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检索条件"任意字段=International Conference on Advances in Science, Engineering and Robotics Technology"

共 47833 条记录，以下是1201-1210 订阅

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Advancements in Fault-Tolerant Quantum Error Correction for Current Progress and Future Directions 2

Advancements in Fault-Tolerant Quantum Error Correction for ...

引用

2nd IEEE international conference on advances in Information technology, ICAIT 2024

作者： Karthick, V. Prabhu, M. Ramkumar Nancy, P. Devipriya, A. Rosaline, R. Anto Arockia Department of Computer Science and Engineering Rajalakshmi Engineering College Thandalam Chennai India Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur Campus Chengalpattu India

ISBN: (纸本)9798350383867

Fault-tolerant quantum error correction (FTQEC) is pivotal for ensuring the reliability and scalability of quantum computers, which harness quantum mechanics principles. This paper presents a comprehensive analysis of FTQEC methodologies, integrating theoretical investigations, experimental validations, error correction capabilities, and simulation comparisons. Theoretical frameworks reveal high error correction capabilities, with success rates ranging from 0.88 to 0.95 and significant error rate reductions of up to 98%. Experimental validations across diverse quantum hardware platforms demonstrate promising results, with high success rates and notable error correction efficiency, albeit challenges in scalability. Analysis of error correction capabilities highlights robustness against errors and preservation of qubits integrity during error correction procedures. Simulation comparisons further validate the efficacy of FTQEC protocols, showing significant improvements in error rate reduction and gate fidelity. However, scalability and resource overhead remain concerns, necessitating further research for efficient and scalable FTQEC protocols. Overall, this study contributes to the understanding and advancement of fault-tolerant quantum error correction, crucial for realizing the transformative potential of quantum computing technology. © 2024 IEEE.

关键词： Quantum computers

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Semantic Segmentation-based Algorithm for Visual Measurement of Rotor Shaft Vibration Features 7

Semantic Segmentation-based Algorithm for Visual Measurement...

引用

7th international conference on robotics, Control and Automation engineering, RCAE 2024

作者： Jiang, Shu Zhao, Jixing Liu, Bingyou Zhang, Dongxiang Anhui Polytechnic University Dept. School of Electrical Engineering Wuhu China Chaohu Power Generation Co. Ltd. Dept. R&d Department Huaneng ChaoHu China Tianbing Electronic Technology Co. Ltd. Dept. R&d Department Anhui Wuhu China

ISBN: (纸本)9798350355642

When detecting rotating objects, the rotating objects are usually in complex industrial environments with complex backgrounds and many interferences. Traditional visual measurement methods are difficult to effectively distinguish between the rotating object and the background, resulting in measurement errors. In this paper, a spindle is used as the image acquisition medium, and a semantic segmentation method based on deep learning is introduced to solve the difficulty of visual vibration measurement of rotating shafts. The semantic segmentation network outperforms the traditional visual measurement methods in extracting the features of rotating objects, and the network model, based on the improvement of U-Net, incorporates the improved CSimAM attention mechanism in each of the encoding and decoding stages of the bottleneck layer, which makes the network more adept at segmenting rotary axes in backgrounds with different lighting, blurring and similarity. The study in this paper not only verifies the effectiveness and superiority of the improved U-KAN network in the visual measurement of rotor shaft vibration displacement, but also provides an important theoretical and practical basis for subsequent research. © 2024 IEEE.

关键词： Semantic Segmentation

来源：评论

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Moodle plugin for real-time face recognition in online exams for Systems engineering and Computer science students at Universidad Continental, Huancayo, Peru 5

Moodle plugin for real-time face recognition in online exams...

引用

5th international conference on robotics and Computer Vision, ICRCV 2023

作者： Vargas, Miguel Torres Valle, Luis Fernando Rojas Vera, Diego Porras Moreno, Daniel Gamarra School of System Engineering and Computer Science Universidad Continental Huancayo Peru

ISBN: (纸本)9798350326369

Facial recognition systems on learning platforms like Moodle enable fast and efficient evaluation, automating the detection of impersonation in online exams. This project implements a Moodle plugin that performs facial recognition on the student attempting to take a quiz. It consists of two parts for authentication through a webcam: the first part occurs before accessing the quiz, and the second part involves surveillance through a camera during the quiz. The plugin was developed using the PHP and JavaScript programming languages, as well as Face-api. The JavaScript API detects and recognizes faces in the web browser using Tiny Yolo v2 and FaceRecognizerNet. It compares a student's photo or image with the image from their webcam while they are taking the quiz. The Moodle plugin achieved an average error probability of 39.39% for face detection similarity distance. © 2023 IEEE.

关键词： Students

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POSITIONING ACCURACY ANALYSIS FOR AN ELECTROMECHANICAL COUPLED ROBOTIC JOINT MODULE UNDER UNCERTAINTIES 14

POSITIONING ACCURACY ANALYSIS FOR AN ELECTROMECHANICAL COUPL...

引用

14th international conference on Quality, Reliability, Risk, Maintenance, and Safety engineering, QR2MSE 2024

作者： Wu, Jun Wang, He Wang, Qiyu Qu, Hongchen Xiahou, Tangfan Chen, Cen Liu, Yu School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Center for System Reliability and Safety University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China

ISBN: (纸本)9781837242672

The robotic joint module is a typical mechatronic system that inevitably faces uncertainties from various fields. These uncertainties significantly influence its positioning accuracy. In this article, we develop a positioning accuracy analysis of a robotic joint module under such uncertainties. First, a comprehensive electromechanical coupling model is constructed by considering the information exchange rules between mechanical and electronic components. Subsequently, a positioning accuracy analysis is performed, taking into account uncertainties from different fields. A variance-based sensitivity analysis method is employed to represent the contribution of these uncertainties. Finally, simulations are carried out to evaluate the effectiveness of the proposed method. © The Institution of engineering & technology 2024.

关键词： Sensitivity analysis

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A Comparative Study of Pre-trained CNNs and GRU-Based Attention for Image Caption Generation 5

A Comparative Study of Pre-trained CNNs and GRU-Based Attent...

引用

5th international conference on robotics and Computer Vision, ICRCV 2023

作者： Khan, Rashid Huang, Bingding Hassan, Haseeb Zaman, Asim Ye, Zhongfu University of Science and Technology of China Hefei College of Big Data and Internet SZTU Shenzhen China College of Big Data and Internet SZTU Shenzhen China College of Health Sciences and Environmental Engineering SZTU Shenzhen China Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei China

ISBN: (纸本)9798350326369

Image captioning is a challenging task involving generating a textual description for an image using good computer vision and natural language processing techniques. This paper proposes a deep neural framework for image caption generation using a GRU-based attention mechanism. Our approach employs multiple pre-trained convolutional neural networks as the encoder to extract features from the image and a GRU-based language model as the decoder to generate descriptive sentences. To improve performance, we integrate the Bahdanau attention model with the GRU decoder to enable learning to focus on specific image parts. We evaluate our approach using the MSCOCO and Flickr30k datasets and show that it achieves competitive scores compared to state-of-the-art methods. Our proposed framework can bridge the gap between computer vision and natural language and can be extended to specific domains. © 2023 IEEE.

关键词： Computer vision

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Research on Fuzzy Control of Two-stage ISD Suspension Based on Variable Inerter 3

Research on Fuzzy Control of Two-stage ISD Suspension Based ...

引用

3rd international conference on Control and Intelligent robotics, ICCIR 2023

作者： Linhao, Jin Jingjing, Fan Fu, Du Ming, Zhan School of Electrical and Control Engineering North China University of Technology Beijing100144 China School of Mechanical Engineering Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781510671867

In order to better balance the driving safety and ride comfort of the car, a new two-stage semi-active suspension structure is designed with three elements of variable inerter, spring and damper as the suspension structure. Firstly, the ISD semi-active suspension is set up in Matlab/Simulink;Besides both the road model and fuzzy controller model are set up to simulate the dynamics of three schemes, namely passive ISD suspension, inerter PID control and inerter fuzzy control respectively. The results indicate that the performance of ISD suspension adopting the fuzzy control strategy is better, compared with the passive ISD suspension and the ISD PID-controlled suspension. thus it verifies the superiority of using fuzzy control strategy. © 2023 SPIE.

关键词： Fuzzy control

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DDPG-based Reactive Power Optimization Strategy For Active Distribution Network 7

DDPG-based Reactive Power Optimization Strategy For Active D...

引用

7th international conference on Intelligent robotics and Control engineering, IRCE 2024

作者： Liu, Xinghua Wang, Xiaoyu Fan, Bangji Li, Beibei Deng, Ruilong Kong, Minru Xi'an University of Technology School of Electrical Engineering Xi'an China Sichuan University Chengdu China Zhejiang University Hangzhou China State Grid Xi'an Power Supply Company Xi'an China

ISBN: (纸本)9798350352399

To tackle challenges such as voltage fluctuations and network losses arising from integrating distributed energy resources into the grid, this paper proposes a novel reactive power optimization approach for active distribution network based on deep reinforcement learning. Diverging from conventional methods, our approach models reactive power optimization as a constrained Markov decision process, encompassing the determination of reactive power outputs from photovoltaic sources and compensation devices. By employing a deep deterministic policy gradient algorithm, the agent learns to make daily decisions based on the state of the environment. The methodology incorporates distributed control by training the agent to formulate optimal coordination strategies for photovoltaic inverters and capacitors. The efficacy of our proposed method is demonstrated by a comprehensive analysis conducted on a modified IEEE 33-node distribution network. The results highlight the superior performance in reducing active losses and mitigating voltage offsets compared to conventional methods. © 2024 IEEE.

关键词： Power distribution networks

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Research on Intelligent Extraction Methods for Key Regions in Hyperspectral Images

Research on Intelligent Extraction Methods for Key Regions i...

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2024 IEEE international conference on Control science and Systems engineering, ICCSSE 2024

作者： Wang, Yunsen Cui, Weiguang Yang, Haifeng Cao, Yangchuang Wang, Haoxuan Kang, Yang Shandong Institute of Space Electronic Technology China Academy of Space Technology Yantai China

ISBN: (纸本)9798331517199

In response to the problem of high complexity and inaccurate extraction of key areas in hyperspectral satellite images, this paper proposes an intelligent extraction method for key areas in hyperspectral images. Firstly, the feature layer fusion target spectral signal matching detection method is adopted, and the subspace projection method is used to suppress background clutter signals and enhance the contrast between the target and background clutter to extract the target area. In the absence of any prior information on key area targets, this method uses anomaly detection algorithms to perform coarse screening on abnormal areas. Finally, key area detection is achieved through the fusion of target spectral signal matching detection and anomaly detection decision level fusion in the feature layer. Experimental results show that the proposed method can effectively suppress clutter signals, enhance the distinguishability between targets and backgrounds, and handle situations whether or not the prior spectral information is known. Moreover, the algorithm has strong robustness and low processing complexity. © 2024 IEEE.

关键词： Radar clutter

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A Fusion of CNN, MLP, and MediaPipe for Advanced Hand Gesture Recognition

A Fusion of CNN, MLP, and MediaPipe for Advanced Hand Gestur...

引用

2024 IEEE international conference on Recent advances in science and engineering technology, ICRASET 2024

作者： Priyanka, K. Rithik, R. Jaswanth, C. Rajesh, C. Nitte Meenakshi Institute of Technology Dept. of Ise Bangalore India

ISBN: (纸本)9798350388602

Hand gesture recognition has become evident as a critical component in human-centered computing systems. It provides users a natural intuitive way for users to interact with technology. The system introduced a concept of Gesture Fusion, a novel approach that leverages the complementary strengths of Convolutional Neural Networks (CNN), Multi-Layer Perceptron (MLP), and the MediaPipe framework to achieve robust hand gesture recognition. By integrating these advanced techniques, fusion of models surpasses the limitations of individual model, delivering improved accuracy and robustness in recognizing a diverse range of hand gestures. The proposed system begins by preprocessing input images using CNNs to extract informative spatial features. Simultaneously, it utilizes the MediaPipe framework to accurately detect and localize key hand landmarks. These landmarks are then processed by MLPs to capture intricate patterns and variations in hand gestures that may not be fully captured by CNNs alone. By combining the outputs of both CNN and MLP models through a weighted fusion mechanism, synthesizes a comprehensive understanding of hand gestures, resulting in more precise and reliable recognition outcomes. Through significant research and evaluation on benchmark datasets, Fusion model outperforms independent CNN and MLP models. The findings obtained demonstrates the improved accuracy, resilience, and adaptability in a variety of real-world circumstances, confirming its potential to revolutionize the field of hand gesture detection. It advances the pursuit for more natural and intuitive human-computer interaction paradigms by seamlessly combining cutting-edge technologies and approaches. © 2024 IEEE.

关键词： Convolutional neural networks

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A Light Waveguide Bending Sensor with a High Sensing Range and High Sensitivity

A Light Waveguide Bending Sensor with a High Sensing Range a...

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2024 IEEE international conference on Real-Time Computing and robotics, RCAR 2024

作者： Liu, Zeyu Li, Zhengwei Wei, Jiachen Li, Houcheng Zou, Yongxiang Meng, Deyuan Cheng, Long Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China

ISBN: (纸本)9798350372601

The optical waveguide bending sensor offers numerous advantages, including high sensitivity, compact size, immunity to electromagnetic interference, corrosion resistance, and biocompatibility. These attributes have led to its extensive adoption in robotics systems. This study introduces a highly sensitive optical waveguide bending sensor with a wide range. Structural optimizations are implemented in the standard waveguide system to minimize interference from ambient light and unwanted deformation. The responses of four core materials to different curvatures and bending angles are thoroughly examined. The experimental findings confirm the efficacy of the cladding modifications and reveal distinct sensitive ranges for each material. Building on the results from single-core waveguides, a tri-core waveguide is developed to broaden the sensor's sensitive range from less than 60° to 120°, resulting in over a 30% reduction in the error of bending angle sensing compared to single-core waveguides. Additionally, the sensor's ability to monitor joint angles is demonstrated through evaluations performed on the wrist and ankle joints. © 2024 IEEE.

关键词： Corrosion resistance

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