## What is/are Random Response?

Random Response - A non-random response alters the composition of the sample of native workers, mechanically changing the average native wage in affected markets and biasing the estimated wage impact of immigration.^{[1]}The algorithm mainly uses the consistent adaptive local margin strategy to index, finds frequent sequences, perturbs transaction data through random response mechanism, and finds all the sensitivities that satisfy local differential privacy.

^{[2]}In this paper, we investigate the asymptotic properties of a nonparametric conditional quantile estimation in the single functional index model for dependent functional data and censored at random responses are observed.

^{[3]}Moreover, the roles of bridge random parameters, track irregularities, and the seismic actions on the random responses are comprehensively investigated.

^{[4]}In this thesis a new robust framework to be used in structural identification is proposed in order to have a reliable numerical model that can be used both for random response estimation and for structural health monitoring.

^{[5]}The random response analysis gives a more appropriate estimation of functioning of the control device and structure.

^{[6]}Yet, the research design commonly suffers from the problem of measurement error in the form of non-strategic respondent error, where some inattentive participants might provide random responses.

^{[7]}Calculating the first and second derivatives of Power Spectrum Density (PSD) function with respect to various design variables is a prerequisite for random responses when gradient-based algorithms are adopted.

^{[8]}The PC method with the Non-Intrusive formulation allows the use of existing deterministic solvers for the accurate prediction of the sought random response, i.

^{[9]}Based on the large-scale grid connection of wind power, this paper explores the correlation between the electromechanical oscillation and the random response of the power system by introducing stochastic differential and algebraic equations, and it concludes that the dynamic information of the power system really exists in the random response.

^{[10]}The accuracy of the proposed model is validated by comparing the obtained free vibration and random response results with those from the published literature.

^{[11]}There are two main problems with this kind of method: one is that the utility function used in the random response loses too much information; the other is that the privacy protection of the set-valued data category is usually ignored.

^{[12]}This study investigated the situation-dependent heterogeneity of car-following behavior, based on field vehicle trajectories in Beijing, and proposed a multidimensional stochastic Newell car-following model (MSNCM) incorporating three stochastic parameters: random response time, speed-dependent critical jam spacing, and speed difference- and spacing-dependent acceleration.

^{[13]}The study shows that the plates have dynamic hardening behaviors, and the existence of thermal loads makes the plate random responses more diverse in stochastic environments.

^{[14]}The Karhunen–Loéve expansion is utilized to discretize the stochastic field, while the point estimate method is applied for calculating the random response of the structure.

^{[15]}Based on the theory of random response analysis, a road noise prediction method is proposed.

^{[16]}The weak points of the structure were identified by taking random response analysis, and the corresponding PSD (power spectral density) spectrums of stress were obtained.

^{[17]}The strength and durability of the buoy are assessed primarily through a random response analysis of its stress-strain state under irregular wind-wave conditions with requirements of actual standards and codes also taken into consideration.

^{[18]}Using a student sample, we assess the measures’ test-retest reliability (N = 88; using a longer time interval than previous studies) and sensitivity to random responses.

^{[19]}Traditional operational modal analysis is based on the random response of white noise.

^{[20]}The application and efficacy of the data-driven method are illustrated by the random response control problems of the Duffing oscillator, van der Pol system, and a two degrees-of-freedom nonlinear system.

^{[21]}Distinction between deterministic and random response components is only possible using a theoretical solution.

^{[22]}A new topology optimization scheme based on the pseudo excitation method (PEM) for calculating structural random responses in a frequency domain is proposed.

^{[23]}Through random vibration theory, the random response for the wire feeder and the method of solving the response extreme value in the reference period are studied.

^{[24]}To analyse this situation, the method of reverberation ray matrix (MRRM) is extended by random vibration theory to the steady-state random response analysis of a three-dimensional multi-span hydraulic pipeline under multi-point base excitations.

^{[25]}The probability and statistics of the random response of wake-oscillator in resonant (lock-in) case and in non-resonant case are analytically obtained, and the analytical results are confirmed using numerical simulation of the original system.

^{[26]}The Poisson distribution describes a random response time and the e-mail forwarding distribution describes a process of receiving and forwarding messages.

^{[27]}The random response of the nonlinear system is analyzed by introducing a generalized harmonic transformation and establishing the relationships between the responses of the nonlinear main system and the IDVA secondary system.

^{[28]}The protocol uses PUF technology to output unique and random responses to different excitation inputs, encrypts the authentication information sent by the tag, and uses the AES encryption algorithm to encrypt the authentication information between the cloud database and the reader.

^{[29]}then, the stress power spectrum density of dangerous parts is obtained by random response analysis; Then, the vibration mode of the welded structure is obtained by random response analysis, and the acceleration power spectral density of the structure is input, and then the stress power spectrum density of the dangerous part is obtained Finally, the appropriate stress probability density distribution model is selected to predict the fatigue life with S-N curve equation and Miner damage accumulation theory.

^{[30]}The random response of hail impact was well captured by simulation results, and the convergence and reliability of the proposed modeling approach was validated by a comparison between simulation results and the experimental data in the literature.

^{[31]}In this paper, an efficient frequency domain scheme based on fast CQC method, which can predict non-stationary buffeting random responses of long-span bridges, is presented, and then this approach is applied to evaluate the buffeting response of a long-span suspension bridge located in a complex mountainous wind environment as an example.

^{[32]}Biomechanical responses of the models to bending moments and vertical vibrational excitation were computed using FE static and random response analyses, respectively.

^{[33]}Moreover, the linear feedback shift register is used in the adaptive physically unclonable function (APUF) for generating the random response value.

^{[34]}This type of tunable stochastic network produces a controllable random response exploiting intrinsic stochasticity within magnetic domain-wall motion at the nanoscale.

^{[35]}We analyse the maximum value of the Lyapunov exponent and see that the random response competes with the chaotic motion to increase the stability of the system.

^{[36]}The change of the equivalent radius of the isolation bearing has no obvious influence on the random response of the pier and the track structure, but will to some extent bring the change of the bearing response.

^{[37]}The random response and mean crossing rate of the fractional order nonlinear system with impact are investigated through the equivalent nonlinearization technique.

^{[38]}Finally, the nature of random response is analyzed using Lyapunov exponents to determine whether the vessel exhibits any chaotic dynamics.

^{[39]}System WFE is impossible to predict from finite element random response results due to the loss of phase information.

^{[40]}Four systems of conceptualization emerged: Random responses (category-R), reflecting no reference to the music; Associative contents (category-A), suggesting extra-musical interpretations; Compound responses (category-C), combining extra- and intra-musical contents; Intra-musical contents (category-I), referring to purely musical properties.

^{[41]}The non-stationary random response analysis of coupled acoustic-structural systems under non-stationary random excitations is investigated in this paper.

^{[42]}A hybrid model consisting of Arbiter PUF and Butterfly PUF are used to generate random responses which are fed to a Finite State Machine (FSM).

^{[43]}These results showed that the studentâ€™s responses to the electromagnetism concepts were nearly all in the null-model and random response states.

^{[44]}Using the theory of speckles, we analyzed the probability density function (PDF) of this random response and its variance.

^{[45]}Using SIEMENS NX software as the application platform, the finite element simulation module was used to perform thermal analysis, structural static analysis and random response analysis on the reliability simulation model.

^{[46]}Equivalent linearization method is the main approach for nonlinear structural system random response analysis.

^{[47]}The study employed an internally controlled method of simulating inconsistent responding by inserting ascending levels of computer-generated random responses into PPI-R protocols.

^{[48]}In the random response analysis, the Large Mass Method (LMM) which attributes artificial large mass values at each driven nodal Degree Of Freedom (DOF) to transforming the base acceleration excitations into force excitations is proposed.

^{[49]}We propose a hash function and random response based framework for the estimation.

^{[50]}

## Structural Random Response

A new topology optimization scheme based on the pseudo excitation method (PEM) for calculating structural random responses in a frequency domain is proposed.^{[1]}The time-dependent reliability is regarded as the probability that the structural random response process does not exceed the specified failure threshold within the forecast time period.

^{[2]}

## random response analysi

The random response analysis gives a more appropriate estimation of functioning of the control device and structure.^{[1]}Based on the theory of random response analysis, a road noise prediction method is proposed.

^{[2]}The weak points of the structure were identified by taking random response analysis, and the corresponding PSD (power spectral density) spectrums of stress were obtained.

^{[3]}The strength and durability of the buoy are assessed primarily through a random response analysis of its stress-strain state under irregular wind-wave conditions with requirements of actual standards and codes also taken into consideration.

^{[4]}To analyse this situation, the method of reverberation ray matrix (MRRM) is extended by random vibration theory to the steady-state random response analysis of a three-dimensional multi-span hydraulic pipeline under multi-point base excitations.

^{[5]}then, the stress power spectrum density of dangerous parts is obtained by random response analysis; Then, the vibration mode of the welded structure is obtained by random response analysis, and the acceleration power spectral density of the structure is input, and then the stress power spectrum density of the dangerous part is obtained Finally, the appropriate stress probability density distribution model is selected to predict the fatigue life with S-N curve equation and Miner damage accumulation theory.

^{[6]}The non-stationary random response analysis of coupled acoustic-structural systems under non-stationary random excitations is investigated in this paper.

^{[7]}Using SIEMENS NX software as the application platform, the finite element simulation module was used to perform thermal analysis, structural static analysis and random response analysis on the reliability simulation model.

^{[8]}Equivalent linearization method is the main approach for nonlinear structural system random response analysis.

^{[9]}In the random response analysis, the Large Mass Method (LMM) which attributes artificial large mass values at each driven nodal Degree Of Freedom (DOF) to transforming the base acceleration excitations into force excitations is proposed.

^{[10]}Random response analysis was performed under white noise excitation at 0–20 Hz in the vertical direction by a modal superposition method.

^{[11]}The time domain signals of the connection points are converted into frequency domain signals, and random response analysis is carried out to obtain the acceleration PSD matrices of the body monitoring points and the battery pack fixture points.

^{[12]}This paper proposes the stochastic isogeometric analysis (IGA) method in conjunction with the perturbation technique for random response analysis of plate structures.

^{[13]}

## random response result

The accuracy of the proposed model is validated by comparing the obtained free vibration and random response results with those from the published literature.^{[1]}System WFE is impossible to predict from finite element random response results due to the loss of phase information.

^{[2]}

## random response time

This study investigated the situation-dependent heterogeneity of car-following behavior, based on field vehicle trajectories in Beijing, and proposed a multidimensional stochastic Newell car-following model (MSNCM) incorporating three stochastic parameters: random response time, speed-dependent critical jam spacing, and speed difference- and spacing-dependent acceleration.^{[1]}The Poisson distribution describes a random response time and the e-mail forwarding distribution describes a process of receiving and forwarding messages.

^{[2]}