Similarity evaluation of topography measurement results by different optical metrology technologies for additive manufactured parts

The surface topographic measurements can be used by the additive manufacturing (AM) industry for in-situ quality inspection. However, disagreements may arise when we use different technologies to measure the topography of the same sample surface due to noise, sampling or optical properties of the sample surface, which may cause miscommunications or confusions between manufacturers. Thus, proposing methods for rating the similarities to match surface topographic data measured by various optical techniques is of crucial importance. This research investigates similarity evaluation methods for three-dimensional point-cloud topography data acquired by different technologies. Two different optical techniques (focus variation microscopy and structured light scanning) are used as testbeds. We propose two similarity evaluation methods for three-dimensional point-cloud data based on image distance method and Pearson’s correlation coefficient. The experimental results demonstrate that the proposed methods are effective and informative in determining whether the measured data are collected from the same sample, even though the measuring systems have different working principles and resolutions. This research facilitates our understanding of the discrepancies between different measuring systems, and meanwhile benefits a cyber-manufacturing system where unified inspection methods are unavailable among different manufacturers sharing the metrology data in cyber space

NerveFormer: A Cross-Sample Aggregation Network for Corneal Nerve Segmentation

The segmentation of corneal nerves in corneal confocal microscopy (CCM) is of great to the quantification of clinical parameters in the diagnosis of eye-related diseases and systematic diseases. Existing works mainly use convolutional neural networks to improve the segmentation accuracy, while further improvement is needed to mitigate the nerve discontinuity and noise interference. In this paper, we propose a novel corneal nerve segmentation network, named NerveFormer, to resolve the above-mentioned limitations. The proposed NerveFormer includes a Deformable and External Attention Module (DEAM), which exploits the Transformer-based Deformable Attention (TDA) and External Attention (TEA) mechanisms. TDA is introduced to explore the local internal nerve features in a single CCM, while TEA is proposed to model global external nerve features across different CCM images. Specifically, to efficiently fuse the internal and external nerve features, TDA obtains the query set required by TEA, thereby strengthening the characterization ability of TEA. Therefore, the proposed model aggregates the learned features from both single-sample and cross-sample, allowing for better extraction of corneal nerve features across the whole dataset. Experimental results on two public CCM datasets show that our proposed method achieves state-of-the-art performance, especially in terms of segmentation continuity and noise discrimination

Perceção de mulheres grávidas relativamente à informação disponível acerca do consumo de álcool durante a gravidez

info:eu-repo/semantics/draf

A Superior Way for the Transforming China: The Ultimate Ideal or a Feasible Solution?

6 Halama

Recent research progress on planetary waves in the middle and upper atmosphere during sudden stratospheric warmings

Sudden stratospheric warming (SSW) is a violent atmospheric disturbance in the polar region of the winter hemisphere. The drastic changes in temperature and wind during SSWs are considered to be the main reasons for the abnormal increase in the energy of atmospheric waves in the upper and middle atmosphere in the winter hemisphere. Meteor radar is an important ground-based detection equipment that can stably and continuously detect neutral wind in the mesosphere and lower thermosphere (MLT) region. Based on one of the National Major Science Infrastructure Projects, the "Meridian Project", China has built several meteor radar observation stations to conduct long-term stable and continuous monitoring of the neutral wind in the MLT region, which provides important observation data for revealing the physical mechanism of abnormal changes in atmospheric waves during SSWs. Here, we briefly review the research progress on planetary waves in the middle and upper atmosphere during SSWs in recent years, especially the scientific findings based on the meteor radars in the Chinese "Meridian Project". The trigger mechanisms of the enhanced planetary waves during SSWs are discussed. With the completion of ten meteor radars in the second phase of the "Meridian Project", this paper prospects the use of its meteor radar monitoring network to further study the characteristics of atmospheric waves in the middle and upper atmosphere during SSWs

Similarity evaluation of 3D surface topography measurements

With the recent advances in three-dimensional (3D) optical scanning technologies, 3D surface topography measurement plays an increasingly important role in many fields, such as product quality inspection in additive manufacturing (AM), gauge capability analysis, and firearm identification in forensic science. In this paper, we establish a thorough and flexible new framework of surface topography data comparison that generates a scaled similarity score for a pair of measurements, and distinguishes matched and non-matched pairs based on the score. If two measurements are portraying the same surface, they are defined as a matched pair. If not, they are defined as a non-matched pair. This similarity evaluation framework can be very useful in comparing optical scanning systems, quantifying different sources of variation in a process, and monitoring the stability and uniformity of a process, thus has a great potential to improve the quality assurance cycle of AM processes in the long run. We illustrate the framework and statistically evaluate the binary classification performance on data measured from additive manufactured parts on a large scale. We also examine how different systems, repeated measurements, and operators affect the similarity score and classification performance. We compare our work with a baseline method using the surface roughness average parameter Ra. The results show that the methodology can distinguish matched and non-matched pairs with high accuracy, and it outperforms the baseline method greatly. The framework serves as a benchmark method and can be generalized to be used in other fields where surface topography plays a critical role.This is the Accepted Manuscript version of an article accepted for publication in Measurement Science and Technology. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it.  The Version of Record is available online at DOI: 10.1088/1361-6501/ac1b41. Copyright 2019 IOP Publishing Ltd. CC BY-NC-ND 4.0. Posted with permission

The Combination of Transformer and You Only Look Once for Automatic Concrete Pavement Crack Detection

The real-time detection of cracks is an important part of road maintenance and an important initiative to reduce traffic accidents caused by road cracks. In response to the lack of efficiency of current research results for the real-time detection of road cracks and the low storage and computational capacity of edge devices, a new automatic crack detection algorithm is proposed: BT–YOLO. We combined Bottleneck Transformer with You Only Look Once (YOLO), which is more conducive to extracting the features of small cracks than YOLOv5s. The introduction of DWConv to the feature extraction network reduced the number of parameters and improved the inference speed of the network. We embedded the SimAM (Simple, Parameter-Free Attention Module) non-parametric attention mechanism to make the crack features more prominent. The experimental results showed that the accuracy of BT–YOLO in crack detection was increased by 4.5%, the mapped value was increased by 8%, and the parameter amount was decreased by 24.9%. Eventually, we deployed edge devices for testing. The frame rate reached 89, which satisfied the requirements of real-time crack detection

Replication Data for: Surface Topography Measurement Similarity Evaluation

This dataset contains scanning data from two scanning systems (SLS and FVM), three operators (Jennifer, Kelsey, and Lara). "w" in folder name indicates window; "s" indicates sample; "t" indicates trial. FVM restores point-clouds with .csv, where three columns are "y", "x", "z". SLS restores point-clouds with .ply, where three columns are "x", "y", "z"