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This paper employs the local Bayesian likelihood methodology to estimate a medium-scale dynamic stochastic general equilibrium (DSGE) model on different frequencies and uses frequency-domain tools to evaluate the time-varying parameter model and the fixed-parameter model. These techniques yield fresh insights into theoretical and empirical implications conveyed by alternative models beyond what conventional time-domain approaches can offer. We show that parameter estimates are sensitive to frequencies, and goodness-of-fit varies substantially with the frequency bands. Overall, the estimated time-varying parameter model captures the properties of the U.S. data better in the business cycle frequency band, and beyond this band, the fixed-parameter model performs better. Additionally, our study also reveals the importance of structural shocks in improving the fit between models and data. Finally, we utilize the spectral representation of generalized forecast error variance decomposition to investigate the frequency dynamics of volatility connectedness. We find shocks to economic activity have an impact on variables at different frequencies with different strengths, and markets become more connected during crisis periods. Furthermore, this study provides insights into a question policymakers are much concerned with: which shocks are major sources of economic volatilities and which sectors serve as major recipients of shocks?

Moments are widely used in pattern recognition, image processing, computer vision and multiresolution analysis. To clarify and to guide the use of different types of moments, we present in this paper a study on the different moments and compare their behavior. After an introduction to geometric, Legendre, Hermite and Gaussian–Hermite moments and their calculation, we analyze at first their behavior in spatial domain. Our analysis shows orthogonal moment base functions of different orders having different number of zero-crossings and very different shapes, therefore they can better separate image features based on different modes, which is very interesting for pattern analysis and shape classification. Moreover, Gaussian–Hermite moment base functions are much more smoothed, they are thus less sensitive to noise and avoid the artifacts introduced by window function discontinuity. We then analyze the spectral behavior of moments in frequency domain. Theoretical and numerical analyses show that orthogonal Legendre and Gaussian–Hermite moments of different orders separate different frequency bands more effectively. It is also shown that Gaussian–Hermite moments present an approach to construct orthogonal features from the results of wavelet analysis. The orthogonality equivalence theorem is also presented. Our analysis is confirmed by numerical results, which are then reported.

Software maintainability is a very important quality attribute. Its prediction for relational database-driven software applications can help organizations improve the maintainability of these applications. The research presented herein adopts a survey-based approach where a survey was conducted with 40 software professionals aimed at identifying and ranking the important maintainability predictors for relational database-driven software applications. The survey results were analyzed using frequency analysis. The results suggest that maintainability prediction for relational database-driven applications is not the same as that of traditional software applications in terms of the importance of the predictors used for this purpose. The results also provide a baseline for creating maintainability prediction models for relational database-driven software applications.

When the entries of Pascal’s triangle which are congruent to a given nonzero residue modulo a fixed prime are mapped to corresponding locations of the unit square, a fractal-like structure emerges. In a previous publication, Bradley, Khalil, Niemeyer and Ossanna [The box-counting dimension of Pascal’s triangle $r$ mod $p$, Fractals26(5) (2018) 1850071] showed that this mapping yields a nonempty compact set which can be realized as a limit of a sequence of sets representing incrementally refined approximations. Moreover, it was shown therein that for any fixed prime, the sequence converges to the same set, regardless of the nonzero residue or combination of nonzero residues considered. Consequently, the fractal (box-counting) dimension of the limiting set is independent of the residue. To study the relative frequency of various residue classes in the sequence of approximating sets, it would be desirable to have a closed-form formula for the number of entries in the first $p$ rows of Pascal’s triangle which are congruent to a given nonzero residue $r$ modulo the prime $p$. Unfortunately, the numerical evidence presented in this paper supports the contention that there is no such formula. Nevertheless, the evidence indicates that for sufficiently large primes $p$, the number of entries congruent to $rmodp$ for $r=1$, $1<r<p-1$, and $r=p-1$ is well approximated by the respective linear functions $3p$, $p/2$, and $p$. In particular, for large primes $p$ there are approximately six times as many occurrences of the residue $1$ in the first $p$ rows of Pascal’s triangle reduced modulo $p$ than there are of any other residue $r$ in the range $1<r<p-1$, and three times as many as $r=p-1$. On the other hand, if we let the nonnegative integer $k$ vary while keeping the prime $p$ fixed, and look at the relative frequency of various residue classes that occur in the first $p^k$ rows, the seemingly substantial differences in frequency between $r=1$, $1<r<p-1$, and $r=p-1$ when $k=1$ are increasingly dissipated as $k$ grows without bound. We show that in the limit as $k$ tends to infinity, all nonzero residues are equally represented with asymptotic proportion $1/(p-1)$.

This paper describes an innovative technique for the quality control of gear pumps based on the frequency analysis of the oscillations of the discharge pressure using a new mathematical tool called "the spectrum of the power cepstrum." It consists in applying Fourier transform of the pressure data sampled in the time domain three times consecutively. The innovative technique makes it possible to obtain an acceptance mask for a set of gear pumps in the same series, in which the class and entity of a defect can be detected.

In active vibration control study, piezoelectric actuators and sensors are bonded on the surface of a beam. They can change the frequency and modal characteristics of the system. This paper presents an analysis of the frequency response to a rotating piezoelectric smart beam. Hamilton’s principle along with the assumed mode method are employed to derive the governing equations of the first-order approximate coupling model for the piezoelectric smart beam. The coupling is taken into account as the second-order coupling effect of the axial elongation caused by the transverse displacement of the beam. Then, the equations are transformed into a dimensionless form after identifying the necessary parameters. The dimensionless natural frequencies of the piezoelectric smart beam corresponding to the bending and stretching vibrations are obtained through a numerical simulation, with comparison made of those of the beam with no actuator or sensor. Furthermore, the implication is investigated of the structural parameters and bond location on the piezoelectric actuators and sensors. Besides, the common case of a smart beam bonded with multiple pairs of piezoelectric actuators and sensors is studied, and the effects of the first natural frequency and tip deformation are analyzed. The research provides a theoretical reference for the optimization of structural parameters and location of piezoelectric actuators and sensors, thereby preventing the resonance when the excitation frequency is approximately equal to the natural frequency of the beam.

An accurate meshfree formulation with higher order mass matrix is proposed for the structural vibration analysis with particular reference to the 1D rod and 2D membrane problems. Unlike the finite element analysis with an explicit mass matrix, the mass matrix of Galerkin meshfree formulation usually does not have an explicit expression due to the rational nature of meshfree shape functions. In order to develop a meshfree higher order mass matrix, a frequency error measure is derived by using the entries of general symmetric stiffness and mass matrices. The frequency error is then expressed as a series expansion of the nodal distance, in which the coefficients of each term are related to the meshfree stiffness and mass matrices. It is theoretically proved that the constant coefficient in the frequency error vanishes identically provided with the linear completeness condition, which does not rely on any specific form of the shape functions. Furthermore, a meshfree higher order mass matrix is developed through a linear combination of the consistent and lumped mass matrices, in which the optimal mass combination coefficient is attained via eliminating the lower order error terms. In particular, the proposed higher order mass matrix with Galerkin meshfree formulation achieves a fourth-order accuracy when the moving least squares or reproducing kernel (RK) meshfree approximation with linear basis function is employed; nonetheless, the conventional meshfree method only gives a second-order accuracy for the frequency computation. In the multidimensional formulation, the optimal mass combination coefficient is a function of the wave propagation angle so that the proposed accurate meshfree method is applicable to the computation of frequencies associated with any wave propagation direction. The superconvergence of the proposed meshfree higher order mass matrix formulation is validated via numerical examples.

In time series modeling, one problem is to identify a small number of influential factors to explain variations in the variable of interest. With a vast number of possible factors available, suitable features need to be identified to yield multi-factor models with good explanatory power. In this paper, we propose a novel subset selection method which makes use of the properties in the frequency domain environment. The proposed system ensures key patterns in the target variable be sought and suitable factors be selected based on frequency peaks in common. It can perform well even when the number of factors is significantly greater than the sample size. Moreover, a very important feature of the proposed system is the capability of handling factors with different timeframes, which is lacking in existing methods. We demonstrate the system via several examples with dataset from finance, economic, road traffic and air pollution.

To assess the effects of changes in somesthetic plantar information on upright quiet stance, a rotary plantar massage was applied under the feet of healthy subjects for ten minutes. The controlling variable, the centre of pressure (CP) displacements, were recorded, before and after massage, through a force platform and decomposed into two elementary motions: the vertical projection of the centre of gravity (CG_v) and the difference between the latter and the CP (CP-CG_v) along medio-lateral ML and antero-posterior AP directions. These motions were processed through frequency analysis and modelled as fractional Brownian motion. For CP-CG_v motions, the frequency analysis shows that massage under the plantar soles induces a decrease of the amplitudes along the ML direction suggesting reduced overall muscular activity (abductor-adductor muscles of the hip according to Winter et al. [49]). A general trend is that the CG_v amplitudes are also diminished after massage especially in the ML direction, indicating a better distribution of the body weight on the two supports. On the other hand, the effects tend to vanish after about 8 minutes. Conversely, when the massage was given under the toes, no particular effect on any elementary motion was observed, suggesting that the plantar mechanoreceptors under the toes necessitate stronger stimulation to respond significantly and/or that the greater sensitivity obtained was not used by the CNS. Overall, this data emphasises the fact that a recalibration of somesthetic cues may occur when enhanced afferent information is fed to the postural system.

Magnetoencephalographic recordings were evaluated in five different states: normal condition, sweet, bitter, sour, and salt taste. Twenty-eight healthy volunteers, 14 male and 14 female, ranging from 12 to 50 years of age, were included in the study. The results showed that, in the normal condition, as well as in the sweet and the bitter taste, the male volunteers exhibited a higher count of low-frequency than high-frequency channels compared to the femal ones; in the case of the sour taste, there was no clear differentiation between the genders; with the salt taste, the female volunteers exhibited a higher count of low-frequency channels whereas there was no clear differentiation in the number of high frequencies between the gender. A discrimination in the spatial distribution of the frequencies provides novel insights into the identification of gender-related taste sensation.

Magnetoencephalography (MEG) recordings were evaluated for 25 healthy female volunteers, in five different gustatory states: normal, sweet, bitter, sour and salty. The study population was divided in two groups according to age: group A (10–19 years old) and group B (20–30 years old). There was a higher count of low frequencies (2 Hz) and a lower count of high frequencies (7 Hz) with increasing age, in all studied states. We compared each state for the frequencies of 2 Hz and 7 Hz between the two groups. Statistically significant differences were found in the normal and sweet states for the frequencies of 2 Hz and 7 Hz and in the salty taste in the frequency of 7 Hz. We also intra-compared the five states in group A and the five states in group B for the 2 Hz and 7 Hz frequencies. The results were not statistically significant. A differentiation in the distribution of the frequencies with increasing age may provide new insights into the age-dependence of taste quality brain centers.

Many firms are increasingly cooperating in their technological undertakings. They engage in strategic technology partnerships (STP) for technological, commercial, industrial, and financial reasons. STP is deemed imperative for easing access to strands of technologies that are unknown to a company. This frequency analysis on STP is based on systematic literature review (SLR) approach and provides a thorough review of 57 articles published in highly-ranked peer-reviewed journals spanning a 26-year period from 1988 to the beginning of 2014. Research on STP is somewhat fragmented which, renders some of the research studies irreconcilable and impedes a greater understanding and consistency of the discipline. There is still a growing body of literature on the subject matter from various disciplinary perspectives which adopt various theoretical and methodological lenses at diverse levels of analysis. In the current paper, we analyze among other things the various methodological, research and theoretical issues underpinning STP and propose a research agenda. Hence, we contribute to the existing body of knowledge on STP literature by offering a state-of-the-art overview of current research and elaborating on promising areas for further investigation.

A two-parameter model that illustrates the way water contained in a reservoir influences the dynamic response of a dam is presented. The model consists of an incompressible water mass attached in series to a damper. The latter is fixed to the upstream face of the dam. The overall trends of the exact analytical solution are duplicated over the whole frequency range. This approximate model can thus be used directly in a time-domain analysis.

This paper describes a theoretical method for free vibration analysis of two elastic and isotropic cylinders filled with a dense fluid. The free vibration of two cylinders is studied on the basis of the linear three-dimensional elasticity theory. The compressible fluid is assumed to be nonviscous and isotropic which satisfy the acoustic wave equation. In this paper, the coupled dispersion equations of longitudinal, flexural and lobar modes are deduced and analytically solved. The finite element results computed by the Comsol Multiphysics software are compared with the present method for validation and an acceptable match between them was obtained. It is shown that the results from the proposed method are in good agreement with the numerical solutions. With this method, the effects of the cylinder parameters, such as the circumferential wave, the axial wavenumber, the thickness-to-radius and the length-to-radius on the coupled frequencies are investigated.

Low flow analysis provides crucial information for water resources development and environmental flow management. Understanding low flows can also give a rise to long-term environmental, economic and social impact and it plays a major role in the hydrological risk management of the river basin. The low flow regime is significantly effective on water resources management especially for the countries like Turkey where demand for water is increasing. The purpose of this study is therefore to perform low flow analysis by determining low flow characteristics of five gauging stations in Kucuk Menderes River basin in the western part of Turkey. The study uses the frequency analysis of low flows, which is applied on D = 1, 7, 14, 30, 90 and 273-day low flows by considering various probability distribution functions to eventually get low flows at 2, 5, 10, 25, 50 and 100-year return periods. Results show that low flow-duration-frequency curves decrease quite fast towards very low flow values and even to zero, which means the river basin is prone to get dry and face with severe hydrological droughts in the future.

Climate change has been recognized as having a profound impact on hydrologic processes. Consequently, there is an urgent need to assess this impact on the extreme rainfalls (ERs) for hydraulic structure design. The key challenge is how to develop the linkage between global-scale climate change information and the short duration ERs at a given local site of interest. In addition, several existing approaches have been proposed to establish this linkage at “gaged” sites but very few methods are available for linking climate change projections to the ERs at an “ungaged” location where rainfall record is limited or unavailable. Therefore, the main objective of this study is to propose an innovative approach that could be used for constructing reliable IDF relations at an ungaged location in consideration of climate change projection uncertainty given by different climate models. The proposed approach consists of a regional-to-point downscaling to link daily regional rainfalls to daily extreme rainfalls at a given ungaged site and a temporal downscaling using the scale-invariance GEV model to link daily-to-sub-daily extreme rainfall distributions at the same location. Results of an illustrative application using the 25-km regional rainfall data downscaled from 21 global climate model outputs and the observed extreme rainfall data from a network of 84 raingages located in Ontario region (Canada) have indicated the feasibility and accuracy of the proposed method.

The purpose of this paper is to show a gain property of frequency response analysis for a biped based on passive dynamic walking mechanism. The walking method is composed of a cyclic length variation of legs and a body constraint control. Some simulated results show that the walking gain property represents an efficiency in the sense of consumed energy. It was found from the result that walking frequencies only depended on frequencies of the leg length variation, and there is a resonance frequency which can be called a walking resonance frequency. Finally, our biped called Prototype Biped Emu-IV (PBEmu-IV) is introduced, and some experimented results are shown in order to verify the effectiveness of the frequency analysis.

Diseases of the heart have become the Number One cause of death in the industrialized nations of the world. Every heart disease affects the biomechanics of the heart in a direct or indirect way. These effects can primarily be analyzed by the signals of the heart sounds and cardiac murmurs using techniques such as auscultation and phonocardiography. But these methods are very sophisticated and require a high degree of specialization. During the last years electronic stethoscopes and commercial PC techniques have improved essentially so an automatic analysis of heart sound has become a potential supporting tool for physicians in particular as a screening method for heart diseases by the general practitioner. This paper introduces a new automatic system to diagnose heart valve diseases based on time and frequency analyzing methods and feature extraction. It also describes an multivariate approach for an enhanced risk stratification in patients with heart failure considering the time interval between the ECG signal, especially the R-wave, and the first heart sound.

In conclusion we could demonstrate, that analysis of the heart sound is a suitable method to evaluate the state of the heart and to detect changes on the biomechanics at an early stage.

Moments are widely used in pattern recognition, image processing, computer vision and multiresolution analysis. To clarify and to guide the use of different types of moments, we present in this paper a study on the different moments and compare their behavior. After an introduction to geometric, Legendre, Hermite and Gaussian–Hermite moments and their calculation, we analyze at first their behavior in spatial domain. Our analysis shows orthogonal moment base functions of different orders having different number of zero-crossings and very different shapes, therefore they can better separate image features based on different modes, which is very interesting for pattern analysis and shape classification. Moreover, Gaussian–Hermite moment base functions are much more smoothed, they are thus less sensitive to noise and avoid the artifacts introduced by window function discontinuity. We then analyze the spectral behavior of moments in frequency domain. Theoretical and numerical analyses show that orthogonal Legendre and Gaussian–Hermite moments of different orders separate different frequency bands more effectively. It is also shown that Gaussian–Hermite moments present an approach to construct orthogonal features from the results of wavelet analysis. The orthogonality equivalence theorem is also presented. Our analysis is confirmed by numerical results, which are then reported.

This paper describes the development and use of real-time non-invasive Multivariate Analysis tools for the performance monitoring of atmospheric pressure plasma. The MVA tools (acoustic spectrogram analysis, principal component analysis (PCA) and non-parametric cluster analysis (NPCA) are embedded within a LabVIEW software program. The software program is used to probe a parallel-plate atmospheric pressure process system. It is found that the acoustic frequency spectrum distribution provides a signature of the plasma mode of operation. The signatures are modeled as overtones of the fundamental drive frequency and combination signals (intermodulation distortion). Within these spectrums syncopated patterns are observed. The acoustic signatures are correlated with changing electrical parameters. Using appropriate scaling factors, PCA of the current and voltage waveform are used to generate data set clusters that are deterministic of the acoustic signals. Non-parametric cluster analysis is used to identify and classify the modes.