Journal articles: 'Time-varying effect modeling'

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Shiyko, Mariya P., Jack Burkhalter, Runze Li, and Bernard J. Park. "Modeling nonlinear time-dependent treatment effects: An application of the generalized time-varying effect model (TVEM)." Journal of Consulting and Clinical Psychology 82, no. 5 (October 2014): 760–72. http://dx.doi.org/10.1037/a0035267.

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Ruhe, Constantin. "Estimating Survival Functions after Stcox with Time-varying Coefficients." Stata Journal: Promoting communications on statistics and Stata 16, no. 4 (December 2016): 867–79. http://dx.doi.org/10.1177/1536867x1601600404.

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In many applications of the Cox model, the proportional-hazards assumption is implausible. In these cases, the solution to nonproportional hazards usually consists of modeling the effect of the variable of interest and its interaction effect with some function of time. Although Stata provides a command to implement this interaction in stcox, it does not allow the typical visualizations using stcurve if stcox was estimated with the tvc() option. In this article, I provide a short workaround that estimates the survival function after stcox with time-dependent coefficients. I introduce and describe the scurve_tvc command, which automates this procedure and allows users to easily visualize survival functions for models with time-varying effects.

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Danieli, Coraline, and Michal Abrahamowicz. "Competing risks modeling of cumulative effects of time-varying drug exposures." Statistical Methods in Medical Research 28, no. 1 (September 7, 2017): 248–62. http://dx.doi.org/10.1177/0962280217720947.

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An accurate assessment of drug safety or effectiveness in pharmaco-epidemiology requires defining an etiologically correct time-varying exposure model, which specifies how previous drug use affects the hazard of the event of interest. An additional challenge is to account for the multitude of mutually exclusive events that may be associated with the use of a given drug. To simultaneously address both challenges, we develop, and validate in simulations, a new approach that combines flexible modeling of the cumulative effects of time-varying exposures with competing risks methodology to separate the effects of the same drug exposure on different outcomes. To account for the dosage, duration and timing of past exposures, we rely on a spline-based weighted cumulative exposure modeling. We also propose likelihood ratio tests to test if the cumulative effects of past exposure on the hazards of the competing events are the same or different. Simulation results indicate that the estimated event-specific weight functions are reasonably accurate, and that the proposed tests have acceptable type I error rate and power. In real-life application, the proposed method indicated that recent use of antihypertensive drugs may reduce the risk of stroke but has no effect on the hazard of coronary heart disease events.

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Kumari, S., and A. Singh. "Effect of Correlations on Routing and Modeling of Time-varying Communication Networks." Acta Physica Polonica B 50, no. 2 (2019): 199. http://dx.doi.org/10.5506/aphyspolb.50.199.

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Flannery, Kaitlin M., Anna Vannucci, and Christine McCauley Ohannessian. "Using Time-Varying Effect Modeling to Examine Age-Varying Gender Differences in Coping Throughout Adolescence and Emerging Adulthood." Journal of Adolescent Health 62, no. 3 (March 2018): S27—S34. http://dx.doi.org/10.1016/j.jadohealth.2017.09.027.

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Fletcher, Robin P., and Johan O. Robertsson. "Time-varying boundary conditions in simulation of seismic wave propagation." GEOPHYSICS 76, no. 1 (January 2011): A1—A6. http://dx.doi.org/10.1190/1.3511526.

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We propose two new boundary conditions to regulate coherent reflections from the model boundaries in numerical solutions of wave equations. Both boundary conditions have the common feature that the boundary condition is varied with respect to time. The first boundary condition expands or contracts the computational model during a modeling simulation. The effect is to cause a Doppler shift in the reflected wavefield that can be used to shift energy outside a frequency band of interest. In addition, when the computational domain is expanding, the range of possible incidence angles on the boundary is restricted. This can be used to increase the effectiveness of many existing absorbing boundary conditions that are more effective for incidence angles close to normal. The second boundary condition is an extension of random boundaries. By carefully changing the realization of a random boundary over time, a more diffusive wavefield can be simulated. We show results with 2D numerical simulations of the scalar wave equation for both these boundary conditions. The first boundary condition has application to modeling, but both these boundary conditions have potential application within algorithms that rely upon modeling kernels, such as reverse-time migration and full-waveform inversion.

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Feingold, Alan. "Time-Varying Effect Sizes for Quadratic Growth Models in Multilevel and Latent Growth Modeling." Structural Equation Modeling: A Multidisciplinary Journal 26, no. 3 (December 20, 2018): 418–29. http://dx.doi.org/10.1080/10705511.2018.1547110.

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Wei, Bowen, Minghan Gu, Huokun Li, Wei Xiong, and Zhenkai Xu. "Modeling method for predicting seepage of RCC dams considering time-varying and lag effect." Structural Control and Health Monitoring 25, no. 2 (August 11, 2017): e2081. http://dx.doi.org/10.1002/stc.2081.

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Xiao, Zhengming, Jinxin Cao, and Yinxin Yu. "Mathematical Modeling and Dynamic Analysis of Planetary Gears System with Time-Varying Parameters." Mathematical Problems in Engineering 2020 (March 16, 2020): 1–9. http://dx.doi.org/10.1155/2020/3185624.

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Planetary gears are widely used in automobiles, helicopters, heavy machinery, etc., due to the high speed reductions in compact spaces; however, the gear fault and early damage induced by the vibration of planetary gears remains a key concern. The time-varying parameters have a vital influence on dynamic performance and reliability of the gearbox. An analytical model is proposed to investigate the effect of gear tooth crack on the gear mesh stiffness, and then the dynamical model of the planetary gears with time-varying parameters is established. The natural characteristics of the transmission system are calculated, and the dynamic responses of transmission components, as well as dynamic meshing force of each pair of gear are investigated based on varying internal excitations induced by time-varying parameters and tooth root crack. The effects of gear tooth root crack size on the planetary gear dynamics are simulated, and the mapping rules between damage degree and gear dynamics are revealed. In order to verify the theoretical model and simulation results, the planetary gear test rig was built by assembling faulty and healthy gear separately. The failure mechanism and dynamic characteristics of the planetary gears with tooth root crack are clarified by comparing the analytical results and experimental data.

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Haneuse, S. J. P. A., K. D. Rudser, and D. L. Gillen. "The separation of timescales in Bayesian survival modeling of the time-varying effect of a time-dependent exposure." Biostatistics 9, no. 3 (November 19, 2007): 400–410. http://dx.doi.org/10.1093/biostatistics/kxm038.

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Martínez Ramírez, Marco A., Emmanouil Benetos, and Joshua D. Reiss. "Deep Learning for Black-Box Modeling of Audio Effects." Applied Sciences 10, no. 2 (January 16, 2020): 638. http://dx.doi.org/10.3390/app10020638.

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Virtual analog modeling of audio effects consists of emulating the sound of an audio processor reference device. This digital simulation is normally done by designing mathematical models of these systems. It is often difficult because it seeks to accurately model all components within the effect unit, which usually contains various nonlinearities and time-varying components. Most existing methods for audio effects modeling are either simplified or optimized to a very specific circuit or type of audio effect and cannot be efficiently translated to other types of audio effects. Recently, deep neural networks have been explored as black-box modeling strategies to solve this task, i.e., by using only input–output measurements. We analyse different state-of-the-art deep learning models based on convolutional and recurrent neural networks, feedforward WaveNet architectures and we also introduce a new model based on the combination of the aforementioned models. Through objective perceptual-based metrics and subjective listening tests we explore the performance of these models when modeling various analog audio effects. Thus, we show virtual analog models of nonlinear effects, such as a tube preamplifier; nonlinear effects with memory, such as a transistor-based limiter and nonlinear time-varying effects, such as the rotating horn and rotating woofer of a Leslie speaker cabinet.

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Lanza, Stephanie T., Sara A. Vasilenko, and Michael A. Russell. "Time-varying effect modeling to address new questions in behavioral research: Examples in marijuana use." Psychology of Addictive Behaviors 30, no. 8 (December 2016): 939–54. http://dx.doi.org/10.1037/adb0000208.

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Estes, Jason P., Danh V. Nguyen, Lorien S. Dalrymple, Yi Mu, and Damla Şentürk. "Time-varying effect modeling with longitudinal data truncated by death: conditional models, interpretations, and inference." Statistics in Medicine 35, no. 11 (December 8, 2015): 1834–47. http://dx.doi.org/10.1002/sim.6836.

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Pierre, Rodrigue, C. Perry Brown, Charlotte Baker, Matthew Dutton, Oghenekome Onokpise, and Brian Hickey. "Competing Risk of Death and Time-Varying Covariates in Cardiovascular Epidemiologic Research: Modeling the Hazards of Coronary Heart Disease in the First National Health and Nutrition Examination Survey Epidemiologic Follow-Up Study." Medical Science & Healthcare Practice 3, no. 1 (February 13, 2019): 20. http://dx.doi.org/10.22158/mshp.v3n1p20.

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Competing risk of death and time-varying covariates, often overlooked during statistical analyses of longitudinal studies, can alter the magnitude of estimates of the effect of covariates on the hazards of health outcomes. This study aimed to investigate whether estimates obtained when modeling the effect of risk factors on the hazards of coronary heart disease (CHD) varied significantly while accounting for the presence of competing risk of death and time-varying covariates. We used data from the First National Health and Nutrition Examination Survey Epidemiologic Follow-Up Study (n=6346) to model estimates of the effect of risk factors on the hazards of CHD using Cox proportional hazards model, Cox extension with time-varying covariates, and the Fine Gray approach. We used a chi-square test to compare coefficient estimates obtained from the three modeling techniques. We obtained a P-value > 0.05 when comparing coefficient estimates for body mass index, age, cholesterol, smoking, and diabetes after fitting the three models. Coefficient estimates obtained when modeling the effect of risk factors on the hazards of CHD did not vary significantly in the presence of competing risk of death and time-varying covariates. Researchers should consider exploring these concepts more systematically in cohort studies with cardiovascular outcomes.

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Ji, Yanju, Li Han, Xingguo Huang, Xuejiao Zhao, Kristian Jensen, and Yibing Yu. "A high-order finite-difference scheme for time-domain modeling of time-varying seismoelectric waves." GEOPHYSICS 87, no. 2 (January 31, 2022): T135—T146. http://dx.doi.org/10.1190/geo2021-0235.1.

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Simulation of the seismoelectric effect serves as a useful tool to capture the observed seismoelectric conversion phenomenon in porous media, thus offering promising potential in underground exploration activities to detect pore fluids such as water, oil, and gas. The static electromagnetic (EM) approximation is among the most widely used methods for numerical simulation of the seismoelectric responses. However, the static approximation ignores the accompanying electric field generated by the shear wave, resulting in considerable errors when compared to analytical results, particularly under high-salinity conditions. To mitigate this problem, we have adopted a spatial high-order finite-difference time-domain method based on Maxwell’s full equations of time-varying EM fields to simulate the seismoelectric response in 2D mode. To improve the computational efficiency influenced by the velocity differences between seismic and EM waves, different time steps are set according to the stability conditions, and the seismic feedback values of EM time nodes are obtained by linear approximation within the seismic unit time step. To improve the simulation accuracy of the seismoelectric response with the time-varying EM calculation method, finite-difference coefficients are obtained by solving the spatial high-order difference approximation based on the Taylor expansion. Our method yields consistent simulation results compared to those obtained from the analytical method under different salinity conditions, thus indicating its validity for simulating seismoelectric responses in porous media. We further apply our method to layered and anomalous body models and extend our algorithm to three dimensions. Results indicate that the time-varying EM calculation method can effectively capture the reflection and transmission phenomena of the seismic and EM wavefields at the interfaces of contrasting media. This may allow for the identification of abnormal locations, thus highlighting the capability of seismoelectric response simulation to detect subsurface properties.

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Jacobson, Nicholas C., Sy-Miin Chow, and Michelle G. Newman. "The Differential Time-Varying Effect Model (DTVEM): A tool for diagnosing and modeling time lags in intensive longitudinal data." Behavior Research Methods 51, no. 1 (August 17, 2018): 295–315. http://dx.doi.org/10.3758/s13428-018-1101-0.

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Gu, Cheng Zhong, and Xin Yue Wu. "Study of the Modeling of the Gear Dynamics Considering Mesh Stiffness and Sliding Friction." Applied Mechanics and Materials 29-32 (August 2010): 618–23. http://dx.doi.org/10.4028/www.scientific.net/amm.29-32.618.

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Time- varying mesh stiffness and sliding friction between teeth are the great excitation for vibration and noise in gears system. But, there are rarely studies on this topic. This paper proposes a new dynamic modeling of gear system, which is effect of mesh stiffness variation, sliding friction and distribution of load. Firstly, the expression of time-varying mesh stiffness is gained, which is a period function. Secondly, a new friction modeling has the same period as mesh stiffness, is proposed. Thirdly, friction torque of each gear pair is calculated respectively, which is considering the distribution of load and time-varying friction arm. Finally, because all parameter have the same cycle, it is easy to get the approximate analytical solution to non-line model of gear dynamic by fourier transform.

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Lum, Yew-Choe, and Sardar M. N. Islam. "Time Varying Behavior of Share Returns in Australia: 1988–2004." Review of Pacific Basin Financial Markets and Policies 19, no. 01 (March 2016): 1650004. http://dx.doi.org/10.1142/s0219091516500041.

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The model in this paper is similar to Brailsford and Faff (1997), using a conditional CAPM model with the GARCH-M framework, but with a significant additional dummy term (in the conditional mean of the share return) that will help explain the models better in both economic and statistical sense. The relatively simpler asymmetric model in this paper is compatible to other more complex asymmetric models and hence should be easier to model and explain for practical purposes. The model in this paper is also a more effective model, in both economical and statistical terms, as compared to some other models in the GARCH family as it captures the asymmetric effect in the modeling process in both the conditional first and second moments. The findings in this paper have contributed in re-evaluating the nature and process of time varying behavior of time series of stock returns and will provide researchers and practitioners additional options and incentives to explore for future research. We have also provided statistical and practical reasons to support these findings.

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Motta, Giovanni, Darlin Soto, and Márcio Catelan. "Periodic Variable Stars Modulated by Time-varying Parameters." Astrophysical Journal 925, no. 1 (January 1, 2022): 73. http://dx.doi.org/10.3847/1538-4357/ac3833.

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Abstract Many astrophysical phenomena are time-varying, in the sense that their brightness changes over time. In the case of periodic stars, previous approaches assumed that changes in period, amplitude, and phase are well described by either parametric or piecewise-constant functions. With this paper, we introduce a new mathematical model for the description of the so-called modulated light curves, as found in periodic variable stars that exhibit smoothly time-varying parameters such as amplitude, frequency, and/or phase. Our model accounts for a smoothly time-varying trend and a harmonic sum with smoothly time-varying weights. In this sense, our approach is flexible because it avoids restrictive assumptions (parametric or piecewise-constant) about the functional form of the trend and amplitudes. We apply our methodology to the light curve of a pulsating RR Lyrae star characterized by the Blazhko effect. To estimate the time-varying parameters of our model, we develop a semi-parametric method for unequally spaced time series. The estimation of our time-varying curves translates into the estimation of time-invariant parameters that can be performed by ordinary least squares, with the following two advantages: modeling and forecasting can be implemented in a parametric fashion, and we are able to cope with missing observations. To detect serial correlation in the residuals of our fitted model, we derive the mathematical definition of the spectral density for unequally spaced time series. The proposed method is designed to estimate smoothly time-varying trends and amplitudes, as well as the spectral density function of the errors. We provide simulation results and applications to real data.

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Büchel, Beda, and Francesco Corman. "Meaningful Modeling of Section Bus Running Times by Time Varying Mixture Distributions of Fixed Components." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 8 (May 18, 2020): 626–37. http://dx.doi.org/10.1177/0361198120918576.

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Understanding the variability of bus travel time is a key issue in the optimization of schedules, transit reliability, route choice analysis, and transit simulation. The statistical modeling of bus travel time data is of increasing importance given the increasing availability of data. In this paper, we introduce a novel approach to modeling the day-to-day variability of urban bus running times on a section level. First, the explanatory power of conventionally used distributions is examined, based on likelihood and effect size. We show that a mixture model is a powerful tool to increase fitting performance, but the applied components need to be justified. To overcome this issue, we propose a novel model consisting of two individual characteristic distributions representing either off-peak or peak hour dynamics. The observed running time distribution at every hour of the day can be described as a combination (mixture) of the two dynamics. The proposed time varying model uses a small set of parameters, which are physically interpretable and capable of accurately describing running time distributions. With our modeling approach, we reduce the complexity of mixture models and increase the explanatory power and fit compared with conventional models.

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Hall, Stephen G., P. A. V. B. Swamy, and George S. Tavlas. "TIME-VARYING COEFFICIENT MODELS: A PROPOSAL FOR SELECTING THE COEFFICIENT DRIVER SETS." Macroeconomic Dynamics 21, no. 5 (January 20, 2016): 1158–74. http://dx.doi.org/10.1017/s1365100515000279.

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Coefficient drivers are observable variables that feed into time-varying coefficients (TVCs) and explain at least part of their movement. To implement the TVC approach, the drivers are split into two subsets, one of which is correlated with the bias-free coefficient that we want to estimate and the other with the misspecification in the model. This split, however, can appear to be arbitrary. We provide a way of splitting the drivers that takes account of any nonlinearity that may be present in the data, with the aim of removing the arbitrary element in driver selection. We also provide an example of the practical use of our method by applying it to modeling the effect of ratings on sovereign-bond spreads.

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Hynes, N. Rajesh Jesudoss, P. Nagaraj, and P. Thanga Kumar. "Mathematical Modeling of Friction Plug Welding with Preheating Effect." Advanced Materials Research 984-985 (July 2014): 600–603. http://dx.doi.org/10.4028/www.scientific.net/amr.984-985.600.

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Friction plug welding, a recent variation of friction welding is a process of joining of two similar or dissimilar materials. The joint efficiency can be enhanced by applying external heat source or pre-heating at the work piece surfaces. Heat flux generation at intermediate surface is computed due to friction between the materials considering the co-efficient of friction. The land width is varied by varying the diameter of the plug to find its effect on the temperature profile. Analytical modeling is carried out with and without the effect of pre-heating. Temperature distribution in the work piece was calculated for different plug diameter with different values of pre-heating temperature ranging from 300oC-600oC. It is observed that while decreasing the land width there is a linear fall in temperature profile. With preheating, higher peak temperature is achieved at less friction time. High quality weld could be achieved with less processing time.

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Zhang, Xing, Jun Zhang, Bo Pang, DiaoDiao Wu, XiaoWei Zheng, and WanHua Zhao. "An efficient approach for milling dynamics modeling and analysis with varying time delay and cutter runout effect." International Journal of Advanced Manufacturing Technology 87, no. 9-12 (April 14, 2016): 3373–88. http://dx.doi.org/10.1007/s00170-016-8671-8.

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Li, Fanjie, Xiaopeng Li, and Dongyang Shang. "Dynamic Modeling and Vibration Characteristics Analysis of Deep-Groove Ball Bearing, Considering Sliding Effect." Mathematics 9, no. 19 (September 28, 2021): 2408. http://dx.doi.org/10.3390/math9192408.

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To study the vibration characteristics of deep-groove ball bearing, considering the influence of sliding, the dynamic model of the DGB 6205 system is established in this paper. The DGB 6205 system model includes the movement of the bearing inner ring in the X and Y directions, the rotation of the cage, the rotation movement of each ball, the revolution movement of each ball and the movement along the radial direction of each ball. Based on the system model, the differential equations of motion of the system are established, and the correctness of the model is verified by experiment. The slip characteristics of the DGB 6205 system are studied by numerical simulation. At the same time, the influence of time-varying load on the vibration characteristics of the system is studied. Then, the sensitivity of system parameters is analyzed. The results show that the sliding speed between the ball and the inner raceway is greater than that between the ball and the outer raceway. The radial vibration response of DGB 6205 system under time-varying load is less than that under constant load. The increase of radial clearance will increase the vibration response of DGB 6205 system.

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Li, Longhao, and Yongshou Dai. "An adaptive soft sensor deterioration evaluation and model updating method for time-varying chemical processes." Chemical Industry and Chemical Engineering Quarterly 26, no. 2 (2020): 135–49. http://dx.doi.org/10.2298/ciceq190419032l.

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Due to the time-varying nature of chemical processes, soft sensor models deteriorate, and data prediction accuracy decreases. To address this problem, an adaptive soft sensor modeling method is proposed that not only evaluates the model deterioration by an adaptive moving window-constrained statistical hypothesis test, but also adaptively updates the modeling samples using moving window-cosine similarity. First, this method evaluates the model deterioration via positioning by constrained statistical hypothesis testing based on the differences between the prediction performance evaluation index data obtained from moving window stepping and the original prediction performance evaluation indexes. Additionally, the dynamic temporal variation in chemical processes causes changes in the impacts of the auxiliary variables on the dominant variable, and this effect limits the improvement in the prediction accuracy of the soft sensor model by updating only the auxiliary variable data. The moving window-cosine similarity method is combined to propose a strategy that updates both the modeled auxiliary variables and the auxiliary variable data. Finally, the parameters of the soft sensor model are optimized via particle swarm optimization (PSO) to improve the fitting performance. Simulated data of a continuous stirred tank reactor (CSTR) and actual data from a debutanizer column process (DCP) are used for model verification to evaluate the performance of the proposed adaptive soft sensor modeling method, and the results show its effectiveness.

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Li, Dongjuan, Dongxing Wang, and Ying Gao. "Adaptive Neural Control and Modeling for Continuous Stirred Tank Reactor with Delays and Full State Constraints." Complexity 2021 (October 7, 2021): 1–12. http://dx.doi.org/10.1155/2021/9948044.

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In this paper, an adaptive neural network control method is described to stabilize a continuous stirred tank reactor (CSTR) subject to unknown time-varying delays and full state constraints. The unknown time delay and state constraints problem of the concentration in the reactor seriously affect the input-output ratio and stability of the entire system. Therefore, the design difficulty of this control scheme is how to debar the effect of time delay in CSTR systems. To deal with time-varying delays, Lyapunov–Krasovskii functionals (LKFs) are utilized in the adaptive controller design. The convergence of the tracking error to a small compact set without violating the constraints can be identified by the time-varying logarithm barrier Lyapunov function (LBLF). Finally, the simulation results on CSTR are shown to reveal the validity of the developed control strategy.

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Epstein, Marina, Karl G. Hill, Stephanie S. Roe, Jennifer A. Bailey, William G. Iacono, Matt McGue, Allison Kristman-Valente, Richard F. Catalano, and Kevin P. Haggerty. "Time-varying effects of families and peers on adolescent marijuana use: Person–environment interactions across development." Development and Psychopathology 29, no. 3 (July 15, 2016): 887–900. http://dx.doi.org/10.1017/s0954579416000559.

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AbstractStudies have demonstrated that the effects of two well-known predictors of adolescent substance use, family monitoring and antisocial peers, are not static but change over the course of adolescence. Moreover, these effects may differ for different groups of youth. The current study uses time-varying effect modeling to examine the changes in the association between family monitoring and antisocial peers and marijuana use from ages 11 to 19, and to compare these associations by gender and levels of behavioral disinhibition. Data are drawn from the Raising Healthy Children study, a longitudinal panel of 1,040 youth. The strength of association between family monitoring and antisocial peers and marijuana use was mostly steady over adolescence, and was greater for girls than for boys. Differences in the strength of the association were also evident by levels of behavioral disinhibition: youth with lower levels of disinhibition were more susceptible to the influence of parents and peers. Stronger influence of family monitoring on girls and less disinhibited youth was most evident in middle adolescence, whereas the stronger effect of antisocial peers was significant during middle and late adolescence. Implications for the timing and targeting of marijuana preventive interventions are discussed.

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Hajdu, Sándor, and Péter Gáspár. "Reducing the mast vibration of single-mast stacker cranes by gain-scheduled control." International Journal of Applied Mathematics and Computer Science 26, no. 4 (December 1, 2016): 791–802. http://dx.doi.org/10.1515/amcs-2016-0056.

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AbstractIn the frame structure of stacker cranes harmful mast vibrations may appear due to the inertial forces of acceleration or the braking movement phase. This effect may reduce the stability and positioning accuracy of these machines. Unfortunately, their dynamic properties also vary with the lifted load magnitude and position. The purpose of the paper is to present a controller design method which can handle the effect of a varying lifted load magnitude and position in a dynamic model and at the same time reveals good reference signal tracking and mast vibration reducing properties. A controller design case study is presented step by step from dynamic modeling through to the validation of the resulting controller. In the paper the dynamic modeling possibilities of single-mast stacker cranes are summarized. The handling of varying dynamical behavior is realized via the polytopic LPV modeling approach. Based on this modeling technique, a gain-scheduled controller design method is proposed, which is suitable for achieving the goals set. Finally, controller validation is presented by means of time domain simulations.

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Zhang, Dong Sheng, Xiao Hong Liu, Jian Guo Shi, Jun Mao, and Zhong Li. "Scraper Conveyor Dynamic Modeling and Simulation." Advanced Materials Research 217-218 (March 2011): 426–30. http://dx.doi.org/10.4028/www.scientific.net/amr.217-218.426.

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Modeled nonlinearity, time-varying, dynamic coupling finite element model of scraper conveyor according to its actual working condition in the mining, studied the transmission mechanism of bulk material power and its parameters test methods，constructed the shape function of scraper conveyor circuitry, realized the computer automatic modeling, by the example carried on digital simulation of all of working condition such as starting, freely stoppage, abnormal load, chains blocked, the difference of chain’s pitch and the chain wheel polygon effect, and so on.

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Meng, Qingxin, Xiangyun Hu, Heping Pan, Huolin Ma, and Miao Luo. "Time-domain induced polarization forward modeling and an apparent spectral parameter solution based on the Weibull growth model." GEOPHYSICS 85, no. 5 (September 1, 2020): D145—D155. http://dx.doi.org/10.1190/geo2018-0693.1.

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The application of the Cole-Cole model within time-domain induced polarization (TDIP) forward field modeling shows that the model parameters can characterize time-varying states of the TDIP field and support observed data analysis. The Cole-Cole model contains real and imaginary parts, and it requires a frequency-to-time conversion for TDIP forward modeling. However, the TDIP field is usually expressed by a real number, and its intuitive time-varying states field intensity increases with charging time. Therefore, the forward model should be constructed in a simpler form. We have aimed to develop a forward model using mathematical functions not based on physical principles. The Weibull (WB) growth model, which is primarily used to describe the time-varying curve features in regression analysis, is introduced into the basic algorithm of the TDIP forward model. Subsequently, a forward expression of the TDIP effect is established. Based on the time-varying shape and scale parameters, this expression describes the time-varying rate and relaxation states of the TDIP fields. Furthermore, based on the extensively used conjugate gradient optimization, an apparent WB parameter scheme is initiated to calculate the spectral parameters that represent the relaxation and time-varying rate obtained from the multi-time-channel TDIP data. Finally, this scheme is applied to interpret the different simulated and actual TDIP data. The results demonstrate that the WB growth model can be used for the TDIP forward model without involving physical principles, the model parameters without specific physical significance can be used to represent the time-varying states of TDIP fields, and apparent WB parameters can be used to discern different TDIP observed data. The setting of the TDIP forward model and model parameters can actually be more flexible and diverse, so as to obtain simpler forward expressions and ensure a highly efficient inverse solution.

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Liu, Yi, Wei Zhou, Bing Ji, Deying Yu, Shaofeng Bian, Shouzhou Gu, and Deyan Li. "Effect of Stochastic Modeling for Inter-Frequency Biases of Receiver on BDS-3 Five-Frequency Undifferenced and Uncombined Precise Point Positioning." Remote Sensing 14, no. 15 (July 27, 2022): 3595. http://dx.doi.org/10.3390/rs14153595.

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The third generation of the Beidou navigation satellite system (BDS-3) broadcasts navigation signals of five frequencies. Focusing on the deep integration of five-frequency signals, we applied the joint BDS-3 five-frequency undifferenced and uncombined precise point positioning (UC-PPP) to analyze the receiver inter-frequency biases (IFB). Firstly, 12 Multi-GNSS Experiment tracking (MGEX) stations are selected to investigate the time-varying characteristics of receiver IFB and, according to random characteristics, three random modeling schemes are proposed. Secondly, the effects of three stochastic modeling methods on zenith tropospheric delay, ionospheric delay, floating ambiguity, and quality control are analyzed. Finally, the effects of three IFB stochastic modeling methods on positioning performance are evaluated. The results showed that the amplitude in the IFB for B2b is 5.139 m, B2a is 1.964 m, and B1C is 0.950 m by measuring one week’s observation data. The IFB stochastic modeling method based on random walks can shorten the PPP convergence time by 4~12%, diminish the false alarm of quality control, and improve the positioning accuracy. The random walk model is recommended to simulate the variation of IFB, which can not only overcome the disadvantage of the time constant model being unable to accurately describe the time-varying characteristics of the IFB, but also avoid reducing the strength of the kinematic PPP positioning model due to the large process noise of the white noise model.

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Aryaie, Mohammad, Hamid Sharifi, Azadeh Saber, Farzaneh Salehi, Mahyar Etminan, Maryam Nazemipour, and Mohammad Ali Mansournia. "Longitudinal causal effect of modified creatinine index on all-cause mortality in patients with end-stage renal disease: Accounting for time-varying confounders using G-estimation." PLOS ONE 17, no. 8 (August 19, 2022): e0272212. http://dx.doi.org/10.1371/journal.pone.0272212.

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Background Standard regression modeling may cause biased effect estimates in the presence of time-varying confounders affected by prior exposure. This study aimed to quantify the relationship between declining in modified creatinine index (MCI), as a surrogate marker of lean body mass, and mortality among end stage renal disease (ESRD) patients using G-estimation accounting appropriately for time-varying confounders. Methods A retrospective cohort of all registered ESRD patients (n = 553) was constructed over 8 years from 2011 to 2019, from 3 hemodialysis centers at Kerman, southeast of Iran. According to changes in MCI, patients were dichotomized to either the decline group or no-decline group. Subsequently the effect of interest was estimated using G-estimation and compared with accelerated failure time (AFT) Weibull models using two modelling strategies. Results Standard models demonstrated survival time ratios of 0.91 (95% confidence interval [95% CI]: 0.64 to 1.28) and 0.84 (95% CI: 0.58 to 1.23) in patients in the decline MCI group compared to those in no-decline MCI group. This effect was demonstrated to be 0.57 (-95% CI: 0.21 to 0.81) using G-estimation. Conclusion Declining in MCI increases mortality in patients with ESRD using G-estimation, while the AFT standard models yield biased effect estimate toward the null.

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Ding, Li, and Ping Hu. "Contagion Processes on Time-Varying Networks with Homophily-Driven Group Interactions." Complexity 2019 (October 30, 2019): 1–13. http://dx.doi.org/10.1155/2019/7130468.

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The complicated interaction patterns among heterogeneous individuals have a profound impact on the contagion process in the networks. In recent years, there has been increasing evidence for the emergence of many-body interactions between two or more nodes in a wide range of biological and social networks. To encode these multinode interactions explicitly, the simplicial complex is now a popular alternative to simple networks. Meanwhile, the time-varying network has been acknowledged as a key ingredient of the contagion process. In this paper, we consider the connectivity pattern of networks affected by the homophily effect associated with individual attributes and investigate the impact of homophily-driven group interactions on the contagion process in temporal networks. The simplicial complex modeling framework is adopted to capture stochastic interactions between passively selected nodes in the paradigm of activity-driven networks. We study the evolution of infection and the epidemic threshold of the contagion process by both analytical and numerical methods. Our results on statistical topological properties of instantaneous network may shed light on accurately characterizing the evolution curve of infection. Furthermore, we show the impact of the homophily-driven interaction pattern on the epidemic threshold, which generalizes the existing results on both the paradigmatic activity-driven network and the simplicial activity-driven network.

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Yang, Lei, Lei Wang, and Wanhua Zhao. "Hybrid modeling and analysis of multidirectional variable stiffness of the linear rolling guideway under combined loads." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 234, no. 13 (February 23, 2020): 2716–27. http://dx.doi.org/10.1177/0954406220908894.

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In the working process of high-speed multiaxis machine tools, inertial loads due to high feed acceleration and time-varying gravity loads due to changing configuration of multiaxis structure result in time-varying complex loads applied to linear rolling guideway. Existing models cannot efficiently represent the effect of complex loads on multidirectional stiffness variation of linear rolling guideway. In this paper, a hybrid model of multidirectional stiffness of linear rolling guideway and the solving algorithm are proposed. The complex loading conditions of linear rolling guideway in high-speed multiaxis machine tool structure are considered. And contact flexibilities between rolling balls and grooves are modeled with the effect of elastic deformations of runner block and rail. The proposed model can calculate the multidirectional stiffness with high accuracy. Meanwhile the differences between the stiffness characteristics in different directions are represented correctly. The variations of multidirectional stiffness of linear rolling guideway under time-varying combined loads are analyzed. This study provides an effective way to comprehensively evaluate the stiffness characteristics of linear rolling guideway which can contribute to the dynamic analysis and active design of high-speed machine tool structure.

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Wang, Zheng, Zhenglong Sun, and Soo Jay Phee. "Modeling tendon-sheath mechanism with flexible configurations for robot control." Robotica 31, no. 7 (May 14, 2013): 1131–42. http://dx.doi.org/10.1017/s0263574713000386.

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SUMMARYSurgical and search/rescue robots often work in environments with very strict spatial constraints. The tendon-sheath mechanism is a promising candidate for driving such systems, allowing power sources and actuation motors placed outside to transmit force and energy to the robot at the distal end through the constrained environment. Having both compactness and high force capability makes it very attractive for manipulation devices. On the other hand, the friction attenuation of tendon tension is nonlinear and configuration-dependent due to tendon/sheath interactions throughout the transmission path. This is a major obstacle for the tendon-sheath mechanism to be widely adopted. Here, we focus on the friction analysis for flexible and time-varying tendon-sheath configurations: the most challenging but yet commonly encountered case for real-world applications. Existing results on fixed-path configurations are reviewed, revisited, and extended to flexible and time-varying cases. The effect of tendon length to friction attenuation is modeled. While focusing on tension transmission, tendon elongation is also discussed with the length effect applied. In the end, two-dimensional results are extended to three-dimensional tendon-sheath configurations. All propositions and theorems are validated on a dedicated experimental platform.

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Vannucci, Anna, Kaitlin M. Flannery, and Christine McCauley Ohannessian. "Age-varying associations between coping and depressive symptoms throughout adolescence and emerging adulthood." Development and Psychopathology 30, no. 2 (April 25, 2018): 665–81. http://dx.doi.org/10.1017/s0954579417001183.

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AbstractThe objective of the current study was to apply the novel technique of time-varying effect modeling to examine age-varying associations between specific coping strategies and depressive symptoms across adolescence and emerging adulthood (ages 14–24). The participants were drawn from a community sample and followed across 4 years of high school and once 5 years postgraduation (N = 1,251, 53% female, 58% non-Hispanic White). Coping and depressive symptom questionnaires were administered across all data collection time points. Time-varying effect modeling used all available data (N = 5,651 measurement occasions) and adjusted for gender. Venting emotions and denial were associated with more depressive symptoms at a similar magnitude across adolescence and emerging adulthood. A positive association between problem solving oriented strategies (planning, active coping) and depressive symptoms was not observed until age 17.5, after which the magnitude of the association strengthened. More frequent instrumental and emotional support seeking were linked to fewer depressive symptoms between ages 18.8 and 23.6. More frequent use of humor was associated with greater depressive symptoms from ages 14.0 to 14.6, but with fewer depressive symptoms from ages 16.8 to 18.8. The findings illuminate when and how associations between specific coping strategies and depressive symptoms may emerge and change across developmental age, generating both theoretical and clinical implications.

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Maher, Jaclyn P., Eldin Dzubur, Jimi Huh, Stephen Intille, and Genevieve F. Dunton. "Within-Day Time-Varying Associations Between Behavioral Cognitions and Physical Activity in Adults." Journal of Sport and Exercise Psychology 38, no. 4 (August 2016): 423–34. http://dx.doi.org/10.1123/jsep.2016-0058.

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This study used time-varying effect modeling to examine time-of-day differences in how behavioral cognitions predict subsequent physical activity (PA). Adults (N = 116) participated in three 4-day “bursts” of ecological momentary assessment (EMA). Participants were prompted with eight EMA questionnaires per day assessing behavioral cognitions (i.e., intentions, self-efficacy, outcome expectations) and wore an accelerometer during waking hours. Subsequent PA was operationalized as accelerometer-derived minutes of moderate- or vigorousintensity PA in the 2 hr following the EMA prompt. On weekdays, intentions positively predicted subsequent PA in the morning (9:25 a.m.–11:45 a.m.) and in the evening (8:15 p.m.–10:00 p.m.). Self-efficacy positively predicted subsequent PA on weekday evenings (7:35 p.m.–10:00 p.m.). Outcome expectations were unrelated to subsequent PA on weekdays. On weekend days, behavior cognitions and subsequent PA were unrelated regardless of time of day. This study identifies windows of opportunity and vulnerability for motivation-based PA interventions aiming to deliver intervention content within the context of adults’ daily lives.

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Wright, Aidan G. C., Michael N. Hallquist, Holly A. Swartz, Ellen Frank, and Jill M. Cyranowski. "Treating co-occurring depression and anxiety: Modeling the dynamics of psychopathology and psychotherapy using the time-varying effect model." Journal of Consulting and Clinical Psychology 82, no. 5 (October 2014): 839–53. http://dx.doi.org/10.1037/a0034430.

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Gao, Shu Zhi, Jing Yang, and Jun Fan. "Modeling of Distillation Tower Temperature Based on D-FNN." Advanced Materials Research 383-390 (November 2011): 1463–69. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.1463.

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Distillation temperature control system is characteristics of nonlinear time-varying and we use dynamic fuzzy neural network to model the temperature of distillation. Firstly, we introduce the structure and algorithm of dynamic fuzzy neural network; Second, after data preprocessing of distillation process, we use dynamic Fuzzy neural network modeling the temperature of distillation. Dynamic fuzzy neural network adopt dynamic learning algorithm, and characteristic of approximation. The simulation results show the effect and accuracy of Dynamic fuzzy neural network model ing method.

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Metsileng, Lebotsa Daniel, Ntebogang Dinah Moroke, and Johannes Tshepiso Tsoku. "Modeling the Exchange Rate Volatility Using the BRICS GARCH-type Models." International Journal of Financial Research 12, no. 5 (October 11, 2021): 166. http://dx.doi.org/10.5430/ijfr.v12n5p166.

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The paper models the performance of GARCH-type models on BRICS exchange rates volatility. The levels of interdependence and dynamic connection among the BRICS financial markets using appropriate univariate time series models were evaluated for the period January 2008 to January 2018. The results revealed the presence of ARCH effects in the BRICS exchange rates. The univariate GARCH models for the BRICS exchange rates were fitted to the data using Student t-distribution. The GARCH (1,1) model found the unconditional volatility for each of the BRICS exchange rates series while EGARCH (1,1) and TGARCH (1,1) models presented the leverage effect. Moreover, the EGARCH (1,1) model illustrated that the asymmetric effects dominate the symmetric effects except for South Africa. The TGARCH (1,1) model on the other hand revealed contrary findings. The paper recommends a study be considered to draw comparison on the different types of GARCH models on the time varying integrated data other than the ones used in the paper.

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Tan, Xiao Long, Jia Zhou, and Wen Bin Wang. "Analysis on Suddenly Stop Running Effect of Wind Turbine in Power System." Applied Mechanics and Materials 556-562 (May 2014): 1779–81. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.1779.

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Wind speed of the time-varying bring many security hidden danger to the operation of the wind turbine, especially under the condition of the wind speed is too low or the wind speed is too large, wind turbine control device can make the wind machine stopped running, at this time on the stability of power grid and significant influence on the distribution of electric power system. Therefore, based on the simulation platform of PSCAD/EMTDC software was carried out on the wind turbine when suddenly stop running of power system modeling and simulation, research on power system transient changes at this moment.

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Strand, Matthew, Daniel Nelson, and Gary Grunwald. "Modeling between-subject differences and within-subject changes for long distance runners by age." Journal of Quantitative Analysis in Sports 14, no. 2 (June 27, 2018): 81–90. http://dx.doi.org/10.1515/jqas-2017-0038.

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Abstract A time-varying predictor in a longitudinal model can be separated into between- and within-subject components. This is important if a researcher is specifically interested in differences between subjects or changes within subjects. If no separation is made, then the effect associated with the time-varying predictor is a combination of the between- and within-subject effects. In this article, running race performances are considered as a nonlinear function of age, for which both absolute and relative difference terms are used to separate between- and within-subject components. Longitudinal data were obtained from 12 consecutive years of the 10-km Bolder Boulder for analysis, for the class of competitive recreational runners. Mixed models were used to fit the data after log transforming the nonlinear model. Results of model fits demonstrated that between-subject differences between ages were somewhat similar to within-subject changes, although the latter tended to change somewhat more slowly, especially after the peak racing ages. For example, the between-subject rate of change for 43 year-old runners was about 1% per year on average (increase in race time), while the within-subject change for a runner of the same age averaged between 0.6 and 0.8% per year.

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Akbari, Nasim, Ali Sadr, and Ali Kazemy. "Robust exponential synchronization of a Markovian jump complex dynamical network with piecewise homogeneous Markovian parameters." IMA Journal of Mathematical Control and Information 37, no. 4 (April 7, 2020): 1168–91. http://dx.doi.org/10.1093/imamci/dnz041.

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Abstract This paper establishes a stochastic synchronization method for a Markovian jump complex dynamical network (MJCDN) with time-delay and uncertainties. The considered Markovian structure is piecewise-homogeneous with piecewise-constant time-varying transition rates (TRs). Two Markovian signals are utilized to construct the piecewise-homogeneous Markovian structure. A low-level Markovian signal with time-varying TRs governs the switching between the system dynamics while it is managed by a high-level Markovian signal. Due to the effect of imperfections induced by modeling errors in the system dynamics, some parametric norm-bounded uncertainties are considered. In addition, uncertain TR matrix is considered which means that inaccurate or uncertain information for each element of the TR matrix is allowable. This modelling makes the MJCDN to be more general and applicable than the existing ones. Synchronization conditions are obtained and reported in the form of linear matrix inequalities by the help of Lyapunov–Krasovskii theory, Wirtinger-based integral inequality approach and reciprocally convex technique. Finally, a numerical example is presented to verify the effectiveness of the proposed method.

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Wu, Jiulin, Yifan Zhou, Wei Jiang, and Xuedong Chen. "Time-Domain Dynamic Modeling and Analysis of Complex Heavy-Duty Gearbox Considering Floating Effect." Applied Sciences 11, no. 15 (July 26, 2021): 6876. http://dx.doi.org/10.3390/app11156876.

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Expert insights into the time-domain dynamic behavior of heavy-duty gearboxes form the foundations of design evaluation and improvement. However, in the existing lateral–torsional coupling (LTC) modeling method for gearboxes that is normally used for frequency-domain dynamic behavior, the meshing forces are modeled as spring dampers with fixed acting points on the meshing gears to simulate only the transient LTC effect, and thus the steady state characteristic in the time domain cannot be obtained due to the unrealistic distortion of positions and orientations as the gear angles increase. In this paper, a novel and generally applicable LTC modeling method for heavy-duty gearboxes, mainly planetary gear sets with floating components, is proposed by using space-fixed spring dampers with floating acting points on the meshing gears to study the time-domain dynamic response and to support the dynamic design of heavy-duty gearboxes. Based on the proposed method, a LTC model of a 2 megawatt (MW) wind turbine gearbox with floating components considering the time-varying meshing stiffness, bearing stiffness, torsional stiffness, and floating effect was established. The simulated results of representative components were in accordance with experimental results on a test rig, and dynamic behavior was calculated.

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Jamli, M. R., Ahmad Kamal Ariffin, D. A. Wahab, A. E. Ismail, and I. A. Shah. "Sensitivity of Modeling in Sheet Metal Three-Point Cyclic Bending." Applied Mechanics and Materials 165 (April 2012): 187–91. http://dx.doi.org/10.4028/www.scientific.net/amm.165.187.

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The aim of this paper is to examine the modeling sensitivity of the three-point bending test by using finite element method (FEM). Three-point bending test has been frequently used to determine the material hardening parameters of sheet metal. As a part of the parameter identification, three-point bending has been simulated and analyzed using FEM. To minimize the computation time, shell element was used to model the sheet metal. The analysis includes implicit and explicit procedures. In particular, this study examines the effect of FEM results by varying the element type, mesh density, and number of integration point. It is shown that the implicit procedure analyze the simulation with very less computation time compared to the explicit procedure. The results also show that only the number of integration point has significant effect on the simulation in both implicit and explicit procedures.

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Nadar, Deslin, Kubendren Naicker, and David Lokhat. "Ultrasonically-Assisted Dissolution of Sugarcane Bagasse during Dilute Acid Pretreatment: Experiments and Kinetic Modeling." Energies 13, no. 21 (October 28, 2020): 5627. http://dx.doi.org/10.3390/en13215627.

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Ultrasonic irradiation is known to enhance various physicochemical processes. In this work, the effect of ultrasound on the dissolution of sugarcane bagasse was studied, with the specific aims of quantifying the effect at low solids loading and mild reaction conditions, and determining whether the enhancement of dissolution by ultrasound is independent of temperature. The effects of agitation speed, reaction time, and sonication were examined on the dissolution of the biomass substrate at varying reaction temperatures during the pretreatment process. Sugarcane bagasse was mixed with a 0.3 M solution of sulfuric acid in a reaction vessel to undergo pretreatment. A kinetic model was applied to the mass dissolution of the biomass, as sonicated runs showed higher mass losses at each reaction time, compared to the non-sonicated runs. The ultrasonic enhancement in mass dissolution was seen to increase for an increase in the reaction time. It was observed that the induction period for the dissolution was eliminated by the application of ultrasound. Ultrasound was found to be more effective than temperature at enhancing mass dissolution at low solids loadings, and the effect of ultrasound was also found to be dependent on the temperature employed.

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Dermody, Sarah S., Katherine M. Thomas, Christopher J. Hopwood, C. Emily Durbin, and Aidan G. C. Wright. "Modeling the complexity of dynamic, momentary interpersonal behavior: Applying the time-varying effect model to test predictions from interpersonal theory." Journal of Research in Personality 68 (June 2017): 54–62. http://dx.doi.org/10.1016/j.jrp.2017.03.001.

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Zamuner, Stefano, Roberto Gomeni, and Alan Bye. "Estimate the time varying brain receptor occupancy in PET imaging experiments using non-linear fixed and mixed effect modeling approach." Nuclear Medicine and Biology 29, no. 1 (January 2002): 115–23. http://dx.doi.org/10.1016/s0969-8051(01)00275-x.

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Liu, Dawei, Dandan Gu, and Zhijia Liu. "Coupled vibration modeling and dynamic characteristics of noncircular face gear drive system with time-varying instantaneous center excitation." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, no. 14 (April 8, 2019): 4947–59. http://dx.doi.org/10.1177/0954406219841085.

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Noncircular face gear drive is a new type of variable transmission ratio mechanism with advantages of light weight, high interchangeability, and convenient installation. Based on its transmission principle, the excitation pattern of the time-varying instantaneous center of the noncircular face gear drive system is investigated. A torsional–lateral–axial coupled dynamic model of the noncircular face gear system is presented under the compound parametric excitations of the time-varying instantaneous center and the mesh stiffness. By using Runge–Kutta numerical integration method, the dynamic responses of the system are derived to analyze the vibration features of the noncircular face gear under compound parametric excitations and the effect of the design parameters on the coupled vibration. The analytical results indicate that there exist multifrequency components in the dynamic responses of the system, including the instantaneous center frequency f1, the meshing one f2, nf1, mf2, and mf2 ± nf1. In addition, the dynamic performance of the noncircular face gear drive can be improved by decreasing the amplitude coefficient of the instantaneous center and the mesh stiffness or increasing their mean values.

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Kozlowska, Anna Maria, Øyvind Øksnes Dalheim, Luca Savio, and Sverre Steen. "Time Domain Modeling of Propeller Forces due to Ventilation in Static and Dynamic Conditions." Journal of Marine Science and Engineering 8, no. 1 (January 9, 2020): 31. http://dx.doi.org/10.3390/jmse8010031.

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This paper presents experimental and theoretical studies on the dynamic effect on the propeller loading due to ventilation by using a simulation model that generates a time domain solution for propeller forces in varying operational conditions. For ventilation modeling, the simulation model applies a formula based on the idea that the change in lift coefficient due to ventilation computes the change in the thrust coefficient. It is discussed how dynamic effects, like hysteresis effects and blade frequency dynamics, can be included in the simulation model. Simulation model validation was completed by comparison with CFD (computational fluid dynamics) calculations and model experiments. Experiments were performed for static and dynamic (heave motion) conditions in the large towing tank at the SINTEF Ocean in Trondheim and in the Marine Cybernetics Laboratories at NTNU (Norwegian University of Science and Technology). The main focus of this paper is to explain and validate the prediction model for thrust loss due to ventilation and out of water effects in static and dynamic heave conditions.

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Journal articles on the topic 'Time-varying effect modeling'

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