Prediction of the undrained shear strength of remolded soil with non-linear regression,fuzzy logic,and artificial neural network

This study aims to predict the undrained shear strength of remolded soil samples using non-linear regression analyses,fuzzy logic,and artificial neural network modeling.A total of 1306 undrained shear strength results from 230 different remolded soil test settings reported in 21 publications were collected,utilizing six different measurement devices.Although water content,plastic limit,and liquid limit were used as input parameters for fuzzy logic and artificial neural network modeling,liquidity index or water content ratio was considered as an input parameter for non-linear regression analyses.In non-linear regression analyses,12 different regression equations were derived for the prediction of undrained shear strength of remolded soil.Feed-Forward backpropagation and the TANSIG transfer function were used for artificial neural network modeling,while the Mamdani inference system was preferred with trapezoidal and triangular membership functions for fuzzy logic modeling.The experimental results of 914 tests were used for training of the artificial neural network models,196 for validation and 196 for testing.It was observed that the accuracy of the artificial neural network and fuzzy logic modeling was higher than that of the non-linear regression analyses.Furthermore,a simple and reliable regression equation was proposed for assessments of undrained shear strength values with higher coefficients of determination.

Nonlinear Auto-Companding Method for Behavioral Modeling of Switched-Current Circuits

A wavelet collocation method with nonlinear auto companding is proposed for behavioral modeling of switched current circuits.The companding function is automatically constructed according to the initial error distribution obtained through approximating the input output function of the SI circuit by conventional wavelet collocation method.In practical applications,the proposed method is a general purpose approach,by which both the small signal effect and the large signal effect are modeled in a unified formulation to ease the process of modeling and simulation.Compared with the published modeling approaches,the proposed nonlinear auto companding method works more efficiently not only in controlling the error distribution but also in reducing the modeling errors.To demonstrate the promising features of the proposed method,several SI circuits are employed as examples to be modeled and simulated.

Companding语音数据压缩算法分析及改进

本文介绍了用于声音文件压缩 /解压缩的 Companding算法及改进。对该算法的思路 ,算法的具体实现过程 ,算法中的几个重要模块的功能及具体流程均作了详细说明 ,并总结了算法的特点。

Closed-Form and Analytical BER Expression for OFDM System with μ-Law Companding Operation

The μ-law companding function has been applied widely in orthogonal frequency division multiplexing (OFDM) to reduce the peak-to-average power ratio (PAPR). However, nonlinear distortion caused by the μ-law companding function is considered a key impairment in OFDM communication systems. Few studies have addressed theoretical nonlinear distortion caused by μ-law companding function for OFDM systems. In this paper, we derive a closed-form expression of signal distortion as well as the closed-form bit error rate (BER) of OFDM system caused by the μ-law companding function. Based on the theoretical signal distortion and BER expression, the theoretical BER value and signal distortion value can also be calculated, which can guide us to choose appropriate μ value for different BER condition and bit-to-noise (Eb/N0) condition efficiently. Then the PAPR performance can also be predicted. The results show good agreement on the Monte-Carlo simulation results and the obtained theoretical BER results. Furthermore, based on theoretical signal distortion and theoretical BER expression, the figure of the relationship among BER value, Eb/N0 and μ is also given. Based on this figure, we can find the appropriate μ law for different BER and Eb/N0 condition. And then the PAPR performance can also be predicted.

Novel PAPR Reduction Scheme Based on Continuous Nonlinear Piecewise Companding Transform for OFDM Systems

In this paper,a novel efficient continuous piecewise nonlinear companding scheme is proposed for reducing the peak-to-average power ratio(PAPR)of orthogonal frequency division multiplexing(OFDM)systems.In the proposed companding transform,signal samples with large amplitudes is clipped for peak power reduction,and the signal samples with medium amplitudes is nonlinear transformed with power compensation.While the signal samples with small amplitudes remain unchanged.The whole companding function is continuous and smooth in the range of positive numbers,which is beneficial for guaranteeing the bit error rate(BER)and power spectral density(PSD)performance.This scheme can achieve a significant reduction in PAPR.And at the same time,it cause little increment in BER and PSD performance.Simulation results indicate the superiority of the proposed scheme over existing companding schemes.

A New Nonlinear Companding Algorithm Based on Tangent Linearization Processing for PAPR Reduction in OFDM Systems

In this paper, a novel nonlinear companding transform(NCT) is proposed to reduce the Peak-to-Average Power Ratio(PAPR) of orthogonal frequency division multiplexing(OFDM) signals. The companding function is designed based on continuously differentiable reshaping of the probability density function(PDF) of signal amplitudes. The original PDF is cut off for PAPR reduction, and lower and medium segments of original PDF are scaled and linearized respectively, for maintaining power and cumulative distribution constraints. The linearized segment is set to be the tangent of the scaled version at the inflexion point, so as to reduce the out-ofband(OOB) radiation as much as possible. Parameters of the proposed scheme are solved under joint constraints of constant power and unity cumulative distribution. A new receiving method is also proposed to improve the bit error rate(BER) performance of OFDM systems. Simulation results indicate the proposed scheme can achieve better OOB radiation and BER performance at same PAPR levels, compared with existing similar companding algorithms.

Combined DCT and Companding for PAPR Reduction in OFDM Signals

The high peak-to-average (PAPR) is one of the serious problems in the application of OFDM technology. The com-panding transform approach is a very attractive technique to reduce PAPR, but large PAPR reduction leads to a high bit error rate (BER) by the available companding transform techniques. In this paper, a joint reduction in PAPR of the OFDM signals based on combining the discrete cosine transform (DCT) with companding is proposed. In the first step of the proposed scheme, the data are transformed by a DCT into new modified data. In the second step, the proposed scheme utilizes the companding technique to further reduce the PAPR of the OFDM signal. The performance of the PAPR is evaluated using a computer simulation. The simulation results indicate that the proposed scheme may obtain about 1 dB PAPR reduction compared with the conventional companding algorithm.

Microsphere femtosecond laser sub-50 nm structuring in far field via non-linear absorption

Creation of arbitrary features with high resolution is critically important in the fabrication of nano-optoelectronic devices.Here,sub-50 nm surface structuring is achieved directly on Sb2S3 thin films via microsphere femtosecond laser irradi-ation in far field.By varying laser fluence and scanning speed,nano-feature sizes can be flexibly tuned.Such small patterns are attributed to the co-effect of microsphere focusing,two-photons absorption,top threshold effect,and high-repetition-rate femtosecond laser-induced incubation effect.The minimum feature size can be reduced down to~30 nm(λ/26)by manipulating film thickness.The fitting analysis between the ablation width and depth predicts that the feature size can be down to~15 nm at the film thickness of~10 nm.A nano-grating is fabricated,which demonstrates desirable beam diffraction performance.This nano-scale resolution would be highly attractive for next-generation laser nano-lithography in far field and in ambient air.

Stochastic Models to Mitigate Sparse Sensor Attacks in Continuous-Time Non-Linear Cyber-Physical Systems

Cyber-Physical Systems are very vulnerable to sparse sensor attacks.But current protection mechanisms employ linear and deterministic models which cannot detect attacks precisely.Therefore,in this paper,we propose a new non-linear generalized model to describe Cyber-Physical Systems.This model includes unknown multivariable discrete and continuous-time functions and different multiplicative noises to represent the evolution of physical processes and randomeffects in the physical and computationalworlds.Besides,the digitalization stage in hardware devices is represented too.Attackers and most critical sparse sensor attacks are described through a stochastic process.The reconstruction and protectionmechanisms are based on aweighted stochasticmodel.Error probability in data samples is estimated through different indicators commonly employed in non-linear dynamics(such as the Fourier transform,first-return maps,or the probability density function).A decision algorithm calculates the final reconstructed value considering the previous error probability.An experimental validation based on simulation tools and real deployments is also carried out.Both,the new technology performance and scalability are studied.Results prove that the proposed solution protects Cyber-Physical Systems against up to 92%of attacks and perturbations,with a computational delay below 2.5 s.The proposed model shows a linear complexity,as recursive or iterative structures are not employed,just algebraic and probabilistic functions.In conclusion,the new model and reconstructionmechanism can protect successfully Cyber-Physical Systems against sparse sensor attacks,even in dense or pervasive deployments and scenarios.

The Existence of Meromorphic Solutions to Non-Linear Delay Differential Equations

In this paper, we study the existence of the transcendental meromorphic solution of the delay differential equations , where a(z) is a rational function, and are polynomials in w(z) with rational coefficients, k is a positive integer. Under the assumption when above equations own transcendental meromorphic solutions with minimal hyper-type, we derive the concrete conditions on the degree of the right side of them. Specially, when w(z)=0 is a root of , its multiplicity is at most k. Some examples are given here to illustrate that our results are accurate.

The ridgelet transform with non-linear threshold for seismic noise attenuation in marine carbonates

Wavelet transforms have been successfully used in seismic data processing with their ability for local time - frequency analysis. However, identification of directionality is limited because wavelet transform coefficients reveal only three spatial orientations. Whereas the ridgelet transform has a superior capability for direction detection and the ability to process signals with linearly changing characteristics. In this paper, we present the issue of low signal-to-noise ratio （SNR） seismic data processing based on the ridgelet transform. Actual seismic data with low SNR from south China has been processed using ridgelet transforms to improve the SNR and the continuity of seismic events. The results show that the ridgelet transform is better than the wavelet transform for these tasks.

Microstructure evolution of Al-Zn-Mg-Cu alloy during non-linear cooling process

The microstructure evolution and properties of an Al-Zn-Mg-Cu alloy were investigated under different non-linear cooling processes from the solution temperature, combined with in-situ electrical resistivity measurements, selected area diffraction patterns （SADPs）, transmission electron microscopy （TEM）, and tensile tests. The relative resistivity was calculated to characterize the phase transformation of the experimental alloy during different cooling processes. The results show that at high temperatures, the microstructure evolutions change from the directional diffusion of Zn and Mg atoms to the precipitation of S phase, depending on the cooling rate. At medium temperatures, q phase nucleates on A13Zr dispersoids and grain boundaries under fast cooling conditions, while S phase precipitates under the slow cooling conditions. The strength and ductility of the aged alloy suffer a significant deterioration due to the heterogeneous precipitation in medium temperature range. At low temperatures, homogeneously nucleated GP zone, η′ and η phases precipitate.

Numerical Analysis of the Magnetic Dipole Effect on a Radiative Ferromagnetic Liquid Flowing over a Porous Stretched Sheet

The effects of a magnetic dipole on a nonlinear thermally radiative ferromagnetic liquidflowing over a stretched surface in the presence of Brownian motion and thermophoresis are investigated.By means of a similarity transformation,ordinary differential equations are derived and solved afterwards using a numerical(the BVP4C)method.The impact of various parameters,namely the velocity,temperature,concentration,is presented graphically.It is shown that the nanoparticles properties,in conjunction with the magnetic dipole effect,can increase the thermal conductivity of the engineered nanofluid and,consequently,the heat transfer.Comparison with earlier studies indicates high accuracy and effectiveness of the numerical approach.An increase in the Brow-nian motion parameter and thermophoresis parameter enhances the concentration and the related boundary layer.The skin-friction rises when the viscosity parameter is increased.A larger value of the ferromagnetic para-meter results in a higher skin-friction and,vice versa,in a smaller Nusselt number.

基于预编码与压扩技术VLC系统研究

针对非对称削波光正交频分复用系统应用在可见光通信中峰值平均功率比过高的问题,在研究编码技术和失真技术的基础上,提出了一种Hadamard编码与归一化μ律压扩联合方案来降低峰值平均功率比。联合方案仿真结果表明,与Hadamard编码技术相比,在峰值平均功率比抑制性能方面提升了5.8 dB;另一方面,与归一化μ律压扩技术相比,在误码率上仍然取得了更好的性能,优化了2 dB。

Design and characterization of a multi-ring nested CMUT array for hydrophone

This paper presents the design,fabrication,packaging,and characterization of a high-performance CMUT array.The array,which features rectangular cells fabricated using a sacrificial release process,achieves a receiving sensitivity of-231.44 d B(re:1 V/μPa)with a 40 d B gain.Notably,the CMUT array exhibits a minimal sensitivity variation of just 0.87 d B across a temperature range of 0 to 60°C.Furthermore,the output voltage non-linearity at 1 k Hz is approximately 0.44%.These test results demonstrate that the reception performance of the 67-element CMUT array is superior to that of commercial transducers.The high performance and compact design of this CMUT array underscore its significant commercial potential for hydrophone applications.

Assessing the effects of model parameter assumptions on surface-wave inversion results

Surface-wave inversion is a powerful tool for revealing the Earth's internal structure.However,aside from shear-wave velocity(v_(S)),other parameters can influence the inversion outcomes,yet these have not been systematically discussed.This study investigates the influence of various parameter assumptions on the results of surface-wave inversion,including the compressional and shear velocity ratio(v_(P)/v_(S)),shear-wave attenuation(Q_(S)),density(ρ),Moho interface,and sedimentary layer.We constructed synthetic models to generate dispersion data and compared the obtained results with different parameter assumptions with those of the true model.The results indicate that the v_(P)/v_(S) ratio,Q_(S),and density(ρ) have minimal effects on absolute velocity values and perturbation patterns in the inversion.Conversely,assumptions about the Moho interface and sedimentary layer significantly influenced absolute velocity values and perturbation patterns.Introducing an erroneous Mohointerface depth in the initial model of the inversion significantly affected the v_(S) model near that depth,while using a smooth initial model results in relatively minor deviations.The assumption on the sedimentary layer not only affects shallow structure results but also impacts the result at greater depths.Non-linear inversion methods outperform linear inversion methods,particularly for the assumptions of the Moho interface and sedimentary layer.Joint inversion with other data types,such as receiver functions or Rayleigh wave ellipticity,and using data from a broader period range or higher-mode surface waves,can mitigate these deviations.Furthermore,incorporating more accurate prior information can improve inversion results.

Effects of shore-normal coastal structure on medium-to long-term embayed shoreline evolution

Based on high-tide shoreline data extracted from 87 Landsat satellite images from 1986 to 2019 as well as using the linear regression rate and performing a Mann-Kendall(M–K)trend test,this study analyzes the linear characteristics and nonlinear behavior of the medium-to long-term shoreline evolution of Jinghai Bay,eastern Guangdong Province.In particular,shoreline rotation caused by a shore-normal coastal structure is emphasized.The results show that the overall shoreline evolution over the past 30 years is characterized by erosion on the southwest beach,with an average erosion rate of 3.1 m/a,and significant accretion on the northeast beach,with an average accretion rate of 5.6 m/a.Results of the M–K trend test indicate that significant shoreline changes occurred in early 2006,which can be attributed to shore-normal engineering.Prior to that engineering construction,the shorelines are slightly eroded,where the average erosion rate is 0.7 m/a.However,after shore-normal engineering is performed,the shoreline is characterized by significant erosion(3.2 m/a)on the southwest beach and significant accretion(8.5 m/a)on the northeast beach,thus indicating that the shore-normal engineering at the updrift headland contributes to clockwise shoreline rotation.Further analysis shows that the clockwise shoreline rotation is promoted not only by longshore sediment transport processes from southwest to northeast,but also by cross-shore sediment transport processes.These findings are crucial for beach erosion risk management,coastal disaster zoning,regional sediment budget assessments,and further observations and predictions of beach morphodynamics.

Influence of Confined Concrete Models on the Seismic Response of RC Frames

In this study, the influence of confined concrete models on the response of reinforced concrete structures is investigatedat member and global system levels. The commonly encountered concrete models such as Modified Kent-Park, Saatçioğlu-Razvi, and Mander are considered. Two moment-resisting frames designed according to thepre-modern code are taken into consideration to reflect the example of an RC moment-resisting frame in thecurrent building stock. The building is in an earthquake-prone zone located on Z3 Soil Type. The inelasticresponse of the building frame is modelled by considering the plastic hinges formed on each beam and columnelement for different concrete classes and stirrups spacings. The models are subjected to non-linear static analyses.The differences between confined concrete models are comparatively investigated at both reinforced concretemember and system levels. Based on the results of the comparative analysis, it is revealed that the column behaviouris mostly influenced by the choice of model, due to axial loads and confinement effects, while the beams areless affected, and also it is observed that the differences exhibited in the moment-curvature response of columncross-sections do not significantly affect the overall behaviour of the global system. This highlights the critical roleof model selection relative to the concrete strength and stirrup spacing of the member.

Optimized CUDA Implementation to Improve the Performance of Bundle Adjustment Algorithm on GPUs

The 3D reconstruction pipeline uses the Bundle Adjustment algorithm to refine the camera and point parameters. The Bundle Adjustment algorithm is a compute-intensive algorithm, and many researchers have improved its performance by implementing the algorithm on GPUs. In the previous research work, “Improving Accuracy and Computational Burden of Bundle Adjustment Algorithm using GPUs,” the authors demonstrated first the Bundle Adjustment algorithmic performance improvement by reducing the mean square error using an additional radial distorting parameter and explicitly computed analytical derivatives and reducing the computational burden of the Bundle Adjustment algorithm using GPUs. The naïve implementation of the CUDA code, a speedup of 10× for the largest dataset of 13,678 cameras, 4,455,747 points, and 28,975,571 projections was achieved. In this paper, we present the optimization of the Bundle Adjustment algorithm CUDA code on GPUs to achieve higher speedup. We propose a new data memory layout for the parameters in the Bundle Adjustment algorithm, resulting in contiguous memory access. We demonstrate that it improves the memory throughput on the GPUs, thereby improving the overall performance. We also demonstrate an increase in the computational throughput of the algorithm by optimizing the CUDA kernels to utilize the GPU resources effectively. A comparative performance study of explicitly computing an algorithm parameter versus using the Jacobians instead is presented. In the previous work, the Bundle Adjustment algorithm failed to converge for certain datasets due to several block matrices of the cameras in the augmented normal equation, resulting in rank-deficient matrices. In this work, we identify the cameras that cause rank-deficient matrices and preprocess the datasets to ensure the convergence of the BA algorithm. Our optimized CUDA implementation achieves convergence of the Bundle Adjustment algorithm in around 22 seconds for the largest dataset compared to 654 seconds for the sequential implementation, resulting in a speedup of 30×. Our optimized CUDA implementation presented in this paper has achieved a 3× speedup for the largest dataset compared to the previous naïve CUDA implementation.

The Media Logic and Cultural Impact of WeChat

Through its media logic, which is defined by programmability, pervasiveness, connectivity, and datafication, WeChat establishes a non-linear, interactive, and user-dominated media environment. This media logic enhances the influence of each user within WeChat’s narrative landscape and revolutionises traditional media narration methods by enabling them to generate and distribute content. In such an environment, users are able to edit, receive, and send information without constraints of time or distance, which enables delayed interactions that broaden the potential for human communication and dissemination. Additionally, WeChat partially replaces social behaviours and institutions, thereby modifying their original structures and characteristics. As individuals become more accustomed to this media environment, they progressively adjust to the forms that are appropriate for media representation on WeChat, thereby completing the mediatization of culture and society. In this process, individuals are becoming more dependent on media and media logic, with WeChat’s influence permeating social and cultural activities through its media logic. This interaction has a substantial impact on society and culture, thereby aiding in their reconstruction.