Spectral-based Method Research Articles

Frequency-domain patterns in foot-force line-of-action: an emergent property of standing balance control.

A recent line of work suggests that the net behavior of the foot-ground interaction force provides insight into quiet-standing-balance dynamics and control. Through human-subject experiments, Boehm et al. found that the relative variations of the center of pressure and force orientation emerge as a distinct pattern in the frequency domain, termed the "intersection-point (IP) height." Subsequent empirical and simulation-based studies showed that different control strategies are reflected in the distribution of intersection-point height across frequency. To facilitate understanding of the strengths and limitations of the intersection-point height in describing the dynamics and control of standing, the present work establishes a spectral-based method that also enables derivation of a closed-form estimate of the intersection-point height from any linear model of quiet stance. This new method explained observations from prior work, including how the measure captures aspects of control and physiological noise. The analysis presented herein highlights the utility of the frequency-dependent foot-force dynamics in probing the balance controller and provides a tool for model development and validation to further our understanding of the neuromotor control of natural upright posture in humans.NEW & NOTEWORTHY The present work details a closed-form analytical result that reveals a direct link between frequency-domain patterns in the foot-force line-of-action and the closed-loop frequency response function of human upright stance. The analytical method developed herein dramatically simplifies the identification of the intersection-point-height measure of standing balance, and further demonstrates that the net behavior of the foot-ground interaction force quantifies essential characteristics of the underlying neuromotor control of human quiet standing.

Efficient pure qP-wave modeling and reverse time migration in tilted transversely isotropic media calculated by a finite-difference approach

Subsurface anisotropy is commonly induced by shale layers, aligned cracks, and fine bedding and has a significant impact on seismic wave propagation. Ignoring anisotropic effects during seismic migration degrades image quality. Therefore, we derive a pure qP-wave equation with high accuracy for modeling seismic wave propagation in tilted transversely isotropic (TTI) media. However, the derived pure qP-wave equation requires a computationally expensive spectral-based method for performing numerical simulations. This is unsuitable for large-scale industrial applications, particularly 3D applications. For numerical efficiency, we first decompose the newly derived wave equation into some fractional differential operators and spatial derivatives. The spatial derivatives can be directly solved by conventional finite-difference (FD) approaches. Then, we use an asymptotic approximation to find an equivalent form of fractional differential operators, obtaining scalar operators that we can discretize with the FD method. Numerical tests show that our TTI pure qP-wave equation with an FD discretization can produce accurate and highly efficient wavefield simulations in TTI media. We also use our TTI pure qP-wave equation with an FD discretization as a forward engine to implement TTI reverse time migration (RTM). Synthetic examples and a field data test demonstrate that our TTI RTM can effectively correct the anisotropic effects, providing high-quality imaging results while maintaining good computational efficiency.

Efficient pure qP-wave simulation and reverse time migration imaging for vertical transverse isotropic (VTI) media

ABSTRACT Anisotropic pseudo-acoustic forward modeling and migration imaging are critical for high-precision seismic exploration. However, the wavefields simulated by the traditional coupled anisotropic acoustic wave equation have the problems of shear wave noise and numerical simulation instability for epsilon that is less than delta. Furthermore, although the pure anisotropic acoustic wave equation expressed by the differential operators can solve the aforementioned noise interference and numerical simulation instability issues, its numerical simulation calculation is large, particularly in 3D industrial applications, because it has to be solved by the spectral-based method. In this paper, a pure anisotropic acoustic wave equation in a vertical transverse isotropic (VTI) medium that can be numerically computed using the efficient finite difference method is derived. This equation not only eliminates noise interference and numerical simulation instabilities, but also allows for an efficient wavefield simulation. We also implement reverse time migration (RTM) using the proposed VTI pure anisotropic acoustic wave equation. Two synthetic tests and one field data test are performed to evaluate the accuracy and robustness of the developed VTI RTM. The imaging results show that the proposed VTI RTM can correct the anisotropy effect on seismic wave propagation and improve migration imaging precision.

FAST-NEPAL: Regionally Calibrated Spectral Method for Reinforced Concrete With Masonry Infills

Reinforced concrete (RC) with masonry infill is one of the most common structural typologies in Nepal, especially in the Kathmandu Valley. Masonry infills are typically made of solid clay bricks produced locally in Nepal. This study aims to calibrate the spectral-based analytical method, namely, FAST, for Nepalese RC-infilled buildings. The FAST method has been initially conceived for Southern European RC buildings with hollow clay brick infills. The calibration is achieved by reviewing code prescriptions and construction practices for RC masonry infills in Nepal and updating the FAST method. The variables of FAST method are calibrated using different information sources and a Bayesian updating procedure to consider the global and local material properties for solid clay bricks. The FAST-NEPAL method obtained is then verified, considering a single school design, for which a detailed state-of-the-art vulnerability assessment is available. Being particularly suitable for large-scale assessment, the method is further validated using data from Ward-35 of Kathmandu Metropolitan City (in the vicinity of Tribhuvan International Airport) obtained from photographic documentation included in a geo-referenced database of buildings collected after the 2015 Nepal earthquake and prepared for census purposes. The comparisons show that the FAST-NEPAL method can be conservative relative to the other data sources for vulnerability and is more accurate at capturing low-level damage. This makes the approach suitable for large-scale preliminary assessment of vulnerability for prioritisation purposes.

Detection of apple proliferation disease in Malus × domestica by near infrared reflectance analysis of leaves

In this study near infrared spectroscopical analysis of dried and ground leaves was performed and combined with a multivariate data analysis to distinguish 'Candidatus Phytoplasma mali' infected from non-infected apple trees (Malus × domestica). The bacterium is the causative agent of Apple Proliferation, one of the most threatening diseases in commercial apple growing regions. In a two-year study, leaves were sampled from three apple orchards, at different sampling events throughout the vegetation period. The spectral data were analyzed with a principal component analysis and classification models were developed. The model performance for the differentiation of Apple Proliferation diseased from non-infected trees increased throughout the vegetation period and gained best results in autumn. Even with asymptomatic leaves from infected trees a correct classification was possible indicating that the spectral-based method provides reliable results even if samples without visible symptoms are analyzed. The wavelength regions that contributed to the differentiation of infected and non-infected trees could be mainly assigned to a reduction of carbohydrates and N-containing organic compounds. Wet chemical analyses confirmed that N-containing compounds are reduced in leaves from infected trees. The results of our study provide a valuable indication that spectral analysis is a promising technique for Apple Proliferation detection in future smart farming approaches.

Urban functional zone mapping by integrating high spatial resolution nighttime light and daytime multi-view imagery

Functional zones are the basic units of cities and the mapping work is fundamental to urban management, investigation, and research. The existing urban functional zone (UFZ) mapping methods usually utilize visual features from high spatial resolution optical images, and focus on two-dimensional image features, such as texture and landscape. However, UFZ is a comprehensive concept including geographical, social, and economic aspects. Therefore, it is reasonable to simultaneously take into account the characteristics of both human activities and image visual features for its accurate interpretation. Multi-view optical satellite images can delineate the physical characteristics of a city, i.e., 3D structures; on the other hand, high spatial resolution nighttime light images are important signals of human activities. These two data sources can be complementary in representing urban landscapes. However, to our knowledge, in the current literature, neither multi-view images nor high spatial resolution nighttime light images have been used for UFZ mapping, and it is poorly understood whether their individual or combined use can achieve satisfactory results. Therefore, in this study, a daytime and nighttime data fusion method, that is, the fusion of daytime multi-view optical images (Ziyuan3-01, 2.1 m) and high spatial resolution nighttime light images (Jilin1-07, 0.92 m), was proposed for UFZ mapping. In particular, a building enhanced nighttime light index (BENI) was proposed to improve the ability of the nighttime light images in discriminating between different functional zones. To verify the effectiveness of the proposed method, experiments were conducted in two megacities of China, i.e., Beijing and Wuhan. Our results indicated that: 1) an OA of ~80% was obtained by the spectral based method; 2) the addition of multi-view features led to ~84% OA, an increment of 4% compared with the spectral features; and 3) the inclusion of nighttime features achieved 85–90% OA, which further improved the OA of daytime features by 1–6%. It was also shown that the proposed BENI was superior to the original nighttime light brightness in identifying functional zones. In general, this study verified the effectiveness and complementarity of daytime (including multispectral and multi-view images) and nighttime images in UFZ mapping, and provided new thoughts for day and night data fusion and urban mapping.

A frequency-time domain method for ship fatigue damage assessment

Ships in ocean waves are suffered from cyclic wave loads which can cause fatigue damage to ship structures. Classification societies require owners to carry out fatigue assessment for ship structure for its potential great loss caused by fatigue failure. Currently there are many fatigue assessment methods including simplified method, deterministic method, spectral-based method and time domain method. But none of them predict fatigue life precisely and effectively. Based on linear superposition theory and the assumption that a linear relationship occurred between waves and ship structural response, some scholars proposed the hybrid frequency-time domain method. This method avoids the imprecise narrow band approximation in spectral-based method and adopts rainflow counting instead. However, the hybrid method is not applied extensively on ship fatigue assessment because relevant research is insufficient. In this paper, aiming to validate the hybrid method, a segmented ship model test is carried out, and the short-term fatigue damages of a 4600TEU container forecasted by hybrid method and traditional methods are compared. Results shows that the hybrid method forecasts the closest fatigue damage prediction to time domain analysis and owns enough efficiency. But in some area located at midship, hybrid method may predict lower fatigue damage than time domain method.

Asma Su Stresinin Hiperspektral Analizi

Viticulture is very sensitive to water stress, which is critical and influenced by all environmental factors, relating to the crop quality and productivity of vineyards. In this study, water stress was examined in veraison and harvest stages for nine different species with spectroradiometric measurements. Leaf water potential (LWP) values from field measurements and original spectra-based (OSB) and continuum removed spectra-based (CRSB) curves were analyzed with correlation and regression analysis to find the highest related wavelengths. The analysis was done for both specific dates of field measurements (i.e. 08.08.2012 and 06.09.2012) and also in aggregate i.e. all measured data. The specific date wavelength-based analysis revealed the “red edge region” as a major water stress indicator. The highest correlated wavelength was found to be 684 nm of CRSB curves with R=0.988. For the aggregate wavelength-based water stress analysis, the “violet and green regions” were identified as the best indicators. The highest correlated wavelength was found to be 410 nm of OSB curves with R=0.820. Furthermore, the Analysis of Variance (ANOVA) testing indicates that the results are significant at relatively high confidence levels. The spectral-based method performed in this study provides fast, flexible, and non-destructive water stress measurements of grapevines when compared to classical methods.

A spectral recovery method for Raman spectroscopy utilizing prior datasets.

Spectral-based method has been widely used for the qualitative and quantitative analysis of different substances in various fields. The spectral recovery method is a crucial role in the spectral-based method, which can save the measurement cost and computation time in measuring. In this paper, we introduce a simple and reliable spectral recovery method base on prior datasets, which can tolerate substantial spectral noise. The method has been successfully applied in the quantitative analysis of the pharmaceutical mixture. The SNR of the recovery spectra can be increased by ~100 times.

Structural Performance Analysis of Simple Offshore Platforms under Ice-Vibrations in Bohai Sea

In China, the oil and natural gas resources of Bohai Sea are mainly marginal oil fields. It is necessary to build both ice-resistant and economical offshore platforms. So, several simple offshore oil platforms with a jacket sub-structure or with a single pillar have been deployed. There are very good economic benefits in the manufacture, installation, removal, and other aspects. These platforms were primarily designed to withstand extreme static ice forces. However, sea ice motion can induce significant vibrations for the platforms in the region. The structural ice-resistant performances have not been well developed. In this paper, combined with the field monitored data of some simple platforms in Bohai Sea, ice-induced vibrations are analyzed. The results show that even though these structures may effectively resist extreme static ice forces, the ice-induced acceleration is more significant. Then, spectral-based method is provided to analyze the fatigue life of a real simple platform. Lastly, the ice-resistant strategy is presented, which provides a basis for the design of these platforms in ice zone.

Spectral Representation of Uncertainty in Experimental Vibration Modal Data

It is well known that structures exhibit uncertainty due to various sources, such as manufacturing tolerances and variations in physical properties of individual components. Modeling and accurate representation of these uncertainties are desirable in many practical applications. In this paper, spectral-based method is employed to represent uncertainty in the natural frequencies of fiber-reinforced composite plates. For that, experimental modal analysis using noncontact method employing Laser-Vibrometer is conducted on 100 samples of plates having identical nominal topology. The random frequencies then are represented employing generalized Polynomial Chaos (gPC) expansions having unknown deterministic coefficients. This provides us with major advantage to approximate the random experimental data using closed form functions combining deterministic coefficients and random orthogonal basis. Knowing the orthogonal basis, the statistical moments of the data are used to estimate the unknown coefficients.

Land Cover Classification using Object-Based Image Analysis of SPOT-6 Imagery for Land Cover and Forest Monitoring in Nagan Raya, Aceh – Indonesia

Digital classification technique using Object-Based Image Analysis (OBIA) of SPOT-6 imagery could improve classification accuracy and provide detail type of land cover. This method is better applied for data with higher spatial resolution imagery which has high heterogeneity where the pixel size is smaller the actual size of the objects. The sequence steps were image preprocessing and pansharpening, identify the potential of landcover types using Jeffries-Matusita (JM) feature separability, determine a stratification boundary, and developing the Object-Based Orientation classification using Erdas Imagine Objective. Detail process of OBIA was image pixel segmentation with the parameters were consists of determining the minimum pixel segmentation ratio which was 1000 and applying the single feature probability and NDVI, and determine cue weight. The second segmentation was object vector classification which segmented the vector object using the empirical distribution analysis. The segmentation is based on region growing of the Multi-Bayesian network. The classification result is then assessed by comparing the classification result of Maximum Likelihood (MLC) using confusion matrix. The result shows that object-based classification technique could improve the classification by 83% compared to the MLC with only 67%. The method of segmentation used the stratification zone in order to make an optimum cue weight in detecting the object through texture, size, and shape while also applying the spectral-based method.

RC infilled building performance against the evidence of the 2016 EEFIT Central Italy post-earthquake reconnaissance mission: empirical fragilities and comparison with the FAST method

Damage data on low-to-mid-rise Reinforced Concrete (RC) buildings, collected during the UK Earthquake Engineering Field Investigation Team post-earthquake reconnaissance mission on the August 24 Central Italy earthquake, are employed to derive empirical fragility relationships. Given the small dataset, the new data distributions are used for the Bayesian update of fragility functions derived for the L’Aquila earthquake (same seismic region and similar construction typologies). Other properties such as number of storeys, age of construction and shape in plan of the buildings are also analyzed. This information is employed to assess the ability of the FAST method to predict damage states in non-regular infilled RC buildings for the municipalities of Amatrice, Accumoli, Arquata del Tronto and Norcia, all severely affected by the 2016 Central Italy sequence. FAST is a spectral-based method to derive capacity curves and peak ground acceleration damage state thresholds for buildings. It is a dedicated methodology for regular RC frame buildings with masonry infills, first calibrated on damage data from the 2009 L’Aquila earthquake and applied to the 2011 Lorca (Spain), the 2012 Emilia (Italy) events for damage back-analyses. The new data from the August 2016 Central Italy earthquake provide a test-bed for FAST further employments in case of less homogenous building samples. The application of FAST presented here accounts for different shake-maps produced by both the United States Geological Survey and the Italian National Institute of Geophysics and Volcanology which are significantly different and representative of different refinements of the demand scenario. For the area of Amatrice, where the two shake-maps provide similar estimates and the buildings considered match reasonably well the typology for which FAST is calibrated, the comparison between damage level observed and as provided by FAST is very satisfactory. For other structural typologies like RC industrial structures and dwellings with non-hollow-clay-bricks as infills, FAST needs further calibration.

A spectral-based numerical method for Kolmogorov equations in Hilbert spaces

We propose a numerical solution for the solution of the Fokker–Planck–Kolmogorov (FPK) equations associated with stochastic partial differential equations in Hilbert spaces. The method is based on the spectral decomposition of the Ornstein–Uhlenbeck semigroup associated to the Kolmogorov equation. This allows us to write the solution of the Kolmogorov equation as a deterministic version of the Wiener–Chaos Expansion. By using this expansion we reformulate the Kolmogorov equation as an infinite system of ordinary differential equations, and by truncating it we set a linear finite system of differential equations. The solution of such system allow us to build an approximation to the solution of the Kolmogorov equations. We test the numerical method with the Kolmogorov equations associated with a stochastic diffusion equation, a Fisher–KPP stochastic equation and a stochastic Burgers equation in dimension 1.

Fourier spectral-based modal curvature analysis and its application to damage detection in beams

In this paper, a simple Fourier spectral-based method is proposed to calculate the modal curvature (MC) of beams instead of the traditional central difference method. Based on the present method, damages in beam-like structures are localized. The present method provides an alternative selection to estimate MC in damage detection. There are two advantages of the present method. Firstly, the spectral calculation of spatial derivatives is conducted globally, which provides the suppression for noise. In addition, signal processing in the wavenumber domain provides an alternative choice for spatial filtering for mode shapes. Secondly, the proposed method provides a precise estimation of the MC which is related to original definition. With the absence of numerical derivative, the estimated results can be more stable and robust. Statistical analysis is conducted to show the effectiveness and noise immunity of the proposed method. In order to obtain the better identification, the MC calculated by the proposed method is employed as the input of continuous wavelet transform, and then the hybrid method is generated. The validations of the present method and comparison with the traditional central difference method are numerically and experimentally demonstrated.

An automatic approach towards modal parameter estimation for high-rise buildings of multicomponent signals under ambient excitations via filter-free Random Decrement Technique

This paper proposes an automatic modal analysis approach for signals of high-rise buildings recorded under real-world ambient excitations. The fact of working over such type of signals is faced with several challenges: the time-domain convolution between the system impulse response and the seismic noise, the existence of several components, the presence of closely-spaced frequency modes, with high additive noises, and low, exponential and damped amplitudes. The proposed approach handles these challenges simultaneously without the need for a user intervention. It is based on a filter-free Random Decrement Technique to estimate the free-decay response, followed by a spectral-based method for a rough modal estimate and finalized by a Maximum-Likelihood Estimation process to refine the modal estimates. Each of these processes is responsible to tackle one or more of the aforementioned challenges in the aim to provide an automatic and moreover a reliable modal analysis of the studied signals.

Hyperspectral mapping of Iranian east ophiolite mélanges using neutral network classification method

Mapping in the areas, which are near the collision zone, needs extensive and exact studies and tools because of the variety of rocks and complex structures. Hyperspectral sensor is one of the most advanced tools that can do imaging in hundreds of delicate and continuous bands in visible and infrared spectrums. Therefore, it can identify many lithologies despite spectral similarities and complications. In the present study, as one of the first hyperspectral data survey for separating ophiolite melange units in Iran, we applied the spectral-based method of neutral network classification method on hyperion images of Tabas in southeast of Iran. Based on various laboratory–field studies, the lithology of the study area can be separated into five general groups: ophiolite series, metamorphic units, Oligocene–Miocene to Quaternary volcanic units, and lime and flysch units. In order to perform an accuracy assessment of the image processing results, some locations and points were sampled. These samples were analyzed under the microscope and by electron microprobe system. Based on field–laboratory works, the accuracy of the resulting image was validated. Consequently, the neutral network method as advanced hyperspectral image processing method produced an average user accuracy coefficient of 62 % in some parts of colored melanges. Therefore, the method based on neutral network theory for spectral classification has acceptable ability to discriminate various lithologies in the complex geological scenarios.

Fourier transform analysis of graphene‐based multilayer structures

In this study, a generic multilayer structure containing metals, dielectrics, line sources and graphene sheets is considered and analysed. The spectral domain techniques (SDTs) have been known as an efficient method for analysis of planar structures. However, since existence of graphene sheet imposes a new boundary condition, conventional SDTs cannot deal with it. Therefore a spectral-based method is proposed by applying the two-dimensional Fourier transform to the fields' equations. First, a graphene sheet described by a conductivity tensor is assumed to be placed between two arbitrary dielectric layers. A generalised transformation matrix is then calculated which relates the electromagnetic fields of the top layer in terms of the ones of the bottom layer. It is shown that considering the tangential electric fields as supporting field components makes an easier analysis and results in more simplified expressions. The proposed method is evaluated through some examples of guiding and radiating structures. Some novel characteristics are observed, which are promising in providing new applications.

Identifying similar functional modules by a new hybrid spectral clustering method

Recently, a large number of researches have focused on finding cellular modules within protein-protein interaction networks. Until now, most of the works have concentrated on finding small modules and protein complexes. The authors have extended the concept of functional module and have identified larger functional modules which are the most similar to the entire network. To this end, a new hybrid spectral-based method is proposed here. First, the original graph is transformed into a line graph. Next, the nodes of the new graph are represented in the Euclidean space by using spectral methods and finally, a self-organising map is applied to the points in the new feature space. The experimental results show that similar modules, obtained from the proposed method, have own local hubs and lots of significant functional subunits concerning each other. These modules not only detect general biological processes that each protein is involved in, but also due to great similarities to the original network, it can be used as significant subnetworks for predicting protein function as detailed as possible. Some interesting properties of these modules are also investigated in this research.

Spectral-based color separation method for a multi-ink printer

A spectral-based 8-ink characterization model is developed to accurately predict the recipe for a multi-ink printer. The 8-ink color separation method is a union of five 3-ink and six 4-ink combinations based on the cellular Yule-Nielsen spectral Neugebauer model with a recipe selection strategy. The performance levels of the forward and backward models are evaluated for individual ink combinations using printed testing samples. Furthermore, the spectral-based method performs better compared with the XYZ-based approach. On the basis of the backward model performance, a novel fast recipe selection strategy is proposed and estimated.