Spatial correlations in time and frequency domains between chlorophyll-a concentration and environmental factors in the Bohai Sea

Based on the reconstructed MODIS data and ECMWF reanalysis data from 2003 to 2021,spatial correlations between chlorophyll a(Chl a)and sea surface temperature(SST),photosynthetically available radiation(PAR),aerosol optical thickness(AOT),and wind speed(WS)in the Bohai Sea were analyzed from the perspective of time domain and frequency domain.Results indicate that the frequency domain analysis was more conducive to revealing the correlations between Chl a and environmental factors.The spatial pattern of time-domain correlations was similar to the isobaths of the Bohai Sea,which was positive in shallow waters and negative in deep waters for SST,PAR,and AOT,and was reversed for WS.Frequency-domain correlations were obtained by performing Fourier Transform and were higher than correlations in time domain.The spatial distributions indicated that the effects of SST and PAR on Chl a were greater than AOT and WS in the Bohai Sea.Additionally,cross-spectrum analysis was applied to explore the response relationships.A depth-dependent pattern was shown in correlations and time lags,indicating that the influential mechanism of environmental factors on Chl-a concentration is related to seawater depth.

Seismic evaluation of frequency influence and resonant behavior for lead rubber bearing isolated rigid rectangular liquid tanks

The seismic behavior of a partially filled rigid rectangular liquid tank is investigated under short-and longduration ground motions.A finite element model is developed to analyze the liquid domain by using four-noded quadrilateral elements.The competency of the model is verified with the available results.Parametric studies are conducted for the dynamic parameters of the base-isolated tank,using a lead rubber bearing to evaluate the optimum damping and time period of the isolator.The application of base isolation has reduced the total and impulsive hydrodynamic components of pressure by 80 to 90 percent,and base shear by 15 to 95 percent,depending upon the frequency content and duration of the considered earthquakes.The sloshing amplitude of the base-isolated tank is reduced by 18 to 94 percent for most of the short-duration earthquakes,while it is increased by 17 to 60 percent for the majority of the long-duration earthquakes.Furthermore,resonance studies are carried out through a long-duration harmonic excitation to obtain the dynamic behavior of non-isolated and isolated tanks,using a nonlinear sloshing model.The seismic responses of the base-isolated tank are obtained as higher when the excitation frequency matches the fundamental sloshing frequency rather than the isolator frequency.

Equalization Reconstruction Algorithm Based on Reference Signal Frequency Domain Block Joint for DTMB-Based Passive Radar

Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small(LSS)target detection,a novel frequency domain block joint equalization algorithm is presented in this article.From the DTMB signal frame structure and channel multipath transmission characteristics,this article adopts a unconventional approach where the delay and frame structure of each DTMB signal frame are reconfigured to create a circular convolution block,facilitating concurrent fast Fourier transform(FFT)calculations.Following equalization,an inverse fast Fourier transform(IFFT)-based joint output and subsequent data reordering are executed to finalize the equalization process for the DTMB signal.Simulation and measured data confirm that this algorithm outperforms conventional techniques by reducing signal errors rate and enhancing real-time processing.In passive radar LSS detection,it effectively suppresses multipath and noise through frequency domain equalization,reducing false alarms and improving the capabilities of weak target detection.

Effects of sampling frequency on node mobility prediction in dynamic networks: A spectral view

The field of mobility prediction has been widely investigated in the recent past,especially the reduction of the coverage radius of cellular networks,which led to an increase in hand-over events.Changing the cell coverage very frequently,for example,may lead to service disruptions if a predictive approach is not deployed in the system.Although several works examined mobility prediction in the new-generation mobile networks,all of these studies focused on studying the time features of mobility traces,and the spectral content of historical mobility patterns was not considered for prediction purposes as yet.In the present study,we propose a new approach to mobility prediction by analyzing the effects of a proper mobility sampling frequency.The proposed approach lies in the mobility analysis in the frequency domain,to extract hidden features of the mobility process.Thus,we proposed a new methodology to determine the spectral content of mobility traces(considered as signals)and,thus,the appropriate sampling frequency,which can provide numerous advantages.We considered several types of mobility models(e.g.pedestrian,urban,and vehicular),containing important details in the time and frequency domains.Several simulation campaigns were performed to observe and analyze the characteristics of mobility from real traces and to evaluate the effects of sampling frequency on the spectral content.

Exploring the asymmetric effect of COVID‑19 pandemic news on the cryptocurrency market:evidence from nonlinear autoregressive distributed lag approach and frequency domain causality

This paper explores the asymmetric effect of COVID-19 pandemic news,as measured by the coronavirus indices(Panic,Hype,Fake News,Sentiment,Infodemic,and Media Coverage),on the cryptocurrency market.Using daily data from January 2020 to September 2021 and the exponential generalized autoregressive conditional heter-oskedasticity model,the results revealed that both adverse and optimistic news had the same effect on Bitcoin returns,indicating fear of missing out behavior does not prevail.Furthermore,when the nonlinear autoregressive distributed lag model is esti-mated,both positive and negative shocks in pandemic indices promote Bitcoin’s daily changes;thus,Bitcoin is resistant to the SARS-CoV-2 pandemic crisis and may serve as a hedge during market turmoil.The analysis of frequency domain causality supports a unidirectional causality running from the Coronavirus Fake News Index and Sentiment Index to Bitcoin returns,whereas daily fluctuations in the Bitcoin price Granger affect the Coronavirus Panic Index and the Hype Index.These findings may have significant policy implications for investors and governments because they highlight the impor-tance of news during turbulent times.The empirical results indicate that pandemic news could significantly influence Bitcoin’s price.

Frequency responses of immersing tunnel element under wave actions

The immersion of large-scale tunnel elements is one of the most important working procedures in the construction of an underwater immersed tunnel. To investigate the dynamic characteristics of tunnel element in the process of immersion, based on the twin-barge immersing operation method, the frequency-domain analysis of the tunnel element motions under wave actions was made. The linear wave diffraction theory and the three-dimensional source distribution method were applied to calculate the wave loads and motion responses of the tunnel element under different incident wave conditions. In the study, movement of the two barges in the water was assumed to be small and was ignored. Cable tension was computed by the static method. On the basis of the above theories, a computer program was made, and two cases were taken to check the validity of the program. The results showed that wave loads acting on the immersed tunnel element are relatively large near the water surface, and they decrease with the increase of immersing depth of the tunnel element. Wave loads first increase, then decrease, with the increase of wave period. The motion responses of the tunnel element are also generally large near the water surface and decrease as the immersing depth increases.

Multi-scale seismic full waveform inversion in the frequency-domain with a multi-grid method

Although full waveform inversion in the frequency domain can overcome the local minima problem in the time direction, such problem still exists in the space direction because of the media subsurface complexity. Based on the optimal steep descent methods, we present an algorithm which combines the preconditioned bi-conjugated gradient stable method and the multi-grid method to compute the wave propagation and the gradient space. The multiple scale prosperity of the waveform inversion and the multi-grid method can overcome the inverse problems local minima defect and accelerate convergence. The local inhomogeneous three-hole model simulated results and the Marmousi model certify the algorithm effectiveness.

The simulation of far-field wavelets using frequency- domain air-gun array near-field wavelets

Air-gun arrays are used in marine-seismic exploration. Far-field wavelets in subsurface media represent the stacking of single air-gun ideal wavelets. We derived single air-gun ideal wavelets using near-field wavelets recorded from near-field geophones and then synthesized them into far-field wavelets. This is critical for processing wavelets in marine- seismic exploration. For this purpose, several algorithms are currently used to decompose and synthesize wavelets in the time domain. If the traveltime of single air-gun wavelets is not an integral multiple of the sampling interval, the complex and error-prone resampling of the seismic signals using the time-domain method is necessary. Based on the relation between the frequency-domain phase and the time-domain time delay, we propose a method that first transforms the real near-field wavelet to the frequency domain via Fourier transforms; then, it decomposes it and composes the wavelet spectrum in the frequency domain, and then back transforms it to the time domain. Thus, the resampling problem is avoided and single air-gun wavelets and far-field wavelets can be reliably derived. The effect of ghost reflections is also considered, while decomposing the wavelet and removing the ghost reflections. Modeling and real data processing were used to demonstrate the feasibility of the proposed method.

Image Fusion Using Wavelet Transformation and XGboost Algorithm

Recently,there have been several uses for digital image processing.Image fusion has become a prominent application in the domain of imaging processing.To create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same item.Image fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual perception.Image fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on application.The research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet transform.Image fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient manner.More precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain characteristics.To tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is proposed.The use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter choice.The simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original images.This study enhances the performance of the eXtreme Gradient Boosting(XGBoost)algorithm in detecting brain malignancies with greater precision through the integration of computational image analysis and feature selection.The performance of images is improved by segmenting them employing the K-Means algorithm.The segmentation method aids in identifying specific regions of interest,using Particle Swarm Optimization(PCA)for trait selection and XGBoost for data classification.Extensive trials confirm the model’s exceptional visual performance,achieving an accuracy of up to 97.067%and providing good objective indicators.

Fast measurement and prediction method for electromagnetic susceptibility of receiver

Aiming at evaluating and predicting rapidly and accurately a high sensitivity receiver’s adaptability in complex electromagnetic environments,a novel testing and prediction method based on dual-channel multi-frequency is proposed to improve the traditional two-tone test.Firstly,two signal generators are used to generate signals at the radio frequency(RF)by frequency scanning,and then a rapid measurement at the intermediate frequency(IF)output port is carried out to obtain a huge amount of sample data for the subsequent analysis.Secondly,the IF output response data are modeled and analyzed to construct the linear and nonlinear response constraint equations in the frequency domain and prediction models in the power domain,which provide the theoretical criteria for interpreting and predicting electromagnetic susceptibility(EMS)of the receiver.An experiment performed on a radar receiver confirms the reliability of the method proposed in this paper.It shows that the interference of each harmonic frequency and each order to the receiver can be identified and predicted with the sensitivity model.Based on this,fast and comprehensive evaluation and prediction of the receiver’s EMS in complex environment can be efficiently realized.

预测规则波浪中船舶运动和载荷的频域三维计算机程序

The development of an in-house computer program for determining the motions and loads of advancing ships through sea waves in the frequency domain,is described in this paper.The code is based on the potential flow formulation and originates from a double-body code enhanced with the regular part of the velocity potential computed using the pulsing source Green function.The code is fully developed in C++language with extensive use of the object-oriented paradigm.The code is capable of estimating the excitation and inertial radiation loads or arbitrary incoming wave frequencies and incidence angles.The hydrodynamic responses such as hydrodynamic coefficients,ship motions,the vertical shear force and the vertical bending moment are estimated.A benchmark container ship and an LNG carrier are selected for testing and validating the computer code.The obtained results are compared with the available experimental data which demonstrate the acceptable compliance for the zero speed whereas there are some discrepancies over the range of frequencies for the advancing ship in different heading angles.

HF-VHF dual-channel multifunctional radio astronomy terminal system

The high frequency-very high frequency(HF-VHF)frequency band is of significant importance in astronomical observations,with applications studying various phenomena such as space weather,solar radio emissions,planetary eruptions in the solar system,pulsars,transient sources,and reionization of the early universe.This article introduces the HF-VHF frequency band multifunctional radio astronomical terminal system based on a dual-channel high-speed acquisition board with a frequency observation range of 1-250 MHz and a sampling rate of 500 Msps(Mega samples per second).The maximum quantization bit of the system is 14 bits,with a maximum time resolution of 0.1 s and a maximum spectral resolution of 16 kHz.The system combines spectral analysis of solar radio signals and recording of time-domain data of signals interfering with long baselines,and adopts a server-client separation mode to allow remote operation with separate permissions.It is used in the China-Malaysia joint astronomy project,which can carry out single-site observation of solar radio signals as well as interferometric observation of signals from multiple sites.

On Normalized Least Mean Square Based Interference Cancellation Algorithm for Integrated Sensing and Communication Systems

Integrated sensing and communication(ISAC)technology is a promising candidate for next-generation communication systems.However,severe co-site interference in existing ISAC systems limits the communication and sensing performance,posing significant challenges for ISAC interference management.In this work,we propose a novel interference management scheme based on the normalized least mean square(NLMS)algorithm,which mitigates the impact of co-site interference by reconstructing the interference from the local transmitter and canceling it from the received signal.Simulation results demonstrate that,compared to typical adaptive interference management schemes based on recursive least square(RLS)and stochastic gradient descent(SGD)algorithms,the proposed NLMS algorithm effectively cancels co-site interference and achieves a good balance between computational complexity and convergence performance.

An Improved Frequency Domain Technique for Determining Soil Water Content

For many years a soil water content sensor with low cost, reliability and sufficient accuracy has been desirable. Thus, an improved measurement method based on the frequency domain (FD) principle for determining soil water content was considered. Unlike other measurement principles, a new measurable index, η, which was independent of the output impedance and the amplitude of the oscillator while relying on the electrical impedance of a multi-pin probe, was pro- posed. Moreover, a model for processing the impedance of the multi-pin soil probe was developed, and several important electrical parameters for establishing their operating ranges applicable to this probe were evaluated. In order to confirm the theoretical analysis, an experiment was conducted with a 4-pin probe. Using the developed model, the relationship between the proposed index η and soil volumetric water content was shown to be linear (R2 = 0.9921). Thus, as the measurable index, η seemed satisfactory.

Application of pseudo-random frequency domain electromagnetic method in mining areas with strong interferences

Due to the strong electromagnetic interferences and human interference,traditional electromagnetic methods cannot obtain high quality resistivity data of mineral deposits in Chinese mines.The wide field electromagnetic method(WFEM),in which the pseudo-random signal is taken as the transmitter source,can extract high quality resistivity data in areas with sever interference by only measuring the electric field component.We use the WFEM to extract the resistivity information of the Dongguashan mine in southeast China.Compared with the audio magnetotelluric(AMT)method,and the controlled source audio-frequency magnetotelluric(CSAMT) method,the WFEM can obtain data with higher quality and simpler operations.The inversion results indicate that the WFEM can accurately identify the location of the main ore-body,which can be used for deep mine exploration in areas with strong interference.

Sampled-Data Asynchronous Fuzzy Output Feedback Control for Active Suspension Systems in Restricted Frequency Domain

This paper proposes a novel sampled-data asynchronous fuzzy output feedback control approach for active suspension systems in restricted frequency domain.In order to better investigate uncertain suspension dynamics,the sampleddata Takagi-Sugeno(T-S)fuzzy half-car active suspension(HCAS)system is considered,which is further modelled as a continuous system with an input delay.Firstly,considering that the fuzzy system and the fuzzy controller cannot share the identical premises due to the existence of input delay,a reconstructed method is employed to synchronize the time scales of membership functions between the fuzzy controller and the fuzzy system.Secondly,since external disturbances often belong to a restricted frequency range,a finite frequency control criterion is presented for control synthesis to reduce conservatism.Thirdly,given a full information of state variables is hardly available in practical suspension systems,a two-stage method is proposed to calculate the static output feedback control gains.Moreover,an iterative algorithm is proposed to compute the optimum solution.Finally,numerical simulations verify the effectiveness of the proposed controllers.

Joint AVO inversion in the time and frequency domain with Bayesian interference

Amplitude variations with offset or incident angle （AVO/AVA） inversion are typically combined with statistical methods, such as Bayesian inference or deterministic inversion. We propose a joint elastic inversion method in the time and frequency domain based on Bayesian inversion theory to improve the resolution of the estimated P- and S-wave velocities and density. We initially construct the objective function using Bayesian inference by combining seismic data in the time and frequency domain. We use Cauchy and Gaussian probability distribution density functions to obtain the prior information for the model parameters and the likelihood function, respectively. We estimate the elastic parameters by solving the initial objective function with added model constraints to improve the inversion robustness. The results of the synthetic data suggest that the frequency spectra of the estimated parameters are wider than those obtained with conventional elastic inversion in the time domain. In addition, the proposed inversion approach offers stronger antinoising compared to the inversion approach in the frequency domain. Furthermore, results from synthetic examples with added Gaussian noise demonstrate the robustness of the proposed approach. From the real data, we infer that more model parameter details can be reproduced with the proposed joint elastic inversion.

Acoustic reflection well logging modeling using the frequency-domain finite-element method with a hybrid PML

In this paper, we propose a hybrid PML （H-PML） combining the normal absorption factor of convolutional PML （C-PML） with tangential absorption factor of Mutiaxial PML （M-PML）. The H-PML boundary conditions can better suppress the numerical instability in some extreme models, and the computational speed of finite-element method and the dynamic range are greatly increased using this HPML. We use the finite-element method with a hybrid PML to model the acoustic reflection of the interface when wireline and well logging while drilling （LWD）, in a formation with a reflector outside the borehole. The simulation results suggests that the PS- and SP- reflected waves arrive at the same time when the inclination between the well and the outer interface is zero, and the difference in arrival times increases with increasing dip angle. When there are fractures outside the well, the reflection signal is clearer in the subsequent reflection waves and may be used to identify the fractured zone. The difference between the dominant wavelength and the model scale shows that LWD reflection logging data are of higher resolution and quality than wireline acoustic reflection logging.

An improved Gaussian frequency domain sparse inversion method based on compressed sensing

The traditional compressed sensing method for improving resolution is realized in the frequency domain.This method is aff ected by noise,which limits the signal-to-noise ratio and resolution,resulting in poor inversion.To solve this problem,we improved the objective function that extends the frequency domain to the Gaussian frequency domain having denoising and smoothing characteristics.Moreover,the reconstruction of the sparse refl ection coeffi cient is implemented by the mixed L1_L2 norm algorithm,which converts the L0 norm problem into an L1 norm problem.Additionally,a fast threshold iterative algorithm is introduced to speed up convergence and the conjugate gradient algorithm is used to achieve debiasing for eliminating the threshold constraint and amplitude error.The model test indicates that the proposed method is superior to the conventional OMP and BPDN methods.It not only has better denoising and smoothing eff ects but also improves the recognition accuracy of thin interbeds.The actual data application also shows that the new method can eff ectively expand the seismic frequency band and improve seismic data resolution,so the method is conducive to the identifi cation of thin interbeds for beach-bar sand reservoirs.

High-performance compensation scheme for frequency-dependent IQ imbalances in OFDM transmitter and receiver

An efficient compensation scheme combining a timedomain Gaussian elimination（GE） channel estimator and a frequency-domain GE equalizer is proposed for orthogonal frequency division multiplexing（OFDM） systems with frequencydependent in-phase and quadrature-phase（IQ） imbalances at both transmitter and receiver.Compared with the traditional least square and least mean square compensation schemes,the proposed compensation scheme achieves the same bit error rate as the ideal IQ branches by using only two training OFDM symbols instead of about 20 OFDM symbols.