India is rich in its heritage and culture. It has many historical monuments and temples where the walls are made of inscribed stones and rocks. The stone inscriptions play a vital role in portraying about the ancient incidents. Hence, the digitization of these stone inscriptions is necessary and contributes much for the epigraphers. Recently, the digitizing of these inscriptions began with the binarization

In this study, we analyzed daily records of newly diagnosed cases in Wuhan, Hubei excluding Wuhan (HEW), and China excluding Hubei (CEH) to investigate the impact of the new coronavirus outbreak in Wuhan on cities around it and throughout China. We used multifractal detrended cross-correlation analysis (MF-DXA) method to investigate the correlations between the daily number of patients in Wuhan and

This paper demonstrates the vulnerability of the Kirchhoff-Law-Johnson-Noise (KLJN) secure key exchanger to compromised random number generator(s) even if these random numbers are used solely to generate the noises emulating the Johnson noise of Alice’s and Bob’s resistors. The attacks shown are deterministic in the sense that Eve’s knowledge of Alice’s and/or Bob’s random numbers is basically deterministic

Our eyes are always in search of exploring our surrounding environment. The brain controls our eyes’ activities through the nervous system. Hence, analyzing the correlation between the activities of the eyes and brain is an important area of research in vision science. This paper evaluates the coupling between the reactions of the eyes and the brain in response to different moving visual stimuli. Since

In this work, we investigated the coupling among the activities of the brain and heart versus the changes in auditory stimuli using information-based analysis. Three music were selected based on the difference in their complexity. We applied these auditory stimuli on 11 subjects, and accordingly, computed and compared the Shannon entropy of electroencephalography (EEG) signals and heart rate variability

Stochastic resonance (SR) and self-induced stochastic resonance (SISR) are two kinds of important dynamical phenomena in the nonlinear system. SR occurs at the frequency of the characteristic signal. However, SISR can occur at a frequency that is included in the excitation. In present, there are volumes of literatures focusing on extracting the bearing fault characteristics from the vibration signal

Recently, several passive and active attack methods have been proposed against the Kirchhoff–Law–Johnson–Noise (KLJN) secure key exchange scheme by utilizing direct (DC) loop currents. The DC current attacks are relatively easy, but their practical importance is low. On the other hand, parasitic alternating (AC) currents are virtually omnipresent in wire-based systems. Such situations exist due to

Stochastic resonance (SR) can realize bearing fault signal diagnosis by transferring noisy energy. In order to enhance the output response of the system and realize effective signal extraction, the nonlinear mass fluctuation SR system caused by nonlinear asymmetric dichotomous noise is cascaded to obtain the cascaded nonlinear mass fluctuation SR system. First, the output amplitude gain of the first-stage

Inverse Weibull distribution is one of the distributions having a wide use for modeling system reliability and survival analysis. Recently, some of the researchers have compounded these distributions with some others to improve their models. In this paper, we present the compounded generalized inverse Weibull with geometric distribution. To estimate the parameters, we discuss the maximum likelihood

A nonlinear master equation is derived, reflecting properly the entropy of open quantum systems. In contrast to linear alternatives, its equilibrium solution is exactly the canonical Gibbs density matrix. The corresponding nonlinear equation for the Wigner function accounts rigorously for the thermo-quantum entropy. It reduces at large friction to the quantum Smoluchowski equation in the coordinate

We propose one-step memory random walk on complex networks for which at each time step, the walker will not be allowed to revisit the last position. Mean first passage time is adopted to quantify its search efficiency and a procedure is provided for calculating it analytically. Interestingly, we find that in the same circumstance, one-step memory random walk usually takes less time than random walk

Unmanned Aerial Vehicles (UAVs) installed with a gripper is an effective and robust way to grab the wanted object from inaccessible locations. In this study, we develop a novel control mechanism to regulate the nonlinear dynamics of the aerial manipulator. In this research, hex-rotor UAV is chosen in order to fulfill the mission requirement in terms of size and weight of the object. It is equipped

In this paper, we deal with the non-autonomous logistic growth model with time-dependent intrinsic growth rate and carrying capacity. Accounting for errors in recorded data, randomness is incorporated into the equation by assuming that the input parameters are random variables. The uncertainty of the model output is quantified by approximations of the first probability density function via the random

Fisher information is a measure to quantify information and estimate system-defining parameters. The scaling and uncertainty properties of this measure, linked with Shannon entropy, are useful to characterize signals through the Fisher–Shannon plane. In addition, several non-gaussian distributions have been exemplified, given that assuming gaussianity in evolving systems is unrealistic, and the derivation

Since the brain regulates our facial reactions, there should be a relationship between their activities. Moving (dynamic) visual stimuli are an important type of visual stimuli that we are dealing with in our daily life. Since EMG and EEG signals contain information, we evaluated the coupling of the reactions of facial muscles and brain to various moving visual stimuli by analysis of the embedded information

This paper presents the development process of the exponential smoothing (ES) model, starts with the traditional ES model and then focuses to the multiple seasonal ES model. This paper describes and visualizes the existing multiple seasonal ES models for the purpose of finding guidance for further development. Though some progress and development have been made in this field, the best fit for many

Speech processing systems are very important in different applications involving speech and voice quality such as automatic speech recognition, forensic phonetics and speech enhancement, among others. In most of them, the acoustic environmental noise is added to the original signal, decreasing the signal-to-noise ratio (SNR) and the speech quality by consequence. Therefore, estimating noise is one

In this paper, we proposed multiscale cross-recurrence quantification analysis (MSCRQA) method to analyze the dynamic states of two time series at different time scales. We apply this method to model system (two coupled van der Pol oscillators) and real-world system (SSEC and SZSE). It demonstrates that the MSCRQA can show richer and more recognizable information compared with single time scale. The

In this study, we utilized the prevailing economic policy uncertainty index (EPU) as the proxy of state economic fluctuation and investigated Sino–US economic fluctuation long horizon cross-correlation with a multifractal detrended cross-correlation analysis (MF-DCCA). With the MF-DCCA approach, we found a reliable long-range cross-correlation between China and US EPU changes. In addition, we discovered

Prediction of urban noise is becoming more significant for tackling noise pollution and protecting human mental health. However, the existing noise prediction algorithms neglected not only the correlation between noise regions, but also the nonlinearity and sparsity of the data, which resulted in low accuracy of filling in the missing entries of data. In this paper, we propose a model based on multiple

In (Nature) Science Report 5 (2015) 13653, Vadai, Mingesz and Gingl (VMG) introduce a new Kirchhoff-law-Johnson-noise (KLJN) secure key exchanger that operates with 4 arbitrary resistors (instead of 2 arbitrary resistance values forming 2 identical resistor pairs in the original system). They state that in this new, VMG-KLJN, non-equilibrium system with nonzero power flow, the security during the exchange

We utilize the multifractal detrended cross-correlation analysis (MF-DCCA) to investigate the cross-correlations between the US economic policy uncertainty (EPU) and US stock markets in the framework of Fractal Market Hypothesis (FMH). The data contain daily closing values of EPU, and the returns of Dow Jones Industrial Average Index (DJI), S&P 500 index (GSPC) and NASDAQ Composite Index (IXIC). Our

A detailed examination of the effect of harvesting on a population has been carried out by extending the standard cubic deterministic model by considering a population under Allee effect with a quadratic function representing harvesting. Weak and strong Allee effect transitions, carrying capacity, and Allee threshold change according to harvesting are first discussed in the deterministic model. A Fokker–Planck

This paper introduces the fractal version of the higher-order dispersion model for the construction of novel soliton solutions through fractal variational technology. Higher-order dispersion model theoretical study of the soliton propagation dynamics is known in the absence of self-phase modulation. In the context of negligibly small group velocity dispersion, this model involves higher-order spatio-temporal

Waveguide analysis indicates that a triaxial cable with uniform bootstrapping is a transmission line with an adjustable characteristic impedance. When the bootstrapping level is high, the characteristic impedance is high. The cable capacitance is reduced while the cable inductance is increased. Simulations confirm that the transmission-line circuit and the lumped-element circuit, including the mutual

This paper investigates whether foreign capital is smarter money using multifractal cross-correlation analysis (MFCCA) and nonlinear Granger Causality test. Using multifractal detrended fluctuation analysis (MF-DFA) method, we find that time series of stock returns, foreign-capital inflow from Shanghai–Hong Kong Stock Connect (SHKSC), and domestic-capital flow (proxied by margin-trading activities

This paper examines the fluctuation and frequency of the motion of a homogeneous solid on a horizontal plane on an exponential crisscross spring. The governing equations of this oscillator are investigated using a modified Homotopy Perturbation method, Energy balance method and artificial parameter–Linstedt–Poincare’ method. A comparison of solutions shows that the fluctuation and frequency of the

Though the high-frequency volatility approaches are increasingly introduced to forecast financial risk in recent years, whether they can improve the accuracies of risk forecasts remains controversial. This paper compares the risk forecasting abilities of four pairs of low- and high-frequency volatility models, by calculating and evaluating the downside and upside value-at-risk and expected shortfall

This paper explores the COVID-19 influences on the cross-correlation between the movie market and the financial market. The nonlinear cross-correlations between movie box office data and Google search volumes of financial terms such as Dow Jones Industrial Average (DJIA), NASDAQ and PMI are investigated based on multifractal detrended cross-correlation analysis (MF-DCCA). The empirical results show

One of the crucial areas of pregnancy research is to analyze the pregnancy development. For this purpose, scientists analyze the different conditions of fetuses to understand their development. In this paper, we conducted complexity and information-based analyses on Phonocardiogram (PCG) signals to investigate pregnancy development. We calculated the fractal dimension, approximate entropy, and sample

In this paper, a Fuzzy controller model has been converted into a time-dependent nonlinear model and then quadratic Riccati differential equation was analyzed to satisfy the solution of the nonlinear active noise behavior of Fuzzy controller. Further, the approximate solutions of this equation using non-perturbation methods i.e., adomian decomposition method (ADM), variational iterational method (VIM)

A stochastic differential formulation for the collective dynamics of ion channel clusters in excitable membranes is developed from the so-called “reduced strong diffusion formulation”. In this error bound optimizing reduced formulation, the potassium channel states n4 and n3, and, the sodium channel states m3h1 and m2h1 are the retained states; consequently, the formulation accommodates only four channel

A fault or mechanical flaw causes several feeble swings in the position signal. Identification of such swings by encoders can help to identify machine performance and health status and provide a convenient alternative to a vibration-based monitoring system. In operations, the trend is usually several orders higher than the interested magnitude swings, thus increasing the difficulty of identifying feeble

Research on fluctuations in energy and temperature is presented for a small specimen. The small specimen in contact with a heat bath shows energy fluctuations, ΔE, at the constant temperature. On the other hand, when this small specimen is isolated from the reservoir and adiabatic isolation is kept, it exhibits temperature fluctuations, ΔT, at the constant energy. This means that the temperature is

This paper investigates the error probability of our proposed modulation technique which is produced by combining the existing pulse position modulation (PPM) technique with Hadamard code (HC). Moreover, the HC is also combined with differential PPM (DPPM). The error performances of existing technique and the proposed technique are compared at high-order modulation (HOM) and low-order modulation. The

With the development of artificial intelligence in recent years, deep learning has been widely used in mechanical system signal classification but the impact of different feature extractions on the efficiency and effectiveness of deep learning neural networks is more important. In this study, a vehicle classification based on engine acoustic emission signal in the time domain, the frequency domain

The technique of Chebyshev polynomials of discrete variable is used to analyze a random time series. The main result of the work is a new theoretical relationship between the structure function and the discrete Chebyshev spectrum. The relationship is used for the trend-resistant structural analysis of electrochemical noise of corrosion process and for the trend-resistant structural analysis of electronic

With the rapid development of economic globalization, the stock markets in China and the US are increasingly linked. The fluctuation features and cross-correlations of the two countries’ markets have attracted extensive attention from market investors and researchers. In this paper, the fractal analysis methods including multifractal asymmetric detrended cross-correlation analysis (MF-ADCCA) and coupled

Traffic noise barriers are one of the most important ways of environmental noise pollution control. Profiled barriers are one of the most successful noise control screens. A simple mathematical model representation of the zones behind rigid and absorbent barriers with the highest insertion loss using the destructive effect of the indirect path via barrier image is introduced. The results are compared

Analysis of fluctuations of uterine contractions under varied gestational ages is clinically significant. In this work, fluctuations associated with Preterm pregnancies are analyzed. For this, uterine electromyography (uEMG) signals in Preterm condition with varied gestational ages are considered. The signals are subjected to Adaptive Fractal Analysis (AFA) where a global trend is identified using

In this paper, the regime shift behaviors between the prosperous state and the extinction state and stochastic resonance (SR) phenomenon for a metapopulation system subjected to time delay and correlated Gaussian colored noises are investigated. Through the numerical calculation of the modified potential function and the stationary probability density function (SPDF), one can make clearly the following

The paper compares the accuracy of two different three points Interpolated Discrete Fourier Transform (M3IpDFT and C3IpDFT) algorithms in the presence of Gaussian white noise. The above two algorithms use the magnitude and the complex value of spectrum line for interpolation, respectively. The theoretical expressions of variances of frequency estimation due to noise are derived and then verified by

A multi-microphone array speech enhancement method using Generalized Sidelobe Canceller (GSC) beamforming with Combined Postfilter (CP) and Sparse Non-negative Matrix Factorization (SNMF) is proposed in this paper. GSC beamforming with CP and SNMF is implemented to reduce directional noise, diffuse noise, residual noise and to separate interferences in adverse environment. In this paper, the directional

Spectrum seems to be the lifeblood of wireless communication, which is of high demand as the traffic doubles every year. This increasing demand drives towards 5G NR, which is expected to support 100 folds increase in mobile devices, gigabit user data rate, ultra-low latency, high traffic and ultra-reliability. Since most of the available spectrum has been saturated, new methods that make use of spectrum

Surface electromyography (sEMG) is a non-invasive technique to assess the electrical activity of contracting skeletal muscles. sEMG-based muscle fatigue detection plays a key role in sports medicine, ergonomics and rehabilitation. These signals are random, multicomponent, nonlinear and the degree of fluctuations is higher in dynamic contractions. Hence, the extraction of reliable biomarkers remains

In this paper, we propose Jensen–Shannon divergence (JSD) based on horizontal visibility graph (HVG) to measure the time series irreversibility for both stationary and non-stationary series efficiently. Numerical simulations are first conducted to show the validity of the proposed method and then empirical applications to the financial time series and traffic time series are investigated. It can be

In this paper, the performance of compressive sensing (CS)-based technique for speech enhancement has been studied and results analyzed with recovery algorithms as a comparison of their performances. This is done for several recovery algorithms such as matching pursuit, orthogonal matching pursuit, stage-wise orthogonal matching pursuit, compressive sampling matching pursuit and generalized orthogonal

It is demonstrated how the Schrödinger equation emerges from stochastic momentum kicks of the force carriers, transmitting the fundamental interactions between the point particles. The picture is consistent with quantum field theory and points out that the force carriers are the only quantum particles. Since the latter are waves in the coordinate space, they are responsible for the wavy character of

The problem of statistical modeling of the geometric count data with a specific probability model of lifetimes is of interest and importance in reliability. In this paper, we construct a geometric process (GP), with parameter a, for modeling the geometric count data when the distribution of first occurrence time is a scaled Muth with parameters λ and β. We investigate the estimators of the process

Finite word length is a practical limitation when discrete-time systems are implemented by using digital hardware. This restriction degrades the performance of a discrete-time system and may even lead it toward instability. This paper, addresses the stability and disturbance attenuation performance analysis of nonlinear discrete-time systems under the influence of energy-bounded external interferences

Electromyogram (EMG) signals are mostly affected by a large number of artifacts. Most commonly affecting artifacts are power line interference (PLW), baseline noise and ECG noise. This work focuses on a novel attenuation noise removal strategy which is concentrated on adaptive filtering concepts. In this paper, an enhanced squirrel search (ESS) algorithm is applied to remove noise using adaptive filters

This study addresses a new question regarding the security of the Kirchhoff-Law-Johnson-Noise (KLJN) scheme compromised by DC sources at Alice and Bob: What is the impact of these parasitic sources on active attacks, such as the man-in-the-middle (MITM) attack, or the current injection attack if Alice and Bod did not eliminate these sources? The surprising answer is that the parasitic DC sources actually

Stochastic resonance systems have the advantages of converting noise energy into signal energy, and have great potential in the field of signal detection and extraction. Aiming at the problems of the performance of classical stochastic resonance system whose model is not perfect enough and the correlation coefficients between parameters is too large to be optimized by algorithm, then a novel model

Stochastic resonance systems have the advantages of converting noise energy into signal energy, and have great potential in the field of signal detection and extraction. Aiming at the problems of the performance of classical stochastic resonance system whose model is not perfect enough and the correlation coefficients between parameters is too large to be optimized by algorithm, then a novel model

This paper investigates the performances of differential phase shift keying (DPSK) and quadrature phase shift keying (QPSK) for 400 channels super dense system for the data rate of 160, 170, 180 and 200Gbps, respectively. Evaluation has also been investigated in terms of bit error rate (BER), quality factor and received output power with varying input power. Final analysis has reflected that DPSK modulation

In this paper, the dynamical complexity of FHN neuron system under the co-excitation of correlated noises and periodic signals is studied by means of information theory measures. Based on the definition of statistical complexity and normalized Shannon entropy, as well as the Bandt–Pompe algorithm, the total statistical complexity and the total normalized Shannon entropy of the FHN neuron system are

The concept of using special electrical circuit design to realize “cold resistors”, i.e., an active resistor circuitry with lower effective noise temperature, was first introduced about 80 years ago. Later on, various kinds of artificial resistors were applied in different research areas, such as gravitational wave detection, photo-amplifiers and quartz oscillators. Their proofs of concepts were experimentally

In a dynamic environment with wind forces and tornadoes, eliminating fluctuations and noise is critical to get the optimal results. Avoiding collision and simultaneous arrival of multiple unmanned aerial vehicles (multi-UAVs) is also a great problem. This paper addresses the cooperative path planning of multi-UAVs with in a dynamic environment. To deal with the aforementioned issues, we combine the

We introduced a new method to compute the European Call (and Put) Option price under the assumption of multifractional Brownian motion (mBm). The reason why we need a procedure for estimating the Option price is due to the absence of a closed formula for this process. To compute the Option price, we first simulated the logarithmic price under mBm and, by using a discount factor, we computed the option’s

The discrete double Fourier transform (DDFT) was developed to search for large-scale multi-periodic patterns in the presence of noise and is based on detection of the equidistant series of harmonics generated by the periodic patterns in the discrete Fourier transform (DFT) spectra. As DDFT retains all generic features of the Fourier transform, the corresponding pattern correlation function (PCF) related