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In the process of laser-based direct energy deposition (DED-LB), the quality of the deposited layer will be affected by the process parameters and the external environment, and there are problems such as poor stability and low accuracy. A molten pool monitoring method based on coaxial vision is proposed. Firstly, the molten pool image is captured by a coaxial CCD camera, and the geometric features of the molten pool are accurately extracted by image processing techniques such as grayscale, median filtering noise reduction, and K-means clustering combined with threshold segmentation. The molten pool width is accurately extracted by the Canny operator combined with the minimum boundary rectangle method, and it is used as the feedback of weld pool control. The influence of process parameters on the molten pool was further analyzed. The results show that with an increase in laser power, the width and area of the molten pool increase monotonously, but exceeding the material limit will cause distortion. Increasing the scanning speed will reduce the size of the molten pool. By comparing the molten pool under constant power mode and width control mode, it is found that in width control mode, the melt pool width fluctuates less, and the machining accuracy is improved, validating the effectiveness of the real-time control system. [ABSTRACT FROM AUTHOR]

With the development of edge computing and deep learning, intelligent human behavior recognition has spawned extensive applications in smart worlds. However, current edge computing technology faces performance bottlenecks due to limited computing resources at the edge, which prevent deploying advanced deep neural networks. In addition, there is a risk of privacy leakage during interactions between the edge and the server. To tackle these problems, we propose an effective, privacy-preserving edge–cloud collaborative interaction scheme based on WiFi, named P-CA, for human behavior sensing. In our scheme, a convolutional autoencoder neural network is split into two parts. The shallow layers are deployed on the edge side for inference and privacy-preserving processing, while the deep layers are deployed on the server side to leverage its computing resources. Experimental results based on datasets collected from real testbeds demonstrate the effectiveness and considerable performance of the P-CA. The recognition accuracy can maintain 88%, although it could achieve about 94.8% without the mixing operation. In addition, the proposed P-CA achieves better recognition accuracy than two state-of-the-art methods, i.e., FedLoc and PPDFL, by 2.7% and 2.1%, respectively, while maintaining privacy. [ABSTRACT FROM AUTHOR]

The measurement data in the power system may be attacked and tampered during the transmission. For this problem, a data encryption and approximate recovery strategy based on double random sorting and CGAN is proposed. The double random sorting encryption algorithm is proposed based on the form of measurement data in plaintext. The randomness of pseudo-random number, random sequence and random sequence insertion will ensure the uncertainty of data block number, sorting order and insertion location of random sequence, which will definitely improve the security of measurement data. Besides, an approximate recovery strategy used to approximately recovery abnormal samples is proposed on the base of CGAN, which can ensure the accuracy of decryption. Finally, the feasibility, and effectiveness of the proposed method are analyzed on wind power and photovoltaic power historical dataset.

The electromagnetic wave absorption properties of flake-shaped carbonyl-iron/paraffin composites with various volume concentrations were calculated by the measured complex permeability and permittivity. The complete electromagnetic wave absorption was searched for the volume concentration of 0.125, 0.15 and 0.20 at 5.8, 4, and 3.6 GHz, respectively. The permittivity is much larger than the permeability at the complete absorption frequency points. Based on the origin of the absorbing peaks, the contour map displaying the relationship between the complex permittivity and complex permeability at the perfect matching point was developed. The complex permittivity obtained from the contour map basically agrees with the experimental data for a given complex permeability. Hence, the contour map can be used to design the absorber for obtaining the excellent electromagnetic wave absorption. [ABSTRACT FROM AUTHOR]

Abstract: Co2Z barium ferrite composite with the added graphite powder was prepared to increase the permittivity. The calculated results showed that the stronger reflection loss (RL) peak and the smaller absorber thickness were simultaneously achieved compared with the pure Co2Z barium ferrite composite with the same permeability but lower permittivity. The origin of the absorption peaks was discussed by quarter-wavelength cancellation. By measuring the reflection coefficient of the composites without (S11-OPEN ) and with (S11-SHORT ) a backed metal plate, the separated electromagnetic wave energy reflected at the air–absorber interface and the absorber–metal plate interface was achieved, and they were used to deeply investigate the reason of the RL enhancement. [Copyright &y& Elsevier]

Objective: To systematically review the literature on radiomics for predicting intracranial aneurysm rupture and conduct a meta-analysis to obtain evidence confirming the value of radiomics in this prediction., Methods: A systematic literature search was conducted in PubMed, Web of Science, Embase, and The Cochrane Library databases up to March 2024. The QUADAS-2 tool was used to assess study quality. Stata 15.0 and Review Manager 5.4.1 were used for statistical analysis. Outcomes included combined sensitivity (Sen), specificity (Spe), positive likelihood ratio (+LR), negative likelihood ratio (-LR), diagnostic odds ratio (DOR), and their 95% confidence intervals (CI), as well as pre-test and post-test probabilities. The SROC curve was plotted, and the area under the curve (AUC) was calculated. Publication bias and small-study effects were assessed using the Deeks' funnel plot., Results: The 9 included studies reported 4,284 patients, with 1,411 patients with intracranial aneurysm rupture (prevalence 32.9%). The overall performance of radiomics for predicting intracranial aneurysm rupture showed a combined Sen of 0.78 (95% CI: 0.74-0.82), Spe of 0.74 (95% CI: 0.70-0.78), +LR of 3.0 (95% CI: 2.7-3.4), -LR of 0.29 (95% CI: 0.25-0.35), DOR of 10 (95% CI: 9-12), and AUC of 0.83 (95% CI: 0.79-0.86). Significant heterogeneity was observed in both Sen (I 2 = 90.93, 95% CI: 89.00-92.87%) and Spe (I 2 = 94.28, 95% CI: 93.21-95.34%)., Conclusion: Radiomics can improve the diagnostic efficacy of intracranial aneurysm rupture. More large-sample, prospective, multicenter clinical studies are needed to further evaluate its predictive value., Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/., Competing Interests: The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Xu, Fan, Liu, Li, Kong and Zhao.)