Effects of Shannon entropy and electric field on polaron in RbCl triangular quantum dot

In this paper, the time evolution of the quantum mechanical state of a polaron is examined using the Pekar type variational method on the condition of the electric-LO-phonon strong-coupling and polar angle in RbC1 triangular quantum dot. We obtain the eigenenergies, and the eigenfunctions of the ground state, and the first excited state respectively. This system in a quantum dot can be treated as a two-level quantum system qubit and the numerical calculations are performed. The effects of Shannon entropy and electric field on the polaron in the RbC1 triangular quantum dot are also studied.

Shannon Entropy as a Measurement of the Information in a Multiconfiguration Dirac-Fock Wavefunction

Discrete Shannon entropy is applied to describe the information in a multiconfiguration Dirac Fock wavefunction. The dependence of Shannon entropy is shown as enlarging the configuration space and it can reach saturation when there are enough configuration state wavefunctions to obtain the convergent energy levels; that is, the calculation procedure in multiconfiguration Dirae Fock method is an entropy saturation process. At the same accuracy level, the basis sets for the smallest entropy are best able to describe the energy state. Additionally, a connection between the sudden change of Shannon information entropies and energy level crossings along with isoelectronic sequence can be set up, which is helpful to find the energy level crossings of interest in interpreting and foreseeing the inversion scheme of energy levels for an x-ray laser.

Invariance and Noises of Shannon Entropy for Information on Oxidative Activity of DNA in All Living Cells for Medical Diagnostics

We analyze oxidative activity of DNA due to fluorescence of chromosomes inside cells, using flow cytometry method with nanometer spatial resolution. Statistics of fluorescence is presented in histogram as frequency distributions of flashes in the dependence on their intensity and in distributions of Shannon entropy, which was defined on the base of normalized distribution of information in original histogram for frequency of flashes. We show that overall sum of entropy, i.e. total entropy E , for any histogram is invariant and has identical trends of changes all values of E(r) = lnr at reduction of histogram’ rank r. This invariance reflects informational homeostasis of chromosomes activity in multi-scale networks of entropy inside all cells in various samples of blood for DNA inside neutrophils, lymphocytes, inside all leukocytes of human and inside chicken erythrocytes for various dyes, colors and various excitations of fluorescence. Informational homeostasis of oxidative activity of 3D DNA in the full set of chromosomes inside living cells exists for any Shannon-Weaver index of biodiversity of cells, at any state of health different beings. Regulation perturbations in information activity DNA provides informational adaptability and vitality of cells at homeostasis support. Noises of entropy, during regulation of informational homeostasis, depend on the states of health in real time. The main structural reconstructions of chromosomal correlations, corresponding to self-regulation of homeostasis, occur in the most large-scale networks of entropy, for rank r<32. We show that stability of homeostasis is supported by activity of all 46 chromosomes inside cells. Patterns, hidden switching and branching in sequences of averages of H?lder and central moments for noises in regulation of homeostasis define new opportunities in diagnostics of health and immunity. All people and all aerobic beings have one overall homeostatic level for countdown of information activity of DNA inside cells. We noted very bad and dangerous properties of artificial cells with other levels of informational homeostasis for all aerobic beings in foods, medical treatment and in biotechnologies.

Quantile-Based Shannon Entropy for Record Statistics

The quantile-based entropy measures possess some unique properties than their distribution function approach.The present communication deals with the study of the quantile-based Shannon entropy for record statistics.In this regard a generalized model is considered for which cumulative distribution function or probability density function does not exist and various examples are provided for illustration purpose.Further we consider the dynamic versions of the proposed entropy measure for record statistics and also give a characterization result for that.At the end,we study F^(α)-family of distributions for the proposed entropy measure.

Nonrelativistic Shannon information entropy for Kratzer potential

The Shannon information entropy is investigated within the nonrelativistic framework. The Kratzer potential is con- sidered as the interaction and the problem is solved in a quasi-exact analytical manner to discuss the ground and first excited states. Some interesting features of the information entropy densities as well as the probability densities are demonstrated. The Bialynicki-Birula-Mycielski inequality is also tested and found to hold for these cases.

Experimental study and Shannon entropy analysis of pressure fluctuations and flow mode transition in fluidized dense phase pneumatic conveying of fly ash

The objective of this study was to relate experimental pressure fluctuation behavior to the transition in mode of flow observed in fluidized dense phase pneumatic conveying of fly ash.Shannon entropy and wavelet analysis were utilized to extract features of the flow regimes.Daubechies db4 wavelet analysis of pulsating air pressure revealed that the flow mechanism of fly ash in a fluidized dense phase possessed non-steady characteristics associated with gradual aeration of dunes along the direction of flow.Variations of Shannon entropy values along the length of the pipeline were assessed to determine the location at which the flow converted from dense to dilute phase mode.The effects of conveying parameters and specific power consumption on Shannon entropy and variations of the local power consumption coefficient are discussed.

Experimental investigation into transient pressure pulses during pneumatic conveying of fine powders using Shannon entropy

This paper presents the results of an ongoing investigation into transient pressure pulses using Shan- non entropy. Pressure fluctuations （produced by gas-solid two-phase flow during fluidized dense-phase conveying） are recorded by pressure transducers installed at strategic locations along a pipeline. This work validates previous work on identifying the flow mode from pressure signals （Mittal, Mallick, ＆ Wypych, 2014）. Two different powders, namely fly ash （median particle diameter 45 μm, particle den- sity 1950 kg/m3. loosely poured bulk density 950 kg/m3） and cement （median particle diameter 15 p,m, particle density 3060 kg/m3, loosely poured bulk density 1070 kg/m3）, are conveyed through different pipelines （51 mm I.D. × 70 m length and 63 mm I.D. × 24 m length）. The transient nature of pressure fluc- tuations （instead of steady-state behavior） is considered in investigating flow characteristics. Shannon entropy is found to increase along straight pipe sections for both solids and both pipelines. However, Shannon entropy decreases after a bend. A comparison of Shannon entropy among different ranges of superficial air velocity reveals that high Shannon entropy corresponds to very low velocities （i.e. 3-5 m/s） and very high velocities （i.e. 11-14 m/s） while low Shannon entropy corresponds to mid-range velocities （i.e. 6-8 m/s）.

The Use of GIS, Remote Sensing and Shannon’s Entropy Statistical Techniques to Analyze and Monitor the Spatial and Temporal Patterns of Urbanization and Sprawl in Zarqa City, Jordan

The aim of this study is to understand and quantify the urban growth and trend in Zarqa city during the period 1990 to 2014 and to produce land use and cover map for the studied area through the use of the GIS and remote sensing techniques with Shannon’s Entropy statistical method. For this purpose, three Landsat images were used for land use classification by using supervised maximum likelihood classification techniques to extract and assess the changes of urban lands. The results indicated that the urban areas in Zarqa city increased by 22.15% in the period from 1990 to 2005 and 14.86% from 2005 to 2014, with a rate of expansion of 0.96 and by 1.31 km2/ year for the two time periods respectively. The entropy value increased from 1.20 in the first period to 1.38 in the second, while the entropy value for the NE, NW, SE and SW zones showed high values, which confirmed that urban expansion and sprawling had existed in the past twenty four years in the study area. Urban expansion and sprawl cause different impacts on the natural, economic, and aesthetic aspects of the city which lead and guide government officials and planners to understand and monitor current growth and visualize future growth.

Performance Evaluation of Public Bus Transportation by Using DEA Models and Shannon’s Entropy:An Example From a Company in a Large City of China

The purpose of this paper is to assess the operational efficiency of a public bus transportation via a case study from a company in a large city of China by using data envelopment analysis(DEA)model and Shannon’s entropy.This company operates 37 main routes on the backbone roads.Thus,it plays a significant role in public transportation in the city.According to bus industry norms,an efficiency evaluation index system is constructed from the perspective of both company operations and passenger demands.For passenger satisfaction,passenger waiting time and passenger-crowding degree are considered,and they are undesirable indicators.To describe such indicators,a superefficient DEA model is constructed.With this model,by using actual data,efficiency is evaluated for each bus route.Results show that the DEA model with Shannon’s entropy being combined achieves more reasonable results.Also,sensitivity analysis is presented.Therefore,the results are meaningful for the company to improve its operations and management.

On Clausius, Boltzmann and Shannon Notions of Entropy

Discrete dynamical systems are given by the pair (X,f) where X is a compact metric space and f: X→X is a continuous map. During years, a long list of results have appeared to precise and understand what is the complexity of the systems. Among them, one of the most popular is that of topological entropy. In modern applications, other conditions on X and f have been considered. For example, X can be non-compact or f can be discontinuous (only in a finite number of points and with bounded jumps on the values of f or even non-bounded jumps). Such systems are interesting from theoretical point of view in Topological Dynamics and appear frequently in applied sciences such as Electronics and Control Theory. In this paper, we are reviewing the origins of the notion of entropy and studying some developing of it leading to modern notions of entropies. At the same time, we will incorporate some mathematical foundations of such old and new ideas until the appearance of Shannon entropy. To this end, we start with the introduction for the first time of the notion of entropy in thermodynamics by R. Clausius and its evolution by L. Boltzmann until the appearing in the twenty century of Shannon and Kolmogorov-Sinai entropies and the subsequent topological entropy. In turn, such notions have evolved to other recent situations where it is necessary to give some extended versions of them adapted to new problems. Of special interest is to appreciate the connexions of the notions of entropy from Boltzmann and Shannon. Since this history is long, we will not deal with the Kolmogorov-Sinai entropy or with topological entropy and modern approaches.

Quantile Version of Mathai-Haubold Entropy of Order Statistics

Many researchers measure the uncertainty of a random variable using quantile-based entropy techniques.These techniques are useful in engineering applications and have some exceptional characteristics than their distribution function method.Considering order statistics,the key focus of this article is to propose new quantile-based Mathai-Haubold entropy and investigate its characteristics.The divergence measure of theMathai-Haubold is also considered and some of its properties are established.Further,based on order statistics,we propose the residual entropy of the quantile-based Mathai-Haubold and some of its property results are proved.The performance of the proposed quantile-based Mathai-Haubold entropy is investigated by simulation studies.Finally,a real data application is used to compare our proposed quantile-based entropy to the existing quantile entropies.The results reveal the outperformance of our proposed entropy to the other entropies.

Characteristics Extraction of Vehicle State Information Based on Entropy Calculation

A method of extracting and detecting vehicle stability state characteristics based on entropy is proposed.The vehicle’s longitudinal and lateral dynamics models are established for complex driving and maneuver conditions.The corresponding state observer is designed by adopting the moving horizon estimation algorithm,which realizes the observation of the vehicle stability state considering the global state information.Meanwhile,the Shannon entropy is modified to approximate entropy,and the approximate entropy value of the observed vehicle state is calculated.Furthermore,the optimal controller is designed to further validate the reliability of the entropy value as the reference of control system.Simulation results demonstrate that this method can quickly detect the instability state of the system during the process of vehicle driving,which provides a reference for risk prediction and active control.

Entropy Bayesian Analysis for the Generalized Inverse Exponential Distribution Based on URRSS

This paper deals with the Bayesian estimation of Shannon entropy for the generalized inverse exponential distribution.Assuming that the observed samples are taken from the upper record ranked set sampling(URRSS)and upper record values(URV)schemes.Formulas of Bayesian estimators are derived depending on a gamma prior distribution considering the squared error,linear exponential and precautionary loss functions,in addition,we obtain Bayesian credible intervals.The random-walk Metropolis-Hastings algorithm is handled to generate Markov chain Monte Carlo samples from the posterior distribution.Then,the behavior of the estimates is examined at various record values.The output of the study shows that the entropy Bayesian estimates under URRSS are more convenient than the other estimates under URV in the majority of the situations.Also,the entropy Bayesian estimates perform well as the number of records increases.The obtained results validate the usefulness and efficiency of the URV method.Real data is analyzed for more clarifying purposes which validate the theoretical results.

Shannon information entropies for position-dependent mass Schrdinger problem with a hyperbolic well

The Shannon information entropy for the Schrodinger equation with a nonuniform solitonic mass is evaluated for a hyperbolic-type potential. The number of nodes of the wave functions in the transformed space z are broken when recovered to original space x. The position Sx and momentum S p information entropies for six low-lying states are calculated. We notice that the Sx decreases with the increasing mass barrier width a and becomes negative beyond a particular width a,while the Sp first increases with a and then decreases with it. The negative Sx exists for the probability densities that are highly localized. We find that the probability density ρ（x） for n = 1, 3, 5 are greater than 1 at position x = 0. Some interesting features of the information entropy densities ρs（x） and ρs（p） are demonstrated. The Bialynicki-Birula-Mycielski（BBM）inequality is also tested for these states and found to hold.

Shannon information entropies for rectangular multiple quantum well systems with constant total lengths

We first study the Shannon information entropies of constant total length multiple quantum well systems and then explore the effects of the number of wells and confining potential depth on position and momentum information entropy density as well as the corresponding Shannon entropy.We find that for small full width at half maximum（FWHM） of the position entropy density,the FWHM of the momentum entropy density is large and vice versa.By increasing the confined potential depth,the FWHM of the position entropy density decreases while the FWHM of the momentum entropy density increases.By increasing the potential depth,the frequency of the position entropy density oscillation within the quantum barrier decreases while that of the position entropy density oscillation within the quantum well increases.By increasing the number of wells,the frequency of the position entropy density oscillation decreases inside the barriers while it increases inside the quantum well.As an example,we might localize the ground state as well as the position entropy densities of the1 st,2 nd,and 6 th excited states for a four-well quantum system.Also,we verify the Bialynicki–Birula–Mycieslki（BBM）inequality.

Sample size adaptive strategy for time-dependent Monte Carlo particle transport simulation

When multiphysics coupling calculations contain time-dependent Monte Carlo particle transport simulations, these simulations often account for the largest part of the calculation time, which is insufferable in certain important cases. This study proposes an adaptive strategy for automatically adjusting the sample size to fulfil more reasonable simulations. This is realized based on an extension of the Shannon entropy concept and is essentially different from the popular methods in timeindependent Monte Carlo particle transport simulations, such as controlling the sample size according to the relative error of a target tally or by experience. The results of the two models show that this strategy can yield almost similar results while significantly reducing the calculation time. Considering the efficiency, the sample size should not be increased blindly if the efficiency cannot be enhanced further. The strategy proposed herein satisfies this requirement.

Information Theory of Cartography:An Information-theoretic Framework for Cartographic Communication

Map is one of the communication means created by human being.Cartographers have been making efforts on the comparison of maps to natural languages so as to establish a"cartographic language"or"map language".One of such efforts is to adopt the Shannon’s Information Theory originated in digital communication into cartography so as to establish an entropy-based cartographic communication theory.However,success has been very limited although research work had started as early as the mid-1960 s.It is then found that the bottleneck problem was the lack of appropriate measures for the spatial(configurational)information of(graphic and image)maps,as the classic Shannon entropy is only capable of characterizing statistical information but fails to capture the configurational information of(graphic and image)maps.Fortunately,after over 40-year development,some bottleneck problems have been solved.More precisely,generalized Shannon entropies for metric and thematic information of(graphic)maps have been developed and the first feasible solution for computing the Boltzmann entropy of image maps has been invented,which is capable of measuring the spatial information of not only numerical images but also categorical maps.With such progress,it is now feasible to build the"Information Theory of Cartography".In this paper,a framework for such a theory is proposed and some key issues are identified.For these issues,some have already been tackled while others still need efforts.As a result,a research agenda is set for future action.After all these issues are tackled,the theory will become matured so as to become a theoretic basis of cartography.It is expected that the Information Theory of Cartography will play an increasingly important role in the discipline of cartography because more and more researchers have advocated that information is more fundamental than matter and energy.

Similarity Studies of Corona Viruses through Chaos Game Representation

The novel coronavirus (SARS-COV-2) is generally referred to as Covid-19 virus has spread to 213 countries with nearly 7 million confirmed cases and nearly 400,000 deaths. Such major outbreaks demand classification and origin of the virus genomic sequence, for planning, containment, and treatment. Motivated by the above need, we report two alignment-free methods combing with CGR to perform clustering analysis and create a phylogenetic tree based on it. To each DNA sequence we associate a matrix then define distance between two DNA sequences to be the distance between their associated matrix. These methods are being used for phylogenetic analysis of coronavirus sequences. Our approach provides a powerful tool for analyzing and annotating genomes and their phylogenetic relationships. We also compare our tool to ClustalX algorithm which is one of the most popular alignment methods. Our alignment-free methods are shown to be capable of finding closest genetic relatives of coronaviruses.

Distributed sampling measurement method of network traffic in high-speed IPv6 networks

With the advent of large-scale and high-speed IPv6 network technology, an effective multi-point traffic sampling is becoming a necessity. A distributed multi-point traffic sampling method that provides an accurate and efficient solution to measure IPv6 traffic is proposed. The proposed method is to sample IPv6 traffic based on the analysis of bit randomness of each byte in the packet header. It offers a way to consistently select the same subset of packets at each measurement point, which satisfies the requirement of the distributed multi-point measurement. Finally, using real IPv6 traffic traces, the conclusion that the sampled traffic data have a good uniformity that satisfies the requirement of sampling randomness and can correctly reflect the packet size distribution of full packet trace is proved.