5,622 research outputs found

    What role is there for the state in contemporary governance? Insights from the Dutch building sector

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    An emerging body of empirical governance studies highlights that the role of the state in governance has been changing. It has moved away from governing societal problems solely through traditional direct regulatory interventions. State actors are now (also) taking up facilitative and enabling roles in innovative voluntary governance arrangements. This article seeks to gain a better understanding of these facilitating and enabling roles of state actors in real world practice and what (clusters of) roles are needed to obtain successful outcomes from these arrangements. It builds on an empirical study of ten different arrangements in the Dutch sustainable building sector, which are analysed using fuzzy set qualitative comparative analysis (fsQCA) methodology. It finds no evidence that any of the specific (clusters of) role(s) is necessary to achieve positive outcomes from the arrangements studied, but uncovers that when combined, such roles affect the outcomes of arrangements. It concludes by presenting an evidence-based typology of combinations of roles that state actors may wish to take up in seeking positive outcomes from innovative voluntary governance arrangements, or preventing negative outcomes

    Local Stereo Matching Using Adaptive Local Segmentation

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    We propose a new dense local stereo matching framework for gray-level images based on an adaptive local segmentation using a dynamic threshold. We define a new validity domain of the fronto-parallel assumption based on the local intensity variations in the 4-neighborhood of the matching pixel. The preprocessing step smoothes low textured areas and sharpens texture edges, whereas the postprocessing step detects and recovers occluded and unreliable disparities. The algorithm achieves high stereo reconstruction quality in regions with uniform intensities as well as in textured regions. The algorithm is robust against local radiometrical differences; and successfully recovers disparities around the objects edges, disparities of thin objects, and the disparities of the occluded region. Moreover, our algorithm intrinsically prevents errors caused by occlusion to propagate into nonoccluded regions. It has only a small number of parameters. The performance of our algorithm is evaluated on the Middlebury test bed stereo images. It ranks highly on the evaluation list outperforming many local and global stereo algorithms using color images. Among the local algorithms relying on the fronto-parallel assumption, our algorithm is the best ranked algorithm. We also demonstrate that our algorithm is working well on practical examples as for disparity estimation of a tomato seedling and a 3D reconstruction of a face

    Detection of the tulip breaking virus (TBV) in tulips using optical sensors

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    The tulip breaking virus (TBV) causes severe economic losses for countries that export tulips such as the Netherlands. Infected plants have to be removed from the field as soon as possible. There is an urgent need for a rapid and objective method of screening. In this study, four proximal optical sensing techniques for the detection of TBV in tulip plants were evaluated and compared with a visual assessment by crop experts as well as with an ELISA (enzyme immunoassay) analysis of the same plants. The optical sensor techniques used were an RGB color camera, a spectrophotometer measuring from 350 to 2500 nm, a spectral imaging camera covering a spectral range from 400 to 900 nm and a chlorophyll fluorescence imaging system that measures the photosynthetic activity. Linear discriminant classification was used to compare the results of these optical techniques and the visual assessment with the ELISA score. The spectral imaging system was the best optical technique and its error was only slightly larger than the visual assessment error. The experimental results appear to be promising, and they have led to further research to develop an autonomous robot for the detection and removal of diseased tulip plants in the open field. The application of this robot system will reduce the amount of insecticides and the considerable pressure on labor for selecting diseased plants by the crop expert. © 2010 The Author(s
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