基于数据质量评价的目标估计

针对目标估计过程需要大量人工参与、自动化程度低的问题，提出了基于数据质量评价的目标估计方法。利用目标数据质量评价方法，对不同传感器得到的目标数据质量进行科学、有效的测度和评价，并根据质量得分动态调整各数据源在目标估计过程中所占的权重，从而减少人工干预，提高目标估计效能。仿真试验结果证明了该方法的有效性。     

Presentation attack detection based on two-stream vision transformers with self-attention fusion

Aiming at the performance degradation of the existing presentation attack detection methods due to the illumination variation, a two-stream vision transformers framework (TSViT) based on transfer learning in two complementary spaces is proposed in this paper. The face images of RGB color space and multi-scale retinex with color restoration (MSRCR) space are fed to TSViT to learn the distinguishing features of presentation attack detection. To effectively fuse features from two sources (RGB color space images and MSRCR images), a feature fusion method based on self-attention is built, which can effectively capture the complementarity of two features. Experiments and analysis on Oulu-NPU, CASIA-MFSD, and Replay-Attack databases show that it outperforms most existing methods in intra-database testing and achieves good generalization performance in cross-database testing.     

Predictive process mapping for laser powder bed fusion: A review of existing analytical solutions

One of the main challenges in the laser powder bed fusion (LPBF) process is making dense and defect-free components. These porosity defects are dependent upon the melt pool geometry and the processing conditions. Power-velocity (PV) processing maps can aid in visualizing the effects of LPBF processing variables and mapping different defect regimes such as lack-of-fusion, under-melting, balling, and keyholing. This work presents an assessment of existing analytical equations and models that provide an estimate of the melt pool geometry as a function of material properties. The melt pool equations are then combined with defect criteria to provide a quick approximation of the PV processing maps for a variety of materials. Finally, the predictions of these processing maps are compared with experimental data from the literature. The predictive processing maps can be computed quickly and can be coupled with dimensionless numbers and high-throughput (HT) experiments for validation. The present work provides a boundary framework for designing the optimal processing parameters for new metals and alloys based on existing analytical solutions.     

Cryptographic Lightweight Encryption Algorithm with Dimensionality Reduction in Edge Computing

Edge Computing is one of the radically evolving systems through generations as it is able to effectively meet the data saving standards of consumers, providers and the workers. Requisition for Edge Computing based items have been increasing tremendously. Apart from the advantages it holds, there remain lots of objections and restrictions, which hinders it from accomplishing the need of consumers all around the world. Some of the limitations are constraints on computing and hardware, functions and accessibility, remote administration and connectivity. There is also a backlog in security due to its inability to create a trust between devices involved in encryption and decryption. This is because security of data greatly depends upon faster encryption and decryption in order to transfer it. In addition, its devices are considerably exposed to side channel attacks, including Power Analysis attacks that are capable of overturning the process. Constrained space and the ability of it is one of the most challenging tasks. To prevail over from this issue we are proposing a Cryptographic Lightweight Encryption Algorithm with Dimensionality Reduction in Edge Computing. The t-Distributed Stochastic Neighbor Embedding is one of the efficient dimensionality reduction technique that greatly decreases the size of the non-linear data. The three dimensional image data obtained from the system, which are connected with it, are dimensionally reduced, and then lightweight encryption algorithm is employed. Hence, the security backlog can be solved effectively using this method.     

Effect of metallurgical evolution during post-weld aging treatment on localised corrosion of resistance spot welding joints of A286 superalloy

The combined effect of resistance spot welding and precipitation hardening on the localised corrosion of A286 superalloy is studied. The specimens tested by double loop electrochemical potentiokinetic reactivation were welded in the solution treated condition, and then subjected to different precipitation hardening treatments. For both base metal and weld nugget, the maximum localised corrosion is reached when η phase is clearly observable. The fact that the localised corrosion resistance of weld nugget is different from that shown by base metal may be explained by the segregation of Ni and Ti towards the interdendritic region of weld nugget (studied by using scanning electron microscope/energy dispersive X-ray analysis).     

基于主成分分析法的熟化菠萝蜜种子品质评价

以菠萝蜜种子为原料,研究水煮、汽蒸、焙烤3种熟化方式对其感官品质、色泽、质构、糊化度、基本营养含量、脂肪酶抑制率、质量损失率和微观结构的影响,并对其品质指标进行主成分分析。结果表明:水煮、汽蒸、焙烤3种熟化方式对不同指标有较大影响,水煮方式糊化度最高且质量损失率最大;焙烤显著加深菠萝蜜种子色泽且脂肪酶抑制率最大;汽蒸熟化后菠萝蜜种子感官评分最高;通过主成分分析可知,焙烤方式获得的品质评价综合得分最高,可作为菠萝蜜种子预熟化的较优选择。