scholarly journals Hierarchic Superposition Revisited

10.29007/w9vg ◽  
2018 ◽  
Author(s):  
Uwe Waldmann
Keyword(s):  
Black Box ◽  
Background Model ◽  
Linear Arithmetic ◽  
Completeness Result ◽  
Standard Models ◽  
Theory Reasoning ◽  
Rational Arithmetic ◽  
Background Models ◽  
Superposition Calculus

In 1994,Bachmair, Ganzinger, and Waldmann introduced the hierarchicalsuperposition calculus as a generalization of the superpositioncalculus for black-box style theory reasoning.Their calculus works in a framework of hierarchic specifications.It tries to prove theunsatisfiability of a set of clauses with respect to interpretationsthat extend a background model such as the integers with linear arithmeticconservatively, that is, withoutidentifying distinct elements of old sorts ("confusion") and withoutadding new elements to old sorts ("junk").We show how the calculus can be improved,report on practical experiments,and present a new completeness result fornon-compact classes of background models(i.e., linear integer or rational arithmetic restricted tostandard models).

Are Social Background Models Time-Bound?

1986 ◽  
Vol 80 (3) ◽  
pp. 957-967 ◽  
Author(s):  
S. Sidney Ulmer
Keyword(s):  
Supreme Court ◽  
Social Background ◽  
Research Note ◽  
Background Model ◽  
Confounding Variable ◽  
Background Models

In this research note I seek to determine whether a significantly predicting social background model for analyzing the votes of Supreme Court justices is time-bound. I argue that an affirmative result poses serious questions for past uses of such models, none of which has controlled for the possibility that time is a confounding variable. A model that significantly predicted the votes of the justices in the Court's 1903–1968 terms was constructed. Analysis with this model for two periods—from 1903 to 1935, and from 1936 to 1968—established that the model was not timeneutral. Appropriate theoretical implications are drawn.

scholarly journals Scattered moonlight observations with X-shooter

2019 ◽  
Vol 624 ◽  
pp. A39
Author(s):  
A. Jones ◽  
S. Noll ◽  
W. Kausch ◽  
S. Unterguggenberger ◽  
C. Szyszka ◽  
...  
Keyword(s):  
Near Infrared ◽  
Current Model ◽  
Background Model ◽  
Lunar Phase ◽  
Aerosol Extinction ◽  
Coarse Particles ◽  
The Moon ◽  
Aerosol Scattering ◽  
Phase Functions ◽  
Background Models

Estimating the sky background is critical for ground-based astronomical research. In the optical, scattered moonlight dominates the sky background, when the moon is above the horizon. The most uncertain component of a scattered moonlight model is the aerosol scattering. The current, official sky background model for Cerro Paranal uses an extrapolated aerosol extinction curve. With a set of X-shooter sky observations, we have tested the current sky background model as well as determined the aerosol extinction from the ultra-violet (UV) to near-infrared (NIR). To our knowledge, this is the first time that a scattered moonlight model has been used for this purpose. These observations were taken of blank sky, during three different lunar phases, and at six different angular distances from the moon for each lunar phase. Overall, the current model does reproduce the observations for average conditions quite well. Using a set of sky background models with varying aerosol distributions to compare with the observations, we found the most likely aerosol extinction curves, phase functions, and volume densities for the three nights of observations and compare them with the current model. While there are some degeneracies in the aerosol scattering properties, the extinction curves tend to flatten towards redder wavelengths and are overall less steep compared to the extrapolated curve used in the current model. Also, the current model had significantly less coarse particles compared to the favored volume densities from the X-shooter data. Having more coarse particles affects the phase function by being more peaked at small angular distances. For the three nights of sky observations, the aerosol size distributions differed, most likely reflecting the changes in atmospheric conditions and aerosol content, which is expected. In short, the current sky background model is in fair agreement with the observations, and we have determined better aerosol extinction curves and phase functions for Cerro Paranal. Using nighttime sky observations of scattered moonlight and a set of sky background models is a new method to probe the aerosol content of the atmosphere.

Background Modeling Approach Based on Eigenspace Decomposition

2012 ◽  
Vol 157-158 ◽  
pp. 1399-1403
Author(s):  
Jian Wu Long ◽  
Xuan Jing Shen ◽  
Hai Peng Chen
Keyword(s):  
Video Sequence ◽  
Moving Objects ◽  
Principal Component ◽  
Background Model ◽  
Training Set ◽  
Training Samples ◽  
The Matrix ◽  
Eigenspace Decomposition ◽  
Svd Decomposition ◽  
Background Models

In this work principal component analysis (PCA) was adopted to construct a background model and moving objects were detected by background subtraction method. Firstly, constructed the matrix of training samples by means of converting the video sequence to vectors. Then calculated the covariance matrix C of the training set, and acquired the eigenvalues and eigenvectors of C through SVD decomposition. Next, sorted the eigenvalues and reconstructed the background model by using several image vectors which had higher cumulative contribution. Finally, comparison experiments are performed with the detection results by GMM approach. Experimental results show that the proposed method in this paper could establish background models more accurate and have better effective of object detection.

scholarly journals Elastic reflection waveform inversion with variable density

Geophysics ◽  
2019 ◽  
Vol 84 (4) ◽  
pp. R553-R567 ◽  
Author(s):  
Yuanyuan Li ◽  
Qiang Guo ◽  
Zhenchun Li ◽  
Tariq Alkhalifah
Keyword(s):  
Waveform Inversion ◽  
Variable Density ◽  
Background Model ◽  
Reverse Time ◽  
S Wave ◽  
Low Frequencies ◽  
Wave Velocities ◽  
Reflection Data ◽  
Time Migration ◽  
Background Models

Elastic full-waveform inversion (FWI) provides a better description of the subsurface information than those given by the acoustic assumption. However, it suffers from a more serious cycle-skipping problem compared with the latter. Reflection waveform inversion (RWI) is able to build a good background model, which can serve as an initial model for elastic FWI. Because, in RWI, we use the model perturbation to explicitly fit reflections, such perturbations should include density, which mainly affects the dynamics. We applied Born modeling to generate synthetic reflection data using optimized perturbations of the P- and S-wave velocities and density. The inversion for the perturbations of the P- and S-wave velocities and density is similar to elastic least-squares reverse time migration. An incorrect background model will lead to misfits mainly at the far offsets, which can be used to update the background P- and S-wave velocities along the reflection wavepath. We optimize the perturbations and background models in an alternate way. We use two synthetic examples and a field-data case to demonstrate our proposed elastic RWI algorithm. The results indicate that our elastic RWI with variable density is able to build reasonably good background models for elastic FWI with the absence of low frequencies, and it can deal with the variable density, which is required in real cases.

REAL-TIME OBJECT DETECTION USING TWO BACKGROUND MODELS UNDER SHAKING CAMERA

2009 ◽  
Vol 06 (01) ◽  
pp. 13-21 ◽  
Author(s):  
TAEHO KIM ◽  
KANG-HYUN JO
Keyword(s):  
Moving Objects ◽  
Displacement Vector ◽  
Motion Vector ◽  
Computational Cost ◽  
Image Sequence ◽  
Background Model ◽  
Experimental Result ◽  
Camera Motion ◽  
Short Period ◽  
Background Models

In this paper, we propose a novel approach to detect moving objects by two background models, multiple background model (MBM) and temporal median background (TMB), from hand-taken image sequence. For this purpose, we record image sequences by hand-held camera without tripod so every frame has variation between consecutive frames. A pixel-based background model is fragile while image sequence has variation. Therefore we calculate the camera movement using correlation between two consecutive images and it helps us to generate MBM under shaking camera. The computational cost of correlation quickly increases if image resolution increases. Hence, we use edge segments to reduce computational cost. These edge segments are gathered by Sobel operator and those are distinctive spatial features to calculate similarity between two regions, belonging to current and previous images, organized by neighbors of edge segments. Based on the similarity result, we obtain a set of best matched regions, centroids of matched regions, and displacement vectors from each pair of previous and current images. Each displacement vector in a set describes the transition of each matched region in the image pair. Using the highest density of displacement vector histogram, we choose the camera motion vector, indicates camera movement between consecutive frames. According to the camera motion vector, every pixel in a current image is related to different position pixels in a previous image. The pixel relation is used to generate MBM in this paper, unlike original MBM [Xiao, M., Han, C. and Kang, K. [2006]. Proc. Int. Conf. Information Fuscon, pp. 1–7.]. The MBM algorithm classifies the variation of pixel values in frame sequence to several clusters. Classification of varying pixel values to several clusters is similar with mixture of gaussian (MOG). Nevertheless, MBM has low cost to calculate because it does not need to estimate parameter. However, MBM is not sensitive to short period changes. Therefore, we use TMB to support MBM. The experimental result shows that proposed algorithm successfully detects moving objects using background subtraction less than 25 ms per frame when camera has 2D translation.

Limited‐view diffraction tomography in a nonuniform background

Geophysics ◽  
1995 ◽  
Vol 60 (2) ◽  
pp. 580-588 ◽  
Author(s):  
Leiv‐J. Gelius
Keyword(s):  
Point Source ◽  
General Structure ◽  
Wave Theory ◽  
Background Model ◽  
Diffraction Tomography ◽  
Strong Resemblance ◽  
Background Wave ◽  
Homogeneous Background ◽  
Paraxial Ray ◽  
Background Models

The main problems in geophysical diffraction tomography are (1) complicated media and (2) rather limited acquisition geometries. Existing algorithms solve the limited‐view problem in an iterative manner, but are valid only for line sources and 2-D homogeneous background models. In this paper, we derive an iterative algorithm based on asymptotic wave theory that can compensate for a limited acquisition geometry. The method is valid for a 2-D nonuniform background model and point‐source illumination (i.e., a 2.5-D geometry). Paraxial ray tracing is employed to model the arbitrary background wave response, and the general structure of the algorithm has a strong resemblance to the iterative ART‐algorithm used in straight ray tomography. Our method is shown to be stable in the presence of moderate white noise and gives reasonable results, both geometrically and quantitatively, when applied to synthetic crosshole data involving a nonhomogeneous background model and limited view.

3D modeling of a deepwater EM exploration survey

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. G239-G248 ◽  
Author(s):  
G. Michael Hoversten ◽  
Gregory A. Newman ◽  
Nathan Geier ◽  
Guy Flanagan
Keyword(s):  
Spatial Pattern ◽  
Electric Fields ◽  
Background Model ◽  
Electrical Anisotropy ◽  
3D Numerical Modeling ◽  
Water Contact ◽  
Magnetotelluric Data ◽  
Oil Water ◽  
Lateral Variations ◽  
Background Models

Analysis of a current offshore prospect employed 3D numerical modeling of a controlled-source electromagnetic (CSEM) exploration system. The analysis considers the sensitivity of data presentations to assumptions about the background model. The numerical simulations show that false anomalies and significant distortion to anomaly magnitude can be caused by normalization of the observed electric fields by reference fields calculated from an incorrect or oversimplified background model. Bathymetry effects on the measured electric fields, if not accounted for, can produce anomalies as large as those of target sands. The maximum sensitivity to oil-water contacts or other strong lateral variations within the modeled channel sands is achieved by profiling along the length of the channel. Profiles run offset from a simulated oil-water contact by as little as [Formula: see text] show a response below the expected noise levels. Good background models can be constructed by taking advantage of the magnetotelluric data recorded by marine receivers during times when the CSEM transmitter is not in operation. The effects of electrical anisotropy can produce anomalies as large as target responses, although the spatial pattern of sheetlike anisotropic zones can be distinguished from the spatial pattern of sand-channel anomalies.

scholarly journals Integrating Linear Arithmetic into Superposition Calculus

2007 ◽  
pp. 223-237 ◽  
Author(s):  
Konstantin Korovin ◽  
Andrei Voronkov
Keyword(s):  
Linear Arithmetic ◽  
Superposition Calculus

Antidepressant Black Box Warning Draws Fire by Not Including Suicide Causality

2005 ◽  
Vol 39 (3) ◽  
pp. 24
Author(s):  
KATE JOHNSON
Keyword(s):  
Black Box

FDA: Contrast Agent Black Box Behind NSF Reduction

2010 ◽  
Vol 41 (1) ◽  
pp. 10
Author(s):  
KERRI WACHTER
Keyword(s):  
Contrast Agent ◽  
Black Box
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