Value Of Noise Intensity Research Articles

Exploring the influence of refuges and additional foods on predator–prey interactions amidst environmental stochasticity and water level fluctuations

By considering that the predators have some additional foods apart from the focal prey and the prey take refuge, a predator–prey model with the effect of seasonality in a fluctuating environment is investigated in this study. Gaussian white noises, created by random fluctuation of water level, are introduced on the prey’s growth rate and predator’s mortality rate. Both the deterministic and stochastic systems are analyzed mathematically as well as numerically. Our analytical findings show that the intensity of environmental noise, additional foods and prey refuge play significant roles in survival as well as extinction of both prey and predator populations in the aquatic system. Our numerical results show that the effectual level of additional foods, depending on water level, has positive as well as negative effects on the predator and prey populations. We find that both species strongly persist at certain water level and for the low intensity of noise. However, for an increased value of noise intensity, they persist weakly and then go to extinction. Overall, our findings show that the variations of water level together with additional food and white noise plays crucial roles in persistence and extinction of species in the ecosystem.

Sound of natural and artificial rain impact on ETFE membranes

Thin membranes are known to produce a drum-like effect when subjected to rainfall. Rain noise affects acoustic comfort and might disrupt communication, speech intelligibility and cognitive task performance. Therefore, assessment of the characteristics of noise produced by impact of rain on membranes in different architectural settings is important. Given inherent disparities between natural and artificial precipitation-primarily in terms of droplet size distribution and terminal velocities-underscores the importance of conducting evaluations using natural rain noise. The focus of this study is on the comparative assessment of the sound generated by natural rainfall versus the sound generated by the impact of individual droplet in a semi-anechoic room on single Ethylene tetrafluoroethylene (ETFE) membranes. The study assesses the extent of spectral variations of the rain sound produced in both approaches and the corresponding absolute value of noise intensity.

Edukasi Bahaya Kebisingan Pada Pekerja Sektor Informal Kota Surabaya

One of the risks that can occur in the workplace is the risk of physical factors, namely noise. The physical environment is one of the important factors to play a role in the occurrence of work accidents. The role of factors in the work environment is very large with the occurrence of Occupational Safety and Health problems. To create a safe and comfortable work environment, it is necessary for workers and companies to apply Occupational Safety and Health when doing work. Noise is an unwanted sound in the work area due to production equipment or production machinery. The results of the initial survey through observation and hazard assessment using JSA and calculation using the CARL method. It was found that the highest risk assessment was the physical factor of noise. Therefore, the purpose of community service is carried out to prevent the existence of physical factor hazards, namely noise. Taking measurements using a Sound Level Meter, from the results of noise measurements that have been taken, there are work areas that exceed the Threshold Value (NAB), which gets a value of 87.92dB. It can be concluded that there is a high value of noise intensity, it should receive attention by controlling hazards that can be applied to the informal sector of PT.X, namely reducing production machine tools on the floor and moving them to the next floor, it can also be controlled by using Personal Protective Equipment (PPE), namely ear plugs when all production machine tools are operating.

Analysis of Noise Levels in Typical Passenger Cars

Passenger cars differ in their levels of emitted noise and mileage, which can have a negative impact on the environment and humans. This was confirmed by the results of this study on the noise levels generated by passenger cars that have the same parameters, or are of one type. The loudest place in the tested vehicles turned out to be the combustion engine compartment, with the average noise level exceeding 90 dB and exhibiting a noticeable, significant increase alongside an increase in the mileage of the vehicles. This value of noise intensity is classified as dangerous for the human body. As a result of the conducted tests, it can be concluded that an engine cover is an important element in damping the sounds emitted by an internal combustion engine after the use of an aluminum heat shield to increase noise absorption. In the future, the environmental problem of noise emission from cars can be solved by encouraging the use of quieter, electric vehicles.

Direction-dependent noise-induced synchronization in mobile oscillators.

Synchronization among uncoupled oscillators can emerge when common noise is applied on them and is famously known as noise-induced synchronization. In previous studies, it was assumed that common noise may drive all the oscillators at the same time when they are static in space. Understanding how to develop a mathematical model that apply common noise to only a fraction of oscillators is of significant importance for noise-induced synchronization. Here, we propose a direction-dependent noise field model for noise-induced synchronization of an ensemble of mobile oscillators/agents, and the effective noise on each moving agent is a function of its direction of motion. This enables the application of common noise if the agents are oriented in the same direction. We observe not only complete synchronization of all the oscillators but also clustered states as a function of the ensemble density beyond a critical value of noise intensity, which is a characteristic of the internal dynamics of the agents. Our results provide a deeper understanding on noise-induced synchronization even in mobile agents and how the mobility of agents affects the synchronization behaviors.

Stall-induced fatigue damage in nonlinear aeroelastic systems under stochastic inflow: Numerical and experimental analyses

This study focuses on characterizing the fatigue damage accumulated in nonlinear aeroelastic systems subjected to stochastic inflows through both numerical simulations and wind tunnel experiments. In the mathematical model, nonlinearities are assumed to exist either in the structure (via a cubic hardening nonlinearity in the pitch stiffness), or in the flow (via dynamic stall condition), or simultaneously in both the structural and aerodynamic counterparts. The aerodynamic loads in the attached flow and dynamic stall conditions are estimated using Wagner’s formulation and semi-empirical Leishman–Beddoes model, respectively. To augment the findings to in-field flow conditions, the oncoming wind flow is considered to be randomly time-varying in nature. The stochastic input flow fluctuations are modeled using a Karhunen–Loeve Expansion formulation. The response dynamics and the associated fatigue damage of the aeroelastic system, possessing different sources of nonlinearities, are systematically investigated under isolated cases of deterministic and stochastic input flows. Specifically, the pertinent role of stochasticity in the input flow is brought out by presenting the response dynamics and the associated fatigue damage accumulation for different values of noise intensity and time scale of the input flow fluctuation. It is demonstrated that under fluctuating flow conditions, the dynamics intermittently switch between attached flow and the dynamic stall regimes even at low mean flow speeds. The intermittent nature of the response varies as the time scale and intensity of the oncoming flow are varied. The role of torsional stresses as the predominant component dictating the fatigue damage accumulation irrespective of the source of nonlinearity is illustrated. Using the rainflow counting method and Miner’s linear damage accumulation theory, it is shown that the accumulated fatigue damage is substantially higher under stochastic flow conditions as compared to deterministic input flows. Importantly, it is observed that different time scales and intensities of the oncoming flow fluctuation play a pivotal role in dictating the fatigue damage in aeroelastic systems. Finally, fatigue damage is observed to be significantly higher for torsionally dominant oscillations in the dynamical stall regime compared to the oscillations at the attached flow regime. The numerical findings are strengthened by drawing comparisons with the preliminary results obtained from wind tunnel experiments performed on a NACA 0012 airfoil undergoing dynamic stall. To the best of our knowledge, this is the first study that systematically bridges the dichotomy between the stall-induced dynamical signatures in stochastic aeroelastic systems and maps the same to the corresponding structural damage.

Stochastic sensitivity analysis and early warning signals of critical transitions in a tri-stable prey-predator system with noise.

Near a tipping point, small changes in a certain parameter cause an irreversible shift in the behavior of a system, called critical transitions. Critical transitions can be observed in a variety of complex dynamical systems, ranging from ecology to financial markets, climate change, molecular bio-systems, health, and disease. As critical transitions can occur suddenly and are hard to manage, it is important to predict their occurrence. Although it is very tough to predict such critical transitions, various recent works suggest that generic early warning signals can detect the situation when systems approach a critical point. The most important indicator that predicts the risk of an upcoming critical transition is critical slowing down (CSD). CSD indicates a slow recovery rate from external perturbations of the stable state close to a bifurcation point. In this contribution, we study a two dimensional prey-predator model. Without any noise, the prey-predator model shows bistability and tri-stability due to the Allee effect in predators. We explore the critical transitions when external noise is added to the prey-predator system. We investigate early warning indicators, e.g., recovery rate, lag-1 autocorrelation, variance, and skewness to predict the critical transition. We explore the confidence domain method using the stochastic sensitivity function (SSF) technique near a stable equilibrium point to find a threshold value of noise intensity for a transition. The SSF technique in a two stage transition through confidence ellipse is described. We also show that the possibility of a transition to the predator-free state is independent of initial conditions. Our result may serve as a paradigm to understand and predict the critical transition in a two dimensional system.

Coherence Resonance Behavior of FitzHugh‐Nagumo Neurons Induced by Electromagnetic Field Driven by Phase Noise

Noise exists widely in the nervous system, and plays a crucial role in the nervous system information processing. Noise can not only enhance but also weaken the ability of the nervous system to process information. Neurons are in a complex and variable electromagnetic field. Electromagnetic induction plays an important role in regulating the changes of neuronal membrane potential. Therefore, this paper simulates the electromagnetic field environment of the nervous system with a memristor and analyses the rich coherence resonance behavior of FitzHugh‐Nagumo (FHN) neuron system under the drive of phase noise. By taking the amplitude, period and noise intensity of phase noise as the main parameters and the parameters of memristor as auxiliary parameters, the two‐parameter changes are made from the angle of the amplitude and period of phase noise, the amplitude and intensity of phase noise, and the noise intensity and period of phase noise, respectively. The dynamic behaviors of coherent resonance of FHN neuron system are analyzed from the amplitude and period, amplitude and intensity as well as intensity and period of phase noise, respectively. When the amplitude and period of the phase noise and the intensity and period of the phase noise are used as independent variables for the two‐parameter analysis, the FHN neuron system shows rich dynamic behaviors such as coherence mono‐resonance, coherence bi‐resonance and coherence multi‐resonance. Especially when the amplitude and period of phase noise change as two‐parameter, the system presents a coherence resonance of discharge pattern with period‐adding cluster discharge at the valley. When the amplitude and intensity of phase noise are taken as independent variables for two‐parameter analysis, FHN neuronal system presents single or dual coherence resonance at any value of noise intensity with the change of phase noise amplitude. The simulated results show that the FHN neuron system demonstrates rich coherence resonance behaviors under the drive of phase noise when the effect of electromagnetic induction in the nervous system is simulated by memristor.

A coral reef benthic system with grazing intensity and immigrated macroalgae in deterministic and stochastic environments

<abstract><p>As the most diverse, productive but vulnerable marine habitats in the world, coral reefs are easily affected by the ubiquitous environmental fluctuations, which could change the population dynamics and induce phase shifts of the ecosystem. In this paper, we consider a coral reef benthic system, where macroalgae, corals and algal turfs compete for the available space on a given region of the seabed with grazing intensity and immigrated macroalgae in both deterministic and stochastic environments. For the deterministic system, we analyze the existence and stability of equilibria, as well as the existence of bifurcations. For the stochastic system, sufficient conditions for the existence of the unique ergodic stationary distribution as well as the extinction of corals are obtained, by choosing suitable Lyapunov functions. Moreover, for the scenario that the system exhibits bistability between a macroalgal-coral coexistence equilibrium and a coral-free equilibrium in the absence of environmental fluctuation, we further investigate the irreversible noise-induced transition from macroalgal-coral coexistence to coral extirpation, and numerically estimate the critical values of noise intensity for the occurrence of such transition with the aids of the technique of stochastic sensitivity functions.</p></abstract>

Memory function of memristive Hindmarsh–Rose model driven by colored noise and electromagnetic induction

Based on the three-dimensional memristive Hindmarsh–Rose model, the effects of Gaussian colored noise and electromagnetic induction on memory function of the memristor and neural firing states are investigated in this paper. It is found that the memory function of memristor can be suppressed by a higher signal frequency, while enhanced by a relatively larger coefficient of the memristor. The memory function of memristor is destroyed by larger values of noise intensity and correlation rate between noises. The neural firing state can be transformed from the spiking state to the chaotic state with the increase of noise intensity or correlation rate. The firing states transition induced by the higher electromagnetic induction intensity is opposite to that by the stronger Gaussian colored noise.

A logistic-harvest model with allee effect under multiplicative noise

This work is devoted to the study of a stochastic logistic growth model with and without the Allee effect. Such a model describes the evolution of a population under environmental stochastic fluctuations and is in the form of a stochastic differential equation driven by multiplicative Gaussian noise. With the help of the associated Fokker–Planck equation, we analyze the population extinction probability and the probability of reaching a large population size before reaching a small one. We further study the impact of the harvest rate, noise intensity and the Allee effect on population evolution. The analysis and numerical experiments show that if the noise intensity and harvest rate are small, the population grows exponentially, and upon reaching the carrying capacity, the population size fluctuates around it. In the stochastic logistic-harvest model without the Allee effect, when noise intensity becomes small (or goes to zero), the stationary probability density becomes more acute and its maximum point approaches one. However, for large noise intensity and harvest rate, the population size fluctuates wildly and does not grow exponentially to the carrying capacity. So as far as biological meanings are concerned, we must catch at small values of noise intensity and harvest rate. Finally, we discuss the biological implications of our results.

Stochastic resonance in two coupled fractional oscillators with potential and coupling parameters subjected to quadratic asymmetric dichotomous noise

Exact analytical expressions for the average output amplitude gains in the very long-time limit for two coupled oscillators governed by fractional-order intrinsic and external damping, under the influence of a multiplicative quadratic asymmetric dichotomous noise affecting the two potential parameters and the coupling factors, and subjected to a noise-free or noise-modulated external periodic force with same frequency, have been derived. The trustworthiness of the analytical expressions has been checked by comparing the numerical results obtained using these for some typical cases with corresponding findings based on numerical simulations. The numerical simulations have also been used to investigate the time-evolution of a representative system in the transient state by studying the probability density and displacements of the two oscillators at different times and for different values of noise intensity. Analytical expressions have been used to obtain plots for gains versus noise intensity to study the effect of (i) variation in mass parameter of one oscillator keeping that of other the same, and (ii) change in the relative values of the two coupling coefficients. Furthermore, the special case where both the potential parameters are taken to be zero, which corresponds to rectilinear motion of the two particles in the absence of fluctuations, has been examined under the influence of the second-order noise and stochastic resonance has been found to occur at lower frequencies of the applied force. This highlights the importance of nonlinear term in the noise, which makes the rectilinear motion to be oscillatory. Also, the key role played by the coupling in this has been brought out.

Probabilistic analysis and ghost-stochastic resonance of a hybrid energy harvester under Gaussian White noise

In this present work, a hybrid energy scavenger using two mechanisms of transduction namely piezoelectric and electromagnetic and subjected to the Gaussian white noise is investigated. The stochastic averaging method is used here in other to construct the Fokker–Plank–Kolmogorov equation of the system whose the statistic response in the stationary state is the probability density. The mean square voltage and current are obtained for different value of white noise intensities as the output power generated by piezoelectric circuit and electromagnetic circuit. In addition, combining the Gaussian white noise and coherence excitation, the Ghost-Stochastic resonance is observed through the mean residence time and improve the amount of energy harvested by the scavenger. The agreement between the analytical method and those obtained numerically validates the effectiveness of analytical investigations. The results obtained in this manuscript reveal that, while the natural frequency is absent in the external coherent force, the amount of energy harvested by the energy scavenging device can be improved for certain value of noise intensity.

Resistance induced P-bifurcation and Ghost-Stochastic resonance of a hybrid energy harvester under colored noise

In this paper, a hybrid energy harvester using two mechanisms of transduction namely piezoelectric and electromagnetic and subjected to the colored noise is investigated. Using the stochastic averaging method, the Fokker−Planck−Kolmogorov equation of the system is constructed whose the statistic response in the stationary state is the probability density. The mean square voltage and current are obtained for different values of the linear and nonlinear resistance as the output power generated by piezoelectric circuit and electromagnetic circuit. The stability of the harvester is investigated by using probability approach. In addition, combining the colored noise and coherence excitation, the Ghost-Stochastic resonance is observed through the mean residence time and improve the amount of energy harvested by the scavenger. The agreements between the analytical method and those obtained numerically validate the effectiveness of analytical investigations. The results obtained in this manuscript shows the interest to use the load resistance exhibiting the nonlinearity in this research field and also, these results reveal that, while the natural frequency is absent in the coherent excitation, the system performance can be improved for a certain value of noise intensity.

Propagation characteristics of weak signal in feedforward Izhikevich neural networks

The feedforward neural network is widely applied in various machine learning architectures, in which the synaptic weight between layers plays an important role in the weak signal propagation. In this paper, the five-layer Izhikevich neural networks with excitatory or excitatory–inhibition neurons are employed to study the effect of Gaussian white noise and synaptic weight between layers on the weak signal transmission characteristics of the subthreshold excitatory postsynaptic currents signal imposed on the input layer. It can be found that there is an optimum value of noise intensity (a medium noise intensity) at which the weak signal can be stably propagated in the five-layer Izhikevich neural networks. The spike timing precision (STP) under the optimal noise intensity will become maximum by increasing the synaptic weight. The noise intensity and synaptic weight corresponding to the maximum value of the STP in the excitatory–inhibition network are smaller than those in excitatory–inhibition network. For the smaller or the bigger noise intensity, however, the STP will become very small, and the weak signal cannot be transmitted from the input layer to the output layer. Furthermore, the weak signal is propagated from the input layer to the output layer and enhanced under a larger synaptic weight in the feedforward neural networks.

Optimal control in a malaria model: intervention of fumigation and bed nets

Malaria is one of the world’s most serious health problems because of the increasing number of cases every year. First, we discuss a deterministic model of epidemic SIR-SI spread of malaria with the intervention of bed nets and fumigation. We found that the malaria-free equilibrium is locally asymptotically stable (LAS) when mathcal{R}_{0} <1 and unstable otherwise. A malaria endemic equilibrium exists and is LAS when mathcal{R}_{0} >1. Sensitivity analysis of mathcal{R}_{0} shows that the use of bed nets and fumigation can reduce mathcal{R}_{0}. We modify the previous model into a stochastic differential equation model to understand the effect of random environmental factors on the spread of malaria. Numerical simulations show that when mathcal{R}_{0} >1, a greater value of noise intensity σ generates a solution that is different from a deterministic solution; when mathcal{R}_{0} <1, regardless of the σ value, the solution approaches a deterministic solution. Then the deterministic model was modified into an optimal control model to determine the best strategy in controlling the spread of malaria by using fumigation as the control variable. Numerical simulations show that periodic fumigations cost less than constant intervention and can reduce the number of infected humans. Priority is given to the endemic prevention strategy rather than to the endemic reduction strategy. For more effective intervention, the value of mathcal{R}_{0} should receive close attention. A potentially endemic (mathcal{R}_{0}>1) environment requires more frequent fumigation than an environment that is not potentially endemic (mathcal{R}_{0}<1). A combination of the use of bed nets and fumigation can reduce the number of infected individuals at minimal cost.

Digital Signal Extraction by Means of Nonlinear Stochastic Filtration

The results of noise immunity analysis for digital communication systems using methods of nonlinear filtering are given. Nonlinear filtration is based on stochastic resonance effect. The stochastic resonance is given to a phenomenon that is manifest in nonlinear systems where by generally feeble input information (such as a weak signal) can be amplified and optimized by the assistance of noise. The stochastic resonance has been observed in a large variety of systems, including bistable ring lasers, semiconductor devices, chemical reactions, and mechanoreceptor cells in the tail fan of a crayfish. Numeral simulation of response at affecting input of the system on additive mixture of harmonic signal and white Gaussian noise are given. Amplitude spectrum of this output signal has been investigated. Results of the output signal-to-noise ratio calculation of the stochastic filter for the additive sum of a harmonic signal and white Gaussian noise for different values of the input noise dispersion are given. It is shown that the output signal-to-noise ratio of the system will peak at a certain value of noise intensity under a action of the input signal and noise. It is shown that the stochastic resonance effect provides separation of a digital signal from the white Gaussian noise. The comparative analysis of noise immunity of the matched filter and nonlinear stochastic filter for input square pulses are given. The effects of signal distortions in nonlinear processing with a stochastic filter are considered. Calculations of the coefficient of nonlinear distortions of a rectangular pulse are performed. It is shown that nonlinear distortions lead to a decrease in the signal-to-noise ratio at the output of the filter.

The effect of time-delayed feedback on logical stochastic resonance

We examine the possibility of obtaining logic operation in a quartic-bistable system with linear time-delayed feedback subjected to Gaussian noise. The effect of time-delayed feedback on the effective potential well is investigated, and explicit numerical stimulation is conducted to study the influence of delay time and strength of the time-delayed feedback on the responses of the system. Although the response deteriorates slightly at low values of noise intensity with time-delayed feedback and the peak correct probability decreases from 100% when the delay time is too long, the reliability of obtaining the desired logic output is enhanced in the higher noise boundary with the help of moderate time-delayed feedback. We also found that increasing the linear factor of the system can shift the optimal noise intensity to a higher level.

Solution of stochastic nonlinear time fractional PDEs using polynomial chaos expansion combined with an exponential integrator

The aim of this paper is to introduce an efficient numerical algorithm for the solution of stochastic time fractional stiff partial differential equations (PDEs). The time fractional derivative is described in the Caputo sense. By applying polynomial chaos (PC) expansion to discretize the random variable, a coupled time fractional deterministic system of PDEs is obtained. For the resulting system of time fractional PDEs we apply the Fourier spectral method to discretize the spatial variable, and use the fast Fourier transform (FFT) during the computation. Then, we use an exponential integrator method to overcome the stability issues due to the stiffness in the resulting time fractional semi-discrete system. The considered models have two challenging parameters, fractional order of equations and noise amplitude. In addition to exponential integrator, we also implemented a predictor–corrector method of Adams–Bashforth–Moulton type. We include numerical results of applying the developed method to stochastic time fractional Burgers and Kuramoto–Sivashinsky (KS) equations, for various values of noise intensity. A comparison of performance of the proposed scheme with fractional Adams method is also reported which confirms the efficiency and applicability of the proposed method based on the exponential integrator scheme.

Coding stimulus amplitude by correlated neural activity.

While correlated activity is observed ubiquitously in the brain, its role in neural coding has remained controversial. Recent experimental results have demonstrated that correlated but not single-neuron activity can encode the detailed time course of the instantaneous amplitude (i.e., envelope) of a stimulus. These have furthermore demonstrated that such coding required and was optimal for a nonzero level of neural variability. However, a theoretical understanding of these results is still lacking. Here we provide a comprehensive theoretical framework explaining these experimental findings. Specifically, we use linear response theory to derive an expression relating the correlation coefficient to the instantaneous stimulus amplitude, which takes into account key single-neuron properties such as firing rate and variability as quantified by the coefficient of variation. The theoretical prediction was in excellent agreement with numerical simulations of various integrate-and-fire type neuron models for various parameter values. Further, we demonstrate a form of stochastic resonance as optimal coding of stimulus variance by correlated activity occurs for a nonzero value of noise intensity. Thus, our results provide a theoretical explanation of the phenomenon by which correlated but not single-neuron activity can code for stimulus amplitude and how key single-neuron properties such as firing rate and variability influence such coding. Correlation coding by correlated but not single-neuron activity is thus predicted to be a ubiquitous feature of sensory processing for neurons responding to weak input.