ﻻ يوجد ملخص باللغة العربية
Ongoing standardization in Industry 4.0 supports tool vendor neutral representations of Piping and Instrumentation diagrams as well as 3D pipe routing. However, a complete digital plant model requires combining these two representations. 3D pipe routing information is essential for building any accurate first-principles process simulation model. Piping and instrumentation diagrams are the primary source for control loops. In order to automatically integrate these information sources to a unified digital plant model, it is necessary to develop algorithms for identifying corresponding elements such as tanks and pumps from piping and instrumentation diagrams and 3D CAD models. One approach is to raise these two information sources to a common level of abstraction and to match them at this level of abstraction. Graph matching is a potential technique for this purpose. This article focuses on automatic generation of the graphs as a prerequisite to graph matching. Algorithms for this purpose are proposed and validated with a case study. The paper concludes with a discussion of further research needed to reprocess the generated graphs in order to enable effective matching.
Digital watermarking has been widely used to protect the copyright and integrity of multimedia data. Previous studies mainly focus on designing watermarking techniques that are robust to attacks of destroying the embedded watermarks. However, the eme
Digital Twin (DT) is a promising technology for the new immersive digital life with a variety of applications in areas such as Industry 4.0, aviation, and healthcare. Proliferation of this technology requires higher data rates, reliability, resilienc
Digital Engineering, the digital transformation of engineering to leverage digital technologies, is coming globally. This paper explores digital systems engineering, which aims at developing theory, methods, models, and tools to support the emerging
Automated methods for breast cancer detection have focused on 2D mammography and have largely ignored 3D digital breast tomosynthesis (DBT), which is frequently used in clinical practice. The two key challenges in developing automated methods for DBT
Industrial processes rely on sensory data for decision-making processes, risk assessment, and performance evaluation. Extracting actionable insights from the collected data calls for an infrastructure that can ensure the dissemination of trustworthy