Local Skewness Research Articles

Investigation of wave-driven currents and statistical moments of irregular waves over a one dimensional horizontal fringing reef

Effects of significant wave height and seaward depth on the distribution of the wave-induced set-up, wave-driven currents and the statistical moments (kurtosis and skewness) of the horizontal velocities and surface elevations of irregular waves propagating over a fringing reef are investigated using a fully non-hydrostatic wave model. It is found that wave-induced set-up and wave-driven currents obviously increase with increasing significant wave height and seaward depth. Besides, as the seaward depth is relatively shallow, the local maximum skewness of horizontal fluid velocities and surface elevations are achieved nearly at the same location. However, the location of the maximum kurtosis of the horizontal fluid velocities is on the inshore side of the flat compared to that of the surface elevations. Additionally, as a seaward depth increases, variations of skewness and kurtosis of horizontal velocities are more significant compared to surface elevations, and the maximum kurtosis and skewness of the horizontal velocities located downstream compared to those of the surface elevations.

The Heterogeneity of Skewness in T2W-Based Radiomics Predicts the Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.

Our study aimed to investigate whether radiomics on MRI sequences can differentiate responder (R) and non-responder (NR) patients based on the tumour regression grade (TRG) assigned after surgical resection in locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy (nCRT). Eighty-five patients undergoing primary staging with MRI were retrospectively evaluated, and 40 patients were finally selected. The ROIs were manually outlined in the tumour site on T2w sequences in the oblique-axial plane. Based on the TRG, patients were grouped as having either a complete or a partial response (TRG = (0,1), n = 15). NR patients had a minimal or poor nCRT response (TRG = (2,3), n = 25). Eighty-four local first-order radiomic features (RFs) were extracted from tumour ROIs. Only single RFs were investigated. Each feature was selected using univariate analysis guided by a one-tailed Wilcoxon rank-sum. ROC curve analysis was performed, using AUC computation and the Youden index (YI) for sensitivity and specificity. The RF measuring the heterogeneity of local skewness of T2w values from tumour ROIs differentiated Rs and NRs with a p-value ≈ 10−5; AUC = 0.90 (95%CI, 0.73–0.96); and YI = 0.68, corresponding to 80% sensitivity and 88% specificity. In conclusion, higher heterogeneity in skewness maps of the baseline tumour correlated with a greater benefit from nCRT.

Intelligent-based decision support system for diagnosing glaucoma in primary eyecare centers using eye tracker

It is quite alarming that the increase of glaucoma is due to the lack of awareness of the disease and the cost for glaucoma screening. The primary eye care centers need to include a comprehensive glaucoma screening and include machine learning models to elaborate it as decision support system. The proposed system considers the state of art of eye gaze features to understand cognitive processing, direction and restriction of visual field. There is no significant difference in global and local ratio and skewness value of fixation duration and saccade amplitude, which suggest that there is no difference in cognitive processing. The significance value of saccadic extent along vertical axis, Horizontal Vertical ratio (HV ratio), convex hull area and saccadic direction show that there is restriction in vertical visual field. The statistical measures (p < 0.05) and Spearman correlation coefficient with class label validate the results. The proposed system compared the performance of seven classifiers: Naïve Bayes classifier, linear and kernel Support Vector classifiers, decision tree classifier, Adaboost, random forest and eXtreme Gradient Boosting (XGBoost) classifier. The discrimination of eye gaze features of glaucoma and normal is efficiently done by XGBoost with accuracy 1.0. The decision support system is cost-effective and portable.

Underwater Target Perception in Local HOS Space

In this paper, we propose an underwater target perception architecture, which adopts the three-stage processing including underwater scene acoustic imaging, local high-order statistics (HOS) space conversion, and region-of-interest (ROI) detection. After analysing the problem of the underwater targets represented by the acoustic images, the unique cube structure of the target in local skewness space is noticed, which is used as a clue to develop the ROI detection of underwater scenes. In order to restore the actual appearance of the ROI as much as possible, the focus processing is explored to achieve the target reconstruction. When the target size and number are unknown, using an uncertain theoretical template can achieve a better target reconstruction effect. The performance of the proposed method in terms of SNR, detection rate, and false alarm rate is verified by experiments with several acoustic image sequences. Moreover, target perception architecture is general and can be generalized to a wider range of underwater applications.

NPSA: Nonorthogonal Principal Skewness Analysis.

Principal skewness analysis (PSA) has been introduced for feature extraction in hyperspectral imagery. As a thirdorder generalization of principal component analysis (PCA), its solution of searching for the local maximum skewness direction is transformed into the problem of calculating the eigenpairs (the eigenvalues and the corresponding eigenvectors) of a coskewness tensor. By combining a fixed-point method with an orthogonal constraint, the new eigenpairs are prevented from converging to the same previously determined maxima. However, in general, the eigenvectors of the supersymmetric tensor are not inherently orthogonal, which implies that the results obtained by the search strategy used in PSA may unavoidably deviate from the actual eigenpairs. In this paper, we propose a new nonorthogonal search strategy to so lve this problem and the new algorithm is named nonorthogonal principal skewness analysis (NPSA). The contribution of NPSA lies in the finding that the search space of the eigenvector to be determined can be enlarged by using the orthogonal complement of the Kronecker product of the previous eigenvector with itself, instead of its orthogonal complement space. We also give a detailed theoretical proof on why we can obtain the more accurate eigenpairs through the new search strategy by comparison with PSA. In addition, after some algebraic derivations, the complexity of the presented algorithm is also greatly reduced. Experiments with both simulated data and real multi/hyperspectral imagery demonstrate its validity in feature extraction.

Contact structures induced by skew fibrations of R3

A smooth fibration of $\mathbb{R}^3$ by oriented lines is given by a smooth unit vector field $V$ on $\mathbb{R}^3$, for which all of the integral curves are oriented lines. Such a fibration is called skew if no two fibers are parallel, and it is called nondegenerate if $\nabla V$ vanishes only in the direction of $V$. Nondegeneracy is a form of local skewness, though in fact any nondegenerate fibration is globally skew. Nondegenerate and skew fibrations have each been recently studied, from both geometric and topological perspectives, in part due to their close relationship with great circle fibrations of $S^3$. Any fibration of $\mathbb{R}^3$ by oriented lines induces a plane field on $\mathbb{R}^3$, obtained by taking the orthogonal plane to the unique line through each point. We show that the plane field induced by any nondegenerate fibration is a tight contact structure. For contactness we require a new characterization of nondegenerate fibrations, whereas the proof of tightness employs a recent result of Etnyre, Komendarczyk, and Massot on tightness in contact metric 3-manifolds. We conclude with some examples which highlight relationships among great circle fibrations, nondegenerate fibrations, skew fibrations, and the contact structures associated to fibrations.

Times are a Changin’? The Emergence of New Firms and Rank Reshuffling

Young firms are known to grow at a faster rate than incumbents. With administrative firm data from Germany, we show that the higher growth rates indeed translate into upward mobility within the sector-specific firm size distribution. Young firms are therefore not only able to catch up with incumbents, but also able to grow larger in absolute values. Recentered influence function regression results reveal that young firms cause significant rank mobility within the stock of firms, which even holds when the local skewness of the firm size distribution is accounted for. The results clearly indicate a Schumpeterian growth process where young firms challenge established ones.

The detection of local irreversibility in time series based on segmentation

We propose a strategy for the detection of local irreversibility in stationary time series based on multiple scale. The detection is beneficial to evaluate the displacement of irreversibility toward local skewness. By means of this method, we can availably discuss the local irreversible fluctuations of time series as the scale changes. The method was applied to simulated nonlinear signals generated by the ARFIMA process and logistic map to show how the irreversibility functions react to the increasing of the multiple scale. The method was applied also to series of financial markets i.e., American, Chinese and European markets. The local irreversibility for different markets demonstrate distinct characteristics. Simulations and real data support the need of exploring local irreversibility.

Laboratory and modeling study on modulated wave properties

Development of Benjamin−Feir instability is investigated under laboratory conditions and by analytical modeling. Nonlinear properties of the wave train with discrete spectrum are also investigated. The mechanically generated waves are composed of several discrete waves, while the newly generated harmonics are still combined into discrete spectra with the same frequency step. The technique proposed in this study allows us to study accurately the nonlinear variations in main properties of each harmonic with fixed frequency, such as amplitude, phase speed, and wavenumber along the wave tank together with velocities of wave packet crests, especially for the large transient waves. The phase speeds of short waves increase near large transient waves, and the velocities of longer waves are close to the values determined by the linear theory of waves. The relative long wave accompanied by short waves can dramatically change the local kurtosis and skewness of the wave field. They may play an important role for the generation of large transient wave and provide an opportunity for triggering of the freak waves.

Infrared Polarization and Intensity Image Fusion Algorithm Based on Visual Brightness and Contrast Response Function

In this paper, a novel fusion algorithm is proposed based on visual brightness and contrast response function, and it can better retain the difference features between infrared and polarization images to improve the visual effect of fused image. Firstly, the source images are enhanced by fractional differentia operator to improve the edge, texture, and brightness. Second, the low frequency and high frequency features of enhanced infrared polarization and intensity image are described by local mean and local skewness. Thirdly, the visual brightness and contrast response function are constructed by using local mean and local skewness based on human visual model. Next, the source images are fused by using the visual brightness and contrast response function, and then two kinds of fused images that are respectively are the low frequency feature fused image and detail feature fused image are gotten. Finally, the fused image is gotten by superposition of the low frequency feature fused image and detail feature fused image. The experiment shows that the result obtained by proposed algorithm performs better in both subjective and objective qualities.

Object representation for multi-beam sonar image using local higher-order statistics

Multi-beam sonar imaging has been widely used in various underwater tasks such as object recognition and object tracking. Problems remain, however, when the sonar images are characterized by low signal-to-noise ratio, low resolution, and amplitude alterations due to viewpoint changes. This paper investigates the capacity of local higher-order statistics (HOS) to represent objects in multi-beam sonar images. The Weibull distribution has been used for modeling the background of the image. Local HOS involving skewness is estimated using a sliding computational window, thus generating the local skewness image of which a square structure is associated with a potential object. The ability of object representation with different signal-to-noise ratio (SNR) between object and background is analyzed, and the choice of the computational window size is discussed. In the case of the object with high SNR, a novel algorithm based on background estimation is proposed to reduce side lobe and retain object regions. The performance of object representation has been evaluated using real data that provided encouraging results in the case of the object with low amplitude, high side lobes, or large fluctuant amplitude. In conclusion, local HOS provides more reliable and stable information relating to the potential object and improves the object representation in multi-beam sonar image.

基于局部联合偏度-峰度的高光谱图像波段选择方法

基于局部联合偏度-峰度的高光谱图像波段选择方法

Impact of Lanice conchilega on seafloor microtopography off the island of Sylt (German Bight, SE North Sea)

This study presents a new in situ method to explore the impact of macrofauna on seafloor microtopography and corresponding microroughness based on underwater laser line scanning. The local microtopography was determined with mm-level accuracy at three stations colonised by the tubeworm Lanice conchilega offshore of the island of Sylt in the German Bight (south-eastern North Sea), covering approximately 0.5 m2 each. Ground truthing was done using underwater video data. Two stations were populated by tubeworm colonies of different population densities, and one station had a hydrodynamically rippled seafloor. Tubeworms caused an increased skewness of the microtopography height distribution and an increased root mean square roughness at short spatial wavelengths compared with hydrodynamic bedforms. Spectral analysis of the 2D Fourier transformed microtopography showed that the roughness magnitude increased at spatial wavelengths between 0.020 and 0.003 m independently of the tubeworm density. This effect was not detected by commonly used 1D roughness profiles but required consideration of the complete spectrum. Overall, the results reveal that new indicator variables for benthic organisms may be developed based on microtopographic data. An example demonstrates the use of local slope and skewness to detect tubeworms in the measured digital elevation model.

Improving the modelling of redshift-space distortions– II. A pairwise velocity model covering large and small scales

We develop a model for the redshift-space correlation function, valid for both dark matter particles and halos on scales $>5\,h^{-1}$Mpc. In its simplest formulation, the model requires the knowledge of the first three moments of the line-of-sight pairwise velocity distribution plus two well-defined dimensionless parameters. The model is obtained by extending the Gaussian-Gaussianity prescription for the velocity distribution, developed in a previous paper, to a more general concept allowing for local skewness, which is required to match simulations. We compare the model with the well known Gaussian streaming model and the more recent Edgeworth streaming model. Using N-body simulations as a reference, we show that our model gives a precise description of the redshift-space clustering over a wider range of scales. We do not discuss the theoretical prescription for the evaluation of the velocity moments, leaving this topic to further investigation.

The role of temporal abundance structure and habitat preferences in the survival of conodonts during the mid-early Silurian Ireviken mass extinction event.

The Ireviken event was one of the most intense extinction episodes that occurred during the mid-Paleozoic era. It had a strong global effect on a range of clades, with conodonts, graptolites and chitinozoans affected most. Using geophysical proxies and conodont species parameters of their temporal abundance structure we investigate how they affected the selectivity of conodont species survival during this calamity. After performing bivariate logistic analyses on 34 species of conodonts, we find three variables that were statistically significantly associated with their odds of survival. These namely include spectral exponents that describe degrees of autocorrelation in a time series, the skewness of species abundance distribution, and average environmental preferences, which are mostly determined by ancient water depths at sampling sites. Model selection of multivariate logistic models found the best model includes species local abundance skewness and substrate preference. A similar pattern is revealed through the regression tree analysis. The apparent extinction selectivity points to a possible causes of environmental deterioration during the Ireviken event. The significant positive relationship between extinction risk and preferential existence in deeper environments suggests the open ocean causal mechanisms of biotic stress that occurred during the Ireviken event. Marine regressions, which were previously suggested as a causal factor in this extinction episode, on theoretical grounds should have had higher impact on species living in near-shore environments, through the processes of habitat loss which are associated with decreases of shelfal areas. In addition, the significant positive correlations found between skewness of abundance distributions and spectral exponent values and the probability of species survival suggest that community and ecosystem processes (which controlled species abundance fluctuation patterns) were significantly related to selectivity processes of this smaller mass extinction event.

AN EXPERIMENTAL STUDY ON NONLINEAR WAVE DYNAMICS: ROUGE WAVE GENERATION AND WAVE BLOCKING

Wave modulation due to Bengamin Feir Instability (BFI) in the presence of long wave (swell) is investigated in the elaborate experiments. The mechanically generated waves are composed of three discrete waves; while the newly generated harmonics due to BFI still combining into discrete spectra with the same frequency difference step. These stable discrete waves allow us to further examine the basic properties of nonlinear wave-wave interactions, such as the variation of phase speeds and wave numbers along the wave tank together with speed of crests, especial for the large transient waves. The measured values have a reasonable correspondence to the available nonlinear model estimations. The technique proposed in this study is verified to accurately measure the phase speed and wave number of each harmonic in the wave group. Phase speeds of short waves have a significant amplification in the vicinity of big transient waves, while the speeds of longer waves are close to linear values. The relative long wave (storm wave) travelling with short waves (wind waves) dramatically change the local kurtosis and skewness and may have an important role for the generation of large transient wave and provide an opportunity for triggering the freak waves.

Local skewness attribute as a seismic phase detector

We propose a novel seismic attribute, local skewness, as an indicator of localized phase of seismic signals. The proposed attribute appears to have a higher dynamical range and a better stability than the previously used local kurtosis. Synthetic and real data examples demonstrate the effectiveness of local skewness in detecting and correcting time-varying, locally observed phase of seismic signals.

Local properties of Wilkinson Microwave Anisotropy Probe cold spot

We investigate the local properties of WMAP Cold Spot (CS) by defining the local statistics: mean temperature, variance, skewness and kurtosis. We find that, compared with the \emph{coldest spots} in random Gaussian simulations, WMAP CS deviates from Gaussianity at $\sim 99%$ significant level. In the meanwhile, when compared with the spots at the same position in the simulated maps, the values of local variance and skewness around CS are all systematically larger in the scale of $R>5^{\circ}$, which implies that WMAP CS is a large-scale non-Gaussian structure, rather than a combination of some small structures. This is consistent with the finding that the non-Gaussianity of CS is totally encoded in the WMAP low multipoles. Furthermore, we find that the cosmic texture can excellently explain all the anomalies in these statistics.

Adaptive bit rate encoding mechanism based on irregular sampling and side-match vector quantization

A novel image compression scheme based on the side match vector quantization (SMVQ) scheme is proposed. The goal of this scheme is to improve the image quality of the SMVQ scheme while keeping a low bit rate. The required bit rate of this scheme is variable, and the bit rate can be control by the proposed adaptive bit rate encoding mechanism. Three techniques are applied in this scheme: the local skewness of the image, the adaptive irregular sampling and the modified side-match distortion measurement to satisfy the variant encoding requirements of the various image contents. The experimental results show that the derailment is suppressed and the image quality is approximated to VQ and enhanced ~2 dB from SMVQ at the same bit rate. Furthermore, the proposed scheme supports the adaptive bit rate encoding approach, which enables it to solve the trade-off between the image quality and the encoding bit rate.

Local Non-Stationary Nature of Brain Waves from Demented Persons

In the present paper, we show the local non-stationary nature of brain waves from demented persons by reconstructing various stochastic processes of averaged local quantities, e.g., fractal dimension, mean, variance, skewness and kurtosis. The characteristic random dynamic features of their local quantities are discussed in the two-dimensional (2D) phase space. The availability of their local non-stationary nature for diagnosing senile dementia is also discussed.