The Shear-Slip Mesh Update Method, designed to handle certain classes of flow problems with moving boundaries and interfaces, is presented. Specifically, we focus on problems with large but regular boundary displacements, such as straight-line translation or rotation. These motions are accommodated by using a thin layer of deforming space-time elements, together with limited remeshing without a...

For a probability distribution with power law tails, a log–log transformation makes the tails of the empirical distribution function resemble a straight line, leading to a least-squares estimate of the tail thickness. Taking into account the mean and covariance structure of the extreme order statistics leads to improved tail estimators, and a surprising connection with Hill’s estimator. c © 200...

Approximation of noisy data in the plane by straight lines or elliptic: or single-branch hyperbolic curve segments arises in pattern recogniticn, data compaction, and other problems. A number of questions concerning the efficient search fo_ and approximation of data by such curves are examined. Fecursive least-squares linear curve-fitting is used, and ellipses and hyperbolas are parameterized a...

Parametric regression (least-squares) techniques are used to estimate a statistical model that attempts to predict a variable based on one, or more, other variables. The model is required to have a specified algebraic form such as a straight line, a parabola, or an exponential curve. An example would be predicting a persons annual income based on their age, years of schooling and gender using a...

This report presents a methodology for missing value imputation. The methodology is based on an ensemble of Self-Organizing Maps (SOM), which is weighted using Nonnegative Least Squares algorithm. Instead of a need for lengthy validation procedure as when using single SOMs, the ensemble proceeds straight into final model building. Therefore, the methodology has very low computational time while...

This paper presents a new algorithm that is capable of extracting circles from complicated and heavily corrupted images. The algorithm uses a least-squares fitting algorithm for arc segments. The arcs are segmented by using the short straight lines which are extracted by a fast line extraction algorithm. The arc segments are used to yield accurate circle parameters. Tests performed on synthetic...

We demonstrate a new generalized least-squares fitting method which can be used to estimate the slope of the best-fitting straight line that results when two separate data sets which are expected to be linearly correlated are subject to different uncertainties in their measurements. The algorithm determines not only the optimum slope, but also produces estimates of the intrinsic errors associat...

Abstract This work is to demonstrate a low cost and time-conserving technique create nano-trenches by transferring nano-scale polymeric sidewalls into substrate. The sidewall vertically spreading layer deposited spin-coating polymer solution on vertical template. By varying processing parameters such as the concentration or speed, dimension of can be changed, which, after pattern transfer, also...

The paper presents a general paradigm of semiautomatic house extraction from aerial stereo image pair. In the semiautomatic extraction system, the house model is defined as the one with multi right angles roof, then under the knowledge of the roof type, low-level and mid-level processing including edge detection, straight line segments extraction and obtaining initial house corners are used to ...

A family of subtraction-based anomalous change detection algorithms is derived from a total least squares (TLSQ) framework. This provides an alternative to the well-known chronochrome algorithm, which is derived from ordinary least squares. In both cases, the most anomalous changes are identified with the pixels that exhibit the largest residuals with respect to the regression of the two images...