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© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works Parameter estimation is vital for modeling and control of fuel cell systems. However, the nonlinear parameterization is an intrinsic characteristic in the fuel cell models such that classical parameter estimation schemes developed for linearly parameterized systems cannot be applied. In this paper, an alternative framework of adaptive parameter estimation is designed to address the real-time parameter estimation for fuel cell systems. The parameter estimation can be divided into two cascaded components. First, the dynamics with the unknown parameters are estimated by a new unknown system dynamics estimator (USDE). Inspired by an invariant manifold, this USDE is designed by applying simple filter operations such that the information of the state derivative is not required. Secondly, an adaptive law driven by the function approximation error is proposed for recovering unknown model parameters. Exponential convergence of the estimated parameters to the true values can be proved under the monotonicity condition. Finally, experimental results on a practical proton exchange membrane fuel cell system are given to verify the effectiveness of the proposed schemes.

This paper presents a stress detection algorithm using heart rate variability (HRV) parameters. Five-minute electrocardiograms were recorded at rest and under exam stress (252 students were involved). The determined HRV parameters were applied to detect stress by means of several classification algorithms. We analysed linear indices in the time (standard deviation of NN intervals (SDNN) and root mean square of successive RR interval differences (RMSSD)) and frequency domains (low frequency (LF) and high frequency (HF) power as well as LF/HF ratio). To study nonlinear HRV indices, we evaluated approximate entropy (ApEn), sample entropy (SampEn), α1 (DFA1) and α2 (DFA2) scaling exponents, correlation dimension D2, and recurrence plot quantification measures (recurrence rate (REC), mean diagonal line length (Lmean), maximum diagonal line length (Lmax), determinism (DET), and Shannon entropy (ShanEn)). Receiver operating characteristic (ROC) was used to test the performance of the classifiers derived from HRV. The highest area under the ROC curve (AUC), sensitivity, and specificity were found for mean RR-interval, DFA1, DFA2, RMSSD, and Lmax. These parameters were used for stress/rest classification with the help of algorithms that are common in clinical and physiological applications, i.e. logistic regression (LR) and linear discriminant analysis (LDA). Classification performance for stress was quantified using accuracy, sensitivity and specificity measures. The LR achieved an accuracy of 68.25 % at an optimal cutoff value of 0.57. LDA determined stress with 67.46 % accuracy. Thus, HRV parameters can serve as an objective tool for stress detection.

A improved torsional nonlinear dynamic model of double-helical star gearing system of Geared Turbofan (GTF) aero-engine is established, considering multiple nonlinear parameters and the effect of tool withdrawal groove that connect helical gears on both sides of double-helical gear. The dynamic responses of the system are solved by Runge–Kutta numerical integration method. The results reveal that the double-helical star gearing system exhibits abundant torsional nonlinear behaviors, which were illustrated by the evolution curve of dynamic meshing force and load sharing coefficient under varying rotational speed, gear backflash and width of groove, with either side of helical gear pairs in double-helical gear system are considered and illustrated, respectively, which can be hardly seen in previous research and worth being analyzed for better understanding of undesirable torsional dynamic motion for the double-helical gear system and therefore provide a reference for the design and control of gear system.

As an efficient meta-heuristic algorithm, the whale optimization algorithm (WOA) has been extensively applied to practical problems. However, WOA still has the drawbacks of converging slowly, and jumping out from extreme points especially for large scale optimization problems. To overcome these defects, a modified whale optimization algorithm integrated with a crisscross optimization algorithm (MWOA-CS) is proposed. In MWOA-CS, each dimension of the optimization problem updates its position by randomly performing improved WOA or crisscross optimization algorithm during the entire iterative process. The improved WOA adopts the new nonlinear convergence factor and nonlinear inertia weight to tune the ability of exploitation and exploration. To analyze the performance of MWOA-CS, a series of numerical experiments were performed on 30 test benchmark functions with dimension ranging from 300 to 1000. The experimental results revealed that the presented MWOA-CS provided better convergence speed and accuracy, and meanwhile, displayed a significantly more effective and robust performance than the original WOA and other state of the art meta-heuristic algorithms for solving large scale global optimization problems.

In this study, networks of interconnected heterogeneous micro-grids are studied. The transient dynamics is modelled as an averaging process whereby micro-grids are assimilated to dynamic agents in a network. An analysis of the convergence of the consensus dynamics is carried out under different assumptions on the damping and inertia parameters and the topology of the network. This study provides an insight into the relation between the network topology and the system's response. An analysis of the ways in which the heterogeneous inertial parameters affect the transient response of the network is also implemented. Additionally, the conditions that guarantee stability are identified when the system is under the influence of uncertain non-linear parameters. Finally, simulations are carried out based on a model calibrated on an existing network in the UK under parameter uncertainties.

Aiming at solving problems such as non-linear, time-varying parameters, and weak digital computing capability in the underground drainage system, the monitoring system is built based on a digital signal processor (DSP). Adopting DSP28335 as its control core, the hardware circuit and software program are designed in this monitoring system. The single-neuron fuzzy proportional, integration, and differential (PID) control algorithm with feedforward proportional and differential compensation is proposed in this study. The simulation results are compared and analysed with a traditional PID algorithm, fuzzy PID algorithm, and single-neuron fuzzy PID algorithm with feedforward in Matlab/Simulink, and the experimental platform is built to verify the application effect of three control algorithms. The simulation and experiment results show that the single-neuron fuzzy PID algorithm with feedforward has significant advantages such as shorter adjustment time, good adaptivity, and strong anti-interference ability, which could effectively improve the work efficiency of an underground mine drainage monitoring system.

PurposePM10 is one of the most dangerous air pollutants which is harmful to the ecological system and human health. Accurate forecasting of PM10 concentration makes it easier for the government to make efficient decisions and policies. However, the PM10 concentration, particularly, the emerging short-term concentration has high uncertainties as it is often impacted by many factors and also time varying. Above all, a new methodology which can overcome such difficulties is needed.Design/methodology/approachThe grey system theory is used to build the short-term PM10 forecasting model. The Euler polynomial is used as a driving term of the proposed grey model, and then the convolutional solution is applied to make the new model computationally feasible. The grey wolf optimizer is used to select the optimal nonlinear parameters of the proposed model.FindingsThe introduction of the Euler polynomial makes the new model more flexible and more general as it can yield several other conventional grey models under certain conditions. The new model presents significantly higher performance, is more accurate and also more stable, than the six existing grey models in three real-world cases and the case of short-term PM10 forecasting in Tianjin China.Practical implicationsWith high performance in the real-world case in Tianjin China, the proposed model appears to have high potential to accurately forecast the PM10 concentration in big cities of China. Therefore, it can be considered as a decision-making support tool in the near future.Originality/valueThis is the first work introducing the Euler polynomial to the grey system models, and a more general formulation of existing grey models is also obtained. The modelling pattern used in this paper can be used as an example for building other similar nonlinear grey models. The practical example of short-term PM10 forecasting in Tianjin China is also presented for the first time.

The classical Wiener filter was engaged into identifying the linear structures, resulting in clear and incredible drawbacks in working with nonlinear integrated system. Currently, the Hermitian-Wiener system are suitable for unpredicted sub-system that consists of numerous and complex inputs. The system introduces a two-stage to analyze the subintervals where the output nonlinearities are noninvertible, through using the unknown orders and parameters. Finally, a practical strategy would be discussed to analyze the nonlinear parameters.

Introduction.Intensive development of coal mining in Kuzbass contributes to the growth of professional pathology. Production factors lead to autonomous dysregulation and damage to peripheral nerves, and the development of upper limb polyneuropathy. Analysis of heart rate variability is currently widely used to determine the features of vegetative maintenance, in the conditions of a clinoorthostatic test, it allows you to assess the safety of vegetative regulation, and makes it possible to predict the course of the disease.The aim of the studywas to study the dynamics of heart rate variability in clinoorthostatic samples in miners with professional upper limb polyneuropathy to assess the nature and level of vegetative disorders.Materials and methods. Th e analysis of changes in spectral and nonlinear parameters of heart rate variability at the stages of performing an active clinoorthostatic test in 40 miners with the established diagnosis of upper limb polyneuropathy and 20 people who do not have harmful occupational factors and symptoms of polyneuropathy, who made up the control group, was carried out.Results. Th e subjects with polyneuropathy had an initial decrease in high-frequency and low-frequency spectral parameters of heart rate variability as a sign of vegetative insuffi ciency. Th e absence of an increase in the low frequency index for a sample with active orthostasis indicates a violation of the sympathetic link reaction, reduced sensitivity of baroreceptors. Changes in the spectral index of a very low frequency of heart rate variability remained in the range of normal values at all stages of the test.Conclusions. Th e study of heart rate variability at the stages of a clinoorthostatic test allows us to determine the nature and level of violations of vegetative regulation in miners with professional polyneuropathy, as well as the possibility of compensatory mechanisms.

Considering multiple nonlinear parameters, a nonlinear dynamic model of star gear-rotor-bearing transmission system of GTF (Geared Turbofan Engine) gearbox is established. The dynamic responses are obtained through Runge-Kutta numerical integration method, and the responses with the variation of input rotational speed are analyzed and illustrated. The abundant nonlinear characteristics are presented in the results, which could be guidance to avoid undesirable nonlinear motion, and provide a reference for the design and control of the transmission system in GTF gearbox.

В данной работе были разработаны мероприятия по оптимизации режима работы ферросплавной руднотермической печи. Проведены эксперименты с целью уточнения сопротивлений печного контура, а также была осуществлена регистрация Ñ€ÐµÐ¶Ð¸Ð¼Ð½Ñ‹Ñ Ð¿Ð°Ñ€Ð°Ð¼ÐµÑ‚Ñ€Ð¾Ð² в Ñ Ð¾Ð´Ðµ реального производственного процесса. Полученные в Ñ Ð¾Ð´Ðµ эксперимента данные были проанализированы, после чего были сформированы, при Ð½ÐµÐ¾Ð±Ñ Ð¾Ð´Ð¸Ð¼Ð¾ÑÑ‚Ð¸, рекомендации по оптимизации режимов работы исследуемой печи для каждой из отпаек трансформаторного агрегата, которые были задействованы в работе, позволяющие ÑÐ¾Ñ Ñ€Ð°Ð½Ð¸Ñ‚ÑŒ требуемую полезную потребляемую активную мощность, но при этом повысить коэффициент полезного действия, а также снизить затраты электрической энергии., In this work, measures were developed to optimize the operating mode of a ferroalloy ore-thermal furnace. Experiments were carried out to clarify the resistance of the furnace circuit, and the registration of operating parameters was carried out during the real production process. The data obtained during the experiment were analyzed, after which, if necessary, recommendations were formed for optimizing the operating modes of the furnace under study for each of the transformer unit's solders that were involved in the operation, allowing to maintain the required useful consumed active power, but at the same time increase the efficiency, as well as reduce the cost of electrical energy.

This study derived a novel computation algorithm for a mechanical system with multiple friction contact interfaces that is well-suited to the investigation of nonlinear mode characteristic of a coupling system. The procedure uses the incremental harmonic balance method to obtain the nonlinear parameters of the contact interface. Thereafter, the computed nonlinear parameters are applied to rebuild the matrices of the coupling system, which can be easily solved to calculate the nonlinear mode characteristics by standard iterative solvers. Lastly, the derived method is applied to a cycle symmetry system, which represents a shaft-disk-blade system subjected to dry friction. Moreover, this study analyzed the effects of the tuned and mistuned contact features on the nonlinear mode characteristics. Numerical results prove that the proposed method is particularly suitable for the study of nonlinear characteristics in such nonlinear systems.

To date, the human balance assessment is mainly achieved by measuring the center of pressure (COP) trajectory of upright posture. However, COP-based metrics provide inconclusive results under certain circumstances, due to the lack of relevance with the body balance mechanism. This paper developed a novel framework to measure the variability in body sway based on the Poincare analysis to enhance the balance assessment. It provided nonlinear parameters SD1, SD2, and their ratio SD1/SD2 as quantitative indicators of the local and global balance regulation capacities. 136 healthy adults were categorized into young and elderly groups and received test on a force platform. COP signals were recorded for 30 s under eyes-opened and eyes-closed vision conditions. The results were analyzed using the two-way mixed-design analysis of variance and show that the technology is able to reveal the effect of age and vision on the balance control by SD1, SD2, and SD1/SD2. SD1 mainly responded to vision, and SD2 was more influenced by age. Due to the information about the subtle adjustment during quiet standing, these Poincare indexes surpassed the conventional COP measurements in demonstrating the balance control behavior. It can be concluded that the supposed method of estimating the local and global variabilities is a valuable approach for the balance assessment.

Background Autonomic dysfunction may occur during the acute phase of COVID‐19. Heart rate variability (HRV) is a useful tool for the assessment of cardiac sympathetic and parasympathetic balance. We aimed to evaluate cardiac autonomic function by using HRV in subjects after recovery from COVID‐19 who had previously symptomatic and were followed outpatiently. Methods The study group composed of 50 subjects with a confirmed history of COVID‐19 and the control group composed of 50 healthy subjects without a history of COVID‐19 and vaccination. All the study participants underwent 2‐dimensional, pulsed‐ and tissue‐Doppler echocardiographic examinations and 24‐hour Holter monitoring for HRV analysis. Results Time domain parameters of SDNN, SDANN, SDNNi, RMSSD, pNN50, and HRV triangular index were all decreased in the study group when compared with the control group. Frequency domain parameters of TP, VLF, LF, HF, and HFnu were also decreased in the study group in comparison with the control group. LFnu was similar between groups. Nonlinear parameters of HRV including α1 and α2 decreased in the study group. By contrast, Lmax, Lmean, DET, REC, and Shannon entropy increased in the study population. Approximate and sample entropies also enhanced in the study group. Conclusions The present study showed that all three domain HRV significantly altered in patients after recovery from COVID‐19 indicating some degree of dysfunction in cardiac autonomic nervous system. HRV may be a useful tool for the detection of preclinical autonomic dysfunction in this group of patients.

This paper presents and applies a mixed iteration method to determine the nonlinear parameters of the material used to study a composite’s creep behavior. To describe the research framework, we made a synthetic presentation of the viscoelastic behavior of composite materials by applying classical models. Further, the presented method was based on a calculation algorithm and program, which was applied on several types of materials. In a consecutive procedure of experiments and calculations, we determined the material parameters of the studied materials. The method was further applied to two composite materials in which the nonlinearity factors at different temperatures were determined.

In this study, The Spotted hyena optimizer Algorithm (SHO) is used to optimize the parameters of the Non-linear type 6 Muskingum model for flood routing. To evaluate the performance of the SHO in the Non-linear Muskingum models, The Wilson River and the Wye River are applied by many researchers for validation. Moreover, in these studies, the Non-linear Muskingum parameters were estimated by the SHO Algorithm. The SSQ and DPO were considered as objective functions between computed and observed data. According to the results of Wilson river flood, the values of these objective functions for the NL3 model are 128.781, and 0.92 m3/s, and for the NL6 model, are 3.20 and 0.027, respectively. The results of the Wye River flood with the SHO showed that the SSQ and DPO for the NL3 model are 34789.39 and 90.05, and for the NL6 model are 30812.07 and 72.35, respectively. The results show that the proposed algorithm can be applied confidently to estimate the parameter optimal values of the nonlinear Muskingum model. Moreover, this algorithm may be applicable to any continuous engineering optimization problems.

Financial development significantly impacts energy consumption. This paper uses cross-country panel data from 21 transitional countries for the period 2006–2015 while considering different financial development indicators and nonlinear relationships between financial development and energy consumption. This is done by selecting five financial development indicators to measure financial development and testing linear and nonlinear relationships between financial development and energy consumption. It found the following: First, there are no significant linear relationships between financial development and energy consumption. Financial development does have significant nonlinear impacts on energy consumption in transitional countries with estimated nonlinear parameters that are significant. Second, financial development affects energy consumption in transitional countries in differing ways. Financial intermediation development positively affected energy consumption in all the countries studied. Stock markets development led decreased energy consumption in China and Poland. Financial openness development reduced energy use except in Georgia and the Kygyz Republic.

This paper reports a novel use of combining nonlinear ultrasonic technique with traditional linear ultrasonic technique to assess the tensile failure in civil mild steel. Two parts are consisted in this research. Firstly, we investigated the tensile damage of the mild steel within its tensile strength, the SEM images reveal that the void initiation and growth are the main damage characteristic here. The nonlinear parameters show a general upward trend at this stage, while the longitudinal wave velocities and attenuation coefficient did not show an obvious regularity. This means that, compared with the traditional linear ultrasonic methods, the nonlinear ultrasonic technique is sensitive to the earlier damage in mild steel. Secondly, we used both ultrasonic techniques to investigate the damage evolution in mild steel when tensile stress exceeds its tensile strength till the specimen fracture. In this process, the main damage characteristic of the specimen are the voids coalescence and micro-cracks propagation. The nonlinear parameters show a decreasing tendency instead of continuing rise, while the attenuation coefficients increase significantly. This result indicates that the nonlinear ultrasonic technique is not appropriate to estimate the severe damage in mild steel such as crack formation and expansion, while we could integrate the traditional linear ultrasonic technique to detected the damage evolution at the late stage.

Different ways of coding radiated signals that probe a tomographized object such as a liquid medium are compared in order to reconstruct the spatial distribution of acoustic nonlinear parameters using a small number of transducers. The results from reconstructing model nonlinear scatterers are discussed. The region of spatial frequencies available for reconstruction is analyzed.

We consider fast sausage solitons and super nonlinearity in straight homogeneous magnetic tubes having coronal parameters. The solitonic behavior is described by the Nonlinear Schrodinger Equation-(NLSE) obtained from the ideal magneto hydrodynamic equations with suitable coronal conditions. For the first time we demonstrated that fast sausage waves are subjected to super nonlinearity and likewise introduced the super nonlinear function that defines this phenomenon. We have obtained classical localized sausage soliton and Peregrine sausage breather soliton solutions for coronal conditions. And finally we have carried out extensive numerical simulations of the evolution of a wave packet governed by the NLS equation with real nonlinear parameters and demonstrated the existence and domain of the above mentioned solitonic modes.

Balanced armature receiver is widely used in hearing aid and earphone because of the small size and high sensitivity. Balanced armature receiver is a product which covers multi-physics. It contains the electromagnetic, mechanical domain and the property such as current and displacement can affect each other. In one hand, the current in electromagnetic domain will take effect on the force which determines the displacement in mechanical domain. In the other hand, displacement change can contribute to the change of back electromotive force (EMF) which affects the current. So the current and displacement are coupled and need to be considered at the same time to analyze the balanced armature receiver. In terms of equation, current and displacement are coupled in the voltage equation which involves the nonlinear parameters such as inductance, speedance, and force factor. Based on lumped parameter method, the nonlinear parameters were calculated as functions of displacement in balanced armature speaker [1]. By using finite element method, Lee et al. analyzed the nonlinear parameters as the function of displacement in microspeaker [2]. In this study, the displacement and current are both considered in the nonlinear parameters to analyze the performance of balanced armature receiver by using FEM.

International audience; This paper shows the complementarity of two nonlinear ultrasonic imaging methods to characterize closed macro cracks in concrete. A time reversal mirror is used to locally probe and image the nonlinearity of a cracked region. Two nonlinear parameters are extracted to map the cracked region. The image obtained using the first parameter relates the harmonic generation due to the contact and frictional behaviors at the crack lips, correlated with vibro-thermography imaging of the same crack. The image obtained using the second parameter is based on the conditioning of the material induced by distributed micro cracks arising from the fracture process zone. These results show a great potential for characterization of fracture processes in concrete, with the possibility to uncouple the effects of the crack itself from surrounding distributed micro damage.

Blood pressure (BP) varies on the long, short and very-short term. Owing to the hidden physiological and pathological information present in BP time-series, increasing interest has been given to the study of continuous, beat-to-beat BP variability (BPV) using invasive and noninvasive methods. Different linear and nonlinear parameters of variability are employed in the characterization of BP signals in health and disease. Although linear parameters of beat-to-beat BPV are mainly measures of dispersion, such as standard deviation (SD), nonlinear parameters of BPV quantify the degree of complexity/irregularity- using measures of entropy or self-similarity/correlation. In this review, we summarize the value of linear and nonlinear parameters in reflecting different information about the pathophysiology of changes in beat-to-beat BPV independent of or superior to mean BP. We then provide a comparison of the relative power of linear and nonlinear parameters of beat-to-beat BPV in detecting early and subtle differences in various states. The practical advantage and utility of beat-to-beat BPV monitoring support its incorporation into routine clinical practices.

The present study focuses on the development of amplitude and physics-based nonlinear parameters for estimating the material nonlinearity and eventually the remnant useful life of fatigued plate structures using Lamb and Rayleigh waves. In the numerical simulations, these waves are propagated through Aluminum (Al) plate structures, and as a result of material nonlinearity, a second harmonic is generated in the response. The spectral amplitudes of the second harmonic are then subsequently used in the amplitude-based nonlinearity parameters to evaluate the nonlinearity for different distances and for different stages of fatigue. The physics-based nonlinear parameter is dependent on the sub-structural evolution parameters and higher order elastic and plastic constants. As it is independent of distance and depends only on the percent of fatigue life, it can be used to construct a theoretical nonlinearity curve (TNC). The estimation of material nonlinearity for different fatigue life through the simulation and amplitude-based parameter is found to be in close agreement with the TNC under the predefined conditions of distance and cycles in the excitation signal. Thus, the knowledge of material nonlinearity parameters evaluated for the pristine and fatigued thick plate specimens using Lamb and Rayleigh waves is shown in the present study to be useful for evaluating the remaining useful life of the fatigued specimens with fair accuracy.

In recent years, artificial intelligent has been widely used as expert systems. In this paper, an intelligent system is provided for determining the risk of cardiovascular diseases. At first, a neuro-fuzzy network is used for risk prediction which the input of this network includes patient's data such as blood pressure, blood sugar, heart rate, number of cigarettes per day, and age, and the output of this network indicates the risk of cardiovascular disease for patients over the next 10 years. In this article, by using genetic algorithm (GA), the features for determining the patient's condition were reduced from 16 to 6 and least-squares algorithm is used to determine the linear network's parameters and, the improved grasshopper optimization algorithm is used to optimize the nonlinear parameters of fuzzy sets. Finally, the proposed network and algorithm are validated by using patient's data which was obtained from patients in Framingham. The results show that the network and algorithm are acceptable.

Grasshopper optimization algorithm (GOA) is a new swarm intelligence algorithm that simulated a model of locust swarm behavior for optimization problems. Still, it has drawbacks, e.g., falling into a local optimum and slow convergence. This paper suggests a method enhancing GOA optimization (namely EGOA) based on an adaptive weight coefficient and nonlinear parameters to balance the global exploration and local development capabilities, to promote the convergence speed, and to avoid trapping of falling into a local optimum the algorithm. In the simulation experiment, four benchmark test functions and the feature selection problem are used to prove that the improved strategy used in the proposed method can effectively enhance the precision and convergence speed of the GOA. The experimental results on seven UCI datasets show that the proposed method can effectively provide the best selection features for increasing classification accuracy.

In this chapter, the basic principles of the computerized cardiotocography are illustrated. After a short historical reconstruction of this fetal monitoring technique, the hardware and software solutions adopted for measuring the fetal heart rate and the toco signals in current commercial cardiotocographs are briefly summarized. A major focus is dedicated to the methodologies for FHR analysis, starting from the extraction of classical morphological and time domain parameters, going through frequency analysis and concluding with advanced nonlinear indices, more recently proposed and adopted by researchers in the field. The chapter has been written taking into account our experience acquired in about 20 years of research in fetal monitoring.

Second harmonic generation (H2) is not desirable for BAW filter applications. Recent BAW filter requires reduction of H2 to achieve high receiver sensitivity. In order to reduce H2, nonlinear parameters of AlN and ScAlN are important because it is widely used in BAW filters. Irieda et al. indicated that second order nonlinear piezoelectric coefficients $\chi_{11}{}^{\mathrm{T}}$ and dielectric $\chi_{02}{}^{\mathrm{E}}$ are dominant for H2 [1], [2]. They showed these nonlinear coefficients $\chi_{11}{}^{\mathrm{T}}$ and $\chi_{02}{}^{\mathrm{E}}$ can be approximately estimated from the change of parallel resonant frequency $f_{\mathrm{p}}$ and inverse dielectric constant $\beta^{\mathrm{S}}$ during a DC bias voltage application. In this study, AlN and ScAlN films were grown on Al bottom electrode/Ta2O5/SiO2 Bragg reflector (SMR) by RF magnetron sputtering. $f_{\mathrm{p}}$ and $\beta^{\mathrm{S}}$ of AlN/SMR and ScAlN/SMR as a function of the DC bias voltage were measured. Nonlinear parameter $\chi_{11}{}^{\mathrm{T}}$ and $\chi_{02}{}^{\mathrm{E}}$ of films were estimated. $\chi_{11}{}^{\mathrm{T}}$ was decreased with increasing of Sc concentration.

Background The analysis of the circadian rhythm of heart rate variability (HRV) represents a relevant physiological tool to assess the vagal system. However, the influence of age (mostly >75 years) on HRV is not widely known. Aims The aim of this study was to evaluate the influence of age on HRV, particularly in the elderly and to identify a model of this relationship. The study was carried out by examining linear and nonlinear parameters extracted from HRV, including individuals over 75 years for which there is no research available. Methods Data from 140 healthy subjects were sex matched and divided into young (young group: 15-39 years old), adult (adult group: 40-64 years old) and senior (senior group: 65-90 years old) groups. 24-h Holter monitoring was used and several HRV parameters were extracted from time, and spectral and nonlinear analyses were examined. Results Time-domain parameters, mainly standard deviation of the NN interval (SDNN) and number of successive differences of intervals which differ by more than 50 ms, presented significant differences between the young group and the other two groups during the 24-h period, while normalized spectral parameters (LFn, HFn and low frequency/high frequency), as well as nonlinear parameters, mainly β exponent and fractal dimension, showed significant difference between the senior group and the other two groups. All these parameters showed a similar circadian rhythm with significant differences between the mean day and night values, especially in young and adult group cohorts. Moreover, a parabolic relationship between these parameters and age was highlighted with an opposite trend over about 60 years compared with younger people. Conclusion A progressive physiological autonomic imbalance is present in ageing. The inverse trend in the relation between HRV parameters and age found in the senior group could be mainly due to a faster fluctuation of RR. This should be considered when studying changes in the cardiac autonomic nervous control.

In order to meet the refinery’s requirements on the properties of raw materials, improve the hydraulic stability of pipeline transporting process, and reduce the energy consumption, it’s necessary to mix up different crude oils transported in pipeline. The traditional method to obtain the physical properties of mixed crude oil, especially the nonlinear parameters such as viscosity and pour point, is experiment test or empirical formula, but the disadvantage is the heavy workload or limited use conditions. In this paper, a nonlinear parameters prediction model based on LS-SVM is put forward for transporting mixed crude oil in pipeline. The modeling method of the nonlinear parameters prediction based on LS-SVM : 1 normalize the different batch sample data; 2 the kernel function of SVM is Gaussian RBF; 3 regress coefficients by genetic algorithm; 4 train parameters and then obtain the nonlinear parameters prediction model. The nonlinear parameters prediction model based on LS-SVM has superiority in aspects of reliability, modeling efficiency, universality and adaptability. It can adapt to the dynamic requirements of refinery on crude oil properties, make full use of the accumulated mixed crude oils’ physical properties and their mixing ratio. The prediction accuracy of non-linear parameters model can be improved continuously. And then, the rationality and efficiency of online mixed transportation in pipeline can be improved effectively.

Nonlinearity is always a hot research topic which leads to difficulties in analysis and design of practical systems. Parameters analysis is a matter of great importance for in-depth insights into the characteristics of nonlinear systems. A novel linear and nonlinear characteristic parameters approach is proposed for analysis and design of nonlinear systems. By using nonlinear characteristic output spectrum function based method, the linear and nonlinear parameters’ influence on system output response is simultaneously considered. The novel nonlinear characteristic spectrum functions’ coefficients are dependent on both linear and nonlinear parameters of interest. The relationship between the system output spectrum and linear and nonlinear parameters can be explicitly revealed. This approach extends the nonlinear characteristic spectrum function based method from the analysis and design of linear and nonlinear parameters in a separated manner to that of hybrid linear and nonlinear parameters. The results of a specific case study demonstrate that the proposed hybrid approach can provide a more comprehensive solution for nonlinear system analysis and design.

Compressional optical coherence elastography (OCE) is the emerging tool to evaluate Young modulus of the tissue with resolution close to optical coherence tomography. Recent versions of compressional OCE based on the strain comparison within the tissue and the calibrated reference silicone layer (sensor) located between the OCT probe and tissue. For standard realizations of compressional OCE the evaluation of the strain within the tissue and the sensor performed only at one point of the stress-strain curve. In the same way the applied stress can be easily estimated in a wide range on the base on the stress-strain relation for calibrated sensor strain that allow to evaluate the stress-strain relation for the underlying tissue not in one point but in the wider range. In this report we demonstrate this approach to nonlinear parameter evaluation for wide range of the tissues. We demonstrate the application of this new tool to breast tissue, vaginal wall, bladder, brain, cartilages, coronary arteries walls in various states. The preliminary results shows that several states of the tissues such as vaginal wall state in case of pelvic organ prolapse, benign breast tumor and coronary arteries plague can be determined on the base of elastic nonlinear parameters.

In this paper, a Sugeno type fuzzy system based on the fuzzy clustering has been developed for a variety of datasets. The number of rules for each dataset is based on the optimum number of clusters in that dataset. Rule sets provide the knowledge base for the classification of data. Each rule set is fine-tuned using the GWO with the intention to improve the classification. The approach is compared with the work of previous researchers on similar data sets using a variety of techniques, including nature-inspired algorithms such as genetic algorithms and Swarm based algorithms. Statistical Analysis of the performance of GWO shows that it is better than five other algorithms 95% of the time.

This paper analyzes the characteristics of interior permanent-magnet synchronous machines using the voltage-frequency control by deriving a generic small-signal model and considering the electric dynamics and nonlinear parameters. Furthermore, a novel closed-loop voltage-frequency control algorithm is developed and demonstrated. By applying this algorithm, it is intended to switch the 3-phase interior permanent-magnet synchronous machines from the field oriented control mode to the voltage-frequency control mode stably on purpose of sensor error diagnosis and compensation in real time.

The presented paper demonstrates the generation of supercontinuum spanning from 2000 nm to over 6000 nm by pumping pulse of peak power 1 kW in a highly nonlinear As38.8Se61.2 chalcogenide holey fiber. The conventional cladding region of a microstructured fiber consists of conventional circular-shaped air holes. In the proposed design of holey fiber, the shape of air holes was modified as elliptical air holes. The geometrical parameters of the modeled design of the fiber are selected to acquire a flat and broad dispersion profile in the anomalous region. The modeled fiber was numerically simulated to investigate the parameters—nonlinear coefficient and effective mode area portraying vital role to achieve the generation of supercontinuum. The observations of the investigations demonstrate that the modeled holey fiber is a suitable design for generating supercontinuum. Additionally, simulations performed to investigate generation of supercontinuum resulted in spectra spreading in mid-infrared region. The applications of the supercontinuum generated are also discussed.

A data-driven parameter estimation strategy is assessed and tested for the estimation of nonlinear parameters in a classic continuous stir tank reactor (CSTR). A decoupled version of the retrospective cost model refinement (RCMR) algorithm serves as the estimation structure. The proposed method studies the simultaneous estimation of three kinetic parameters within a CSTR considering one available measurement. The decoupled RCMR algorithm is adapted and implemented as an efficient estimation structure for the proposed problem, and contrasted with its original structure.

Monitoring uterine contractions is essential during pregnancy and labor to obtain information on time-to-delivery and maternal and fetal wellbeing Intrauterine pressure (IUP) is considered the "gold standard" to monitor uterine activity, though it requires membrane rupture and is highly invasive. Considering that uterine mechanical activity is a direct consequence of uterine myoelectrical activity, IUP signal can be non-invasively estimated from abdominal electrohysterogram (EHG) recordings. Previous works have reported EHG-based IUP estimates with linear parameters as root-mean-square or Teager energy. Due to non-linear nature of biological processes, the aim of this study was to test the performance of different non-linear EHG parameters to estimate IUP signal. Simultaneous EHG and IUP recordings were conducted in 17 women during labour. Teager energy (TE), Sample entropy (SampEn), Spectral entropy (SpEn), Lempel-Ziv (LZ), and Poincare parameters: SD1, SD2, SDRR and SD1/SD2 were computed from the EHG. Different window lengths for computation and for a smoothing moving average filter were tested. Mono-variable linear regression models were used to obtain IUP estimates. The best results were obtained with TE and SD1, both computed and filtered with windows of 5 s and 20 s, respectively. In the latter case, the RMSerror was 12.25 +/- 4.03 mmHg, which points that non-linear EHG parameters can provide relevant information for non-invasive uterine activity monitoring.

In this paper, two-pump optical parametric amplification (OPA) of S-band signals based on a tellurite microstructured optical fiber (MOF) is proposed and simulated. Since the length required to obtain high parametric gain reduces dramatically since, tellurite-based MOFs possess higher nonlinear parameters than those of standard silica fibers. Simulation results showing a wide and flat band with a very high gain over the S-band region which implies that tellurite-based fiber OPAs are comparable with the conventional thulium-doped fiber amplifiers. This unique feature may be used in diverse fields including satellite communication, microwave, and wireless network devices.

The purpose of this study was to compare the postnatal evolution of spectral–amplitude and nonlinear parameters of surface electromyogram (sEMG) in the full-term and preterm infants with regard to their biological and calendar age. In full-term infants, all sEMG parameters (dimension, entropy, mean frequency, and amplitude) are increased by 10–30% two weeks after birth. On the contrary, sEMG parameters in preterm infants were constant for six weeks after birth. This finding indicates that both postnatal and antenatal periods are important for the development of the motor system of infants. Therefore, the adaptation of the motor system to extrauterine conditions consists of two stages. The authors suppose that gravity can be a driving factor of these sEMG metamorphoses.

A mathematical apparatus which foresees the use of vector analysis is offered. It provides new possibilities for the analysis of economic processes. The reduction of nonlinear tasks to the simplified linear form can result in the losses of roots, or groups of roots, system errors and solutions subject to errors. The use of linear models for the set up of and for the solutions for economic tasks is possible only in application to the practical needs of the certain, limited number of cases with a minimum set of parameters. Therefore, there was a need to change the methodological approaches to the mathematical optimal modeling in the economy. The avoidance of oversimplification gives the possibility to set up he problem in a objective mathematical way and to find the solution more precisely. The modern computing engineering and application packages allow deciding such problems in a general view – without oversimplification.

This paper introduces a method to identify the parameters in a weak nonlinear vibration system. Based on the existed backbone curve identification method which can identify the parameters in weak nonlinear symmetric systems, method in the present paper extends the application of ‘backbone curve’ method to nonlinear systems with asymmetry. Based on the introducing of offset term caused by the asymmetry, this method can increase the number of identification equations to broaden its application. Meanwhile, the data obtained from the displacement attenuation signal offer valuable information of system nonlinearity in this method. So we can identify all the parameters of system only from its displacement attenuation signal. As an application, we design a vertical cantilever beam with initial deflection and tip mass as an experimental object with asymmetric structure. The displacement data of the top of beam are acquired by a laser vibrometer. The provided method is applied to identify all nonlinear parameters in the model of the nonlinear cantilever beam. Then, the validity and accuracy of method can be evaluated by the comparison between theoretical parameters and identified parameters of beam model.

The Human heart rate though appears regular, it is not. There is a change in the time intervals between two successive heart beats, these variations are referred to as heart rate variability (HRV). The HRV will be in certain regular pattern and differs from individuals. HRV depends on state of pathology and physiology of the individual. Research has been carried out to find whether if they could predict the disease early and could avoid complications which might be fatal. It helps the physician in early diagnosis and alertness of the disease which will denote the step for better care. The vital advantage of HRV is that, it is noninvasive and the individuals can check there HRV parameters without any inconvenience at any time without any after effects. In this work ECG signals are obtained from physionet data base. Data of normal ECG signals and ECG of Supraventricular Tachycardia of 57 subjects each are considered for the study of HRV parameters. Linear parameters of HRV like time-domain, frequency-domain parameters non-linear parameters like Poincare plot is analyzed. The new software is developed on MATLAB tool for carrying HRV analysis, code has been developed to obtain linear and nonlinear parameters of HRV with the filtering option embedded in the software. Using the developed software statistical analyses was carried on to obtain the optimum parameter that can distinguish normal and diseased conditions which can be further considered for embedding in wearable device hardware. Though HRV has huge potential in diagnosing and predicting diseases, it is yet to be used as a diagnostic tool. Identification of Linear and non-linear parameters which are significant in diagnoses of diseases will be useful in predicting ANS modifying diseases early.

Polarizabilities and hyperpolarizabilities, α1, β1, γ1, α2, β2, γ2, α3, β3, γ3, δ and ε of hydrogenic systems have been calculated in the presence of a Debye–Huckel potential, using pseudostates for the S, P, D and F states. All of these converge very quickly as the number of terms in the pseudostates is increased and are essentially independent of the nonlinear parameters. All the results are in good agreement with the results obtained for hydrogenic systems obtained by Drachman. The effective potential seen by the outer electron is −α1/x4 + (6β1 − α2)/x6 + higher-order terms, where x is the distance from the outer electron to the nucleus. The exchange and electron–electron correlations are unimportant because the outer electron is far away from the nucleus. This implies that the conventional variational calculations are not necessary. The results agree well with the results of Drachman for the screening parameter equal to zero in the Debye–Huckel potential. We can calculate the energies of Rydberg states by using the polarizabilities and hyperpolarizabilities in the presence of Debye potential seen by the outer electron when the atoms are embedded in a plasma. Most calculations are carried out in the absence of the Debye–Huckel potential. However, it is not possible to carry out experiments when there is a complete absence of plasma at a particular electron temperature and density. The present calculations of polarizabilities and hyperpolarizabilities will provide accurate results for Rydberg states when the measurements for such states are carried out.

Additive manufacturing (AM) is becoming increasingly popular due to its ability to build parts with customer-designed complex geometries. However, the lack of established quality control/assurance practices for the built parts poses a challenge to a wider adoption of additive manufacturing by some industries. In this study, we investigate the utility of nonlinear resonance ultrasonic spectroscopy (NRUS) for predicting the fatigue life of cylindrical Ti–6Al–4V samples manufactured using powder bed fusion on the same build. We use NRUS to measure several linear and nonlinear parameters for the samples before and after hot isostatic pressing (HIPing). The samples are then fatigue tested. We report the correlation between NRUS parameters and fatigue life. Our findings suggest that resonance frequency, quality factor, and the hysteretic nonlinearity of the samples are correlated to their fatigue life. These correlations are promising because the measurements are obtained from distinct samples as opposed to collecting data on the same sample undergoing increasing fatigue cycles. This study suggests that NRUS has the potential to be used as a nondestructive evaluation (NDE) tool for AM part quality control.

Objective: The present study aimed to analyze the influence of smoking on heart autonomic control in elderly adults who did and did not smoke. Methods: In a population-based study, all community-dwelling elderly adults (≥60 years old) from Aiquara, Bahia, Brazil, were invited to participate in the study. Two-hundred-thirty-two (232) elderly adults provided information about their smoking habits and underwent 5-min recordings of successive RR intervals. Analysis of the variability of the RR intervals was performed in time and frequency domains and with nonlinear methods. The HAC parameters were adjusted for the following potential confounders: age, sex, diabetes, beta-blocker use, cardiovascular disease, body mass index and physical activity level. After exclusions, 210 elderly adults were divided into 2 groups, nonsmokers or those who stopped smoking (NSMOK [n=190]) and current smokers (SMOK [n=20]). Owing to the absence of a normal distribution, the Mann-Whitney test was used for group comparisons. Results: For unadjusted HAC parameters, a significant difference was observed (p

The aim of the present work is to study the vibration behavior of sandwich composites with shear damages on the foams. The effect of the densities of damage on the linear and nonlinear vibration parameters is studied. The sandwich materials used in this study is constructed with glass fiber laminates as skins and with PVC closed-cell foams with density 60 and 100 kg m−3 as core. After a serie of vibration tests, the change of natural frequencies and modal damping due to the damage and the foam densities. For an intact specimen, the resonance frequency was constant when we increase the excitation amplitude. For damaged specimens, the resonance frequencies decrease and the loss factors increase proportionally with the increasing excitation amplitude. The nonlinear parameters corresponding to the elastic modulus and damping were determined for each frequency modes and each damage and foam densities. The results showed that nonlinear dissipative parameters were more sensitive to damage than linear elastic and dissipative parameters.

The multi-frequency excitation of a microbeam, resting on a nonlinear foundation, is investigated and the governing equation of motion of the microbeam system is developed. The viscoelastic-type foundation is considered by assuming nonlinear parameters for both Pasternak and Winkler coefficients. The well-known Galerkin approach is utilized to discretize the governing equation of motion and to obtain its nonlinear ordinary differential equations. The multiple time-scales method is employed to study the multi-frequency excitation of the microbeam. Furthermore, the resonant conditions due to the external excitation as well as the combination resonances for the first two modes are investigated. The influences of different parameters, namely the Pasternak and Winkler coefficients, the position of the applied force and the geometrical factors on the frequency response of the system are examined.

The dynamical properties of a laminated glass are investigated by applying the Fitting Time History (FTH) method to experimental free vibration response. Both linear and the nonlinear parameters are detected, and attention is focused on these latters since they are the most important element of novelty of this work. Some one-mode identifications are considered first, and then the approximation is improved by considering multi-mode identifications, that allow us to detect simultaneously the linear and nonlinear properties of various vibration modes, a fact that is an appealing feature of the FTH method.

Paper presents experimental and numerical research on tank local overheating. By using an experimental model, phenomena of tank local overheating are investigated without need of expensive experiments on real transformer unit. This first step of research is made with reliable measurements of losses and temperatures in tank on a simple experimental setup. Using commercial numerical tools based on finite element method (FEM) for coupled electromagnetic-thermal calculation, temperatures on experimental model are calculated. Both electromagnetic and thermal model have nonlinear parameters that can have high influence on value of stray losses and cooling conditions. Calculated temperatures are compared to measurement results. In the last part of the paper, measurements of tank temperatures with infrared camera on real three-phase power transformer are presented. 3D nonlinear numerical model of power transformer is created in FEM. Numerical model includes core, windings, LV leads and metal parts. Obtained temperatures are compared to calculation results by FEM and give good agreement.