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Optimized viscous dampers mitigate the dynamic response of building with plan asymmetry. Previous research efforts limit the optimization method to time domain requiring time history analyses to optimize damper placement for plan eccentricity-induced torsional response combined with translational response. This can consume high computational effort and lead to the variability in the ground motion selection. To expedite the optimization process while taking ground motion variability into account, this study will offer a novel criterion based on stochastic performance. This technique will skip the traditional approach of employing time history analyses and will take frequency domain variability into account. Through given distance between the center of mass (CM) and the target frame, the study establishes the stochastic criterion for the response at the perimeter of the building where the maximum torsional-translational response occurs. This allows the optimization methods to generate high quality solution with less computational efforts compared to traditional approach (i.e. time domain-based optimization). It is noteworthy that the proposed criterion is applicable to extensive kinds of responses (e.g. peak floor acceleration, story shear and etc.) once the geometric relationship is given. The proposed criterion as the objective function is compared against their counterpart in time domain through a case study. The case study is based on a reinforced concrete (RC) moment-resisting-frame (MRF) building with two-way asymmetric plan and adopts Element Exchange Method (EEM) to optimize the damper placement. The effectiveness of optimized design based in frequency domain and time domain is evaluated for their total running time and maximum peak interstory drift against a suite of ground motions. The result showed that the proposed criterion can offer the improvement against the traditional approach in terms of solution quality (i.e. performance in time domain and frequency domain) and computational efforts (i.e. total running time for optimization).

The “hard water” factor shows the management of water in the Nusa Tenggara Timur, which shows a higher ratio based on the ion’s minerals. The incessant use of hard water presents kidney dysfunction, which produces diabetic and vascular kinds of diseases. Therefore, it is essential to recognize the influences of hard water on kidney function. A novel design of a stochastic solver using the transfer radial basis function is provided by applying the Bayesian regularization neural network for solving the model. The kidney dysfunction mathematical system is divided into humans (susceptible, infected, recovered) and water components (magnesium, calcium). Twelve numbers of neurons with the radial basis transfer function have been used in the hidden layers for solving the model. The approach performance is remarked through the results comparison and further reducible absolute error found around $10^{-06}$ to $10^{-08}$ develop the scheme’s exactness. Moreover, the statistical performances including regression coefficient performances around 1 for each case of the model validate the reliability and exactness of the scheme for solving the model.

In this paper, a novel approach based on the wavelet orthonormal decomposition is presented to extract features in pattern recognition. The proposed approach first reduces the dimensionality of a two-dimensional pattern, and thereafter performs wavelet transform on the derived one-dimensional pattern to generate a set of wavelet transform subpatterns, namely, several uncorrelated functions. Based on these functions, new features are readily computed to represent the original two-dimensional pattern. As an application, experiments were conducted using a set of printed characters with varying orientations and fonts. The results obtained from these experiments have consistently shown that the proposed feature vectors can yield an excellent classification rate in pattern recognition.

In this paper, the discrete Fourier transform is used to determine the coefficients of a transfer function of a new generalized two-dimensional system of second-order: Ex(i₁ + 2, i₂ + 2) = A₀x(i₁ + 1, i₂ + 1) + A₁x(i₁ + 1, i₂) + A₂x(i₁, i₂ + 1). The algorithm is straightforward and has been implemented using the software package Matlab™. A step-by-step example illustrating the application of the algorithm is presented.

In this paper, closed-form models for the computation of finite ramp responses of current-mode resistance inductance capacitance (RLC) interconnects in VLSI circuits are presented. These models are based on extended Eudes model and Scaling and Squaring algorithm which allow numerical estimation of delay in lossy very large scale integration (VLSI) interconnects. The existing Eudes model for interconnect transfer function approximation is extended to higher-order and then Scaling and Squaring method is applied for further improving the accuracy of delay estimation. With the equivalent lossy interconnect transfer function, finite ramp responses are obtained and line delay is estimated for various line lengths, per unit inductances and load capacitances. The estimated 50% delay values are compared with HSPICE W-element model. The worst case errors observed in the estimated delay values are 14.3% for Eudes model and 2% for extended Eudes model while the proposed Scaling and Squaring based model with 1% error is in very good agreement with HSPICE for line lengths 0.1–0.5 cm. The estimated crosstalk induced delay values of proposed model maximum error percentage is nearly half of the extended Eudes model. For both single and three coupled interconnect lines, the proposed model is in good agreement with HSPICE.

The issue of Web reliability is gaining importance, as different Web-based applications are getting popularity with time. In order to enhance the reliability of a Web system, the Web administrator have to determine if there exists any relationship or correlation among different Web workload characteristics and the errors having an impact on the reliability of the Web system, so that he will be able to predict them accurately. It may not be possible to establish a generalized relationship among different Web workload characteristics. Hence, in this paper, we have performed principal component analysis (PCA) to check whether different Web workload characteristics, for particular Web software are correlated or not. Then, we have proposed a transfer function based model for Web software fault prediction. Also, we have used the pre-whitening technique to eliminate the noise present in the data for developing an efficient transfer function based model to predict the cumulative occurrences of different Web failures having an impact on the reliability of the Web software.

This paper analyzed the vibration of planar frame structures using the transfer function, which is obtained as the Laplace transform of Green’s function. The transfer function was used to represent the relationship between the excitation (including the initial and boundary conditions) and the response of the system; that is, it can determine the vibration response and stability of the system. The frame was divided into several joint blocks with substructures (beams). A state-space matrix form was used to represent the equation of motion in the beams. The compatibility between the joint blocks and beams allows us to establish the characteristic matrix of the frame, of which the determinant is the characteristic equation. With the eigenvalues obtained as the roots of the characteristic equation, one can establish the eigenfunction of the frame. The receptance of the structure with a single point excitation was also studied. The application of the transfer function to analysis of the L- and H-shaped planar frame structures was conducted in this paper. The results agree well with those published in the literature.

This paper aims to study the transfer laws of vibration signals in the free field near a high-speed train line by conducting a field test. The characteristics of ground vibration acceleration were analyzed in the time and frequency domains, and a prediction method in the frequency domain was proposed. The results show: (1) there is a vibration amplification area away from the bottom of the pier under the influence of high-speed trains running over the bridge due to the fluctuation attenuation of the vibration waves; (2) the dominant peak frequency points in the frequency spectrum of the acceleration can be regarded as the resonance frequency induced by periodic loading; and (3) the soil vibration can be effectively predicted by the proposed method with a strong capability to defend the interference of environmental vibrations according to the comparison between the predicted value and the experimental data.

This paper proposes a scaled model to investigate the dynamic characteristics and stability of a hoop truss antenna on the ground. First, the statically indeterminate equation for the multi-point suspension is established, along with the voltage of the suspension motor calculated. Then the transfer function of the system is theoretically established. The scaled model is established before and after suspension, and the static deformation and natural frequency of the system are obtained by calculation and measurement. There exist the shaking mode and nodding mode. Also, a vibration experiment is conducted for the system to obtain the vibration response. With this, the transfer function is identified by the system identification method, which appears to be of the second order, and the stability is analyzed through the zero pole diagram. The experiment results show that the first two frequencies are close before and after suspension. Moreover, the stability of the system can be judged by the open-loop transfer function. It is concluded that the vibration experimental data of the scaled model can be used as a reference for the large hoop truss antenna structure.

Volume data often have redundant information for clinical uses. The essence of volume rendering can be regarded as a mechanism to determine visibility of redundant information and structures of interest using different approaches. Controlling the visibility of these structures in volume rendering depends on the following factors in existing rendering algorithms: The data value of current voxel and its derivatives (used in transfer function based approaches), and the voxel position (used in volume clipping). This paper introduces the distance which is defined by the user into volume rendering pipeline to control the visibility of structures. The distance based approach, which is named as distance transfer function, has the flexibility of transfer functions for depicting data information and the advantages of volume clippings for visualizing inner structures. The results show that the distance based approach is a powerful tool for volume data information depiction.

Several types of middle ear implants (MEIs) have been invented as an alternative to conventional hearing aids for the rehabilitation of sensorineural hearing loss. Temporal bone and clinical studies have shown that the implantation of MEIs’ transducers influences middle ear transfer function. But there is little comparative data available about these influences. We conducted comparative studies on the influences of three principal types of MEI transducers in respect to their attachment points on the ossicular chain. To aid the investigation, a human middle ear finite element model was constructed. The model was built based on a complete set of micro-computerized tomography section images of a human ear by reverse engineering technology. The validity of the developed model was verified by comparing the motions obtained by this model with published experimental measurements on human temporal bones. The results show that the eardrum driving transducer (EDT) and the floating mass transducer (FMT) decrease stapes displacement prominently at high frequencies. The greater these transducers’ mass, the smaller is the displacement of the stapes footplate. In contrast, the incus body driving transducer (IBDT) decreases stapes displacement severely at low frequencies, and its adverse effect on residual hearing increases with increasing stiffness of the IBDT’s driving rod.

From the viewpoint of statistical inverse problems, identification of transfer functions in feedback models is applied for neurodynamics of somatosensory cortices, and brain communication among active regions can be expressed in terms of transfer functions. However, brain activities have been investigated mainly by averaged waveforms in the conventional magnetoencephalography analysis, and thus brain communication among active regions has not yet been identified. It is shown that brain communication among two more than three brain regions is determined, when fluctuations related to concatenate averaged waveforms can be obtained by using a suitable blind source separation method. In blind identification of feedback model, some transfer functions or their impulse responses between output variables of current dipoles corresponding to active regions are identified from reconstructed time series data of fluctuations by the method of inverse problem. Neurodynamics of somatosensory cortices in 5 Hz median nerve stimuli can be shown by cerebral communication among active regions of somatosensory cortices in terms of impulse responses of feedback model.

Regenerative chatter is a major hurdle to the productivity and quality of machining operations. This is because of the undesirable surface finish, excessive tool wear and deteriorated dimensional accuracy. Machining chatter analysis techniques examine the stability of a closed-loop model of machining forces and tool-workpiece system. This model is based on mathematical manipulations of machining forces and the dynamic responses of machining tooling. Almost all techniques derive the dynamic responses from physical test. In this paper, a novel approach of milling chatter stability analysis is introduced by using FEA applications to obtain the dynamic responses of the machine tool. The accuracy of this methodology is validated by machine shop tests.

Transfer functions in the linear dynamic system theory are applied to characterize dynamic mechanical properties of viscoelastic materials. Correlation between transfer functions and typical rheological models and fractional derivative ones are briefly introduced. The transfer function of a rheological model may be expressed in terms of multiplication of factored polynomials. The frequency–response data are presented in the form of a Bode plot of magnitude, from which a transfer function can be established. The characteristic times can be conveniently identified via the corner frequencies of asymptotes of the magnitude curve. Dynamic frequency sweep results for a typical viscoelastic solid are presented to illustrate the use of the Bode diagram method for parameter identification.

This paper introduces an accurate analysis of time domain response of carbon nanotube (CNT) interconnects based on distributed RLC model that takes the effect of both the series resistance and the output parasitic capacitance of the driver into account. Using rigorous principle calculations, accurate expressions for the transfer function of these lines and their time domain response have been presented. It has been shown that the second-order transfer function cannot represent the distributed behavior of the long CNT interconnects, and the fourth-order approximation offers a better result. Also, the time response of a driven long CNT interconnect versus length and diameter have been studied. The obtained results show that the overshoot increases and the time delay decreases with increasing the CNT diameter, such that with the diameter value of 10 nm for a 3.3 mm CNT interconnect, the maximum overshoot value reaches about 95% of the amplitude of the driver input. On the contrary, the overshoot increases and the time delay decreases with decreasing the length of the CNT, such that with the length value of 1 mm for a 5 nm diameter CNT interconnect, the maximum overshoot reaches about 90% of the amplitude of the driver input.

Extended projects usually undergo different motions at their supports located at varying soil property conditions when an earthquake occurs. A theoretical framework including the key transfer function is proposed for simulating multi-support seismic underground motions in media-transition sites. First, a multi-layer media-transition site is illustrated. Then, the transfer function is theoretically derived and given explicitly using seismic wave propagation theory and fulfilling rigorously continuous boundary conditions. The obtained transfer function is the critical factor to calculate the underground Auto-Power Spectral Density (A-PSD). Meanwhile, the derivation and illustration of the other key factor (i.e. underground coherency function) is also given and the essential effect caused by media transition is further disclosed. The underground Cross-Power Spectral Density (C-PSD) is obtained by combining the underground coherency function with the transfer function. The underground Power Spectral Density Matrix (PSDM) is finally assembled by combining the A-PSD with C-PSD. Subsequently, multi-support seismic motions at varying depths of the media-transition site are generated, and its accuracy is further validated. Additionally, a numerical study is conducted to demonstrate the effect of water and soil phase on transfer functions and the underground seismic motions among dual-phase and media-transition sites. Results show the difference of seismic underground motions in two sites is obvious. This paper can provide a specific and feasible methodology for generating the multi-support seismic underground motions.

In this paper, we propose to study four meteorological and seasonal time series (TS) coupled with a multi-layer perceptron (MLP) modeling. We chose to combine two transfer functions for the nodes of the hidden layer, and to use a temporal indicator (time index as input) in order to take into account the seasonal aspect of the studied TS. The results of the prediction concern two years of measurements and the learning step, eight independent years. We show that this methodology can improve the accuracy of meteorological data estimation compared to a classical MLP modeling with a homogenous transfer function.

This paper researches the proportional-derivative (PD) feedback control with feed-forward compensations from input for a triangular tethered satellite system (TTSS), and the extended state observer (ESO) design which is further incorporated in control to estimate the structural uncertainties in system. By expanding Lagrangian equations under chosen variables, the dynamic equations of TTSS are derived which is the second-order nonlinear equation. Then the feedback control under typical feed-forward compensations is discussed as the nonlinear functions in system are counteracted, and the controlled outputs are computed by deriving the transfer functions of the transformed structures. Moreover, in case of the uncertain structures in system which may constrain the control effect, ESO-based PD control is further proposed, and the observed error and controlled accuracy are analyzed by Lyapunov functions. Simulation results on the designed controls are presented to validate the theoretic analyses.

This chapter provides an overview of parametric modeling of microwave components using combined neural network and transfer function (neuro-transfer function or neuro-TF). Transfer functions are used to represent the electromagnetic (EM) responses of passive components versus frequency. With the help of the transfer function, the nonlinearity of the neural network structure can be significantly decreased. We first introduce the neuro-TF modeling approach in rational format. Following that, we review the recent neuro-TF modeling approach in pole/zero format, where a pole/zero-matching algorithm is needed for addressing the issue of mismatch of poles and zeros before training the overall neuro-TF model. The neuro-TF modeling technique in pole/residue format is also reviewed. The orders of the pole–residue transfer functions may vary over different regions of geometrical parameters. A pole–residue tracking technique can be used to solve this order-changing problem. As a further advancement, we discuss the sensitivity analysis-based neuro-TF modeling technique. The purpose is to increase the model accuracy by utilizing EM sensitivity information and to speed up the model development process by reducing the number of training data required for developing the model. After the modeling process, the trained model can be used to provide accurate and fast prediction of the EM responses with respect to the geometrical variables and can be subsequently used in the high-level circuit and system design.

The ability to model the suspended sediment flux (SSflux) and associated water flow from terrain affected by selective logging is important to the establishment of credible measures to improve the ecological sustainability of forestry practices. Recent appreciation of the impact of parameter uncertainty on the statistical credibility of complex models with little internal state validation supports the use of more parsimonious approaches such as data-based mechanistic (DBM) modelling. The DBM approach combines physically based understanding with model structure identification based on transfer functions and objective statistical inference. Within this study, these approaches have been newly applied to rainfall–SSflux response. The dynamics of the sediment system, together with the rainfall–river flow system, were monitored at five nested contributory areas within a 44 ha headwater region in Malaysian Borneo. The data series analysed covered a whole year at a 5 min resolution, and were collected during a period some five to six years after selective timber harvesting had ceased. Physically based and statistical interpretation of these data was possible given the wealth of contemporary and past hydrogeomorphic data collected within the same region.

The results indicated that parsimonious, three-parameter models of rainfall–river flow and rainfall-SSflux for the whole catchment describe 80 and 90% of the variance, respectively, and that parameter changes between scales could be explained in physically meaningful terms. Indeed, the modelling indicated some new conceptual descriptions of the river flow and sediment-generation systems. An extreme rainstorm having a 10–20 year return period was present within the data series and was shown to generate new mass movements along the forestry roads that had a differential impact on the monitored contributory areas. Critically, this spatially discrete behaviour was captured by the modelling and may indicate the potential use of DBM approaches for (i) predicting the differential effect of alternative forestry practices, (ii) estimating uncertainty in the behaviour of ungauged areas and (iii) forecasting river flow and SSflux in terrain with temporal changes in rainfall regime and forestry impacts.