Cosmic Ray Rejection by Linear Filtering of Single Images

We present a convolution-based algorithm for finding cosmic rays in single well-sampled astronomical images. The spatial filter used is the point spread function (approximated by a Gaussian) minus a scaled delta function, and cosmic rays are identified by thresholding the filtered image. This filter searches for features with significant power at spatial frequencies too high for legitimate objects. Noise properties of the filtered image are readily calculated, which allows us to compute the probability of rejecting a pixel not contaminated by a cosmic ray (the false alarm probability). We demonstrate that the false alarm probability for a pixel containing object flux will never exceed the corresponding probability for a blank sky pixel, provided we choose the convolution kernel appropriately. This allows confident rejection of cosmic rays superposed on real objects. Identification of multiple-pixel cosmic ray hits can be enhanced by running the algorithm iteratively, replacing flagged pixels with the background level at each iteration.Comment: Accepted for publication in PASP (May 2000 issue). An iraf script implementing the algorithm is available from the author, or from http://sol.stsci.edu/~rhoads/ . 16 pages including 3 figures. Uses AASTeX aaspp4 styl

Latitude: A Model for Mixed Linear-Tropical Matrix Factorization

Nonnegative matrix factorization (NMF) is one of the most frequently-used matrix factorization models in data analysis. A significant reason to the popularity of NMF is its interpretability and the `parts of whole' interpretation of its components. Recently, max-times, or subtropical, matrix factorization (SMF) has been introduced as an alternative model with equally interpretable `winner takes it all' interpretation. In this paper we propose a new mixed linear--tropical model, and a new algorithm, called Latitude, that combines NMF and SMF, being able to smoothly alternate between the two. In our model, the data is modeled using the latent factors and latent parameters that control whether the factors are interpreted as NMF or SMF features, or their mixtures. We present an algorithm for our novel matrix factorization. Our experiments show that our algorithm improves over both baselines, and can yield interpretable results that reveal more of the latent structure than either NMF or SMF alone.Comment: 14 pages, 6 figures. To appear in 2018 SIAM International Conference on Data Mining (SDM '18). For the source code, see https://people.mpi-inf.mpg.de/~pmiettin/linear-tropical

Max-Plus Algebraic Statistical Leverage Scores

The statistical leverage scores of a matrix A ∈ Rn×d record the degree of alignment between col(A) and the coordinate axes in Rn. These scores are used in random sampling algorithms for solving certain numerical linear algebra problems. In this paper we present a max-plus algebraic analogue of statistical leverage scores. We show that max-plus statistical leverage scores can be used to calculate the exact asymptotic behavior of the conventional statistical leverage scores of a generic radial basis function network (RBFN) matrix. We also show how max-plus statistical leverage scores can provide a novel way to approximate the conventional statistical leverage scores of a fixed, nonparametrized matrix

As goes the seminary : how seminaries are intentionally producing spiritually alive pastors

https://place.asburyseminary.edu/ecommonsatsdissertations/1232/thumbnail.jp

Performance analysis of asynchronous parallel Jacobi

The directed acyclic graph (DAG) associated with a parallel algorithm captures the partial order in which separaT.L.cal computations are completed and how their outputs are subsequently used in further computations. Unlike in a synchronous parallel algorithm, the DAG associated with an asynchronous parallel algorithm is not predetermined. Instead, it is a product of the asynchronous timing dynamics of the machine and cannot be known in advance, as such it is best thought of as a pseudorandom variable. In this paper, we present a formalism for analyzing the performance of asynchronous parallel Jacobi’s method in terms of its DAG. We use this app.roach to prove error bounds and bounds on the rate of convergence. The rate of convergence bounds is based on the statistical properties of the DAG and is valid for systems with a non-negative iteration matrix. We supp.ort our theoretical results with a suit of numerical examples, where we compare the performance of synchronous and asynchronous parallel Jacobi to certain statistical properties of the DAGs associated with the computations. We also present some examples of small matrices with elements of mixed sign, which demonstrate that determining whether a system will converge under asynchronous iteration in this more general setting is a far more difficult problem

The reliability and validity of screening measures in reading

National educational groups have recommended the use of universal screening to assist in the early identification of reading problems. One of the most widely used measures used for the universal screening of reading is oral reading fluency (ORF) (Fewster & Macmillan, 2002). However, ORF is somewhat time consuming to administer and has been reported to lack “face validity” with teachers (Fuchs, Fuchs & Maxwell, 1988). The purpose of this study was to investigate maze and other group-administered reading assessments because of their potential as a time efficient assessment that is as psychometrically valid as ORF. In this study, maze and a variation of maze known as sentence maze, both group-administered measures of basic reading performance and comprehension, were studied. A third assessment, picture word fluency, which measures a combination of site word reading and simple vocabulary, was also evaluated. The study consisted of two experiments. In the first experiment, these assessments were evaluated based on their psychometric adequacy, as well as their utility and accuracy for decision-making in the context of the requirements for universal screening. The purpose of the second experiment was to examine the generality of the results to another state with different criterion measures. A total of 789 regular education first, third and fifth grade students in two states participated in the two experiments. Students were administered CBM assessments and a criterion achievement measure. Two groups of validity analyses were reported: (a) those pertaining to concurrent/predictive validity, and (b) those pertaining to classification accuracy. These analyses revealed validity estimates for the two maze assessments similar to those shown in previous research studies. Similarly, the validity analyses for picture word fluency were also promising. Most germane to the evaluation of the screening measures was the classification accuracy analyses. Although the results were somewhat variable by grade, the results indicated that there was a moderate to high degree of concordance between those students identified as at risk by the group-administered CBM measures and the criterion measures used in this study, including ORF and the state accountability tests. The limitations of the study are discussed with suggestions for future research