Effect of Tool Coatings on Machining Properties of Compacted Graphite Iron.

Compacted graphite iron (CGI) has become the most ideal material for automotive engine manufacturing owing to its excellent mechanical properties. However, tools are severely worn during processing, considerably shortening their lifespan. In this study, we prepared a series of cemented carbide-coated tools and evaluated their coating properties in cutting tests. Among all tested coatings, PVD coating made of AlCrN (AC) presented with the best surface integrity and mechanical properties, achieving the best comprehensive performance in the coating test. The AC-coated tool also exhibited the best cutting performance at a low speed of 120 m/min, corresponding to a 60% longer cutting life and the lowest workpiece surface roughness relative to other coated tools. In the cutting test at a high speed of 350 m/min, the CVD double-layer coated tool (MT) with a TiCN inner layer of and an Al2O3 outer layer had a 70% longer cutting life and the lowest workpiece surface roughness relative to other coated tools.

A novel approach to form Normal Distribution of Medical Image Segmentation based on multiple doctors' annotations.

Medical image segmentation annotated by experts provides the labeled data sets for many scientific researches. However, due to the unevenly experienced backgrounds of the experts and limited numbers of patients with certain diseases or illnesses, not only do such labeled data sets have smaller samples but their quality and normality also can range in wide variabilities and be ambiguous. In practice, these segmentations are usually assigned to be the ground truths for the scientific studies, so it may undermine the trustworthiness of the resulting findings. Therefore, it is meaningful to consider how to give a more unified opinion of the annotations among different experts. In this paper, a novel approach to form normal distributions of segmentation is proposed based on multiple doctors' annotations for the same patient. The proposed approach is developed through the following steps: (1) utilize a framework7 of averaging images to construct an averaged annotation based on different given annotations; (2) determine the image registration deformations from the averaged annotation to the given annotations; (3) build a joint multivariate Gaussian distribution over the logorithm of Jacobian determinants and curls of the registration deformations; lastly, (4) simulate a normal distribution of segmentation by the joint Gaussian distribution of registration deformation. This work translates the problem of forming a normal distribution of the image segmentation into a problem of forming joint Gaussian distribution of image registration deformations, which the latter can be reasoned by Jacobian determinant (models local size of pixel cells) and curl (models local rotation of pixel cells) information. In the following sections, a detailed walk-through of the proposed approach is provided along with its analytical mathematics and numerical examples for its effectiveness. A synthetic example of 3 manually defined label image is made to show how to construct a mean label image, and an example of a real cancer image annotated by 3 doctors demonstrates the formation of the normal distribution and the effectiveness of the propose method.