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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68649 条记录，以下是531-540 订阅

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Fast Correspondence Clustering by Cluster-Wise Spatial Compatibility for Point Cloud Registration 3

Fast Correspondence Clustering by Cluster-Wise Spatial Compa...

引用

3rd international conference on computer science, Electronic Information Engineering and Intelligent Control technology, CEI 2023

作者： Liu, Chen Zhang, Yifan Xu, Ziwen Ma, Jie School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China China Ship Development and Design Wuhan China

ISBN: (纸本)9798350372052

Spatial compatibility (SC) is a widely used similarity measure in outlier rejection methods. However, the single compatibility check used in the spatial compatibility measure is vulnerable to problems such as feature ambiguity, resulting in inaccurate or even incorrect alignment. To solve this problem, we extend the common spatial compatibility measure to correspondence cluster and propose the cluster-wise spatial compatibility (CSC) measure, which eliminates outliers by performing multiple compatibility checks between correspondence clusters. Then, to better utilize the advantages of CSC measure, we design an innovative and efficient correspondence clustering strategy to group the initial correspondences into different clusters. Finally, we use weighted SVD algorithm to solve the rigid transformation from reliable clusters and select the best model as the result. Sufficient experiments show that our method achieves excellent performance in both outdoor and indoor scenes. © 2023 IEEE.

关键词： Statistics

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IoT-Enabled Ethanol Detection System: A Transformative Stride in Ensuring Food Authenticity

IoT-Enabled Ethanol Detection System: A Transformative Strid...

引用

2023 international conference on System, Computation, automation and Networking, ICSCAN 2023

作者： Deenadayalan, T. Deepakraj, E. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350315127

In the present era, the rapid rise of IoT technology has brought forth innovative solutions, particularly in ensuring food safety. This study introduces an IoT-based ethanol detection system tailored to preserve the quality and security of food products. Ethanol, a key indicator of food spoilage, can endanger consumer well-being in excessive amounts. Food adulteration with hazardous substances like ethanol poses a serious public health challenge;the Food Safety and Standards Authority of India (FSSAI) reported that 30% of tested food samples (2017-2019) exceeded safe ethanol levels. Addressing this, we present an IoTbased Ethanol Detection System (IoTEDS), merging sensitive ethanol sensors and IoT tech. IoTEDS monitors ethanol levels in real-time across the food supply chain, enabling remote data analysis and swift risk detection. Through advanced algorithms, the system processes sensor data, generating precise alerts to prevent compromised product distribution. This tech enhances food safety, cuts losses, and safeguards public health. By incorporating touch-sensitive ethanol sensors with IoT capabilities, this research pioneers modern quality assurance, fostering transparent supply chains and industry accountability. IoTEDS' real-time monitoring, data analysis, and risk mitigation position it as a transformative stride in ensuring food authenticity. © 2023 IEEE.

关键词： Quality control

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Streamlined Deployment and Monitoring of Cloud-Native Applications on AWS with Kubernetes Prometheus Grafana

Streamlined Deployment and Monitoring of Cloud-Native Applic...

引用

2023 international conference on Advances in Computation, Communication and Information technology, ICAICCIT 2023

作者： Abirami, T. Mapari, Shrikant Jayadharshini, P. Krishnasamy, Lalitha Vigneshwaran, R. Ragavendra Kongu Engineering College Department of Information Technology Erode Tamilnadu Perundurai India Symbiosis International Pune India Kongu Engineering College Department of Artificial Intelligence Erode Tamilnadu Perundurai India Christ University School of Engineering and Technology Department of Computer Science and Engineering Bangalore Kengeri India

ISBN: (纸本)9798350344387

As organizations increasingly move their applications to the cloud, it becomes essential to have an efficient and cost-effective method for deploying and managing those applications. Manual deployment can be time-consuming, error-prone, and expensive. Additionally, managing logs and monitoring resources for each deployment can lead to even greater costs. To address these challenges, we propose implementing an automation strategy for deployment in the cloud. With automation, the deployment process can be streamlined and standardized across different cloud providers, reducing the potential for errors and saving time and resources. Furthermore, a central log system can be implemented to manage logs from different deployments in one location. This provides a unified view of all logs and allows for easier troubleshooting and analysis. automation can also be used to set up monitoring resources, such as alerts and dashboards, across different deployments. Overall, implementing an automation strategy for deployment in the cloud can help organizations save time and resources while improving their ability to manage and monitor their applications. A centralized log management system can further enhance these benefits by providing a unified view of logs from all deployments © 2023 IEEE.

关键词： ArgoCD AWS EC2 EKS Grafana Helm Keda Kubernetes Prometheus

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Trajectory Tracking Control of Autonomous Vehicles based on Improved Model-free Adaptive Control 3

Trajectory Tracking Control of Autonomous Vehicles based on ...

引用

3rd international conference on Testing technology and automation Engineering, TTAE 2023

作者： Wang, Wanting Wang, Siming Han, Taoguo School of Automation and Electrical Engineering Lanzhou Jiaotong University Lanzhou730070 China College of Computer and control engineering Northeast Forestry University Harbin150000 China

ISBN: (纸本)9781510674769

This paper presents a novel approach to address the lateral control issue in trajectory tracking for autonomous cars. Traditional model-free adaptive control algorithms have some limitations, prompting the development of an enhanced data-driven model-free adaptive control scheme. More precisely, inside a specified trajectory, the vehicle's issue of lateral control is converted into a problem of tracking the preview-deviation-angle. A dynamic linearized data model is developed for the lateral control of autonomous cars, taking into account the input and output data. To enhance the steering angle control rate, a time-varying proportional control term is incorporated. An enhanced trajectory tracking control technique for the MFAC system is proposed, followed by a demonstration of its convergence. The simulation findings demonstrate that the IMFAC scheme exhibits a superior output response compared to both MFAC and PID in both low-speed and high-speed scenarios. Furthermore, the IMFAC system is capable of achieving autonomous vehicle path tracking. © 2024 SPIE.

关键词： Autonomous vehicles

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Improvement of Simultaneous Localization and Mapping Based on Extended Kalman Filter using Iterative Closest Point Algorithm 9

Improvement of Simultaneous Localization and Mapping Based o...

引用

9th international conference on Control, Instrumentation and automation, ICCIA 2023

作者： Eraghi, Hasan Enami Taban, Mohammad Reza Bahreinian, Sayed Farzad Isfahan University of Technology Department of Electrical and Computer Engineering Isfahan84156-83111 Iran Subsea Science and Technology Research Institute Isfahan University of Technology Isfahan84156-83111 Iran

ISBN: (纸本)9798350366013

The Extended Kalman Filter (EKF) is one of the most common and widely used nonlinear estimators employed for Simultaneous Localization and Mapping (SLAM) tasks. In this paper, by employing the Iterative Closest Point (ICP) algorithm in the prediction step based on the updated information at the previous time, the accuracy of the EKF-based SLAM has been significantly improved. In the proposed method, we improve the accuracy of the robot's position estimation by matching two consecutive observations of the robot from its surroundings and then by using the position coordinates of reobserved landmarks between these two consecutive observations. Simulation results show that incorporating the ICP algorithm into the EKF-based SLAM significantly improves the accuracy of robot and landmarks position estimation. This method also exhibits better convergence and stability compared to the EKF-based SLAM. © 2023 IEEE.

关键词： Extended Kalman filters

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Memristor Modeling with Homeostatic Threshold Variation for Simulation and Application

Memristor Modeling with Homeostatic Threshold Variation for ...

引用

2023 international conference on Neuromorphic Computing, ICNC 2023

作者： Shi, Xinming Wang, Zilu University of Birmingham School of Computer Science BirminghamB15 2TT United Kingdom Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen518000 China School of Mechanical Engineering and Automation Shenzhen518000 China

ISBN: (纸本)9798350316889

This paper proposes a novel approach to emulating biological neural components using memristors. The nanoscale, resistance variability, and non-volatility of the memristor make it a suitable candidate for this task. A homeostasis-type switching mechanism is induced into the memristor modeling, inspired by the homeostatic switching behavior of biological neural components. The proposed model is generalizable and adaptable to various threshold-type memristor models. A SPICE model is proposed, and the memristor model is utilized to implement a neuron circuit that follows the homeostasis-type mechanism. A spiking neural network and its verification platform are designed, where pattern recognition can be achieved. The simulation is carried out in Cadence PSPICE, and a test comparison between scenarios with homeostasis and non-homeostasis is proposed. This work demonstrates the potential of memristors in implementing neuromorphic computing systems. © 2023 IEEE.

关键词： Memristors

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Machine Learning Model used Efficiently to Manage the Smart Grid and Renewable Energy

Machine Learning Model used Efficiently to Manage the Smart ...

引用

2023 international conference on New Frontiers in Communication, automation, Management and Security, ICCAMS 2023

作者： Narayan, Yogendra Selvaraj, Sivakumar Suryawanshi, Mahesh A. Ramya, S. Chandigarh University Department of Ece Mohali India VelTech Rangarajan Dr Sagunthala R and D Institute of Science and Technology Department of Electrical and Electronics Engineering Chennai India Bharati Vidyapeeth College of Engineering Department of Chemical Engineering Navi Mumbai India Kongu Engineering College Department of Computer Science and Engineering Erode India

ISBN: (纸本)9798350317060

A new technology, a Smart Grid Management System (SGMS), explains how it uses machine learning algorithms to distribute power more effectively. This article overviews intelligent grid management systems, including their design, advantages, and problems. Machine learning methods, including decision trees, neural networks, and Support Vector Machines (SVM), are also discussed in this study as they are employed in intelligent grid management systems. Increased efficiency, less waste, enhanced dependability, and decreased expenses are a few benefits of using deep learning techniques in intelligent energy systems for management. Protection of data, Security, and capacity are only some issues that arise when applying machine learning techniques to innovativegrid management systems. The report finishes with a discussion of potentialnext steps for machine research learning-based intelligent control systems for grids. © 2023 IEEE.

关键词： Support vector machines

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Framework for Faster-Than-Real-Time Testing of IEC 61499 Applications with Embedded Process Simulation 22

Framework for Faster-Than-Real-Time Testing of IEC 61499 App...

引用

22nd IEEE international conference on Industrial Informatics, INDIN 2024

作者： Vyatkin, Valeriy Rumiantcev, Roman Department of Electrical Engineering and Automation Aalto University Espoo Finland Department of Computer Science Computer and Space Engineering Lulea Tekniska Universitet Sweden

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527471

This paper presents a novel framework for testing automation applications compliant with the international standard IEC 61499 and including process simulation. The framework enables automation programs to be run in testing mode faster than real time, validated by an external tester program. Application of the approach is illustrated on example of a simple component-based system. © 2024 IEEE.

关键词： Automatic testing

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An Industry 4.0 Oriented Predictive Maintenance Solution Deployed in Real-World Automotive Manufacturing Facilities 24

An Industry 4.0 Oriented Predictive Maintenance Solution Dep...

引用

24th international conference on Control Systems and computer science, CSCS 2023

作者： Nicolae, Andrei Burlacu, Camelia Stanciu, Andrei Korodi, Adrian Posa, Bogdan Mihaila, Flavius Politehnica University Department of Automation and Applied Informatics Timişoara Romania Industrial Engineering Continental Automotive Romania Timişoara Romania

ISBN: (纸本)9798350313390

Industry 4.0 drives a significant revolution in the industrial manufacturing area in recent years, with predictive maintenance consolidating its potential to increase efficiency and productivity by reducing downtime. The research presented in the current paper transposes the previously mentioned concepts into a real-world automotive manufacturing facility. A software solution capable of predicting the probability of wear down-induced cylinder break downs was developed and installed at an industrial partner, aiming to reduce the number of productivity-impacting complete production line shutdown events. © 2023 IEEE.

关键词： Industry 4.0

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Software Entity Automated Visual Recognition Method Based on Deep Learning Algorithm 3

Software Entity Automated Visual Recognition Method Based on...

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3rd international conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, SPIoT2023

作者： Gao, Hui Shandong Transport Vocational College Weifang China

Automated visual recognition is a process that utilizes computer vision technology to analyze, process, and recognize images and videos, thereby achieving automation. It is an important branch of computer vision technology, bringing great convenience to people's production and life. This article mainly studies software entity automated visual recognition methods based on deep learning algorithms. Combining image processing technology and deep learning theory, a visual recognition method based on convolutional neural networks is proposed. On this basis, the advantages and disadvantages of this method were analyzed, and improvement suggestions were proposed to address its shortcomings. The experimental results show that the visual recognition method based on deep learning algorithm exhibits excellent performance in terms of accuracy and robustness. © 2023 Elsevier B.V.. All rights reserved.

关键词： automation

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