Robust Structured Low-Rank Approximation on the Grassmannian

Over the past years Robust PCA has been established as a standard tool for reliable low-rank approximation of matrices in the presence of outliers. Recently, the Robust PCA approach via nuclear norm minimization has been extended to matrices with linear structures which appear in applications such as system identification and data series analysis. At the same time it has been shown how to control the rank of a structured approximation via matrix factorization approaches. The drawbacks of these methods either lie in the lack of robustness against outliers or in their static nature of repeated batch-processing. We present a Robust Structured Low-Rank Approximation method on the Grassmannian that on the one hand allows for fast re-initialization in an online setting due to subspace identification with manifolds, and that is robust against outliers due to a smooth approximation of the $\ell_p$-norm cost function on the other hand. The method is evaluated in online time series forecasting tasks on simulated and real-world data

Effects of two oil dispersants on phototaxis and swimming behaviour of barnacle larvae

The effects of two oil dispersants (Vecom B-1425 GL and Norchem OSD-570) mixed with diesel oil on the survival and behaviour of the stage II nauplii of the barnacle Balanus amphitrite were investigated. The 24 and 48-hour LC50 values for Vecom B-1425 GL:diesel mixture were 514 and 48 mg 1-1 respectively, while respective values for Norchem OSD-570:diesel mixture were 505 and 71 mg 1-1. Under sublethal concentrations, increased levels of the dispersant:diesel mixtures caused a reduction in phototactic responses. Balanus amphitrite nauplii failed to exhibit phototactic responses when exposed to Vecom B-1425 GL:diesel mixtures of 400 mg 1-1 and higher for 24 hours. A longer exposure time of 48 hours further reduced the Lowest Observable Effect Concentrations (LOECs) to 60 mg 1-1. The LOECs for Norchem OSD-570:diesel mixtures under exposure periods of 24 and 48 hours were 400 and 80 mg 1-1 respectively. The curvilinear velocities (VCL) and straight-line velocities (VSL) of the stage II nauplii ranged from 0.7-1.1 and 0.2-0.4 mm s-1 respectively. Increased concentrations of dispersant:diesel mixtures caused a significant change in the curvilinear and straight-line velocities. Both oil dispersants, dispersant:diesel mixtures of 20 to 40 mg 1-1 caused significant increases in VCL, but no significant change in VSL. Dispersant:diesel mixtures of 100 mg 1-1 and higher resulted in a reduction in VSL for both dispersants. ©1997 Kluwer Academic Publishers.link_to_subscribed_fulltex

A Study of Grid Artifacts Formation and Elimination in Computed Radiographic Images

Computed radiography (CR) has many advantages such as filmless operations, efficiency, and convenience. Furthermore, it is easier to integrate with the picture archiving and communication systems. Another important advantage is that CR images generally have a wider dynamic range than conventional screen film. Unfortunately, grid artifacts and moiré pattern artifacts may be present in CR images. These artifacts become a more serious problem when viewing CR images on a computer monitor when a clinic grade monitor is not available. Images produced using a grid with higher frequency or a Potter–Bucky grid (i.e., a moving grid, Bucky for short) can reduce occurrence but cannot guarantee elimination of these artifacts [CR & PACS (2000); Detrick F (2001), pp 7–8]. In this paper, the formation of the artifacts is studied. We show that the grid artifacts occur in a narrow band of frequency in the frequency domain. The frequency can be determined, accurately located, and thus removed from the frequency domain. When comparing the results obtained from the proposed method against the results obtained using previous computer methods, we show that our method can achieve better image quality

Nový jednoduchý, rychlý a robustní výpočet totálních nejmenších čtvercových chyb v e2: Experimentální srovnání

Mnoho problémů, nejen při zpracování signálů, zpracování obrazu, digitálním zobrazování, počítačovém vidění a vizualizaci, vede k problému s nejmenším čtvercovým omylem (LSE) nebo k výpočtu celkového (ortogonálního) problému s chybou nejmenšího čtverce (TLSE). Obvykle se používá metoda nejmenších čtvercových chyb pro aproximaci vzhledem ke své jednoduchosti, ale není to optimální řešení, protože neopravňuje ortogonální vzdálenosti, ale pouze vertikální vzdálenosti. Existuje mnoho problémů, pro které není LSE vhodné a TLSE se používá. Bohužel, TLSE je výpočtově mnohem dražší. Tento článek představuje nový, jednoduchý, robustní a rychlý algoritmus pro výpočet nejmenších čtvercových chyb v E2.Many problems, not only in signal processing, image processing, digital imaging, computer vision and visualization, lead to the Least Square Error (LSE) problem or Total (Orthogonal) Least Square Error (TLSE) problem computation. Usually the standard least square error approximation method is used due to its simplicity, but it is not an optimal solution, as it does not optimize the orthogonal distances, but only the vertical distances. There are many problems for which the LSE is not convenient and the TLSE is to be used. Unfortunately, the TLSE is computationally much more expensive. This paper presents a new, simple, robust and fast algorithm for the total least square error computation in E2