scholarly journals Framework for Reconstruction of Pseudo Quad Polarimetric Imagery from General Compact Polarimetry

2021 ◽  
Vol 13 (3) ◽  
pp. 530
Author(s):  
Junjun Yin ◽  
Jian Yang
Keyword(s):  
Linear Equations ◽  
Estimation Method ◽  
Data Sets ◽  
Reconstruction Procedure ◽  
Component Decomposition ◽  
Reconstruction Methods ◽  
Sar Imagery ◽  
Key Aspects ◽  
Non Linear Equations ◽  
Reconstruction Model

Pseudo quad polarimetric (quad-pol) image reconstruction from the hybrid dual-pol (or compact polarimetric (CP)) synthetic aperture radar (SAR) imagery is a category of important techniques for radar polarimetric applications. There are three key aspects concerned in the literature for the reconstruction methods, i.e., the scattering symmetric assumption, the reconstruction model, and the solving approach of the unknowns. Since CP measurements depend on the CP mode configurations, different reconstruction procedures were designed when the transmit wave varies, which means the reconstruction procedures were not unified. In this study, we propose a unified reconstruction framework for the general CP mode, which is applicable to the mode with an arbitrary transmitted ellipse wave. The unified reconstruction procedure is based on the formalized CP descriptors. The general CP symmetric scattering model-based three-component decomposition method is also employed to fit the reconstruction model parameter. Finally, a least squares (LS) estimation method, which was proposed for the linear π/4 CP data, is extended for the arbitrary CP mode to estimate the solution of the system of non-linear equations. Validation is carried out based on polarimetric data sets from both RADARSAT-2 (C-band) and ALOS-2/PALSAR (L-band), to compare the performances of reconstruction models, methods, and CP modes.

scholarly journals A sparse reconstruction method for the estimation of multi-resolution emission fields via atmospheric inversion

2015 ◽  
Vol 8 (4) ◽  
pp. 1259-1273 ◽  
Author(s):  
J. Ray ◽  
J. Lee ◽  
V. Yadav ◽  
S. Lefantzi ◽  
A. M. Michalak ◽  
...  
Keyword(s):  
Field Model ◽  
Computational Cost ◽  
Estimation Method ◽  
Sparse Reconstruction ◽  
Model Parameters ◽  
Reconstruction Method ◽  
Reconstruction Procedure ◽  
Reconstruction Methods ◽  
Atmospheric Inversion ◽  
Atmospheric Inversions

Abstract. Atmospheric inversions are frequently used to estimate fluxes of atmospheric greenhouse gases (e.g., biospheric CO2 flux fields) at Earth's surface. These inversions typically assume that flux departures from a prior model are spatially smoothly varying, which are then modeled using a multi-variate Gaussian. When the field being estimated is spatially rough, multi-variate Gaussian models are difficult to construct and a wavelet-based field model may be more suitable. Unfortunately, such models are very high dimensional and are most conveniently used when the estimation method can simultaneously perform data-driven model simplification (removal of model parameters that cannot be reliably estimated) and fitting. Such sparse reconstruction methods are typically not used in atmospheric inversions. In this work, we devise a sparse reconstruction method, and illustrate it in an idealized atmospheric inversion problem for the estimation of fossil fuel CO2 (ffCO2) emissions in the lower 48 states of the USA. Our new method is based on stagewise orthogonal matching pursuit (StOMP), a method used to reconstruct compressively sensed images. Our adaptations bestow three properties to the sparse reconstruction procedure which are useful in atmospheric inversions. We have modified StOMP to incorporate prior information on the emission field being estimated and to enforce non-negativity on the estimated field. Finally, though based on wavelets, our method allows for the estimation of fields in non-rectangular geometries, e.g., emission fields inside geographical and political boundaries. Our idealized inversions use a recently developed multi-resolution (i.e., wavelet-based) random field model developed for ffCO2 emissions and synthetic observations of ffCO2 concentrations from a limited set of measurement sites. We find that our method for limiting the estimated field within an irregularly shaped region is about a factor of 10 faster than conventional approaches. It also reduces the overall computational cost by a factor of 2. Further, the sparse reconstruction scheme imposes non-negativity without introducing strong nonlinearities, such as those introduced by employing log-transformed fields, and thus reaps the benefits of simplicity and computational speed that are characteristic of linear inverse problems.

Fully automated near-surface analysis by surface-consistent refraction method

Geophysics ◽  
2016 ◽  
Vol 81 (4) ◽  
pp. U39-U49 ◽  
Author(s):  
Daniele Colombo ◽  
Federico Miorelli ◽  
Ernesto Sandoval ◽  
Kevin Erickson
Keyword(s):  
Surface Analysis ◽  
Seismic Data ◽  
Linear Equations ◽  
Time Shift ◽  
Data Sets ◽  
Time Lags ◽  
Data Set ◽  
Near Surface ◽  
Seismic Acquisition ◽  
Key Aspects

Industry practices for near-surface analysis indicate difficulties in coping with the increased number of channels in seismic acquisition systems, and new approaches are needed to fully exploit the resolution embedded in modern seismic data sets. To achieve this goal, we have developed a novel surface-consistent refraction analysis method for low-relief geology to automatically derive near-surface corrections for seismic data processing. The method uses concepts from surface-consistent analysis applied to refracted arrivals. The key aspects of the method consist of the use of common midpoint (CMP)-offset-azimuth binning, evaluation of mean traveltime and standard deviation for each bin, rejection of anomalous first-break (FB) picks, derivation of CMP-based traveltime-offset functions, conversion to velocity-depth functions, evaluation of long-wavelength statics, and calculation of surface-consistent residual statics through waveform crosscorrelation. Residual time lags are evaluated in multiple CMP-offset-azimuth bins by crosscorrelating a pilot trace with all the other traces in the gather in which the correlation window is centered at the refracted arrival. The residuals are then used to build a system of linear equations that is simultaneously inverted for surface-consistent shot and receiver time shift corrections plus a possible subsurface residual term. All the steps are completely automated and require a fraction of the time needed for conventional near-surface analysis. The developed methodology was successfully performed on a complex 3D land data set from Central Saudi Arabia where it was benchmarked against a conventional tomographic work flow. The results indicate that the new surface-consistent refraction statics method enhances seismic imaging especially in portions of the survey dominated by noise.

Advanced Thermodynamics Applications Using Mathcad

2009 ◽  
Author(s):  
Stephen T. McClain
Keyword(s):  
Thermodynamic Property ◽  
Linear Equations ◽  
Data Sets ◽  
Text File ◽  
Steam Power ◽  
Power Cycle ◽  
Undergraduate Engineering ◽  
Newton Raphson ◽  
Non Linear Equations ◽  
Insight Into

Mathcad thermodynamic property function sets have been developed for many engineering fluids. In past publications, which introduced the property function sets, examples were provided that demonstrated the usefulness of the functions in solving typical homework problems for either an Introduction to Thermodynamics or an Applied Thermodynamics course. The capabilities of Mathcad allow for much more complicated analyses than are typically discussed in undergraduate engineering thermodynamics courses. Specifically, Mathcad’s abilities 1) to perform calculations on multi-dimensional arrays, 2) to optimize functions using modified Newton-Raphson techniques, 3) to read text-file data sets, and 4) solve systems of non-linear equations, enables the analysis of very complex thermodynamic problems. Examples are provided to demonstrate the very robust capabilities of Mathcad using previously developed thermodynamic property function sets. The examples discussed include the optimization of a steam power cycle using two feedwater heaters, the analysis of gas turbine data acquired from a small turbojet apparatus, and the analysis of evaporator flooding on the performance of an industrial refigeration system. The analyses and figures produced in Mathcad demonstrate its effectiveness for complex thermodynamic calculations and for providing insight into the performance of complex thermodynamic systems.

scholarly journals A master exceptional field theory

2021 ◽  
Vol 2021 (6) ◽  
Author(s):  
Guillaume Bossard ◽  
Axel Kleinschmidt ◽  
Ergin Sezgin
Keyword(s):  
Field Theory ◽  
Gauge Invariance ◽  
Sigma Model ◽  
Linear Equations ◽  
Field Theories ◽  
Gauge Invariant ◽  
Non Linear ◽  
Non Linear Equations

Abstract We construct a pseudo-Lagrangian that is invariant under rigid E11 and transforms as a density under E11 generalised diffeomorphisms. The gauge-invariance requires the use of a section condition studied in previous work on E11 exceptional field theory and the inclusion of constrained fields that transform in an indecomposable E11-representation together with the E11 coset fields. We show that, in combination with gauge-invariant and E11-invariant duality equations, this pseudo-Lagrangian reduces to the bosonic sector of non-linear eleven-dimensional supergravity for one choice of solution to the section condi- tion. For another choice, we reobtain the E8 exceptional field theory and conjecture that our pseudo-Lagrangian and duality equations produce all exceptional field theories with maximal supersymmetry in any dimension. We also describe how the theory entails non-linear equations for higher dual fields, including the dual graviton in eleven dimensions. Furthermore, we speculate on the relation to the E10 sigma model.

scholarly journals An edge-cloud collaboration architecture for pattern anomaly detection of time series in wireless sensor networks

2021 ◽  
Author(s):  
Cong Gao ◽  
Ping Yang ◽  
Yanping Chen ◽  
Zhongmin Wang ◽  
Yue Wang
Keyword(s):  
Time Series ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Anomaly Detection ◽  
Estimation Method ◽  
Feature Representation ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Data Sets ◽  
Edge Node

AbstractWith large deployment of wireless sensor networks, anomaly detection for sensor data is becoming increasingly important in various fields. As a vital data form of sensor data, time series has three main types of anomaly: point anomaly, pattern anomaly, and sequence anomaly. In production environments, the analysis of pattern anomaly is the most rewarding one. However, the traditional processing model cloud computing is crippled in front of large amount of widely distributed data. This paper presents an edge-cloud collaboration architecture for pattern anomaly detection of time series. A task migration algorithm is developed to alleviate the problem of backlogged detection tasks at edge node. Besides, the detection tasks related to long-term correlation and short-term correlation in time series are allocated to cloud and edge node, respectively. A multi-dimensional feature representation scheme is devised to conduct efficient dimension reduction. Two key components of the feature representation trend identification and feature point extraction are elaborated. Based on the result of feature representation, pattern anomaly detection is performed with an improved kernel density estimation method. Finally, extensive experiments are conducted with synthetic data sets and real-world data sets.

scholarly journals Striated Tire Yaw Marks—Modeling and Validation

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4309
Author(s):  
Wojciech Wach ◽  
Jakub Zębala
Keyword(s):  
Vehicle Dynamics ◽  
Linear Equations ◽  
Tire Model ◽  
Vehicle Accidents ◽  
The Road ◽  
Variable Curvature ◽  
Macro Scale ◽  
On The Road ◽  
Multi Body ◽  
Non Linear Equations

Tire yaw marks deposited on the road surface carry a lot of information of paramount importance for the analysis of vehicle accidents. They can be used: (a) in a macro-scale for establishing the vehicle’s positions and orientation as well as an estimation of the vehicle’s speed at the start of yawing; (b) in a micro-scale for inferring among others things the braking or acceleration status of the wheels from the topology of the striations forming the mark. A mathematical model of how the striations will appear has been developed. The model is universal, i.e., it applies to a tire moving along any trajectory with variable curvature, and it takes into account the forces and torques which are calculated by solving a system of non-linear equations of vehicle dynamics. It was validated in the program developed by the author, in which the vehicle is represented by a 36 degree of freedom multi-body system with the TMeasy tire model. The mark-creating model shows good compliance with experimental data. It gives a deep view of the nature of striated yaw marks’ formation and can be applied in any program for the simulation of vehicle dynamics with any level of simplification.

scholarly journals Compartmental Learning versus Joint Learning in Engineering Education

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 662
Author(s):  
María Jesús Santos ◽  
Alejandro Medina ◽  
José Miguel Mateos Roco ◽  
Araceli Queiruga-Dios
Keyword(s):  
Engineering Students ◽  
Chemical Engineering ◽  
Linear Equations ◽  
Mathematical Software ◽  
Mathematical Concepts ◽  
Joint Learning ◽  
The University ◽  
Academic Year ◽  
Non Linear Equations ◽  
Mathematics And Physics

Sophomore students from the Chemical Engineering undergraduate Degree at the University of Salamanca are involved in a Mathematics course during the third semester and in an Engineering Thermodynamics course during the fourth one. When they participate in the latter they are already familiar with mathematical software and mathematical concepts about numerical methods, including non-linear equations, interpolation or differential equations. We have focused this study on the way engineering students learn Mathematics and Engineering Thermodynamics. As students use to learn each matter separately and do not associate Mathematics and Physics, they separate each matter into different and independent compartments. We have proposed an experience to increase the interrelationship between different subjects, to promote transversal skills, and to make the subjects closer to real work. The satisfactory results of the experience are exposed in this work. Moreover, we have analyzed the results obtained in both courses during the academic year 2018–2019. We found that there is a relation between both courses and student’s final marks do not depend on the course.

Partially Invariant Solutions for Two-dimensional Ideal MHD Equations

1990 ◽  
Vol 45 (11-12) ◽  
pp. 1219-1229 ◽  
Author(s):  
D.-A. Becker ◽  
E. W. Richter
Keyword(s):  
Differential Equations ◽  
Linear Equations ◽  
Mhd Equations ◽  
Two Dimensional ◽  
Invariant Solutions ◽  
First Order ◽  
Partially Invariant Solutions ◽  
Quasilinear Systems ◽  
Ideal Mhd ◽  
Non Linear Equations

AbstractA generalization of the usual method of similarity analysis of differential equations, the method of partially invariant solutions, was introduced by Ovsiannikov. The degree of non-invariance of these solutions is characterized by the defect of invariance d. We develop an algorithm leading to partially invariant solutions of quasilinear systems of first-order partial differential equations. We apply the algorithm to the non-linear equations of the two-dimensional non-stationary ideal MHD with a magnetic field perpendicular to the plane of motion.

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