Correction to: Connecting Knowledge Compilation Classes and Width Parameters

Theory of Computing Systems - The article title in the original publication contains an error. The correct title is presented in this Erratum. The online version of the original article can be...     

MPM: a hierarchical clustering algorithm using matrix partitioning method for non-numeric data

The Publisher regrets that the original article incorrectly listed the authors’ location as the “People’s Republic of China”. This was a typesetting error. Their correct location is the “Republic of China”, which is also known as Taiwan. Their full affiliation is Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan. The online version of the original article can be found at .     

Erratum

Baraglia R, Ferrini R, Ritrovato P. A static mapping heuristics to map parallel applications to heterogeneous computing systems. Concurrency Computation: Practice and Experience 2005; 17 : 1579–1605. Due to a printing error, all of the equations in the above article were printed incorrectly. The correct version of the article can be viewed online at: http://www3.interscience.wiley.com/cgi‐bin/fulltext/110546382/PDFSTART The Publishers would like to apologise for any confusion that might have been caused by this error.     

Retracted and replaced: Software component composition: a subdomain‐based testing foundation

The following article from Software Testing, Verification and Reliability, Software component composition: a subdomain‐based testing foundation by Dick Hamlet published online on 14 June 2007 in Wiley InterScience ( www.interscience.wiley.com ), has been retracted by agreement between the author, the journal Editor‐in‐Chief Jeff Offutt and John Wiley & Sons, Ltd. The retraction has been agreed because the article was not ready for publication and an early version without revisions was published in error. Replacement article DOI: 10.1002/stvr.376 . Copyright © 2007 John Wiley & Sons, Ltd.     

Correction to: Darcy–Forchheimer flow and heat transfer augmentation of a viscoelastic fluid over an incessant moving needle in the presence of viscous dissipation

Microsystem Technologies - The original version of the article unfortunately contained an error in Acknowledgements section. Below is the corrected version.     

Analysis of a Discontinuous Finite Element Method for the Coupled Stokes and Darcy Problems

The coupled Stokes and Darcy flows problem is solved by the locally conservative discontinuous Galerkin method. Optimal error estimates for the fluid velocity and pressure are derived. This revised version was published online in July 2005 with corrected volume and issue numbers.     

Errata corrige

The online version of the original article can be found at     

A unified distance transform algorithm and architecture

The online version of the original article can be found at     

An A Posteriori Error Estimate for the Local Discontinuous Galerkin Method

In this work an a posteriori global error estimate for the Local Discontinuous Galerkin (LDG) applied to a linear second order elliptic problem is analyzed. Using a mixed formulation, an upper bound of the error in the primal variable is derived from explicit computations. Finally, a local adaptive scheme based on explicit error estimators is studied numerically using one dimensional problems.This revised version was published online in July 2005 with corrected volume and issue numbers.     

Edge-Oriented Spatial Interpolation for Error Concealment of Consecutive Blocks

This paper proposes a low-complexity spatial-domain error concealment （EC） algorithm for recovering consecutive blocks error in still images or intra-coded （I） frames of video sequences. The proposed algorithm works with the following steps. Firstly the Sobel operator is performed on the top and bottom adjacent pixels to detect the most probable edge direction of current block area. After that one-dimensional （1-D） matching is used on the available block boundaries. Displacement between edge direction candidate and most probable edge direction is taken into consideration as an important factor to improve stability of 1-D boundary matching. Then the corrupted pixels are recovered by linear weighting interpolation along the estimated edge direction. Finally the interpolated values are merged to get last recovered picture. Simulation results demonstrate that the proposed algorithms obtain good subjective quality and higher PSNR than the methods in literatures for most images.     

Author Correction: Customer support ticket escalation prediction using feature engineering

Requirements Engineering - The original version of this article contains an error in the Acknowledgements section. The correct text should read as follows.     

New results on recurrent network training: unifying the algorithmsand accelerating convergence

How to efficiently train recurrent networks remains a challenging and active research topic. Most of the proposed training approaches are based on computational ways to efficiently obtain the gradient of the error function, and can be generally grouped into five major groups. In this study we present a derivation that unifies these approaches. We demonstrate that the approaches are only five different ways of solving a particular matrix equation. The second goal of this paper is develop a new algorithm based on the insights gained from the novel formulation. The new algorithm, which is based on approximating the error gradient, has lower computational complexity in computing the weight update than the competing techniques for most typical problems. In addition, it reaches the error minimum in a much smaller number of iterations. A desirable characteristic of recurrent network training algorithms is to be able to update the weights in an online fashion. We have also developed an online version of the proposed algorithm, that is based on updating the error gradient approximation in a recursive manner.     

Adaptive divided difference filtering for simultaneous state and parameter estimation

A novel adaptive version of the divided difference filter (DDF) applicable to non-linear systems with a linear output equation is presented in this work. In order to make the filter robust to modeling errors, upper bounds on the state covariance matrix are derived. The parameters of this upper bound are then estimated using a combination of offline tuning and online optimization with a linear matrix inequality (LMI) constraint, which ensures that the predicted output error covariance is larger than the observed output error covariance. The resulting sub-optimal, high-gain filter is applied to the problem of joint state and parameter estimation. Simulation results demonstrate the superior performance of the proposed filter as compared to the standard DDF.     

Cascaded online boosting

In this paper, we propose a cascaded version of the online boosting algorithm to speed-up the execution time and guarantee real-time performance even when employing a large number of classifiers. This is the case for target tracking purposes in computer vision applications. We thus revise the online boosting framework by building on-the-fly a cascade of classifiers dynamically for each new frame. The procedure takes into account both the error and the computational requirements of the available features and populates the levels of the cascade accordingly to optimize the detection rate while retaining real-time performance. We demonstrate the effectiveness of our approach on standard datasets.     

How Online Reviews Interact with a Firm's Free Version Strategy

This study developed a game-theory model to explore interactions between online reviews and free version strategies. Results show that a firm could have four strategies as a strategic tool to respond best to availability of online reviews depending on the relative strength of network effect, cannibalization effect, and dispersed effect. Moreover, when offering a free version is the best strategy both with and without online reviews, online reviews and the free version strategy could still be both complementary and substitutive. This result provides possible theoretical explanations for mixed empirical conclusions regarding whether online reviews complement or substitute free version strategies.     

On performance evaluation in online approximation for control

This article analyzes the evaluation of approximation accuracy in online applications. In particular, it is first shown that the most commonly used approximation accuracy evaluation method (e.g., analysis of training or tracking error) is not in itself sufficient to demonstrate proper function approximation. In spite of this, many articles use tracking (training) errors as the means to demonstrate successful function approximation. This article presents two alternative methods for the evaluation of online performance. Related issues include probably approximately correct learning from statistics and persistence of excitation from adaptive control.     

基于FPGA实时错误检测技术

高可靠性的系统都要求具备实时错误检测。针对内建错误检测,提出了三种在线模型的自我实时检测方法。错误检测模型利用了现场可编程门阵列(FPGA)中的两个管道,通过比较当前配置信息与FPGA外配置内存中的原始信息是否一致,可以实时地检测错误,而且可以通过比较它们的配置数据来定位那些具有单粒子翻转(SEU)错误的逻辑块。仿真测试结果表明所提出的方法比在线BIST有着更好的性能。     

The local minima of the error surface of the 2-2-1 XOR network

All local minima of the error surface of the 2-2-1 XOR network are described. A local minimum is defined as a point such that all points in a neighbourhood have an error value greater than or equal to the error value in that point. It is proved that the error surface of the two-layer XOR network with two hidden units has a number of regions with local minima. These regions of local minima occur for combinations of the weights from the inputs to the hidden nodes such that one or both hidden nodes are saturated for at least two patterns. However, boundary points of these regions of local minima are saddle points. It will be concluded that from each finite point in weight space a strictly decreasing path exists to a point with error zero. This also explains why experiments using higher numerical precision find less “local minima”. This revised version was published online in June 2006 with corrections to the Cover Date.     

Software release policies with gain in reliability justifying the costs

An important question in the developing process of software products is when to stop testing to make the gain in reliability justify the costs. In this paper, a software reliability-cost model is presented to determine the optimal release policies that maximize the expected net gain in reliability. Several software cost factors are considered in this study, such as the cost of removing detected errors and the risk cost due to software failure. The error removal cost is modeled based on a stochastic process. A software reliability model based on the non-homogeneous Poisson process is used. Numerical examples are provided to illustrate the results. This revised version was published online in June 2006 with corrections to the Cover Date.     

A formal framework for on-line software version change

The usual way of installing a new version of a software system is to shut down the running program and then install the new version. This necessitates a sometimes unacceptable delay during which service is denied to the users of the software. An online software replacement system replaces parts of the software while it is in execution, thus eliminating the shutdown. While a number of implementations of online version change systems have been described in the literature, little investigation has been done on its theoretical aspects. We describe a formal framework for studying online software version change. We give a general definition of validity of an online change, show that it is in general undecidable and then develop sufficient conditions for ensuring validity for a procedural language