background: two questions about diagnostic value of urinary neutrophil gelatin associated lipocalin (ungal) in detection of acute kidney injury (aki) in children have remained unanswered; first, which cut-off point of ungal has the highest value in detection of aki; and second when is the best time for measuring this biomarker in a patient? accordingly, the present study aimed to conduct a syst...

In this paper, a Bayesian approach is proposed for shift point detection in an inverse Gaussian distribution. In this study, the mean parameter of inverse Gaussian distribution is assumed to be constant and shift points in shape parameter is considered. First the posterior distribution of shape parameter is obtained. Then the Bayes estimators are derived under a class of priors and using variou...

In this work we present an automatic algorithm to detect basic shapes in unorganized point clouds. The algorithm decomposes the point cloud into a concise, hybrid structure of inherent shapes and a set of remaining points. Each detected shape serves as a proxy for a set of corresponding points. Our method is based on random sampling and detects planes, spheres, cylinders and cones. For models w...

The detection of change-points in a spatially or time ordered data sequence is an important problem in many fields such as genetics and finance. We derive the asymptotic distribution of a statistic recently suggested for detecting change-points. Simulation of its estimated limit distribution leads to a new and computationally efficient change-point detection algorithm, which can be used on very...

We consider the testing and estimation of change-points—locations where the distribution abruptly changes—in a data sequence. A new approach, based on scan statistics utilizing graphs representing the similarity between observations, is proposed. The graph-based approach is nonparametric, and can be applied to any data set as long as an informative similarity measure on the sample space can be ...

This paper explores a Bayesian method for the detection of sudden changes in the generative parameters of a data series. The problem is phrased as a hidden Markov model, where change point locations correspond to unobserved states, which grow in number with the number of observations. Our interest lies in the marginal change point posterior density. Rather than optimize a likelihood function of...

This paper evaluates 2D feature detection methods with respect to invariance and efficiency properties. The studied feature detection methods are as follows: Speeded Up Robust Features, Scale Invariant Feature Transform, Binary Robust Invariant Scalable Keypoints, Oriented Binary Robust Independent Elementary Features, Features from Accelerated Segment Test, Maximally Stable Extremal Regions, B...

As scientific computation continues to scale, it is crucial to use floating-point arithmetic processors as efficiently as possible. Lower precision allows streaming architectures to perform more operations per second and can reduce memory bandwidth pressure on all architectures. However, using a precision that is too low for a given algorithm and data set will result in inaccurate results. Thus...