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检索条件"任意字段=3rd International Conference on Robotics and Control Engineering, RobCE 2023"

共 3888 条记录，以下是51-60 订阅

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Revolutionizing Biomedical engineering with Microcontroller Applications: A Comprehensive Review 3rd

Revolutionizing Biomedical Engineering with Microcontroller ...

引用

3rd international conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2023

作者： Pawase, Chinmay D’Souza, Sandra Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal India

ISBN: (纸本)9789819784288

This far-reaching study paper blends bits of knowledge from selected vital papers, featuring the instrumental job of microcontrollers in raising medical care diagnostics and checking. Microcontrollers, high level coordinated circuits with implanted handling capacities, are vital apparatuses for exact information procurement, top to bottom examination, and complex control frameworks, empowering momentous advancement in biomedical designing. The reconciliation of microcontrollers has become imperative for creating inventive clinical gadgets and analytic apparatuses as medical services progress. These conservative, superior stages are sent in different applications, from wearable wellbeing screens following imperative signs to implantable gadgets controlling insulin levels and supporting cardiovascular capabilities. They likewise assume a critical part in overseeing complex information streams, guaranteeing consistent transmission and capacity of patient data. The considered papers highlight microcontroller’s adaptability and effect in the biomedical field, upgrading analytic apparatus precision and unwavering quality, encouraging patient commitment and autonomy, and further developing medical care administrations. This paper has immensely encouraged in understanding the concepts gathered during the Microcontroller course and it gives a strong research base in the field of Microcontrollers. Microcontrollers have changed medical care by propelling diagnostics and observing accuracy, effectiveness, and availability. The cooperative energy among microcontrollers and biomedical applications has developed wonderful progressions for patients and medical care suppliers. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Diagnosis

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An online sparse least square support vector regression and particle filter for remaining useful life prediction of capacitive-type pressure transducer 3

An online sparse least square support vector regression and ...

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2024 3rd international conference on Aerospace and control engineering, ICoACE 2024

作者： Wang, Senlin Dai, Lingfeng Guo, Mingzhe Lu, Yikang Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences Fujian Fuzhou362200 China Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System Quanzhou362200 China Fujian College University of Chinese Academy of Sciences Fujian Fuzhou350002 China School of Advanced Manufacturing Fuzhou University Fujian Quanzhou350108 China School of College of Computer and Cyberspace Security Fujian Normal University Fujian350007 China

This paper proposes a novel online sparse least square support vector regression without bias for forecasting capacitive type pressure transducer remaining useful life prediction (RUL). The proposed approach is based on mechanism and statistical knowledge. The impedance variables are applied to calibrate the correlation between pressure capacitance capacity degradation and the resistance value to improve the prediction precision. Furthermore, a particle filter algorithm is proposed to estimate the pressure capacitance impedance fade parameters, and then the probability density function of the predicted RUL value is obtained by Gaussian. Lastly, experimental results consider #5 and #6. The pressure capacitance data set verifies the hybrid RUL prognostics strategy with high accuracy and robust stability. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Support vector regression

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Minimizing Average Job Completion Time for Multi-resource Queuing Computing Systems Using Drift-Plus-Penalty 3rd

Minimizing Average Job Completion Time for Multi-resource Q...

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3rd international conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Chen, Chuanxu Li, Ruiting Guan, Quansheng Shi, Zhan Zeng, Ying Zheng, Jianping School of Electronic and Information Engineering South China University of Technology Guangzhou China Electric Power Dispatch and Control Center Guangdong Power Grid Co. Ltd. Guangzhou China

ISBN: (纸本)9789819616978

The Lyapunov drift-based scheduling algorithms control the queue length to stabilize the system and maximize the throughput for multi-resource multi-queue cloud/edge systems. However, these algorithms often ignore the heterogeneity in job length, thus leading to a long delay for job processing. To this end, this paper takes the job completion time (JCT) as a penalty in the drift-plus-penalty expression to minimize the average job competition time, and proposes a Lyapunov drift-plus-time (LDPT) based scheduling algorithm for multi-resource queuing computing systems. The optimality of LDPT with respect to average JCT and queue length is analyzed. By using the Amazon EC2 to simulate, the results show that LDPT can improve average JCT and average queuing time fairness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Scheduling algorithms

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Using Sliding Mode controller to Trajectory Tracking of the Four Mecanum Wheel Mobile Robot Applied in Automotive Plants

Using Sliding Mode Controller to Trajectory Tracking of the ...

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Mechatronics, control and robotics (ICMCR), international conference on

作者： Tran Vo Dang Huy Bui Thanh Luan HUTECH Institute of Engineering HUTECH University Ho Chi Minh City Viet Nam Industrial Maintenance Training Center Ho Chi Minh City University of Technology (HCMUT) Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh (VNU-HCM) Thu Duc city Ho Chi Minh City Vietnam

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

This research paper proposes a mobile robot configuration tailored to optimize transportation processes for the Skoda automobile manufacturing plant. When operating in a factory, the FMWMR is subject to external disturbances and uncertainties, so the sliding mode control (SMC) method is introduced. The control law is derived by selecting an appropriate Lyapunov function based on the robot's dynamic model. Simulation results in Matlab demonstrate the effectiveness of the proposed control algorithm in enabling the robot to follow predefined trajectories.

关键词： Uncertainty Trajectory tracking Simulation Wheels Production facilities Hardware Manufacturing Mobile robots MATLAB Sliding mode control

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Application of 3D geological modeling to analyse Fault-controlled hydrocarbon accumulation in complex structural zones: a case study of the northern part of qikou sag 3

Application of 3D geological modeling to analyse Fault-Contr...

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3rd international conference on Geographic Information and Remote Sensing Technology, GIRST 2024

作者： Chen, Yan Liu, Haitao Jiang, Zhenglong Sun, Jinghui Zhao, Changyi Wang, Jufeng Sun, Deqiang Tang, Zijun Zhang, Chunming Wu, Fengcheng School of Ocean Sciences China University of Geosciences Beijing100083 China Research Institute of Petroleum Exploration and Development Beijing100083 China Beijing Institute of Geo-Environment Monitoring Beijing100195 China Institutes of Science and Development Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781510689077

The Qikou sag forming massive of fault-type oil and gasreservoirs. Based on previous achievements and data such as three-dimensional seismic data, this article analyzes the relationship between faults and petroleum and natural gas reservoirs in the northern part of Qikou sag through three-dimensional geological modeling. The results show that the faultcontrolled reservoir model in the study area can be roughly divided into four types: synthetic fault shielding oil and gas accumulation mode, antithetic fault shielding oil and gas accumulation mode, cross-fault shielding type petroleum and gas accumulation mode, and fault reactivation control secondary oil and gas accumulation mode. This 3D structural model shows that fault-controlled reservoir characteristics in the northern part of Qikou sag in three-dimensional space. © 2025 SPIE.

关键词： Gasoline

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Geometric control Methods for On-Orbit Assembly of Modular Spacecraft Cluster

Geometric Control Methods for On-Orbit Assembly of Modular S...

引用

Mechatronics, control and robotics (ICMCR), international conference on

作者： Jingxian Wang Rong Chen Yuzhu Bai Yong Zhao College of Aerospace Science and Engineering National University of Defense Technology Changsha China

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

In this paper, a cluster geometry control method is proposed for the problem of on-orbit assembly of modular spacecraft clusters. The method bases the cluster system on a manifold. A collision avoidance constraint that does not generate terminal position mutual exclusion is designed for the characteristics of the assembly problem. Assembly and task time constraints are further considered to integrate the non-convex multiple constraints with the system metric matrix. Finally, model predictive control is used to realize tracking control. Simulation results show that the method can arrive at the target position to complete the on-orbit assembly within any initial position and different fixed time constraints and achieve the purpose of energy optimization.

关键词： Space vehicles Manifolds Target tracking Self-assembly Trajectory planning Simulation Trajectory Time factors Collision avoidance Assembly

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Employing the ResNet50 and InceptionV3 Models for the Detection of Diseases in Both Strawberry Leaves and Fruit 3rd

Employing the ResNet50 and InceptionV3 Models for the Detect...

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3rd international conference on Trends in Electronics and Health Informatics, TEHI 2023

作者： Shadman Sakib Mahee, B.M. Fazle Rabbi, M.M. Khanom, Tasnuba Akter, Sanu Usha, Nusrat Jahan Hasan, Md. Rabby Department of Computer Science and Engineering Bangladesh University of Business and Technology Dhaka1216 Bangladesh

ISBN: (纸本)9789819739363

The study uses powerful learning methods to identify powdery mildew and leaf scorch on strawberry fruit and leaves. The suggested solution combines ResNet50 and InceptionV3 cognitive neural networks. This strategy involves collecting powdery mildew and leaf scorch datasets and improving them. ResNet50 and InceptionV3 extract discriminative features and detect powdery mildew and leaf scorch patterns. The aggregate characteristics are put into a fully connected layer and a softmax classifier for illness classification. An optimized technique adjusts the model’s hyperparameters during training for optimal classification performance. Comprehensive testing shows that the combined model beats ResNet50, InceptionV3, and other illness diagnostic approaches. Integration of information utilizing fusion approaches improves representation and illness diagnosis. Research suggests that the reinforcement learning-based approach can identify powdery mildew and leaf scorch in strawberry fruits with an accuracy rate of 98.42% and a validation rate of 99%. This technology impacts strawberry crop disease control. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Fruits

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TinyML Speech Classification Embedded Ai Module for Hand Rehabilitation Device

TinyML Speech Classification Embedded Ai Module for Hand Reh...

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Mechatronics, control and robotics (ICMCR), international conference on

作者： Arkorn Numsomran Arjin Numsomran Jutarut Chaoraingern Triam Udom Suksa Pattanakarn Suvarnabhumi School Bangkok Thailand Department of Instrumentation and Control Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Robotics and AI Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

Recent advancements in artificial intelligence and machine learning have significantly improved healthcare, especially in the development of assistive technologies for rehabilitation. This paper introduces a method for hand rehabilitation that utilizes the capabilities of tiny machine learning to enhance speech classification in a rehabilitation device. The proposed method employs a CNN model capable of classifying speech signals that are indicative of different hand movement patterns. Patients emit these speech signals during prescribed hand exercises, which are crucial for their rehabilitation process. The main focus of this study is on training and deploying a speech classification system that can work in the resource-limited environment of TinyML platforms. We detail the process of capturing speech data, preprocessing it, and extracting the most features relevant to different hand movements. Our results show that using TinyML to help with hand rehabilitation works. The method we came up with shows how TinyML could change the way rehabilitative devices are controlled, and it also shows us what personalized and easy-to-use rehabilitation tools might look like in the future.

关键词： Hands Training Technological innovation Tiny machine learning Medical treatment Speech recognition Transforms Speech enhancement Feature extraction Robots

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Deep Learning Precision Farming: Identification of Bangladeshi-Grown Fruits Using Transfer Learning-Based Detection 3rd

Deep Learning Precision Farming: Identification of Banglades...

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3rd international conference on Trends in Electronics and Health Informatics, TEHI 2023

作者： Siddiki, Marjuk Ahmed Rony, Mohammad Abu Tareq Naim Hossain, Md. Saha, Pritom Islam, Mohammad Shariful Ahmed, Ishtiak Satu, Shoykth Shaharior Ahammad, Mejbah Nazmul Alam, Shah Md. Computer Science and Engineering Daffodil International University Dhaka Bangladesh Noakhali3814 Bangladesh Noakhali3814 Bangladesh Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh Computer Science and Engineering Shaikh Burhanuddin Post Graduate College Dhaka Bangladesh Computer Science and Engineering American International University Bangladesh Dhaka Bangladesh Masters of Computer Science University Arizona State University TempeAZ United States

ISBN: (纸本)9789819739363

The dynamic potential of Convolutional Neural Networks (CNN) enhanced by Transfer Learning offers a promising avenue for object recognition within the realm of agriculture. To explore this potential in the context of Bangladeshi agriculture, this study leverages CNN enhanced by Transfer Learning to identify Bangladeshi-grown fruits from a dataset featuring 24 distinct types, including Mango, Jackfruits, and Lychee, among others. Utilizing an extensive dataset that encapsulated high-quality images of these fruits, we embarked on a comparative analysis of six advanced CNN architectures: VGG19, Xception, ResNet152V2, MobileNet, DenseNet201, and NASNetLarge. The results were illuminating. While VGG19 lagged behind with an accuracy of 48%, most models showcased impressive performance, with DenseNet201 emerging as the frontrunner at a remarkable 95% accuracy. The findings not only underscore the transformative role of Transfer Learning in optimizing CNN performance, especially when faced with limited labeled datasets, but also spotlight the applicability of these models in revolutionizing quality control and management within the Bangladeshi agricultural sector. As the demand for automated and accurate agricultural systems gains traction globally, the insights from this research offer a foundation for further exploration and application in similar contexts, demonstrating the scalability and adaptability of Transfer Learning-enhanced CNNs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Incremental Sliding-Mode control for Morphing Flight Vehicles Subject to Mismatched Uncertainties and Input Saturations

Incremental Sliding-Mode Control for Morphing Flight Vehicle...

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Mechatronics, control and robotics (ICMCR), international conference on

作者： Siyu Hua Xugang Wang Zhongyuan Wang Heow Pueh Lee Department of Mechanical Engineering School of Energy and Power Engineering Nanjing University of Science and Technology National University of Singapore School of Energy and Power Engineering Nanjing University of Science and Technology Department of Mechanical Engineering National University of Singapore

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

This work focuses on a novel incremental sliding mode controller (ISMC), integrated with an anti-windup compensator (AW), for a morphing flight vehicle subject to uncertainties and input saturations. The ISMC consists of two loops based on a control-oriented model of the morphing vehicle with symmetric-sweep wings. Theoretical analysis shows that there is no need to apply chattering reduction methods as the ISMC itself is a continuous function without any approximation compared to conventional sliding mode control structures. The ISMC also has demonstrated enhanced robustness against matched uncertainties and, notably, mismatched uncertainties. Furthermore, it exhibits some anti-saturation capability. By incorporating the AW design, the system achieves improved robustness against uncertainties and input constraints with reduced model dependency. The advantages of ISMC-AW are validated through comparative simulations under multiple uncertainties. Compared with an adaptive sliding mode controller combined with an anti-saturation auxiliary system (ASMC-AS), the proposed ISMC-AW demonstrates smaller tracking errors, a higher convergence rate, and lower vibration amplitudes, and it can help the actuator exit the saturation region rapidly.

关键词： Vibrations Adaptation models Uncertainty Mechatronics Adaptive systems Robustness Sliding mode control Robots Convergence Aerospace control

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