In response to the varied application scenarios of Human-Cyber-Physical systems (HCPS) and the dynamic roles humans play, we have introduced three specialized controller frameworks: H-CP, C-HP, and HP-CP. We designed ...
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In the context of rapidly evolving technology and increased attention to social and environmental dimensions, the industrial sector is transitioning from Industry 4.0 to Industry 5.0. This new paradigm emphasizes huma...
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ISBN:
(纸本)9783031807596;9783031807602
In the context of rapidly evolving technology and increased attention to social and environmental dimensions, the industrial sector is transitioning from Industry 4.0 to Industry 5.0. This new paradigm emphasizes human centrality in highly automated environments, necessitating the exploration of collaboration mechanisms between humans and robots. This study investigates the application of Physics-Informed Neural Networks (PINNs) to enhance Human-Robot Collaboration (HRC). PINNs integrates the traditional data-driven approach based on machine learning models with a prior physical knowledge of the system, providing a valuable solution when data are scarce or physical models are too complex or incomplete. The study first focuses on the main aspects of interest in the field of HRC through a state-of-the-art analysis, evaluating the application of Physics-Informed Neural Networks (PINNs) in HRC and robotics. It then delves into the definition of PINNs and their implementation. Finally, as a proof of concept, the model is applied to a case study concerning collision detection in a 6 DoF robotic arm. This is achieved by predicting the joint currents and comparing them with the measured values to identify the contribution due to external forces such as collisions. The results demonstrate that the PINNs model outperforms a traditional neural network, achieving an average error below 10%. Additionally, the collision detection application shows an f1_score of 0.80, indicating strong performance.
According to the actual needs of students majoring in vehicle engineering, this paper focuses on the application of virtual simulation experimental environment in their professional learning and ability training. Thro...
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The continual growth of the computer vision and artificial intelligence fields overtime have provided the basis for more efficient and accurate surveillance. This paper examines the use of YOLO, a deep learning model ...
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OOSEM (Object-Oriented systems Engineering Method) is a MBSE(Model-Based systems Engineering) method. OOSEM is scenario-driven and it can analyze the requirements from system-level to component-level. As a selected MB...
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ISBN:
(数字)9798331541545
ISBN:
(纸本)9798331541552
OOSEM (Object-Oriented systems Engineering Method) is a MBSE(Model-Based systems Engineering) method. OOSEM is scenario-driven and it can analyze the requirements from system-level to component-level. As a selected MBSE method, OOSEM is applied in system security engineering. When focusing on requirement analysis, the OOSEM approach includes system requirements analysis. In OOSEM approach of this paper, SysML model is provided according to requirements analysis of Boundary Security system specially for concerning requirements analysis. In SysML model of Boundary Security system, package diagrams model, use case diagrams model, state machine diagram model and sequence diagram model respectively are applied in OOSEM process. These models provide strong design support for requirement analysis of system security Engineering.
The proceedings contain 24 papers. The special focus in this conference is on Empirical Methodologies for Research in Enterprise Architecture and Service-oriented Computing. The topics include: Spotting the Wease...
In analyzing and recognizing wrist pulse signals, it isn’t easy to mine the nonlinear information of wrist pulse signals using analysis methods such as time and frequency. Traditional machine learning methods require...
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The proceedings contain 113 papers. The special focus in this conference is on Advances in Information and Communication Technology. The topics include: Using Opals Program system and Sparse CNN Model in Processing an...
ISBN:
(纸本)9783031809422
The proceedings contain 113 papers. The special focus in this conference is on Advances in Information and Communication Technology. The topics include: Using Opals Program system and Sparse CNN Model in Processing and Classifying Airborne Laser Scanning Data;polyp Segmentation Based on Transformer;an Effective Approach for Object Detection in Adverse Weather Conditions;Enhancing DGA Botnet Classification Based on Large Language Models and Transfer Learning;deep Learning application for Images Augmentation in Electrical Component Classification system;Enhancing the Performance of Vietnamese Online Public Service Chatbots with RAG;A Hybrid Approach: Transformer and LSTM Combination for Text Summarization in Vietnamese;vizAgent: Towards an Intelligent and Versatile Data Visualization Framework Powered by Large Language Models;enhancing Telecom Churn Prediction Using an Advanced Stacking Model;an Efficient Methodology to Assess Ki-67 and Tumor-Infiltrating Lymphocytes in Heterogeneous Tumors Detection;transformating trigonometric function to apply in software reliability modeling;application of Large Language Models in Geographic Map Analysis and Visualization;FMN-Voting: A Semi-supervised Clustering Technique Based on Voting Methods Using FMM Neural Networks;An Automatic Machine Learning Based Customer Segmentation Model with RFM Analysis;enhanced Literature Review Visualization: A Novel Sorted Stream Graphs with Integrated Word Elements;transfer Learning for Cervical Cancer Multi-class Classification;a Study on Ensemble Learning for Cervical Cytology Classification;EFL-Net: An Enhanced Feature-Based Learning Network for Object Detection in Rainy Weather Conditions;A Trace-Selection Preprocessing Approach of Discovering Structurally Complete ICN-Process Models from Process Logs;improve the Quality of Machine Translation in Low-Resource Language Pairs;Faster-RCNN in Human Detecting on Thermal Images;deep Learning for Speech Separation: A Comprehensive Review;predicting
In the absence of any observation system or low veracity of the data, it is possible to provide control over a limited time interval basing on a high-precision control object model used. The paper proposes to use a mu...
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This paper provides an overview of microgrid control strategies, examining differences between centralized and decentralized approaches, and focusing on classical hierarchical control schemes as well as the structure ...
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