A secure visual framework for multi-index protection evaluation in networks

Mining the core value of Industrial Internet of Things(IIoT)data safely and reducing the risk of malicious attacks are the inherent requirements of industrial data visualization.Visualization technology has become the main tool for data aggregation,mining and analysis of IIoT data through graphical representation.However,visualization technology still has two shortcomings in big data calculation and analysis scenarios.On the one hand,visual results will lead to the disclosure of sensitive privacy.On the other hand,most visualization tools can't provide an interactive framework for users to select the suitable solutions.To address these problems,we present an open accessible Visual framework based on Differential Privacy theory(VisDP),which provides Multi-index Quantitative comprehensive Evaluation technology(MQE)for data mining results.Considering the advantages of interactive mechanism,VisDP provides rich optional schemes,including the operating web,calling API and the downloading SDK.Finally,we verify the availability and privacy of MQE through mathematical proofs,analyze the hospital medical waste detection system that actually applies the framework,and the experimental results have showed the effectiveness and practicality of the proposed platform.

Plant-based meat substitutes by high-moisture extrusion:Visualizing the whole process in data systematically from raw material to the products

High-moisture extrusion technology should be considered one of the best choices for producing plant-based meat substitutes with the rich fibrous structure offered by real animal meat products.Unfortunately,the extrusion process has been seen as a“black box”with limited information about what occurs inside,causing serious obstacles in developing meat substitutes.This study designed a high-moisture extrusion process and developed 10 new plant-based meat substitutes comparable to the fibrous structure of real animal meat.The study used the Feature-Augmented Principal Component Analysis(FA-PCA)method to visualize and understand the whole extrusion process in three ways systematically and accurately.It established six sets of mathematical models of the high-moisture extrusion process based on 8000 pieces of data,including five types of parameters.The FA-PCA method improved the R^(2) values significantly compared with the PCA method.The Way 3 was the best to predict product quality(Z),demonstrating that the gradually molecular conformational changes(Y^(n'))were critical in controlling the final quality of the plant-based meat substitutes.Moreover,the first visualization platform software for the high-moisture extrusion process has been established to clearly show the“black box”by combining the virtual simulation technology.Through the software,some practice work such as equipment installation,parameter adjustment,equipment disassembly,and data prediction can be easily achieved.