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Automated Configuration of Behavior Models in Digital Twins based on a Knowledge-Graph

Procedia CIRP 2024年 130卷 683-688页

作者： Daniel Dittler Frederike Bodenstein Gary Hildebrandt Nasser Jazdi Michael Weyrich Institute of Industrial Automation and Software Engineering University of Stuttgart Pfaffenwaldring 47 70569 Stuttgart Germany Institute of Smart Systems and Services Pforzheim University of Applied Sciences Pforzheim Germany

A modular production plant can be simulated with different behavior models with varying modeling depths, thus enabling a wide variety of applications. However, the plant operator faces the challenge of linking the right models for his application. This contribution describes the need to adapt model configurations and associated challenges. Related approaches from the literature and standards are discussed. Subsequently, a novel modeling approach is presented that combines and extends the information from the analyzed approaches to enable automatic linking of model configurations. The approach is realized with the help of a knowledge-graph and evaluated using a material flow simulation scenario.

关键词： model adaption behavior models knowledge-graph digital twin simulation

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Large dynamic range Shack-Hartmann wavefront sensor based on adaptive spot matching

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Light(Advanced Manufacturing) 2024年第1期5卷 40-49页

作者： Jiamiao Yang Jichong Zhou Lirong Qiu Rongjun Shao Linxian Liu Qiaozhi He School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghai 200240China Beijing Key Lab for Precision Optoelectronic Measurement Instrument and Technology School of OptoelectronicsBeijing Institute of TechnologyBeijing 100081China School of Automation and Software Engineering Shanxi UniversityTaiyuan 030006China

The Shack-Hartmann wavefront sensor(SHWS)is widely used for high-speed,precise,and stable wavefront ***,conventional SHWSs encounter a limitation in that the focused spot from each microlens is restricted to a single microlens,leading to a limited dynamic ***,we propose an adaptive spot matching(ASM)-based SHWS to extend the dynamic *** approach involves seeking an incident wavefront that best matches the detected spot distribution by employing a Hausdorff-distance-based nearest-distance matching *** ASM-SHWS enables comprehensive spot matching across the entire imaging plane without requiring initial spot ***,due to its global matching capability,ASM-SHWS can maintain its capacity even if a portion of the spots are *** showed that the ASM-SHWS could measure a high-curvature spherical wavefront with a local slope of 204.97 mrad,despite a 12.5%absence of *** value exceeds that of the conventional SHWS by a factor of 14.81.

关键词： Wavefront sensing Large dynamic range Shack-Hartmann sensor

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Improving the Educational Value of Operating Systems 23

Improving the Educational Value of Operating Systems

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23rd RoEduNet Conference: Networking in Education and Research, RoEduNet 2024

作者： Sava, Cezar Deaconescu, Razvan Kroning, Martin Monti, Antonello Turcanu, Dinu POLITEHNICA of Bucharest Computer Science and Engineering Department Bucharest Romania RWTH Aachen University Institute for Automation of Complex Power Systems Aachen Germany Fraunhofer Center Digital Energy Fraunhofer FIT Aachen Germany University of Moldova Department of Software Engineering and Automatics Technical Chişinǎu Moldova

ISBN: (纸本)9798331540388

Educational operating systems are crucial for facilitating learning in the digital age, as they exist at the intersection of technology and education. While their technical role is well understood, improving their educational value requires enhancing traditional approaches. This paper explores ways to enrich educational operating systems not just through technological advancement, but also by integrating pedagogical principles. In an ever-changing world, the need for an adaptive and responsive educational operating system to meet diverse student needs is crucial. Through case studies, we analyze how design, interactivity, and accessibility can transform these systems into effective and appealing learning environments. We propose a series of recommendations for the future development of educational operating systems, focusing on enhancing the learning experience and promoting student autonomy, thereby offering a fresh perspective on how technology and education can blend harmoniously and efficiently. © 2024 IEEE.

关键词： Contrastive Learning

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Modulation of two-dimensional cylindrical wake by free liquid surface in linear density stratified flow 34th

Modulation of two-dimensional cylindrical wake by free liqui...

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34th International Ocean and Polar engineering Conference, ISOPE 2024

作者： Zheng, Minmin Liu, Yadong Tang, Yuying Sun, Jiajie Liu, Weihuang Pang, Bo School of Naval Architecture Ocean & Civil Engineering Shanghai Jiao Tong University Shanghai China State Key Laboratory of Ocean Engineering Shanghai Jiao Tong University Shanghai China Institute of Marine Equipment Shanghai Jiao Tong University Shanghai China School of Automation and Software Engineering Shanxi University Taiyuan China

ISBN: (纸本)9781880653784

Due to variations in the global distribution of temperature and salinity in the oceans, the natural stratification of seawater is commonlyac knowledged as a pervasive phenomenon worldwide, with regions of rapidly stratified seawater referred to as "thermocline" or "pycnocline".The generation of density gradients provides a prerequisite for the initiation of internal waves. As vessels and submarines navigate through these stratified environments, disturbances to the density-stratified flow field are induced due to the effects of buoyancy, thereby triggering the far-field propagation of internal waves. In recent years, research and discussions on the wakes of underwater vehicles in density-stratified flows have become relatively prevalent. However, analyses and summaries of the interference caused by free liquid surfaces in density stratified flows remain unexplored. This study employs a two dimensional cylinder model to investigate the regulatory effects of a free liquid surface on the wake of a two-dimensional cylinder in a stratified flow environment. A comparison is made between the force coefficients and far-field wake of the two-dimensional cylinder in the real thermocline environment and a homogeneous flow environment around the Froude number range of 0.1 – 0.5. The results indicate that the favorable adverse pressure gradient generated in the stratified environment can reduce the drag force on the cylinder. Despite the lower frequency, stratification is still capable of suppressing the vertical movement range of the wake at © 2024 by the International Society of Offshore and Polar Engineers (ISOPE).

关键词： Wakes

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Research on Lightweight Encryption Methods for In-Vehicle Ethernet in Intelligent Automobiles 6

Research on Lightweight Encryption Methods for In-Vehicle Et...

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6th International Conference on Internet of Things, automation and Artificial Intelligence, IoTAAI 2024

作者： Dong, Bin Zhao, Xi Fan, Zhirong Cai, Yanbo Wuhan University of Technology School of Automation Hubei Wuhan China R&d Institute Dongfeng Motor Corporation Software Engineering Research Center Hubei Wuhan China R&d Institute Dongfeng Motor Corporation Department of Digitalization and Capability Assurance Hubei Wuhan China

ISBN: (纸本)9798350386974

In recent years, the trends of electrification, intelligence, connectivity, and sharing have led to increasingly complex automotive electronic and electrical systems. Against this backdrop, innovating and expanding the automotive electronic and electrical architecture has become particularly crucial. Service-Oriented Architecture (SOA), AUTOSAR standards, and in-vehicle Ethernet technology have emerged as key technologies and trends driving this development. SOME/IP (Scalable Service-Oriented Middleware over IP) is an important protocol for implementing SOA architecture, inheriting characteristics such as high speed, real-time performance, high fault tolerance, and flexibility from Ethernet. The main function of SOME/IP is to transmit messages from the sender to the receiver during communication. However, the lack of considerations for security verification, integrity, and confidentiality increases uncertainty and risks. Therefore, this paper designs and implements an Ethernet secure communication solution from the perspective of SOME/IP protocol security. This solution innovatively encrypts and decrypts service interface parameters at the application layer, enhancing the security of the in-vehicle network. © 2024 IEEE.

关键词： automotive Ethernet encryption security service interfaces SOME/IP

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Branching Time Series Prediction Method based on CNN and LSTM 7

Branching Time Series Prediction Method based on CNN and LST...

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7th IEEE Information Technology and Mechatronics engineering Conference, ITOEC 2023

作者： Li, Xiaoyu Liang, Liang Yu, Boyang School of Information and Automation Engineering Shandong China Shandong Siasun Industrial Software Research Institute Co. Ltd Shandong China Shandong Zhengzhong Information Technology Co. Ltd Shandong China

ISBN: (纸本)9798350334197

Time series data, an increasingly common form of data in real-world applications, is typically time-dependent. Time series forecasting seeks to extract potential information from time series data to forecast future trends. The complexity and nonlinearity of current time series data make it difficult for traditional forecasting algorithms to handle them, hence this paper suggests a branching time series forecasting method based on convolutional neural network (CNN) and long short-term memory network (LSTM). The method initially uses CNN to extract features from time series data, then uses CNN and LSTM to map these features to future prediction values, and lastly inputs to the fully connected layer to obtain the prediction results. According to the experimental findings, the branching prediction method based on CNN and LSTM has superior time series prediction accuracy and stability. © 2023 IEEE.

关键词： Long short-term memory

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FPGA-based acceleration for binary neural networks in edge computing

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Journal of Electronic Science and Technology 2023年第2期21卷 65-77页

作者： Jin-Yu Zhan An-Tai Yu Wei Jiang Yong-Jia Yang Xiao-Na Xie Zheng-Wei Chang Jun-Huan Yang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu610054China School of Automation Chengdu University of Information TechnologyChengdu610225China State Grid Sichuan Electric Power Research Institute Chengdu610095China Department of Information Sciences and Technology George Mason UniversityFairfaxVA22030USA

As a core component in intelligent edge computing,deep neural networks(DNNs)will increasingly play a critically important role in addressing the intelligence-related issues in the industry domain,like smart factories and autonomous *** to the requirement for a large amount of storage space and computing resources,DNNs are unfavorable for resource-constrained edge computing devices,especially for mobile terminals with scarce energy *** of DNN has become a promising technology to achieve a high performance with low resource consumption in edge ***-programmable gate array(FPGA)-based acceleration can further improve the computation efficiency to several times higher compared with the central processing unit(CPU)and graphics processing unit(GPU).This paper gives a brief overview of binary neural networks(BNNs)and the corresponding hardware accelerator designs on edge computing environments,and analyzes some significant studies in *** performances of some methods are evaluated through the experiment results,and the latest binarization technologies and hardware acceleration methods are *** first give the background of designing BNNs and present the typical types of *** FPGA implementation technologies of BNNs are then *** comparison with experimental evaluation on typical BNNs and their FPGA implementation is further ***,certain interesting directions are also illustrated as future work.

关键词： Accelerator Binarization Field-programmable gate array(FPGA) Neural networks Quantification

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DPFedSAM-Meas: Comparison Of Differential Privacy Federated Learning In Medical Image Classification

DPFedSAM-Meas: Comparison Of Differential Privacy Federated ...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Jiang, Shunrong Wang, Zhi He, Zixuan Li, Yonggang Li, Xiaofan Chi, Haotian Du, Xiaojiang China University of Mining and Technology School of Computer Science Xuzhou221116 China Jiangsu Jingchuang Electric CO. LTD China Shanxi University School of Automation and Software Engineering Taiyuan030006 China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ United States

ISBN: (纸本)9798350351255

Machine learning is widely used in medical image classification tasks. However, medical images often exhibit uneven distribution and high sensitivity to noise. A feasible solution involves using federated learning (FL) with differential privacy (DP), a distributed training method that protects patient privacy. In this work, many studies have proposed improved solutions for localized differential-private federated learning (DP-FL) frameworks. However, these studies are isolated, which would be detrimental to privacy practitioners in designing and using the algorithms. To provide a comprehensive analysis of these algorithms, we propose DPFedSAM-Meas, as a framework for comprehensive utility analysis of DP-FL. In this framework, we employed the state-of-the-art federated learning framework FedSAM. Moreover, we categorize DP algorithms into Laplace DP and Gaussian DP by the underlying DP mechanisms, and into Gradient DP and Parameter DP by the DP position in FL train. DPFedSAM-Meas allows a comparative analysis of these four DP techniques, measuring their model utility, privacy leakage, and overhead when FL uses different network structures. Finally, we evaluate DPFedSAM-Meas on datasets of Pneumonia, Blood, and Path, aiming to investigate the performance of different DP techniques on mainstream deep learning algorithms, including Convolutional Neural Networks (CNN) and Vision Transformers (ViT). © 2024 IEEE.

关键词： Federated learning

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Extending the Intelligent Digital Twin with a context modeling service: A decision support use case

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Procedia CIRP 2022年 107卷 463-468页

作者： Nada Sahlab Dominik Braun Christian Köhler Nasser Jazdi Michael Weyrich Institute of Industrial Automation and Software Engineering University of Stuttgart Stuttgart 70569 Germany

Considering the surrounding context of manufacturing systems at runtime enhances their adaptability, which is advantageous given the increasing demand for flexible production. Context-awareness presents a viable approach to continuously model the surrounding context and relate it to the system’s operation. As the surrounding context is both acquirable from heterogeneous data sources and is dynamic in nature, a coherent and evolving context model is necessary. The context modeling approach needs to be both: system-centric to enable re-usability of the model by different applications as well as continuously and efficiently extendable to continuously represent the environment. Some approaches to model context within the manufacturing domain exist, but are mostly tailored to specific applications or do not consider an extension at runtime. To include the surrounding context of a system effectively and adapt it accordingly, a relation between the modeled context and the system during runtime is necessary. The intelligent Digital Twin provides essential interdisciplinary models of a physical system, which can be used for its analysis and monitoring. Adding a further service in the form of a model to represent the surrounding context enhances the intelligent Digital Twin to be used by various applications, e.g., for reconfiguration or decision-support. In our previous work, we have presented a tier-based model to realize context-awareness for intelligent Digital Twins. The presented tier model has different levels corresponding to different context scopes. In this contribution, we present an approach to realize an extendible and evolving tier-based context model with a generic ontology and model transformation to a labeled property graph with focus on the external context. To show the applicability and added value of the context model, a use case is presented, which addresses an intelligent warehouse’s Digital Twin and its context-model supported decision-making.

关键词： context-awareness Digital Twin ontology labeled property graph intelligent warehouse cyber-physical systems

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Efficient Creation of Behavior Models for Libraries of Mechatronic Components with Minimal Effort 57

Efficient Creation of Behavior Models for Libraries of Mecha...

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18th IFAC Workshop on Time Delay Systems, TDS 2024

作者： Stegmaier, Valentin Dittler, Daniel Artelt, Maurice Jazdi, Nasser Weyrich, Michael University of Stuttgart Nobelstraße 12 Stuttgart70569 Germany Institute of Industrial Automation and Software Engineering University of Stuttgart Pfaffenwaldring 47 Stuttgart70569 Germany J. Schmalz GmbH Johannes-Schmalz-Straße 1 Glatten72293 Germany

There are several approaches in the literature for the low-effort creation of behavior models. Some of these approaches use a library that must be created in advance. This article presents a method for creating such a library of behavior models with minimal effort. Different sources of information can be used with appropriate pre-processing. Behavior models for a library are constructed from the basic building blocks of each discipline using an existing method. The behavior models of each discipline can be assigned to different modelling depths. © 2024 The Authors.

关键词： Mechatronics

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