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Bounding overwatch
About: Bounding overwatch is a research topic. Over the lifetime, 966 publications have been published within this topic receiving 15156 citations.
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TL;DR: In this article , a quasi-steady aerodynamic model whose force and torque coefficients are informed by experimental measurements is proposed to reproduce the observed motions of paper planes in air and plates in water.
Abstract: Abstract Falling paper flutters and tumbles through air, whereas a paper airplane glides smoothly if its leading edge is appropriately weighted. We investigate this transformation from ‘plain paper’ to ‘paper plane’ through experiments, aerodynamic modelling and free flight simulations of thin plates with differing centre of mass (CoM) locations. Periodic modes such as fluttering, tumbling and bounding give way to steady gliding and then downward diving as the CoM is increasingly displaced towards one edge. To explain these observations, we formulate a quasi-steady aerodynamic model whose force and torque coefficients are informed by experimental measurements. The dependencies on angle of attack reflect the transition from attached to separated flow and a dynamic centre of pressure, effects that prove critical to reproducing the observed motions of paper planes in air and plates in water. Because the model successfully accounts for unsteady and steady flight modes, it may be usefully applied to further problems involving actuated motions, feedback control and interactions with ambient flows.
3 citations
TL;DR: In this article , an effective numerical scheme for solving impulsive fractional differential equations is proposed, where Hermite interpolation is used to approximate fractional-order integrals and convergence analysis is studied in detail by bounding the approximation error.
Abstract: This paper proposes an effective numerical scheme for solving impulsive fractional differential equations. For this purpose, Hermite interpolation is used to approximate fractional-order integrals. The proposed methods convergence analysis is studied in detail by bounding the approximation error. Finally, the application and performance of the presented method are illustrated in two practical examples, including the impulsive control of the family of Lorenz systems, and the obtained results are compared with an existing method.
3 citations
TL;DR: Wang et al. as mentioned in this paper introduced the first semi-supervised point cloud instance segmentation framework (SPIB) using both labeled and unlabeled bounding boxes as supervision, which involves a two-stage learning procedure.
Abstract: Point cloud instance segmentation has achieved huge progress with the emergence of deep learning. However, these methods are usually data-hungry with expensive and time-consuming dense point cloud annotations. To alleviate the annotation cost, unlabeled or weakly labeled data is still less explored in the task. In this paper, we introduce the first semi-supervised point cloud instance segmentation framework (SPIB) using both labeled and unlabelled bounding boxes as supervision. To be specific, our SPIB architecture involves a two-stage learning procedure. For stage one, a bounding box proposal generation network is trained under a semi-supervised setting with perturbation consistency regularization (SPCR). The regularization works by enforcing an invariance of the bounding box predictions over different perturbations applied to the input point clouds, to provide self-supervision for network learning. For stage two, the bounding box proposals with SPCR are grouped into some subsets, and the instance masks are mined inside each subset with a novel semantic propagation module and a property consistency graph module. Moreover, we introduce a novel occupancy ratio guided refinement module to refine the instance masks. Extensive experiments on the challenging ScanNet v2 dataset demonstrate our method can achieve competitive performance compared with the recent fully-supervised methods.
3 citations
TL;DR: Wang et al. as discussed by the authors proposed a semi-supervised real-time method based on the Siamese network using a new polar representation, which reduced the parameters for encoding masks with subtle accuracy loss so that the algorithm speed can be improved significantly.
3 citations
10 Nov 2009
TL;DR: Families of upper bounding models are proposed for the response time of composite Web services for two kinds of composition: the statical and random « fork and merge ».
Abstract: The quality of service (QoS) of Web services is a key factor of their success. This requires to design new methods in order to study it. Here we propose families of upper bounding models for the response time of composite Web services for two kinds of composition: the statical and random « fork and merge ». In the r st case, the complexity of bounding models belongs to O(n p n) where n is the number of called services whereas the complexity of the exact model belongs to O(n 2 ). In the second case, the complexity of bounding models still belongs to O(n p n) whereas the complexity of the exact model belongs to O(n 3 ). Furthermore, having a family of bounding models allows to choose the bounding model depending on the parameters of the exact model. The numerical results show the interest of our approach w.r.t. complexity and accuracy of the bound.
3 citations