approach is proved to be an effective fault recognition method for rotating machinery.
de Klerk, Etienne; Laurent, Monique
We consider the problem of minimizing a continuous function f over a compact set K. We compare the hierarchy of upper bounds proposed by Lasserre in [SIAM J. Optim. 21(3) (2011), pp. 864-885] to bounds that may be obtained from simulated annealing. We show that, when f is a polynomial and K a convex
Xu, Pengcheng; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi; Liu, Jiufu; Zou, Ying; He, Ruimin
2017-12-01
Hydrometeorological data are needed for obtaining point and areal mean, quantifying the spatial variability of hydrometeorological variables, and calibration and verification of hydrometeorological models. Hydrometeorological networks are utilized to collect such data. Since data collection is expensive, it is essential to design an optimal network based on the minimal number of hydrometeorological stations in order to reduce costs. This study proposes a two-phase copula entropy- based multiobjective optimization approach that includes: (1) copula entropy-based directional information transfer (CDIT) for clustering the potential hydrometeorological gauges into several groups, and (2) multiobjective method for selecting the optimal combination of gauges for regionalized groups. Although entropy theory has been employed for network design before, the joint histogram method used for mutual information estimation has several limitations. The copula entropy-based mutual information (MI) estimation method is shown to be more effective for quantifying the uncertainty of redundant information than the joint histogram (JH) method. The effectiveness of this approach is verified by applying to one type of hydrometeorological gauge network, with the use of three model evaluation measures, including Nash-Sutcliffe Coefficient (NSC), arithmetic mean of the negative copula entropy (MNCE), and MNCE/NSC. Results indicate that the two-phase copula entropy-based multiobjective technique is capable of evaluating the performance of regional hydrometeorological networks and can enable decision makers to develop strategies for water resources management.
Fozouni, Niloufar; Chopp, Michael; Nejad-Davarani, Siamak P; Zhang, Zheng Gang; Lehman, Norman L; Gu, Steven; Ueno, Yuji; Lu, Mei; Ding, Guangliang; Li, Lian; Hu, Jiani; Bagher-Ebadian, Hassan; Hearshen, David; Jiang, Quan
2013-01-01
To overcome the limitations of conventional diffusion tensor magnetic resonance imaging resulting from the assumption of a Gaussian diffusion model for characterizing voxels containing multiple axonal orientations, Shannon's entropy was employed to evaluate white matter structure in human brain and in brain remodeling after traumatic brain injury (TBI) in a rat. Thirteen healthy subjects were investigated using a Q-ball based DTI data sampling scheme. FA and entropy values were measured in white matter bundles, white matter fiber crossing areas, different gray matter (GM) regions and cerebrospinal fluid (CSF). Axonal densities' from the same regions of interest (ROIs) were evaluated in Bielschowsky and Luxol fast blue stained autopsy (n = 30) brain sections by light microscopy. As a case demonstration, a Wistar rat subjected to TBI and treated with bone marrow stromal cells (MSC) 1 week after TBI was employed to illustrate the superior ability of entropy over FA in detecting reorganized crossing axonal bundles as confirmed by histological analysis with Bielschowsky and Luxol fast blue staining. Unlike FA, entropy was less affected by axonal orientation and more affected by axonal density. A significant agreement (r = 0.91) was detected between entropy values from in vivo human brain and histologically measured axonal density from post mortum from the same brain structures. The MSC treated TBI rat demonstrated that the entropy approach is superior to FA in detecting axonal remodeling after injury. Compared with FA, entropy detected new axonal remodeling regions with crossing axons, confirmed with immunohistological staining. Entropy measurement is more effective in distinguishing axonal remodeling after injury, when compared with FA. Entropy is also more sensitive to axonal density than axonal orientation, and thus may provide a more accurate reflection of axonal changes that occur in neurological injury and disease.
Fozouni, Niloufar; Chopp, Michael; Nejad-Davarani, Siamak P.; Zhang, Zheng Gang; Lehman, Norman L.; Gu, Steven; Ueno, Yuji; Lu, Mei; Ding, Guangliang; Li, Lian; Hu, Jiani; Bagher-Ebadian, Hassan; Hearshen, David; Jiang, Quan
2013-01-01
Background To overcome the limitations of conventional diffusion tensor magnetic resonance imaging resulting from the assumption of a Gaussian diffusion model for characterizing voxels containing multiple axonal orientations, Shannon's entropy was employed to evaluate white matter structure in human brain and in brain remodeling after traumatic brain injury (TBI) in a rat. Methods Thirteen healthy subjects were investigated using a Q-ball based DTI data sampling scheme. FA and entropy values were measured in white matter bundles, white matter fiber crossing areas, different gray matter (GM) regions and cerebrospinal fluid (CSF). Axonal densities' from the same regions of interest (ROIs) were evaluated in Bielschowsky and Luxol fast blue stained autopsy (n = 30) brain sections by light microscopy. As a case demonstration, a Wistar rat subjected to TBI and treated with bone marrow stromal cells (MSC) 1 week after TBI was employed to illustrate the superior ability of entropy over FA in detecting reorganized crossing axonal bundles as confirmed by histological analysis with Bielschowsky and Luxol fast blue staining. Results Unlike FA, entropy was less affected by axonal orientation and more affected by axonal density. A significant agreement (r = 0.91) was detected between entropy values from in vivo human brain and histologically measured axonal density from post mortum from the same brain structures. The MSC treated TBI rat demonstrated that the entropy approach is superior to FA in detecting axonal remodeling after injury. Compared with FA, entropy detected new axonal remodeling regions with crossing axons, confirmed with immunohistological staining. Conclusions Entropy measurement is more effective in distinguishing axonal remodeling after injury, when compared with FA. Entropy is also more sensitive to axonal density than axonal orientation, and thus may provide a more accurate reflection of axonal changes that occur in neurological injury and disease
The Grading Entropy-based Criteria for Structural Stability of Granular Materials and Filters
Directory of Open Access Journals (Sweden)
Janos Lőrincz
2015-05-01
Full Text Available This paper deals with three grading entropy-based rules that describe different soil structure stability phenomena: an internal stability rule, a filtering rule and a segregation rule. These rules are elaborated on the basis of a large amount of laboratory testing and from existing knowledge in the field. Use is made of the theory of grading entropy to derive parameters which incorporate all of the information of the grading curve into a pair of entropy-based parameters that allow soils with common behaviours to be grouped into domains on an entropy diagram. Applications of the derived entropy-based rules are presented by examining the reason of a dam failure, by testing against the existing filter rules from the literature, and by giving some examples for the design of non-segregating grading curves (discrete particle size distributions by dry weight. A physical basis for the internal stability rule is established, wherein the higher values of base entropy required for granular stability are shown to reflect the closeness between the mean and maximum grain diameters, which explains how there are sufficient coarser grains to achieve a stable grain skeleton.
Improved Ordinary Measure and Image Entropy Theory based intelligent Copy Detection Method
Directory of Open Access Journals (Sweden)
Dengpan Ye
2011-10-01
Full Text Available Nowadays, more and more multimedia websites appear in social network. It brings some security problems, such as privacy, piracy, disclosure of sensitive contents and so on. Aiming at copyright protection, the copy detection technology of multimedia contents becomes a hot topic. In our previous work, a new computer-based copyright control system used to detect the media has been proposed. Based on this system, this paper proposes an improved media feature matching measure and an entropy based copy detection method. The Levenshtein Distance was used to enhance the matching degree when using for feature matching measure in copy detection. For entropy based copy detection, we make a fusion of the two features of entropy matrix of the entropy feature we extracted. Firstly,we extract the entropy matrix of the image and normalize it. Then, we make a fusion of the eigenvalue feature and the transfer matrix feature of the entropy matrix. The fused features will be used for image copy detection. The experiments show that compared to use these two kinds of features for image detection singly, using feature fusion matching method is apparent robustness and effectiveness. The fused feature has a high detection for copy images which have been received some attacks such as noise, compression, zoom, rotation and so on. Comparing with referred methods, the method proposed is more intelligent and can be achieved good performance.
Conflict management based on belief function entropy in sensor fusion.
Yuan, Kaijuan; Xiao, Fuyuan; Fei, Liguo; Kang, Bingyi; Deng, Yong
2016-01-01
Wireless sensor network plays an important role in intelligent navigation. It incorporates a group of sensors to overcome the limitation of single detection system. Dempster-Shafer evidence theory can combine the sensor data of the wireless sensor network by data fusion, which contributes to the improvement of accuracy and reliability of the detection system. However, due to different sources of sensors, there may be conflict among the sensor data under uncertain environment. Thus, this paper proposes a new method combining Deng entropy and evidence distance to address the issue. First, Deng entropy is adopted to measure the uncertain information. Then, evidence distance is applied to measure the conflict degree. The new method can cope with conflict effectually and improve the accuracy and reliability of the detection system. An example is illustrated to show the efficiency of the new method and the result is compared with that of the existing methods.
An Entropy-Based Statistic for Genomewide Association Studies
Zhao, Jinying; Boerwinkle, Eric; Xiong, Momiao
2005-01-01
Efficient genotyping methods and the availability of a large collection of single-nucleotide polymorphisms provide valuable tools for genetic studies of human disease. The standard χ2 statistic for case-control studies, which uses a linear function of allele frequencies, has limited power when the number of marker loci is large. We introduce a novel test statistic for genetic association studies that uses Shannon entropy and a nonlinear function of allele frequencies to amplify the difference...
Directory of Open Access Journals (Sweden)
Hou Hucan
2017-01-01
Full Text Available Inspired by wide application of the second law of thermodynamics to flow and heat transfer devices, local entropy production analysis method was creatively introduced into energy assessment system of centrifugal water pump. Based on Reynolds stress turbulent model and energy equation model, the steady numerical simulation of the whole flow passage of one IS centrifugal pump was carried out. The local entropy production terms were calculated by user defined functions, mainly including wall entropy production, turbulent entropy production, and viscous entropy production. The numerical results indicated that the irreversible energy loss calculated by the local entropy production method agreed well with that calculated by the traditional method but with some deviations which were probably caused by high rotatability and high curvature of impeller and volute. The wall entropy production and turbulent entropy production took up large part of the whole entropy production about 48.61% and 47.91%, respectively, which indicated that wall friction and turbulent fluctuation were the major factors in affecting irreversible energy loss. Meanwhile, the entropy production rate distribution was discussed and compared with turbulent kinetic energy dissipation rate distribution, it showed that turbulent entropy production rate increased sharply at the near wall regions and both distributed more uniformly. The blade region in leading edge near suction side, trailing edge and volute tongue were the main regions to generate irreversible exergy loss. This research broadens a completely new view in evaluating energy loss and further optimizes pump using entropy production minimization.
Zhao, Yong; Hong, Wen-Xue
2011-11-01
Fast, nondestructive and accurate identification of special quality eggs is an urgent problem. The present paper proposed a new feature extraction method based on symbol entropy to identify near infrared spectroscopy of special quality eggs. The authors selected normal eggs, free range eggs, selenium-enriched eggs and zinc-enriched eggs as research objects and measured the near-infrared diffuse reflectance spectra in the range of 12 000-4 000 cm(-1). Raw spectra were symbolically represented with aggregation approximation algorithm and symbolic entropy was extracted as feature vector. An error-correcting output codes multiclass support vector machine classifier was designed to identify the spectrum. Symbolic entropy feature is robust when parameter changed and the highest recognition rate reaches up to 100%. The results show that the identification method of special quality eggs using near-infrared is feasible and the symbol entropy can be used as a new feature extraction method of near-infrared spectra.
Generalized sample entropy analysis for traffic signals based on similarity measure
Shang, Du; Xu, Mengjia; Shang, Pengjian
2017-05-01
Sample entropy is a prevailing method used to quantify the complexity of a time series. In this paper a modified method of generalized sample entropy and surrogate data analysis is proposed as a new measure to assess the complexity of a complex dynamical system such as traffic signals. The method based on similarity distance presents a different way of signals patterns match showing distinct behaviors of complexity. Simulations are conducted over synthetic data and traffic signals for providing the comparative study, which is provided to show the power of the new method. Compared with previous sample entropy and surrogate data analysis, the new method has two main advantages. The first one is that it overcomes the limitation about the relationship between the dimension parameter and the length of series. The second one is that the modified sample entropy functions can be used to quantitatively distinguish time series from different complex systems by the similar measure.
Alameddine, Ibrahim; Karmakar, Subhankar; Qian, Song S.; Paerl, Hans W.; Reckhow, Kenneth H.
2013-10-01
The total maximum daily load program aims to monitor more than 40,000 standard violations in around 20,000 impaired water bodies across the United States. Given resource limitations, future monitoring efforts have to be hedged against the uncertainties in the monitored system, while taking into account existing knowledge. In that respect, we have developed a hierarchical spatiotemporal Bayesian model that can be used to optimize an existing monitoring network by retaining stations that provide the maximum amount of information, while identifying locations that would benefit from the addition of new stations. The model assumes the water quality parameters are adequately described by a joint matrix normal distribution. The adopted approach allows for a reduction in redundancies, while emphasizing information richness rather than data richness. The developed approach incorporates the concept of entropy to account for the associated uncertainties. Three different entropy-based criteria are adopted: total system entropy, chlorophyll-a standard violation entropy, and dissolved oxygen standard violation entropy. A multiple attribute decision making framework is adopted to integrate the competing design criteria and to generate a single optimal design. The approach is implemented on the water quality monitoring system of the Neuse River Estuary in North Carolina, USA. The model results indicate that the high priority monitoring areas identified by the total system entropy and the dissolved oxygen violation entropy criteria are largely coincident. The monitoring design based on the chlorophyll-a standard violation entropy proved to be less informative, given the low probabilities of violating the water quality standard in the estuary.
Fuzzy 2-partition entropy threshold selection based on Big Bang–Big Crunch Optimization algorithm
Directory of Open Access Journals (Sweden)
Baljit Singh Khehra
2015-03-01
Full Text Available The fuzzy 2-partition entropy approach has been widely used to select threshold value for image segmenting. This approach used two parameterized fuzzy membership functions to form a fuzzy 2-partition of the image. The optimal threshold is selected by searching an optimal combination of parameters of the membership functions such that the entropy of fuzzy 2-partition is maximized. In this paper, a new fuzzy 2-partition entropy thresholding approach based on the technology of the Big Bang–Big Crunch Optimization (BBBCO is proposed. The new proposed thresholding approach is called the BBBCO-based fuzzy 2-partition entropy thresholding algorithm. BBBCO is used to search an optimal combination of parameters of the membership functions for maximizing the entropy of fuzzy 2-partition. BBBCO is inspired by the theory of the evolution of the universe; namely the Big Bang and Big Crunch Theory. The proposed algorithm is tested on a number of standard test images. For comparison, three different algorithms included Genetic Algorithm (GA-based, Biogeography-based Optimization (BBO-based and recursive approaches are also implemented. From experimental results, it is observed that the performance of the proposed algorithm is more effective than GA-based, BBO-based and recursion-based approaches.
International Nuclear Information System (INIS)
Ye, Xuemin; Li, Chunxi
2013-01-01
As one of the most significant measures to improve energy utilization efficiency and save energy, cogeneration or combined heat and power (CHP) has been widely applied and promoted with positive motivations in many countries. A rational cost allocation model should indicate the performance of cogenerations and balance the benefits between electricity generation and heat production. Based on the second law of thermodynamics, the present paper proposes an entropy change method for cost allocation by choosing exhaust steam entropy as a datum point, and the new model works in conjunction with entropy change and irreversibility during energy conversion processes. The allocation ratios of heat cost with the present and existing methods are compared for different types of cogenerations. Results show that the allocation ratios with the entropy change method are more rational and the cost allocation model can make up some limitations involved in other approaches. The future energy policies and innovational directions for cogenerations and heat consumers should be developed. - Highlights: • A rational model of cogeneration cost allocation is established. • Entropy change method integrates the relation of entropy change and exergy losses. • The unity of measuring energy quality and quantity is materialized. • The benefits between electricity generation and heat production are balanced
Harmonic analysis of electric locomotive and traction power system based on wavelet singular entropy
Dun, Xiaohong
2018-05-01
With the rapid development of high-speed railway and heavy-haul transport, the locomotive and traction power system has become the main harmonic source of China's power grid. In response to this phenomenon, the system's power quality issues need timely monitoring, assessment and governance. Wavelet singular entropy is an organic combination of wavelet transform, singular value decomposition and information entropy theory, which combines the unique advantages of the three in signal processing: the time-frequency local characteristics of wavelet transform, singular value decomposition explores the basic modal characteristics of data, and information entropy quantifies the feature data. Based on the theory of singular value decomposition, the wavelet coefficient matrix after wavelet transform is decomposed into a series of singular values that can reflect the basic characteristics of the original coefficient matrix. Then the statistical properties of information entropy are used to analyze the uncertainty of the singular value set, so as to give a definite measurement of the complexity of the original signal. It can be said that wavelet entropy has a good application prospect in fault detection, classification and protection. The mat lab simulation shows that the use of wavelet singular entropy on the locomotive and traction power system harmonic analysis is effective.
ACCUMULATED DEFORMATION MODELING OF PERMANENT WAY BASED ON ENTROPY SYSTEM
Directory of Open Access Journals (Sweden)
D. M. Kurhan
2015-07-01
Full Text Available Purpose. The work provides a theoretical research about the possibility of using methods that determine the lifetime of a railway track not only in terms of total stresses, and accounting its structure and dynamic characteristics. The aim of these studies is creation the model of deformations accumulation for assessment of service life of a railway track taking into account these features. Methodology. To simulate a gradual change state during the operation (accumulation of deformations the railway track is presented as a system that consists of many particles of different materials collected in a coherent design. It is appropriate to speak not about the appearance of deformations of a certain size in a certain section of the track, and the probability of such event on the site. If to operate the probability of occurrence of deviations, comfortable state of the system is characterized by the number of breaks of the conditional internal connections. The same state of the system may correspond to different combinations of breaks. The more breaks, the more the number of options changes in the structure of the system appropriate to its current state. Such a process can be represented as a gradual transition from an ordered state to a chaotic one. To describe the characteristics of the system used the numerical value of the entropy. Findings. Its entropy is constantly increasing at system aging. The growth of entropy is expressed by changes in the internal energy of the system, which can be determined using mechanical work forces, which leads to deformation. This gives the opportunity to show quantitative indication of breaking the bonds in the system as a consequence of performing mechanical work. According to the results of theoretical research methods for estimation of the timing of life cycles of railway operation considering such factors as the structure of the flow of trains, construction of the permanent way, the movement of trains at high
A Possible Ethical Imperative Based on the Entropy Law
Directory of Open Access Journals (Sweden)
Mehrdad Massoudi
2016-11-01
Full Text Available Lindsay in an article titled, “Entropy consumption and values in physical science,” (Am. Sci. 1959, 47, 678–696 proposed a Thermodynamic Imperative similar to Kant’s Ethical Categorical Imperative. In this paper, after describing the concept of ethical imperative as elaborated by Kant, we provide a brief discussion of the role of science and its relationship to the classical thermodynamics and the physical implications of the first and the second laws of thermodynamics. We finally attempt to extend and supplement Lindsay’s Thermodynamic Imperative (TI, by another Imperative suggesting simplicity, conservation, and harmony.
Multiscale entropy based study of the pathological time series
International Nuclear Information System (INIS)
Wang Jun; Ma Qianli
2008-01-01
This paper studies the multiscale entropy (MSE) of electrocardiogram's ST segment and compares the MSE results of ST segment with that of electrocardiogram in the first time. Electrocardiogram complexity changing characteristics has important clinical significance for early diagnosis. Study shows that the average MSE values and the varying scope fluctuation could be more effective to reveal the heart health status. Particularly the multiscale values varying scope fluctuation is a more sensitive parameter for early heart disease detection and has a clinical diagnostic significance. (general)
International Nuclear Information System (INIS)
Giangaspero, Giorgio; Sciubba, Enrico
2013-01-01
This paper presents an application of the entropy generation minimization method to the pseudo-optimization of the configuration of the heat exchange surfaces in a Solar Rooftile. An initial “standard” commercial configuration is gradually improved by introducing design changes aimed at the reduction of the thermodynamic losses due to heat transfer and fluid friction. Different geometries (pins, fins and others) are analysed with a commercial CFD (Computational Fluid Dynamics) code that also computes the local entropy generation rate. The design improvement process is carried out on the basis of a careful analysis of the local entropy generation maps and the rationale behind each step of the process is discussed in this perspective. The results are compared with other entropy generation minimization techniques available in the recent technical literature. It is found that the geometry with pin-fins has the best performance among the tested ones, and that the optimal pin array shape parameters (pitch and span) can be determined by a critical analysis of the integrated and local entropy maps and of the temperature contours. - Highlights: ► An entropy generation minimization method is applied to a solar heat exchanger. ► The approach is heuristic and leads to a pseudo-optimization process with CFD as main tool. ► The process is based on the evaluation of the local entropy generation maps. ► The geometry with pin-fins in general outperforms all other configurations. ► The entropy maps and temperature contours can be used to determine the optimal pin array design parameters
Entropy-based automated classification of independent components separated from fMCG
International Nuclear Information System (INIS)
Comani, S; Srinivasan, V; Alleva, G; Romani, G L
2007-01-01
Fetal magnetocardiography (fMCG) is a noninvasive technique suitable for the prenatal diagnosis of the fetal heart function. Reliable fetal cardiac signals can be reconstructed from multi-channel fMCG recordings by means of independent component analysis (ICA). However, the identification of the separated components is usually accomplished by visual inspection. This paper discusses a novel automated system based on entropy estimators, namely approximate entropy (ApEn) and sample entropy (SampEn), for the classification of independent components (ICs). The system was validated on 40 fMCG datasets of normal fetuses with the gestational age ranging from 22 to 37 weeks. Both ApEn and SampEn were able to measure the stability and predictability of the physiological signals separated with ICA, and the entropy values of the three categories were significantly different at p <0.01. The system performances were compared with those of a method based on the analysis of the time and frequency content of the components. The outcomes of this study showed a superior performance of the entropy-based system, in particular for early gestation, with an overall ICs detection rate of 98.75% and 97.92% for ApEn and SampEn respectively, as against a value of 94.50% obtained with the time-frequency-based system. (note)
An entropy-based improved k-top scoring pairs (TSP) method for ...
African Journals Online (AJOL)
An entropy-based improved k-top scoring pairs (TSP) (Ik-TSP) method was presented in this study for the classification and prediction of human cancers based on gene-expression data. We compared Ik-TSP classifiers with 5 different machine learning methods and the k-TSP method based on 3 different feature selection ...
A Novel Entropy-Based Centrality Approach for Identifying Vital Nodes in Weighted Networks
Directory of Open Access Journals (Sweden)
Tong Qiao
2018-04-01
Full Text Available Measuring centrality has recently attracted increasing attention, with algorithms ranging from those that simply calculate the number of immediate neighbors and the shortest paths to those that are complicated iterative refinement processes and objective dynamical approaches. Indeed, vital nodes identification allows us to understand the roles that different nodes play in the structure of a network. However, quantifying centrality in complex networks with various topological structures is not an easy task. In this paper, we introduce a novel definition of entropy-based centrality, which can be applicable to weighted directed networks. By design, the total power of a node is divided into two parts, including its local power and its indirect power. The local power can be obtained by integrating the structural entropy, which reveals the communication activity and popularity of each node, and the interaction frequency entropy, which indicates its accessibility. In addition, the process of influence propagation can be captured by the two-hop subnetworks, resulting in the indirect power. In order to evaluate the performance of the entropy-based centrality, we use four weighted real-world networks with various instance sizes, degree distributions, and densities. Correspondingly, these networks are adolescent health, Bible, United States (US airports, and Hep-th, respectively. Extensive analytical results demonstrate that the entropy-based centrality outperforms degree centrality, betweenness centrality, closeness centrality, and the Eigenvector centrality.
Directory of Open Access Journals (Sweden)
Yingjun Zhang
2013-01-01
Full Text Available Multiattribute decision making (MADM is one of the central problems in artificial intelligence, specifically in management fields. In most cases, this problem arises from uncertainty both in the data derived from the decision maker and the actions performed in the environment. Fuzzy set and high-order fuzzy sets were proven to be effective approaches in solving decision-making problems with uncertainty. Therefore, in this paper, we investigate the MADM problem with completely unknown attribute weights in the framework of interval-valued intuitionistic fuzzy (IVIF set (IVIFS. We first propose a new definition of IVIF entropy and some calculation methods for IVIF entropy. Furthermore, we propose an entropy-based decision-making method to solve IVIF MADM problems with completely unknown attribute weights. Particular emphasis is put on assessing the attribute weights based on IVIF entropy. Instead of the traditional methods, which use divergence among attributes or the probabilistic discrimination of attributes to obtain attribute weights, we utilize the IVIF entropy to assess the attribute weights based on the credibility of the decision-making matrix for solving the problem. Finally, a supplier selection example is given to demonstrate the feasibility and validity of the proposed MADM method.
Fault Diagnosis Method Based on Information Entropy and Relative Principal Component Analysis
Directory of Open Access Journals (Sweden)
Xiaoming Xu
2017-01-01
Full Text Available In traditional principle component analysis (PCA, because of the neglect of the dimensions influence between different variables in the system, the selected principal components (PCs often fail to be representative. While the relative transformation PCA is able to solve the above problem, it is not easy to calculate the weight for each characteristic variable. In order to solve it, this paper proposes a kind of fault diagnosis method based on information entropy and Relative Principle Component Analysis. Firstly, the algorithm calculates the information entropy for each characteristic variable in the original dataset based on the information gain algorithm. Secondly, it standardizes every variable’s dimension in the dataset. And, then, according to the information entropy, it allocates the weight for each standardized characteristic variable. Finally, it utilizes the relative-principal-components model established for fault diagnosis. Furthermore, the simulation experiments based on Tennessee Eastman process and Wine datasets demonstrate the feasibility and effectiveness of the new method.
Value at risk estimation with entropy-based wavelet analysis in exchange markets
He, Kaijian; Wang, Lijun; Zou, Yingchao; Lai, Kin Keung
2014-08-01
In recent years, exchange markets are increasingly integrated together. Fluctuations and risks across different exchange markets exhibit co-moving and complex dynamics. In this paper we propose the entropy-based multivariate wavelet based approaches to analyze the multiscale characteristic in the multidimensional domain and improve further the Value at Risk estimation reliability. Wavelet analysis has been introduced to construct the entropy-based Multiscale Portfolio Value at Risk estimation algorithm to account for the multiscale dynamic correlation. The entropy measure has been proposed as the more effective measure with the error minimization principle to select the best basis when determining the wavelet families and the decomposition level to use. The empirical studies conducted in this paper have provided positive evidence as to the superior performance of the proposed approach, using the closely related Chinese Renminbi and European Euro exchange market.
Entropy based statistical inference for methane emissions released from wetland
Czech Academy of Sciences Publication Activity Database
Sabolová, R.; Sečkárová, Vladimíra; Dušek, Jiří; Stehlík, M.
2015-01-01
Roč. 141, č. 1 (2015), s. 125-133 ISSN 0169-7439 R&D Projects: GA ČR GA13-13502S; GA ČR(CZ) GAP504/11/1151; GA MŠk(CZ) ED1.1.00/02.0073 Grant - others:GA ČR(CZ) GA201/12/0083; GA UK(CZ) SVV 2014-260105 Institutional support: RVO:67985556 ; RVO:67179843 Keywords : chaos * entropy * Kullback-Leibler divergence * Pareto distribution * saddlepoint approaximation * wetland ecosystem Subject RIV: BB - Applied Statistics, Operational Research; EH - Ecology, Behaviour (UEK-B) Impact factor: 2.217, year: 2015 http://library.utia.cas.cz/separaty/2014/AS/seckarova-0438651.pdf
Minimum Entropy-Based Cascade Control for Governing Hydroelectric Turbines
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Mifeng Ren
2014-06-01
Full Text Available In this paper, an improved cascade control strategy is presented for hydroturbine speed governors. Different from traditional proportional-integral-derivative (PID control and model predictive control (MPC strategies, the performance index of the outer controller is constructed by integrating the entropy and mean value of the tracking error with the constraints on control energy. The inner controller is implemented by a proportional controller. Compared with the conventional PID-P and MPC-P cascade control methods, the proposed cascade control strategy can effectively decrease fluctuations of hydro-turbine speed under non-Gaussian disturbance conditions in practical hydropower plants. Simulation results show the advantages of the proposed cascade control method.
Branch length similarity entropy-based descriptors for shape representation
Kwon, Ohsung; Lee, Sang-Hee
2017-11-01
In previous studies, we showed that the branch length similarity (BLS) entropy profile could be successfully used for the shape recognition such as battle tanks, facial expressions, and butterflies. In the present study, we proposed new descriptors, roundness, symmetry, and surface roughness, for the recognition, which are more accurate and fast in the computation than the previous descriptors. The roundness represents how closely a shape resembles to a circle, the symmetry characterizes how much one shape is similar with another when the shape is moved in flip, and the surface roughness quantifies the degree of vertical deviations of a shape boundary. To evaluate the performance of the descriptors, we used the database of leaf images with 12 species. Each species consisted of 10 - 20 leaf images and the total number of images were 160. The evaluation showed that the new descriptors successfully discriminated the leaf species. We believe that the descriptors can be a useful tool in the field of pattern recognition.
A generalized complexity measure based on Rényi entropy
Sánchez-Moreno, Pablo; Angulo, Juan Carlos; Dehesa, Jesus S.
2014-08-01
The intrinsic statistical complexities of finite many-particle systems (i.e., those defined in terms of the single-particle density) quantify the degree of structure or patterns, far beyond the entropy measures. They are intuitively constructed to be minima at the opposite extremes of perfect order and maximal randomness. Starting from the pioneering LMC measure, which satisfies these requirements, some extensions of LMC-Rényi type have been published in the literature. The latter measures were shown to describe a variety of physical aspects of the internal disorder in atomic and molecular systems (e.g., quantum phase transitions, atomic shell filling) which are not grasped by their mother LMC quantity. However, they are not minimal for maximal randomness in general. In this communication, we propose a generalized LMC-Rényi complexity which overcomes this problem. Some applications which illustrate this fact are given.
International Nuclear Information System (INIS)
He, Z J; Zhang, X L; Chen, X F
2012-01-01
Aiming at reliability evaluation of condition identification of mechanical equipment, it is necessary to analyze condition monitoring information. A new method of reliability evaluation based on wavelet information entropy extracted from vibration signals of mechanical equipment is proposed. The method is quite different from traditional reliability evaluation models that are dependent on probability statistics analysis of large number sample data. The vibration signals of mechanical equipment were analyzed by means of second generation wavelet package (SGWP). We take relative energy in each frequency band of decomposed signal that equals a percentage of the whole signal energy as probability. Normalized information entropy (IE) is obtained based on the relative energy to describe uncertainty of a system instead of probability. The reliability degree is transformed by the normalized wavelet information entropy. A successful application has been achieved to evaluate the assembled quality reliability for a kind of dismountable disk-drum aero-engine. The reliability degree indicates the assembled quality satisfactorily.
Entropy Based Analysis of DNS Query Traffic in the Campus Network
Directory of Open Access Journals (Sweden)
Dennis Arturo Ludeña Romaña
2008-10-01
Full Text Available We carried out the entropy based study on the DNS query traffic from the campus network in a university through January 1st, 2006 to March 31st, 2007. The results are summarized, as follows: (1 The source IP addresses- and query keyword-based entropies change symmetrically in the DNS query traffic from the outside of the campus network when detecting the spam bot activity on the campus network. On the other hand (2, the source IP addresses- and query keywordbased entropies change similarly each other when detecting big DNS query traffic caused by prescanning or distributed denial of service (DDoS attack from the campus network. Therefore, we can detect the spam bot and/or DDoS attack bot by only watching DNS query access traffic.
Biological Aging and Life Span Based on Entropy Stress via Organ and Mitochondrial Metabolic Loading
Directory of Open Access Journals (Sweden)
Kalyan Annamalai
2017-10-01
Full Text Available The energy for sustaining life is released through the oxidation of glucose, fats, and proteins. A part of the energy released within each cell is stored as chemical energy of Adenosine Tri-Phosphate molecules, which is essential for performing life-sustaining functions, while the remainder is released as heat in order to maintain isothermal state of the body. Earlier literature introduced the availability concepts from thermodynamics, related the specific irreversibility and entropy generation rates to metabolic efficiency and energy release rate of organ k, computed whole body specific entropy generation rate of whole body at any given age as a sum of entropy generation within four vital organs Brain, Heart, Kidney, Liver (BHKL with 5th organ being the rest of organs (R5 and estimated the life span using an upper limit on lifetime entropy generated per unit mass of body, σM,life. The organ entropy stress expressed in terms of lifetime specific entropy generated per unit mass of body organs (kJ/(K kg of organ k was used to rank organs and heart ranked highest while liver ranked lowest. The present work includes the effects of (1 two additional organs: adipose tissue (AT and skeletal muscles (SM which are of importance to athletes; (2 proportions of nutrients oxidized which affects blood temperature and metabolic efficiencies; (3 conversion of the entropy stress from organ/cellular level to mitochondrial level; and (4 use these parameters as metabolism-based biomarkers for quantifying the biological aging process in reaching the limit of σM,life. Based on the 7-organ model and Elia constants for organ metabolic rates for a male of 84 kg steady mass and using basic and derived allometric constants of organs, the lifetime energy expenditure is estimated to be 2725 MJ/kg body mass while lifetime entropy generated is 6050 kJ/(K kg body mass with contributions of 190; 1835.0; 610; 290; 700; 1470 and 95 kJ/K contributed by AT-BHKL-SM-R7 to 1 kg body
Persistence-Based Branch Misprediction Bounds for WCET Analysis
DEFF Research Database (Denmark)
Puffitsch, Wolfgang
2015-01-01
Branch prediction is an important feature of pipelined processors to achieve high performance. However, it can lead to overly pessimistic worst-case execution time (WCET) bounds when being modeled too conservatively. This paper presents bounds on the number of branch mispredictions for local...... dynamic branch predictors. To handle interferences between branch instructions we use the notion of persistence, a concept that is also found in cache analyses. The bounds apply to branches in general, not only to branches that close a loop. Furthermore, the bounds can be easily integrated into integer...... linear programming formulations of the WCET problem. An evaluation on a number of benchmarks shows that with these bounds, dynamic branch prediction does not necessarily lead to higher WCET bounds than static prediction schemes....
Tuck, Adrian F
2017-09-07
There is no widely agreed definition of entropy, and consequently Gibbs energy, in open systems far from equilibrium. One recent approach has sought to formulate an entropy and Gibbs energy based on observed scale invariances in geophysical variables, particularly in atmospheric quantities, including the molecules constituting stratospheric chemistry. The Hamiltonian flux dynamics of energy in macroscopic open nonequilibrium systems maps to energy in equilibrium statistical thermodynamics, and corresponding equivalences of scale invariant variables with other relevant statistical mechanical variables such as entropy, Gibbs energy, and 1/(k Boltzmann T), are not just formally analogous but are also mappings. Three proof-of-concept representative examples from available adequate stratospheric chemistry observations-temperature, wind speed and ozone-are calculated, with the aim of applying these mappings and equivalences. Potential applications of the approach to scale invariant observations from the literature, involving scales from molecular through laboratory to astronomical, are considered. Theoretical support for the approach from the literature is discussed.
Risk Contagion in Chinese Banking Industry: A Transfer Entropy-Based Analysis
Directory of Open Access Journals (Sweden)
Jianping Li
2013-12-01
Full Text Available What is the impact of a bank failure on the whole banking industry? To resolve this issue, the paper develops a transfer entropy-based method to determine the interbank exposure matrix between banks. This method constructs the interbank market structure by calculating the transfer entropy matrix using bank stock price sequences. This paper also evaluates the stability of Chinese banking system by simulating the risk contagion process. This paper contributes to the literature on interbank contagion mainly in two ways: it establishes a convincing connection between interbank market and transfer entropy, and exploits the market information (stock price rather than presumptions to determine the interbank exposure matrix. Second, the empirical analysis provides an in depth understanding of the stability of the current Chinese banking system.
Histace, A; Meziou, B J; Matuszewski, Bogdan; Precioso, F; Murphy, M F; Carreiras, F
2013-01-01
We propose an unsupervised statistical region based active contour approach integrating an original fractional entropy measure for image segmentation with a particular application to single channel actin tagged fluorescence confocal microscopy image segmentation. Following description of statistical based active contour segmentation and the mathematical definition of the proposed fractional entropy descriptor, we demonstrate comparative segmentation results between the proposed approach and s...
Entropy based classifier for cross-domain opinion mining
Directory of Open Access Journals (Sweden)
Jyoti S. Deshmukh
2018-01-01
Full Text Available In recent years, the growth of social network has increased the interest of people in analyzing reviews and opinions for products before they buy them. Consequently, this has given rise to the domain adaptation as a prominent area of research in sentiment analysis. A classifier trained from one domain often gives poor results on data from another domain. Expression of sentiment is different in every domain. The labeling cost of each domain separately is very high as well as time consuming. Therefore, this study has proposed an approach that extracts and classifies opinion words from one domain called source domain and predicts opinion words of another domain called target domain using a semi-supervised approach, which combines modified maximum entropy and bipartite graph clustering. A comparison of opinion classification on reviews on four different product domains is presented. The results demonstrate that the proposed method performs relatively well in comparison to the other methods. Comparison of SentiWordNet of domain-specific and domain-independent words reveals that on an average 72.6% and 88.4% words, respectively, are correctly classified.
Activity-Based Approach for Teaching Aqueous Solubility, Energy, and Entropy
Eisen, Laura; Marano, Nadia; Glazier, Samantha
2014-01-01
We describe an activity-based approach for teaching aqueous solubility to introductory chemistry students that provides a more balanced presentation of the roles of energy and entropy in dissolution than is found in most general chemistry textbooks. In the first few activities, students observe that polar substances dissolve in water, whereas…
He, Jiayi; Shang, Pengjian; Xiong, Hui
2018-06-01
Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.
A Text Steganographic System Based on Word Length Entropy Rate
Directory of Open Access Journals (Sweden)
Francis Xavier Kofi Akotoye
2017-10-01
Full Text Available The widespread adoption of electronic distribution of material is accompanied by illicit copying and distribution. This is why individuals, businesses and governments have come to think of how to protect their work, prevent such illicit activities and trace the distribution of a document. It is in this context that a lot of attention is being focused on steganography. Implementing steganography in text document is not an easy undertaking considering the fact that text document has very few places in which to embed hidden data. Any minute change introduced to text objects can easily be noticed thus attracting attention from possible hackers. This study investigates the possibility of embedding data in text document by employing the entropy rate of the constituent characters of words not less than four characters long. The scheme was used to embed bits in text according to the alphabetic structure of the words, the respective characters were compared with their neighbouring characters and if the first character was alphabetically lower than the succeeding character according to their ASCII codes, a zero bit was embedded otherwise 1 was embedded after the characters had been transposed. Before embedding, the secret message was encrypted with a secret key to add a layer of security to the secret message to be embedded, and then a pseudorandom number was generated from the word counts of the text which was used to paint the starting point of the embedding process. The embedding capacity of the scheme was relatively high compared with the space encoding and semantic method.
Energy Technology Data Exchange (ETDEWEB)
Jiang, Qingchao; Yan, Xuefeng; Lv, Zhaomin; Guo, Meijin [East China University of Science and Technology, Shanghai (China)
2013-06-15
Considering that kernel entropy component analysis (KECA) is a promising new method of nonlinear data transformation and dimensionality reduction, a KECA based method is proposed for nonlinear chemical process monitoring. In this method, an angle-based statistic is designed because KECA reveals structure related to the Renyi entropy of input space data set, and the transformed data sets are produced with a distinct angle-based structure. Based on the angle difference between normal status and current sample data, the current status can be monitored effectively. And, the confidence limit of the angle-based statistics is determined by kernel density estimation based on sample data of the normal status. The effectiveness of the proposed method is demonstrated by case studies on both a numerical process and a simulated continuous stirred tank reactor (CSTR) process. The KECA based method can be an effective method for nonlinear chemical process monitoring.
International Nuclear Information System (INIS)
Jiang, Qingchao; Yan, Xuefeng; Lv, Zhaomin; Guo, Meijin
2013-01-01
Considering that kernel entropy component analysis (KECA) is a promising new method of nonlinear data transformation and dimensionality reduction, a KECA based method is proposed for nonlinear chemical process monitoring. In this method, an angle-based statistic is designed because KECA reveals structure related to the Renyi entropy of input space data set, and the transformed data sets are produced with a distinct angle-based structure. Based on the angle difference between normal status and current sample data, the current status can be monitored effectively. And, the confidence limit of the angle-based statistics is determined by kernel density estimation based on sample data of the normal status. The effectiveness of the proposed method is demonstrated by case studies on both a numerical process and a simulated continuous stirred tank reactor (CSTR) process. The KECA based method can be an effective method for nonlinear chemical process monitoring
On the Entropy Based Associative Memory Model with Higher-Order Correlations
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Masahiro Nakagawa
2010-01-01
Full Text Available In this paper, an entropy based associative memory model will be proposed and applied to memory retrievals with an orthogonal learning model so as to compare with the conventional model based on the quadratic Lyapunov functional to be minimized during the retrieval process. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may be reduced asymptotically to the above-mentioned conventional dynamics as a special case ignoring the higher-order correlations. According to the introduction of the entropy functional, one may involve higer-order correlation effects between neurons in a self-contained manner without any heuristic coupling coefficients as in the conventional manner. In fact we shall show such higher order coupling tensors are to be uniquely determined in the framework of the entropy based approach. From numerical results, it will be found that the presently proposed novel approach realizes much larger memory capacity than that of the quadratic Lyapunov functional approach, e.g., associatron.
A Real-Time Analysis Method for Pulse Rate Variability Based on Improved Basic Scale Entropy
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Yongxin Chou
2017-01-01
Full Text Available Base scale entropy analysis (BSEA is a nonlinear method to analyze heart rate variability (HRV signal. However, the time consumption of BSEA is too long, and it is unknown whether the BSEA is suitable for analyzing pulse rate variability (PRV signal. Therefore, we proposed a method named sliding window iterative base scale entropy analysis (SWIBSEA by combining BSEA and sliding window iterative theory. The blood pressure signals of healthy young and old subjects are chosen from the authoritative international database MIT/PhysioNet/Fantasia to generate PRV signals as the experimental data. Then, the BSEA and the SWIBSEA are used to analyze the experimental data; the results show that the SWIBSEA reduces the time consumption and the buffer cache space while it gets the same entropy as BSEA. Meanwhile, the changes of base scale entropy (BSE for healthy young and old subjects are the same as that of HRV signal. Therefore, the SWIBSEA can be used for deriving some information from long-term and short-term PRV signals in real time, which has the potential for dynamic PRV signal analysis in some portable and wearable medical devices.
Zhao, Hui; Qu, Weilu; Qiu, Weiting
2018-03-01
In order to evaluate sustainable development level of resource-based cities, an evaluation method with Shapely entropy and Choquet integral is proposed. First of all, a systematic index system is constructed, the importance of each attribute is calculated based on the maximum Shapely entropy principle, and then the Choquet integral is introduced to calculate the comprehensive evaluation value of each city from the bottom up, finally apply this method to 10 typical resource-based cities in China. The empirical results show that the evaluation method is scientific and reasonable, which provides theoretical support for the sustainable development path and reform direction of resource-based cities.
Fault Detection and Diagnosis for Gas Turbines Based on a Kernelized Information Entropy Model
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Weiying Wang
2014-01-01
Full Text Available Gas turbines are considered as one kind of the most important devices in power engineering and have been widely used in power generation, airplanes, and naval ships and also in oil drilling platforms. However, they are monitored without man on duty in the most cases. It is highly desirable to develop techniques and systems to remotely monitor their conditions and analyze their faults. In this work, we introduce a remote system for online condition monitoring and fault diagnosis of gas turbine on offshore oil well drilling platforms based on a kernelized information entropy model. Shannon information entropy is generalized for measuring the uniformity of exhaust temperatures, which reflect the overall states of the gas paths of gas turbine. In addition, we also extend the entropy to compute the information quantity of features in kernel spaces, which help to select the informative features for a certain recognition task. Finally, we introduce the information entropy based decision tree algorithm to extract rules from fault samples. The experiments on some real-world data show the effectiveness of the proposed algorithms.
Fault detection and diagnosis for gas turbines based on a kernelized information entropy model.
Wang, Weiying; Xu, Zhiqiang; Tang, Rui; Li, Shuying; Wu, Wei
2014-01-01
Gas turbines are considered as one kind of the most important devices in power engineering and have been widely used in power generation, airplanes, and naval ships and also in oil drilling platforms. However, they are monitored without man on duty in the most cases. It is highly desirable to develop techniques and systems to remotely monitor their conditions and analyze their faults. In this work, we introduce a remote system for online condition monitoring and fault diagnosis of gas turbine on offshore oil well drilling platforms based on a kernelized information entropy model. Shannon information entropy is generalized for measuring the uniformity of exhaust temperatures, which reflect the overall states of the gas paths of gas turbine. In addition, we also extend the entropy to compute the information quantity of features in kernel spaces, which help to select the informative features for a certain recognition task. Finally, we introduce the information entropy based decision tree algorithm to extract rules from fault samples. The experiments on some real-world data show the effectiveness of the proposed algorithms.
Entropy of the Mixture of Sources and Entropy Dimension
Smieja, Marek; Tabor, Jacek
2011-01-01
We investigate the problem of the entropy of the mixture of sources. There is given an estimation of the entropy and entropy dimension of convex combination of measures. The proof is based on our alternative definition of the entropy based on measures instead of partitions.
COLLAGE-BASED INVERSE PROBLEMS FOR IFSM WITH ENTROPY MAXIMIZATION AND SPARSITY CONSTRAINTS
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Herb Kunze
2013-11-01
Full Text Available We consider the inverse problem associated with IFSM: Given a target function f, find an IFSM, such that its invariant fixed point f is sufficiently close to f in the Lp distance. In this paper, we extend the collage-based method developed by Forte and Vrscay (1995 along two different directions. We first search for a set of mappings that not only minimizes the collage error but also maximizes the entropy of the dynamical system. We then include an extra term in the minimization process which takes into account the sparsity of the set of mappings. In this new formulation, the minimization of collage error is treated as multi-criteria problem: we consider three different and conflicting criteria i.e., collage error, entropy and sparsity. To solve this multi-criteria program we proceed by scalarization and we reduce the model to a single-criterion program by combining all objective functions with different trade-off weights. The results of some numerical computations are presented. Numerical studies indicate that a maximum entropy principle exists for this approximation problem, i.e., that the suboptimal solutions produced by collage coding can be improved at least slightly by adding a maximum entropy criterion.
Energy Technology Data Exchange (ETDEWEB)
Zunino, Luciano, E-mail: lucianoz@ciop.unlp.edu.ar [Centro de Investigaciones Ópticas (CONICET La Plata – CIC), C.C. 3, 1897 Gonnet (Argentina); Departamento de Ciencias Básicas, Facultad de Ingeniería, Universidad Nacional de La Plata (UNLP), 1900 La Plata (Argentina); Olivares, Felipe, E-mail: olivaresfe@gmail.com [Instituto de Física, Pontificia Universidad Católica de Valparaíso (PUCV), 23-40025 Valparaíso (Chile); Scholkmann, Felix, E-mail: Felix.Scholkmann@gmail.com [Research Office for Complex Physical and Biological Systems (ROCoS), Mutschellenstr. 179, 8038 Zurich (Switzerland); Biomedical Optics Research Laboratory, Department of Neonatology, University Hospital Zurich, University of Zurich, 8091 Zurich (Switzerland); Rosso, Osvaldo A., E-mail: oarosso@gmail.com [Instituto de Física, Universidade Federal de Alagoas (UFAL), BR 104 Norte km 97, 57072-970, Maceió, Alagoas (Brazil); Instituto Tecnológico de Buenos Aires (ITBA) and CONICET, C1106ACD, Av. Eduardo Madero 399, Ciudad Autónoma de Buenos Aires (Argentina); Complex Systems Group, Facultad de Ingeniería y Ciencias Aplicadas, Universidad de los Andes, Av. Mons. Álvaro del Portillo 12.455, Las Condes, Santiago (Chile)
2017-06-15
A symbolic encoding scheme, based on the ordinal relation between the amplitude of neighboring values of a given data sequence, should be implemented before estimating the permutation entropy. Consequently, equalities in the analyzed signal, i.e. repeated equal values, deserve special attention and treatment. In this work, we carefully study the effect that the presence of equalities has on permutation entropy estimated values when these ties are symbolized, as it is commonly done, according to their order of appearance. On the one hand, the analysis of computer-generated time series is initially developed to understand the incidence of repeated values on permutation entropy estimations in controlled scenarios. The presence of temporal correlations is erroneously concluded when true pseudorandom time series with low amplitude resolutions are considered. On the other hand, the analysis of real-world data is included to illustrate how the presence of a significant number of equal values can give rise to false conclusions regarding the underlying temporal structures in practical contexts. - Highlights: • Impact of repeated values in a signal when estimating permutation entropy is studied. • Numerical and experimental tests are included for characterizing this limitation. • Non-negligible temporal correlations can be spuriously concluded by repeated values. • Data digitized with low amplitude resolutions could be especially affected. • Analysis with shuffled realizations can help to overcome this limitation.
Multiscale multifractal multiproperty analysis of financial time series based on Rényi entropy
Yujun, Yang; Jianping, Li; Yimei, Yang
This paper introduces a multiscale multifractal multiproperty analysis based on Rényi entropy (3MPAR) method to analyze short-range and long-range characteristics of financial time series, and then applies this method to the five time series of five properties in four stock indices. Combining the two analysis techniques of Rényi entropy and multifractal detrended fluctuation analysis (MFDFA), the 3MPAR method focuses on the curves of Rényi entropy and generalized Hurst exponent of five properties of four stock time series, which allows us to study more universal and subtle fluctuation characteristics of financial time series. By analyzing the curves of the Rényi entropy and the profiles of the logarithm distribution of MFDFA of five properties of four stock indices, the 3MPAR method shows some fluctuation characteristics of the financial time series and the stock markets. Then, it also shows a richer information of the financial time series by comparing the profile of five properties of four stock indices. In this paper, we not only focus on the multifractality of time series but also the fluctuation characteristics of the financial time series and subtle differences in the time series of different properties. We find that financial time series is far more complex than reported in some research works using one property of time series.
Entropy-based derivation of generalized distributions for hydrometeorological frequency analysis
Chen, Lu; Singh, Vijay P.
2018-02-01
Frequency analysis of hydrometeorological and hydrological extremes is needed for the design of hydraulic and civil infrastructure facilities as well as water resources management. A multitude of distributions have been employed for frequency analysis of these extremes. However, no single distribution has been accepted as a global standard. Employing the entropy theory, this study derived five generalized distributions for frequency analysis that used different kinds of information encoded as constraints. These distributions were the generalized gamma (GG), the generalized beta distribution of the second kind (GB2), and the Halphen type A distribution (Hal-A), Halphen type B distribution (Hal-B) and Halphen type inverse B distribution (Hal-IB), among which the GG and GB2 distribution were previously derived by Papalexiou and Koutsoyiannis (2012) and the Halphen family was first derived using entropy theory in this paper. The entropy theory allowed to estimate parameters of the distributions in terms of the constraints used for their derivation. The distributions were tested using extreme daily and hourly rainfall data. Results show that the root mean square error (RMSE) values were very small, which indicated that the five generalized distributions fitted the extreme rainfall data well. Among them, according to the Akaike information criterion (AIC) values, generally the GB2 and Halphen family gave a better fit. Therefore, those general distributions are one of the best choices for frequency analysis. The entropy-based derivation led to a new way for frequency analysis of hydrometeorological extremes.
Application of SNODAS and hydrologic models to enhance entropy-based snow monitoring network design
Keum, Jongho; Coulibaly, Paulin; Razavi, Tara; Tapsoba, Dominique; Gobena, Adam; Weber, Frank; Pietroniro, Alain
2018-06-01
Snow has a unique characteristic in the water cycle, that is, snow falls during the entire winter season, but the discharge from snowmelt is typically delayed until the melting period and occurs in a relatively short period. Therefore, reliable observations from an optimal snow monitoring network are necessary for an efficient management of snowmelt water for flood prevention and hydropower generation. The Dual Entropy and Multiobjective Optimization is applied to design snow monitoring networks in La Grande River Basin in Québec and Columbia River Basin in British Columbia. While the networks are optimized to have the maximum amount of information with minimum redundancy based on entropy concepts, this study extends the traditional entropy applications to the hydrometric network design by introducing several improvements. First, several data quantization cases and their effects on the snow network design problems were explored. Second, the applicability the Snow Data Assimilation System (SNODAS) products as synthetic datasets of potential stations was demonstrated in the design of the snow monitoring network of the Columbia River Basin. Third, beyond finding the Pareto-optimal networks from the entropy with multi-objective optimization, the networks obtained for La Grande River Basin were further evaluated by applying three hydrologic models. The calibrated hydrologic models simulated discharges using the updated snow water equivalent data from the Pareto-optimal networks. Then, the model performances for high flows were compared to determine the best optimal network for enhanced spring runoff forecasting.
Cooperative Localization for Multi-AUVs Based on GM-PHD Filters and Information Entropy Theory
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Lichuan Zhang
2017-10-01
Full Text Available Cooperative localization (CL is considered a promising method for underwater localization with respect to multiple autonomous underwater vehicles (multi-AUVs. In this paper, we proposed a CL algorithm based on information entropy theory and the probability hypothesis density (PHD filter, aiming to enhance the global localization accuracy of the follower. In the proposed framework, the follower carries lower cost navigation systems, whereas the leaders carry better ones. Meanwhile, the leaders acquire the followers’ observations, including both measurements and clutter. Then, the PHD filters are utilized on the leaders and the results are communicated to the followers. The followers then perform weighted summation based on all received messages and obtain a final positioning result. Based on the information entropy theory and the PHD filter, the follower is able to acquire a precise knowledge of its position.
Crane Safety Assessment Method Based on Entropy and Cumulative Prospect Theory
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Aihua Li
2017-01-01
Full Text Available 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.
Tang, Jian; Jiang, Xiaoliang
2017-01-01
Image segmentation has always been a considerable challenge in image analysis and understanding due to the intensity inhomogeneity, which is also commonly known as bias field. In this paper, we present a novel region-based approach based on local entropy for segmenting images and estimating the bias field simultaneously. Firstly, a local Gaussian distribution fitting (LGDF) energy function is defined as a weighted energy integral, where the weight is local entropy derived from a grey level distribution of local image. The means of this objective function have a multiplicative factor that estimates the bias field in the transformed domain. Then, the bias field prior is fully used. Therefore, our model can estimate the bias field more accurately. Finally, minimization of this energy function with a level set regularization term, image segmentation, and bias field estimation can be achieved. Experiments on images of various modalities demonstrated the superior performance of the proposed method when compared with other state-of-the-art approaches.
Non-Gaussian Systems Control Performance Assessment Based on Rational Entropy
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Jinglin Zhou
2018-05-01
Full Text Available Control loop Performance Assessment (CPA plays an important role in system operations. Stochastic statistical CPA index, such as a minimum variance controller (MVC-based CPA index, is one of the most widely used CPA indices. In this paper, a new minimum entropy controller (MEC-based CPA method of linear non-Gaussian systems is proposed. In this method, probability density function (PDF and rational entropy (RE are respectively used to describe the characteristics and the uncertainty of random variables. To better estimate the performance benchmark, an improved EDA algorithm, which is used to estimate the system parameters and noise PDF, is given. The effectiveness of the proposed method is illustrated through case studies on an ARMAX system.
A Novel MADM Approach Based on Fuzzy Cross Entropy with Interval-Valued Intuitionistic Fuzzy Sets
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Xin Tong
2015-01-01
Full Text Available The paper presents a novel multiple attribute decision-making (MADM approach for the problem with completely unknown attribute weights in the framework of interval-valued intuitionistic fuzzy sets (IVIFS. First, the fuzzy cross entropy and discrimination degree of IVIFS are defied. Subsequently, based on the discrimination degree of IVIFS, a nonlinear programming model to minimize the total deviation of discrimination degrees between alternatives and the positive ideal solution PIS as well as the negative ideal solution (NIS is constructed to obtain the attribute weights and, then, the weighted discrimination degree. Finally, all the alternatives are ranked according to the relative closeness coefficients using the extended TOPSIS method, and the most desirable alternative is chosen. The proposed approach extends the research method of MADM based on the IVIF cross entropy. Finally, we illustrate the feasibility and validity of the proposed method by two examples.
Special Issue on Entropy-Based Applied Cryptography and Enhanced Security for Ubiquitous Computing
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James (Jong Hyuk Park
2016-09-01
Full Text Available Entropy is a basic and important concept in information theory. It is also often used as a measure of the unpredictability of a cryptographic key in cryptography research areas. Ubiquitous computing (Ubi-comp has emerged rapidly as an exciting new paradigm. In this special issue, we mainly selected and discussed papers related with ore theories based on the graph theory to solve computational problems on cryptography and security, practical technologies; applications and services for Ubi-comp including secure encryption techniques, identity and authentication; credential cloning attacks and countermeasures; switching generator with resistance against the algebraic and side channel attacks; entropy-based network anomaly detection; applied cryptography using chaos function, information hiding and watermark, secret sharing, message authentication, detection and modeling of cyber attacks with Petri Nets, and quantum flows for secret key distribution, etc.
Relative entropy of steering: on its definition and properties
International Nuclear Information System (INIS)
Kaur, Eneet; Wilde, Mark M
2017-01-01
In Gallego and Aolita (2015 Phys. Rev . X 5 041008), the authors proposed a definition for the relative entropy of steering and showed that the resulting quantity is a convex steering monotone. Here we advocate for a different definition for relative entropy of steering, based on well grounded concerns coming from quantum Shannon theory. We prove that this modified relative entropy of steering is a convex steering monotone. Furthermore, we establish that it is uniformly continuous and faithful, in both cases giving quantitative bounds that should be useful in applications. We also consider a restricted relative entropy of steering which is relevant for the case in which the free operations in the resource theory of steering have a more restricted form (the restricted operations could be more relevant in practical scenarios). The restricted relative entropy of steering is convex, monotone with respect to these restricted operations, uniformly continuous, and faithful. (paper)
Bounding quantum gate error rate based on reported average fidelity
International Nuclear Information System (INIS)
Sanders, Yuval R; Wallman, Joel J; Sanders, Barry C
2016-01-01
Remarkable experimental advances in quantum computing are exemplified by recent announcements of impressive average gate fidelities exceeding 99.9% for single-qubit gates and 99% for two-qubit gates. Although these high numbers engender optimism that fault-tolerant quantum computing is within reach, the connection of average gate fidelity with fault-tolerance requirements is not direct. Here we use reported average gate fidelity to determine an upper bound on the quantum-gate error rate, which is the appropriate metric for assessing progress towards fault-tolerant quantum computation, and we demonstrate that this bound is asymptotically tight for general noise. Although this bound is unlikely to be saturated by experimental noise, we demonstrate using explicit examples that the bound indicates a realistic deviation between the true error rate and the reported average fidelity. We introduce the Pauli distance as a measure of this deviation, and we show that knowledge of the Pauli distance enables tighter estimates of the error rate of quantum gates. (fast track communication)
DEFF Research Database (Denmark)
Yuri, Shtarkov; Justesen, Jørn
1997-01-01
The concept of entropy for an image on a discrete two dimensional grid is introduced. This concept is used as an information theoretic bound on the coding rate for the image. It is proved that this quantity exists as a limit for arbitrary sets satisfying certain conditions.......The concept of entropy for an image on a discrete two dimensional grid is introduced. This concept is used as an information theoretic bound on the coding rate for the image. It is proved that this quantity exists as a limit for arbitrary sets satisfying certain conditions....
A Note on the W-S Lower Bound of the MEE Estimation
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Badong Chen
2014-02-01
Full Text Available The minimum error entropy (MEE estimation is concerned with the estimation of a certain random variable (unknown variable based on another random variable (observation, so that the entropy of the estimation error is minimized. This estimation method may outperform the well-known minimum mean square error (MMSE estimation especially for non-Gaussian situations. There is an important performance bound on the MEE estimation, namely the W-S lower bound, which is computed as the conditional entropy of the unknown variable given observation. Though it has been known in the literature for a considerable time, up to now there is little study on this performance bound. In this paper, we reexamine the W-S lower bound. Some basic properties of the W-S lower bound are presented, and the characterization of Gaussian distribution using the W-S lower bound is investigated.
Energy Technology Data Exchange (ETDEWEB)
Bao, Ning [Institute for Quantum Information and Matter, California Institute of Technology,Pasadena, CA 91125 (United States); Walter Burke Institute for Theoretical Physics, California Institute of Technology,452-48, Pasadena, CA 91125 (United States); Nezami, Sepehr [Stanford Institute for Theoretical Physics, Stanford University,Stanford, CA 94305 (United States); Ooguri, Hirosi [Walter Burke Institute for Theoretical Physics, California Institute of Technology,452-48, Pasadena, CA 91125 (United States); Kavli Institute for the Physics and Mathematics of the Universe, University of Tokyo,Kashiwa 277-8583 (Japan); Stoica, Bogdan [Walter Burke Institute for Theoretical Physics, California Institute of Technology,452-48, Pasadena, CA 91125 (United States); Sully, James [Theory Group, SLAC National Accelerator Laboratory, Stanford University,Menlo Park, CA 94025 (United States); Walter, Michael [Stanford Institute for Theoretical Physics, Stanford University,Stanford, CA 94305 (United States)
2015-09-21
We initiate a systematic enumeration and classification of entropy inequalities satisfied by the Ryu-Takayanagi formula for conformal field theory states with smooth holographic dual geometries. For 2, 3, and 4 regions, we prove that the strong subadditivity and the monogamy of mutual information give the complete set of inequalities. This is in contrast to the situation for generic quantum systems, where a complete set of entropy inequalities is not known for 4 or more regions. We also find an infinite new family of inequalities applicable to 5 or more regions. The set of all holographic entropy inequalities bounds the phase space of Ryu-Takayanagi entropies, defining the holographic entropy cone. We characterize this entropy cone by reducing geometries to minimal graph models that encode the possible cutting and gluing relations of minimal surfaces. We find that, for a fixed number of regions, there are only finitely many independent entropy inequalities. To establish new holographic entropy inequalities, we introduce a combinatorial proof technique that may also be of independent interest in Riemannian geometry and graph theory.
International Nuclear Information System (INIS)
Bao, Ning; Nezami, Sepehr; Ooguri, Hirosi; Stoica, Bogdan; Sully, James; Walter, Michael
2015-01-01
We initiate a systematic enumeration and classification of entropy inequalities satisfied by the Ryu-Takayanagi formula for conformal field theory states with smooth holographic dual geometries. For 2, 3, and 4 regions, we prove that the strong subadditivity and the monogamy of mutual information give the complete set of inequalities. This is in contrast to the situation for generic quantum systems, where a complete set of entropy inequalities is not known for 4 or more regions. We also find an infinite new family of inequalities applicable to 5 or more regions. The set of all holographic entropy inequalities bounds the phase space of Ryu-Takayanagi entropies, defining the holographic entropy cone. We characterize this entropy cone by reducing geometries to minimal graph models that encode the possible cutting and gluing relations of minimal surfaces. We find that, for a fixed number of regions, there are only finitely many independent entropy inequalities. To establish new holographic entropy inequalities, we introduce a combinatorial proof technique that may also be of independent interest in Riemannian geometry and graph theory.
BRISENT: An Entropy-Based Model for Bridge-Pier Scour Estimation under Complex Hydraulic Scenarios
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Alonso Pizarro
2017-11-01
Full Text Available The goal of this paper is to introduce the first clear-water scour model based on both the informational entropy concept and the principle of maximum entropy, showing that a variational approach is ideal for describing erosional processes under complex situations. The proposed bridge–pier scour entropic (BRISENT model is capable of reproducing the main dynamics of scour depth evolution under steady hydraulic conditions, step-wise hydrographs, and flood waves. For the calibration process, 266 clear-water scour experiments from 20 precedent studies were considered, where the dimensionless parameters varied widely. Simple formulations are proposed to estimate BRISENT’s fitting coefficients, in which the ratio between pier-diameter and sediment-size was the most critical physical characteristic controlling scour model parametrization. A validation process considering highly unsteady and multi-peaked hydrographs was carried out, showing that the proposed BRISENT model reproduces scour evolution with high accuracy.
The prediction of engineering cost for green buildings based on information entropy
Liang, Guoqiang; Huang, Jinglian
2018-03-01
Green building is the developing trend in the world building industry. Additionally, construction costs are an essential consideration in building constructions. Therefore, it is necessary to investigate the problems of cost prediction in green building. On the basis of analyzing the cost of green building, this paper proposes the forecasting method of actual cost in green building based on information entropy and provides the forecasting working procedure. Using the probability density obtained from statistical data, such as labor costs, material costs, machinery costs, administration costs, profits, risk costs a unit project quotation and etc., situations can be predicted which lead to cost variations between budgeted cost and actual cost in constructions, through estimating the information entropy of budgeted cost and actual cost. The research results of this article have a practical significance in cost control of green building. Additionally, the method proposed in this article can be generalized and applied to a variety of other aspects in building management.
Rolling Bearing Fault Diagnosis Based on ELCD Permutation Entropy and RVM
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Jiang Xingmeng
2016-01-01
Full Text Available Aiming at the nonstationary characteristic of a gear fault vibration signal, a recognition method based on permutation entropy of ensemble local characteristic-scale decomposition (ELCD and relevance vector machine (RVM is proposed. First, the vibration signal was decomposed by ELCD; then a series of intrinsic scale components (ISCs were obtained. Second, according to the kurtosis of ISCs, principal ISCs were selected and then the permutation entropy of principal ISCs was calculated and they were combined into a feature vector. Finally, the feature vectors were input in RVM classifier to train and test and identify the type of rolling bearing faults. Experimental results show that this method can effectively diagnose four kinds of working condition, and the effect is better than local characteristic-scale decomposition (LCD method.
Evaluation of Intensive Construction Land Use in the Emerging City Based on PSR-Entropy model
Jia, Yuanyuan; Lei, Guangyu
2018-01-01
A comprehensive understanding of emerging city land utilization and the evaluation of intensive land use in the Emerging City will provide the comprehensive and reliable technical basis for the planning and management. It is an important node. According to the Han cheng from 2008 to 2016 years of land use, based on PSR-Entropy model of land use evaluation system, using entropy method to determine the index weight, the introduction of comprehensive index method to evaluate the degree of land use. The results show that the intensive land use comprehensive evaluation index of Han cheng increased from 2008 to 2015, but the land intensive use can not achieve the standards. The potential of further enhancing space is relatively large.
An Entropy-Based Adaptive Hybrid Particle Swarm Optimization for Disassembly Line Balancing Problems
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Shanli Xiao
2017-11-01
Full Text Available In order to improve the product disassembly efficiency, the disassembly line balancing problem (DLBP is transformed into a problem of searching for the optimum path in the directed and weighted graph by constructing the disassembly hierarchy information graph (DHIG. Then, combining the characteristic of the disassembly sequence, an entropy-based adaptive hybrid particle swarm optimization algorithm (AHPSO is presented. In this algorithm, entropy is introduced to measure the changing tendency of population diversity, and the dimension learning, crossover and mutation operator are used to increase the probability of producing feasible disassembly solutions (FDS. Performance of the proposed methodology is tested on the primary problem instances available in the literature, and the results are compared with other evolutionary algorithms. The results show that the proposed algorithm is efficient to solve the complex DLBP.
Wan, Minjie; Gu, Guohua; Qian, Weixian; Ren, Kan; Chen, Qian; Maldague, Xavier
2018-06-01
Infrared image enhancement plays a significant role in intelligent urban surveillance systems for smart city applications. Unlike existing methods only exaggerating the global contrast, we propose a particle swam optimization-based local entropy weighted histogram equalization which involves the enhancement of both local details and fore-and background contrast. First of all, a novel local entropy weighted histogram depicting the distribution of detail information is calculated based on a modified hyperbolic tangent function. Then, the histogram is divided into two parts via a threshold maximizing the inter-class variance in order to improve the contrasts of foreground and background, respectively. To avoid over-enhancement and noise amplification, double plateau thresholds of the presented histogram are formulated by means of particle swarm optimization algorithm. Lastly, each sub-image is equalized independently according to the constrained sub-local entropy weighted histogram. Comparative experiments implemented on real infrared images prove that our algorithm outperforms other state-of-the-art methods in terms of both visual and quantized evaluations.
Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS
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Moshen Kuai
2018-03-01
Full Text Available For planetary gear has the characteristics of small volume, light weight and large transmission ratio, it is widely used in high speed and high power mechanical system. Poor working conditions result in frequent failures of planetary gear. A method is proposed for diagnosing faults in planetary gear based on permutation entropy of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN Adaptive Neuro-fuzzy Inference System (ANFIS in this paper. The original signal is decomposed into 6 intrinsic mode functions (IMF and residual components by CEEMDAN. Since the IMF contains the main characteristic information of planetary gear faults, time complexity of IMFs are reflected by permutation entropies to quantify the fault features. The permutation entropies of each IMF component are defined as the input of ANFIS, and its parameters and membership functions are adaptively adjusted according to training samples. Finally, the fuzzy inference rules are determined, and the optimal ANFIS is obtained. The overall recognition rate of the test sample used for ANFIS is 90%, and the recognition rate of gear with one missing tooth is relatively high. The recognition rates of different fault gears based on the method can also achieve better results. Therefore, the proposed method can be applied to planetary gear fault diagnosis effectively.
Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS.
Kuai, Moshen; Cheng, Gang; Pang, Yusong; Li, Yong
2018-03-05
For planetary gear has the characteristics of small volume, light weight and large transmission ratio, it is widely used in high speed and high power mechanical system. Poor working conditions result in frequent failures of planetary gear. A method is proposed for diagnosing faults in planetary gear based on permutation entropy of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) Adaptive Neuro-fuzzy Inference System (ANFIS) in this paper. The original signal is decomposed into 6 intrinsic mode functions (IMF) and residual components by CEEMDAN. Since the IMF contains the main characteristic information of planetary gear faults, time complexity of IMFs are reflected by permutation entropies to quantify the fault features. The permutation entropies of each IMF component are defined as the input of ANFIS, and its parameters and membership functions are adaptively adjusted according to training samples. Finally, the fuzzy inference rules are determined, and the optimal ANFIS is obtained. The overall recognition rate of the test sample used for ANFIS is 90%, and the recognition rate of gear with one missing tooth is relatively high. The recognition rates of different fault gears based on the method can also achieve better results. Therefore, the proposed method can be applied to planetary gear fault diagnosis effectively.
Directory of Open Access Journals (Sweden)
Hujun He
2017-01-01
Full Text Available The prediction and risk classification of collapse is an important issue in the process of highway construction in mountainous regions. Based on the principles of information entropy and Mahalanobis distance discriminant analysis, we have produced a collapse hazard prediction model. We used the entropy measure method to reduce the influence indexes of the collapse activity and extracted the nine main indexes affecting collapse activity as the discriminant factors of the distance discriminant analysis model (i.e., slope shape, aspect, gradient, and height, along with exposure of the structural face, stratum lithology, relationship between weakness face and free face, vegetation cover rate, and degree of rock weathering. We employ postearthquake collapse data in relation to construction of the Yingxiu-Wolong highway, Hanchuan County, China, as training samples for analysis. The results were analyzed using the back substitution estimation method, showing high accuracy and no errors, and were the same as the prediction result of uncertainty measure. Results show that the classification model based on information entropy and distance discriminant analysis achieves the purpose of index optimization and has excellent performance, high prediction accuracy, and a zero false-positive rate. The model can be used as a tool for future evaluation of collapse risk.
Topology optimization of bounded acoustic problems using the hybrid finite element-wave based method
DEFF Research Database (Denmark)
Goo, Seongyeol; Wang, Semyung; Kook, Junghwan
2017-01-01
This paper presents an alternative topology optimization method for bounded acoustic problems that uses the hybrid finite element-wave based method (FE-WBM). The conventional method for the topology optimization of bounded acoustic problems is based on the finite element method (FEM), which...
High Entropy Random Selection Protocols
H. Buhrman (Harry); M. Christandl (Matthias); M. Koucky (Michal); Z. Lotker (Zvi); B. Patt-Shamir; M. Charikar; K. Jansen; O. Reingold; J. Rolim
2007-01-01
textabstractIn this paper, we construct protocols for two parties that do not trust each other, to generate random variables with high Shannon entropy. We improve known bounds for the trade off between the number of rounds, length of communication and the entropy of the outcome.
Efficient algorithms and implementations of entropy-based moment closures for rarefied gases
Energy Technology Data Exchange (ETDEWEB)
Schaerer, Roman Pascal, E-mail: schaerer@mathcces.rwth-aachen.de; Bansal, Pratyuksh; Torrilhon, Manuel
2017-07-01
We present efficient algorithms and implementations of the 35-moment system equipped with the maximum-entropy closure in the context of rarefied gases. While closures based on the principle of entropy maximization have been shown to yield very promising results for moderately rarefied gas flows, the computational cost of these closures is in general much higher than for closure theories with explicit closed-form expressions of the closing fluxes, such as Grad's classical closure. Following a similar approach as Garrett et al. (2015) , we investigate efficient implementations of the computationally expensive numerical quadrature method used for the moment evaluations of the maximum-entropy distribution by exploiting its inherent fine-grained parallelism with the parallelism offered by multi-core processors and graphics cards. We show that using a single graphics card as an accelerator allows speed-ups of two orders of magnitude when compared to a serial CPU implementation. To accelerate the time-to-solution for steady-state problems, we propose a new semi-implicit time discretization scheme. The resulting nonlinear system of equations is solved with a Newton type method in the Lagrange multipliers of the dual optimization problem in order to reduce the computational cost. Additionally, fully explicit time-stepping schemes of first and second order accuracy are presented. We investigate the accuracy and efficiency of the numerical schemes for several numerical test cases, including a steady-state shock-structure problem.
Efficient algorithms and implementations of entropy-based moment closures for rarefied gases
International Nuclear Information System (INIS)
Schaerer, Roman Pascal; Bansal, Pratyuksh; Torrilhon, Manuel
2017-01-01
We present efficient algorithms and implementations of the 35-moment system equipped with the maximum-entropy closure in the context of rarefied gases. While closures based on the principle of entropy maximization have been shown to yield very promising results for moderately rarefied gas flows, the computational cost of these closures is in general much higher than for closure theories with explicit closed-form expressions of the closing fluxes, such as Grad's classical closure. Following a similar approach as Garrett et al. (2015) , we investigate efficient implementations of the computationally expensive numerical quadrature method used for the moment evaluations of the maximum-entropy distribution by exploiting its inherent fine-grained parallelism with the parallelism offered by multi-core processors and graphics cards. We show that using a single graphics card as an accelerator allows speed-ups of two orders of magnitude when compared to a serial CPU implementation. To accelerate the time-to-solution for steady-state problems, we propose a new semi-implicit time discretization scheme. The resulting nonlinear system of equations is solved with a Newton type method in the Lagrange multipliers of the dual optimization problem in order to reduce the computational cost. Additionally, fully explicit time-stepping schemes of first and second order accuracy are presented. We investigate the accuracy and efficiency of the numerical schemes for several numerical test cases, including a steady-state shock-structure problem.
Efficient algorithms and implementations of entropy-based moment closures for rarefied gases
Schaerer, Roman Pascal; Bansal, Pratyuksh; Torrilhon, Manuel
2017-07-01
We present efficient algorithms and implementations of the 35-moment system equipped with the maximum-entropy closure in the context of rarefied gases. While closures based on the principle of entropy maximization have been shown to yield very promising results for moderately rarefied gas flows, the computational cost of these closures is in general much higher than for closure theories with explicit closed-form expressions of the closing fluxes, such as Grad's classical closure. Following a similar approach as Garrett et al. (2015) [13], we investigate efficient implementations of the computationally expensive numerical quadrature method used for the moment evaluations of the maximum-entropy distribution by exploiting its inherent fine-grained parallelism with the parallelism offered by multi-core processors and graphics cards. We show that using a single graphics card as an accelerator allows speed-ups of two orders of magnitude when compared to a serial CPU implementation. To accelerate the time-to-solution for steady-state problems, we propose a new semi-implicit time discretization scheme. The resulting nonlinear system of equations is solved with a Newton type method in the Lagrange multipliers of the dual optimization problem in order to reduce the computational cost. Additionally, fully explicit time-stepping schemes of first and second order accuracy are presented. We investigate the accuracy and efficiency of the numerical schemes for several numerical test cases, including a steady-state shock-structure problem.
Structure of a Global Network of Financial Companies Based on Transfer Entropy
Directory of Open Access Journals (Sweden)
Leonidas Sandoval
2014-08-01
Full Text Available This work uses the stocks of the 197 largest companies in the world, in terms of market capitalization, in the financial area, from 2003 to 2012. We study the causal relationships between them using Transfer Entropy, which is calculated using the stocks of those companies and their counterparts lagged by one day. With this, we can assess which companies influence others according to sub-areas of the financial sector, which are banks, diversified financial services, savings and loans, insurance, private equity funds, real estate investment companies, and real estate trust funds. We also analyze the exchange of information between those stocks as seen by Transfer Entropy and the network formed by them based on this measure, verifying that they cluster mainly according to countries of origin, and then by industry and sub-industry. Then we use data on the stocks of companies in the financial sector of some countries that are suffering the most with the current credit crisis, namely Greece, Cyprus, Ireland, Spain, Portugal, and Italy, and assess, also using Transfer Entropy, which companies from the largest 197 are most affected by the stocks of these countries in crisis. The aim is to map a network of influences that may be used in the study of possible contagions originating in those countries in financial crisis.
Li, Xin Xin; Sang, Yan Fang; Xie, Ping; Liu, Chang Ming
2018-04-01
Daily precipitation process in China showed obvious randomness and spatiotemporal variation. It is important to accurately understand the influence of precipitation changes on control of flood and waterlogging disaster. Using the daily precipitation data measured at 520 stations in China during 1961-2013, we quantified the stochastic characteristics of daily precipitation over China based on the index of information entropy. Results showed that the randomness of daily precipitation in the southeast region were larger than that in the northwest region. Moreover, the spatial distribution of stochastic characteristics of precipitation was different at various grades. Stochastic characteri-stics of P 0 (precipitation at 0.1-10 mm) was large, but the spatial variation was not obvious. The stochastic characteristics of P 10 (precipitation at 10-25 mm) and P 25 (precipitation at 25-50 mm) were the largest and their spatial difference was obvious. P 50 (precipitation ≥50 mm) had the smallest stochastic characteristics and the most obviously spatial difference. Generally, the entropy values of precipitation obviously increased over the last five decades, indicating more significantly stochastic characteristics of precipitation (especially the obvious increase of heavy precipitation events) in most region over China under the scenarios of global climate change. Given that the spatial distribution and long-term trend of entropy values of daily precipitation could reflect thespatial distribution of stochastic characteristics of precipitation, our results could provide scientific basis for the control of flood and waterlogging disaster, the layout of agricultural planning, and the planning of ecological environment.
Directory of Open Access Journals (Sweden)
Sheng Lin
2015-07-01
Full Text Available On the basis of analyzing high-voltage direct current (HVDC transmission system and its fault superimposed circuit, the direction of the fault components of the voltage and the current measured at one end of transmission line is certified to be different for internal faults and external faults. As an estimate of the differences between two signals, relative entropy is an effective parameter for recognizing transient signals in HVDC transmission lines. In this paper, the relative entropy of wavelet energy is applied to distinguish internal fault from external fault. For internal faults, the directions of fault components of voltage and current are opposite at the two ends of the transmission line, indicating a huge difference of wavelet energy relative entropy; for external faults, the directions are identical, indicating a small difference. The simulation results based on PSCAD/EMTDC show that the proposed pilot protection system acts accurately for faults under different conditions, and its performance is not affected by fault type, fault location, fault resistance and noise.
Maximum entropy production rate in quantum thermodynamics
Energy Technology Data Exchange (ETDEWEB)
Beretta, Gian Paolo, E-mail: beretta@ing.unibs.i [Universita di Brescia, via Branze 38, 25123 Brescia (Italy)
2010-06-01
, well-behaved and intriguing, general closure of the dynamics, compatible with the nontrivial requirements of strong separability. Based on the time-energy Heisenberg uncertainty relation, we derive a lower bound to the internal-relaxation-time functionals that determine the rate of entropy generation. This bound entails an upper bound to the rate of entropy generation. By this extreme maximal-entropy-generation-rate ansatz, each indivisible subsystem follows the direction of steepest locally perceived entropy ascent at the highest rate compatible with the time- energy uncertainty principle.
A risk standard based on societal cost with bounded consequences
International Nuclear Information System (INIS)
Worledge, D.H.
1982-01-01
A risk standard is proposed that relates the frequency of occurrence of single events to the consequences of the events. Maximum consequences and risk aversion are used to give the cumulative risk curve a shape similar to the results of a risk assessment and to bound the expectation of deaths. Societal costs in terms of deaths are used to fix the parameters of the model together with an approximate comparison with individual risks. The proposed standard is compared with some practical applications of risk assessment to nuclear reactor systems
International Nuclear Information System (INIS)
Clariá, F; Vallverdú, M; Caminal, P; Baranowski, R; Chojnowska, L
2008-01-01
In hypertrophic cardiomyopathy (HCM) patients there is an increased risk of premature death, which can occur with little or no warning. Furthermore, classification for sudden cardiac death on patients with HCM is very difficult. The aim of our study was to improve the prognostic value of heart rate variability (HRV) in HCM patients, giving insight into changes of the autonomic nervous system. In this way, the suitability of linear and nonlinear measures was studied to assess the HRV. These measures were based on time–frequency representation (TFR) and on Shannon and Rényi entropies, and compared with traditional HRV measures. Holter recordings of 64 patients with HCM and 55 healthy subjects were analyzed. The HCM patients consisted of two groups: 13 high risk patients, after aborted sudden cardiac death (SCD); 51 low risk patients, without SCD. Five-hour RR signals, corresponding to the sleep period of the subjects, were considered for the analysis as a comparable standard situation. These RR signals were filtered in the three frequency bands: very low frequency band (VLF, 0–0.04 Hz), low frequency band (LF, 0.04–0.15 Hz) and high frequency band (HF, 0.15–0.45 Hz). TFR variables based on instantaneous frequency and energy functions were able to classify HCM patients and healthy subjects (control group). Results revealed that measures obtained from TFR analysis of the HRV better classified the groups of subjects than traditional HRV parameters. However, results showed that nonlinear measures improved group classification. It was observed that entropies calculated in the HF band showed the highest statistically significant levels comparing the HCM group and the control group, p-value < 0.0005. The values of entropy measures calculated in the HCM group presented lower values, indicating a decreasing of complexity, than those calculated from the control group. Moreover, similar behavior was observed comparing high and low risk of premature death, the values of
Yao, Lei; Wang, Zhenpo; Ma, Jun
2015-10-01
This paper proposes a method of fault detection of the connection of Lithium-Ion batteries based on entropy for electric vehicle. In electric vehicle operation process, some factors, such as road conditions, driving habits, vehicle performance, always affect batteries by vibration, which easily cause loosing or virtual connection between batteries. Through the simulation of the battery charging and discharging experiment under vibration environment, the data of voltage fluctuation can be obtained. Meanwhile, an optimal filtering method is adopted using discrete cosine filter method to analyze the characteristics of system noise, based on the voltage set when batteries are working under different vibration frequency. Experimental data processed by filtering is analyzed based on local Shannon entropy, ensemble Shannon entropy and sample entropy. And the best way to find a method of fault detection of the connection of lithium-ion batteries based on entropy is presented for electric vehicle. The experimental data shows that ensemble Shannon entropy can predict the accurate time and the location of battery connection failure in real time. Besides electric-vehicle industry, this method can also be used in other areas in complex vibration environment.
Cross entropy-based memetic algorithms: An application study over the tool switching problem
Directory of Open Access Journals (Sweden)
Jhon Edgar Amaya
2013-05-01
Full Text Available This paper presents a parameterized schema for building memetic algorithms based on cross-entropy (CE methods. This novel schema is general in nature, and features multiple probability mass functions and Lamarckian learning. The applicability of the approach is assessed by considering the Tool Switching Problem, a complex combinatorial problem in the field of Flexible Manufacturing Systems. An exhaustive evaluation (including techniques ranging from local search and evolutionary algorithms to constructive methods provides evidence of the effectiveness of CE-based memetic algorithms.
A Novel Entropy-Based Decoding Algorithm for a Generalized High-Order Discrete Hidden Markov Model
Directory of Open Access Journals (Sweden)
Jason Chin-Tiong Chan
2018-01-01
Full Text Available The optimal state sequence of a generalized High-Order Hidden Markov Model (HHMM is tracked from a given observational sequence using the classical Viterbi algorithm. This classical algorithm is based on maximum likelihood criterion. We introduce an entropy-based Viterbi algorithm for tracking the optimal state sequence of a HHMM. The entropy of a state sequence is a useful quantity, providing a measure of the uncertainty of a HHMM. There will be no uncertainty if there is only one possible optimal state sequence for HHMM. This entropy-based decoding algorithm can be formulated in an extended or a reduction approach. We extend the entropy-based algorithm for computing the optimal state sequence that was developed from a first-order to a generalized HHMM with a single observational sequence. This extended algorithm performs the computation exponentially with respect to the order of HMM. The computational complexity of this extended algorithm is due to the growth of the model parameters. We introduce an efficient entropy-based decoding algorithm that used reduction approach, namely, entropy-based order-transformation forward algorithm (EOTFA to compute the optimal state sequence of any generalized HHMM. This EOTFA algorithm involves a transformation of a generalized high-order HMM into an equivalent first-order HMM and an entropy-based decoding algorithm is developed based on the equivalent first-order HMM. This algorithm performs the computation based on the observational sequence and it requires OTN~2 calculations, where N~ is the number of states in an equivalent first-order model and T is the length of observational sequence.
Adjoint entropy vs topological entropy
Giordano Bruno, Anna
2012-01-01
Recently the adjoint algebraic entropy of endomorphisms of abelian groups was introduced and studied. We generalize the notion of adjoint entropy to continuous endomorphisms of topological abelian groups. Indeed, the adjoint algebraic entropy is defined using the family of all finite-index subgroups, while we take only the subfamily of all open finite-index subgroups to define the topological adjoint entropy. This allows us to compare the (topological) adjoint entropy with the known topologic...
Chen, Dong; Gara, Alana; Heidelberger, Philip; Kumar, Sameer; Ohmacht, Martin; Steinmacher-Burow, Burkhard; Wisniewski, Robert
2014-09-16
Implementation primitives for concurrent array-based stacks, queues, double-ended queues (deques) and wrapped deques are provided. In one aspect, each element of the stack, queue, deque or wrapped deque data structure has its own ticket lock, allowing multiple threads to concurrently use multiple elements of the data structure and thus achieving high performance. In another aspect, new synchronization primitives FetchAndIncrementBounded (Counter, Bound) and FetchAndDecrementBounded (Counter, Bound) are implemented. These primitives can be implemented in hardware and thus promise a very fast throughput for queues, stacks and double-ended queues.
International Nuclear Information System (INIS)
Baccetti, Valentina; Visser, Matt
2013-01-01
Even if a probability distribution is properly normalizable, its associated Shannon (or von Neumann) entropy can easily be infinite. We carefully analyze conditions under which this phenomenon can occur. Roughly speaking, this happens when arbitrarily small amounts of probability are dispersed into an infinite number of states; we shall quantify this observation and make it precise. We develop several particularly simple, elementary, and useful bounds, and also provide some asymptotic estimates, leading to necessary and sufficient conditions for the occurrence of infinite Shannon entropy. We go to some effort to keep technical computations as simple and conceptually clear as possible. In particular, we shall see that large entropies cannot be localized in state space; large entropies can only be supported on an exponentially large number of states. We are for the time being interested in single-channel Shannon entropy in the information theoretic sense, not entropy in a stochastic field theory or quantum field theory defined over some configuration space, on the grounds that this simple problem is a necessary precursor to understanding infinite entropy in a field theoretic context. (paper)
Large Field Inflation and Gravitational Entropy
DEFF Research Database (Denmark)
Kaloper, Nemanja; Kleban, Matthew; Lawrence, Albion
2016-01-01
species will lead to a violation of the covariant entropy bound at large $N$. If so, requiring the validity of the covariant entropy bound could limit the number of light species and their couplings, which in turn could severely constrain axion-driven inflation. Here we show that there is no such problem...... entropy of de Sitter or near-de Sitter backgrounds at leading order. Working in detail with $N$ scalar fields in de Sitter space, renormalized to one loop order, we show that the gravitational entropy automatically obeys the covariant entropy bound. Furthermore, while the axion decay constant is a strong...... in this light, and show that they are perfectly consistent with the covariant entropy bound. Thus, while quantum gravity might yet spoil large field inflation, holographic considerations in the semiclassical theory do not obstruct it....
Refined multiscale fuzzy entropy based on standard deviation for biomedical signal analysis.
Azami, Hamed; Fernández, Alberto; Escudero, Javier
2017-11-01
Multiscale entropy (MSE) has been a prevalent algorithm to quantify the complexity of biomedical time series. Recent developments in the field have tried to alleviate the problem of undefined MSE values for short signals. Moreover, there has been a recent interest in using other statistical moments than the mean, i.e., variance, in the coarse-graining step of the MSE. Building on these trends, here we introduce the so-called refined composite multiscale fuzzy entropy based on the standard deviation (RCMFE σ ) and mean (RCMFE μ ) to quantify the dynamical properties of spread and mean, respectively, over multiple time scales. We demonstrate the dependency of the RCMFE σ and RCMFE μ , in comparison with other multiscale approaches, on several straightforward signal processing concepts using a set of synthetic signals. The results evidenced that the RCMFE σ and RCMFE μ values are more stable and reliable than the classical multiscale entropy ones. We also inspect the ability of using the standard deviation as well as the mean in the coarse-graining process using magnetoencephalograms in Alzheimer's disease and publicly available electroencephalograms recorded from focal and non-focal areas in epilepsy. Our results indicated that when the RCMFE μ cannot distinguish different types of dynamics of a particular time series at some scale factors, the RCMFE σ may do so, and vice versa. The results showed that RCMFE σ -based features lead to higher classification accuracies in comparison with the RCMFE μ -based ones. We also made freely available all the Matlab codes used in this study at http://dx.doi.org/10.7488/ds/1477 .
Quantum aspects of black hole entropy
Indian Academy of Sciences (India)
Quantum corrections to the semiclassical Bekenstein–Hawking area law for black hole entropy, obtained within the quantum geometry framework, are treated in some detail. Their ramiﬁcation for the holographic entropy bound for bounded stationary spacetimes is discussed. Four dimensional supersymmetric extremal black ...
Chaos control of ferroresonance system based on RBF-maximum entropy clustering algorithm
International Nuclear Information System (INIS)
Liu Fan; Sun Caixin; Sima Wenxia; Liao Ruijin; Guo Fei
2006-01-01
With regards to the ferroresonance overvoltage of neutral grounded power system, a maximum-entropy learning algorithm based on radial basis function neural networks is used to control the chaotic system. The algorithm optimizes the object function to derive learning rule of central vectors, and uses the clustering function of network hidden layers. It improves the regression and learning ability of neural networks. The numerical experiment of ferroresonance system testifies the effectiveness and feasibility of using the algorithm to control chaos in neutral grounded system
Local curvature entropy-based 3D terrain representation using a comprehensive Quadtree
Chen, Qiyu; Liu, Gang; Ma, Xiaogang; Mariethoz, Gregoire; He, Zhenwen; Tian, Yiping; Weng, Zhengping
2018-05-01
Large scale 3D digital terrain modeling is a crucial part of many real-time applications in geoinformatics. In recent years, the improved speed and precision in spatial data collection make the original terrain data more complex and bigger, which poses challenges for data management, visualization and analysis. In this work, we presented an effective and comprehensive 3D terrain representation based on local curvature entropy and a dynamic Quadtree. The Level-of-detail (LOD) models of significant terrain features were employed to generate hierarchical terrain surfaces. In order to reduce the radical changes of grid density between adjacent LODs, local entropy of terrain curvature was regarded as a measure of subdividing terrain grid cells. Then, an efficient approach was presented to eliminate the cracks among the different LODs by directly updating the Quadtree due to an edge-based structure proposed in this work. Furthermore, we utilized a threshold of local entropy stored in each parent node of this Quadtree to flexibly control the depth of the Quadtree and dynamically schedule large-scale LOD terrain. Several experiments were implemented to test the performance of the proposed method. The results demonstrate that our method can be applied to construct LOD 3D terrain models with good performance in terms of computational cost and the maintenance of terrain features. Our method has already been deployed in a geographic information system (GIS) for practical uses, and it is able to support the real-time dynamic scheduling of large scale terrain models more easily and efficiently.
International Nuclear Information System (INIS)
Ko, T.H.
2006-01-01
In the present paper, the entropy generation and optimal Reynolds number for developing forced convection in a double sine duct with various wall heat fluxes, which frequently occurs in plate heat exchangers, are studied based on the entropy generation minimization principle by analytical thermodynamic analysis as well as numerical investigation. According to the thermodynamic analysis, a very simple expression for the optimal Reynolds number for the double sine duct as a function of mass flow rate, wall heat flux, working fluid and geometric dimensions is proposed. In the numerical simulations, the investigated Reynolds number (Re) covers the range from 86 to 2000 and the wall heat flux (q'') varies as 160, 320 and 640 W/m 2 . From the numerical simulation of the developing laminar forced convection in the double sine duct, the effect of Reynolds number on entropy generation in the duct has been examined, through which the optimal Reynolds number with minimal entropy generation is detected. The optimal Reynolds number obtained from the analytical thermodynamic analysis is compared with the one from the numerical solutions and is verified to have a similar magnitude of entropy generation as the minimal entropy generation predicted by the numerical simulations. The optimal analysis provided in the present paper gives worthy information for heat exchanger design, since the thermal system could have the least irreversibility and best exergy utilization if the optimal Re can be used according to practical design conditions
Chatter detection in milling process based on VMD and energy entropy
Liu, Changfu; Zhu, Lida; Ni, Chenbing
2018-05-01
This paper presents a novel approach to detect the milling chatter based on Variational Mode Decomposition (VMD) and energy entropy. VMD has already been employed in feature extraction from non-stationary signals. The parameters like number of modes (K) and the quadratic penalty (α) need to be selected empirically when raw signal is decomposed by VMD. Aimed at solving the problem how to select K and α, the automatic selection method of VMD's based on kurtosis is proposed in this paper. When chatter occurs in the milling process, energy will be absorbed to chatter frequency bands. To detect the chatter frequency bands automatically, the chatter detection method based on energy entropy is presented. The vibration signal containing chatter frequency is simulated and three groups of experiments which represent three cutting conditions are conducted. To verify the effectiveness of method presented by this paper, chatter feather extraction has been successfully employed on simulation signals and experimental signals. The simulation and experimental results show that the proposed method can effectively detect the chatter.
EEG-Based Computer Aided Diagnosis of Autism Spectrum Disorder Using Wavelet, Entropy, and ANN
Directory of Open Access Journals (Sweden)
Ridha Djemal
2017-01-01
Full Text Available Autism spectrum disorder (ASD is a type of neurodevelopmental disorder with core impairments in the social relationships, communication, imagination, or flexibility of thought and restricted repertoire of activity and interest. In this work, a new computer aided diagnosis (CAD of autism based on electroencephalography (EEG signal analysis is investigated. The proposed method is based on discrete wavelet transform (DWT, entropy (En, and artificial neural network (ANN. DWT is used to decompose EEG signals into approximation and details coefficients to obtain EEG subbands. The feature vector is constructed by computing Shannon entropy values from each EEG subband. ANN classifies the corresponding EEG signal into normal or autistic based on the extracted features. The experimental results show the effectiveness of the proposed method for assisting autism diagnosis. A receiver operating characteristic (ROC curve metric is used to quantify the performance of the proposed method. The proposed method obtained promising results tested using real dataset provided by King Abdulaziz Hospital, Jeddah, Saudi Arabia.
An Integrated Dictionary-Learning Entropy-Based Medical Image Fusion Framework
Directory of Open Access Journals (Sweden)
Guanqiu Qi
2017-10-01
Full Text Available Image fusion is widely used in different areas and can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. Medical image fusion, as an important image fusion application, can extract the details of multiple images from different imaging modalities and combine them into an image that contains complete and non-redundant information for increasing the accuracy of medical diagnosis and assessment. The quality of the fused image directly affects medical diagnosis and assessment. However, existing solutions have some drawbacks in contrast, sharpness, brightness, blur and details. This paper proposes an integrated dictionary-learning and entropy-based medical image-fusion framework that consists of three steps. First, the input image information is decomposed into low-frequency and high-frequency components by using a Gaussian filter. Second, low-frequency components are fused by weighted average algorithm and high-frequency components are fused by the dictionary-learning based algorithm. In the dictionary-learning process of high-frequency components, an entropy-based algorithm is used for informative blocks selection. Third, the fused low-frequency and high-frequency components are combined to obtain the final fusion results. The results and analyses of comparative experiments demonstrate that the proposed medical image fusion framework has better performance than existing solutions.
A Roller Bearing Fault Diagnosis Method Based on LCD Energy Entropy and ACROA-SVM
Directory of Open Access Journals (Sweden)
HungLinh Ao
2014-01-01
Full Text Available This study investigates a novel method for roller bearing fault diagnosis based on local characteristic-scale decomposition (LCD energy entropy, together with a support vector machine designed using an Artificial Chemical Reaction Optimisation Algorithm, referred to as an ACROA-SVM. First, the original acceleration vibration signals are decomposed into intrinsic scale components (ISCs. Second, the concept of LCD energy entropy is introduced. Third, the energy features extracted from a number of ISCs that contain the most dominant fault information serve as input vectors for the support vector machine classifier. Finally, the ACROA-SVM classifier is proposed to recognize the faulty roller bearing pattern. The analysis of roller bearing signals with inner-race and outer-race faults shows that the diagnostic approach based on the ACROA-SVM and using LCD to extract the energy levels of the various frequency bands as features can identify roller bearing fault patterns accurately and effectively. The proposed method is superior to approaches based on Empirical Mode Decomposition method and requires less time.
Jesudason, Christopher G.
2003-09-01
Recently, there have appeared interesting correctives or challenges [Entropy 1999, 1, 111-147] to the Second law formulations, especially in the interpretation of the Clausius equivalent transformations, closely related in area to extensions of the Clausius principle to irreversible processes [Chem. Phys. Lett. 1988, 143(1), 65-70]. Since the traditional formulations are central to science, a brief analysis of some of these newer theories along traditional lines is attempted, based on well-attested axioms which have formed the basis of equilibrium thermodynamics. It is deduced that the Clausius analysis leading to the law of increasing entropy does not follow from the given axioms but it can be proved that for irreversible transitions, the total entropy change of the system and thermal reservoirs (the "Universe") is not negative, even for the case when the reservoirs are not at the same temperature as the system during heat transfer. On the basis of two new simple theorems and three corollaries derived for the correlation between irreversible and reversible pathways and the traditional axiomatics, it is shown that a sequence of reversible states can never be used to describe a corresponding sequence of irreversible states for at least closed systems, thereby restricting the principle of local equilibrium. It is further shown that some of the newer irreversible entropy forms given exhibit some paradoxical properties relative to the standard axiomatics. It is deduced that any reconciliation between the traditional approach and novel theories lie in creating a well defined set of axioms to which all theoretical developments should attempt to be based on unless proven not be useful, in which case there should be consensus in removing such axioms from theory. Clausius' theory of equivalent transformations do not contradict the traditional understanding of heat- work efficiency. It is concluded that the intuitively derived assumptions over the last two centuries seem to
Directory of Open Access Journals (Sweden)
Beatriz García-Martínez
2016-06-01
Full Text Available Recognition of emotions is still an unresolved challenge, which could be helpful to improve current human-machine interfaces. Recently, nonlinear analysis of some physiological signals has shown to play a more relevant role in this context than their traditional linear exploration. Thus, the present work introduces for the first time the application of three recent entropy-based metrics: sample entropy (SE, quadratic SE (QSE and distribution entropy (DE to discern between emotional states of calm and negative stress (also called distress. In the last few years, distress has received growing attention because it is a common negative factor in the modern lifestyle of people from developed countries and, moreover, it may lead to serious mental and physical health problems. Precisely, 279 segments of 32-channel electroencephalographic (EEG recordings from 32 subjects elicited to be calm or negatively stressed have been analyzed. Results provide that QSE is the first single metric presented to date with the ability to identify negative stress. Indeed, this metric has reported a discriminant ability of around 70%, which is only slightly lower than the one obtained by some previous works. Nonetheless, discriminant models from dozens or even hundreds of features have been previously obtained by using advanced classifiers to yield diagnostic accuracies about 80%. Moreover, in agreement with previous neuroanatomy findings, QSE has also revealed notable differences for all the brain regions in the neural activation triggered by the two considered emotions. Consequently, given these results, as well as easy interpretation of QSE, this work opens a new standpoint in the detection of emotional distress, which may gain new insights about the brain’s behavior under this negative emotion.
Trustworthiness Measurement Algorithm for TWfMS Based on Software Behaviour Entropy
Directory of Open Access Journals (Sweden)
Qiang Han
2018-03-01
Full Text Available As the virtual mirror of complex real-time business processes of organisations’ underlying information systems, the workflow management system (WfMS has emerged in recent decades as a new self-autonomous paradigm in the open, dynamic, distributed computing environment. In order to construct a trustworthy workflow management system (TWfMS, the design of a software behaviour trustworthiness measurement algorithm is an urgent task for researchers. Accompanying the trustworthiness mechanism, the measurement algorithm, with uncertain software behaviour trustworthiness information of the WfMS, should be resolved as an infrastructure. Based on the framework presented in our research prior to this paper, we firstly introduce a formal model for the WfMS trustworthiness measurement, with the main property reasoning based on calculus operators. Secondly, this paper proposes a novel measurement algorithm from the software behaviour entropy of calculus operators through the principle of maximum entropy (POME and the data mining method. Thirdly, the trustworthiness measurement algorithm for incomplete software behaviour tests and runtime information is discussed and compared by means of a detailed explanation. Finally, we provide conclusions and discuss certain future research areas of the TWfMS.
Measuring time series regularity using nonlinear similarity-based sample entropy
International Nuclear Information System (INIS)
Xie Hongbo; He Weixing; Liu Hui
2008-01-01
Sampe Entropy (SampEn), a measure quantifying regularity and complexity, is believed to be an effective analyzing method of diverse settings that include both deterministic chaotic and stochastic processes, particularly operative in the analysis of physiological signals that involve relatively small amount of data. However, the similarity definition of vectors is based on Heaviside function, of which the boundary is discontinuous and hard, may cause some problems in the validity and accuracy of SampEn. Sigmoid function is a smoothed and continuous version of Heaviside function. To overcome the problems SampEn encountered, a modified SampEn (mSampEn) based on nonlinear Sigmoid function was proposed. The performance of mSampEn was tested on the independent identically distributed (i.i.d.) uniform random numbers, the MIX stochastic model, the Rossler map, and the Hennon map. The results showed that mSampEn was superior to SampEn in several aspects, including giving entropy definition in case of small parameters, better relative consistency, robust to noise, and more independence on record length when characterizing time series generated from either deterministic or stochastic system with different regularities
Zheng, Jinde; Pan, Haiyang; Yang, Shubao; Cheng, Junsheng
2018-01-01
Multiscale permutation entropy (MPE) is a recently proposed nonlinear dynamic method for measuring the randomness and detecting the nonlinear dynamic change of time series and can be used effectively to extract the nonlinear dynamic fault feature from vibration signals of rolling bearing. To solve the drawback of coarse graining process in MPE, an improved MPE method called generalized composite multiscale permutation entropy (GCMPE) was proposed in this paper. Also the influence of parameters on GCMPE and its comparison with the MPE are studied by analyzing simulation data. GCMPE was applied to the fault feature extraction from vibration signal of rolling bearing and then based on the GCMPE, Laplacian score for feature selection and the Particle swarm optimization based support vector machine, a new fault diagnosis method for rolling bearing was put forward in this paper. Finally, the proposed method was applied to analyze the experimental data of rolling bearing. The analysis results show that the proposed method can effectively realize the fault diagnosis of rolling bearing and has a higher fault recognition rate than the existing methods.
Combined Forecasting of Rainfall Based on Fuzzy Clustering and Cross Entropy
Directory of Open Access Journals (Sweden)
Baohui Men
2017-12-01
Full Text Available Rainfall is an essential index to measure drought, and it is dependent upon various parameters including geographical environment, air temperature and pressure. The nonlinear nature of climatic variables leads to problems such as poor accuracy and instability in traditional forecasting methods. In this paper, the combined forecasting method based on data mining technology and cross entropy is proposed to forecast the rainfall with full consideration of the time-effectiveness of historical data. In view of the flaws of the fuzzy clustering method which is easy to fall into local optimal solution and low speed of operation, the ant colony algorithm is adopted to overcome these shortcomings and, as a result, refine the model. The method for determining weights is also improved by using the cross entropy. Besides, the forecast is conducted by analyzing the weighted average rainfall based on Thiessen polygon in the Beijing–Tianjin–Hebei region. Since the predictive errors are calculated, the results show that improved ant colony fuzzy clustering can effectively select historical data and enhance the accuracy of prediction so that the damage caused by extreme weather events like droughts and floods can be greatly lessened and even kept at bay.
A Novel Object Tracking Algorithm Based on Compressed Sensing and Entropy of Information
Directory of Open Access Journals (Sweden)
Ding Ma
2015-01-01
Full Text Available Object tracking has always been a hot research topic in the field of computer vision; its purpose is to track objects with specific characteristics or representation and estimate the information of objects such as their locations, sizes, and rotation angles in the current frame. Object tracking in complex scenes will usually encounter various sorts of challenges, such as location change, dimension change, illumination change, perception change, and occlusion. This paper proposed a novel object tracking algorithm based on compressed sensing and information entropy to address these challenges. First, objects are characterized by the Haar (Haar-like and ORB features. Second, the dimensions of computation space of the Haar and ORB features are effectively reduced through compressed sensing. Then the above-mentioned features are fused based on information entropy. Finally, in the particle filter framework, an object location was obtained by selecting candidate object locations in the current frame from the local context neighboring the optimal locations in the last frame. Our extensive experimental results demonstrated that this method was able to effectively address the challenges of perception change, illumination change, and large area occlusion, which made it achieve better performance than existing approaches such as MIL and CT.
Energy and entropy analysis of closed adiabatic expansion based trilateral cycles
International Nuclear Information System (INIS)
Garcia, Ramon Ferreiro; Carril, Jose Carbia; Gomez, Javier Romero; Gomez, Manuel Romero
2016-01-01
Highlights: • The adiabatic expansion based TC surpass Carnot factor at low temperatures. • The fact of surpassing Carnot factor doesn’t violate the 2nd law. • An entropy analysis is applied to verify the fulfilment of the second law. • Correction of the exergy transfer associated with heat transferred to a cycle. - Abstract: A vast amount of heat energy is available at low cost within the range of medium and low temperatures. Existing thermal cycles cannot make efficient use of such available low grade heat because they are mainly based on conventional organic Rankine cycles which are limited by Carnot constraints. However, recent developments related to the performance of thermal cycles composed of closed processes have led to the exceeding of the Carnot factor. Consequently, once the viability of closed process based thermal cycles that surpass the Carnot factor operating at low and medium temperatures is globally accepted, research work will aim at looking into the consequences that lead from surpassing the Carnot factor while fulfilling the 2nd law, its impact on the 2nd law efficiency definition as well as the impact on the exergy transfer from thermal power sources to any heat consumer, including thermal cycles. The methodology used to meet the proposed objectives involves the analysis of energy and entropy on trilateral closed process based thermal cycles. Thus, such energy and entropy analysis is carried out upon non-condensing mode trilateral thermal cycles (TCs) characterised by the conversion of low grade heat into mechanical work undergoing closed adiabatic path functions: isochoric heat absorption, adiabatic heat to mechanical work conversion and isobaric heat rejection. Firstly, cycle energy analysis is performed to determine the range of some relevant cycle parameters, such as the operating temperatures and their associated pressures, entropies, internal energies and specific volumes. In this way, the ranges of temperatures within which
Constructing a Measurement Method of Differences in Group Preferences Based on Relative Entropy
Directory of Open Access Journals (Sweden)
Shiyu Zhang
2017-01-01
Full Text Available 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.
Entropy and equilibrium via games of complexity
Topsøe, Flemming
2004-09-01
It is suggested that thermodynamical equilibrium equals game theoretical equilibrium. Aspects of this thesis are discussed. The philosophy is consistent with maximum entropy thinking of Jaynes, but goes one step deeper by deriving the maximum entropy principle from an underlying game theoretical principle. The games introduced are based on measures of complexity. Entropy is viewed as minimal complexity. It is demonstrated that Tsallis entropy ( q-entropy) and Kaniadakis entropy ( κ-entropy) can be obtained in this way, based on suitable complexity measures. A certain unifying effect is obtained by embedding these measures in a two-parameter family of entropy functions.
Entropy-Based Voltage Fault Diagnosis of Battery Systems for Electric Vehicles
Directory of Open Access Journals (Sweden)
Peng Liu
2018-01-01
Full Text Available The battery is a key component and the major fault source in electric vehicles (EVs. Ensuring power battery safety is of great significance to make the diagnosis more effective and predict the occurrence of faults, for the power battery is one of the core technologies of EVs. This paper proposes a voltage fault diagnosis detection mechanism using entropy theory which is demonstrated in an EV with a multiple-cell battery system during an actual operation situation. The preliminary analysis, after collecting and preprocessing the typical data periods from Operation Service and Management Center for Electric Vehicle (OSMC-EV in Beijing, shows that overvoltage fault for Li-ion batteries cell can be observed from the voltage curves. To further locate abnormal cells and predict faults, an entropy weight method is established to calculate the objective weight, which reduces the subjectivity and improves the reliability. The result clearly identifies the abnormity of cell voltage. The proposed diagnostic model can be used for EV real-time diagnosis without laboratory testing methods. It is more effective than traditional methods based on contrastive analysis.
The SSVEP-Based BCI Text Input System Using Entropy Encoding Algorithm
Directory of Open Access Journals (Sweden)
Yeou-Jiunn Chen
2015-01-01
Full Text Available The so-called amyotrophic lateral sclerosis (ALS or motor neuron disease (MND is a neurodegenerative disease with various causes. It is characterized by muscle spasticity, rapidly progressive weakness due to muscle atrophy, and difficulty in speaking, swallowing, and breathing. The severe disabled always have a common problem that is about communication except physical malfunctions. The steady-state visually evoked potential based brain computer interfaces (BCI, which apply visual stimulus, are very suitable to play the role of communication interface for patients with neuromuscular impairments. In this study, the entropy encoding algorithm is proposed to encode the letters of multilevel selection interface for BCI text input systems. According to the appearance frequency of each letter, the entropy encoding algorithm is proposed to construct a variable-length tree for the letter arrangement of multilevel selection interface. Then, the Gaussian mixture models are applied to recognize electrical activity of the brain. According to the recognition results, the multilevel selection interface guides the subject to spell and type the words. The experimental results showed that the proposed approach outperforms the baseline system, which does not consider the appearance frequency of each letter. Hence, the proposed approach is able to ease text input interface for patients with neuromuscular impairments.
Directory of Open Access Journals (Sweden)
Shaofeng Xie
2017-01-01
Full Text Available Given the chaotic characteristics of the time series of landslides, a new method based on modified ensemble empirical mode decomposition (MEEMD, approximate entropy and the weighted least square support vector machine (WLS-SVM was proposed. The method mainly started from the chaotic sequence of time-frequency analysis and improved the model performance as follows: first a deformation time series was decomposed into a series of subsequences with significantly different complexity using MEEMD. Then the approximate entropy method was used to generate a new subsequence for the combination of subsequences with similar complexity, which could effectively concentrate the component feature information and reduce the computational scale. Finally the WLS-SVM prediction model was established for each new subsequence. At the same time, phase space reconstruction theory and the grid search method were used to select the input dimension and the optimal parameters of the model, and then the superposition of each predicted value was the final forecasting result. Taking the landslide deformation data of Danba as an example, the experiments were carried out and compared with wavelet neural network, support vector machine, least square support vector machine and various combination schemes. The experimental results show that the algorithm has high prediction accuracy. It can ensure a better prediction effect even in landslide deformation periods of rapid fluctuation, and it can also better control the residual value and effectively reduce the error interval.
A new qualitative acoustic emission parameter based on Shannon's entropy for damage monitoring
Chai, Mengyu; Zhang, Zaoxiao; Duan, Quan
2018-02-01
An important objective of acoustic emission (AE) non-destructive monitoring is to accurately identify approaching critical damage and to avoid premature failure by means of the evolutions of AE parameters. One major drawback of most parameters such as count and rise time is that they are strongly dependent on the threshold and other settings employed in AE data acquisition system. This may hinder the correct reflection of original waveform generated from AE sources and consequently bring difficulty for the accurate identification of the critical damage and early failure. In this investigation, a new qualitative AE parameter based on Shannon's entropy, i.e. AE entropy is proposed for damage monitoring. Since it derives from the uncertainty of amplitude distribution of each AE waveform, it is independent of the threshold and other time-driven parameters and can characterize the original micro-structural deformations. Fatigue crack growth test on CrMoV steel and three point bending test on a ductile material are conducted to validate the feasibility and effectiveness of the proposed parameter. The results show that the new parameter, compared to AE amplitude, is more effective in discriminating the different damage stages and identifying the critical damage.
Analysis of financial time series using multiscale entropy based on skewness and kurtosis
Xu, Meng; Shang, Pengjian
2018-01-01
There is a great interest in studying dynamic characteristics of the financial time series of the daily stock closing price in different regions. Multi-scale entropy (MSE) is effective, mainly in quantifying the complexity of time series on different time scales. This paper applies a new method for financial stability from the perspective of MSE based on skewness and kurtosis. To better understand the superior coarse-graining method for the different kinds of stock indexes, we take into account the developmental characteristics of the three continents of Asia, North America and European stock markets. We study the volatility of different financial time series in addition to analyze the similarities and differences of coarsening time series from the perspective of skewness and kurtosis. A kind of corresponding relationship between the entropy value of stock sequences and the degree of stability of financial markets, were observed. The three stocks which have particular characteristics in the eight piece of stock sequences were discussed, finding the fact that it matches the result of applying the MSE method to showing results on a graph. A comparative study is conducted to simulate over synthetic and real world data. Results show that the modified method is more effective to the change of dynamics and has more valuable information. The result is obtained at the same time, finding the results of skewness and kurtosis discrimination is obvious, but also more stable.
International Nuclear Information System (INIS)
Ohdaira, Tetsushi
2014-01-01
Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision. (paper)
Ohdaira, Tetsushi
2014-07-01
Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision.
Microscopic insights into the NMR relaxation based protein conformational entropy meter
Kasinath, Vignesh; Sharp, Kim A.; Wand, A. Joshua
2013-01-01
Conformational entropy is a potentially important thermodynamic parameter contributing to protein function. Quantitative measures of conformational entropy are necessary for an understanding of its role but have been difficult to obtain. An empirical method that utilizes changes in conformational dynamics as a proxy for changes in conformational entropy has recently been introduced. Here we probe the microscopic origins of the link between conformational dynamics and conformational entropy using molecular dynamics simulations. Simulation of seven pro! teins gave an excellent correlation with measures of side-chain motion derived from NMR relaxation. The simulations show that the motion of methyl-bearing side-chains are sufficiently coupled to that of other side chains to serve as excellent reporters of the overall side-chain conformational entropy. These results tend to validate the use of experimentally accessible measures of methyl motion - the NMR-derived generalized order parameters - as a proxy from which to derive changes in protein conformational entropy. PMID:24007504
Directory of Open Access Journals (Sweden)
Hui Chen
2018-06-01
Full Text Available According to the fact that high frequency will be abnormally attenuated when seismic signals travel across reservoirs, a new method, which is named high-precision time-frequency entropy based on synchrosqueezing generalized S-transform, is proposed for hydrocarbon reservoir detection in this paper. First, the proposed method obtains the time-frequency spectra by synchrosqueezing generalized S-transform (SSGST, which are concentrated around the real instantaneous frequency of the signals. Then, considering the characteristics and effects of noises, we give a frequency constraint condition to calculate the entropy based on time-frequency spectra. The synthetic example verifies that the entropy will be abnormally high when seismic signals have an abnormal attenuation. Besides, comparing with the GST time-frequency entropy and the original SSGST time-frequency entropy in field data, the results of the proposed method show higher precision. Moreover, the proposed method can not only accurately detect and locate hydrocarbon reservoirs, but also effectively suppress the impact of random noises.
International Nuclear Information System (INIS)
Romero, R.; Pelegrina, J.L.
2003-01-01
A study of the entropy change ΔS between the β phase and the martensite in Cu-based shape memory alloys is presented. From a compilation of available experimental data, the composition dependence of ΔS was studied. The experimental data were analyzed within the frame of a simple model, which is based on the specific heats of the phases. It was demonstrated that the dependence of ΔS with composition comes only through the lattice parameter and the effective mass of the alloy. For the studied composition range, the greater vibrational entropy of β phase is mainly controlled by the high-mass Cu atoms
Analysis of Entropy Generation in Flow of Methanol-Based Nanofluid in a Sinusoidal Wavy Channel
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Muhammad Qasim
2017-10-01
Full Text Available The entropy generation due to heat transfer and fluid friction in mixed convective peristaltic flow of methanol-Al2O3 nano fluid is examined. Maxwell’s thermal conductivity model is used in analysis. Velocity and temperature profiles are utilized in the computation of the entropy generation number. The effects of involved physical parameters on velocity, temperature, entropy generation number, and Bejan number are discussed and explained graphically.
Digital Image Stabilization Method Based on Variational Mode Decomposition and Relative Entropy
Directory of Open Access Journals (Sweden)
Duo Hao
2017-11-01
Full Text Available Cameras mounted on vehicles frequently suffer from image shake due to the vehicles’ motions. To remove jitter motions and preserve intentional motions, a hybrid digital image stabilization method is proposed that uses variational mode decomposition (VMD and relative entropy (RE. In this paper, the global motion vector (GMV is initially decomposed into several narrow-banded modes by VMD. REs, which exhibit the difference of probability distribution between two modes, are then calculated to identify the intentional and jitter motion modes. Finally, the summation of the jitter motion modes constitutes jitter motions, whereas the subtraction of the resulting sum from the GMV represents the intentional motions. The proposed stabilization method is compared with several known methods, namely, medium filter (MF, Kalman filter (KF, wavelet decomposition (MD method, empirical mode decomposition (EMD-based method, and enhanced EMD-based method, to evaluate stabilization performance. Experimental results show that the proposed method outperforms the other stabilization methods.
Feature extraction and learning using context cue and Rényi entropy based mutual information
DEFF Research Database (Denmark)
Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping
2015-01-01
information. In particular, for feature extraction, we develop a new set of kernel descriptors−Context Kernel Descriptors (CKD), which enhance the original KDES by embedding the spatial context into the descriptors. Context cues contained in the context kernel enforce some degree of spatial consistency, thus...... improving the robustness of CKD. For feature learning and reduction, we propose a novel codebook learning method, based on a Rényi quadratic entropy based mutual information measure called Cauchy-Schwarz Quadratic Mutual Information (CSQMI), to learn a compact and discriminative CKD codebook. Projecting...... as the information about the underlying labels of the CKD using CSQMI. Thus the resulting codebook and reduced CKD are discriminative. We verify the effectiveness of our method on several public image benchmark datasets such as YaleB, Caltech-101 and CIFAR-10, as well as a challenging chicken feet dataset of our own...
[GSH fermentation process modeling using entropy-criterion based RBF neural network model].
Tan, Zuoping; Wang, Shitong; Deng, Zhaohong; Du, Guocheng
2008-05-01
The prediction accuracy and generalization of GSH fermentation process modeling are often deteriorated by noise existing in the corresponding experimental data. In order to avoid this problem, we present a novel RBF neural network modeling approach based on entropy criterion. It considers the whole distribution structure of the training data set in the parameter learning process compared with the traditional MSE-criterion based parameter learning, and thus effectively avoids the weak generalization and over-learning. Then the proposed approach is applied to the GSH fermentation process modeling. Our results demonstrate that this proposed method has better prediction accuracy, generalization and robustness such that it offers a potential application merit for the GSH fermentation process modeling.
Nonuniform Sparse Data Clustering Cascade Algorithm Based on Dynamic Cumulative Entropy
Directory of Open Access Journals (Sweden)
Ning Li
2016-01-01
Full Text Available A small amount of prior knowledge and randomly chosen initial cluster centers have a direct impact on the accuracy of the performance of iterative clustering algorithm. In this paper we propose a new algorithm to compute initial cluster centers for k-means clustering and the best number of the clusters with little prior knowledge and optimize clustering result. It constructs the Euclidean distance control factor based on aggregation density sparse degree to select the initial cluster center of nonuniform sparse data and obtains initial data clusters by multidimensional diffusion density distribution. Multiobjective clustering approach based on dynamic cumulative entropy is adopted to optimize the initial data clusters and the best number of the clusters. The experimental results show that the newly proposed algorithm has good performance to obtain the initial cluster centers for the k-means algorithm and it effectively improves the clustering accuracy of nonuniform sparse data by about 5%.
Directory of Open Access Journals (Sweden)
Yuntao Zhao
2016-01-01
Full Text Available DDoS attacks can prevent legitimate users from accessing the service by consuming resource of the target nodes, whose availability of network and service is exposed to a significant threat. Therefore, DDoS traffic perception is the premise and foundation of the whole system security. In this paper the method of DDoS traffic perception for SOA network based on time united conditional entropy was proposed. According to many-to-one relationship mapping between the source IP address and destination IP addresses of DDoS attacks, traffic characteristics of services are analyzed based on conditional entropy. The algorithm is provided with perception ability of DDoS attacks on SOA services by introducing time dimension. Simulation results show that the novel method can realize DDoS traffic perception with analyzing abrupt variation of conditional entropy in time dimension.
Upper Bound Performance Estimation for Copper Based Broadband Access
DEFF Research Database (Denmark)
Jensen, Michael; Gutierrez Lopez, Jose Manuel
2012-01-01
of copper based access connections at a household level by using Geographical Information System data. This can be combined with different configurations of DSLAMs distributions, in order to calculate the required number of active equipment points to guarantee certain QoS levels. This method can be used...
Cryptographic protocol security analysis based on bounded constructing algorithm
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
An efficient approach to analyzing cryptographic protocols is to develop automatic analysis tools based on formal methods. However, the approach has encountered the high computational complexity problem due to reasons that participants of protocols are arbitrary, their message structures are complex and their executions are concurrent. We propose an efficient automatic verifying algorithm for analyzing cryptographic protocols based on the Cryptographic Protocol Algebra (CPA) model proposed recently, in which algebraic techniques are used to simplify the description of cryptographic protocols and their executions. Redundant states generated in the analysis processes are much reduced by introducing a new algebraic technique called Universal Polynomial Equation and the algorithm can be used to verify the correctness of protocols in the infinite states space. We have implemented an efficient automatic analysis tool for cryptographic protocols, called ACT-SPA, based on this algorithm, and used the tool to check more than 20 cryptographic protocols. The analysis results show that this tool is more efficient, and an attack instance not offered previously is checked by using this tool.
An Entropy-based gene selection method for cancer classification using microarray data
Directory of Open Access Journals (Sweden)
Krishnan Arun
2005-03-01
Full Text Available Abstract Background Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of non-redundant but relevant genes is difficult. The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. Results The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. A merit called normalized mutual information is employed to measure the relevance and the redundancy of the genes. In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. The algorithm was applied to three different data sets and the results obtained were compared to work done by others using the same data sets Conclusion This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. In addition, the feature set obtained is very compact, that is, the redundancy between genes is reduced to a large extent. This implies that classifiers can be built with a smaller subset of genes.
Nonsymmetric entropy and maximum nonsymmetric entropy principle
International Nuclear Information System (INIS)
Liu Chengshi
2009-01-01
Under the frame of a statistical model, the concept of nonsymmetric entropy which generalizes the concepts of Boltzmann's entropy and Shannon's entropy, is defined. Maximum nonsymmetric entropy principle is proved. Some important distribution laws such as power law, can be derived from this principle naturally. Especially, nonsymmetric entropy is more convenient than other entropy such as Tsallis's entropy in deriving power laws.
Assessment of sustainable urban transport development based on entropy and unascertained measure.
Li, Yancang; Yang, Jing; Shi, Huawang; Li, Yijie
2017-01-01
To find a more effective method for the assessment of sustainable urban transport development, the comprehensive assessment model of sustainable urban transport development was established based on the unascertained measure. On the basis of considering the factors influencing urban transport development, the comprehensive assessment indexes were selected, including urban economical development, transport demand, environment quality and energy consumption, and the assessment system of sustainable urban transport development was proposed. In view of different influencing factors of urban transport development, the index weight was calculated through the entropy weight coefficient method. Qualitative and quantitative analyses were conducted according to the actual condition. Then, the grade was obtained by using the credible degree recognition criterion from which the urban transport development level can be determined. Finally, a comprehensive assessment method for urban transport development was introduced. The application practice showed that the method can be used reasonably and effectively for the comprehensive assessment of urban transport development.
Permutation entropy analysis of financial time series based on Hill's diversity number
Zhang, Yali; Shang, Pengjian
2017-12-01
In this paper the permutation entropy based on Hill's diversity number (Nn,r) is introduced as a new way to assess the complexity of a complex dynamical system such as stock market. We test the performance of this method with simulated data. Results show that Nn,r with appropriate parameters is more sensitive to the change of system and describes the trends of complex systems clearly. In addition, we research the stock closing price series from different data that consist of six indices: three US stock indices and three Chinese stock indices during different periods, Nn,r can quantify the changes of complexity for stock market data. Moreover, we get richer information from Nn,r, and obtain some properties about the differences between the US and Chinese stock indices.
Analyzing the Performances of Automotive Companies Using Entropy Based MAUT and SAW Methods
Directory of Open Access Journals (Sweden)
Nuri Ömürbek
2016-06-01
Full Text Available In this study, performances of automotive companies traded on BİST (Istanbul Stock Exchange and also operated in our country have been compared with the multi-criteria decision making techniques. Data of the most important automotive companies operating in Turkey have been analyzed based on capital, stock certificate, marketing value, sales revenue, number of employees, net profit margin, current ratio, net profit/capital, net profit/sales and net sales/number of employees. Criteria applied on Performance measurement was gained operating reports of companies in 2014. Entropy method has been used to determine the weights of the criteria. Those weights have been used MAUT (Multi-Attribute Utility Theory and SAW (Simple Additive Weighting methods to rank automative companies’ performances The findings highlight that the same companies were in the first three places in both methods.
Bayesian Maximum Entropy Based Algorithm for Digital X-ray Mammogram Processing
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Radu Mutihac
2009-06-01
Full Text Available Basics of Bayesian statistics in inverse problems using the maximum entropy principle are summarized in connection with the restoration of positive, additive images from various types of data like X-ray digital mammograms. An efficient iterative algorithm for image restoration from large data sets based on the conjugate gradient method and Lagrange multipliers in nonlinear optimization of a specific potential function was developed. The point spread function of the imaging system was determined by numerical simulations of inhomogeneous breast-like tissue with microcalcification inclusions of various opacities. The processed digital and digitized mammograms resulted superior in comparison with their raw counterparts in terms of contrast, resolution, noise, and visibility of details.
Theoretical Bound of CRLB for Energy Efficient Technique of RSS-Based Factor Graph Geolocation
Kahar Aziz, Muhammad Reza; Heriansyah; Saputra, EfaMaydhona; Musa, Ardiansyah
2018-03-01
To support the increase of wireless geolocation development as the key of the technology in the future, this paper proposes theoretical bound derivation, i.e., Cramer Rao lower bound (CRLB) for energy efficient of received signal strength (RSS)-based factor graph wireless geolocation technique. The theoretical bound derivation is crucially important to evaluate whether the energy efficient technique of RSS-based factor graph wireless geolocation is effective as well as to open the opportunity to further innovation of the technique. The CRLB is derived in this paper by using the Fisher information matrix (FIM) of the main formula of the RSS-based factor graph geolocation technique, which is lied on the Jacobian matrix. The simulation result shows that the derived CRLB has the highest accuracy as a bound shown by its lowest root mean squared error (RMSE) curve compared to the RMSE curve of the RSS-based factor graph geolocation technique. Hence, the derived CRLB becomes the lower bound for the efficient technique of RSS-based factor graph wireless geolocation.
International Nuclear Information System (INIS)
De Nicola, Sergio; Fedele, Renato; Man'ko, Margarita A; Man'ko, Vladimir I
2007-01-01
The tomographic-probability description of quantum states is reviewed. The symplectic tomography of quantum states with continuous variables is studied. The symplectic entropy of the states with continuous variables is discussed and its relation to Shannon entropy and information is elucidated. The known entropic uncertainty relations of the probability distribution in position and momentum of a particle are extended and new uncertainty relations for symplectic entropy are obtained. The partial case of symplectic entropy, which is optical entropy of quantum states, is considered. The entropy associated to optical tomogram is shown to satisfy the new entropic uncertainty relation. The example of Gaussian states of harmonic oscillator is studied and the entropic uncertainty relations for optical tomograms of the Gaussian state are shown to minimize the uncertainty relation
A Review of Solid-Solution Models of High-Entropy Alloys Based on Ab Initio Calculations
Directory of Open Access Journals (Sweden)
Fuyang Tian
2017-11-01
Full Text Available Similar to the importance of XRD in experiments, ab initio calculations, as a powerful tool, have been applied to predict the new potential materials and investigate the intrinsic properties of materials in theory. As a typical solid-solution material, the large degree of uncertainty of high-entropy alloys (HEAs results in the difficulty of ab initio calculations application to HEAs. The present review focuses on the available ab initio based solid-solution models (virtual lattice approximation, coherent potential approximation, special quasirandom structure, similar local atomic environment, maximum-entropy method, and hybrid Monte Carlo/molecular dynamics and their applications and limits in single phase HEAs.
International Nuclear Information System (INIS)
Maes, Christian
2012-01-01
In contrast to the quite unique entropy concept useful for systems in (local) thermodynamic equilibrium, there is a variety of quite distinct nonequilibrium entropies, reflecting different physical points. We disentangle these entropies as they relate to heat, fluctuations, response, time asymmetry, variational principles, monotonicity, volume contraction or statistical forces. However, not all of those extensions yield state quantities as understood thermodynamically. At the end we sketch how aspects of dynamical activity can take over for obtaining an extended Clausius relation.
Han, Yongming; Long, Chang; Geng, Zhiqiang; Zhang, Keyu
2018-01-01
Environmental protection and carbon emission reduction play a crucial role in the sustainable development procedure. However, the environmental efficiency analysis and evaluation based on the traditional data envelopment analysis (DEA) cross model is subjective and inaccurate, because all elements in a column or a row of the cross evaluation matrix (CEM) in the traditional DEA cross model are given the same weight. Therefore, this paper proposes an improved environmental DEA cross model based on the information entropy to analyze and evaluate the carbon emission of industrial departments in China. The information entropy is applied to build the entropy distance based on the turbulence of the whole system, and calculate the weights in the CEM of the environmental DEA cross model in a dynamic way. The theoretical results show that the new weight constructed based on the information entropy is unique and optimal globally by using the Monte Carlo simulation. Finally, compared with the traditional environmental DEA and DEA cross model, the improved environmental DEA cross model has a better efficiency discrimination ability based on the data of industrial departments in China. Moreover, the proposed model can obtain the potential of carbon emission reduction of industrial departments to improve the energy efficiency. Copyright © 2017 Elsevier Ltd. All rights reserved.
DEFF Research Database (Denmark)
Olsen, Lars Rønn; Zhang, Guang Lan; Keskin, Derin B.
2011-01-01
residues. The block entropy analysis provides broad coverage of variant antigens. We applied the block entropy analysis method to the proteomes of the four serotypes of dengue virus (DENV) and found 1,551 blocks of 9-mer peptides, which cover 99% of available sequences with five or fewer unique peptides...
Membrane-based ethylene/ethane separation: The upper bound and beyond
Rungta, Meha
2013-08-02
Ethylene/ethane separation via cryogenic distillation is extremely energy-intensive, and membrane separation may provide an attractive alternative. In this paper, ethylene/ethane separation performance using polymeric membranes is summarized, and an experimental ethylene/ethane polymeric upper bound based on literature data is presented. A theoretical prediction of the ethylene/ethane upper bound is also presented, and shows good agreement with the experimental upper bound. Further, two ways to overcome the ethylene/ethane upper bound, based on increasing the sorption or diffusion selectivity, is also discussed, and a review on advanced membrane types such as facilitated transport membranes, zeolite and metal organic framework based membranes, and carbon molecular sieve membranes is presented. Of these, carbon membranes have shown the potential to surpass the polymeric ethylene/ethane upper bound performance. Furthermore, a convenient, potentially scalable method for tailoring the performance of carbon membranes for ethylene/ethane separation based on tuning the pyrolysis conditions has also been demonstrated. © 2013 American Institute of Chemical Engineers.
Directory of Open Access Journals (Sweden)
Lv Xiaogui
2006-11-01
Full Text Available Abstract Background There are many differences between healthy tissue and growing tumor tissue, including metabolic, structural and thermodynamic differences. Both structural and thermodynamic differences can be used to follow the entropy differences in cancerous and normal tissue. Entropy production is a bilinear form of the rates of irreversible processes and the corresponding "generalized forces". Entropy production due to various dissipation mechanisms based on temperature differences, chemical potential gradient, chemical affinity, viscous stress and exerted force is a promising tool for calculations relating to potential targets for tumor isolation and demarcation. Methods The relative importance of five forms of entropy production was assessed through mathematical estimation. Using our mathematical model we demonstrated that the rate of entropy production by a cancerous cell is always higher than that of a healthy cell apart from the case of the application of external energy. Different rates of entropy production by two kinds of cells influence the direction of entropy flow between the cells. Entropy flow from a cancerous cell to a healthy cell transfers information regarding the cancerous cell and propagates its invasive action to the healthy tissues. To change the direction of entropy flow, in addition to designing certain biochemical pathways to reduce the rate of entropy production by cancerous cells, we suggest supplying external energy to the tumor area, changing the relative rate of entropy production by the two kinds of cells and leading to a higher entropy accumulation in the surrounding normal cells than in the tumorous cells. Conclusion Through the use of mathematical models it was quantitatively demonstrated that when no external force field is applied, the rate of entropy production of cancerous cells is always higher than that of healthy cells. However, when the external energy of square wave electric pulses is applied to
International Nuclear Information System (INIS)
Cao, Guangxi; Zhang, Qi; Li, Qingchen
2017-01-01
Highlights: • Mutual information is used as the edge weights of nodes instead of PCC, which overcomes the shortcomings of linear correlation functions. • SGD turns into a new cluster center and gradually becomes a point connecting the Asian and European clusters during and after the US sub-prime crisis. • Liang's entropy theory, which has not been adopted before in the global foreign exchange market, is considered. - Abstract: The foreign exchange (FX) market is a typical complex dynamic system under the background of exchange rate marketization reform and is an important part of the financial market. This study aims to generate an international FX network based on complex network theory. This study employs the mutual information method to judge the nonlinear characteristics of 54 major currencies in international FX markets. Through this method, we find that the FX network possesses a small average path length and a large clustering coefficient under different thresholds and that it exhibits small-world characteristics as a whole. Results show that the relationship between FX rates is close. Volatility can quickly transfer in the whole market, and the FX volatility of influential individual states transfers at a fast pace and a large scale. The period from July 21, 2005 to March 31, 2015 is subdivided into three sub-periods (i.e., before, during, and after the US sub-prime crisis) to analyze the topology evolution of FX markets using the maximum spanning tree approach. Results show that the USD gradually lost its core position, EUR remained a stable center, and the center of the Asian cluster became unstable. Liang's entropy theory is used to analyze the causal relationship between the four large clusters of the world.
Mahler, Jeffrey; Pokorny, Florian T.; McCarthy, Zoe; van der Stappen, A.F.; Goldberg, Ken
Caging grasps are valuable as they can be robust to bounded variations in object shape and pose, do not depend on friction, and enable transport of an object without full immobilization. Complete caging of an object is useful but may not be necessary in cases where forces such as gravity are
Bounded distance decoding of linear error-correcting codes with Gröbner bases
Bulygin, S.; Pellikaan, G.R.
2009-01-01
The problem of bounded distance decoding of arbitrary linear codes using Gröbner bases is addressed. A new method is proposed, which is based on reducing an initial decoding problem to solving a certain system of polynomial equations over a finite field. The peculiarity of this system is that, when
On the Conditional Entropy of Wireless Networks
DEFF Research Database (Denmark)
Coon, Justin P.; Badiu, Mihai Alin; Gündüz, Deniz
2018-01-01
The characterization of topological uncertainty in wireless networks using the formalism of graph entropy has received interest in the spatial networks community. In this paper, we develop lower bounds on the entropy of a wireless network by conditioning on potential network observables. Two...... approaches are considered: 1) conditioning on subgraphs, and 2) conditioning on node positions. The first approach is shown to yield a relatively tight bound on the network entropy. The second yields a loose bound, in general, but it provides insight into the dependence between node positions (modelled using...
Shannon's information is not entropy
International Nuclear Information System (INIS)
Schiffer, M.
1990-01-01
In this letter we clear up the long-standing misidentification of Shannon's Information with Entropy. We show that Information, in contrast to Entropy, is not invariant under unitary transformations and that these quantities are only equivalent for representations consisting of Hamiltonian eigenstates. We illustrate this fact through a toy system consisting of a harmonic oscillator in a coherent state. It is further proved that the representations which maximize the information are those which are energy-eigenstates. This fact sets the entropy as an upper bound for Shannon's Information. (author)
Properties of Fuzzy Entropy Based on the Shape Change of Membership Function
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Modification of a fuzzy partition often leads to the change of fuzziness of a fuzzy system. Researches on the change of fuzzy entropy of a fuzzy set, responding to shape alteration of membership function, therefore, play a significant role in analysis of the change of fuzziness of a fuzzy system because a fuzzy partition consists of a set of fuzzy sets which satisfy some special constraints. This paper has shown several results about entropy changes of a fuzzy set. First, the entropies of two same type of fuzzy sets have a constant proportional relationship which depends on the ratio of the sizes of their support intervals. Second, as for Triangular Fuzzy Numbers (TFNs), the entropies of any two TFNs which can not be always the same type, also,have a constant proportional relationship which depends on the ratio of the sizes of their support intervals. Hence, any two TFNs with the same sizes of support intervals have the same entropies. Third, concerning two Triangular Fuzzy Sets (TFSs) with same sizes of support intervals and different heights, the relationship of their entropies lies on their height.Finally, we point it out a mistake that Chen's assertion that the entropy of resultant fuzzy set of elevation operation is directly proportional to that of the original one while elevation factor just acts as a proportional factor. These results should contribute to the analysis and design of a fuzzy system.
Wavelet Entropy-Based Traction Inverter Open Switch Fault Diagnosis in High-Speed Railways
Directory of Open Access Journals (Sweden)
Keting Hu
2016-03-01
Full Text Available In this paper, a diagnosis plan is proposed to settle the detection and isolation problem of open switch faults in high-speed railway traction system traction inverters. Five entropy forms are discussed and compared with the traditional fault detection methods, namely, discrete wavelet transform and discrete wavelet packet transform. The traditional fault detection methods cannot efficiently detect the open switch faults in traction inverters because of the low resolution or the sudden change of the current. The performances of Wavelet Packet Energy Shannon Entropy (WPESE, Wavelet Packet Energy Tsallis Entropy (WPETE with different non-extensive parameters, Wavelet Packet Energy Shannon Entropy with a specific sub-band (WPESE3,6, Empirical Mode Decomposition Shannon Entropy (EMDESE, and Empirical Mode Decomposition Tsallis Entropy (EMDETE with non-extensive parameters in detecting the open switch fault are evaluated by the evaluation parameter. Comparison experiments are carried out to select the best entropy form for the traction inverter open switch fault detection. In addition, the DC component is adopted to isolate the failure Isolated Gate Bipolar Transistor (IGBT. The simulation experiments show that the proposed plan can diagnose single and simultaneous open switch faults correctly and timely.
Bound on viscosity and the generalized second law of thermodynamics
International Nuclear Information System (INIS)
Fouxon, Itzhak; Betschart, Gerold; Bekenstein, Jacob D.
2008-01-01
We describe a new paradox for ideal fluids. It arises in the accretion of an ideal fluid onto a black hole, where, under suitable boundary conditions, the flow can violate the generalized second law of thermodynamics. The paradox indicates that there is in fact a lower bound to the correlation length of any real fluid, the value of which is determined by the thermodynamic properties of that fluid. We observe that the universal bound on entropy, itself suggested by the generalized second law, puts a lower bound on the correlation length of any fluid in terms of its specific entropy. With the help of a new, efficient estimate for the viscosity of liquids, we argue that this also means that viscosity is bounded from below in a way reminiscent of the conjectured Kovtun-Son-Starinets lower bound on the ratio of viscosity to entropy density. We conclude that much light may be shed on the Kovtun-Son-Starinets bound by suitable arguments based on the generalized second law
Entropy of Bit-Stuffing-Induced Measures for Two-Dimensional Checkerboard Constraints
DEFF Research Database (Denmark)
Forchhammer, Søren; Vaarby, Torben Strange
2007-01-01
A modified bit-stuffing scheme for two-dimensional (2-D) checkerboard constraints is introduced. The entropy of the scheme is determined based on a probability measure defined by the modified bit-stuffing. Entropy results of the scheme are given for 2-D constraints on a binary alphabet....... The constraints considered are 2-D RLL (d, infinity) for d = 2, 3 and 4 as well as for the constraint with a minimum 1-norm distance of 3 between Is. For these results the entropy is within 1-2% of an upper bound on the capacity for the constraint. As a variation of the scheme, periodic merging arrays are also...
Gravel Image Segmentation in Noisy Background Based on Partial Entropy Method
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult o segment gravel objects. In this paper, we develop a partial entropy method and succeed to realize gravel objects segmentation. We give entropy principles and fur calculation methods. Moreover, we use minimum entropy error automaticly to select a threshold to segment image. We introduce the filter method using mathematical morphology. The segment experiments are performed by using different window dimensions for a group of gravel image and demonstrates that this method has high segmentation rate and low noise sensitivity.
Entropy equilibrium equation and dynamic entropy production in environment liquid
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
The entropy equilibrium equation is the basis of the nonequilibrium state thermodynamics. But the internal energy implies the kinetic energy of the fluid micelle relative to mass center in the classical entropy equilibrium equation at present. This internal energy is not the mean kinetic energy of molecular movement in thermodynamics. Here a modified entropy equilibrium equation is deduced, based on the concept that the internal energy is just the mean kinetic energy of the molecular movement. A dynamic entropy production is introduced into the entropy equilibrium equation to describe the dynamic process distinctly. This modified entropy equilibrium equation can describe not only the entropy variation of the irreversible processes but also the reversible processes in a thermodynamic system. It is more reasonable and suitable for wider applications.
Huang, Feimin; Li, Tianhong; Yu, Huimin; Yuan, Difan
2018-06-01
We are concerned with the global existence and large time behavior of entropy solutions to the one-dimensional unipolar hydrodynamic model for semiconductors in the form of Euler-Poisson equations in a bounded interval. In this paper, we first prove the global existence of entropy solution by vanishing viscosity and compensated compactness framework. In particular, the solutions are uniformly bounded with respect to space and time variables by introducing modified Riemann invariants and the theory of invariant region. Based on the uniform estimates of density, we further show that the entropy solution converges to the corresponding unique stationary solution exponentially in time. No any smallness condition is assumed on the initial data and doping profile. Moreover, the novelty in this paper is about the unform bound with respect to time for the weak solutions of the isentropic Euler-Poisson system.
An entropy-based improved k-top scoring pairs (TSP) method for ...
African Journals Online (AJOL)
DR. NJ TONUKARI
2012-06-05
Jun 5, 2012 ... Key words: Cancer classification, gene expression, k-TSP, information entropy, gene selection. INTRODUCTION ..... The 88 kDa precursor protein, progranulin, is also ... TCF3 is in acute myeloid leukemia pathway, so it is.
Tight Bounds for Beacon-Based Coverage in Simple Rectilinear Polygons
Bae, Sang Won; Shin, Chan-Su; Vigneron, Antoine E.
2016-01-01
We establish tight bounds for beacon-based coverage problems. In particular, we show that $$\\lfloor \\frac{n}{6} \\rfloor $$⌊n6⌋ beacons are always sufficient and sometimes necessary to cover a simple rectilinear polygon P with n vertices. When P is monotone and rectilinear, we prove that this bound becomes $$\\lfloor \\frac{n+4}{8} \\rfloor $$⌊n+48⌋. We also present an optimal linear-time algorithm for computing the beacon kernel of P.
Tight Bounds for Beacon-Based Coverage in Simple Rectilinear Polygons
Bae, Sang Won
2016-03-21
We establish tight bounds for beacon-based coverage problems. In particular, we show that $$\\\\lfloor \\\\frac{n}{6} \\ floor $$⌊n6⌋ beacons are always sufficient and sometimes necessary to cover a simple rectilinear polygon P with n vertices. When P is monotone and rectilinear, we prove that this bound becomes $$\\\\lfloor \\\\frac{n+4}{8} \\ floor $$⌊n+48⌋. We also present an optimal linear-time algorithm for computing the beacon kernel of P.
Manufacturing lines under surplus-based control : multiple products and bounded buffers
Starkov, K.; Pogromskiy, A.Y.; Adan, I.J.B.F.
2015-01-01
Challenged by the scheduling complexity for production flow processes in industrial facilities, we study the performance of multi-product producing lines. We analyse the performance of multi-product lines that consist a number of machines and bounded buffers with preselected base stock levels. It is
Proof of the insecurity of quantum secret sharing based on the Smolin bound entangled states
International Nuclear Information System (INIS)
Ya-Fei, Yu; Zhi-Ming, Zhang
2009-01-01
This paper reconsiders carefully the possibility of using the Smolin bound entangled states as the carrier for sharing quantum secret. It finds that the process of quantum secret sharing based on Smolin states has insecurity though the Smolin state was reported to violate maximally the two-setting Bell-inequality. The general proof is given. (general)
Lower and Upper Bounds in Zone Based Abstractions of Timed Automata
DEFF Research Database (Denmark)
Behrmann, Gerd; Bouyer, Patricia; Larsen, Kim Guldstrand
2004-01-01
Timed automata have an infinite semantics. For verification purposes, one usually uses zone based abstractions w.r.t. the maximal constants to which clocks of the timed automaton are compared. We show that by distinguishing maximal lower and upper bounds, significantly coarser abstractions can...... dramatically increases the scalability of the real-time model checker Uppaal....
Lower and Upper Bounds in Zone-Based Abstractions of Timed Automata
DEFF Research Database (Denmark)
Behrmann, Gerd; Bouyer, Patricia; Larsen, Kim Guldstrand
2005-01-01
The semantics of timed automata is defined using an infinite-state transition system. For verification purposes, one usually uses zone based abstractions w.r.t. the maximal constants to which clocks of the timed automaton are compared. We show that by distinguishing maximal lower and upper bounds...
Design of high entropy alloys based on the experience from commercial superalloys
Wang, Z.; Huang, Y.; Wang, J.; Liu, C. T.
2015-01-01
High entropy alloys (HEAs) have been drawing increasing attention recently and gratifying results have been obtained. However, the existing metallurgic rules of HEAs could not provide specific information of selecting candidate alloys for structural applications. Our brief survey reveals that many commercial superalloys have medium and even to high configurational entropies. The experience of commercial superalloys provides a clue for helping us in the development of HEAs for structural applications.
Predicting the Outcome of NBA Playoffs Based on the Maximum Entropy Principle
Ge Cheng; Zhenyu Zhang; Moses Ntanda Kyebambe; Nasser Kimbugwe
2016-01-01
Predicting the outcome of National Basketball Association (NBA) matches poses a challenging problem of interest to the research community as well as the general public. In this article, we formalize the problem of predicting NBA game results as a classification problem and apply the principle of Maximum Entropy to construct an NBA Maximum Entropy (NBAME) model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs using the model. Our results reveal that...
International Nuclear Information System (INIS)
Garcia-Morales, Vladimir; Pellicer, Julio; Manzanares, Jose A.
2008-01-01
We present some novel thermodynamic ideas based on the Maupertuis principle. By considering Hamiltonians written in terms of appropriate action-angle variables we show that thermal states can be characterized by the action variables and by their evolution in time when the system is nonintegrable. We propose dynamical definitions for the equilibrium temperature and entropy as well as an expression for the nonequilibrium entropy valid for isolated systems with many degrees of freedom. This entropy is shown to increase in the relaxation to equilibrium of macroscopic systems with short-range interactions, which constitutes a dynamical justification of the Second Law of Thermodynamics. Several examples are worked out to show that this formalism yields the right microcanonical (equilibrium) quantities. The relevance of this approach to nonequilibrium situations is illustrated with an application to a network of coupled oscillators (Kuramoto model). We provide an expression for the entropy production in this system finding that its positive value is directly related to dissipation at the steady state in attaining order through synchronization
Directory of Open Access Journals (Sweden)
Frederico Sassoli Fazan
2018-01-01
Full Text Available Quantifying complexity from heart rate variability (HRV series is a challenging task, and multiscale entropy (MSE, along with its variants, has been demonstrated to be one of the most robust approaches to achieve this goal. Although physical training is known to be beneficial, there is little information about the long-term complexity changes induced by the physical conditioning. The present study aimed to quantify the changes in physiological complexity elicited by physical training through multiscale entropy-based complexity measurements. Rats were subject to a protocol of medium intensity training ( n = 13 or a sedentary protocol ( n = 12 . One-hour HRV series were obtained from all conscious rats five days after the experimental protocol. We estimated MSE, multiscale dispersion entropy (MDE and multiscale SDiff q from HRV series. Multiscale SDiff q is a recent approach that accounts for entropy differences between a given time series and its shuffled dynamics. From SDiff q , three attributes (q-attributes were derived, namely SDiff q m a x , q m a x and q z e r o . MSE, MDE and multiscale q-attributes presented similar profiles, except for SDiff q m a x . q m a x showed significant differences between trained and sedentary groups on Time Scales 6 to 20. Results suggest that physical training increases the system complexity and that multiscale q-attributes provide valuable information about the physiological complexity.
Directory of Open Access Journals (Sweden)
Jun Liu
2017-01-01
Full Text Available Under the interval-valued hesitant fuzzy information environment, we investigate a multiattribute group decision making (MAGDM method with continuous entropy weights and improved Hamacher information aggregation operators. Firstly, we introduce the axiomatic definition of entropy for interval-valued hesitant fuzzy elements (IVHFEs and construct a continuous entropy formula on the basis of the continuous ordered weighted averaging (COWA operator. Then, based on the Hamacher t-norm and t-conorm, the adjusted operational laws for IVHFEs are defined. In order to aggregate interval-valued hesitant fuzzy information, some new improved interval-valued hesitant fuzzy Hamacher aggregation operators are investigated, including the improved interval-valued hesitant fuzzy Hamacher ordered weighted averaging (I-IVHFHOWA operator and the improved interval-valued hesitant fuzzy Hamacher ordered weighted geometric (I-IVHFHOWG operator, the desirable properties of which are discussed. In addition, the relationship among these proposed operators is analyzed in detail. Applying the continuous entropy and the proposed operators, an approach to MAGDM is developed. Finally, a numerical example for emergency operating center (EOC selection is provided, and comparative analyses with existing methods are performed to demonstrate that the proposed approach is both valid and practical to deal with group decision making problems.
International Nuclear Information System (INIS)
Li, Guanchen; Al-Abbasi, Omar; Von Spakovsky, Michael R
2014-01-01
This paper outlines an atomistic-level framework for modeling the non-equilibrium behavior of chemically reactive systems. The framework called steepest- entropy-ascent quantum thermodynamics (SEA-QT) is based on the paradigm of intrinsic quantum thermodynamic (IQT), which is a theory that unifies quantum mechanics and thermodynamics into a single discipline with wide applications to the study of non-equilibrium phenomena at the atomistic level. SEA-QT is a novel approach for describing the state of chemically reactive systems as well as the kinetic and dynamic features of the reaction process without any assumptions of near-equilibrium states or weak-interactions with a reservoir or bath. Entropy generation is the basis of the dissipation which takes place internal to the system and is, thus, the driving force of the chemical reaction(s). The SEA-QT non-equilibrium model is able to provide detailed information during the reaction process, providing a picture of the changes occurring in key thermodynamic properties (e.g., the instantaneous species concentrations, entropy and entropy generation, reaction coordinate, chemical affinities, reaction rate, etc). As an illustration, the SEA-QT framework is applied to an atomistic-level chemically reactive system governed by the reaction mechanism F + H 2 ↔ FH + H
Entropy in bimolecular simulations: A comprehensive review of atomic fluctuations-based methods.
Kassem, Summer; Ahmed, Marawan; El-Sheikh, Salah; Barakat, Khaled H
2015-11-01
Entropy of binding constitutes a major, and in many cases a detrimental, component of the binding affinity in biomolecular interactions. While the enthalpic part of the binding free energy is easier to calculate, estimating the entropy of binding is further more complicated. A precise evaluation of entropy requires a comprehensive exploration of the complete phase space of the interacting entities. As this task is extremely hard to accomplish in the context of conventional molecular simulations, calculating entropy has involved many approximations. Most of these golden standard methods focused on developing a reliable estimation of the conformational part of the entropy. Here, we review these methods with a particular emphasis on the different techniques that extract entropy from atomic fluctuations. The theoretical formalisms behind each method is explained highlighting its strengths as well as its limitations, followed by a description of a number of case studies for each method. We hope that this brief, yet comprehensive, review provides a useful tool to understand these methods and realize the practical issues that may arise in such calculations. Copyright © 2015 Elsevier Inc. All rights reserved.
Hosseini, Marjan; Kerachian, Reza
2017-09-01
This paper presents a new methodology for analyzing the spatiotemporal variability of water table levels and redesigning a groundwater level monitoring network (GLMN) using the Bayesian Maximum Entropy (BME) technique and a multi-criteria decision-making approach based on ordered weighted averaging (OWA). The spatial sampling is determined using a hexagonal gridding pattern and a new method, which is proposed to assign a removal priority number to each pre-existing station. To design temporal sampling, a new approach is also applied to consider uncertainty caused by lack of information. In this approach, different time lag values are tested by regarding another source of information, which is simulation result of a numerical groundwater flow model. Furthermore, to incorporate the existing uncertainties in available monitoring data, the flexibility of the BME interpolation technique is taken into account in applying soft data and improving the accuracy of the calculations. To examine the methodology, it is applied to the Dehgolan plain in northwestern Iran. Based on the results, a configuration of 33 monitoring stations for a regular hexagonal grid of side length 3600 m is proposed, in which the time lag between samples is equal to 5 weeks. Since the variance estimation errors of the BME method are almost identical for redesigned and existing networks, the redesigned monitoring network is more cost-effective and efficient than the existing monitoring network with 52 stations and monthly sampling frequency.
An entropy-variables-based formulation of residual distribution schemes for non-equilibrium flows
Garicano-Mena, Jesús; Lani, Andrea; Degrez, Gérard
2018-06-01
In this paper we present an extension of Residual Distribution techniques for the simulation of compressible flows in non-equilibrium conditions. The latter are modeled by means of a state-of-the-art multi-species and two-temperature model. An entropy-based variable transformation that symmetrizes the projected advective Jacobian for such a thermophysical model is introduced. Moreover, the transformed advection Jacobian matrix presents a block diagonal structure, with mass-species and electronic-vibrational energy being completely decoupled from the momentum and total energy sub-system. The advantageous structure of the transformed advective Jacobian can be exploited by contour-integration-based Residual Distribution techniques: established schemes that operate on dense matrices can be substituted by the same scheme operating on the momentum-energy subsystem matrix and repeated application of scalar scheme to the mass-species and electronic-vibrational energy terms. Finally, the performance gain of the symmetrizing-variables formulation is quantified on a selection of representative testcases, ranging from subsonic to hypersonic, in inviscid or viscous conditions.
Wu, Jingjing; Wu, Xinming; Li, Pengfei; Li, Nan; Mao, Xiaomei; Chai, Lihe
2017-04-01
Meridian system is not only the basis of traditional Chinese medicine (TCM) method (e.g. acupuncture, massage), but also the core of TCM's basic theory. This paper has introduced a new informational perspective to understand the reality and the holographic field of meridian. Based on maximum information entropy principle (MIEP), a dynamic equation for the holographic field has been deduced, which reflects the evolutionary characteristics of meridian. By using self-organizing artificial neural network as algorithm, the evolutionary dynamic equation of the holographic field can be resolved to assess properties of meridians and clinically diagnose the health characteristics of patients. Finally, through some cases from clinical patients (e.g. a 30-year-old male patient, an apoplectic patient, an epilepsy patient), we use this model to assess the evolutionary properties of meridians. It is proved that this model not only has significant implications in revealing the essence of meridian in TCM, but also may play a guiding role in clinical assessment of patients based on the holographic field of meridians.
Transportation Mode Detection Based on Permutation Entropy and Extreme Learning Machine
Directory of Open Access Journals (Sweden)
Lei Zhang
2015-01-01
Full Text Available With the increasing prevalence of GPS devices and mobile phones, transportation mode detection based on GPS data has been a hot topic in GPS trajectory data analysis. Transportation modes such as walking, driving, bus, and taxi denote an important characteristic of the mobile user. Longitude, latitude, speed, acceleration, and direction are usually used as features in transportation mode detection. In this paper, first, we explore the possibility of using Permutation Entropy (PE of speed, a measure of complexity and uncertainty of GPS trajectory segment, as a feature for transportation mode detection. Second, we employ Extreme Learning Machine (ELM to distinguish GPS trajectory segments of different transportation. Finally, to evaluate the performance of the proposed method, we make experiments on GeoLife dataset. Experiments results show that we can get more than 50% accuracy when only using PE as a feature to characterize trajectory sequence. PE can indeed be effectively used to detect transportation mode from GPS trajectory. The proposed method has much better accuracy and faster running time than the methods based on the other features and SVM classifier.
Fuzzy Shannon Entropy: A Hybrid GIS-Based Landslide Susceptibility Mapping Method
Directory of Open Access Journals (Sweden)
Majid Shadman Roodposhti
2016-09-01
Full Text Available Assessing Landslide Susceptibility Mapping (LSM contributes to reducing the risk of living with landslides. Handling the vagueness associated with LSM is a challenging task. Here we show the application of hybrid GIS-based LSM. The hybrid approach embraces fuzzy membership functions (FMFs in combination with Shannon entropy, a well-known information theory-based method. Nine landslide-related criteria, along with an inventory of landslides containing 108 recent and historic landslide points, are used to prepare a susceptibility map. A random split into training (≈70% and testing (≈30% samples are used for training and validation of the LSM model. The study area—Izeh—is located in the Khuzestan province of Iran, a highly susceptible landslide zone. The performance of the hybrid method is evaluated using receiver operating characteristics (ROC curves in combination with area under the curve (AUC. The performance of the proposed hybrid method with AUC of 0.934 is superior to multi-criteria evaluation approaches using a subjective scheme in this research in comparison with a previous study using the same dataset through extended fuzzy multi-criteria evaluation with AUC value of 0.894, and was built on the basis of decision makers’ evaluation in the same study area.
Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.
2011-06-01
For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.
Sze, Vivienne; Marpe, Detlev
2014-01-01
Context-Based Adaptive Binary Arithmetic Coding (CABAC) is a method of entropy coding first introduced in H.264/AVC and now used in the latest High Efficiency Video Coding (HEVC) standard. While it provides high coding efficiency, the data dependencies in H.264/AVC CABAC make it challenging to parallelize and thus limit its throughput. Accordingly, during the standardization of entropy coding for HEVC, both aspects of coding efficiency and throughput were considered. This chapter describes th...
Manfredi; Feix
2000-10-01
The properties of an alternative definition of quantum entropy, based on Wigner functions, are discussed. Such a definition emerges naturally from the Wigner representation of quantum mechanics, and can easily quantify the amount of entanglement of a quantum state. It is shown that smoothing of the Wigner function induces an increase in entropy. This fact is used to derive some simple rules to construct positive-definite probability distributions which are also admissible Wigner functions.
Manfredi, G.; Feix, M. R.
2002-01-01
The properties of an alternative definition of quantum entropy, based on Wigner functions, are discussed. Such definition emerges naturally from the Wigner representation of quantum mechanics, and can easily quantify the amount of entanglement of a quantum state. It is shown that smoothing of the Wigner function induces an increase in entropy. This fact is used to derive some simple rules to construct positive definite probability distributions which are also admissible Wigner functions
Gulamsarwar, Syazwani; Salleh, Zabidin
2017-08-01
The purpose of this paper is to generalize the notions of Adler's topological entropy along with their several fundamental properties. A function f : X → Y is said to be R-map if f-1 (V) is regular open in X for every regular open set V in Y. Thus, we initiated a notion of topological nearly entropy for topological R-dynamical systems which is based on nearly compact relative to the space by using R-map.
International Nuclear Information System (INIS)
Wu Shuang-Shuang; Wu Zhi-Hai; Peng Li; Xie Lin-Bo
2017-01-01
This paper investigates asymptotic bounded consensus tracking (ABCT) of double-integrator multi-agent systems (MASs) with an asymptotically-unbounded-acceleration and bounded-jerk target (AUABJT) available to partial agents based on sampled-data without velocity measurements. A sampled-data consensus tracking protocol (CTP) without velocity measurements is proposed to guarantee that double-integrator MASs track an AUABJT available to only partial agents. The eigenvalue analysis method together with the augmented matrix method is used to obtain the necessary and sufficient conditions for ABCT. A numerical example is provided to illustrate the effectiveness of theoretical results. (paper)
Bounding species distribution models
Directory of Open Access Journals (Sweden)
Thomas J. STOHLGREN, Catherine S. JARNEVICH, Wayne E. ESAIAS,Jeffrey T. MORISETTE
2011-10-01
Full Text Available Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for “clamping” model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART and maximum entropy (Maxent models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5: 642–647, 2011].
Bounding Species Distribution Models
Stohlgren, Thomas J.; Jarnevich, Cahterine S.; Morisette, Jeffrey T.; Esaias, Wayne E.
2011-01-01
Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS) might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for "clamping" model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART) and maximum entropy (Maxent) models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5): 642-647, 2011].
On the Conditional Entropy of Wireless Networks
DEFF Research Database (Denmark)
Coon, Justin P.; Badiu, Mihai Alin; Gündüz, Deniz
2018-01-01
The characterization of topological uncertainty in wireless networks using the formalism of graph entropy has received interest in the spatial networks community. In this paper, we develop lower bounds on the entropy of a wireless network by conditioning on potential network observables. Two appr...... a homogeneous binomial point process in this work) and the network topology....
Directory of Open Access Journals (Sweden)
Rong Jiang
2015-04-01
Full Text Available Complexity is an important factor throughout the software life cycle. It is increasingly difficult to guarantee software quality, cost and development progress with the increase in complexity. Excessive complexity is one of the main reasons for the failure of software projects, so effective recognition, measurement and control of complexity becomes the key of project management. At first, this paper analyzes the current research situation of software complexity systematically and points out existing problems in current research. Then, it proposes a WSR framework of software complexity, which divides the complexity of software into three levels of Wuli (WL, Shili (SL and Renli (RL, so that the staff in different roles may have a better understanding of complexity. Man is the main source of complexity, but the current research focuses on WL complexity, and the research of RL complexity is extremely scarce, so this paper emphasizes the research of RL complexity of software projects. This paper not only analyzes the composing factors of RL complexity, but also provides the definition of RL complexity. Moreover, it puts forward a quantitative measurement method of the complexity of personnel organization hierarchy and the complexity of personnel communication information based on information entropy first and analyzes and validates the scientificity and rationality of this measurement method through a large number of cases.
Yan, Zhi Gang; Li, Jun Qing
2017-12-01
The areas of the habitat and bamboo forest, and the size of the giant panda wild population have greatly increased, while habitat fragmentation and local population isolation have also intensified in recent years. Accurate evaluation of ecosystem status of the panda in the giant panda distribution area is important for giant panda conservation. The ecosystems of the distribution area and six mountain ranges were subdivided into habitat and population subsystems based on the hie-rarchical system theory. Using the panda distribution area as the study area and the three national surveys as the time node, the evolution laws of ecosystems were studied using the entropy method, coefficient of variation, and correlation analysis. We found that with continuous improvement, some differences existed in the evolution and present situation of the ecosystems of six mountain ranges could be divided into three groups. Ecosystems classified into the same group showed many commonalities, and difference between the groups was considerable. Problems of habitat fragmentation and local population isolation became more serious, resulting in ecosystem degradation. Individuali-zed ecological protection measures should be formulated and implemented in accordance with the conditions in each mountain system to achieve the best results.
Directory of Open Access Journals (Sweden)
Jinkyu Kim
Full Text Available The assessment of information transfer in the global economic network helps to understand the current environment and the outlook of an economy. Most approaches on global networks extract information transfer based mainly on a single variable. This paper establishes an entirely new bioinformatics-inspired approach to integrating information transfer derived from multiple variables and develops an international economic network accordingly. In the proposed methodology, we first construct the transfer entropies (TEs between various intra- and inter-country pairs of economic time series variables, test their significances, and then use a weighted sum approach to aggregate information captured in each TE. Through a simulation study, the new method is shown to deliver better information integration compared to existing integration methods in that it can be applied even when intra-country variables are correlated. Empirical investigation with the real world data reveals that Western countries are more influential in the global economic network and that Japan has become less influential following the Asian currency crisis.
Robot Evaluation and Selection with Entropy-Based Combination Weighting and Cloud TODIM Approach
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Jing-Jing Wang
2018-05-01
Full Text Available Nowadays robots have been commonly adopted in various manufacturing industries to improve product quality and productivity. The selection of the best robot to suit a specific production setting is a difficult decision making task for manufacturers because of the increase in complexity and number of robot systems. In this paper, we explore two key issues of robot evaluation and selection: the representation of decision makers’ diversified assessments and the determination of the ranking of available robots. Specifically, a decision support model which utilizes cloud model and TODIM (an acronym in Portuguese of interactive and multiple criteria decision making method is developed for the purpose of handling robot selection problems with hesitant linguistic information. Besides, we use an entropy-based combination weighting technique to estimate the weights of evaluation criteria. Finally, we illustrate the proposed cloud TODIM approach with a robot selection example for an automobile manufacturer, and further validate its effectiveness and benefits via a comparative analysis. The results show that the proposed robot selection model has some unique advantages, which is more realistic and flexible for robot selection under a complex and uncertain environment.
Instability risk assessment of construction waste pile slope based on fuzzy entropy
Ma, Yong; Xing, Huige; Yang, Mao; Nie, Tingting
2018-05-01
Considering the nature and characteristics of construction waste piles, this paper analyzed the factors affecting the stability of the slope of construction waste piles, and established the system of the assessment indexes for the slope failure risks of construction waste piles. Based on the basic principles and methods of fuzzy mathematics, the factor set and the remark set were established. The membership grade of continuous factor indexes is determined using the "ridge row distribution" function, while that for the discrete factor indexes was determined by the Delphi Method. For the weight of factors, the subjective weight was determined by the Analytic Hierarchy Process (AHP) and objective weight by the entropy weight method. And the distance function was introduced to determine the combination coefficient. This paper established a fuzzy comprehensive assessment model of slope failure risks of construction waste piles, and assessed pile slopes in the two dimensions of hazard and vulnerability. The root mean square of the hazard assessment result and vulnerability assessment result was the final assessment result. The paper then used a certain construction waste pile slope as the example for analysis, assessed the risks of the four stages of a landfill, verified the assessment model and analyzed the slope's failure risks and preventive measures against a slide.
Kim, Jinkyu; Kim, Gunn; An, Sungbae; Kwon, Young-Kyun; Yoon, Sungroh
2013-01-01
The assessment of information transfer in the global economic network helps to understand the current environment and the outlook of an economy. Most approaches on global networks extract information transfer based mainly on a single variable. This paper establishes an entirely new bioinformatics-inspired approach to integrating information transfer derived from multiple variables and develops an international economic network accordingly. In the proposed methodology, we first construct the transfer entropies (TEs) between various intra- and inter-country pairs of economic time series variables, test their significances, and then use a weighted sum approach to aggregate information captured in each TE. Through a simulation study, the new method is shown to deliver better information integration compared to existing integration methods in that it can be applied even when intra-country variables are correlated. Empirical investigation with the real world data reveals that Western countries are more influential in the global economic network and that Japan has become less influential following the Asian currency crisis.
An Entropy-Based Propagation Speed Estimation Method for Near-Field Subsurface Radar Imaging
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Pistorius Stephen
2010-01-01
Full Text Available During the last forty years, Subsurface Radar (SR has been used in an increasing number of noninvasive/nondestructive imaging applications, ranging from landmine detection to breast imaging. To properly assess the dimensions and locations of the targets within the scan area, SR data sets have to be reconstructed. This process usually requires the knowledge of the propagation speed in the medium, which is usually obtained by performing an offline measurement from a representative sample of the materials that form the scan region. Nevertheless, in some novel near-field SR scenarios, such as Microwave Wood Inspection (MWI and Breast Microwave Radar (BMR, the extraction of a representative sample is not an option due to the noninvasive requirements of the application. A novel technique to determine the propagation speed of the medium based on the use of an information theory metric is proposed in this paper. The proposed method uses the Shannon entropy of the reconstructed images as the focal quality metric to generate an estimate of the propagation speed in a given scan region. The performance of the proposed algorithm was assessed using data sets collected from experimental setups that mimic the dielectric contrast found in BMI and MWI scenarios. The proposed method yielded accurate results and exhibited an execution time in the order of seconds.
An Entropy-Based Propagation Speed Estimation Method for Near-Field Subsurface Radar Imaging
Flores-Tapia, Daniel; Pistorius, Stephen
2010-12-01
During the last forty years, Subsurface Radar (SR) has been used in an increasing number of noninvasive/nondestructive imaging applications, ranging from landmine detection to breast imaging. To properly assess the dimensions and locations of the targets within the scan area, SR data sets have to be reconstructed. This process usually requires the knowledge of the propagation speed in the medium, which is usually obtained by performing an offline measurement from a representative sample of the materials that form the scan region. Nevertheless, in some novel near-field SR scenarios, such as Microwave Wood Inspection (MWI) and Breast Microwave Radar (BMR), the extraction of a representative sample is not an option due to the noninvasive requirements of the application. A novel technique to determine the propagation speed of the medium based on the use of an information theory metric is proposed in this paper. The proposed method uses the Shannon entropy of the reconstructed images as the focal quality metric to generate an estimate of the propagation speed in a given scan region. The performance of the proposed algorithm was assessed using data sets collected from experimental setups that mimic the dielectric contrast found in BMI and MWI scenarios. The proposed method yielded accurate results and exhibited an execution time in the order of seconds.
Multiple Sclerosis Identification Based on Fractional Fourier Entropy and a Modified Jaya Algorithm
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Shui-Hua Wang
2018-04-01
Full Text Available Aim: Currently, identifying multiple sclerosis (MS by human experts may come across the problem of “normal-appearing white matter”, which causes a low sensitivity. Methods: In this study, we presented a computer vision based approached to identify MS in an automatic way. This proposed method first extracted the fractional Fourier entropy map from a specified brain image. Afterwards, it sent the features to a multilayer perceptron trained by a proposed improved parameter-free Jaya algorithm. We used cost-sensitivity learning to handle the imbalanced data problem. Results: The 10 × 10-fold cross validation showed our method yielded a sensitivity of 97.40 ± 0.60%, a specificity of 97.39 ± 0.65%, and an accuracy of 97.39 ± 0.59%. Conclusions: We validated by experiments that the proposed improved Jaya performs better than plain Jaya algorithm and other latest bioinspired algorithms in terms of classification performance and training speed. In addition, our method is superior to four state-of-the-art MS identification approaches.
Directory of Open Access Journals (Sweden)
Serafini Maria
2003-11-01
Full Text Available Abstract Background We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process. Results With E-RFE, we speed up the recursive feature elimination (RFE with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Conclusions Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.
A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method
Energy Technology Data Exchange (ETDEWEB)
Huang, Shengzhi; Ming, Bo; Huang, Qiang; Leng, Guoyong; Hou, Beibei
2017-05-05
It is critically meaningful to accurately predict NDVI (Normalized Difference Vegetation Index), which helps guide regional ecological remediation and environmental managements. In this study, a combination forecasting model (CFM) was proposed to improve the performance of NDVI predictions in the Yellow River Basin (YRB) based on three individual forecasting models, i.e., the Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM) models. The entropy weight method was employed to determine the weight coefficient for each individual model depending on its predictive performance. Results showed that: (1) ANN exhibits the highest fitting capability among the four orecasting models in the calibration period, whilst its generalization ability becomes weak in the validation period; MLR has a poor performance in both calibration and validation periods; the predicted results of CFM in the calibration period have the highest stability; (2) CFM generally outperforms all individual models in the validation period, and can improve the reliability and stability of predicted results through combining the strengths while reducing the weaknesses of individual models; (3) the performances of all forecasting models are better in dense vegetation areas than in sparse vegetation areas.
Analysis of QCD sum rule based on the maximum entropy method
International Nuclear Information System (INIS)
Gubler, Philipp
2012-01-01
QCD sum rule was developed about thirty years ago and has been used up to the present to calculate various physical quantities like hadrons. It has been, however, needed to assume 'pole + continuum' for the spectral function in the conventional analyses. Application of this method therefore came across with difficulties when the above assumption is not satisfied. In order to avoid this difficulty, analysis to make use of the maximum entropy method (MEM) has been developed by the present author. It is reported here how far this new method can be successfully applied. In the first section, the general feature of the QCD sum rule is introduced. In section 2, it is discussed why the analysis by the QCD sum rule based on the MEM is so effective. In section 3, the MEM analysis process is described, and in the subsection 3.1 likelihood function and prior probability are considered then in subsection 3.2 numerical analyses are picked up. In section 4, some cases of applications are described starting with ρ mesons, then charmoniums in the finite temperature and finally recent developments. Some figures of the spectral functions are shown. In section 5, summing up of the present analysis method and future view are given. (S. Funahashi)
Entropy based quantification of Ki-67 positive cell images and its evaluation by a reader study
Niazi, M. Khalid Khan; Pennell, Michael; Elkins, Camille; Hemminger, Jessica; Jin, Ming; Kirby, Sean; Kurt, Habibe; Miller, Barrie; Plocharczyk, Elizabeth; Roth, Rachel; Ziegler, Rebecca; Shana'ah, Arwa; Racke, Fred; Lozanski, Gerard; Gurcan, Metin N.
2013-03-01
Presence of Ki-67, a nuclear protein, is typically used to measure cell proliferation. The quantification of the Ki-67 proliferation index is performed visually by the pathologist; however, this is subject to inter- and intra-reader variability. Automated techniques utilizing digital image analysis by computers have emerged. The large variations in specimen preparation, staining, and imaging as well as true biological heterogeneity of tumor tissue often results in variable intensities in Ki-67 stained images. These variations affect the performance of currently developed methods. To optimize the segmentation of Ki-67 stained cells, one should define a data dependent transformation that will account for these color variations instead of defining a fixed linear transformation to separate different hues. To address these issues in images of tissue stained with Ki-67, we propose a methodology that exploits the intrinsic properties of CIE L∗a∗b∗ color space to translate this complex problem into an automatic entropy based thresholding problem. The developed method was evaluated through two reader studies with pathology residents and expert hematopathologists. Agreement between the proposed method and the expert pathologists was good (CCC = 0.80).
Information Entropy-Based Metrics for Measuring Emergences in Artificial Societies
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Mingsheng Tang
2014-08-01
Full Text Available Emergence is a common phenomenon, and it is also a general and important concept in complex dynamic systems like artificial societies. Usually, artificial societies are used for assisting in resolving several complex social issues (e.g., emergency management, intelligent transportation system with the aid of computer science. The levels of an emergence may have an effect on decisions making, and the occurrence and degree of an emergence are generally perceived by human observers. However, due to the ambiguity and inaccuracy of human observers, to propose a quantitative method to measure emergences in artificial societies is a meaningful and challenging task. This article mainly concentrates upon three kinds of emergences in artificial societies, including emergence of attribution, emergence of behavior, and emergence of structure. Based on information entropy, three metrics have been proposed to measure emergences in a quantitative way. Meanwhile, the correctness of these metrics has been verified through three case studies (the spread of an infectious influenza, a dynamic microblog network, and a flock of birds with several experimental simulations on the Netlogo platform. These experimental results confirm that these metrics increase with the rising degree of emergences. In addition, this article also has discussed the limitations and extended applications of these metrics.
Risk assessment of security systems based on entropy theory and the Neyman–Pearson criterion
International Nuclear Information System (INIS)
Lv, Haitao; Yin, Chao; Cui, Zongmin; Zhan, Qin; Zhou, Hongbo
2015-01-01
For a security system, the risk assessment is an important method to verdict whether its protection effectiveness is good or not. In this paper, a security system is regarded abstractly as a network by the name of a security network. A security network is made up of security nodes that are abstract functional units with the ability of detecting, delaying and responding. By the use of risk entropy and the Neyman–Pearson criterion, we construct a model to computer the protection probability of any position in the area where a security network is deployed. We provide a solution to find the most vulnerable path of a security network and the protection probability on the path is considered as the risk measure. Finally, we study the effect of some parameters on the risk and the breach protection probability of a security network. Ultimately, we can gain insight about the risk assessment of a security system. - Highlights: • A security system is regarded abstractly as a network made up of security nodes. • We construct a model to computer the protection probability provided by a security network. • We provide a better solution to find the most vulnerable path of a security network. • We build a risk assessment model for a security network based on the most vulnerable path
UV-Visible Spectroscopy-Based Quantification of Unlabeled DNA Bound to Gold Nanoparticles.
Baldock, Brandi L; Hutchison, James E
2016-12-20
DNA-functionalized gold nanoparticles have been increasingly applied as sensitive and selective analytical probes and biosensors. The DNA ligands bound to a nanoparticle dictate its reactivity, making it essential to know the type and number of DNA strands bound to the nanoparticle surface. Existing methods used to determine the number of DNA strands per gold nanoparticle (AuNP) require that the sequences be fluorophore-labeled, which may affect the DNA surface coverage and reactivity of the nanoparticle and/or require specialized equipment and other fluorophore-containing reagents. We report a UV-visible-based method to conveniently and inexpensively determine the number of DNA strands attached to AuNPs of different core sizes. When this method is used in tandem with a fluorescence dye assay, it is possible to determine the ratio of two unlabeled sequences of different lengths bound to AuNPs. Two sizes of citrate-stabilized AuNPs (5 and 12 nm) were functionalized with mixtures of short (5 base) and long (32 base) disulfide-terminated DNA sequences, and the ratios of sequences bound to the AuNPs were determined using the new method. The long DNA sequence was present as a lower proportion of the ligand shell than in the ligand exchange mixture, suggesting it had a lower propensity to bind the AuNPs than the short DNA sequence. The ratio of DNA sequences bound to the AuNPs was not the same for the large and small AuNPs, which suggests that the radius of curvature had a significant influence on the assembly of DNA strands onto the AuNPs.
Indian Academy of Sciences (India)
Abstract. It is shown that (i) every probability density is the unique maximizer of relative entropy in an appropriate class and (ii) in the class of all pdf f that satisfy. ∫ fhi dμ = λi for i = 1, 2,...,...k the maximizer of entropy is an f0 that is pro- portional to exp(. ∑ ci hi ) for some choice of ci . An extension of this to a continuum of.
Indian Academy of Sciences (India)
It is shown that (i) every probability density is the unique maximizer of relative entropy in an appropriate class and (ii) in the class of all pdf that satisfy ∫ f h i d = i for i = 1 , 2 , … , … k the maximizer of entropy is an f 0 that is proportional to exp ( ∑ c i h i ) for some choice of c i . An extension of this to a continuum of ...
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Tommaso Toffoli
2016-06-01
Full Text Available Here we deconstruct, and then in a reasoned way reconstruct, the concept of “entropy of a system”, paying particular attention to where the randomness may be coming from. We start with the core concept of entropy as a count associated with a description; this count (traditionally expressed in logarithmic form for a number of good reasons is in essence the number of possibilities—specific instances or “scenarios”—that match that description. Very natural (and virtually inescapable generalizations of the idea of description are the probability distribution and its quantum mechanical counterpart, the density operator. We track the process of dynamically updating entropy as a system evolves. Three factors may cause entropy to change: (1 the system’s internal dynamics; (2 unsolicited external influences on it; and (3 the approximations one has to make when one tries to predict the system’s future state. The latter task is usually hampered by hard-to-quantify aspects of the original description, limited data storage and processing resource, and possibly algorithmic inadequacy. Factors 2 and 3 introduce randomness—often huge amounts of it—into one’s predictions and accordingly degrade them. When forecasting, as long as the entropy bookkeping is conducted in an honest fashion, this degradation will always lead to an entropy increase. To clarify the above point we introduce the notion of honest entropy, which coalesces much of what is of course already done, often tacitly, in responsible entropy-bookkeping practice. This notion—we believe—will help to fill an expressivity gap in scientific discourse. With its help, we shall prove that any dynamical system—not just our physical universe—strictly obeys Clausius’s original formulation of the second law of thermodynamics if and only if it is invertible. Thus this law is a tautological property of invertible systems!
Shi, Bin; Jiang, Jiping; Sivakumar, Bellie; Zheng, Yi; Wang, Peng
2018-05-01
Field monitoring strategy is critical for disaster preparedness and watershed emergency environmental management. However, development of such is also highly challenging. Despite the efforts and progress thus far, no definitive guidelines or solutions are available worldwide for quantitatively designing a monitoring network in response to river chemical spill incidents, except general rules based on administrative divisions or arbitrary interpolation on routine monitoring sections. To address this gap, a novel framework for spatial-temporal network design was proposed in this study. The framework combines contaminant transport modelling with discrete entropy theory and spectral analysis. The water quality model was applied to forecast the spatio-temporal distribution of contaminant after spills and then corresponding information transfer indexes (ITIs) and Fourier approximation periodic functions were estimated as critical measures for setting sampling locations and times. The results indicate that the framework can produce scientific preparedness plans of emergency monitoring based on scenario analysis of spill risks as well as rapid design as soon as the incident happened but not prepared. The framework was applied to a hypothetical spill case based on tracer experiment and a real nitrobenzene spill incident case to demonstrate its suitability and effectiveness. The newly-designed temporal-spatial monitoring network captured major pollution information at relatively low costs. It showed obvious benefits for follow-up early-warning and treatment as well as for aftermath recovery and assessment. The underlying drivers of ITIs as well as the limitations and uncertainty of the approach were analyzed based on the case studies. Comparison with existing monitoring network design approaches, management implications, and generalized applicability were also discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.
Straka, Mika J.; Caldarelli, Guido; Squartini, Tiziano; Saracco, Fabio
2018-04-01
Bipartite networks provide an insightful representation of many systems, ranging from mutualistic networks of species interactions to investment networks in finance. The analyses of their topological structures have revealed the ubiquitous presence of properties which seem to characterize many—apparently different—systems. Nestedness, for example, has been observed in biological plant-pollinator as well as in country-product exportation networks. Due to the interdisciplinary character of complex networks, tools developed in one field, for example ecology, can greatly enrich other areas of research, such as economy and finance, and vice versa. With this in mind, we briefly review several entropy-based bipartite null models that have been recently proposed and discuss their application to real-world systems. The focus on these models is motivated by the fact that they show three very desirable features: analytical character, general applicability, and versatility. In this respect, entropy-based methods have been proven to perform satisfactorily both in providing benchmarks for testing evidence-based null hypotheses and in reconstructing unknown network configurations from partial information. Furthermore, entropy-based models have been successfully employed to analyze ecological as well as economic systems. As an example, the application of entropy-based null models has detected early-warning signals, both in economic and financial systems, of the 2007-2008 world crisis. Moreover, they have revealed a statistically-significant export specialization phenomenon of country export baskets in international trade, a result that seems to reconcile Ricardo's hypothesis in classical economics with recent findings on the (empirical) diversification industrial production at the national level. Finally, these null models have shown that the information contained in the nestedness is already accounted for by the degree sequence of the corresponding graphs.
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Kai Yan
2015-01-01
Full Text Available A predictive model for droplet size and velocity distributions of a pressure swirl atomizer has been proposed based on the maximum entropy formalism (MEF. The constraint conditions of the MEF model include the conservation laws of mass, momentum, and energy. The effects of liquid swirling strength, Weber number, gas-to-liquid axial velocity ratio and gas-to-liquid density ratio on the droplet size and velocity distributions of a pressure swirl atomizer are investigated. Results show that model based on maximum entropy formalism works well to predict droplet size and velocity distributions under different spray conditions. Liquid swirling strength, Weber number, gas-to-liquid axial velocity ratio and gas-to-liquid density ratio have different effects on droplet size and velocity distributions of a pressure swirl atomizer.
A subgradient-based branch-and-bound algorithm for the capacitated facility location problem
DEFF Research Database (Denmark)
Görtz, Simon; Klose, Andreas
This paper presents a simple branch-and-bound method based on Lagrangean relaxation and subgradient optimization for solving large instances of the capacitated facility location problem (CFLP) to optimality. In order to guess a primal solution to the Lagrangean dual, we average solutions to the L......This paper presents a simple branch-and-bound method based on Lagrangean relaxation and subgradient optimization for solving large instances of the capacitated facility location problem (CFLP) to optimality. In order to guess a primal solution to the Lagrangean dual, we average solutions...... to the Lagrangean subproblem. Branching decisions are then based on this estimated (fractional) primal solution. Extensive numerical results reveal that the method is much more faster and robust than other state-of-the-art methods for solving the CFLP exactly....
Energy Technology Data Exchange (ETDEWEB)
Fox, Zachary [School of Biomedical Engineering, Colorado State University, Fort Collins, Colorado 80523 (United States); Neuert, Gregor [Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee 37232 (United States); Department of Pharmacology, School of Medicine, Vanderbilt University, Nashville, Tennessee 37232 (United States); Department of Biomedical Engineering, Vanderbilt University School of Engineering, Nashville, Tennessee 37232 (United States); Munsky, Brian [School of Biomedical Engineering, Colorado State University, Fort Collins, Colorado 80523 (United States); Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, Colorado 80523 (United States)
2016-08-21
Emerging techniques now allow for precise quantification of distributions of biological molecules in single cells. These rapidly advancing experimental methods have created a need for more rigorous and efficient modeling tools. Here, we derive new bounds on the likelihood that observations of single-cell, single-molecule responses come from a discrete stochastic model, posed in the form of the chemical master equation. These strict upper and lower bounds are based on a finite state projection approach, and they converge monotonically to the exact likelihood value. These bounds allow one to discriminate rigorously between models and with a minimum level of computational effort. In practice, these bounds can be incorporated into stochastic model identification and parameter inference routines, which improve the accuracy and efficiency of endeavors to analyze and predict single-cell behavior. We demonstrate the applicability of our approach using simulated data for three example models as well as for experimental measurements of a time-varying stochastic transcriptional response in yeast.
Directory of Open Access Journals (Sweden)
H. T. R. Kurmasha
2017-12-01
Full Text Available An Edge-based image quality measure (IQM technique for the assessment of histogram equalization (HE-based contrast enhancement techniques has been proposed that outperforms the Absolute Mean Brightness Error (AMBE and Entropy which are the most commonly used IQMs to evaluate Histogram Equalization based techniques, and also the two prominent fidelity-based IQMs which are Multi-Scale Structural Similarity (MSSIM and Information Fidelity Criterion-based (IFC measures. The statistical evaluation results show that the Edge-based IQM, which was designed for detecting noise artifacts distortion, has a Person Correlation Coefficient (PCC > 0.86 while the others have poor or fair correlation to human opinion, considering the Human Visual Perception (HVP. Based on HVP, this paper propose an enhancement to classic Edge-based IQM by taking into account the brightness saturation distortion which is the most prominent distortion in HE-based contrast enhancement techniques. It is tested and found to have significantly well correlation (PCC > 0.87, Spearman rank order correlation coefficient (SROCC > 0.92, Root Mean Squared Error (RMSE < 0.1054, and Outlier Ratio (OR = 0%.
Liu, Jian; Zou, Renling; Zhang, Dongheng; Xu, Xiulin; Hu, Xiufang
2016-06-01
Exercise-induced muscle fatigue is a phenomenon that the maximum voluntary contraction force or power output of muscle is temporarily reduced due to muscular movement.If the fatigue is not treated properly,it will bring about a severe injury to the human body.With multi-channel collection of lower limb surface electromyography signals,this article analyzes the muscle fatigue by adoption of band spectrum entropy method which combined electromyographic signal spectral analysis and nonlinear dynamics.The experimental result indicated that with the increase of muscle fatigue,muscle signal spectrum began to move to low frequency,the energy concentrated,the system complexity came down,and the band spectrum entropy which reflected the complexity was also reduced.By monitoring the entropy,we can measure the degree of muscle fatigue,and provide an indicator to judge fatigue degree for the sports training and clinical rehabilitation training.
Generalization bounds of ERM-based learning processes for continuous-time Markov chains.
Zhang, Chao; Tao, Dacheng
2012-12-01
Many existing results on statistical learning theory are based on the assumption that samples are independently and identically distributed (i.i.d.). However, the assumption of i.i.d. samples is not suitable for practical application to problems in which samples are time dependent. In this paper, we are mainly concerned with the empirical risk minimization (ERM) based learning process for time-dependent samples drawn from a continuous-time Markov chain. This learning process covers many kinds of practical applications, e.g., the prediction for a time series and the estimation of channel state information. Thus, it is significant to study its theoretical properties including the generalization bound, the asymptotic convergence, and the rate of convergence. It is noteworthy that, since samples are time dependent in this learning process, the concerns of this paper cannot (at least straightforwardly) be addressed by existing methods developed under the sample i.i.d. assumption. We first develop a deviation inequality for a sequence of time-dependent samples drawn from a continuous-time Markov chain and present a symmetrization inequality for such a sequence. By using the resultant deviation inequality and symmetrization inequality, we then obtain the generalization bounds of the ERM-based learning process for time-dependent samples drawn from a continuous-time Markov chain. Finally, based on the resultant generalization bounds, we analyze the asymptotic convergence and the rate of convergence of the learning process.
Yu, Hwa-Lung; Wang, Chih-Hsin
2013-02-05
Understanding the daily changes in ambient air quality concentrations is important to the assessing human exposure and environmental health. However, the fine temporal scales (e.g., hourly) involved in this assessment often lead to high variability in air quality concentrations. This is because of the complex short-term physical and chemical mechanisms among the pollutants. Consequently, high heterogeneity is usually present in not only the averaged pollution levels, but also the intraday variance levels of the daily observations of ambient concentration across space and time. This characteristic decreases the estimation performance of common techniques. This study proposes a novel quantile-based Bayesian maximum entropy (QBME) method to account for the nonstationary and nonhomogeneous characteristics of ambient air pollution dynamics. The QBME method characterizes the spatiotemporal dependence among the ambient air quality levels based on their location-specific quantiles and accounts for spatiotemporal variations using a local weighted smoothing technique. The epistemic framework of the QBME method can allow researchers to further consider the uncertainty of space-time observations. This study presents the spatiotemporal modeling of daily CO and PM10 concentrations across Taiwan from 1998 to 2009 using the QBME method. Results show that the QBME method can effectively improve estimation accuracy in terms of lower mean absolute errors and standard deviations over space and time, especially for pollutants with strong nonhomogeneous variances across space. In addition, the epistemic framework can allow researchers to assimilate the site-specific secondary information where the observations are absent because of the common preferential sampling issues of environmental data. The proposed QBME method provides a practical and powerful framework for the spatiotemporal modeling of ambient pollutants.
Ebrahimnejad, Ali
2015-08-01
There are several methods, in the literature, for solving fuzzy variable linear programming problems (fuzzy linear programming in which the right-hand-side vectors and decision variables are represented by trapezoidal fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings a new method based on the bounded dual simplex method is proposed to determine the fuzzy optimal solution of that kind of fuzzy variable linear programming problems in which some or all variables are restricted to lie within lower and upper bounds. To illustrate the proposed method, an application example is solved and the obtained results are given. The advantages of the proposed method over existing methods are discussed. Also, one application of this algorithm in solving bounded transportation problems with fuzzy supplies and demands is dealt with. The proposed method is easy to understand and to apply for determining the fuzzy optimal solution of bounded fuzzy variable linear programming problems occurring in real-life situations.
Roushangar, Kiyoumars; Alizadeh, Farhad; Adamowski, Jan
2018-08-01
Understanding precipitation on a regional basis is an important component of water resources planning and management. The present study outlines a methodology based on continuous wavelet transform (CWT) and multiscale entropy (CWME), combined with self-organizing map (SOM) and k-means clustering techniques, to measure and analyze the complexity of precipitation. Historical monthly precipitation data from 1960 to 2010 at 31 rain gauges across Iran were preprocessed by CWT. The multi-resolution CWT approach segregated the major features of the original precipitation series by unfolding the structure of the time series which was often ambiguous. The entropy concept was then applied to components obtained from CWT to measure dispersion, uncertainty, disorder, and diversification of subcomponents. Based on different validity indices, k-means clustering captured homogenous areas more accurately, and additional analysis was performed based on the outcome of this approach. The 31 rain gauges in this study were clustered into 6 groups, each one having a unique CWME pattern across different time scales. The results of clustering showed that hydrologic similarity (multiscale variation of precipitation) was not based on geographic contiguity. According to the pattern of entropy across the scales, each cluster was assigned an entropy signature that provided an estimation of the entropy pattern of precipitation data in each cluster. Based on the pattern of mean CWME for each cluster, a characteristic signature was assigned, which provided an estimation of the CWME of a cluster across scales of 1-2, 3-8, and 9-13 months relative to other stations. The validity of the homogeneous clusters demonstrated the usefulness of the proposed approach to regionalize precipitation. Further analysis based on wavelet coherence (WTC) was performed by selecting central rain gauges in each cluster and analyzing against temperature, wind, Multivariate ENSO index (MEI), and East Atlantic (EA) and
Wu, Jun; Li, Chengbing; Huo, Yueying
2014-01-01
Safety of dangerous goods transport is directly related to the operation safety of dangerous goods transport enterprise. Aiming at the problem of the high accident rate and large harm in dangerous goods logistics transportation, this paper took the group decision making problem based on integration and coordination thought into a multiagent multiobjective group decision making problem; a secondary decision model was established and applied to the safety assessment of dangerous goods transport enterprise. First of all, we used dynamic multivalue background and entropy theory building the first level multiobjective decision model. Secondly, experts were to empower according to the principle of clustering analysis, and combining with the relative entropy theory to establish a secondary rally optimization model based on relative entropy in group decision making, and discuss the solution of the model. Then, after investigation and analysis, we establish the dangerous goods transport enterprise safety evaluation index system. Finally, case analysis to five dangerous goods transport enterprises in the Inner Mongolia Autonomous Region validates the feasibility and effectiveness of this model for dangerous goods transport enterprise recognition, which provides vital decision making basis for recognizing the dangerous goods transport enterprises.
Directory of Open Access Journals (Sweden)
Mohamed Idhammad
2018-01-01
Full Text Available Cloud Computing services are often delivered through HTTP protocol. This facilitates access to services and reduces costs for both providers and end-users. However, this increases the vulnerabilities of the Cloud services face to HTTP DDoS attacks. HTTP request methods are often used to address web servers’ vulnerabilities and create multiple scenarios of HTTP DDoS attack such as Low and Slow or Flooding attacks. Existing HTTP DDoS detection systems are challenged by the big amounts of network traffic generated by these attacks, low detection accuracy, and high false positive rates. In this paper we present a detection system of HTTP DDoS attacks in a Cloud environment based on Information Theoretic Entropy and Random Forest ensemble learning algorithm. A time-based sliding window algorithm is used to estimate the entropy of the network header features of the incoming network traffic. When the estimated entropy exceeds its normal range the preprocessing and the classification tasks are triggered. To assess the proposed approach various experiments were performed on the CIDDS-001 public dataset. The proposed approach achieves satisfactory results with an accuracy of 99.54%, a FPR of 0.4%, and a running time of 18.5s.
International Nuclear Information System (INIS)
Han, J; Dong, F; Xu, Y Y
2009-01-01
This paper introduces the fundamental of cross-section measurement system based on Electrical Resistance Tomography (ERT). The measured data of four flow regimes of the gas/liquid two-phase flow in horizontal pipe flow are obtained by an ERT system. For the measured data, five entropies are extracted to analyze the experimental data according to the different flow regimes, and the analysis method is examined and compared in three different perspectives. The results indicate that three different perspectives of entropy-based feature extraction are sensitive to the flow pattern transition in gas/liquid two-phase flow. By analyzing the results of three different perspectives with the changes of gas/liquid two-phase flow parameters, the dynamic structures of gas/liquid two-phase flow is obtained, and they also provide an efficient supplementary to reveal the flow pattern transition mechanism of gas/liquid two-phase flow. Comparison of the three different methods of feature extraction shows that the appropriate entropy should be used for the identification and prediction of flow regimes.
CoFea: A Novel Approach to Spam Review Identification Based on Entropy and Co-Training
Directory of Open Access Journals (Sweden)
Wen Zhang
2016-11-01
Full Text Available With the rapid development of electronic commerce, spam reviews are rapidly growing on the Internet to manipulate online customers’ opinions on goods being sold. This paper proposes a novel approach, called CoFea (Co-training by Features, to identify spam reviews, based on entropy and the co-training algorithm. After sorting all lexical terms of reviews by entropy, we produce two views on the reviews by dividing the lexical terms into two subsets. One subset contains odd-numbered terms and the other contains even-numbered terms. Using SVM (support vector machine as the base classifier, we further propose two strategies, CoFea-T and CoFea-S, embedded with the CoFea approach. The CoFea-T strategy uses all terms in the subsets for spam review identification by SVM. The CoFea-S strategy uses a predefined number of terms with small entropy for spam review identification by SVM. The experiment results show that the CoFea-T strategy produces better accuracy than the CoFea-S strategy, while the CoFea-S strategy saves more computing time than the CoFea-T strategy with acceptable accuracy in spam review identification.
Fragment-based modelling of single stranded RNA bound to RNA recognition motif containing proteins
de Beauchene, Isaure Chauvot; de Vries, Sjoerd J.; Zacharias, Martin
2016-01-01
Abstract Protein-RNA complexes are important for many biological processes. However, structural modeling of such complexes is hampered by the high flexibility of RNA. Particularly challenging is the docking of single-stranded RNA (ssRNA). We have developed a fragment-based approach to model the structure of ssRNA bound to a protein, based on only the protein structure, the RNA sequence and conserved contacts. The conformational diversity of each RNA fragment is sampled by an exhaustive library of trinucleotides extracted from all known experimental protein–RNA complexes. The method was applied to ssRNA with up to 12 nucleotides which bind to dimers of the RNA recognition motifs (RRMs), a highly abundant eukaryotic RNA-binding domain. The fragment based docking allows a precise de novo atomic modeling of protein-bound ssRNA chains. On a benchmark of seven experimental ssRNA–RRM complexes, near-native models (with a mean heavy-atom deviation of <3 Å from experiment) were generated for six out of seven bound RNA chains, and even more precise models (deviation < 2 Å) were obtained for five out of seven cases, a significant improvement compared to the state of the art. The method is not restricted to RRMs but was also successfully applied to Pumilio RNA binding proteins. PMID:27131381
In-gap bound states induced by interstitial Fe impurities in iron-based superconductors
Energy Technology Data Exchange (ETDEWEB)
Zhang, Degang, E-mail: degangzhang@yahoo.com
2015-12-15
Highlights: • We provide an explanation for the interesting STM observation of the robust zero energy bound state on the interstitial Fe impurities in iron-based superconductors. - Abstract: Based on a two-orbit four-band tight binding model, we investigate the low-lying electronic states around the interstitial excess Fe ions in the iron-based superconductors by using T-matrix approach. It is shown that the local density of states at the interstitial Fe impurity (IFI) possesses a strong resonance inside the gap, which seems to be insensitive to the doping and the pairing symmetry in the Fe–Fe plane, while a single or two resonances appear at the nearest neighboring (NN) Fe sites. The location and height of the resonance peaks only depend on the hopping t and the pairing parameter Δ{sub I} between the IFI and the NN Fe sites. These in-gap resonances are originated in the Andreev’s bound states due to the quasiparticle tunneling through the IFI, leading to the change of the magnitude of the superconducting order parameter. When both t and Δ{sub I} are small, this robust zero-energy bound state near the IFI is consistent with recent scanning tunneling microscopy observations.
Entropy for Mechanically Vibrating Systems
Tufano, Dante
, which demonstrates the applicability of entropy-based approaches to real-world systems. Three systems are considered to demonstrate these findings: 1) a rod end-coupled to a simple oscillator, 2) two end-coupled rods, and 3) two end-coupled beams. The aforementioned work utilizes the weak coupling assumption to determine the entropy of composite systems. Following this discussion, a direct method of finding entropy is developed which does not rely on this limiting assumption. The resulting entropy provides a useful benchmark for evaluating the accuracy of the weak coupling approach, and is validated using systems of coupled oscillators. The later chapters of this work discuss Khinchin's entropy as applied to nonlinear and nonconservative systems, respectively. The discussion of entropy for nonlinear systems is motivated by the desire to expand the applicability of SEA techniques beyond the linear regime. The discussion of nonconservative systems is also crucial, since real-world systems interact with their environment, and it is necessary to confirm the validity of an entropy approach for systems that are relevant in the context of SEA. Having developed a mathematical framework for determining entropy under a number of previously unexplored cases, the relationship between thermodynamics and statistical vibroacoustics can be better understood. Specifically, vibroacoustic temperatures can be obtained for systems that are not necessarily linear or weakly coupled. In this way, entropy provides insight into how the power flow proportionality of statistical energy analysis (SEA) can be applied to a broader class of vibroacoustic systems. As such, entropy is a useful tool for both justifying and expanding the foundational results of SEA.
Cuesta-Frau, David; Miró-Martínez, Pau; Jordán Núñez, Jorge; Oltra-Crespo, Sandra; Molina Picó, Antonio
2017-08-01
This paper evaluates the performance of first generation entropy metrics, featured by the well known and widely used Approximate Entropy (ApEn) and Sample Entropy (SampEn) metrics, and what can be considered an evolution from these, Fuzzy Entropy (FuzzyEn), in the Electroencephalogram (EEG) signal classification context. The study uses the commonest artifacts found in real EEGs, such as white noise, and muscular, cardiac, and ocular artifacts. Using two different sets of publicly available EEG records, and a realistic range of amplitudes for interfering artifacts, this work optimises and assesses the robustness of these metrics against artifacts in class segmentation terms probability. The results show that the qualitative behaviour of the two datasets is similar, with SampEn and FuzzyEn performing the best, and the noise and muscular artifacts are the most confounding factors. On the contrary, there is a wide variability as regards initialization parameters. The poor performance achieved by ApEn suggests that this metric should not be used in these contexts. Copyright © 2017 Elsevier Ltd. All rights reserved.
Black hole entropy, curved space and monsters
International Nuclear Information System (INIS)
Hsu, Stephen D.H.; Reeb, David
2008-01-01
We investigate the microscopic origin of black hole entropy, in particular the gap between the maximum entropy of ordinary matter and that of black holes. Using curved space, we construct configurations with entropy greater than the area A of a black hole of equal mass. These configurations have pathological properties and we refer to them as monsters. When monsters are excluded we recover the entropy bound on ordinary matter S 3/4 . This bound implies that essentially all of the microstates of a semiclassical black hole are associated with the growth of a slightly smaller black hole which absorbs some additional energy. Our results suggest that the area entropy of black holes is the logarithm of the number of distinct ways in which one can form the black hole from ordinary matter and smaller black holes, but only after the exclusion of monster states
Entropy: From Thermodynamics to Hydrology
Directory of Open Access Journals (Sweden)
Demetris Koutsoyiannis
2014-02-01
Full Text Available Some known results from statistical thermophysics as well as from hydrology are revisited from a different perspective trying: (a to unify the notion of entropy in thermodynamic and statistical/stochastic approaches of complex hydrological systems and (b to show the power of entropy and the principle of maximum entropy in inference, both deductive and inductive. The capability for deductive reasoning is illustrated by deriving the law of phase change transition of water (Clausius-Clapeyron from scratch by maximizing entropy in a formal probabilistic frame. However, such deductive reasoning cannot work in more complex hydrological systems with diverse elements, yet the entropy maximization framework can help in inductive inference, necessarily based on data. Several examples of this type are provided in an attempt to link statistical thermophysics with hydrology with a unifying view of entropy.
Bounds on the vibrational energy that can be harvested from random base motion
Langley, R. S.
2015-03-01
This paper is concerned with the development of upper bounds on the energy harvesting performance of a general multi-degree-of-freedom nonlinear electromechanical system that is subjected to random base motion and secondary applied periodic forces. The secondary forces are applied with the aim of enhancing the energy harvested from the base motion, and they may constitute direct excitation, or they may produce parametric terms in the equations of motion. It is shown that when the base motion has white noise acceleration then the power input by the base is always πS0 M / 2 where S0 is the single sided spectral density of the acceleration, and M is the mass of the system. This implies that although the secondary forces may enhance the energy harvested by causing a larger fraction of the power input from the base to be harvested rather than dissipated, there is an upper limit on the power that can be harvested. Attention is then turned to narrow band excitation, and it is found that in the absence of secondary forces a bound can be derived for a single degree of freedom system with linear damping and arbitrary nonlinear stiffness. The upper bound on the power input by the base is πM max [ S (ω) ] / 2, where S (ω) is the single sided base acceleration spectrum. The validity of this result for more general systems is found to be related to the properties of the first Wiener kernel, and this issue is explored analytically and by numerical simulation.
Tang, Jinjun; Zhang, Shen; Chen, Xinqiang; Liu, Fang; Zou, Yajie
2018-03-01
Understanding Origin-Destination distribution of taxi trips is very important for improving effects of transportation planning and enhancing quality of taxi services. This study proposes a new method based on Entropy-Maximizing theory to model OD distribution in Harbin city using large-scale taxi GPS trajectories. Firstly, a K-means clustering method is utilized to partition raw pick-up and drop-off location into different zones, and trips are assumed to start from and end at zone centers. A generalized cost function is further defined by considering travel distance, time and fee between each OD pair. GPS data collected from more than 1000 taxis at an interval of 30 s during one month are divided into two parts: data from first twenty days is treated as training dataset and last ten days is taken as testing dataset. The training dataset is used to calibrate model while testing dataset is used to validate model. Furthermore, three indicators, mean absolute error (MAE), root mean square error (RMSE) and mean percentage absolute error (MPAE), are applied to evaluate training and testing performance of Entropy-Maximizing model versus Gravity model. The results demonstrate Entropy-Maximizing model is superior to Gravity model. Findings of the study are used to validate the feasibility of OD distribution from taxi GPS data in urban system.
Alloying behavior of iron, gold and silver in AlCoCrCuNi-based equimolar high-entropy alloys
International Nuclear Information System (INIS)
Hsu, U.S.; Hung, U.D.; Yeh, J.W.; Chen, S.K.; Huang, Y.S.; Yang, C.C.
2007-01-01
High-entropy alloys are newly developed alloys that are composed, by definition, of at least five principal elements with concentrations in the range of 5-35 at.%. Therefore, the alloying behavior of any given principal element is significantly affected by all the other principal elements present. In order to elucidate this further, the influence of iron, silver and gold addition on the microstructure and hardness of AlCoCrCuNi-based equimolar alloys has been examined. The as-cast AlCoCrCuNi base alloy is found to have a dendritic structure, of which only solid solution FCC and BCC phases can be observed. The BCC dendrite has a chemical composition close to that of the nominal alloy, with a deficiency in copper however, which is found to segregate and form a FCC Cu-rich interdendrite. The microstructure of the iron containing alloys is similar to that of the base alloy. It is found that both of these aforementioned alloys have hardnesses of about 420 HV, which is equated to their similar microstructures. The as-cast ingot forms two layers of distinct composition with the addition of silver. These layers, which are gold and silver in color, are determined to have a hypoeutectic Ag-Cu composition and a multielement mixture of the other principal elements, respectively. This indicates the chemical incompatibility of silver with the other principal elements. The hardnesses of the gold (104 HV) and silver layers (451 HV) are the lowest and highest of the alloy systems studied. This is attributed to the hypoeutectic Ag-Cu composition of the former and the reduced copper content of the latter. Only multielement mixtures, i.e. without copper segregation, form in the gold containing alloy. Thus, it may be said that gold acts as a 'mixing agent' between copper and the other elements. Although several of the atom pairs in the gold containing alloy have positive enthalpies, thermodynamic considerations show that the high entropy contribution is sufficient to counterbalance
Relation Entropy and Transferable Entropy Think of Aggregation on Group Decision Making
Institute of Scientific and Technical Information of China (English)
CHENG Qi-yue; QIU Wan-hua; LIU Xiao-feng
2002-01-01
In this paper, aggregation question based on group decision making and a single decision making is studied. The theory of entropy is applied to the sets pair analysis. The system of relation entropy and the transferable entropy notion are put. The character is studied. An potential by the relation entropy and transferable entropy are defined. It is the consistency measure on the group between a single decision making. We gained a new aggregation effective definition on the group misjudge.
Logarithmic black hole entropy corrections and holographic Renyi entropy
Energy Technology Data Exchange (ETDEWEB)
Mahapatra, Subhash [The Institute of Mathematical Sciences, Chennai (India); KU Leuven - KULAK, Department of Physics, Kortrijk (Belgium)
2018-01-15
The entanglement and Renyi entropies for spherical entangling surfaces in CFTs with gravity duals can be explicitly calculated by mapping these entropies first to the thermal entropy on hyperbolic space and then, using the AdS/CFT correspondence, to the Wald entropy of topological black holes. Here we extend this idea by taking into account corrections to the Wald entropy. Using the method based on horizon symmetries and the asymptotic Cardy formula, we calculate corrections to the Wald entropy and find that these corrections are proportional to the logarithm of the area of the horizon. With the corrected expression for the entropy of the black hole, we then find corrections to the Renyi entropies. We calculate these corrections for both Einstein and Gauss-Bonnet gravity duals. Corrections with logarithmic dependence on the area of the entangling surface naturally occur at the order G{sub D}{sup 0}. The entropic c-function and the inequalities of the Renyi entropy are also satisfied even with the correction terms. (orig.)
Logarithmic black hole entropy corrections and holographic Renyi entropy
International Nuclear Information System (INIS)
Mahapatra, Subhash
2018-01-01
The entanglement and Renyi entropies for spherical entangling surfaces in CFTs with gravity duals can be explicitly calculated by mapping these entropies first to the thermal entropy on hyperbolic space and then, using the AdS/CFT correspondence, to the Wald entropy of topological black holes. Here we extend this idea by taking into account corrections to the Wald entropy. Using the method based on horizon symmetries and the asymptotic Cardy formula, we calculate corrections to the Wald entropy and find that these corrections are proportional to the logarithm of the area of the horizon. With the corrected expression for the entropy of the black hole, we then find corrections to the Renyi entropies. We calculate these corrections for both Einstein and Gauss-Bonnet gravity duals. Corrections with logarithmic dependence on the area of the entangling surface naturally occur at the order G D 0 . The entropic c-function and the inequalities of the Renyi entropy are also satisfied even with the correction terms. (orig.)
Anisimov, D. N.; Dang, Thai Son; Banerjee, Santo; Mai, The Anh
2017-07-01
In this paper, an intelligent system use fuzzy-PD controller based on relation models is developed for a two-wheeled self-balancing robot. Scaling factors of the fuzzy-PD controller are optimized by a Cross-Entropy optimization method. A linear Quadratic Regulator is designed to bring a comparison with the fuzzy-PD controller by control quality parameters. The controllers are ported and run on STM32F4 Discovery Kit based on the real-time operating system. The experimental results indicate that the proposed fuzzy-PD controller runs exactly on embedded system and has desired performance in term of fast response, good balance and stabilize.
Evaluation of single and multi-threshold entropy-based algorithms for folded substrate analysis
Directory of Open Access Journals (Sweden)
Magdolna Apro
2011-10-01
Full Text Available This paper presents a detailed evaluation of two variants of Maximum Entropy image segmentation algorithm(single and multi-thresholding with respect to their performance on segmenting test images showing folded substrates.The segmentation quality was determined by evaluating values of four different measures: misclassificationerror, modified Hausdorff distance, relative foreground area error and positive-negative false detection ratio. Newnormalization methods were proposed in order to combine all parameters into a unique algorithm evaluation rating.The segmentation algorithms were tested on images obtained by three different digitalisation methods coveringfour different surface textures. In addition, the methods were also tested on three images presenting a perfect fold.The obtained results showed that Multi-Maximum Entropy algorithm is better suited for the analysis of imagesshowing folded substrates.
Analysis of calculating methods for failure distribution function based on maximal entropy principle
International Nuclear Information System (INIS)
Guo Chunying; Lin Yuangen; Jiang Meng; Wu Changli
2009-01-01
The computation of invalidation distribution functions of electronic devices when exposed in gamma rays is discussed here. First, the possible devices failure distribution models are determined through the tests of statistical hypotheses using the test data. The results show that: the devices' failure distribution can obey multi-distributions when the test data is few. In order to decide the optimum failure distribution model, the maximal entropy principle is used and the elementary failure models are determined. Then, the Bootstrap estimation method is used to simulate the intervals estimation of the mean and the standard deviation. On the basis of this, the maximal entropy principle is used again and the simulated annealing method is applied to find the optimum values of the mean and the standard deviation. Accordingly, the electronic devices' optimum failure distributions are finally determined and the survival probabilities are calculated. (authors)
Predicting the Outcome of NBA Playoffs Based on the Maximum Entropy Principle
Directory of Open Access Journals (Sweden)
Ge Cheng
2016-12-01
Full Text Available Predicting the outcome of National Basketball Association (NBA matches poses a challenging problem of interest to the research community as well as the general public. In this article, we formalize the problem of predicting NBA game results as a classification problem and apply the principle of Maximum Entropy to construct an NBA Maximum Entropy (NBAME model that fits to discrete statistics for NBA games, and then predict the outcomes of NBA playoffs using the model. Our results reveal that the model is able to predict the winning team with 74.4% accuracy, outperforming other classical machine learning algorithms that could only afford a maximum prediction accuracy of 70.6% in the experiments that we performed.
Using entropy measures to characterize human locomotion.
Leverick, Graham; Szturm, Tony; Wu, Christine Q
2014-12-01
Entropy measures have been widely used to quantify the complexity of theoretical and experimental dynamical systems. In this paper, the value of using entropy measures to characterize human locomotion is demonstrated based on their construct validity, predictive validity in a simple model of human walking and convergent validity in an experimental study. Results show that four of the five considered entropy measures increase meaningfully with the increased probability of falling in a simple passive bipedal walker model. The same four entropy measures also experienced statistically significant increases in response to increasing age and gait impairment caused by cognitive interference in an experimental study. Of the considered entropy measures, the proposed quantized dynamical entropy (QDE) and quantization-based approximation of sample entropy (QASE) offered the best combination of sensitivity to changes in gait dynamics and computational efficiency. Based on these results, entropy appears to be a viable candidate for assessing the stability of human locomotion.
Liang, Xuedong; Si, Dongyang; Zhang, Xinli
2017-10-13
According to the implementation of a scientific development perspective, sustainable development needs to consider regional development, economic and social development, and the harmonious development of society and nature, but regional sustainable development is often difficult to quantify. Through an analysis of the structure and functions of a regional system, this paper establishes an evaluation index system, which includes an economic subsystem, an ecological environmental subsystem and a social subsystem, to study regional sustainable development capacity. A sustainable development capacity measure model for Sichuan Province was established by applying the information entropy calculation principle and the Brusselator principle. Each subsystem and entropy change in a calendar year in Sichuan Province were analyzed to evaluate Sichuan Province's sustainable development capacity. It was found that the established model could effectively show actual changes in sustainable development levels through the entropy change reaction system, at the same time this model could clearly demonstrate how those forty-six indicators from the three subsystems impact on the regional sustainable development, which could make up for the lack of sustainable development research.
Bounds on the Capacity of Weakly constrained two-dimensional Codes
DEFF Research Database (Denmark)
Forchhammer, Søren
2002-01-01
Upper and lower bounds are presented for the capacity of weakly constrained two-dimensional codes. The maximum entropy is calculated for two simple models of 2-D codes constraining the probability of neighboring 1s as an example. For given models of the coded data, upper and lower bounds...... on the capacity for 2-D channel models based on occurrences of neighboring 1s are considered....
International Nuclear Information System (INIS)
Zambon, Ilaria; Colantoni, Andrea; Carlucci, Margherita; Morrow, Nathan; Sateriano, Adele; Salvati, Luca
2017-01-01
Land Degradation (LD) in socio-environmental systems negatively impacts sustainable development paths. This study proposes a framework to LD evaluation based on indicators of diversification in the spatial distribution of sensitive land. We hypothesize that conditions for spatial heterogeneity in a composite index of land sensitivity are more frequently associated to areas prone to LD than spatial homogeneity. Spatial heterogeneity is supposed to be associated with degraded areas that act as hotspots for future degradation processes. A diachronic analysis (1960–2010) was performed at the Italian agricultural district scale to identify environmental factors associated with spatial heterogeneity in the degree of land sensitivity to degradation based on the Environmentally Sensitive Area Index (ESAI). In 1960, diversification in the level of land sensitivity measured using two common indexes of entropy (Shannon's diversity and Pielou's evenness) increased significantly with the ESAI, indicating a high level of land sensitivity to degradation. In 2010, surface area classified as “critical” to LD was the highest in districts with diversification in the spatial distribution of ESAI values, confirming the hypothesis formulated above. Entropy indexes, based on observed alignment with the concept of LD, constitute a valuable base to inform mitigation strategies against desertification. - Highlights: • Spatial heterogeneity is supposed to be associated with degraded areas. • Entropy indexes can inform mitigation strategies against desertification. • Assessing spatial diversification in the degree of land sensitivity to degradation. • Mediterranean rural areas have an evident diversity in agricultural systems. • A diachronic analysis carried out at the Italian agricultural district scale.
Energy Technology Data Exchange (ETDEWEB)
Zambon, Ilaria, E-mail: ilaria.zambon@unitus.it [Department of Agricultural and Forestry scieNcEs (DAFNE), Tuscia University, Via S. Camillo de Lellis, I-01100 Viterbo (Italy); Colantoni, Andrea [Department of Agricultural and Forestry scieNcEs (DAFNE), Tuscia University, Via S. Camillo de Lellis, I-01100 Viterbo (Italy); Carlucci, Margherita [Department of Social and Economic Science, University of Rome La Sapienza, Piazzale A. Moro 5, I-00185 Rome (Italy); Morrow, Nathan [Tulane University, Payson Program in International Development at the School of Law, New Orleans (United States); Sateriano, Adele; Salvati, Luca [Italian Council for Agricultural Research and Economics (CREA-RPS), Via della Navicella 2-4, I-00184 Rome (Italy)
2017-05-15
Land Degradation (LD) in socio-environmental systems negatively impacts sustainable development paths. This study proposes a framework to LD evaluation based on indicators of diversification in the spatial distribution of sensitive land. We hypothesize that conditions for spatial heterogeneity in a composite index of land sensitivity are more frequently associated to areas prone to LD than spatial homogeneity. Spatial heterogeneity is supposed to be associated with degraded areas that act as hotspots for future degradation processes. A diachronic analysis (1960–2010) was performed at the Italian agricultural district scale to identify environmental factors associated with spatial heterogeneity in the degree of land sensitivity to degradation based on the Environmentally Sensitive Area Index (ESAI). In 1960, diversification in the level of land sensitivity measured using two common indexes of entropy (Shannon's diversity and Pielou's evenness) increased significantly with the ESAI, indicating a high level of land sensitivity to degradation. In 2010, surface area classified as “critical” to LD was the highest in districts with diversification in the spatial distribution of ESAI values, confirming the hypothesis formulated above. Entropy indexes, based on observed alignment with the concept of LD, constitute a valuable base to inform mitigation strategies against desertification. - Highlights: • Spatial heterogeneity is supposed to be associated with degraded areas. • Entropy indexes can inform mitigation strategies against desertification. • Assessing spatial diversification in the degree of land sensitivity to degradation. • Mediterranean rural areas have an evident diversity in agricultural systems. • A diachronic analysis carried out at the Italian agricultural district scale.
Trif, Mircea; Dmytruk, Olesia; Bouchiat, Hélène; Aguado, Ramón; Simon, Pascal
2018-02-01
We theoretically study a Josephson junction based on a semiconducting nanowire subject to a time-dependent flux bias. We establish a general density-matrix approach for the dynamical response of the Majorana junction and calculate the resulting flux-dependent susceptibility using both microscopic and effective low-energy descriptions for the nanowire. We find that the diagonal component of the susceptibility, associated with the dynamics of the Majorana state populations, dominates over the standard Kubo contribution for a wide range of experimentally relevant parameters. The diagonal term, explored, in this Rapid Communication, in the context of Majorana physics, allows probing accurately the presence of Majorana bound states in the junction.
Directory of Open Access Journals (Sweden)
Xiong Luo
2016-07-01
Full Text Available With the recent emergence of wireless sensor networks (WSNs in the cloud computing environment, it is now possible to monitor and gather physical information via lots of sensor nodes to meet the requirements of cloud services. Generally, those sensor nodes collect data and send data to sink node where end-users can query all the information and achieve cloud applications. Currently, one of the main disadvantages in the sensor nodes is that they are with limited physical performance relating to less memory for storage and less source of power. Therefore, in order to avoid such limitation, it is necessary to develop an efficient data prediction method in WSN. To serve this purpose, by reducing the redundant data transmission between sensor nodes and sink node while maintaining the required acceptable errors, this article proposes an entropy-based learning scheme for data prediction through the use of kernel least mean square (KLMS algorithm. The proposed scheme called E-KLMS develops a mechanism to maintain the predicted data synchronous at both sides. Specifically, the kernel-based method is able to adjust the coefficients adaptively in accordance with every input, which will achieve a better performance with smaller prediction errors, while employing information entropy to remove these data which may cause relatively large errors. E-KLMS can effectively solve the tradeoff problem between prediction accuracy and computational efforts while greatly simplifying the training structure compared with some other data prediction approaches. What’s more, the kernel-based method and entropy technique could ensure the prediction effect by both improving the accuracy and reducing errors. Experiments with some real data sets have been carried out to validate the efficiency and effectiveness of E-KLMS learning scheme, and the experiment results show advantages of the our method in prediction accuracy and computational time.
Accelerating rejection-based simulation of biochemical reactions with bounded acceptance probability
Energy Technology Data Exchange (ETDEWEB)
Thanh, Vo Hong, E-mail: vo@cosbi.eu [The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Priami, Corrado, E-mail: priami@cosbi.eu [The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Department of Mathematics, University of Trento, Trento (Italy); Zunino, Roberto, E-mail: roberto.zunino@unitn.it [Department of Mathematics, University of Trento, Trento (Italy)
2016-06-14
Stochastic simulation of large biochemical reaction networks is often computationally expensive due to the disparate reaction rates and high variability of population of chemical species. An approach to accelerate the simulation is to allow multiple reaction firings before performing update by assuming that reaction propensities are changing of a negligible amount during a time interval. Species with small population in the firings of fast reactions significantly affect both performance and accuracy of this simulation approach. It is even worse when these small population species are involved in a large number of reactions. We present in this paper a new approximate algorithm to cope with this problem. It is based on bounding the acceptance probability of a reaction selected by the exact rejection-based simulation algorithm, which employs propensity bounds of reactions and the rejection-based mechanism to select next reaction firings. The reaction is ensured to be selected to fire with an acceptance rate greater than a predefined probability in which the selection becomes exact if the probability is set to one. Our new algorithm improves the computational cost for selecting the next reaction firing and reduces the updating the propensities of reactions.
A gravitational entropy proposal
International Nuclear Information System (INIS)
Clifton, Timothy; Tavakol, Reza; Ellis, George F R
2013-01-01
We propose a thermodynamically motivated measure of gravitational entropy based on the Bel–Robinson tensor, which has a natural interpretation as the effective super-energy–momentum tensor of free gravitational fields. The specific form of this measure differs depending on whether the gravitational field is Coulomb-like or wave-like, and reduces to the Bekenstein–Hawking value when integrated over the interior of a Schwarzschild black hole. For scalar perturbations of a Robertson–Walker geometry we find that the entropy goes like the Hubble weighted anisotropy of the gravitational field, and therefore increases as structure formation occurs. This is in keeping with our expectations for the behaviour of gravitational entropy in cosmology, and provides a thermodynamically motivated arrow of time for cosmological solutions of Einstein’s field equations. It is also in keeping with Penrose’s Weyl curvature hypothesis. (paper)
Microscopic entropy and nonlocality
International Nuclear Information System (INIS)
Karpov, E.; Ordonets, G.; Petroskij, T.; Prigozhin, I.
2003-01-01
We have obtained a microscopic expression for entropy in terms of H function based on nonunitary Λ transformation which leads from the time evolution as a unitary group to a Markovian dynamics and unifies the reversible and irreversible aspects of quantum mechanics. This requires a new representation outside the Hilbert space. In terms of H, we show the entropy production and the entropy flow during the emission and absorption of radiation by an atom. Analyzing the time inversion experiment, we emphasize the importance of pre- and postcollisional correlations, which break the symmetry between incoming and outgoing waves. We consider the angle dependence of the H function in a three-dimensional situation. A model including virtual transitions is discussed in a subsequent paper
International Nuclear Information System (INIS)
Kong Yan; Li Zhenjie; Ren Xin; Wang Chuan
2012-01-01
Nuclear power plants (NPPs) are very complex grey system, in which faults and signs have not certain corresponding connection, so it's hard to diagnose the faults. A model based on weighted degree of grey incidence of optimized entropy was proposed according to the problem. To validate the system, some simulation experiments about the typical faults of condenser of NPPs were conducted. The results show that the system's conclusion is right, and the system's velocity is fast which can satisfy diagnosis in real time, and with the distinctive features such as good stability, high resolution rate and so on. (authors)
Establishing the existence of a distance-based upper bound for a fuzzy DEA model using duality
International Nuclear Information System (INIS)
Soleimani-damaneh, M.
2009-01-01
In a recent paper [Soleimani-damaneh M. Fuzzy upper bounds and their applications. Chaos, Solitons and Fractals 2008;36:217-25.], I established the existence of a distance-based fuzzy upper bound for the objective function of a fuzzy DEA model, using the properties of a discussed signed distance, and provided an effective approach to solve that model. In this paper a new dual-based proof for the existence of the above-mentioned upper bound is provided which gives a useful insight into the theory of fuzzy DEA.
A New Feature Extraction Method Based on EEMD and Multi-Scale Fuzzy Entropy for Motor Bearing
Directory of Open Access Journals (Sweden)
Huimin Zhao
2016-12-01
Full Text Available 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.
Entropy production of stationary diffusions on non-compact Riemannian manifolds
Institute of Scientific and Technical Information of China (English)
龚光鲁; 钱敏平
1997-01-01
The closed form of the entropy production of stationary diffusion processes with bounded Nelson’s current velocity is given.The limit of the entropy productions of a sequence of reflecting diffusions is also discussed.
ERROR BOUNDS FOR SURFACE AREA ESTIMATORS BASED ON CROFTON’S FORMULA
Directory of Open Access Journals (Sweden)
Markus Kiderlen
2011-05-01
Full Text Available According to Crofton's formula, the surface area S(A of a sufficiently regular compact set A in Rd is proportional to the mean of all total projections pA (u on a linear hyperplane with normal u, uniformly averaged over all unit vectors u. In applications, pA (u is only measured in k directions and the mean is approximated by a finite weighted sum bS(A of the total projections in these directions. The choice of the weights depends on the selected quadrature rule. We define an associated zonotope Z (depending only on the projection directions and the quadrature rule, and show that the relative error bS (A/S (A is bounded from below by the inradius of Z and from above by the circumradius of Z. Applying a strengthened isoperimetric inequality due to Bonnesen, we show that the rectangular quadrature rule does not give the best possible error bounds for d =2. In addition, we derive asymptotic behavior of the error (with increasing k in the planar case. The paper concludes with applications to surface area estimation in design-based digital stereology where we show that the weights due to Bonnesen's inequality are better than the usual weights based on the rectangular rule and almost optimal in the sense that the relative error of the surface area estimator is very close to the minimal error.
A python-based docking program utilizing a receptor bound ligand shape: PythDock.
Chung, Jae Yoon; Cho, Seung Joo; Hah, Jung-Mi
2011-09-01
PythDock is a heuristic docking program that uses Python programming language with a simple scoring function and a population based search engine. The scoring function considers electrostatic and dispersion/repulsion terms. The search engine utilizes a particle swarm optimization algorithm. A grid potential map is generated using the shape information of a bound ligand within the active site. Therefore, the searching area is more relevant to the ligand binding. To evaluate the docking performance of PythDock, two well-known docking programs (AutoDock and DOCK) were also used with the same data. The accuracy of docked results were measured by the difference of the ligand structure between x-ray structure, and docked pose, i.e., average root mean squared deviation values of the bound ligand were compared for fourteen protein-ligand complexes. Since the number of ligands' rotational flexibility is an important factor affecting the accuracy of a docking, the data set was chosen to have various degrees of flexibility. Although PythDock has a scoring function simpler than those of other programs (AutoDock and DOCK), our results showed that PythDock predicted more accurate poses than both AutoDock4.2 and DOCK6.2. This indicates that PythDock could be a useful tool to study ligand-receptor interactions and could also be beneficial in structure based drug design.
Configurational entropy change of netropsin and distamycin upon DNA minor-groove binding.
Dolenc, Jozica; Baron, Riccardo; Oostenbrink, Chris; Koller, Joze; van Gunsteren, Wilfred F
2006-08-15
Binding of a small molecule to a macromolecular target reduces its conformational freedom, resulting in a negative entropy change that opposes the binding. The goal of this study is to estimate the configurational entropy change of two minor-groove-binding ligands, netropsin and distamycin, upon binding to the DNA duplex d(CGCGAAAAACGCG).d(CGCGTTTTTCGCG). Configurational entropy upper bounds based on 10-ns molecular dynamics simulations of netropsin and distamycin in solution and in complex with DNA in solution were estimated using the covariance matrix of atom-positional fluctuations. The results suggest that netropsin and distamycin lose a significant amount of configurational entropy upon binding to the DNA minor groove. The estimated changes in configurational entropy for netropsin and distamycin are -127 J K(-1) mol(-1) and -104 J K(-1) mol(-1), respectively. Estimates of the configurational entropy contributions of parts of the ligands are presented, showing that the loss of configurational entropy is comparatively more pronounced for the flexible tails than for the relatively rigid central body.
Ronglian, Yuan; Mingye, Ai; Qiaona, Jia; Yuxuan, Liu
2018-03-01
Sustainable development is the only way for the development of human society. As an important part of the national economy, the steel industry is an energy-intensive industry and needs to go further for sustainable development. In this paper, we use entropy method and Topsis method to evaluate the development of China’s steel industry during the “12th Five-Year Plan” from four aspects: resource utilization efficiency, main energy and material consumption, pollution status and resource reuse rate. And we also put forward some suggestions for the development of China’s steel industry.
DYNAMIC PARAMETER ESTIMATION BASED ON MINIMUM CROSS-ENTROPY METHOD FOR COMBINING INFORMATION SOURCES
Czech Academy of Sciences Publication Activity Database
Sečkárová, Vladimíra
2015-01-01
Roč. 24, č. 5 (2015), s. 181-188 ISSN 0204-9805. [XVI-th International Summer Conference on Probability and Statistics (ISCPS-2014). Pomorie, 21.6.-29.6.2014] R&D Projects: GA ČR GA13-13502S Grant - others:GA UK(CZ) SVV 260225/2015 Institutional support: RVO:67985556 Keywords : minimum cross- entropy principle * Kullback-Leibler divergence * dynamic diffusion estimation Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2015/AS/seckarova-0445817.pdf
Comprehensive benefits analysis of steel structure modular residence based on the entropy evaluation
Zhang, Xiaoxiao; Wang, Li; Jiang, Pengming
2017-04-01
Steel structure modular residence is the outstanding residential industrialization. It has many advantages, such as the low whole cost, high resource recovery, a high degree of industrialization. This paper compares the comprehensive benefits of steel structural in modular buildings with prefabricated reinforced concrete residential from economic benefits, environmental benefits, social benefits and technical benefits by the method of entropy evaluation. Finally, it is concluded that the comprehensive benefits of steel structural in modular buildings is better than that of prefabricated reinforced concrete residential. The conclusion of this study will provide certain reference significance to the development of steel structural in modular buildings in China.
Multivariate refined composite multiscale entropy analysis
International Nuclear Information System (INIS)
Humeau-Heurtier, Anne
2016-01-01
Multiscale entropy (MSE) has become a prevailing method to quantify signals complexity. MSE relies on sample entropy. However, MSE may yield imprecise complexity estimation at large scales, because sample entropy does not give precise estimation of entropy when short signals are processed. A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. Nevertheless, RCMSE is for univariate signals only. The simultaneous analysis of multi-channel (multivariate) data often over-performs studies based on univariate signals. We therefore introduce an extension of RCMSE to multivariate data. Applications of multivariate RCMSE to simulated processes reveal its better performances over the standard multivariate MSE. - Highlights: • Multiscale entropy quantifies data complexity but may be inaccurate at large scale. • A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. • Nevertheless, RCMSE is adapted to univariate time series only. • We herein introduce an extension of RCMSE to multivariate data. • It shows better performances than the standard multivariate multiscale entropy.
Directory of Open Access Journals (Sweden)
Li Pan
2016-03-01
Full Text Available Virtualization technologies make it possible for cloud providers to consolidate multiple IaaS provisions into a single server in the form of virtual machines (VMs. Additionally, in order to fulfill the divergent service requirements from multiple users, a cloud provider needs to offer several types of VM instances, which are associated with varying configurations and performance, as well as different prices. In such a heterogeneous virtual machine placement process, one significant problem faced by a cloud provider is how to optimally accept and place multiple VM service requests into its cloud data centers to achieve revenue maximization. To address this issue, in this paper, we first formulate such a revenue maximization problem during VM admission control as a multiple-dimensional knapsack problem, which is known to be NP-hard to solve. Then, we propose to use a cross-entropy-based optimization approach to address this revenue maximization problem, by obtaining a near-optimal eligible set for the provider to accept into its data centers, from the waiting VM service requests in the system. Finally, through extensive experiments and measurements in a simulated environment with the settings of VM instance classes derived from real-world cloud systems, we show that our proposed cross-entropy-based admission control optimization algorithm is efficient and effective in maximizing cloud providers’ revenue in a public cloud computing environment.
Zu, Xianghuan; Yang, Chuanlei; Wang, Hechun; Wang, Yinyan
2018-01-01
Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization.
Development of a statistically-based lower bound fracture toughness curve (Ksub(IR) curve)
International Nuclear Information System (INIS)
Wullaert, R.A.; Server, W.L.; Oldfield, W.; Stahlkopf, K.E.
1977-01-01
A program of initiation fracture toughness measurements on fifty heats of nuclear pressure vessel production materials (including weldments) was used to develop a methodology for establishing a revised reference toughness curve. The new methodology was statistically developed and provides a predefined confidence limit (or tolerance limit) for fracture toughness based upon many heats of a particular type of material. Overall reference curves were developed for seven specific materials using large specimen static and dynamic fracture toughness results. The heat-to-heat variation was removed by normalizing both the fracture toughness and temperature data with the precracked Charpy tanh curve coefficients for each particular heat. The variance and distribution about the curve were determined, and lower bounds of predetermined statistical significance were drawn based upon a Pearson distribution in the lower shelf region (since the data were skewed to high values) and a t-distribution in the transition temperature region (since the data were normally distributed)
Bounded Rational Managers Struggle with Talent Management - An Agent-based Modelling Approach
DEFF Research Database (Denmark)
Adamsen, Billy; Thomsen, Svend Erik
This study applies an agent-based modeling approach to explore some aspects of an important managerial task: finding and cultivating talented individuals capable of creating value for their organization at some future state. Given that the term talent in talent management is an empty signifier...... and its denotative meaning floating, we propose that bounded rational managers base their decisions on a simple heuristic, i.e. selecting and cultivating individuals so that their capabilities resemble their own capabilities the most (Adamsen 2015). We model the consequences of this talent management...... heuristic by varying the capabilities of today’s managers, which in turn impact which individuals will be selected as talent. We model the average level of capabilities and the distribution thereof in the sample where managers identify and select individuals from. We consider varying degrees of path...
Entropy-Based Experimental Design for Optimal Model Discrimination in the Geosciences
Directory of Open Access Journals (Sweden)
Wolfgang Nowak
2016-11-01
Full Text Available Choosing between competing models lies at the heart of scientific work, and is a frequent motivation for experimentation. Optimal experimental design (OD methods maximize the benefit of experiments towards a specified goal. We advance and demonstrate an OD approach to maximize the information gained towards model selection. We make use of so-called model choice indicators, which are random variables with an expected value equal to Bayesian model weights. Their uncertainty can be measured with Shannon entropy. Since the experimental data are still random variables in the planning phase of an experiment, we use mutual information (the expected reduction in Shannon entropy to quantify the information gained from a proposed experimental design. For implementation, we use the Preposterior Data Impact Assessor framework (PreDIA, because it is free of the lower-order approximations of mutual information often found in the geosciences. In comparison to other studies in statistics, our framework is not restricted to sequential design or to discrete-valued data, and it can handle measurement errors. As an application example, we optimize an experiment about the transport of contaminants in clay, featuring the problem of choosing between competing isotherms to describe sorption. We compare the results of optimizing towards maximum model discrimination with an alternative OD approach that minimizes the overall predictive uncertainty under model choice uncertainty.
Peng, Da; Yin, Cheng
2017-09-01
Locating small-scale discontinuities is one of the most challenging geophysical tasks; these subtle geological features are significant since they are often associated with subsurface petroleum traps. Subtle faults, fractures, unconformities, reef textures, channel boundaries, thin-bed boundaries and other structural and stratigraphic discontinuities have subtle geological edges which may provide lateral variation in seismic expression. Among the different geophysical techniques available, 3D seismic discontinuity attributes are particularly useful for highlighting discontinuities in the seismic data. Traditional seismic discontinuity attributes are sensitive to noise and are not very appropriate for detecting small-scale discontinuities. Thus, we present a dip-oriented gradient energy entropy (DOGEE) coherence estimation method to detect subtle faults and structural features. The DOGEE coherence estimation method uses the gradient structure tensor (GST) algorithm to obtain local dip information and construct a gradient correlation matrix to calculate gradient energy entropy. The proposed DOGEE coherence estimation method is robust to noise, and also improves the clarity of fault edges. It is effective for small-scale discontinuity characterisation and interpretation.
Directory of Open Access Journals (Sweden)
Guoqiang Xu
2017-10-01
Full Text Available Active control of heat flux can be realized with transformation optics (TO thermal metamaterials. Recently, a new class of metamaterial tunable cells has been proposed, aiming to significantly reduce the difficulty of fabrication and to flexibly switch functions by employing several cells assembled on related positions following the TO design. However, owing to the integration and rotation of materials in tunable cells, they might lead to extra thermal losses as compared with the previous continuum design. This paper focuses on investigating the thermodynamic properties of tunable cells under related design parameters. The universal expression for the local entropy generation rate in such metamaterial systems is obtained considering the influence of rotation. A series of contrast schemes are established to describe the thermodynamic process and thermal energy distributions from the viewpoint of entropy analysis. Moreover, effects of design parameters on thermal dissipations and system irreversibility are investigated. In conclusion, more thermal dissipations and stronger thermodynamic processes occur in a system with larger conductivity ratios and rotation angles. This paper presents a detailed description of the thermodynamic properties of metamaterial tunable cells and provides reference for selecting appropriate design parameters on related positions to fabricate more efficient and energy-economical switchable TO devices.
Entropy Based Test Point Evaluation and Selection Method for Analog Circuit Fault Diagnosis
Directory of Open Access Journals (Sweden)
Yuan Gao
2014-01-01
Full Text Available By simplifying tolerance problem and treating faulty voltages on different test points as independent variables, integer-coded table technique is proposed to simplify the test point selection process. Usually, simplifying tolerance problem may induce a wrong solution while the independence assumption will result in over conservative result. To address these problems, the tolerance problem is thoroughly considered in this paper, and dependency relationship between different test points is considered at the same time. A heuristic graph search method is proposed to facilitate the test point selection process. First, the information theoretic concept of entropy is used to evaluate the optimality of test point. The entropy is calculated by using the ambiguous sets and faulty voltage distribution, determined by component tolerance. Second, the selected optimal test point is used to expand current graph node by using dependence relationship between the test point and graph node. Simulated results indicate that the proposed method more accurately finds the optimal set of test points than other methods; therefore, it is a good solution to minimize the size of the test point set. To simplify and clarify the proposed method, only catastrophic and some specific parametric faults are discussed in this paper.
Optimization of source and detector configurations based on Cramer-Rao lower bound analysis
Chen, Ling; Chen, Nanguang
2011-03-01
Optimization of source and detector (SD) arrangements in a diffuse optical tomography system is helpful for improving measurements' sensitivity to localized changes in imaging domain and enhancing the capacity of noise resistance. We introduced a rigorous and computationally efficient methodology and adapt it into the diffuse optics field to realize the optimizations of SD arrangements. Our method is based on Cramer-Rao lower bound analysis, which combines the diffusion-forward model and a noise model together. This method can be used to investigate the performance of the SD arrangements through quantitative estimations of lower bounds of the standard variances of the reconstructed perturbation depths and values. More importantly, it provides direct estimations of parameters without solving the inverse problem. Simulations are conducted in the reflection geometry to validate the effectiveness of the method on selections of the optimized SD sets, with a fixed number of sources and detectors, from an SD group on a planar probe surface. The impacts of different noise levels and target perturbation depths are considered in the simulations. It is demonstrated that the SD sets selected by this method afford better reconstructed images. This methodology can be adapted to other probe surfaces and other imaging geometries.
A film-based wall shear stress sensor for wall-bounded turbulent flows
Amili, Omid; Soria, Julio
2011-07-01
In wall-bounded turbulent flows, determination of wall shear stress is an important task. The main objective of the present work is to develop a sensor which is capable of measuring surface shear stress over an extended region applicable to wall-bounded turbulent flows. This sensor, as a direct method for measuring wall shear stress, consists of mounting a thin flexible film on the solid surface. The sensor is made of a homogeneous, isotropic, and incompressible material. The geometry and mechanical properties of the film are measured, and particles with the nominal size of 11 μm in diameter are embedded on the film's surface to act as markers. An optical technique is used to measure the film deformation caused by the flow. The film has typically deflection of less than 2% of the material thickness under maximum loading. The sensor sensitivity can be adjusted by changing the thickness of the layer or the shear modulus of the film's material. The paper reports the sensor fabrication, static and dynamic calibration procedure, and its application to a fully developed turbulent channel flow at Reynolds numbers in the range of 90,000-130,000 based on the bulk velocity and channel full height. The results are compared to alternative wall shear stress measurement methods.
Directory of Open Access Journals (Sweden)
Aneta Daniel
2016-03-01
Full Text Available The subject of the investigation is the translation of neologism and culture-bound items based on the first chapter of the third book of The Witcher Saga, entitled Baptism of Fire. The analyzed fragment abounds in neologisms and nomenclature; therefore, the processes of word formation are briefly described. Furthermore, some of Hejwowski’s ([2004] 2009, pp. 76–83 procedures are cited to present methods of dealing with the creativity resulting from word formation processes. It is shown that a translator, when translating culture-bound items, is not always able to find an equivalent in the target language and may try either to describe a certain phenomenon or to use a literal translation. The way in which neologisms are coined in a fictional novel may differ from the coinage of words in the standard language; nevertheless, the word formation processes are the same as in Standard English or Standard Polish. Moreover, there is still little evidence of what makes a borrowed word catch on in the standard language.
Autonomous Positioning Techniques Based on Cramér-Rao Lower Bound Analysis
Directory of Open Access Journals (Sweden)
Urruela Andreu
2006-01-01
Full Text Available We consider the problem of autonomously locating a number of asynchronous sensor nodes in a wireless network. A strong focus lies on reducing the processing resources needed to solve the relative positioning problem, an issue of great interest in resource-constrained wireless sensor networks. In the first part of the paper, based on a well-known derivation of the Cramér-Rao lower bound for the asynchronous sensor positioning problem, we are able to construct optimal preprocessing methods for sensor clock-offset cancellation. A cancellation of unknown clock-offsets from the asynchronous positioning problem reduces processing requirements, and, under certain reasonable assumptions, allows for statistically efficient distributed positioning algorithms. Cramér-Rao lower bound theory may also be used for estimating the performance of a positioning algorithm. In the second part of this paper, we exploit this property in developing a distributed algorithm, where the global positioning problem is solved suboptimally, using a divide-and-conquer approach of low complexity. The performance of this suboptimal algorithm is evaluated through computer simulation, and compared to previously published algorithms.
Efficient decoupling schemes with bounded controls based on Eulerian orthogonal arrays
International Nuclear Information System (INIS)
Wocjan, Pawel
2006-01-01
The task of decoupling, i.e., removing unwanted internal couplings of a quantum system and its couplings to an environment, plays an important role in quantum control theory. There are many efficient decoupling schemes based on combinatorial concepts such as orthogonal arrays, difference schemes, and Hadamard matrices. So far these combinatorial decoupling schemes have relied on the ability to effect sequences of instantaneous, arbitrarily strong control Hamiltonians (bang-bang controls). To overcome the shortcomings of bang-bang control, Viola and Knill proposed a method called 'Eulerian decoupling' that allows the use of bounded-strength controls for decoupling. However, their method was not directly designed to take advantage of the local structure of internal couplings and couplings to an environment that typically occur in multipartite quantum systems. In this paper we define a combinatorial structure called Eulerian orthogonal array. It merges the desirable properties of orthogonal arrays and Eulerian cycles in Cayley graphs (that are the basis of Eulerian decoupling). We show that this structure gives rise to decoupling schemes with bounded-strength control Hamiltonians that can be used to remove both internal couplings and couplings to an environment of a multipartite quantum system. Furthermore, we show how to construct Eulerian orthogonal arrays having good parameters in order to obtain efficient decoupling schemes
Directory of Open Access Journals (Sweden)
F. TopsÃƒÂ¸e
2001-09-01
Full Text Available Abstract: In its modern formulation, the Maximum Entropy Principle was promoted by E.T. Jaynes, starting in the mid-fifties. The principle dictates that one should look for a distribution, consistent with available information, which maximizes the entropy. However, this principle focuses only on distributions and it appears advantageous to bring information theoretical thinking more prominently into play by also focusing on the "observer" and on coding. This view was brought forward by the second named author in the late seventies and is the view we will follow-up on here. It leads to the consideration of a certain game, the Code Length Game and, via standard game theoretical thinking, to a principle of Game Theoretical Equilibrium. This principle is more basic than the Maximum Entropy Principle in the sense that the search for one type of optimal strategies in the Code Length Game translates directly into the search for distributions with maximum entropy. In the present paper we offer a self-contained and comprehensive treatment of fundamentals of both principles mentioned, based on a study of the Code Length Game. Though new concepts and results are presented, the reading should be instructional and accessible to a rather wide audience, at least if certain mathematical details are left aside at a rst reading. The most frequently studied instance of entropy maximization pertains to the Mean Energy Model which involves a moment constraint related to a given function, here taken to represent "energy". This type of application is very well known from the literature with hundreds of applications pertaining to several different elds and will also here serve as important illustration of the theory. But our approach reaches further, especially regarding the study of continuity properties of the entropy function, and this leads to new results which allow a discussion of models with so-called entropy loss. These results have tempted us to speculate over
Aur, Dorian; Vila-Rodriguez, Fidel
2017-01-01
Complexity measures for time series have been used in many applications to quantify the regularity of one dimensional time series, however many dynamical systems are spatially distributed multidimensional systems. We introduced Dynamic Cross-Entropy (DCE) a novel multidimensional complexity measure that quantifies the degree of regularity of EEG signals in selected frequency bands. Time series generated by discrete logistic equations with varying control parameter r are used to test DCE measures. Sliding window DCE analyses are able to reveal specific period doubling bifurcations that lead to chaos. A similar behavior can be observed in seizures triggered by electroconvulsive therapy (ECT). Sample entropy data show the level of signal complexity in different phases of the ictal ECT. The transition to irregular activity is preceded by the occurrence of cyclic regular behavior. A significant increase of DCE values in successive order from high frequencies in gamma to low frequencies in delta band reveals several phase transitions into less ordered states, possible chaos in the human brain. To our knowledge there are no reliable techniques able to reveal the transition to chaos in case of multidimensional times series. In addition, DCE based on sample entropy appears to be robust to EEG artifacts compared to DCE based on Shannon entropy. The applied technique may offer new approaches to better understand nonlinear brain activity. Copyright Â© 2016 Elsevier B.V. All rights reserved.
Optimized Kernel Entropy Components.
Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau
2017-06-01
This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.
Directory of Open Access Journals (Sweden)
Jorge Pereira
2015-12-01
Full Text Available Biological invasion by exotic organisms became a key issue, a concern associated to the deep impacts on several domains described as resultant from such processes. A better understanding of the processes, the identification of more susceptible areas, and the definition of preventive or mitigation measures are identified as critical for the purpose of reducing associated impacts. The use of species distribution modeling might help on the purpose of identifying areas that are more susceptible to invasion. This paper aims to present preliminary results on assessing the susceptibility to invasion by the exotic species Acacia dealbata Mill. in the Ceira river basin. The results are based on the maximum entropy modeling approach, considered one of the correlative modelling techniques with better predictive performance. Models which validation is based on independent data sets present better performance, an evaluation based on the AUC of ROC accuracy measure.
Entropy estimates for simple random fields
DEFF Research Database (Denmark)
Forchhammer, Søren; Justesen, Jørn
1995-01-01
We consider the problem of determining the maximum entropy of a discrete random field on a lattice subject to certain local constraints on symbol configurations. The results are expected to be of interest in the analysis of digitized images and two dimensional codes. We shall present some examples...... of binary and ternary fields with simple constraints. Exact results on the entropies are known only in a few cases, but we shall present close bounds and estimates that are computationally efficient...
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Kartik V. Bulusu
2015-09-01
Full Text Available The coherent secondary flow structures (i.e., swirling motions in a curved artery model possess a variety of spatio-temporal morphologies and can be encoded over an infinitely-wide range of wavelet scales. Wavelet analysis was applied to the following vorticity fields: (i a numerically-generated system of Oseen-type vortices for which the theoretical solution is known, used for bench marking and evaluation of the technique; and (ii experimental two-dimensional, particle image velocimetry data. The mother wavelet, a two-dimensional Ricker wavelet, can be dilated to infinitely large or infinitesimally small scales. We approached the problem of coherent structure detection by means of continuous wavelet transform (CWT and decomposition (or Shannon entropy. The main conclusion of this study is that the encoding of coherent secondary flow structures can be achieved by an optimal number of binary digits (or bits corresponding to an optimal wavelet scale. The optimal wavelet-scale search was driven by a decomposition entropy-based algorithmic approach and led to a threshold-free coherent structure detection method. The method presented in this paper was successfully utilized in the detection of secondary flow structures in three clinically-relevant blood flow scenarios involving the curved artery model under a carotid artery-inspired, pulsatile inflow condition. These scenarios were: (i a clean curved artery; (ii stent-implanted curved artery; and (iii an idealized Type IV stent fracture within the curved artery.
Entropy-Based Method of Choosing the Decomposition Level in Wavelet Threshold De-noising
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Yan-Fang Sang
2010-06-01
Full Text Available In this paper, the energy distributions of various noises following normal, log-normal and Pearson-III distributions are first described quantitatively using the wavelet energy entropy (WEE, and the results are compared and discussed. Then, on the basis of these analytic results, a method for use in choosing the decomposition level (DL in wavelet threshold de-noising (WTD is put forward. Finally, the performance of the proposed method is verified by analysis of both synthetic and observed series. Analytic results indicate that the proposed method is easy to operate and suitable for various signals. Moreover, contrary to traditional white noise testing which depends on “autocorrelations”, the proposed method uses energy distributions to distinguish real signals and noise in noisy series, therefore the chosen DL is reliable, and the WTD results of time series can be improved.
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Xiao-ping Bai
2013-01-01
Full Text Available Selecting construction schemes of the building engineering project is a complex multiobjective optimization decision process, in which many indexes need to be selected to find the optimum scheme. Aiming at this problem, this paper selects cost, progress, quality, and safety as the four first-order evaluation indexes, uses the quantitative method for the cost index, uses integrated qualitative and quantitative methodologies for progress, quality, and safety indexes, and integrates engineering economics, reliability theories, and information entropy theory to present a new evaluation method for building construction project. Combined with a practical case, this paper also presents detailed computing processes and steps, including selecting all order indexes, establishing the index matrix, computing score values of all order indexes, computing the synthesis score, sorting all selected schemes, and making analysis and decision. Presented method can offer valuable references for risk computing of building construction projects.
Maximum entropy based reconstruction of soft X ray emissivity profiles in W7-AS
International Nuclear Information System (INIS)
Ertl, K.; Linden, W. von der; Dose, V.; Weller, A.
1996-01-01
The reconstruction of 2-D emissivity profiles from soft X ray tomography measurements constitutes a highly underdetermined and ill-posed inversion problem, because of the restricted viewing access, the number of chords and the increased noise level in most plasma devices. An unbiased and consistent probabilistic approach within the framework of Bayesian inference is provided by the maximum entropy method, which is independent of model assumptions, but allows any prior knowledge available to be incorporated. The formalism is applied to the reconstruction of emissivity profiles in an NBI heated plasma discharge to determine the dependence of the Shafranov shift on β, the reduction of which was a particular objective in designing the advanced W7-AS stellarator. (author). 40 refs, 7 figs
International Nuclear Information System (INIS)
Avci, E.
2007-01-01
In this paper, an automatic system is presented for word recognition using real Turkish word signals. This paper especially deals with combination of the feature extraction and classification from real Turkish word signals. A Discrete Wavelet Neural Network (DWNN) model is used, which consists of two layers: discrete wavelet layer and multi-layer perceptron. The discrete wavelet layer is used for adaptive feature extraction in the time-frequency domain and is composed of Discrete Wavelet Transform (DWT) and wavelet entropy. The multi-layer perceptron used for classification is a feed-forward neural network. The performance of the used system is evaluated by using noisy Turkish word signals. Test results showing the effectiveness of the proposed automatic system are presented in this paper. The rate of correct recognition is about 92.5% for the sample speech signals. (author)
Bai, Xiao-ping; Zhang, Xi-wei
2013-01-01
Selecting construction schemes of the building engineering project is a complex multiobjective optimization decision process, in which many indexes need to be selected to find the optimum scheme. Aiming at this problem, this paper selects cost, progress, quality, and safety as the four first-order evaluation indexes, uses the quantitative method for the cost index, uses integrated qualitative and quantitative methodologies for progress, quality, and safety indexes, and integrates engineering economics, reliability theories, and information entropy theory to present a new evaluation method for building construction project. Combined with a practical case, this paper also presents detailed computing processes and steps, including selecting all order indexes, establishing the index matrix, computing score values of all order indexes, computing the synthesis score, sorting all selected schemes, and making analysis and decision. Presented method can offer valuable references for risk computing of building construction projects.
The integration of weighted gene association networks based on information entropy.
Yang, Fan; Wu, Duzhi; Lin, Limei; Yang, Jian; Yang, Tinghong; Zhao, Jing
2017-01-01
Constructing genome scale weighted gene association networks (WGAN) from multiple data sources is one of research hot spots in systems biology. In this paper, we employ information entropy to describe the uncertain degree of gene-gene links and propose a strategy for data integration of weighted networks. We use this method to integrate four existing human weighted gene association networks and construct a much larger WGAN, which includes richer biology information while still keeps high functional relevance between linked gene pairs. The new WGAN shows satisfactory performance in disease gene prediction, which suggests the reliability of our integration strategy. Compared with existing integration methods, our method takes the advantage of the inherent characteristics of the component networks and pays less attention to the biology background of the data. It can make full use of existing biological networks with low computational effort.
Entropy and Graph Based Modelling of Document Coherence using Discourse Entities
DEFF Research Database (Denmark)
Petersen, Casper; Lioma, Christina; Simonsen, Jakob Grue
2015-01-01
We present two novel models of document coherence and their application to information retrieval (IR). Both models approximate document coherence using discourse entities, e.g. the subject or object of a sentence. Our first model views text as a Markov process generating sequences of discourse...... entities (entity n-grams); we use the entropy of these entity n-grams to approximate the rate at which new information appears in text, reasoning that as more new words appear, the topic increasingly drifts and text coherence decreases. Our second model extends the work of Guinaudeau & Strube [28......] that represents text as a graph of discourse entities, linked by different relations, such as their distance or adjacency in text. We use several graph topology metrics to approximate different aspects of the discourse flow that can indicate coherence, such as the average clustering or betweenness of discourse...
Directory of Open Access Journals (Sweden)
Enrico Sciubba
2011-06-01
Full Text Available In this paper, the entropy generation minimization (EGM method is applied to an industrial heat transfer problem: the forced convective cooling of a LED-based spotlight. The design specification calls for eighteen diodes arranged on a circular copper plate of 35 mm diameter. Every diode dissipates 3 W and the maximum allowedtemperature of the plate is 80 °C. The cooling relies on the forced convection driven by a jet of air impinging on the plate. An initial complex geometry of plate fins is presented and analyzed with a commercial CFD code that computes the entropy generation rate. A pseudo-optimization process is carried out via a successive series of design modifications based on a careful analysis of the entropy generation maps. One of the advantages of the EGM method is that the rationale behind each step of the design process can be justified on a physical basis. It is found that the best performance is attained when the fins are periodically spaced in the radial direction.
Enthalpy-entropy compensation in protein unfolding
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
Enthalpy-entropy compensation was found to be a universal law in protein unfolding based on over 3 000 experimental data. Water molecular reorganization accompanying the protein unfolding was suggested as the origin of the enthalpy-entropy compensation in protein unfolding. It is indicated that the enthalpy-entropy compensation constitutes the physical foundation that satisfies the biological need of the small free energy changes in protein unfolding, without the sacrifice of the bio-diversity of proteins. The enthalpy-entropy compensation theory proposed herein also provides valuable insights into the Privalov's puzzle of enthalpy and entropy convergence in protein unfolding.
Controlling the Shannon Entropy of Quantum Systems
Xing, Yifan; Wu, Jun
2013-01-01
This paper proposes a new quantum control method which controls the Shannon entropy of quantum systems. For both discrete and continuous entropies, controller design methods are proposed based on probability density function control, which can drive the quantum state to any target state. To drive the entropy to any target at any prespecified time, another discretization method is proposed for the discrete entropy case, and the conditions under which the entropy can be increased or decreased are discussed. Simulations are done on both two- and three-dimensional quantum systems, where division and prediction are used to achieve more accurate tracking. PMID:23818819
Controlling the Shannon Entropy of Quantum Systems
Directory of Open Access Journals (Sweden)
Yifan Xing
2013-01-01
Full Text Available This paper proposes a new quantum control method which controls the Shannon entropy of quantum systems. For both discrete and continuous entropies, controller design methods are proposed based on probability density function control, which can drive the quantum state to any target state. To drive the entropy to any target at any prespecified time, another discretization method is proposed for the discrete entropy case, and the conditions under which the entropy can be increased or decreased are discussed. Simulations are done on both two- and three-dimensional quantum systems, where division and prediction are used to achieve more accurate tracking.
Excess Entropy and Diffusivity
Indian Academy of Sciences (India)
First page Back Continue Last page Graphics. Excess Entropy and Diffusivity. Excess entropy scaling of diffusivity (Rosenfeld,1977). Analogous relationships also exist for viscosity and thermal conductivity.
Statistical properties of entropy production derived from fluctuation theorems
International Nuclear Information System (INIS)
Merhav, Neri; Kafri, Yariv
2010-01-01
Several implications of well-known fluctuation theorems, on the statistical properties of entropy production, are studied using various approaches. We begin by deriving a tight lower bound on the variance of the entropy production for a given mean of this random variable. It is shown that the Evans–Searles fluctuation theorem alone imposes a significant lower bound on the variance only when the mean entropy production is very small. It is then nonetheless demonstrated that upon incorporating additional information concerning the entropy production, this lower bound can be significantly improved, so as to capture extensivity properties. Another important aspect of the fluctuation properties of the entropy production is the relationship between the mean and the variance, on the one hand, and the probability of the event where the entropy production is negative, on the other hand. Accordingly, we derive upper and lower bounds on this probability in terms of the mean and the variance. These bounds are tighter than previous bounds that can be found in the literature. Moreover, they are tight in the sense that there exist probability distributions, satisfying the Evans–Searles fluctuation theorem, that achieve them with equality. Finally, we present a general method for generating a wide class of inequalities that must be satisfied by the entropy production. We use this method to derive several new inequalities that go beyond the standard derivation of the second law
Wall-based identification of coherent structures in wall-bounded turbulence
Sanmiguel Vila, C.; Flores, O.
2018-04-01
During the last decades, a number of reduced order models based on coherent structures have been proposed to describe wall-bounded turbulence. Many of these models emphasize the importance of coherent wall-normal velocity eddies (ν-eddies), which drive the generation of the very long streamwise velocity structures observed in the logarithmic and outer region. In order to use these models to improve our ability to control wall-bounded turbulence in realistic applications, these ν-eddies need to be identified from the wall in a non-intrusive way. In this paper, the possibility of using the pressure signal at the wall to identify these ν-eddies is explored, analyzing the cross-correlation between the wall-normal velocity component and the pressure fluctuations at the wall in a DNS of a turbulent channel flow at Reτ = 939. The results show that the cross-correlation has a region of negative correlation upstream, and a region of positive correlation backwards. In the spanwise direction the correlation decays monotonously, except very close to the wall where a change of sign of the correlation coefficient is observed. Moreover, filtering the pressure fluctuations at the wall in space results in an increase of the region where the cross-correlation is strong, both for the positively and the negatively correlated regions. The use of a time filter for the pressure fluctuations at the wall yields different results, displacing the regions of strong correlation without changing much their sizes. The results suggest that space-filtering the pressure at the wall is a feasible way to identify ν-eddies of different sizes, which could be used to trigger turbulent control strategies.
Tight bounds on the size of neural networks for classification problems
Energy Technology Data Exchange (ETDEWEB)
Beiu, V. [Los Alamos National Lab., NM (United States); Pauw, T. de [Universite Catholique de Louvain, Louvain-la-Neuve (Belgium). Dept. de Mathematique
1997-06-01
This paper relies on the entropy of a data-set (i.e., number-of-bits) to prove tight bounds on the size of neural networks solving a classification problem. First, based on a sequence of geometrical steps, the authors constructively compute an upper bound of O(mn) on the number-of-bits for a given data-set - here m is the number of examples and n is the number of dimensions (i.e., R{sup n}). This result is used further in a nonconstructive way to bound the size of neural networks which correctly classify that data-set.
Explaining the entropy concept and entropy components
Directory of Open Access Journals (Sweden)
Marko Popovic
2018-04-01
Full Text Available Total entropy of a thermodynamic system consists of two components: thermal entropy due to energy, and residual entropy due to molecular orientation. In this article, a three-step method for explaining entropy is suggested. Step one is to use a classical method to introduce thermal entropy STM as a function of temperature T and heat capacity at constant pressure Cp: STM = ∫(Cp/T dT. Thermal entropy is the entropy due to uncertainty in motion of molecules and vanishes at absolute zero (zero-point energy state. It is also the measure of useless thermal energy that cannot be converted into useful work. The next step is to introduce residual entropy S0 as a function of the number of molecules N and the number of distinct orientations available to them in a crystal m: S0 = N kB ln m, where kB is the Boltzmann constant. Residual entropy quantifies the uncertainty in molecular orientation. Residual entropy, unlike thermal entropy, is independent of temperature and remains present at absolute zero. The third step is to show that thermal entropy and residual entropy add up to the total entropy of a thermodynamic system S: S = S0 + STM. This method of explanation should result in a better comprehension of residual entropy and thermal entropy, as well as of their similarities and differences. The new method was tested in teaching at Faculty of Chemistry University of Belgrade, Serbia. The results of the test show that the new method has a potential to improve the quality of teaching.
McPeake, John D.; And Others
1991-01-01
Describes adolescent chemical dependency treatment model developed at Beech Hill Hospital (New Hampshire) which integrated Twelve Step-oriented alcohol and drug rehabilitation program with experiential education school, Hurricane Island Outward Bound School. Describes Beech Hill Hurricane Island Outward Bound School Adolescent Chemical Dependency…
Maravall, Darío; de Lope, Javier; Fuentes, Juan P
2017-01-01
We introduce a hybrid algorithm for the self-semantic location and autonomous navigation of robots using entropy-based vision and visual topological maps. In visual topological maps the visual landmarks are considered as leave points for guiding the robot to reach a target point (robot homing) in indoor environments. These visual landmarks are defined from images of relevant objects or characteristic scenes in the environment. The entropy of an image is directly related to the presence of a unique object or the presence of several different objects inside it: the lower the entropy the higher the probability of containing a single object inside it and, conversely, the higher the entropy the higher the probability of containing several objects inside it. Consequently, we propose the use of the entropy of images captured by the robot not only for the landmark searching and detection but also for obstacle avoidance. If the detected object corresponds to a landmark, the robot uses the suggestions stored in the visual topological map to reach the next landmark or to finish the mission. Otherwise, the robot considers the object as an obstacle and starts a collision avoidance maneuver. In order to validate the proposal we have defined an experimental framework in which the visual bug algorithm is used by an Unmanned Aerial Vehicle (UAV) in typical indoor navigation tasks.
Directory of Open Access Journals (Sweden)
Darío Maravall
2017-08-01
Full Text Available We introduce a hybrid algorithm for the self-semantic location and autonomous navigation of robots using entropy-based vision and visual topological maps. In visual topological maps the visual landmarks are considered as leave points for guiding the robot to reach a target point (robot homing in indoor environments. These visual landmarks are defined from images of relevant objects or characteristic scenes in the environment. The entropy of an image is directly related to the presence of a unique object or the presence of several different objects inside it: the lower the entropy the higher the probability of containing a single object inside it and, conversely, the higher the entropy the higher the probability of containing several objects inside it. Consequently, we propose the use of the entropy of images captured by the robot not only for the landmark searching and detection but also for obstacle avoidance. If the detected object corresponds to a landmark, the robot uses the suggestions stored in the visual topological map to reach the next landmark or to finish the mission. Otherwise, the robot considers the object as an obstacle and starts a collision avoidance maneuver. In order to validate the proposal we have defined an experimental framework in which the visual bug algorithm is used by an Unmanned Aerial Vehicle (UAV in typical indoor navigation tasks.
Entropic Lower Bound for Distinguishability of Quantum States
Directory of Open Access Journals (Sweden)
Seungho Yang
2015-01-01
Full Text Available For a system randomly prepared in a number of quantum states, we present a lower bound for the distinguishability of the quantum states, that is, the success probability of determining the states in the form of entropy. When the states are all pure, acquiring the entropic lower bound requires only the density operator and the number of the possible states. This entropic bound shows a relation between the von Neumann entropy and the distinguishability.
Zucker, M. H.
This paper is a critical analysis and reassessment of entropic functioning as it applies to the question of whether the ultimate fate of the universe will be determined in the future to be "open" (expanding forever to expire in a big chill), "closed" (collapsing to a big crunch), or "flat" (balanced forever between the two). The second law of thermodynamics declares that entropy can only increase and that this principle extends, inevitably, to the universe as a whole. This paper takes the position that this extension is an unwarranted projection based neither on experience nonfact - an extrapolation that ignores the powerful effect of a gravitational force acting within a closed system. Since it was originally presented by Clausius, the thermodynamic concept of entropy has been redefined in terms of "order" and "disorder" - order being equated with a low degree of entropy and disorder with a high degree. This revised terminology more subjective than precise, has generated considerable confusion in cosmology in several critical instances. For example - the chaotic fireball of the big bang, interpreted by Stephen Hawking as a state of disorder (high entropy), is infinitely hot and, thermally, represents zero entropy (order). Hawking, apparently focusing on the disorderly "chaotic" aspect, equated it with a high degree of entropy - overlooking the fact that the universe is a thermodynamic system and that the key factor in evaluating the big-bang phenomenon is the infinitely high temperature at the early universe, which can only be equated with zero entropy. This analysis resolves this confusion and reestablishes entropy as a cosmological function integrally linked to temperature. The paper goes on to show that, while all subsystems contained within the universe require external sources of energization to have their temperatures raised, this requirement does not apply to the universe as a whole. The universe is the only system that, by itself can raise its own
Xiang, Min; Qu, Qinqin; Chen, Cheng; Tian, Li; Zeng, Lingkang
2017-11-01
To improve the reliability of communication service in smart distribution grid (SDG), an access selection algorithm based on dynamic network status and different service types for heterogeneous wireless networks was proposed. The network performance index values were obtained in real time by multimode terminal and the variation trend of index values was analyzed by the growth matrix. The index weights were calculated by entropy-weight and then modified by rough set to get the final weights. Combining the grey relational analysis to sort the candidate networks, and the optimum communication network is selected. Simulation results show that the proposed algorithm can implement dynamically access selection in heterogeneous wireless networks of SDG effectively and reduce the network blocking probability.
Entropy considerations in constraining the mSUGRA parameter space
International Nuclear Information System (INIS)
Nunez, Dario; Sussman, Roberto A.; Zavala, Jesus; Nellen, Lukas; Cabral-Rosetti, Luis G.; Mondragon, Myriam
2006-01-01
We explore the use of two criteria to constraint the allowed parameter space in mSUGRA models. Both criteria are based in the calculation of the present density of neutralinos as dark matter in the Universe. The first one is the usual ''abundance'' criterion which is used to calculate the relic density after the ''freeze-out'' era. To compute the relic density we used the numerical public code micrOMEGAs. The second criterion applies the microcanonical definition of entropy to a weakly interacting and self-gravitating gas evaluating then the change in the entropy per particle of this gas between the ''freeze-out'' era and present day virialized structures (i.e systems in virial equilibrium). An ''entropy-consistency'' criterion emerges by comparing theoretical and empirical estimates of this entropy. The main objective of our work is to determine for which regions of the parameter space in the mSUGRA model are both criteria consistent with the 2σ bounds according to WMAP for the relic density: 0.0945 < ΩCDMh2 < 0.1287. As a first result, we found that for A0 = 0, sgnμ +, small values of tanβ are not favored; only for tanβ ≅ 50 are both criteria significantly consistent
Wavelet entropy characterization of elevated intracranial pressure.
Xu, Peng; Scalzo, Fabien; Bergsneider, Marvin; Vespa, Paul; Chad, Miller; Hu, Xiao
2008-01-01
Intracranial Hypertension (ICH) often occurs for those patients with traumatic brain injury (TBI), stroke, tumor, etc. Pathology of ICH is still controversial. In this work, we used wavelet entropy and relative wavelet entropy to study the difference existed between normal and hypertension states of ICP for the first time. The wavelet entropy revealed the similar findings as the approximation entropy that entropy during ICH state is smaller than that in normal state. Moreover, with wavelet entropy, we can see that ICH state has the more focused energy in the low wavelet frequency band (0-3.1 Hz) than the normal state. The relative wavelet entropy shows that the energy distribution in the wavelet bands between these two states is actually different. Based on these results, we suggest that ICH may be formed by the re-allocation of oscillation energy within brain.
Analysis of Neural Oscillations on Drosophila’s Subesophageal Ganglion Based on Approximate Entropy
Directory of Open Access Journals (Sweden)
Tian Mei
2015-10-01
Full Text Available The suboesophageal ganglion (SOG, which connects to both central and peripheral nerves, is the primary taste-processing center in the Drosophila’s brain. The neural oscillation in this center may be of great research value yet it is rarely reported. This work aims to determine the amount of unique information contained within oscillations of the SOG and describe the variability of these patterns. The approximate entropy (ApEn values of the spontaneous membrane potential (sMP of SOG neurons were calculated in this paper. The arithmetic mean (MA, standard deviation (SDA and the coefficient of variation (CVA of ApEn were proposed as the three statistical indicators to describe the irregularity and complexity of oscillations. The hierarchical clustering method was used to classify them. As a result, the oscillations in SOG were divided into five categories, including: (1 Continuous spike pattern; (2 Mixed oscillation pattern; (3 Spikelet pattern; (4 Busting pattern and (5 Sparse spike pattern. Steady oscillation state has a low level of irregularity, and vice versa. The dopamine stimulation can distinctly cut down the complexity of the mixed oscillation pattern. The current study provides a quantitative method and some critera on mining the information carried in neural oscillations.
Entropy Based Feature Selection for Fuzzy Set-Valued Information Systems
Ahmed, Waseem; Sufyan Beg, M. M.; Ahmad, Tanvir
2018-06-01
In Set-valued Information Systems (SIS), several objects contain more than one value for some attributes. Tolerance relation used for handling SIS sometimes leads to loss of certain information. To surmount this problem, fuzzy rough model was introduced. However, in some cases, SIS may contain some real or continuous set-values. Therefore, the existing fuzzy rough model for handling Information system with fuzzy set-values needs some changes. In this paper, Fuzzy Set-valued Information System (FSIS) is proposed and fuzzy similarity relation for FSIS is defined. Yager's relative conditional entropy was studied to find the significance measure of a candidate attribute of FSIS. Later, using these significance values, three greedy forward algorithms are discussed for finding the reduct and relative reduct for the proposed FSIS. An experiment was conducted on a sample population of the real dataset and a comparison of classification accuracies of the proposed FSIS with the existing SIS and single-valued Fuzzy Information Systems was made, which demonstrated the effectiveness of proposed FSIS.
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Qian Yang
2016-08-01
Full Text Available Urban ecosystem health evaluation can assist in sustainable ecological management at a regional level. This study examined urban agglomeration ecosystem health in the middle reaches of the Yangtze River with entropy weight and extension theories. The model overcomes information omissions and subjectivity problems in the evaluation process of urban ecosystem health. Results showed that human capital and education, economic development level as well as urban infrastructure have a significant effect on the health states of urban agglomerations. The health status of the urban agglomeration’s ecosystem was not optimistic in 2013. The majority of the cities were unhealthy or verging on unhealthy, accounting for 64.52% of the total number of cities in the urban agglomeration. The regional differences of the 31 cities’ ecosystem health are significant. The cause originated from an imbalance in economic development and the policy guidance of city development. It is necessary to speed up the integration process to promote coordinated regional development. The present study will aid us in understanding and advancing the health situation of the urban ecosystem in the middle reaches of the Yangtze River and will provide an efficient urban ecosystem health evaluation method that can be used in other areas.
Entropy-Based Application Layer DDoS Attack Detection Using Artificial Neural Networks
Directory of Open Access Journals (Sweden)
Khundrakpam Johnson Singh
2016-10-01
Full Text Available Distributed denial-of-service (DDoS attack is one of the major threats to the web server. The rapid increase of DDoS attacks on the Internet has clearly pointed out the limitations in current intrusion detection systems or intrusion prevention systems (IDS/IPS, mostly caused by application-layer DDoS attacks. Within this context, the objective of the paper is to detect a DDoS attack using a multilayer perceptron (MLP classification algorithm with genetic algorithm (GA as learning algorithm. In this work, we analyzed the standard EPA-HTTP (environmental protection agency-hypertext transfer protocol dataset and selected the parameters that will be used as input to the classifier model for differentiating the attack from normal profile. The parameters selected are the HTTP GET request count, entropy, and variance for every connection. The proposed model can provide a better accuracy of 98.31%, sensitivity of 0.9962, and specificity of 0.0561 when compared to other traditional classification models.
Directory of Open Access Journals (Sweden)
Guo-Jheng Yang
2013-08-01
Full Text Available The fragile watermarking technique is used to protect intellectual property rights while also providing security and rigorous protection. In order to protect the copyright of the creators, it can be implanted in some representative text or totem. Because all of the media on the Internet are digital, protection has become a critical issue, and determining how to use digital watermarks to protect digital media is thus the topic of our research. This paper uses the Logistic map with parameter u = 4 to generate chaotic dynamic behavior with the maximum entropy 1. This approach increases the security and rigor of the protection. The main research target of information hiding is determining how to hide confidential data so that the naked eye cannot see the difference. Next, we introduce one method of information hiding. Generally speaking, if the image only goes through Arnold’s cat map and the Logistic map, it seems to lack sufficient security. Therefore, our emphasis is on controlling Arnold’s cat map and the initial value of the chaos system to undergo small changes and generate different chaos sequences. Thus, the current time is used to not only make encryption more stringent but also to enhance the security of the digital media.
Pathological brain detection based on wavelet entropy and Hu moment invariants.
Zhang, Yudong; Wang, Shuihua; Sun, Ping; Phillips, Preetha
2015-01-01
With the aim of developing an accurate pathological brain detection system, we proposed a novel automatic computer-aided diagnosis (CAD) to detect pathological brains from normal brains obtained by magnetic resonance imaging (MRI) scanning. The problem still remained a challenge for technicians and clinicians, since MR imaging generated an exceptionally large information dataset. A new two-step approach was proposed in this study. We used wavelet entropy (WE) and Hu moment invariants (HMI) for feature extraction, and the generalized eigenvalue proximal support vector machine (GEPSVM) for classification. To further enhance classification accuracy, the popular radial basis function (RBF) kernel was employed. The 10 runs of k-fold stratified cross validation result showed that the proposed "WE + HMI + GEPSVM + RBF" method was superior to existing methods w.r.t. classification accuracy. It obtained the average classification accuracies of 100%, 100%, and 99.45% over Dataset-66, Dataset-160, and Dataset-255, respectively. The proposed method is effective and can be applied to realistic use.
Directory of Open Access Journals (Sweden)
Yimeng Zhang
2013-05-01
Full Text Available A method of blind recognition of the coding parameters for binary Bose-Chaudhuri-Hocquenghem (BCH codes is proposed in this paper. We consider an intelligent communication receiver which can blindly recognize the coding parameters of the received data stream. The only knowledge is that the stream is encoded using binary BCH codes, while the coding parameters are unknown. The problem can be addressed on the context of the non-cooperative communications or adaptive coding and modulations (ACM for cognitive radio networks. The recognition processing includes two major procedures: code length estimation and generator polynomial reconstruction. A hard decision method has been proposed in a previous literature. In this paper we propose the recognition approach in soft decision situations with Binary-Phase-Shift-Key modulations and Additive-White-Gaussian-Noise (AWGN channels. The code length is estimated by maximizing the root information dispersion entropy function. And then we search for the code roots to reconstruct the primitive and generator polynomials. By utilizing the soft output of the channel, the recognition performance is improved and the simulations show the efficiency of the proposed algorithm.
Environmental efficiency analysis of power industry in China based on an entropy SBM model
International Nuclear Information System (INIS)
Zhou, Yan; Xing, Xinpeng; Fang, Kuangnan; Liang, Dapeng; Xu, Chunlin
2013-01-01
In order to assess the environmental efficiency of power industry in China, this paper first proposes a new non-radial DEA approach by integrating the entropy weight and the SBM model. This will improve the assessment reliability and reasonableness. Using the model, this study then evaluates the environmental efficiency of the Chinese power industry at the provincial level during 2005–2010. The results show a marked difference in environmental efficiency of the power industry among Chinese provinces. Although the annual, average, environmental efficiency level fluctuates, there is an increasing trend. The Tobit regression analysis reveals the innovation ability of enterprises, the proportion of electricity generated by coal-fired plants and the generation capacity have a significantly positive effect on environmental efficiency. However the waste fees levied on waste discharge and investment in industrial pollutant treatment are negatively associated with environmental efficiency. - Highlights: ► We assess the environmental efficiency of power industry in China by E-SBM model. ► Environmental efficiency of power industry is different among provinces. ► Efficiency stays at a higher level in the eastern and the western area. ► Proportion of coal-fired plants has a positive effect on the efficiency. ► Waste fees and the investment have a negative effect on the efficiency
Coarse-graining using the relative entropy and simplex-based optimization methods in VOTCA
Rühle, Victor; Jochum, Mara; Koschke, Konstantin; Aluru, N. R.; Kremer, Kurt; Mashayak, S. Y.; Junghans, Christoph
2014-03-01
Coarse-grained (CG) simulations are an important tool to investigate systems on larger time and length scales. Several methods for systematic coarse-graining were developed, varying in complexity and the property of interest. Thus, the question arises which method best suits a specific class of system and desired application. The Versatile Object-oriented Toolkit for Coarse-graining Applications (VOTCA) provides a uniform platform for coarse-graining methods and allows for their direct comparison. We present recent advances of VOTCA, namely the implementation of the relative entropy method and downhill simplex optimization for coarse-graining. The methods are illustrated by coarse-graining SPC/E bulk water and a water-methanol mixture. Both CG models reproduce the pair distributions accurately. SYM is supported by AFOSR under grant 11157642 and by NSF under grant 1264282. CJ was supported in part by the NSF PHY11-25915 at KITP. K. Koschke acknowledges funding by the Nestle Research Center.
Tackling Information Asymmetry in Networks: A New Entropy-Based Ranking Index
Barucca, Paolo; Caldarelli, Guido; Squartini, Tiziano
2018-06-01
Information is a valuable asset in socio-economic systems, a significant part of which is entailed into the network of connections between agents. The different interlinkages patterns that agents establish may, in fact, lead to asymmetries in the knowledge of the network structure; since this entails a different ability of quantifying relevant, systemic properties (e.g. the risk of contagion in a network of liabilities), agents capable of providing a better estimation of (otherwise) inaccessible network properties, ultimately have a competitive advantage. In this paper, we address the issue of quantifying the information asymmetry of nodes: to this aim, we define a novel index—InfoRank—intended to rank nodes according to their information content. In order to do so, each node ego-network is enforced as a constraint of an entropy-maximization problem and the subsequent uncertainty reduction is used to quantify the node-specific accessible information. We, then, test the performance of our ranking procedure in terms of reconstruction accuracy and show that it outperforms other centrality measures in identifying the "most informative" nodes. Finally, we discuss the socio-economic implications of network information asymmetry.
Shao, Xingling; Wang, Honglun
2015-01-01
This paper investigates a novel compound control scheme combined with the advantages of trajectory linearization control (TLC) and alternative active disturbance rejection control (ADRC) for hypersonic reentry vehicle (HRV) attitude tracking system with bounded uncertainties. Firstly, in order to overcome actuator saturation problem, nonlinear tracking differentiator (TD) is applied in the attitude loop to achieve fewer control consumption. Then, linear extended state observers (LESO) are constructed to estimate the uncertainties acting on the LTV system in the attitude and angular rate loop. In addition, feedback linearization (FL) based controllers are designed using estimates of uncertainties generated by LESO in each loop, which enable the tracking error for closed-loop system in the presence of large uncertainties to converge to the residual set of the origin asymptotically. Finally, the compound controllers are derived by integrating with the nominal controller for open-loop nonlinear system and FL based controller. Also, comparisons and simulation results are presented to illustrate the effectiveness of the control strategy. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
A Theoretical Basis for Entropy-Scaling Effects in Human Mobility Patterns.
Osgood, Nathaniel D; Paul, Tuhin; Stanley, Kevin G; Qian, Weicheng
2016-01-01
Characterizing how people move through space has been an important component of many disciplines. With the advent of automated data collection through GPS and other location sensing systems, researchers have the opportunity to examine human mobility at spatio-temporal resolution heretofore impossible. However, the copious and complex data collected through these logging systems can be difficult for humans to fully exploit, leading many researchers to propose novel metrics for encapsulating movement patterns in succinct and useful ways. A particularly salient proposed metric is the mobility entropy rate of the string representing the sequence of locations visited by an individual. However, mobility entropy rate is not scale invariant: entropy rate calculations based on measurements of the same trajectory at varying spatial or temporal granularity do not yield the same value, limiting the utility of mobility entropy rate as a metric by confounding inter-experimental comparisons. In this paper, we derive a scaling relationship for mobility entropy rate of non-repeating straight line paths from the definition of Lempel-Ziv compression. We show that the resulting formulation predicts the scaling behavior of simulated mobility traces, and provides an upper bound on mobility entropy rate under certain assumptions. We further show that this formulation has a maximum value for a particular sampling rate, implying that optimal sampling rates for particular movement patterns exist.
Electroencephalogram–Electromyography Coupling Analysis in Stroke Based on Symbolic Transfer Entropy
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Yunyuan Gao
2018-01-01
Full Text Available The coupling strength between electroencephalogram (EEG and electromyography (EMG signals during motion control reflects the interaction between the cerebral motor cortex and muscles. Therefore, neuromuscular coupling characterization is instructive in assessing motor function. In this study, to overcome the limitation of losing the characteristics of signals in conventional time series symbolization methods, a variable scale symbolic transfer entropy (VS-STE analysis approach was proposed for corticomuscular coupling evaluation. Post-stroke patients (n = 5 and healthy volunteers (n = 7 were recruited and participated in various tasks (left and right hand gripping, elbow bending. The proposed VS-STE was employed to evaluate the corticomuscular coupling strength between the EEG signal measured from the motor cortex and EMG signal measured from the upper limb in both the time-domain and frequency-domain. Results showed a greater strength of the bi-directional (EEG-to-EMG and EMG-to-EEG VS-STE in post-stroke patients compared to healthy controls. In addition, the strongest EEG–EMG coupling strength was observed in the beta frequency band (15–35 Hz during the upper limb movement. The predefined coupling strength of EMG-to-EEG in the affected side of the patient was larger than that of EEG-to-EMG. In conclusion, the results suggested that the corticomuscular coupling is bi-directional, and the proposed VS-STE can be used to quantitatively characterize the non-linear synchronization characteristics and information interaction between the primary motor cortex and muscles.
A new accuracy measure based on bounded relative error for time series forecasting.
Chen, Chao; Twycross, Jamie; Garibaldi, Jonathan M
2017-01-01
Many accuracy measures have been proposed in the past for time series forecasting comparisons. However, many of these measures suffer from one or more issues such as poor resistance to outliers and scale dependence. In this paper, while summarising commonly used accuracy measures, a special review is made on the symmetric mean absolute percentage error. Moreover, a new accuracy measure called the Unscaled Mean Bounded Relative Absolute Error (UMBRAE), which combines the best features of various alternative measures, is proposed to address the common issues of existing measures. A comparative evaluation on the proposed and related measures has been made with both synthetic and real-world data. The results indicate that the proposed measure, with user selectable benchmark, performs as well as or better than other measures on selected criteria. Though it has been commonly accepted that there is no single best accuracy measure, we suggest that UMBRAE could be a good choice to evaluate forecasting methods, especially for cases where measures based on geometric mean of relative errors, such as the geometric mean relative absolute error, are preferred.
Topological entropy of continuous functions on topological spaces
International Nuclear Information System (INIS)
Liu Lei; Wang Yangeng; Wei Guo
2009-01-01
Adler, Konheim and McAndrew introduced the concept of topological entropy of a continuous mapping for compact dynamical systems. Bowen generalized the concept to non-compact metric spaces, but Walters indicated that Bowen's entropy is metric-dependent. We propose a new definition of topological entropy for continuous mappings on arbitrary topological spaces (compactness, metrizability, even axioms of separation not necessarily required), investigate fundamental properties of the new entropy, and compare the new entropy with the existing ones. The defined entropy generates that of Adler, Konheim and McAndrew and is metric-independent for metrizable spaces. Yet, it holds various basic properties of Adler, Konheim and McAndrew's entropy, e.g., the entropy of a subsystem is bounded by that of the original system, topologically conjugated systems have a same entropy, the entropy of the induced hyperspace system is larger than or equal to that of the original system, and in particular this new entropy coincides with Adler, Konheim and McAndrew's entropy for compact systems
Bubble Entropy: An Entropy Almost Free of Parameters.
Manis, George; Aktaruzzaman, Md; Sassi, Roberto
2017-11-01
Objective : A critical point in any definition of entropy is the selection of the parameters employed to obtain an estimate in practice. We propose a new definition of entropy aiming to reduce the significance of this selection. Methods: We call the new definition Bubble Entropy . Bubble Entropy is based on permutation entropy, where the vectors in the embedding space are ranked. We use the bubble sort algorithm for the ordering procedure and count instead the number of swaps performed for each vector. Doing so, we create a more coarse-grained distribution and then compute the entropy of this distribution. Results: Experimental results with both real and synthetic HRV signals showed that bubble entropy presents remarkable stability and exhibits increased descriptive and discriminating power compared to all other definitions, including the most popular ones. Conclusion: The definition proposed is almost free of parameters. The most common ones are the scale factor r and the embedding dimension m . In our definition, the scale factor is totally eliminated and the importance of m is significantly reduced. The proposed method presents increased stability and discriminating power. Significance: After the extensive use of some entropy measures in physiological signals, typical values for their parameters have been suggested, or at least, widely used. However, the parameters are still there, application and dataset dependent, influencing the computed value and affecting the descriptive power. Reducing their significance or eliminating them alleviates the problem, decoupling the method from the data and the application, and eliminating subjective factors. Objective : A critical point in any definition of entropy is the selection of the parameters employed to obtain an estimate in practice. We propose a new definition of entropy aiming to reduce the significance of this selection. Methods: We call the new definition Bubble Entropy . Bubble Entropy is based on permutation
Entropy Stability and the No-Slip Wall Boundary Condition
Svä rd, Magnus; Carpenter, Mark H.; Parsani, Matteo
2018-01-01
We present an entropy stable numerical scheme subject to no-slip wall boundary conditions. To enforce entropy stability only the no-penetration boundary condition and a temperature condition are needed at a wall, and this leads to an L bound on the conservative variables. In this article, we take the next step and design a finite difference scheme that also bounds the velocity gradients. This necessitates the use of the full no-slip conditions.
Entropy Stability and the No-Slip Wall Boundary Condition
Svärd, Magnus
2018-01-18
We present an entropy stable numerical scheme subject to no-slip wall boundary conditions. To enforce entropy stability only the no-penetration boundary condition and a temperature condition are needed at a wall, and this leads to an L bound on the conservative variables. In this article, we take the next step and design a finite difference scheme that also bounds the velocity gradients. This necessitates the use of the full no-slip conditions.
SpatEntropy: Spatial Entropy Measures in R
Altieri, Linda; Cocchi, Daniela; Roli, Giulia
2018-01-01
This article illustrates how to measure the heterogeneity of spatial data presenting a finite number of categories via computation of spatial entropy. The R package SpatEntropy contains functions for the computation of entropy and spatial entropy measures. The extension to spatial entropy measures is a unique feature of SpatEntropy. In addition to the traditional version of Shannon's entropy, the package includes Batty's spatial entropy, O'Neill's entropy, Li and Reynolds' contagion index, Ka...
Directory of Open Access Journals (Sweden)
Bernard S. Kay
2015-12-01
Full Text Available We give a review, in the style of an essay, of the author’s 1998 matter-gravity entanglement hypothesis which, unlike the standard approach to entropy based on coarse-graining, offers a definition for the entropy of a closed system as a real and objective quantity. We explain how this approach offers an explanation for the Second Law of Thermodynamics in general and a non-paradoxical understanding of information loss during black hole formation and evaporation in particular. It also involves a radically different from usual description of black hole equilibrium states in which the total state of a black hole in a box together with its atmosphere is a pure state—entangled in just such a way that the reduced state of the black hole and of its atmosphere are each separately approximately thermal. We also briefly recall some recent work of the author which involves a reworking of the string-theory understanding of black hole entropy consistent with this alternative description of black hole equilibrium states and point out that this is free from some unsatisfactory features of the usual string theory understanding. We also recall the author’s recent arguments based on this alternative description which suggest that the Anti de Sitter space (AdS/conformal field theory (CFT correspondence is a bijection between the boundary CFT and just the matter degrees of freedom of the bulk theory.
Entropy in molecular recognition by proteins.
Caro, José A; Harpole, Kyle W; Kasinath, Vignesh; Lim, Jackwee; Granja, Jeffrey; Valentine, Kathleen G; Sharp, Kim A; Wand, A Joshua
2017-06-20
Molecular recognition by proteins is fundamental to molecular biology. Dissection of the thermodynamic energy terms governing protein-ligand interactions has proven difficult, with determination of entropic contributions being particularly elusive. NMR relaxation measurements have suggested that changes in protein conformational entropy can be quantitatively obtained through a dynamical proxy, but the generality of this relationship has not been shown. Twenty-eight protein-ligand complexes are used to show a quantitative relationship between measures of fast side-chain motion and the underlying conformational entropy. We find that the contribution of conformational entropy can range from favorable to unfavorable, which demonstrates the potential of this thermodynamic variable to modulate protein-ligand interactions. For about one-quarter of these complexes, the absence of conformational entropy would render the resulting affinity biologically meaningless. The dynamical proxy for conformational entropy or "entropy meter" also allows for refinement of the contributions of solvent entropy and the loss in rotational-translational entropy accompanying formation of high-affinity complexes. Furthermore, structure-based application of the approach can also provide insight into long-lived specific water-protein interactions that escape the generic treatments of solvent entropy based simply on changes in accessible surface area. These results provide a comprehensive and unified view of the general role of entropy in high-affinity molecular recognition by proteins.
Dynamical noise filter and conditional entropy analysis in chaos synchronization.
Wang, Jiao; Lai, C-H
2006-06-01
It is shown that, in a chaotic synchronization system whose driving signal is exposed to channel noise, the estimation of the drive system states can be greatly improved by applying the dynamical noise filtering to the response system states. If the noise is bounded in a certain range, the estimation errors, i.e., the difference between the filtered responding states and the driving states, can be made arbitrarily small. This property can be used in designing an alternative digital communication scheme. An analysis based on the conditional entropy justifies the application of dynamical noise filtering in generating quality synchronization.
On Uniform Decay of the Entropy for Reaction–Diffusion Systems
Mielke, Alexander
2014-09-10
This work provides entropy decay estimates for classes of nonlinear reaction–diffusion systems modeling reversible chemical reactions under the detailed-balance condition. We obtain explicit bounds for the exponential decay of the relative logarithmic entropy, being based essentially on the application of the Log-Sobolev estimate and a convexification argument only, making it quite robust to model variations. An important feature of our analysis is the interaction of the two different dissipative mechanisms: pure diffusion, forcing the system asymptotically to the homogeneous state, and pure reaction, forcing the solution to the (possibly inhomogeneous) chemical equilibrium. Only the interaction of both mechanisms provides the convergence to the homogeneous equilibrium. Moreover, we introduce two generalizations of the main result: (i) vanishing diffusion constants in some chemical components and (ii) usage of different entropy functionals. We provide a few examples to highlight the usability of our approach and shortly discuss possible further applications and open questions.
Integrating Entropy-Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard.
Liu, Rui; Chen, Yun; Wu, Jianping; Gao, Lei; Barrett, Damian; Xu, Tingbao; Li, Xiaojuan; Li, Linyi; Huang, Chang; Yu, Jia
2017-04-01
Regional flood risk caused by intensive rainfall under extreme climate conditions has increasingly attracted global attention. Mapping and evaluation of flood hazard are vital parts in flood risk assessment. This study develops an integrated framework for estimating spatial likelihood of flood hazard by coupling weighted naïve Bayes (WNB), geographic information system, and remote sensing. The north part of Fitzroy River Basin in Queensland, Australia, was selected as a case study site. The environmental indices, including extreme rainfall, evapotranspiration, net-water index, soil water retention, elevation, slope, drainage proximity, and density, were generated from spatial data representing climate, soil, vegetation, hydrology, and topography. These indices were weighted using the statistics-based entropy method. The weighted indices were input into the WNB-based model to delineate a regional flood risk map that indicates the likelihood of flood occurrence. The resultant map was validated by the maximum inundation extent extracted from moderate resolution imaging spectroradiometer (MODIS) imagery. The evaluation results, including mapping and evaluation of the distribution of flood hazard, are helpful in guiding flood inundation disaster responses for the region. The novel approach presented consists of weighted grid data, image-based sampling and validation, cell-by-cell probability inferring and spatial mapping. It is superior to an existing spatial naive Bayes (NB) method for regional flood hazard assessment. It can also be extended to other likelihood-related environmental hazard studies. © 2016 Society for Risk Analysis.
Directory of Open Access Journals (Sweden)
Qing Ye
2015-01-01
Full Text Available This research proposes a novel framework of final drive simultaneous failure diagnosis containing feature extraction, training paired diagnostic models, generating decision threshold, and recognizing simultaneous failure modes. In feature extraction module, adopt wavelet package transform and fuzzy entropy to reduce noise interference and extract representative features of failure mode. Use single failure sample to construct probability classifiers based on paired sparse Bayesian extreme learning machine which is trained only by single failure modes and have high generalization and sparsity of sparse Bayesian learning approach. To generate optimal decision threshold which can convert probability output obtained from classifiers into final simultaneous failure modes, this research proposes using samples containing both single and simultaneous failure modes and Grid search method which is superior to traditional techniques in global optimization. Compared with other frequently used diagnostic approaches based on support vector machine and probability neural networks, experiment results based on F1-measure value verify that the diagnostic accuracy and efficiency of the proposed framework which are crucial for simultaneous failure diagnosis are superior to the existing approach.
Maximizing Entropy over Markov Processes
DEFF Research Database (Denmark)
Biondi, Fabrizio; Legay, Axel; Nielsen, Bo Friis
2013-01-01
The channel capacity of a deterministic system with confidential data is an upper bound on the amount of bits of data an attacker can learn from the system. We encode all possible attacks to a system using a probabilistic specification, an Interval Markov Chain. Then the channel capacity...... as a reward function, a polynomial algorithm to verify the existence of an system maximizing entropy among those respecting a specification, a procedure for the maximization of reward functions over Interval Markov Chains and its application to synthesize an implementation maximizing entropy. We show how...... to use Interval Markov Chains to model abstractions of deterministic systems with confidential data, and use the above results to compute their channel capacity. These results are a foundation for ongoing work on computing channel capacity for abstractions of programs derived from code....
Maximizing entropy over Markov processes
DEFF Research Database (Denmark)
Biondi, Fabrizio; Legay, Axel; Nielsen, Bo Friis
2014-01-01
The channel capacity of a deterministic system with confidential data is an upper bound on the amount of bits of data an attacker can learn from the system. We encode all possible attacks to a system using a probabilistic specification, an Interval Markov Chain. Then the channel capacity...... as a reward function, a polynomial algorithm to verify the existence of a system maximizing entropy among those respecting a specification, a procedure for the maximization of reward functions over Interval Markov Chains and its application to synthesize an implementation maximizing entropy. We show how...... to use Interval Markov Chains to model abstractions of deterministic systems with confidential data, and use the above results to compute their channel capacity. These results are a foundation for ongoing work on computing channel capacity for abstractions of programs derived from code. © 2014 Elsevier...
Black hole entropy functions and attractor equations
International Nuclear Information System (INIS)
Lopes Cardoso, Gabriel; Wit, Bernard de; Mahapatra, Swapna
2007-01-01
The entropy and the attractor equations for static extremal black hole solutions follow from a variational principle based on an entropy function. In the general case such an entropy function can be derived from the reduced action evaluated in a near-horizon geometry. BPS black holes constitute special solutions of this variational principle, but they can also be derived directly from a different entropy function based on supersymmetry enhancement at the horizon. Both functions are consistent with electric/magnetic duality and for BPS black holes their corresponding OSV-type integrals give identical results at the semi-classical level. We clarify the relation between the two entropy functions and the corresponding attractor equations for N = 2 supergravity theories with higher-derivative couplings in four space-time dimensions. We discuss how non-holomorphic corrections will modify these entropy functions
Energy Technology Data Exchange (ETDEWEB)
Marc O Delchini; Jean E. Ragusa; Ray A. Berry
2015-07-01
We present a new version of the entropy viscosity method, a viscous regularization technique for hyperbolic conservation laws, that is well-suited for low-Mach flows. By means of a low-Mach asymptotic study, new expressions for the entropy viscosity coefficients are derived. These definitions are valid for a wide range of Mach numbers, from subsonic flows (with very low Mach numbers) to supersonic flows, and no longer depend on an analytical expression for the entropy function. In addition, the entropy viscosity method is extended to Euler equations with variable area for nozzle flow problems. The effectiveness of the method is demonstrated using various 1-D and 2-D benchmark tests: flow in a converging–diverging nozzle; Leblanc shock tube; slow moving shock; strong shock for liquid phase; low-Mach flows around a cylinder and over a circular hump; and supersonic flow in a compression corner. Convergence studies are performed for smooth solutions and solutions with shocks present.
Properties of Risk Measures of Generalized Entropy in Portfolio Selection
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Rongxi Zhou
2017-12-01
Full Text Available This paper systematically investigates the properties of six kinds of entropy-based risk measures: Information Entropy and Cumulative Residual Entropy in the probability space, Fuzzy Entropy, Credibility Entropy and Sine Entropy in the fuzzy space, and Hybrid Entropy in the hybridized uncertainty of both fuzziness and randomness. We discover that none of the risk measures satisfy all six of the following properties, which various scholars have associated with effective risk measures: Monotonicity, Translation Invariance, Sub-additivity, Positive Homogeneity, Consistency and Convexity. Measures based on Fuzzy Entropy, Credibility Entropy, and Sine Entropy all exhibit the same properties: Sub-additivity, Positive Homogeneity, Consistency, and Convexity. These measures based on Information Entropy and Hybrid Entropy, meanwhile, only exhibit Sub-additivity and Consistency. Cumulative Residual Entropy satisfies just Sub-additivity, Positive Homogeneity, and Convexity. After identifying these properties, we develop seven portfolio models based on different risk measures and made empirical comparisons using samples from both the Shenzhen Stock Exchange of China and the New York Stock Exchange of America. The comparisons show that the Mean Fuzzy Entropy Model performs the best among the seven models with respect to both daily returns and relative cumulative returns. Overall, these results could provide an important reference for both constructing effective risk measures and rationally selecting the appropriate risk measure under different portfolio selection conditions.
Mishra, V.; Cruise, J. F.; Mecikalski, J. R.
2015-12-01
Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Earlier studies show that the principle of maximum entropy (POME) can be utilized to develop vertical soil moisture profiles with accuracy (MAE of about 1% for a monotonically dry profile; nearly 2% for monotonically wet profiles and 3.8% for mixed profiles) with minimum constraints (surface, mean and bottom soil moisture contents). In this study, the constraints for the vertical soil moisture profiles were obtained from remotely sensed data. Low resolution (25 km) MW soil moisture estimates (AMSR-E) were downscaled to 4 km using a soil evaporation efficiency index based disaggregation approach. The downscaled MW soil moisture estimates served as a surface boundary condition, while 4 km resolution TIR based Atmospheric Land Exchange Inverse (ALEXI) estimates provided the required mean root-zone soil moisture content. Bottom soil moisture content is assumed to be a soil dependent constant. Mulit-year (2002-2011) gridded profiles were developed for the southeastern United States using the POME method. The soil moisture profiles were compared to those generated in land surface models (Land Information System (LIS) and an agricultural model DSSAT) along with available NRCS SCAN sites in the study region. The end product, spatial soil moisture profiles, can be assimilated into agricultural and hydrologic models in lieu of precipitation for data scarce regions.Developing accurate vertical soil moisture profiles with minimum input requirements is important to agricultural as well as land surface modeling. Previous studies have shown that the principle of maximum entropy (POME) can be utilized with minimal constraints to develop vertical soil moisture profiles with accuracy (MAE = 1% for monotonically dry profiles; MAE = 2% for monotonically wet profiles and MAE = 3.8% for mixed profiles) when compared to laboratory and field
Entropy of self-gravitating radiation
International Nuclear Information System (INIS)
Sorkin, R.D.; Wald, R.M.; Jiu, Z.Z.
1981-01-01
The entropy of self-gravitating radiation confined to a spherical box of radius R is examined in the context of general relativity. It is expected that configurations (i.e., initial data) which extremize total entropy will be spherically symmetric, time symmetric distributions of radiation in local thermodynamic equilibrium. Assuming this is the case, it is proved that extrema of S coincide precisely with static equilibrium configurations of the radiation fluid. Furthermore, dynamically stable equilibrium configurations are shown to coincide with local maxima of S. The equilibrium configurations and their entropies are calculated and their properties are discussed. However, it is shown that entropies higher than these local extrema can be achieved and, indeed, arbitrarily high entropies can be attained by configurations inside of or outside but arbitrarily near their own Schwarzschild radius. However, consideration is limited to configurations which are outside their own Schwarzschild radius by at least one radiation wavelength, then the entropy is bounded and it is found Ssub(max) < is approximately equal to MR, where M is the total mass. This supports the validity for self-gravitating systems of the Bekenstein upper limit on the entropy to energy ratio of material bodies. (author)
New Definition and Properties of Fuzzy Entropy
Institute of Scientific and Technical Information of China (English)
Qing Ming; Qin Yingbing
2006-01-01
Let X = (x1,x2 ,…,xn ) and F(X) be a fuzzy set on a universal set X. A new definition of fuzzy entropy about a fuzzy set A on F(X), e*, is defined based on the order relation "≤" on [0,1/2] n. It is proved that e* is a σ-entropy under an additional requirement. Besides, some entropy formulas are presented and related properties are discussed.
Permutation Entropy: New Ideas and Challenges
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Karsten Keller
2017-03-01
Full Text Available Over recent years, some new variants of Permutation entropy have been introduced and applied to EEG analysis, including a conditional variant and variants using some additional metric information or being based on entropies that are different from the Shannon entropy. In some situations, it is not completely clear what kind of information the new measures and their algorithmic implementations provide. We discuss the new developments and illustrate them for EEG data.
Entropy In the Universe: A New Approach
Directory of Open Access Journals (Sweden)
Antonio Alfonso-Faus
2000-09-01
Full Text Available Abstract: We propose a new definition of entropy for any mass m, based on gravitation and through the concept of a gravitational cross section. It turns out to be proportional to mass, and therefore extensive, and to the age of the Universe. It is a Machian approach. It is also the number of gravity quanta the mass has emitted through its age. The entropy of the Uni-verse is so determined and the cosmological entropy problem solved.
Directory of Open Access Journals (Sweden)
Chengquan Zhou
2018-02-01
Full Text Available To obtain an accurate count of wheat spikes, which is crucial for estimating yield, this paper proposes a new algorithm that uses computer vision to achieve this goal from an image. First, a home-built semi-autonomous multi-sensor field-based phenotype platform (FPP is used to obtain orthographic images of wheat plots at the filling stage. The data acquisition system of the FPP provides high-definition RGB images and multispectral images of the corresponding quadrats. Then, the high-definition panchromatic images are obtained by fusion of three channels of RGB. The Gram–Schmidt fusion algorithm is then used to fuse these multispectral and panchromatic images, thereby improving the color identification degree of the targets. Next, the maximum entropy segmentation method is used to do the coarse-segmentation. The threshold of this method is determined by a firefly algorithm based on chaos theory (FACT, and then a morphological filter is used to de-noise the coarse-segmentation results. Finally, morphological reconstruction theory is applied to segment the adhesive part of the de-noised image and realize the fine-segmentation of the image. The computer-generated counting results for the wheat plots, using independent regional statistical function in Matlab R2017b software, are then compared with field measurements which indicate that the proposed method provides a more accurate count of wheat spikes when compared with other traditional fusion and segmentation methods mentioned in this paper.
DEFF Research Database (Denmark)
Emiris, Ioannis Z.; Mourrain, Bernard; Tsigaridas, Elias
2010-01-01
) resultant by means of mixed volume, as well as recent advances on aggregate root bounds for univariate polynomials, and are applicable to arbitrary positive dimensional systems. We improve upon Canny's gap theorem [7] by a factor of O(dn-1), where d bounds the degree of the polynomials, and n is the number...... bound on the number of steps that subdivision-based algorithms perform in order to isolate all real roots of a polynomial system. This leads to the first complexity bound of Milne's algorithm [22] in 2D....
The improvement of Clausius entropy and its application in entropy analysis
Institute of Scientific and Technical Information of China (English)
WU Jing; GUO ZengYuan
2008-01-01
The defects of Cleusius entropy which Include s premise of reversible process and a process quantlty of heat in Its definition are discussed in this paper. Moreover, the heat temperature quotient under reversible conditions, i.e. (δQ/T)rev, is essentially a process quantity although it is numerically equal to the entropy change. The sum of internal energy temperature quotient and work temperature quotient is defined as the improved form of Clausius entropy and it can be further proved to be a state funcllon. Unlike Clausius entropy, the improved deflnltion consists of system properties wlthout premise just like other state functions, for example, pressure p and enthalpy h, etc. it is unnecessary to invent reversible paths when calculating entropy change for irreversible processes based on the improved form of entropy since it is independent of process. Furthermore, entropy balance equations for internally and externally irreversible processes are deduced respectively based on the concepts of thermal reservoir entropy transfer and system entropy transfer. Finally, some examples are presented to show that the improved deflnitlon of Clausius entropy provides a clear concept as well as a convenient method for en-tropy change calculation.
de Klerk, Etienne; Laurent, Monique; Sun, Zhao
We consider the problem of minimizing a continuous function f over a compact set K. We analyze a hierarchy of upper bounds proposed by Lasserre (SIAM J Optim 21(3):864–885, 2011), obtained by searching for an optimal probability density function h on K which is a sum of squares of polynomials, so
de Klerk, E.; Laurent, M.; Sun, Z.
2014-01-01
We consider the problem of minimizing a continuous function f over a compact set K. We analyze a hierarchy of upper bounds proposed by Lasserre in [SIAM J. Optim. 21(3) (2011), pp. 864--885], obtained by searching for an optimal probability density function h on K which is a sum of squares of
Bounded Rationality and Satisficing in Young People's Web-Based Decision Making.
Agosto, Denise E.
2002-01-01
Investigated behavioral decision-making theories of bounded rationality and satisficing in relation to young people's decision making in the World Wide Web and considered the role of personal preferences. Results of this study of ninth- and tenth-grade females consider time constraints, information overload, physical constraints, reduction…
Quantum dynamical entropy revisited
International Nuclear Information System (INIS)
Hudetz, T.
1996-10-01
We define a new quantum dynamical entropy, which is a 'hybrid' of the closely related, physically oriented entropy introduced by Alicki and Fannes in 1994, and of the mathematically well-developed, single-argument entropy introduced by Connes, Narnhofer and Thirring in 1987. We show that this new quantum dynamical entropy has many properties similar to the ones of the Alicki-Fannes entropy, and also inherits some additional properties from the CNT entropy. In particular, the 'hybrid' entropy interpolates between the two different ways in which both the AF and the CNT entropy of the shift automorphism on the quantum spin chain agree with the usual quantum entropy density, resulting in even better agreement. Also, the new quantum dynamical entropy generalizes the classical dynamical entropy of Kolmogorov and Sinai in the same way as does the AF entropy. Finally, we estimate the 'hybrid' entropy both for the Powers-Price shift systems and for the noncommutative Arnold map on the irrational rotation C * -algebra, leaving some interesting open problems. (author)
Entropy type complexity of quantum processes
International Nuclear Information System (INIS)
Watanabe, Noboru
2014-01-01
von Neumann entropy represents the amount of information in the quantum state, and this was extended by Ohya for general quantum systems [10]. Umegaki first defined the quantum relative entropy for σ-finite von Neumann algebras, which was extended by Araki, and Uhlmann, for general von Neumann algebras and *-algebras, respectively. In 1983 Ohya introduced the quantum mutual entropy by using compound states; this describes the amount of information correctly transmitted through the quantum channel, which was also extended by Ohya for general quantum systems. In this paper, we briefly explain Ohya's S-mixing entropy and the quantum mutual entropy for general quantum systems. By using structure equivalent class, we will introduce entropy type functionals based on quantum information theory to improve treatment for the Gaussian communication process. (paper)
Bounded Intention Planning Revisited
Sievers Silvan; Wehrle Martin; Helmert Malte
2014-01-01
Bounded intention planning provides a pruning technique for optimal planning that has been proposed several years ago. In addition partial order reduction techniques based on stubborn sets have recently been investigated for this purpose. In this paper we revisit bounded intention planning in the view of stubborn sets.
Zhang, Yin; Liu, Yue; Li, Yannan; Zhao, Xia; Zhuo, Lin; Zhou, Ajian; Zhang, Li; Su, Zeqi; Chen, Cen; Du, Shiyu; Liu, Daming; Ding, Xia
2018-03-22
Chronic atrophic gastritis (CAG) is the precancerous stage of gastric carcinoma. Traditional Chinese Medicine (TCM) has been widely used in treating CAG. This study aimed to reveal core pathogenesis of CAG by validating the TCM syndrome patterns and provide evidence for optimization of treatment strategies. This is a cross-sectional study conducted in 4 hospitals in China. Hierarchical clustering analysis (HCA) and complex system entropy clustering analysis (CSECA) were performed, respectively, to achieve syndrome pattern validation. Based on HCA, 15 common factors were assigned to 6 syndrome patterns: liver depression and spleen deficiency and blood stasis in the stomach collateral, internal harassment of phlegm-heat and blood stasis in the stomach collateral, phlegm-turbidity internal obstruction, spleen yang deficiency, internal harassment of phlegm-heat and spleen deficiency, and spleen qi deficiency. By CSECA, 22 common factors were assigned to 7 syndrome patterns: qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, yang deficiency, and yin deficiency. Combination of qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, yang deficiency, and yin deficiency may play a crucial role in CAG pathogenesis. In accord with this, treatment strategies by TCM herbal prescriptions should be targeted to regulating qi, activating blood, resolving turbidity, clearing heat, removing toxin, nourishing yin, and warming yang. Further explorations are needed to verify and expand the current conclusions.
International Nuclear Information System (INIS)
Hao, Rujiang; Chu, Fulei; Peng, Zhike; Feng, Zhipeng
2011-01-01
This paper presents a novel pattern classification approach for the fault diagnostics of rolling element bearings, which combines the morphological multi-scale analysis and the 'one to others' support vector machine (SVM) classifiers. The morphological pattern spectrum describes the shape characteristics of the inspected signal based on the morphological opening operation with multi-scale structuring elements. The pattern spectrum entropy and the barycenter scale location of the spectrum curve are extracted as the feature vectors presenting different faults of the bearing, which are more effective and representative than the kurtosis and the enveloping demodulation spectrum. The 'one to others' SVM algorithm is adopted to distinguish six kinds of fault signals which were measured in the experimental test rig under eight different working conditions. The recognition results of the SVM are ideal and more precise than those of the artificial neural network even though the training samples are few. The combination of the morphological pattern spectrum parameters and the 'one to others' multi-class SVM algorithm is suitable for the on-line automated fault diagnosis of the rolling element bearings. This application is promising and worth well exploiting
Directory of Open Access Journals (Sweden)
Jia Xiao
2016-11-01
Full Text Available Constructing a merged concept lattice with formal concept analysis (FCA is an important research direction in the field of integrating multi-source geo-ontologies. Extracting essential geographical properties and reducing the concept lattice are two key points of previous research. A formal integration method is proposed to address the challenges in these two areas. We first extract essential properties from multi-source geo-ontologies and use FCA to build a merged formal context. Second, the combined importance weight of each single attribute of the formal context is calculated by introducing the inclusion degree importance from rough set theory and information entropy; then a weighted formal context is built from the merged formal context. Third, a combined weighted concept lattice is established from the weighted formal context with FCA and the importance weight value of every concept is defined as the sum of weight of attributes belonging to the concept’s intent. Finally, semantic granularity of concept is defined by its importance weight; we, then gradually reduce the weighted concept lattice by setting up diminishing threshold of semantic granularity. Additionally, all of those reduced lattices are organized into a regular hierarchy structure based on the threshold of semantic granularity. A workflow is designed to demonstrate this procedure. A case study is conducted to show feasibility and validity of this method and the procedure to integrate multi-source geo-ontologies.
Directory of Open Access Journals (Sweden)
Isis Didier Lins
2018-03-01
Full Text Available The Generalized Renewal Process (GRP is a probabilistic model for repairable systems that can represent the usual states of a system after a repair: as new, as old, or in a condition between new and old. It is often coupled with the Weibull distribution, widely used in the reliability context. In this paper, we develop novel GRP models based on probability distributions that stem from the Tsallis’ non-extensive entropy, namely the q-Exponential and the q-Weibull distributions. The q-Exponential and Weibull distributions can model decreasing, constant or increasing failure intensity functions. However, the power law behavior of the q-Exponential probability density function for specific parameter values is an advantage over the Weibull distribution when adjusting data containing extreme values. The q-Weibull probability distribution, in turn, can also fit data with bathtub-shaped or unimodal failure intensities in addition to the behaviors already mentioned. Therefore, the q-Exponential-GRP is an alternative for the Weibull-GRP model and the q-Weibull-GRP generalizes both. The method of maximum likelihood is used for their parameters’ estimation by means of a particle swarm optimization algorithm, and Monte Carlo simulations are performed for the sake of validation. The proposed models and algorithms are applied to examples involving reliability-related data of complex systems and the obtained results suggest GRP plus q-distributions are promising techniques for the analyses of repairable systems.
Zhao, Liang; Adhikari, Avishek; Sakurai, Kouichi
Watermarking is one of the most effective techniques for copyright protection and information hiding. It can be applied in many fields of our society. Nowadays, some image scrambling schemes are used as one part of the watermarking algorithm to enhance the security. Therefore, how to select an image scrambling scheme and what kind of the image scrambling scheme may be used for watermarking are the key problems. Evaluation method of the image scrambling schemes can be seen as a useful test tool for showing the property or flaw of the image scrambling method. In this paper, a new scrambling evaluation system based on spatial distribution entropy and centroid difference of bit-plane is presented to obtain the scrambling degree of image scrambling schemes. Our scheme is illustrated and justified through computer simulations. The experimental results show (in Figs. 6 and 7) that for the general gray-scale image, the evaluation degree of the corresponding cipher image for the first 4 significant bit-planes selection is nearly the same as that for the 8 bit-planes selection. That is why, instead of taking 8 bit-planes of a gray-scale image, it is sufficient to take only the first 4 significant bit-planes for the experiment to find the scrambling degree. This 50% reduction in the computational cost makes our scheme efficient.
Directory of Open Access Journals (Sweden)
Pace Umberto
2006-05-01
Full Text Available Abstract Background We describe an ELISA-based method that can be used to identify and quantitate proteins in biological samples. In this method, peptides in solution, derived from proteolytic digests of the sample, compete with substrate-attached synthetic peptides for antibodies, also in solution, generated against the chosen peptides. The peptides used for the ELISA are chosen on the basis of their being (i products of the proteolytic (e.g. tryptic digestion of the protein to be identified and (ii unique to the target protein, as far as one can know from the published sequences. Results In this paper we describe the competition assay and we define the optimal conditions for the most effective assay. We have performed an analysis of the kinetics of interaction between the four components of the assay: the plastic substratum to which the peptide is bound, the bound peptide itself, the competing added peptide, and the antibody that is specific for the peptide and we compare the results of theoretical simulations to the actual data in some model systems. Conclusion The data suggest that the peptides bind to the plastic substratum in more than one conformation and that, once bound, the peptide displays different affinities for the antibody, depending on how it has bound to the plate
Directory of Open Access Journals (Sweden)
Urban Kordes
2005-10-01
Full Text Available The paper tries to tackle the question of connection between entropy and the living. Definitions of life as the phenomenon that defies entropy are overviewed and the conclusion is reached that life is in a way dependant on entropy - it couldn't exist without it. Entropy is a sort of medium, a fertile soil, that gives life possibility to blossom. Paper ends with presenting some consequences for the field of artificial intelligence.
Entropy of Baker's Transformation
Institute of Scientific and Technical Information of China (English)
栾长福
2003-01-01
Four theorems about four different kinds of entropies for Baker's transformation are presented. The Kolmogorov entropy of Baker's transformation is sensitive to the initial flips by the time. The topological entropy of Baker's transformation is found to be log k. The conditions for the state of Baker's transformation to be forbidden are also derived. The relations among the Shanonn, Kolmogorov, topological and Boltzmann entropies are discussed in details.
Relationship between Entropy and Dimension of Financial Correlation-Based Network
Directory of Open Access Journals (Sweden)
Chun-xiao Nie
2018-03-01
Full Text Available We analyze the dimension of a financial correlation-based network and apply our analysis to characterize the complexity of the network. First, we generalize the volume-based dimension and find that it is well defined by the correlation-based network. Second, we establish the relationship between the Rényi index and the volume-based dimension. Third, we analyze the meaning of the dimensions sequence, which characterizes the level of departure from the comparison benchmark based on the randomized time series. Finally, we use real stock market data from three countries for empirical analysis. In some cases, our proposed analysis method can more accurately capture the structural differences of networks than the power law index commonly used in previous studies.
Physical entropy, information entropy and their evolution equations
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Inspired by the evolution equation of nonequilibrium statistical physics entropy and the concise statistical formula of the entropy production rate, we develop a theory of the dynamic information entropy and build a nonlinear evolution equation of the information entropy density changing in time and state variable space. Its mathematical form and physical meaning are similar to the evolution equation of the physical entropy: The time rate of change of information entropy density originates together from drift, diffusion and production. The concise statistical formula of information entropy production rate is similar to that of physical entropy also. Furthermore, we study the similarity and difference between physical entropy and information entropy and the possible unification of the two statistical entropies, and discuss the relationship among the principle of entropy increase, the principle of equilibrium maximum entropy and the principle of maximum information entropy as well as the connection between them and the entropy evolution equation.
Constraining the mSUGRA parameter space through entropy and abundance criteria
International Nuclear Information System (INIS)
Cabral-Rosetti, Luis G.; Mondragon, Myriam; Nunez, Dario; Sussman, Roberto A.; Zavala, Jesus; Nellen, Lukas
2007-01-01
We explore the use of two criteria to constrain the allowed parameter space in mSUGRA models; both criteria are based in the calculation of the present density of neutralinos χ0 as Dark Matter in the Universe. The first one is the usual ''abundance'' criterion that requieres that present neutralino relic density complies with 0.0945 < ΩCDMh2 < 0.1287, which are the 2σ bounds according to WMAP. To calculate the relic density we use the public numerical code micrOMEGAS. The second criterion is the original idea presented in [3] that basically applies the microcanonical definition of entropy to a weakly interacting and self-gravitating gas, and then evaluate the change in entropy per particle of this gas between the freeze-out era and present day virialized structures. An 'entropy consistency' criterion emerges by comparing theoretical and empirical estimates of this entropy. One of the objetives of the work is to analyze the joint application of both criteria, already done in [3], to see if their results, using approximations for the calculations of the relic density, agree with the results coming from the exact numerical results of micrOMEGAS. The main objetive of the work is to use this method to constrain the parameter space in mSUGRA models that are inputs for the calculations of micrOMEGAS, and thus to get some bounds on the predictions for the SUSY spectra
Baxa, Michael C.; Haddadian, Esmael J.; Jumper, John M.; Freed, Karl F.; Sosnick, Tobin R.
2014-01-01
The loss of conformational entropy is a major contribution in the thermodynamics of protein folding. However, accurate determination of the quantity has proven challenging. We calculate this loss using molecular dynamic simulations of both the native protein and a realistic denatured state ensemble. For ubiquitin, the total change in entropy is TΔSTotal = 1.4 kcal⋅mol−1 per residue at 300 K with only 20% from the loss of side-chain entropy. Our analysis exhibits mixed agreement with prior studies because of the use of more accurate ensembles and contributions from correlated motions. Buried side chains lose only a factor of 1.4 in the number of conformations available per rotamer upon folding (ΩU/ΩN). The entropy loss for helical and sheet residues differs due to the smaller motions of helical residues (TΔShelix−sheet = 0.5 kcal⋅mol−1), a property not fully reflected in the amide N-H and carbonyl C=O bond NMR order parameters. The results have implications for the thermodynamics of folding and binding, including estimates of solvent ordering and microscopic entropies obtained from NMR. PMID:25313044
Ben-Naim, Arieh
2011-01-01
Changes in entropy can "sometimes" be interpreted in terms of changes in disorder. On the other hand, changes in entropy can "always" be interpreted in terms of changes in Shannon's measure of information. Mixing and demixing processes are used to highlight the pitfalls in the association of entropy with disorder. (Contains 3 figures.)
Resolvent-based modeling of passive scalar dynamics in wall-bounded turbulence
Dawson, Scott; Saxton-Fox, Theresa; McKeon, Beverley
2017-11-01
The resolvent formulation of the Navier-Stokes equations expresses the system state as the output of a linear (resolvent) operator acting upon a nonlinear forcing. Previous studies have demonstrated that a low-rank approximation of this linear operator predicts many known features of incompressible wall-bounded turbulence. In this work, this resolvent model for wall-bounded turbulence is extended to include a passive scalar field. This formulation allows for a number of additional simplifications that reduce model complexity. Firstly, it is shown that the effect of changing scalar diffusivity can be approximated through a transformation of spatial wavenumbers and temporal frequencies. Secondly, passive scalar dynamics may be studied through the low-rank approximation of a passive scalar resolvent operator, which is decoupled from velocity response modes. Thirdly, this passive scalar resolvent operator is amenable to approximation by semi-analytic methods. We investigate the extent to which this resulting hierarchy of models can describe and predict passive scalar dynamics and statistics in wall-bounded turbulence. The support of AFOSR under Grant Numbers FA9550-16-1-0232 and FA9550-16-1-0361 is gratefully acknowledged.
Entropy of the system formed in heavy ion collision
International Nuclear Information System (INIS)
Gudima, K.K.; Schulz, H.; Toneev, V.D.
1985-01-01
In frames of a cascade model the entropy evolution in a system producted in heavy ion collisions is investigated. Entropy calculation is based on smoothing of the distribution function over the momentum space by the temperature field introduction. The resulting entropy per one nucleon is shown to be rather sensitive to phase space subdivision into cells at the stage of free scattering of reaction products. Compared to recent experimental results for specific entropy values inferred from the composite particle yield of 4π measurements, it is found that cascade calculations do not favour some particular entropy model treatments and suggest smaller entropy values than following from consideration within equilibrium statistics
Software Component Clustering and Retrieval: An Entropy-based Fuzzy k-Modes Methodology
Stylianou, Constantinos; Andreou, Andreas S.
2008-01-01
The number of software houses attempting to adopt a component-based development approach is rapidly increasing. However many organisations still find it difficult to complete the shift as it requires them to alter their entire software development process and philosophy. Furthermore, to promote component-based software engineering, organisations must be ready to promote reusability and this can only be attained if the proper framework exists from which a developer can access, search and retri...
Shabat-Hadas, Efrat; Mamane, Hadas; Gitis, Vitaly
2017-10-01
Rhodamine B (RhB) is a water-soluble fluorescent dye that is often used to determine flux and flow direction in biotechnological and environmental applications. In the current research, RhB in soluble (termed free) and virus-bound (termed nano-bound) forms was used as an efficiency indicator for three environmental processes. The degradation of free and nano-bound RhB by (i) direct UV photolysis and (ii) UV/H 2 O 2 advanced oxidation process (AOP) was studied in a collimated beam apparatus equipped with medium-pressure mercury vapor lamp. The degradation by (iii) solar light-induced photocatalysis was studied in a solar simulator with titanium dioxide and bismuth photocatalysts. Results showed negligible RhB degradation by direct UV and solar light, and its nearly linear degradation by UV/H 2 O 2 and photocatalysis/photosensitization in the presence of a solid catalyst. Considerable adsorption of free RhB on bismuth-based catalyst vs. no adsorption of nano-bound RhB on this catalyst or of any form of the dye on titanium dioxide produced two important conclusions. First, the better degradation of free RhB by the bismuth catalyst suggests that close proximity of a catalyst hole and the decomposing molecule significantly influences degradation. Second, the soluble form of the dye might not be the best option for its use as an indicator. Nano-bound RhB showed high potential as an AOP indicator, featuring possible separation from water after the analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.
Kusaba, Akira; Li, Guanchen; von Spakovsky, Michael R.; Kangawa, Yoshihiro; Kakimoto, Koichi
2017-01-01
Clearly understanding elementary growth processes that depend on surface reconstruction is essential to controlling vapor-phase epitaxy more precisely. In this study, ammonia chemical adsorption on GaN(0001) reconstructed surfaces under metalorganic vapor phase epitaxy (MOVPE) conditions (3Ga-H and Nad-H + Ga-H on a 2 × 2 unit cell) is investigated using steepest-entropy-ascent quantum thermodynamics (SEAQT). SEAQT is a thermodynamic-ensemble based, first-principles framework that can predict...
Meysman, F.J.R.; Bruers, S.
2007-01-01
Because ecosystems fit so nicely the framework of a “dissipative system”, a better integration of thermodynamic and ecological perspectives could benefit the quantitative analysis of ecosystems. One obstacle is that traditional food web models are solely based upon the principles of mass and energy
The improvement of Clausius entropy and its application in entropy analysis
Institute of Scientific and Technical Information of China (English)
2008-01-01
The defects of Clausius entropy which include a premise of reversible process and a process quantity of heat in its definition are discussed in this paper. Moreover, the heat temperature quotient under reversible conditions, i.e. (δQ/T)rev, is essentially a process quantity although it is numerically equal to the entropy change. The sum of internal energy temperature quotient and work temperature quotient is defined as the improved form of Clausius entropy and it can be further proved to be a state function. Unlike Clausius entropy, the improved definition consists of system properties without premise just like other state functions, for example, pressure p and enthalpy h, etc. It is unnecessary to invent reversible paths when calculating entropy change for irreversible processes based on the improved form of entropy since it is independent of process. Furthermore, entropy balance equations for internally and externally irreversible processes are deduced respectively based on the concepts of thermal reservoir entropy transfer and system entropy transfer. Finally, some examples are presented to show that the improved definition of Clausius entropy provides a clear concept as well as a convenient method for en- tropy change calculation.
Li, Peng; Xu, Chao; Chen, Long; Wang, Ruchuan
2015-01-01
Evaluation of security risks in radio frequency identification (RFID) systems is a challenging problem in Internet of Things (IoT). This paper proposes an extended attack tree (EAT) model to identify RFID system’s flaws and vulnerabilities. A corresponding formal description of the model is described which adds a probability SAND node together with the probability attribute of the node attack. In addition, we model the process of an RFID data privacy attack based on EAT, taking a sensitive in...
Bayes-Optimal Entropy Pursuit for Active Choice-Based Preference Learning
Pallone, Stephen N.; Frazier, Peter I.; Henderson, Shane G.
2017-01-01
We analyze the problem of learning a single user's preferences in an active learning setting, sequentially and adaptively querying the user over a finite time horizon. Learning is conducted via choice-based queries, where the user selects her preferred option among a small subset of offered alternatives. These queries have been shown to be a robust and efficient way to learn an individual's preferences. We take a parametric approach and model the user's preferences through a linear classifier...
The Entropy of Co-Compact Open Covers
Directory of Open Access Journals (Sweden)
Steven Bourquin
2013-06-01
Full Text Available Co-compact entropy is introduced as an invariant of topological conjugation for perfect mappings defined on any Hausdorff space (compactness and metrizability are not necessarily required. This is achieved through the consideration of co-compact covers of the space. The advantages of co-compact entropy include: (1 it does not require the space to be compact and, thus, generalizes Adler, Konheim and McAndrew’s topological entropy of continuous mappings on compact dynamical systems; and (2 it is an invariant of topological conjugation, compared to Bowen’s entropy, which is metric-dependent. Other properties of co-compact entropy are investigated, e.g., the co-compact entropy of a subsystem does not exceed that of the whole system. For the linear system, (R; f, defined by f(x = 2x, the co-compact entropy is zero, while Bowen’s entropy for this system is at least log 2. More generally, it is found that co-compact entropy is a lower bound of Bowen’s entropies, and the proof of this result also generates the Lebesgue Covering Theorem to co-compact open covers of non-compact metric spaces.
Quantum chaos: entropy signatures
International Nuclear Information System (INIS)
Miller, P.A.; Sarkar, S.; Zarum, R.
1998-01-01
A definition of quantum chaos is given in terms of entropy production rates for a quantum system coupled weakly to a reservoir. This allows the treatment of classical and quantum chaos on the same footing. In the quantum theory the entropy considered is the von Neumann entropy and in classical systems it is the Gibbs entropy. The rate of change of the coarse-grained Gibbs entropy of the classical system with time is given by the Kolmogorov-Sinai (KS) entropy. The relation between KS entropy and the rate of change of von Neumann entropy is investigated for the kicked rotator. For a system which is classically chaotic there is a linear relationship between these two entropies. Moreover it is possible to construct contour plots for the local KS entropy and compare it with the corresponding plots for the rate of change of von Neumann entropy. The quantitative and qualitative similarities of these plots are discussed for the standard map (kicked rotor) and the generalised cat maps. (author)
International Nuclear Information System (INIS)
Zhou Yunlong; Chen Fei; Sun Bin
2008-01-01
Based on the characteristic that wavelet packet transform image can be decomposed by different scales, a flow regime identification method based on image wavelet packet information entropy feature and genetic neural network was proposed. Gas-liquid two-phase flow images were captured by digital high speed video systems in horizontal pipe. The information entropy feature from transformation coefficients were extracted using image processing techniques and multi-resolution analysis. The genetic neural network was trained using those eigenvectors, which was reduced by the principal component analysis, as flow regime samples, and the flow regime intelligent identification was realized. The test result showed that image wavelet packet information entropy feature could excellently reflect the difference between seven typical flow regimes, and the genetic neural network with genetic algorithm and BP algorithm merits were with the characteristics of fast convergence for simulation and avoidance of local minimum. The recognition possibility of the network could reach up to about 100%, and a new and effective method was presented for on-line flow regime. (authors)
Zan, Hao; Li, Haowei; Jiang, Yuguang; Wu, Meng; Zhou, Weixing; Bao, Wen
2018-06-01
As part of our efforts to find ways and means to further improve the regenerative cooling technology in scramjet, the experiments of thermo-acoustic instability dynamic characteristics of hydrocarbon fuel flowing have been conducted in horizontal circular tubes at different conditions. The experimental results indicate that there is a developing process from thermo-acoustic stability to instability. In order to have a deep understanding on the developing process of thermo-acoustic instability, the method of Multi-scale Shannon Wavelet Entropy (MSWE) based on Wavelet Transform Correlation Filter (WTCF) and Multi-Scale Shannon Entropy (MSE) is adopted in this paper. The results demonstrate that the developing process of thermo-acoustic instability from noise and weak signals is well detected by MSWE method and the differences among the stability, the developing process and the instability can be identified. These properties render the method particularly powerful for warning thermo-acoustic instability of hydrocarbon fuel flowing in scramjet cooling channels. The mass flow rate and the inlet pressure will make an influence on the developing process of the thermo-acoustic instability. The investigation on thermo-acoustic instability dynamic characteristics at supercritical pressure based on wavelet entropy method offers guidance on the control of scramjet fuel supply, which can secure stable fuel flowing in regenerative cooling system.
Heat transfer and entropy generation analysis of HFE 7000 based nanorefrigerants
Helvaci, H.; Khan, Zulfiqar Ahmad
2017-01-01
In this study, two dimensional numerical simulations of forced convection flow of HFE 7000 based nanofluids in a horizontal circular tube subjected to a constant and uniform heat flux in laminar flow was performed by using single phase homogeneous model. Four different nanofluids considered in the present study are Al2O3, CuO, SiO2 and MgO nanoparticles dispersed in pure HFE 7000. The simulations were performed with particle volumetric concentrations of 0, 1, 4 and 6% and Reynolds number of 4...
Volkenstein, Mikhail V
2009-01-01
The book "Entropy and Information" deals with the thermodynamical concept of entropy and its relationship to information theory. It is successful in explaining the universality of the term "Entropy" not only as a physical phenomenon, but reveals its existence also in other domains. E.g., Volkenstein discusses the "meaning" of entropy in a biological context and shows how entropy is related to artistic activities. Written by the renowned Russian bio-physicist Mikhail V. Volkenstein, this book on "Entropy and Information" surely serves as a timely introduction to understand entropy from a thermodynamic perspective and is definitely an inspiring and thought-provoking book that should be read by every physicist, information-theorist, biologist, and even artist.
DEFF Research Database (Denmark)
Han, Renke; Meng, Lexuan; Ferrari-Trecate, Giancarlo
2017-01-01
This paper offers a highly flexible and reliable control strategy to achieve voltage bounded regulation and accurate reactive power sharing coordinately in AC Micro-Grids. A containment and consensus-based distributed coordination controller is proposed, by which each output voltage magnitude can...... be bounded within a reasonable range and the accurate reactive power sharing among distributed generators can be also achieved. Combined with the two proposed controllers and electrical part of the AC Micro-Grid, a small signal model is fully developed to analyze the sensitivity of different control...... parameters. The effectiveness of the proposed controller in case of load variation, communication failure, plug-and-play capability are verified by the experimental setup as an islanded Micro-Grid....
RNA Thermodynamic Structural Entropy.
Garcia-Martin, Juan Antonio; Clote, Peter
2015-01-01
Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV absorption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs). However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, such as the repression of heat shock gene expression (ROSE) element, we determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and we plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner'99 and Turner'04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. Source code is available at https://github.com/clotelab/RNAentropy/; a full web server is available at http
RNA Thermodynamic Structural Entropy.
Directory of Open Access Journals (Sweden)
Juan Antonio Garcia-Martin
Full Text Available Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV absorption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs. However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, such as the repression of heat shock gene expression (ROSE element, we determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and we plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner'99 and Turner'04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. Source code is available at https://github.com/clotelab/RNAentropy/; a full web server is available at http
The nexus between geopolitical uncertainty and crude oil markets: An entropy-based wavelet analysis
Uddin, Gazi Salah; Bekiros, Stelios; Ahmed, Ali
2018-04-01
The global financial crisis and the subsequent geopolitical turbulence in energy markets have brought increased attention to the proper statistical modeling especially of the crude oil markets. In particular, we utilize a time-frequency decomposition approach based on wavelet analysis to explore the inherent dynamics and the casual interrelationships between various types of geopolitical, economic and financial uncertainty indices and oil markets. Via the introduction of a mixed discrete-continuous multiresolution analysis, we employ the entropic criterion for the selection of the optimal decomposition level of a MODWT as well as the continuous-time coherency and phase measures for the detection of business cycle (a)synchronization. Overall, a strong heterogeneity in the revealed interrelationships is detected over time and across scales.
Li, Jimeng; Li, Ming; Zhang, Jinfeng
2017-08-01
Rolling bearings are the key components in the modern machinery, and tough operation environments often make them prone to failure. However, due to the influence of the transmission path and background noise, the useful feature information relevant to the bearing fault contained in the vibration signals is weak, which makes it difficult to identify the fault symptom of rolling bearings in time. Therefore, the paper proposes a novel weak signal detection method based on time-delayed feedback monostable stochastic resonance (TFMSR) system and adaptive minimum entropy deconvolution (MED) to realize the fault diagnosis of rolling bearings. The MED method is employed to preprocess the vibration signals, which can deconvolve the effect of transmission path and clarify the defect-induced impulses. And a modified power spectrum kurtosis (MPSK) index is constructed to realize the adaptive selection of filter length in the MED algorithm. By introducing the time-delayed feedback item in to an over-damped monostable system, the TFMSR method can effectively utilize the historical information of input signal to enhance the periodicity of SR output, which is beneficial to the detection of periodic signal. Furthermore, the influence of time delay and feedback intensity on the SR phenomenon is analyzed, and by selecting appropriate time delay, feedback intensity and re-scaling ratio with genetic algorithm, the SR can be produced to realize the resonance detection of weak signal. The combination of the adaptive MED (AMED) method and TFMSR method is conducive to extracting the feature information from strong background noise and realizing the fault diagnosis of rolling bearings. Finally, some experiments and engineering application are performed to evaluate the effectiveness of the proposed AMED-TFMSR method in comparison with a traditional bistable SR method.
Methods for calculating nonconcave entropies
International Nuclear Information System (INIS)
Touchette, Hugo
2010-01-01
Five different methods which can be used to analytically calculate entropies that are nonconcave as functions of the energy in the thermodynamic limit are discussed and compared. The five methods are based on the following ideas and techniques: (i) microcanonical contraction, (ii) metastable branches of the free energy, (iii) generalized canonical ensembles with specific illustrations involving the so-called Gaussian and Betrag ensembles, (iv) the restricted canonical ensemble, and (v) the inverse Laplace transform. A simple long-range spin model having a nonconcave entropy is used to illustrate each method
International Nuclear Information System (INIS)
Bian Yiwen; Yang Feng
2010-01-01
Data envelopment analysis (DEA) has been widely used in energy efficiency and environment efficiency analysis in recent years. Based on the existing environment DEA technology, this paper presents several DEA models for estimating the aggregated efficiency of resource and environment. These models can evaluate DMUs' energy efficiencies and environment efficiencies simultaneously. However, efficiency ranking results obtained from these models are not the same, and each model can provide some valuable information of DMUs' efficiencies, which we could not ignore. Under this situation, it may be hard for us to choose a specific model in practice. To address this kind of performance evaluation problem, the current paper extends Shannon-DEA procedure to establish a comprehensive efficiency measure for appraising DMUs' resource and environment efficiencies. In the proposed approach, the measure for evaluating a model's importance degree is provided, and the targets setting approach of inputs/outputs for DMU managers to improve DMUs' energy and environmental efficiencies is also discussed. We illustrate the proposed approach using real data set of 30 provinces in China.
Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection
Directory of Open Access Journals (Sweden)
Jaesung Lee
2016-11-01
Full Text Available Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computational cost of multi-label feature selection increases according to the number of labels, the algorithm may suffer from a degradation in performance when processing very large datasets. In this study, we propose an efficient multi-label feature selection method based on an information-theoretic label selection strategy. By identifying a subset of labels that significantly influence the importance of features, the proposed method efficiently outputs a feature subset. Experimental results demonstrate that the proposed method can identify a feature subset much faster than conventional multi-label feature selection methods for large multi-label datasets.
Directory of Open Access Journals (Sweden)
Christian Corda
2018-01-01
Full Text Available In this paper we consider the metric entropies of the maps of an iterated function system deduced from a black hole which are known the Bekenstein–Hawking entropies and its subleading corrections. More precisely, we consider the recent model of a Bohr-like black hole that has been recently analysed in some papers in the literature, obtaining the intriguing result that the metric entropies of a black hole are created by the metric entropies of the functions, created by the black hole principal quantum numbers, i.e., by the black hole quantum levels. We present a new type of topological entropy for general iterated function systems based on a new kind of the inverse of covers. Then the notion of metric entropy for an Iterated Function System ( I F S is considered, and we prove that these definitions for topological entropy of IFS’s are equivalent. It is shown that this kind of topological entropy keeps some properties which are hold by the classic definition of topological entropy for a continuous map. We also consider average entropy as another type of topological entropy for an I F S which is based on the topological entropies of its elements and it is also an invariant object under topological conjugacy. The relation between Axiom A and the average entropy is investigated.
A holographic bound for D3-brane
Energy Technology Data Exchange (ETDEWEB)
Momeni, Davood; Myrzakul, Aizhan; Myrzakulov, Ratbay [Eurasian National University, Eurasian International Center for Theoretical Physics, Astana (Kazakhstan); Eurasian National University, Department of General Theoretical Physics, Astana (Kazakhstan); Faizal, Mir [University of British Columbia-Okanagan, Irving K. Barber School of Arts and Sciences, Kelowna, BC (Canada); University of Lethbridge, Department of Physics and Astronomy, Lethbridge, AB (Canada); Bahamonde, Sebastian [University College London, Department of Mathematics, London (United Kingdom)
2017-06-15
In this paper, we will regularize the holographic entanglement entropy, holographic complexity and fidelity susceptibility for a configuration of D3-branes. We will also study the regularization of the holographic complexity from the action for a configuration of D3-branes. It will be demonstrated that for a spherical shell of D3-branes the regularized holographic complexity is always greater than or equal to the regularized fidelity susceptibility. Furthermore, we will also demonstrate that the regularized holographic complexity is related to the regularized holographic entanglement entropy for this system. Thus, we will obtain a holographic bound involving regularized holographic complexity, regularized holographic entanglement entropy and regularized fidelity susceptibility of a configuration of D3-brane. We will also discuss a bound for regularized holographic complexity from action, for a D3-brane configuration. (orig.)
Maximum-entropy clustering algorithm and its global convergence analysis
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Constructing a batch of differentiable entropy functions touniformly approximate an objective function by means of the maximum-entropy principle, a new clustering algorithm, called maximum-entropy clustering algorithm, is proposed based on optimization theory. This algorithm is a soft generalization of the hard C-means algorithm and possesses global convergence. Its relations with other clustering algorithms are discussed.
Soni, Vinay Kumar; Sanyal, S.; Sinha, S. K.
2018-05-01
The present work reports the structural and phase stability analysis of equiatomic FeCoNiCuZn High entropy alloy (HEA) systems prepared by mechanical alloying (MA) method. In this research effort some 1287 alloy combinations were extensively studied to arrive at most favourable combination. FeCoNiCuZn based alloy system was selected on the basis of physiochemical parameters such as enthalpy of mixing (ΔHmix), entropy of mixing (ΔSmix), atomic size difference (ΔX) and valence electron concentration (VEC) such that it fulfils the formation criteria of stable multi component high entropy alloy system. In this context, we have investigated the effect of novel alloying addition in view of microstructure and phase formation aspect. XRD plots of the MA samples shows the formation of stable solid solution with FCC (Face Cantered Cubic) after 20 hr of milling time and no indication of any amorphous or intermetallic phase formation. Our results are in good agreement with calculation and analysis done on the basis of physiochemical parameters during selection of constituent elements of HEA.
Gravitational entropies in LTB dust models
International Nuclear Information System (INIS)
Sussman, Roberto A; Larena, Julien
2014-01-01
We consider generic Lemaître–Tolman–Bondi (LTB) dust models to probe the gravitational entropy proposals of Clifton, Ellis and Tavakol (CET) and of Hosoya and Buchert (HB). We also consider a variant of the HB proposal based on a suitable quasi-local scalar weighted average. We show that the conditions for entropy growth for all proposals are directly related to a negative correlation of similar fluctuations of the energy density and Hubble scalar. While this correlation is evaluated locally for the CET proposal, it must be evaluated in a non-local domain dependent manner for the two HB proposals. By looking at the fulfilment of these conditions at the relevant asymptotic limits we are able to provide a well grounded qualitative description of the full time evolution and radial asymptotic scaling of the three entropies in generic models. The following rigorous analytic results are obtained for the three proposals: (i) entropy grows when the density growing mode is dominant, (ii) all ever-expanding hyperbolic models reach a stable terminal equilibrium characterized by an inhomogeneous entropy maximum in their late time evolution; (iii) regions with decaying modes and collapsing elliptic models exhibit unstable equilibria associated with an entropy minimum (iv) near singularities the CET entropy diverges while the HB entropies converge; (v) the CET entropy converges for all models in the radial asymptotic range, whereas the HB entropies only converge for models asymptotic to a Friedmann–Lemaître–Robertson–Walker background. The fact that different independent proposals yield fairly similar conditions for entropy production, time evolution and radial scaling in generic LTB models seems to suggest that their common notion of a ‘gravitational entropy’ may be a theoretically robust concept applicable to more general spacetimes. (paper)
ENTROPIES AND FLUX-SPLITTINGS FOR THE ISENTROPIC EULER EQUATIONS
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
The authors establish the existence of a large class of mathematical entropies (the so-called weak entropies) associated with the Euler equations for an isentropic, compressible fluid governed by a general pressure law. A mild assumption on the behavior of the pressure law near the vacuum is solely required. The analysis is based on an asymptotic expansion of the fundamental solution (called here the entropy kernel) of a highly singular Euler-Poisson-Darboux equation. The entropy kernel is only H lder continuous and its regularity is carefully investigated. Relying on a notion introduced earlier by the authors, it is also proven that, for the Euler equations, the set of entropy flux-splittings coincides with the set of entropies-entropy fluxes. These results imply the existence of a flux-splitting consistent with all of the entropy inequalities.
The Conditional Entropy Power Inequality for Bosonic Quantum Systems
DEFF Research Database (Denmark)
de Palma, Giacomo; Trevisan, Dario
2018-01-01
We prove the conditional Entropy Power Inequality for Gaussian quantum systems. This fundamental inequality determines the minimum quantum conditional von Neumann entropy of the output of the beam-splitter or of the squeezing among all the input states where the two inputs are conditionally...... independent given the memory and have given quantum conditional entropies. We also prove that, for any couple of values of the quantum conditional entropies of the two inputs, the minimum of the quantum conditional entropy of the output given by the conditional Entropy Power Inequality is asymptotically...... achieved by a suitable sequence of quantum Gaussian input states. Our proof of the conditional Entropy Power Inequality is based on a new Stam inequality for the quantum conditional Fisher information and on the determination of the universal asymptotic behaviour of the quantum conditional entropy under...
Entropy generation of nanofluid flow in a microchannel heat sink
Manay, Eyuphan; Akyürek, Eda Feyza; Sahin, Bayram
2018-06-01
Present study aims to investigate the effects of the presence of nano sized TiO2 particles in the base fluid on entropy generation rate in a microchannel heat sink. Pure water was chosen as base fluid, and TiO2 particles were suspended into the pure water in five different particle volume fractions of 0.25%, 0.5%, 1.0%, 1.5% and 2.0%. Under laminar, steady state flow and constant heat flux boundary conditions, thermal, frictional, total entropy generation rates and entropy generation number ratios of nanofluids were experimentally analyzed in microchannel flow for different channel heights of 200 μm, 300 μm, 400 μm and 500 μm. It was observed that frictional and total entropy generation rates increased as thermal entropy generation rate were decreasing with an increase in particle volume fraction. In microchannel flows, thermal entropy generation could be neglected due to its too low rate smaller than 1.10e-07 in total entropy generation. Higher channel heights caused higher thermal entropy generation rates, and increasing channel height yielded an increase from 30% to 52% in thermal entropy generation. When channel height decreased, an increase of 66%-98% in frictional entropy generation was obtained. Adding TiO2 nanoparticles into the base fluid caused thermal entropy generation to decrease about 1.8%-32.4%, frictional entropy generation to increase about 3.3%-21.6%.
Entropy of black holes with multiple horizons
Directory of Open Access Journals (Sweden)
Yun He
2018-05-01
Full Text Available We examine the entropy of black holes in de Sitter space and black holes surrounded by quintessence. These black holes have multiple horizons, including at least the black hole event horizon and a horizon outside it (cosmological horizon for de Sitter black holes and “quintessence horizon” for the black holes surrounded by quintessence. Based on the consideration that the two horizons are not independent each other, we conjecture that the total entropy of these black holes should not be simply the sum of entropies of the two horizons, but should have an extra term coming from the correlations between the two horizons. Different from our previous works, in this paper we consider the cosmological constant as the variable and employ an effective method to derive the explicit form of the entropy. We also try to discuss the thermodynamic stabilities of these black holes according to the entropy and the effective temperature.
Entropy of black holes with multiple horizons
He, Yun; Ma, Meng-Sen; Zhao, Ren
2018-05-01
We examine the entropy of black holes in de Sitter space and black holes surrounded by quintessence. These black holes have multiple horizons, including at least the black hole event horizon and a horizon outside it (cosmological horizon for de Sitter black holes and "quintessence horizon" for the black holes surrounded by quintessence). Based on the consideration that the two horizons are not independent each other, we conjecture that the total entropy of these black holes should not be simply the sum of entropies of the two horizons, but should have an extra term coming from the correlations between the two horizons. Different from our previous works, in this paper we consider the cosmological constant as the variable and employ an effective method to derive the explicit form of the entropy. We also try to discuss the thermodynamic stabilities of these black holes according to the entropy and the effective temperature.
Entanglement entropy in top-down models
Energy Technology Data Exchange (ETDEWEB)
Jones, Peter A.R.; Taylor, Marika [Mathematical Sciences and STAG Research Centre, University of Southampton,Highfield, Southampton, SO17 1BJ (United Kingdom)
2016-08-26
We explore holographic entanglement entropy in ten-dimensional supergravity solutions. It has been proposed that entanglement entropy can be computed in such top-down models using minimal surfaces which asymptotically wrap the compact part of the geometry. We show explicitly in a wide range of examples that the holographic entanglement entropy thus computed agrees with the entanglement entropy computed using the Ryu-Takayanagi formula from the lower-dimensional Einstein metric obtained from reduction over the compact space. Our examples include not only consistent truncations but also cases in which no consistent truncation exists and Kaluza-Klein holography is used to identify the lower-dimensional Einstein metric. We then give a general proof, based on the Lewkowycz-Maldacena approach, of the top-down entanglement entropy formula.
Entanglement entropy in top-down models
International Nuclear Information System (INIS)
Jones, Peter A.R.; Taylor, Marika
2016-01-01
We explore holographic entanglement entropy in ten-dimensional supergravity solutions. It has been proposed that entanglement entropy can be computed in such top-down models using minimal surfaces which asymptotically wrap the compact part of the geometry. We show explicitly in a wide range of examples that the holographic entanglement entropy thus computed agrees with the entanglement entropy computed using the Ryu-Takayanagi formula from the lower-dimensional Einstein metric obtained from reduction over the compact space. Our examples include not only consistent truncations but also cases in which no consistent truncation exists and Kaluza-Klein holography is used to identify the lower-dimensional Einstein metric. We then give a general proof, based on the Lewkowycz-Maldacena approach, of the top-down entanglement entropy formula.
Problems in black-hole entropy interpretation
International Nuclear Information System (INIS)
Liberati, S.
1997-01-01
In this work some proposals for black-hole entropy interpretation are exposed and investigated. In particular, the author will firstly consider the so-called 'entanglement entropy' interpretation, in the framework of the brick wall model and the divergence problem arising in the one-loop calculations of various thermodynamical quantities, like entropy, internal energy and heat capacity. It is shown that the assumption of equality of entanglement entropy and Bekenstein-Hawking one appears to give inconsistent results. These will be a starting point for a different interpretation of black.hole entropy based on peculiar topological structures of manifolds with 'intrinsic' thermodynamical features. It is possible to show an exact relation between black-hole gravitational entropy and topology of these Euclidean space-times. the expression for the Euler characteristic, through the Gauss-Bonnet integral, and the one for entropy for gravitational instantons are proposed in a form which makes the relation between these self-evident. Using this relation he propose a generalization of the Bekenstein-Hawking entropy in which the former and Euler characteristic are related in the equation S = χA / 8. Finally, he try to expose some conclusions and hypotheses about possible further development of this research
Maximum Quantum Entropy Method
Sim, Jae-Hoon; Han, Myung Joon
2018-01-01
Maximum entropy method for analytic continuation is extended by introducing quantum relative entropy. This new method is formulated in terms of matrix-valued functions and therefore invariant under arbitrary unitary transformation of input matrix. As a result, the continuation of off-diagonal elements becomes straightforward. Without introducing any further ambiguity, the Bayesian probabilistic interpretation is maintained just as in the conventional maximum entropy method. The applications o...
Transplanckian entanglement entropy
International Nuclear Information System (INIS)
Chang, Darwin; Chu, C.-S.; Lin Fengli
2004-01-01
The entanglement entropy of the event horizon is known to be plagued by the UV divergence due to the infinitely blue-shifted near horizon modes. In this Letter we calculate the entanglement entropy using the transplanckian dispersion relation, which has been proposed to model the quantum gravity effects. We show that, very generally, the entropy is rendered UV finite due to the suppression of high energy modes effected by the transplanckian dispersion relation
2015-09-29
antiferroelectrics. Phys. Rev. Lett. 110, 017603 (2013). 22. Cantor , B., Chang, I., Knight, P. & Vincent, A. Microstructural development in equiatomic...Science 345, 1153–1158 (2014). 24. Gali, A. & George , E. Tensile properties of high- and medium-entropy alloys. Intermetallics 39, 74–78 (2013). 25...148–153 (2014). 26. Otto, F., Yang, Y., Bei, H. & George , E. Relative effects of enthalpy and entropy on the phase stability of equiatomic high-entropy
Directory of Open Access Journals (Sweden)
Jinlu Sheng
2016-07-01
Full Text Available To effectively extract the typical features of the bearing, a new method that related the local mean decomposition Shannon entropy and improved kernel principal component analysis model was proposed. First, the features are extracted by time–frequency domain method, local mean decomposition, and using the Shannon entropy to process the original separated product functions, so as to get the original features. However, the features been extracted still contain superfluous information; the nonlinear multi-features process technique, kernel principal component analysis, is introduced to fuse the characters. The kernel principal component analysis is improved by the weight factor. The extracted characteristic features were inputted in the Morlet wavelet kernel support vector machine to get the bearing running state classification model, bearing running state was thereby identified. Cases of test and actual were analyzed.
Directory of Open Access Journals (Sweden)
Laskowski Rafał
2015-09-01
Full Text Available The internal diameter of a tube in a ‘church window’ condenser was estimated using an entropy generation minimization approach. The adopted model took into account the entropy generation due to heat transfer and flow resistance from the cooling-water side. Calculations were performed considering two equations for the flow resistance coefficient for four different roughness values of a condenser tube. Following the analysis, the internal diameter of the tube was obtained in the range of 17.5 mm to 20 mm (the current internal diameter of the condenser tube is 22 mm. The calculated diameter depends on and is positively related to the roughness assumed in the model.
International Nuclear Information System (INIS)
Kolb, E.W.; Lindley, D.; Seckel, D.
1984-01-01
For a cosmological model with d noncompact and D compact spatial dimensions and symmetry R 1 x S/sup d/ x S/sup D/, we calculate the entropy produced in d dimensions due to the compactification of D dimensions and show it too small to be of cosmological interest. Although insufficient entropy is produced in the model we study, the contraction of extra dimensions does lead to entropy production. We discuss modifications of our assumptions, including changing our condition for decoupling of the extra dimensions, which may lead to a large entropy production and change our conclusions
ENTROPY FUNCTIONAL FOR CONTINUOUS SYSTEMS OF FINITE ENTROPY
Institute of Scientific and Technical Information of China (English)
M. Rahimi A. Riazi
2012-01-01
In this article,we introduce the concept of entropy functional for continuous systems on compact metric spaces,and prove some of its properties.We also extract the Kolmogorov entropy from the entropy functional.
Directory of Open Access Journals (Sweden)
Yuntao Zhao
2018-01-01
Full Text Available The application-layer distributed denial of service (AL-DDoS attack makes a great threat against cyberspace security. The attack detection is an important part of the security protection, which provides effective support for defense system through the rapid and accurate identification of attacks. According to the attacker’s different URL of the Web service, the AL-DDoS attack is divided into three categories, including a random URL attack and a fixed and a traverse one. In order to realize identification of attacks, a mapping matrix of the joint entropy vector is constructed. By defining and computing the value of EUPI and jEIPU, a visual coordinate discrimination diagram of entropy vector is proposed, which also realizes data dimension reduction from N to two. In terms of boundary discrimination and the region where the entropy vectors fall in, the class of AL-DDoS attack can be distinguished. Through the study of training data set and classification, the results show that the novel algorithm can effectively distinguish the web server DDoS attack from normal burst traffic.
Li, Tie; He, Xiaoyang; Tang, Junci; Zeng, Hui; Zhou, Chunying; Zhang, Nan; Liu, Hui; Lu, Zhuoxin; Kong, Xiangrui; Yan, Zheng
2018-02-01
Forasmuch as the distinguishment of islanding is easy to be interfered by grid disturbance, island detection device may make misjudgment thus causing the consequence of photovoltaic out of service. The detection device must provide with the ability to differ islanding from grid disturbance. In this paper, the concept of deep learning is introduced into classification of islanding and grid disturbance for the first time. A novel deep learning framework is proposed to detect and classify islanding or grid disturbance. The framework is a hybrid of wavelet transformation, multi-resolution singular spectrum entropy, and deep learning architecture. As a signal processing method after wavelet transformation, multi-resolution singular spectrum entropy combines multi-resolution analysis and spectrum analysis with entropy as output, from which we can extract the intrinsic different features between islanding and grid disturbance. With the features extracted, deep learning is utilized to classify islanding and grid disturbance. Simulation results indicate that the method can achieve its goal while being highly accurate, so the photovoltaic system mistakenly withdrawing from power grids can be avoided.