SAR Image Compression Using Integer to Integer Transformations, Dimensionality Reduction, and High Correlation Modeling

In this document, we present new techniques for near-lossless and lossy compression of SAR imagery saved in PNG and binary formats of magnitude and phase data based on the application of transforms, dimensionality reduction methods, and lossless compression. In particular, we discuss the use of blockwise integer to integer transforms, subsequent application of a dimensionality reduction method, and Burrows-Wheeler based lossless compression for the PNG data and the use of high correlation based modeling of sorted transform coefficients for the raw floating point magnitude and phase data. The gains exhibited are substantial over the application of different lossless methods directly on the data and competitive with existing lossy approaches. The methods presented are effective for large scale processing of similar data formats as they are heavily based on techniques which scale well on parallel architectures.

Digital image correlation based high-speed crack tip locatingmethod and its application

Based on a digital image correlation（DIC）method with the measurements of a high speed crack＇s displacement and strain fields,a technique to accurately and automatically locate its crack tip has been developed.The crack tip is identified by finding the abrupt jump on the opening（or dislocation）curve of a point on the trace of the crack propagation,while the opening is measured through a virtual extensometer technique and the abrupt jump is identified by finding the peak on the curve.The method was verified using a specially designed experiment and applied to measure the critical crack tip opening angle of a rock sample.Because the involvement of analytical models has been avoided and then the good performance could be ensured for low resolution speckle images,this technique is expected to be very useful in the quantitative study of high speed cracks in experiments using high speed cameras.

Quantitative characterization of deformation and damage process by digital volume correlation:A review

Characterizing material 3D deformation and damage is a key challenge in mechanical research. Digital volume correlation （DVC）, as a tool for quantifying the internal mechanical response, can comprehensively study the extraction of key failure parameters. This review summarizes the recent progresses in the study of the internal movement of granular materials, inhomogeneous deformation of composite materials, and stress intensity factor around a crack front in static and fatigue states using DVC. To elaborate on the technique＇s potential, we discussed the accuracy and efficiency of the algorithm and the acquisition of real microstructure data within the material under a complex environment.

RELATIONSHIPS BETWEEN PRECEDING PACIFIC SEA SURFACE TEMPERATURES AND SUBTROPICAL HIGH INDEXES OF MAIN RAINING SEASONS

With correlation analysis and factor analysis methods, the effects of preceding Pacific SSTs on subtropical high indexes of main raining seasons are discussed. The results of correlation analysis show that the effects of SSTs on five subtropical high indexes differ in seasons and regions. The variation of SSTs mostly affects the area and intensity indexes of the subtropical high, followed by the western ridge index, and the effect on the ridge line index is more remarkable than on the north boundary index. The results of factor analysis reveals that the first common factor of SST of each season reflected mainly the inverse relation of SSTs variation between the central and eastern part of equatorial Pacific and the western Pacific, which correlates better with the subtropical high indexes in the main raining seasons than other common factors of SST. The analysis of interdecadal variation indicated that the variation of SSTs was conducive to the emergence of the La Ni?a event before the end of 1970s, such that in the summer the subtropical high is likely to be weaker and smaller and located eastward and northward. After the 1980s, the opposite characteristics prevailed.

Variable Selection for Generalized Linear Model with Highly Correlated Covariates

The penalized variable selection methods are often used to select the relevant covariates and estimate the unknown regression coefficients simultaneously,but these existing methods may fail to be consistent for the setting with highly correlated covariates.In this paper,the semi-standard partial covariance(SPAC)method with Lasso penalty is proposed to study the generalized linear model with highly correlated covariates,and the consistencies of the estimation and variable selection are shown in high-dimensional settings under some regularity conditions.Some simulation studies and an analysis of colon tumor dataset are carried out to show that the proposed method performs better in addressing highly correlated problem than the traditional penalized variable selection methods.

High-resolution Givetian-Frasnian boundary recognition from conodont-chemo-stratigraphic correlation at Liujing, Guangxi, South China

The Givetian-Frasnian boundary at Liujing, Guangxi, South China is for the first time recognized and correlated in high resolution using characteristic chemocycles of element abundance fluctuation integrated with conodont biostratignphy. The first appearance of Ancyrodella rotundiloba early form is as a biomarker, and the boundary of lowering fluctuation of element abundance followed by a sequence of characteristic chemocycles with a sequence of cmodonts is as an abiotic auxiliary marker. The error is not more than 0.10 Ma. The study indicates that in a quiet interval, characteristic chemocycles integrated with biomarkers can be used for boundary recognition and regional cormlation in high resolution, and this method has potential for intercontinental correlation

The TBD method for dim targets based on multi-level crossover and matching operator

In order to improve the tracking performance in this paper following TBD(Track before Detection) framework multi-level crossover and matching operator is presented.In data association stage the greedy principle is adopted to handle time complexity in DPA and at the same time crossover mathing operator is given to construct candidate trajectory.In addition the corresponding strategy is introduced in preprocessing and postprocessing to remove clutter and suppress false alarm rate.By the experimental comparison and analysis it can be found that the method is more perfer to strengthen the tracking performance of targets with SNR < 2.0 dB.