Reducing impacts of systematic errors in the observation data on inversing ecosystem model parameters using different normalization methods L. Zhang, M. Xu, M. Huang, and G. Yu Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing, China Received: 31 August 2009 – Accepted: 24 October 20...

trabeculectomy is the most common procedure performed in glaucoma patients to reduce intraocular pressure for a long-time period. this intervention can cause alterations in axial length (0.1-0.9 mm), anterior chamber depth (0.11±0.22 mm), and keratometry readings (1.07±1.14 diopter). these changes may linger for more than one year and may negatively affect the precision of intraocular lens powe...

This paper introduces a method for measuring odometry errors in mobile robots and for expressing these errors quantitatively. When measuring odometry errors, one must distinguish between (1) systematic errors, which are caused by kinematic imperfections of the mobile robot (for example, unequal wheel-diameters), and (2) non-systematic errors, which may be caused by wheel-slippage or irregularit...

we present an approach to design of fault tolerant computing systems. in this paper, a technique is employed that enable the combination of several codes, in order to obtain flexibility in the design of error correcting codes. code combining techniques are very effective, which one of these codes are turbo codes. the algorithm-based fault tolerance techniques that to detect errors rely on the c...

We present an improved version of the POTENT method for reconstructing the velocity and mass density fields from radial peculiar velocities, test it with mock catalogs, and apply it to the Mark III Catalog of Galaxy Peculiar Velocities. The method is improved in several ways: (a) the inhomogeneous Malmquist bias is reduced by grouping and corrected statistically in either forward or inverse ana...

We consider the multiple-response regression problem, where the response is subject to sparse gross errors, in the high-dimensional setup. We propose a tractable regularized M-estimator that is robust to such error, where the sum of two individual regularization terms are used: the first one encourages row-sparse regression parameters, and the second one encourages a sparse error term. We obtai...

In this study, a duration{based measure is formulated for assigning con dence scores to phonetic time{alignments produced by an automatic speech segmentation system. For speech corrupted by additive noise or telephone channel environments, the proposed con dence measure is shown to provide a reliable means by which gross segmentation errors can be automatically detected and marked for human han...