Reduction of JT8D powered aircraft noise by engine refanning

The technical feasibility is described of substantially reducing the noise levels of existing JT8D powered aircraft by retrofitting the existing fleet with quieter refan engines and new acoustically treated nacelles. No major technical problems exist that preclude the development and installation of refanned engines on aircraft currently powered by the JT8D engine. The refan concept is technically feasible and provides calculated noise reductions of from 7 to 8 EPNdb for the B727-200 aircraft and from 10 to 12 EPNdb for the DC-9-32 aircraft at the FAR Part 36 measuring stations. These noise levels are lower than both the FAR Part 36 noise standards and the noise levels of the wide-body DC-10-10. Corresponding reductions in the 90 EPNdb footprint area are estimated to vary from about 70 percent for the DC-9 to about 80 percent for the B727

Multispecies Fruit Flower Detection Using a Refined Semantic Segmentation Network

In fruit production, critical crop management decisions are guided by bloom intensity, i.e., the number of flowers present in an orchard. Despite its importance, bloom intensity is still typically estimated by means of human visual inspection. Existing automated computer vision systems for flower identification are based on hand-engineered techniques that work only under specific conditions and with limited performance. This letter proposes an automated technique for flower identification that is robust to uncontrolled environments and applicable to different flower species. Our method relies on an end-to-end residual convolutional neural network (CNN) that represents the state-of-the-art in semantic segmentation. To enhance its sensitivity to flowers, we fine-tune this network using a single dataset of apple flower images. Since CNNs tend to produce coarse segmentations, we employ a refinement method to better distinguish between individual flower instances. Without any preprocessing or dataset-specific training, experimental results on images of apple, peach, and pear flowers, acquired under different conditions demonstrate the robustness and broad applicability of our method

Geometrical CP violation in multi-Higgs models

We introduce several methods to obtain calculable phases with geometrical values that are independent of arbitrary parameters in the scalar potential. These phases depend on the number of scalars and on the order of the discrete non-Abelian group considered. Using these methods we present new geometrical CP violation candidates with vacuum expectation values that must violate CP (the transformation that would make them CP conserving is not a symmetry of the potential). We also extend to non-renormalisable potentials the proof that more than two scalars are needed to obtain these geometrical CP violation candidates.Comment: 8 pages, 2 figures. v2: table added, accepted by JHE