The contribution of board structure and process dynamics to organiza tional and board effectiveness is the focus of this article. Based on data collected from a cross section of Canadian nonprofit organizations, the results show a positive association between the perception of board effec tiveness and the use of many of the most widely advocated prescriptions on how a nonprofit board of directors should operate. However, when objective indicators of organizational performance are examined, the link between performance and board behaviors is found to be more limited.
We propose the use of multiscale amplitude-modulation frequency-modulation (AM-FM) methods for discriminating between normal and pathological retinal images. The method presented in this paper is tested using standard images from the Early Treatment Diabetic Retinopathy Study (ETDRS). We use 120 regions of 40×40 pixels containing 4 types of lesions commonly associated with diabetic retinopathy (DR) and two types of normal retinal regions that were manually selected by a trained analyst. The region types included: microaneurysms, exudates, neovascularization on the retina, hemorrhages, normal retinal background, and normal vessels patterns. The cumulative distribution functions of the instantaneous amplitude, the instantaneous frequency magnitude, and the relative instantaneous frequency angle from multiple scales are used as texture features vectors. We use distance metrics between the extracted feature vectors to measure interstructure similarity. Our results demonstrate a statistical differentiation of normal retinal structures and pathological lesions based on AM-FM features. We further demonstrate our AM-FM methodology by applying it to classification of retinal images from the MESSIDOR database. Overall, the proposed methodology shows significant capability for use in automatic DR screening.
We develop new multiscale amplitude-modulation frequency-modulation (AM-FM) demodulation methods for image processing. The approach is based on three basic ideas: (i) AM-FM demodulation using a new multiscale filterbank, (ii) new, accurate methods for instantaneous frequency (IF) estimation, and (iii) multiscale least squares AM-FM reconstructions. In particular, we introduce a variable-spacing local linear phase (VS-LLP) method for improved instantaneous frequency (IF) estimation and compare it to an extended quasilocal method and the quasi-eigen function approximation (QEA). It turns out that the new VS-LLP method is a generalization of the QEA method where we choose the best integer spacing between the samples to adapt as a function of frequency. We also introduce a new quasi-local method (QLM) for IF and IA estimation and discuss some of its advantages and limitations. The new IF estimation methods lead to significantly improved estimates. We present different multiscale decompositions to show that the proposed methods can be used to reconstruct and analyze general images.
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