On the aeroacoustic and flow structures developed on a flat plate with a serrated sawtooth trailing edge

Open Access funded by Engineering and Physical Sciences Research Council.Results of an experimental study on turbulent flow over a flat plate with a serrated sawtooth trailing edge are presented in this paper. After tripping the boundary layer to become turbulent, the broadband noise sources at the sawtooth serrated trailing edge is studied by several experimental techniques. Broadband noise reduction by the serrated sawtooth trailing edge can be realistically achieved in the flat plate configuration. The variations of wall pressure power spectral density and the spanwise coherence (which relates to the spanwise correlation length) in a sawtooth trailing edge play a minor role in the mechanisms underpinning the reduction of self noise radiation. Conditional-averaging technique was applied in the boundary layer data where a pair of pressure-driven oblique vortical structures near the sawtooth side edges is identified. In the current flat plate configuration, the interaction between the vortical structures and the local turbulent boundary layer results in a redistribution of the momentum transport and turbulent shear stress near the sawtooth side edges as well as the sawtooth tip, thus affecting the efficiency of self noise radiation.The authors are grateful for the support from the EPSRC Doctoral Training Grants in the United Kingdom

Proceedings of the NASA Workshop on Image Analysis

Three major topics of image analysis are addressed: segmentation, shape and texture analysis, and structural analysis

Temperature and velocity measurements in turbulent plumes

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Perception of visual forms in intensely noisy television images

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Attention and visual memory in visualization and computer graphics

Abstract—A fundamental goal of visualization is to produce images of data that support visual analysis, exploration, and discovery of novel insights. An important consideration during visualization design is the role of human visual perception. How we “see ” details in an image can directly impact a viewer’s efficiency and effectiveness. This paper surveys research on attention and visual perception, with a specific focus on results that have direct relevance to visualization and visual analytics. We discuss theories of low-level visual perception, then show how these findings form a foundation for more recent work on visual memory and visual attention. We conclude with a brief overview of how knowledge of visual attention and visual memory is being applied in visualization and graphics. We also discuss how challenges in visualization are motivating research in psychophysics

Models and Analysis of Vocal Emissions for Biomedical Applications

The International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy

Use of multi-scale phase-based methods to determine optical flow in dynamic scene analysis

Estimates of optical flow in images can be made by applying a complex periodic transform to the images and tracking the movement of points of constant phase in the complex output. This approach however suffers from the problem that filters of large width give information only about broad scale image features, whilst those of small spatial extent (high resolution) cannot track fast motion, which causes a feature to move a distance that is large compared to the filter-size. A method is presented in which the flow is measured at different scales, using a series of complex filters of decreasing width. The largest filter is used to give a large scale flow estimate at each image point. Estimates at smaller scales are then carried out by using the previous result as an a priori estimate. Rather than comparing the same region in different images in order to estimate flow, the regions to be compared are displaced from one another by an amount given by the most recent previous flow estimate. This results in an estimate of flow relative to the earlier estimate. The two estimates are then added together to give a new estimate of the absolute displacement. The process is repeated at successively smaller scales. The method can therefore detect small local velocity variations superimposed on the broad scale flow, even where the magnitude of the absolute displacement is larger than the scope of the smaller filters. Without the assistance of the earlier estimates in ‘tuning\u27 the smaller filters in this manner, a smaller filter could fail to capture these velocity variations, because the absolute displacement carry the feature out of range of-the filter during successive frames. The output of the method is a series of scale-dependent flow fields corresponding to different scales, reflecting the fact that motion in the real world is a scale-dependent quantity. Application of the method to some 1 dimensional test images gives good results, with realistic flow values that could be used as an aid to segmentation. Some synthetic 2-dimentional images containing only a small number of well defined features aIso yield good-results but the method performs poorly on a random-dot stereogram and on a real-world test image pair selected from the Hamburg Taxi sequence

Exploitation d'indices visuels liés au mouvement pour l'interprétation du contenu des séquences vidéos

L'interprétation du contenu des séquences vidéo est un des principaux domaines de recherche en vision artificielle. Dans le but d'enrichir l'information provenant des indices visuels qui sont propres à une seule image, on peut se servir d'indices découlant du mouvement entre les images. Ce mouvement peut être causé par un changement d'orientation ou de position du système d'acquisition, par un déplacement des objets dans la scène, et par bien d'autres facteurs. Je me suis intéressé à deux phénomènes découlant du mouvement dans les séquences vidéo. Premièrement, le mouvement causé par la caméra, et comment il est possible de l'interpréter par une combinaison du mouvement apparent entre les images, et du déplacement de points de fuite dans ces images. Puis, je me suis intéressé à la détection et la classification du phénomène d'occultation, qui est causé par le mouvement dans une scène complexe, grâce à un modèle géométrique dans le volume spatio-temporel. Ces deux travaux sont présentés par le biais de deux articles soumis pour publication dans des revues scientifiques