Using software robots that communicate with systems via their user interfaces, robotic processautomation (RPA) attempts to automate corporate operations while increasing efficiency and cutting costs. To prevent ineff...
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The article proposes a stepwise evolution of an algorithmic software solution for purchase order recognition to an AI upgraded system to improve the overall data extraction accuracy and to minimize the need for human ...
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The article proposes a stepwise evolution of an algorithmic software solution for purchase order recognition to an AI upgraded system to improve the overall data extraction accuracy and to minimize the need for human validation of the results and postprocessing in business data processing. Copyright (C) 2024 The Authors.
Cloud-native architecture is changing the cloud computing environment and introducing new dimensions to cloud computing adoption through the advancement in virtualisation, scalability and automation. However, many org...
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ISBN:
(纸本)9783031516634;9783031516641
Cloud-native architecture is changing the cloud computing environment and introducing new dimensions to cloud computing adoption through the advancement in virtualisation, scalability and automation. However, many organisations found it challenging to adopt cloud-native architectures because of some issues, mainly the decision-making around migration because of the need for the adoption decision process. However, there are many decision-support systems or processes for cloud computing. Nevertheless, the additional characteristic and complexity of cloud-native architecture made many organisations find it challenging to adopt cloud-native architecture solutions. The need for a new decision-support process for the migration of either a native cloud application or legacy application to cloud-native architecture is highly needed to help the developers to be able to select the choice of model and whether to migrate or not. Therefore, this paper provides a step-by-step decision process for an organisation to migrate their application to cloud-native architecture to fill the gap. The decision process depends on the step-by-step cross-analysis of the steps and the tasks to help identify and resolve critical constraints that can affect migration into cloud-native architecture. An expert evaluationmethod was used to evaluate the decision process and steps. The decision process was helpful as they informed the decision makers about the needful steps and tasks to consider before migrating to the cloud-native architecture.
Advanced Driver Assistance Systems, or ADAS for short, are a group of technologies intended to help drivers operate their automobiles more safely and effectively. These systems often employ sensors, cameras, and other...
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Industrial automation has become increasingly important in recent years. It has allowed for increased efficiency, productivity and safety in the workplace, as well as improved quality control of products. However, wit...
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Direct ink writing is a 3D printing process and the quality of this process depends on the steady-state flow of materials at the tip of nozzle. In this paper, we investigate a data-driven approach, the physics informe...
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In this contribution, the Dynamic Mode Decomposition with control (DMDc) is used to derive a surrogate model of a continuous PHA biopolymer production process based on a recently published complex process model. Here,...
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In this contribution, the Dynamic Mode Decomposition with control (DMDc) is used to derive a surrogate model of a continuous PHA biopolymer production process based on a recently published complex process model. Here, snapshot simulation data of the original model is processed to obtain a linear surrogate model formulation using delay coordinates. The quality of the surrogate is statistically validated within simulation studies. Additionally, the influence of the of the order of delay coordinates is investigated. It is shown, that the highly nonlinear dynamics of the PHA-manufacturing process can be approximated accurately by the DMD-based model even for large variations of initial conditions and control variables. This offers the opportunity to apply well-studied and established tools from robust and optimal control in future investigations. Copyright (c) 2025 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)
This paper explores methodologies for localization of RFID tags on logistical handling units to create a Digital Twin of an industrial order-picking and stock replenishment process. The research is focused on the util...
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The rise of smart factories is driving the complete automation of manufacturing environments, making anomaly detection a more important task than ever. With highly intelligent equipment deployed on fully-automated pro...
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ISBN:
(纸本)9798350368567;9798350368550
The rise of smart factories is driving the complete automation of manufacturing environments, making anomaly detection a more important task than ever. With highly intelligent equipment deployed on fully-automated production lines, even a slight anomaly may seriously impact the entire manufacturing process. However, most industrial data containing slight anomalous features exhibits strong correlations that are not fully exploited by existing machine learning models. In general, the anomaly detection model needs to run within programmable logic controllers (PLCs) since it is the main controller of the intelligent equipment, and PLCs have limited resources making it difficult to execute larger models effectively. To address the challenge, we propose a graph anomaly detection method in programmable logic controllers based on service computing (PCSC). The model establishes a data relationship graph through clustering and then feeds it into a neural network with a symmetric structure consisting of graph convolutional layers and LSTM units. This approach enables the analysis of correlations within industrial data and facilitates the extraction of slight abnormal features. For efficient execution of the model, we establish service computing nodes in the PLCs that support model splitting. We tested the model on several publicly available datasets and an actual dataset from an injection molding production line. The results show that the model performs well on different datasets.
Network security is an important research direction in today's times. Neural connection-level clipping, taking specific parameters as objects or clear network connections, can make network clipping more refined, i...
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