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检索条件"任意字段=International Conference on Process Automation, Control and Computing"

共 28217 条记录，以下是131-140 订阅

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Surrogate Modeling for control of Microbial Biopolymer Production process 11

Surrogate Modeling for Control of Microbial Biopolymer Produ...

引用

11th Vienna international conference on Mathematical Modelling (MATHMOD)

作者： Duerr, Robert Otto, Eric Kok, Rudolph L. Duvigneau, Stefanie Kienle, Achim Bueck, Andreas Magdeburg Stendal Univ Appl Sci D-39114 Magdeburg Germany Otto Guericke Univ D-39106 Magdeburg Germany Max Planck Inst Dynam Complex Tech Syst D-39106 Magdeburg Germany Friedrich Alexander Univ Erlangen Nuremberg D-39058 Erlangen Germany

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/)

关键词： Dynamic Mode Decomposition Black-Box-Identification Surrogate Modeling Polymerisation

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Evaluating Healthcare automation: A Multi-Case Study on the Utilization of automation Initiatives in Healthcare Operations 16

Evaluating Healthcare Automation: A Multi-Case Study on the ...

引用

16th international conference on Knowledge Management and Information Systems, KMIS 2024 as part of 16th international Joint conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2024

作者： Kaitosalmi, Jani Ratia, Milla Department of Industrial Engineering and Management Aalto University Otakaari 1B Espoo Finland

ISBN: (纸本)9789897587160

automation technologies such as robotic process automation (RPA) and intelligent automation (IA) are essential for managing rising healthcare costs and ensuring sustainable health services. Although these solutions have been implemented in several Finnish healthcare organizations, their overall impact has not been systematically evaluated. This research investigates the impact and evaluation of healthcare automation through a multi-case study conducted in two Finnish healthcare organizations. While automation has improved resource utilization, process efficiency, and standardization across units, the findings highlight the need for a more comprehensive evaluation and continuous monitoring of automation benefits. Future research should focus on developing a specific evaluation framework tailored to healthcare automation technologies. The adoption of holistic evaluation methods could allow healthcare organizations to better understand the impact of automation and further enhance operational efficiency and patient care. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Healthcare automation Impact Assessment Intelligent automation Robotic process automation

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Requirements and Challenges in the Configuration of a Real-Time Node for OPC UA Publish-Subscribe Communication 29

Requirements and Challenges in the Configuration of a Real-T...

引用

29th international conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Neumann, Rebekka von Arnim, Christian Neubauer, Michael Lechler, Armin Verl, Alexander Univ Stuttgart Inst Control Engn Machine Tools & Mfg Units ISW Stuttgart Germany

ISBN: (纸本)9798350325621

Factory automation is evolving from a hierarchical structure towards an interconnected architecture in which systems at different levels can communicate seamlessly with each other. This requires an appropriate replacement of proprietary fieldbus systems in the automation sector. A promising solution to implement cross-plane end-to-end real-time capable communication between computing nodes is proposed in literature. The usage of Open Platform Communication Unified Architecture (OPC UA) as the information model with the Publish-Subscribe (PubSub) communication mechanism in combination with Time Sensitive Networking (TSN) is presented to fulfill the requirements for message transmission. In contrast to the state of the art of configuring fieldbus systems, the configuration of such a real-time communication node has to be done manually. This process is complex, as deep knowledge in different domains is required. In this work we elaborate the requirements for such a communication node and present the resulting implementation challenges, which can be used as the basis for a configuration tool.

关键词： OPC UA PubSub real-time communication computing node

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Enhancing Financial Decision-Making with Edge computing and Ai in Accounting Environments 2

Enhancing Financial Decision-Making with Edge Computing and ...

引用

2nd IEEE international conference on IoT, Communication and automation Technology, ICICAT 2024

作者： Qureshi, Naila Iqbal Princess Noura Bint Abdul Rahman University Management Department College of Business Administration Riyadh Saudi Arabia

ISBN: (纸本)9798350368109

Due to the current day's financial landscape, which is data-driven and changing rapidly, the latest use of technology has become an order of the day to further increase efficiency in the decision-making process within accounting environments. This paper explores edge computing combined with artificial intelligence (AI) in redefining the financial decision-making process. On one side, edge computing is decentralized data processing much closer to its source;therefore, it reduces latency and increases efficiency. On the other side, artificial intelligence is an overarching term that refers to a collection of a number of different techniques that allow machines to imitate human cognitive functions. This coupled with AI presents vast opportunities for the revolution in accounting environments through real-time insights, accuracy, and efficient resource utilization. In this regard, it is thereby established how these two technologies complement one another in an attempt to make these capabilities strong relative to financial decisions in the different areas. Another benefit of the integration of edge computing with AI in the accounting environment is its ability to process huge loads of financial data with very little to zero latency. Edge computing reduces the latencies between the data generation, processing of the data, and decision-making process by moving the computation closer to where data is created, enabling almost real-time analysis and decision-making. This is complemented by AI algorithms that autonomously analyze patterns in the data, detect anomalies, and generate actionable insights toward empowering the professionals of finance to take informed decisions promptly. © 2024 IEEE.

关键词： Decentralized finance

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LEAD: Latency-Efficient Application Deployment for Microservices Architecture 29

LEAD: Latency-Efficient Application Deployment for Microserv...

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29th international conference on automation and computing (ICAC)

作者： Mirzaei, Mohammad-Ali Poorsistani, Parsa Javadi, Seyyed Ahmad Amirkabir Univ Technol Dept Comp Engn Tehran Iran Amirkabir Univ Technol Dept Math & Comp Sci Tehran Iran

ISBN: (纸本)9798350360882;9798350360899

In cloud computing, microservices architecture has become the preferred choice for many applications. Accordingly, several small and decoupled containerized services hosted on different servers communicate through the network. Therefore, communication latency significantly impacts end-to-end latency. Kubernetes, the de facto standard for container orchestration, cannot reduce this overhead due to its lack of awareness of service interactions. We present LEAD, a Latency-Efficient Application Deployment framework that integrates with Kubernetes without modifying its core components. LEAD considers the inter-service relationships and resource constraints, improving service placement to reduce end-to-end latency. The idea behind LEAD is straightforward: keep the cooperating services close to each other to exploit faster in-node communication and automate this process. The proposed idea is realized by leveraging a scoring algorithm and monitoring framework to achieve dynamic improvement of service placement. Our experimental results show an average 20% improvement in the 99th percentile latency compared to Kubernetes default scheduler.

关键词： Cloud computing Microservices architecture Tail-latency Resource management Container placement

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Coffee Bean Grading Based on Weight Estimation Using Densenet121 Model 7

Coffee Bean Grading Based on Weight Estimation Using Densene...

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2023 7th international conference On computing, Communication, control And automation, ICCUBEA 2023

作者： Bipin Nair, B.J. Abrav Nanda, K.M. Shalwin, A.S. Likith Rao Mohethe, G. Raghavendra, V. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science Mysuru India

ISBN: (纸本)9798350304268

Coffee bean grading is a crucial process in the coffee industry, traditionally done manually by human experts, which is time-consuming, expensive, and prone to errors. To address these challenges, deep learning models have emerged as a powerful tool for automating coffee bean grading. This study uses the Densenet121 model to analyze a dataset of 363 images of manually graded coffee beans to recognize the different grades based on their features and patterns. The results show that the deep learning model achieves an accuracy of 81.89%, demonstrating its potential for revolutionizing the coffee industry by offering speed, accuracy, cost-effectiveness, scalability, and consistency in quality production. This study highlights the promising potential of deep learning models in image analysis and grading for various industries, with further research and development. © 2023 IEEE.

关键词： classification coffee bean Deep Learning grading image processing

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A Reinforcement Adversarial Framework Targeting Endogenous Functional Safety in ICS: Applied to Tennessee Eastman process 16

A Reinforcement Adversarial Framework Targeting Endogenous F...

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16th international conference on Computer and automation Engineering (ICCAE)

作者： Wu, Xinyi Ding, Yulong Yang, Shuang-Hua Southern Univ Sci & Technol Dept Comp Sci & Engn Next Generat Ind Internet Shenzhen Key Lab Safety & Secur Shenzhen Peoples R China Southern Univ Sci & Technol Shenzhen Key Lab Safety & Secur Next Generat Ind Internet Shenzhen Peoples R China Univ Reading Dept Comp Sci Reading Berks England

ISBN: (纸本)9798350370058;9798350370164

Endogenous Safety and Security (ESS) of Industrial control Systems (ICS) has gained great attention with the advent of Industry 4.0. However, with rising cyber threats, most current research has focused mainly on cybersecurity aspects. Our study aims to fill this research gap by focusing on the endogenous functional safety of ICS, with a particular emphasis on key control parameters "setpoints". We propose a reinforcement adversarial framework to investigate the functional security issues arising from unexpected operations and malicious tampering against setpoints. In this framework, a deep reinforcement learning(DRL) agent interacts with a custom input rule model, which serves as both a dynamic validator and an adversary, aiming to explore previously unforeseen behaviors. Explored unexpected behaviors are continuously updated to the input rule model, enhancing system adaptability and robustness. Our study employed the Tennessee Eastman process as a case study, using the proximal policy optimization(PPO) algorithm with Beta and Gaussian distributions. Our approach exhibited significant advantages in exploration efficiency over baseline methods such as random agents and simulated annealing. These findings underscore DRL's important role in augmenting ICS functional safety, thereby enhancing system resilience and security in Industry 4.0.

关键词： endogenous functional safety deep reinforcement learning industrial control systems

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Sparse Gaussian process Regression for Residual Dynamics Learning in Multi-rotor Aerial Vehicles control 20

Sparse Gaussian Process Regression for Residual Dynamics Lea...

引用

IEEE 20th international conference on automation Science and Engineering (CASE)

作者： Kulathunga, Geesara Hanheide, Marc Klintchik, Alexandr Univ Lincoln Lincoln Inst Agrifood Technol Lincoln LN1 England Univ Lincoln Sch Comp Sci Lincoln LN6 England

ISBN: (纸本)9798350358513;9798350358520

This paper introduces a method for modeling residual dynamics between a high-level planner and a low-level controller, using reference trajectory tracking in a cluttered environment as a case study. We aim to mitigate residual dynamics resulting solely from the kinematical modeling employed in high-level planning. Our high-level planner utilizes a simplified motion model for quadrotor motion. We propose a Sparse Gaussian process Regression-based technique to model residual dynamics. In contrast, Data-Driven MPC, a recent technique, targets aggressive maneuvers without obstacle constraints. Our proposed method is compared with Data-Driven MPC in estimating residual dynamics error, including obstacle constraints. Comparative analysis indicates that our technique reduces nominal model error by an average factor of 2. Furthermore, we evaluate our complete framework against four other trajectorytracking approaches in terms of tracking reference trajectory while avoiding collisions. Our approach demonstrates superior performance, achieving shorter flight times without sacrificing computational efficiency.

关键词： Gaussian distribution

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Deep Convolutional Neural Networks for Intelligent Emotional computing: A Multidimensional Analysis and Practical Application of Emotional Features in Digital Learning Interfaces 2

Deep Convolutional Neural Networks for Intelligent Emotional...

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2nd international conference on Artificial Intelligence and automation control, AIAC 2024

作者： Zhang, Naixin Leong, Waiyie Zhang, Tong Chengdu Jincheng College Inti International University Sichuan Chengdu China Inti International University Faculty of Engineering and Quantity Surveying Nilai Malaysia The Affiliated Hospital of Southwest Jiao Tong University The Third People's Hospital of Chengdu Department of Cardiology Chengdu China

ISBN: (纸本)9798331529147

This study explores an intelligent emotional computing method baed on deep convolutional neural networks (DCNNs) aimed at accurately identifying and analyzing learners' emotional states within digital learning interfaces. A multi-channel, multi-scale convolutional neural network structure is designed to effectively integrate multimodal emotional features such as facial expressions, physiological signals, behavioral data, and learning environments. Experimental validation on both self-built datasets and publicly available datasets demonstrates that the proposed model achieves superior performance in emotion recognition tasks, with an average accuracy rate of 85.2%, significantly outperforming traditional methods based on handcrafted features and shallow networks. © 2024 IEEE.

关键词： Contrastive Learning

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A Method for Analyzing Data in Measuring Devices Using a Specialized computing System for Synthesizing and Evaluating Statistical Hypotheses 5

A Method for Analyzing Data in Measuring Devices Using a Spe...

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5th international conference on control Systems, Mathematical Modeling, automation and Energy Efficiency, SUMMA 2023

作者： Tarasov, Ilya RTU MIREA Laboratory of Specialized Computer Systems Moscow Russia

ISBN: (纸本)9798350309126

The article examines the application of a method for processing experimental data in measurement systems by generating hypotheses about the presence of a given set of parameters and estimating their probability. The difference between the method is the use of the error probability distribution function with an independent parameter "distribution scale"and the search for a combination of process model parameters at which the posterior probability function takes the maximum value. The method is characterized by high resistance to impulse noise, as a result of which it can be used in measuring systems. A special feature of the method is the large number of calculations required to generate hypotheses and test their probability. To solve this problem, a parallel computing system architecture has been proposed that generates hypotheses and evaluates them using independent processing elements. © 2023 IEEE.

关键词： Impulse noise

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