The proceedings contain 72 papers. The special focus in this conference is on Production and Industrial Engineering. The topics include: A Comprehensive Overview on Additive Manufacturing processes: Materials, Applica...
ISBN:
(纸本)9789819960934
The proceedings contain 72 papers. The special focus in this conference is on Production and Industrial Engineering. The topics include: A Comprehensive Overview on Additive Manufacturing processes: Materials, Applications, and Challenges;an Overview of the Untapped Potential of Soft Robotic Arms with Integration of Machining Tools;life Cycle Assessment of Abrasive Flow Machining of 3D Printed Parts: A Comparative analysis;Modelling and Simulation of Wire DED Additive Manufacturing process;an Overview of the Recent Advances in Additive Manufacturing, and Its Scope for the Benefit of Research and Development in Commercial Vehicle Industries;design and Development of Customized Helmet for Military Personnel;additive Manufacturing and Sustainability: The Mediating Role of Supply Chain;leverage of Metal 3D Printing Technology in the Automotive Industry;digital Twins of Hybrid Additive and Subtractive Manufacturing Systems–A Review;exploring Sustainable Manufacturing: A Comprehensive Review of Literature and Practices;performance analysis of 3D Printed Impellers for Portable Vacuum Cleaner;3D Printed Electronics: Role of Materials and processes;electrochemical Micromachining: A Review on Principles, processes, and Applications;friction and Wear Characteristics of Engine Oil Through Four-Ball Tester;recent Trends in 4th Industrial Revolution for A Sustainable Future–A Review;AI control of EMG Sensor data for 3D Printed Prosthesis Hand.
The proceedings contain 104 papers. The special focus in this conference is on Computer Aided Systems Theory. The topics include: Influence of Spike Encoding, Neuron Models and Quantization on SNN Perfo...
ISBN:
(纸本)9783031838873
The proceedings contain 104 papers. The special focus in this conference is on Computer Aided Systems Theory. The topics include: Influence of Spike Encoding, Neuron Models and Quantization on SNN Performance;adaptive Combination in Frequency Domain: An Approach for Robust Nonlinear Acoustic Echo Cancellation;using of a Robotic Platform to Detect Acoustic Events for Indoor Environments;modeling Wildlife Accident Risk with Gaussian Mixture Models;towards a Unified Incident Detection and Response System for Autonomous Transportation;edge-processing of Myoelectric Signals for the control of Hand and Arm-Prostheses;AI-Driven Gesture and Action Recognition for Learning Medicine Through Virtual Reality;Medical Protocols and AI-Driven Algorithms for Enhanced Monitoring of Cardiac Implantable Electronic Devices;a Survey of Machine Learning Methods for Analyzing Synovitis Arthritis in Human Joints;motion Tracking in Augmented and Mixed Realities for Healthcare and Medicine Applications;advancements and Applications of Medical Human Digital Twin Technology in Cerebral Palsy Diagnosis, Therapy, and Rehabilitation;Transformation of IEC 61131-3 onto an Embedded Platform Using LLVM;machine Learning Based Parameter Estimation of Energy Models in Digital Production Environments;efficient Classification of Live Sensor data on Low-Energy IoT Devices with Simple Machine Learning Methods;machine Learning Using a Hybrid Quantum Classical Algorithm with Amplitude data Encoding;quantitative Trend analysis of Reinforcement Learning Algorithms in Production Systems;Using AutomationML for Advanced Simulation in Industrial Automation;AR Digital Twin Demonstrator for Industrial Robotics Education;Accelerating Manual Pick-and-Place Operations with AR-Projected CAD Plans and AI-Assisted Object Recognition;variety Engineering – A Cybernetic Concept with Practical Implications;using a System Archetype to Explore a Business Model for Digital Textile Microfactories;interacting with the Water Cycle -
The proceedings contain 73 papers. The special focus in this conference is on Electrical Engineering and Information Technologies for Rail Transportation. The topics include: Electromagnetic Wind Energy Harvester for ...
ISBN:
(纸本)9789819993109
The proceedings contain 73 papers. The special focus in this conference is on Electrical Engineering and Information Technologies for Rail Transportation. The topics include: Electromagnetic Wind Energy Harvester for Condition Monitoring System of High-Speed Train Bogies;an Exploration of Voltage-Type Rotor Magnetic Field Indirect Vector control;method to Detect Arc Across Pantograph-Catenary Structure Atop Train Based on Frequency Features of Entry Current;a Foreign Object Detection Method for Railway Overhead Lines Based on Few-Shot Learning;transformer-Aware Graph Convolution Networks for Relation Extraction of Railway Safety Risk;a Comprehensive Study on Train Operation Dynamics and Passenger Comfort Optimization;model-Driven Study of Intelligent Passenger Information System for Urban Rail Transit;research on Positioning of Permanent Magnet Maglev Trains Based on Weighted Adaptive Kalman Information Fusion;Real-Time Low-Light Image Enhancement Method for Train Driving Scene Based on Improved Zero-DCE;analysis of Dynamic Characteristics of Dropper in Catenary System;a Power Flow Optimization Method for Urban Rail Flexible Traction Power Supply System Considering Train Dwell Time;a Mechanism and data-Driven Hybrid Mechanical Model of Rotary Arm Positioning Rubber Joint;high Speed Train Bracket Arm Visualization Experiment System;design of Cabinet-Level Refrigeration System in Subway Station Communication Signal Room;active control of Pantograph Sliding Mode Under Fluctuating Wind Excitation;Time Synchronized Sensor Network with IEEE1588 for Vibration Measurement in Structural Health Monitoring of Railway System;modeling and Implementation of EMU Traction System;traffic Operation Status Research Based on Multi-source data Fusion;isochronous Deterministic Ethernet System Research;wave Propagation in the Overhead Conductor Rail System.
The current pace of development of cyber-physical systems requires the elaboration of fast methods for analyzing data circulating in them. Anomalies are patterns of data that do not conform to the concept of normal (e...
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In urban road traffic system, a variety of travel modes coexist and interact with each other. Micro modeling and analysis methods are difficult to capture the macro evolution characteristics and interaction of traffic...
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Integrated vehicle dynamics control systems require real-time communication among their components to improve performance and process efficiency. This communication relies on the use of sensor data, hardware interface...
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ISBN:
(数字)9798350358803
ISBN:
(纸本)9798350358810
Integrated vehicle dynamics control systems require real-time communication among their components to improve performance and process efficiency. This communication relies on the use of sensor data, hardware interfaces, transmission protocols, and control strategies, which all have an impact on the system’s reliability. However, as the number of functionalized electronic control units (ECUs) and wiring systems increases, advanced control systems encounter complex functional and cybersecurity issues. To mitigate this complexity, the automotive industry widely employs the controller Area Network (CAN) communication bus. Nevertheless, the inherent vulnerabilities of CAN and the rich interfaces with external environments increase the systems’ susceptibility to soft errors caused by uncertainty factors such as process changes. Therefore, detecting abnormalities in automotive CAN communication is *** paper introduces a machine learning (ML)-based anomaly detection framework to identify anomalies through CAN messages, extracting key features and employing ML models for predictive analysis. It also uses Triple Modular Redundancy (TMR) for trusted ML computation in anomaly detection. The study provides a comparative analysis of various ML algorithms, highlighting the effectiveness of Deep Neural Networks in identifying anomalies within both synthetic and real Hyundai CAN data for a wheel speed control system, showcasing the framework’s capability to enhance system reliability and security.
Aiming at the fact that the research of direct location algorithm needs a lot of simulation experiments and a large number of parameters are repeatedly modified in the complicated and huge algorithm program, a passive...
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Modern experience in the development and operation of automatic control systems for power units of sea and river vessels shows that the introduction of intellectual technologies is an indispensable condition for incre...
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In the offline sales process, we found that there may be characteristics of mutual influence between the sales of different categories of vegetables. Therefore, we hypothesized that there might be a potential link bet...
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Identifying upstream processes responsible for wafer defects is challenging due to the combinatorial nature of process flows and the inherent variability in processing routes, which arises from factors such as rework ...
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ISBN:
(数字)9798331531850
ISBN:
(纸本)9798331531867
Identifying upstream processes responsible for wafer defects is challenging due to the combinatorial nature of process flows and the inherent variability in processing routes, which arises from factors such as rework operations and random process waiting times. This paper presents a novel framework for wafer defect root cause analysis, called Partial Trajectory Regression (PTR). The proposed framework is carefully designed to address the limitations of conventional vector-based regression models, particularly in handling variable-length processing routes that span a large number of heterogeneous physical processes. To compute the attribution score of each process given a detected high defect density on a specific wafer, we propose a new algorithm that compares two counterfactual outcomes derived from partial process trajectories. This is enabled by new representation learning methods, proc2vec and route2vec. We demonstrate the effectiveness of the proposed framework using real wafer history data from the NY CREATES fab in Albany.
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