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共 1356 条记录，以下是191-200 订阅

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ChatGPT: Information Retrieval from Image using Robotic Process automation and OCR 7

ChatGPT: Information Retrieval from Image using Robotic Proc...

引用

7th international conference on Intelligent Computing and Control systems, ICICCS 2023

作者： Shidaganti, Ganeshayya Sanjana, R. Shubeeksh, K. Monish Raman, V.R. thakshith, Valmeeki M.S. Ramaiah Institute of Technology Dept. of Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9798350397253

ChatGPT hit 1M users in just 5 days once it went public, the leading companies such as Facebook, Instagram, Spotify, Netflix took several months to years to achieve this mark. As a result of the conversational AI Chabot being hailed as a technological revolution, ChatGPT has emerged as one of the year's most popular buzzwords. this research study intends to initiate interaction with ChatGPT more convenient to users by using user sent WhatsApp images containing text as input by converting it into text-based prompt which is accepted by ChatGPT and provide the user with the response generated by ChatGPT. this is achieved by integrating RPA to automate an in-depth examination of images for information discovery using OCR to extract text and ChatGpt to retrieve information. this research study also focuses on providing a quick response to the user by comparing images with previous users' inputs and sending the same response in case there is repetition of images which increases efficiency in terms of computation resources too. the proposed solution is designed to provide a quick suitable response to the user inscribed text in the image. © 2023 IEEE.

关键词： robotics

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Fault Diagnostic Opportunities for Electromagnetic Coils of Active Magnetic Bearings using Physics-of-Failure Analysis

Fault Diagnostic Opportunities for Electromagnetic Coils of ...

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System Reliability and Safety Engineering (SRSE), international conference on

作者： Ruiqi Li Kai Wang Peng Zeng Jiwei Cao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Department of Electrical Engineering Harbin Institute of Technology China

Active magnetic bearings (AMBs) have many advantages over traditional oil bearings due to their non-contact characteristics. they are environmentally friendly solution and have been proven to be highly reliable and available. Electromagnetic coils are vital components of AMB and they are failure prone. In this paper, the failure mode of magnetic bearing coil and its corresponding failure mechanism are reviewed by FMMEA method, and the existing coil fault diagnosis methods are introduced. Future directions for coil insulation health monitoring aiming at the application characteristics of AMBs are also discussed.

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Research on information security risk assessment based on integrated influence of neighborhood 6

Research on information security risk assessment based on in...

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6th international conference on Electronic Information Technology and Computer Engineering, EITCE 2022

作者： Wang, Tianyu Zhao, Jianming Zhang, Bowen Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781450397148

At present, the information technology of industrial automation control system is developing rapidly, and the system information security is facing severe challenges. Accurate and efficient risk assessment of industrial control systems is conducive to their protection and efficient production. Although there have been quite a few studies on the risk assessment of industrial control systems, there is less consideration of the interaction between the equipment in the system at present. In view of this, this paper proposes an information security risk assessment method based on the impact of neighborhood integration, which can fully consider the changes of equipment functions within the damaged range of industrial control systems. the experimental results in some model systems reveal that the algorithm in this paper can evaluate the information security risks of industrial control systems more accurately, and provides a theoretical method for the stable operation of industrial systems. © 2022 Association for Computing Machinery.

关键词： Risk assessment

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Practical Integration of IoT Sensor Data with Open-Source ERP: Optimizing Processes, Driving Insights, and Enabling Smart Vision and Full Business automation

Practical Integration of IoT Sensor Data with Open-Source ER...

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Artificial Intelligence, robotics and Control (AIRC), international conference on

作者： Ahmed Lamey Hatem Abdelkader Arabi Keshk Sherif Eletriby Computer Science Department Faculty of Computers & Information Minoufia University Menofia Egypt Information System Department Faculty of Computers & Information Minoufia University Menofia Egypt

ISBN: (数字)9798350385076

ISBN: (纸本)9798350385083

the integration of Internet of things (IoT) sensor data with Enterprise Resource Planning (ERP) systems has emerged as a pivotal technology-driven initiative, offering vast potential for process optimization, enhanced data-driven decision-making, and profound business impact. this research endeavors to delve into this integration, comprehensively examining the implications for organizations, with a practical project serving as a proof of concept. the study scrutinizes the intricacies of IoT sensor integration with ERP systems, shedding light on the optimization of business processes and the extraction of valuable data insights. In addition, the research extends its focus towards “smart vision” technologies, aiming to achieve a higher level of automation and real-time decision support. the core of this research lies in the practical project, where a proof of concept is executed to integrate temperature sensors with the Odoo ERP system. this project serves as a real-world demonstration of the integration's applicability and the tangible benefits it brings. By bridging the gap between theoretical concepts and practical implementation through this proof of concept, the study aims to provide actionable insights for organizations looking to harness the power of IoT sensor data, smart vision, and automation within their ERP systems. the outcomes of this research not only contribute to the growing body of knowledge on IoT-ERP integration but also provide a roadmap for organizations to leverage these technologies effectively in the modern business landscape.

关键词： Temperature sensors automation Decision making Organizations Machine learning Robot sensing systems Real-time systems

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A Multi-scale Temporal Convolutional Network-based Method for sEMG Upper Limb Motion Intention Recognition 5

A Multi-scale Temporal Convolutional Network-based Method fo...

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5th international conference on Intelligent robotics and Control Engineering, IRCE 2022

作者： Zhu, Yuxuan Li, Xing Wang, Jianhui Ji, Ying Sun, Yuechao School of Information Science and Engineering Northeastern University Shen Yang China School of Electrical Engineering & Intelligentization Dongguan University of Technology China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shen Yang China School of Information Science and Engineering Shenyang Ligong University Shenyang China

ISBN: (数字)9781665469951

ISBN: (纸本)9781665469951

Surface electromyographys (sEMG) is an electrical signal generated by human muscle contraction, it is easy to obtain, less invasive, and contains rich motor information. It is widely used in medical and rehabilitation fields. In this paper, we propose a motion intention recognition method based on a multi-scale temporal convolutional network(TCN) model. We extract the time domain features and frequency domain features of each channel of sEMG to form a feature vector. then we use TCN of different sizes to extract features of different scales for feature fusion to improve the recognition accuracy. the experimental results show that the average recognition accuracy is 85.1% for 12 upper limb movements, which is better than the traditional machine learning methods and single-scale TCN, verifying the superiority of the proposed method. © 2022 IEEE.

关键词： Frequency domain analysis

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Zero-Shot Kidney Stone Segmentation Based on Segmentation Anything Model for Robotic-Assisted Endoscope Navigation 16th

Zero-Shot Kidney Stone Segmentation Based on Segmentation A...

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16th international conference on Intelligent robotics and Applications, ICIRA 2023

作者： Meng, Hui Chen, Lingkai Zhu, Shiqiang Fei, Chentao Zhang, Yong Zheng, Miaojuan Han, Jianda Song, Wei School of Intelligent Science and Technology Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences 1 Sub-lane Xiangshan Hangzhou310024 China Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Hangzhou ElephantChain Network Technology Co. Ltd. Hangzhou China Faculty of Mechanical Engineering and Automation Zhejiang Sci-Tech University Hangzhou310018 China College of Artificial Intelligence and Tianjin Key Laboratory of Intelligent Robotics Institute of Robotics and Automatic Information Systems Nankai University Tianjin300350 China

ISBN: (纸本)9789819964888

Biomedical robotics has had a significant impact on flexible ureteroscopy (FURS) for the management of nephrolithiasis. the biomedical robots provide a suitable and safe platform for FURS. However, operating the robots expertly still represents a challenge for surgeons. Vision-based navigation is an effective means to simplify the operations of robots by surgeons, which has great potential to improve surgical efficiency. To achieve vision-based navigation, the localization of kidney stones in endoscopic images is the first step. In this paper, we propose a stone segmentation method (SSM) based on zero-shot learning, which consists of segmentation anything model (SAM), an image preprocessing module, and a mask postprocessing module. the SAM segments all objects in endoscopic images, which lack semantic information. the preprocessing module is designed to suppress interference of reflective area in endoscopic images, and the mask postprocessing module is used to filter noise masks. the experimental results on our collected endoscopic images indicate that our method achieves close accuracy on stone segmentation compared with supervised U-Net and VGG_U-Net, which significantly outperforms the Ostu and the SAM. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Endoscopy

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the Method of Basic Functions in the Analysis of Monomer Conversion in Radical Polymerization

The Method of Basic Functions in the Analysis of Monomer Con...

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international conference on Control systems, Mathematical Modelling, automation and Energy Efficiency (SUMMA)

作者： D. R. Gizzatov A. A. Kornilova G. K. Khisametdinova E. R. Gizzatova Institute of Chemistry and Protection in Emergency Situations Ufa University of Science and Technology Ufa Russia Institute of Mathematics Computer Science and Robotics Ufa University of Science and Technology Ufa Russia

In this paper, for the process of radical polymerization, a method is used to obtain basic functions linking the kinetic constants of the process rates. It is shown that when analyzing the conversion curve, depending on different basic functions, the intervals of stationary and non-stationary modes of operation of the process are sufficiently well visualized and determined. At the same time, parametrizing the basic functions of the degrees of expenditure of the initiator and the monomer, it is possible to obtain monomodal curves, the peak values of which are analogs of the values of the velocity constants. the obtained graphical dependencies indicate the adequacy of the research.

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Wheel-Inertial Fusion Localization Strategy for Mobile Robots in Confined Pipeline Spaces

Wheel-Inertial Fusion Localization Strategy for Mobile Robot...

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robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： Hongpeng Liang Shuyue Zhang Jianliang Mao Chuanlin Zhang College of Automation Engineering Shanghai University of Electric Power Shanghai China

Pipeline robots hold significant promise in fields like large-scale industrial manufacturing and electric energy production. However, their current limitations in precise positioning and autonomous operation are primarily due to the constraints of the narrow and confined pipeline environments. To address the common issue of noise interference with conventional inertial positioning systems, we propose an enhanced wheel-inertial fusion positioning framework aimed at achieving effective robot positioning for short to medium-range travel. this method comprises a front-end positioning module and a parallel-running back-end positioning module. In the front-end positioning, robot pose is calculated based on data from inertial measurement units (IMU) and wheel encoders, utilizing the error state Kalman filter (ESKF) fusion algorithm and graph optimization. the back-end module focuses on global optimization of historical poses and inertial parameters through graph optimization. Additionally, the system estimates certain inertial parameters during the system's initialization phase. Experimental results show that the method presented in this paper effectively improves the robot's positioning accuracy in closed pipelines.

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Wave Problems of the Influence of Acoustic Pressure on the Accuracy of Inertial Sensors 5

Wave Problems of the Influence of Acoustic Pressure on the A...

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5th international conference on Control, robotics and Informatics, ICCRI 2022

作者： Korobiichuk, Igor Mel'nick, Viktorij Shybetskyi, Vladyslav Kostyk, Sergii Kalinina, Myroslava Warsaw University of Technology Institute of Automatic Control and Robotics Warsaw Poland National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Kyiv Ukraine

ISBN: (数字)9781665468008

ISBN: (纸本)9781665468008

this research is devoted to the study of the nature and degree of the influence of acoustic radiation, as well as the mechanical models of the disturbed movement, depend on the ratio between the dimensions of the product and half the length of the sound wave. the studied parameters of a double-shell structure with a rectangular hole in the conditions of irradiation with sound waves of different frequencies, namely: shell velocity, linear deformations and acoustic pressure, are important for predicting the behavior of the gyroscope shell and the possibility of resonant phenomena. It is established that high-intensity acoustic radiation causes measurement errors above the sensitivity threshold of the device. the largest values of systematic error reach the level of 0.6 deg s-1 and are observed at a frequency of 800 Hz. To analyze the effect of diffraction phenomena on the suspension of the angular velocity sensor, computer simulations were performed in the Harmonic Acoustic analysis system. It is established that in the system at a frequency of 2200 Hz there is a resonance and the displacement of the suspension surface reaches 28.3 μm. the obtained results can be used at the stage of designing the elements of the navigation system to improve their performance designing the elements of the navigation system to improve their performance. © 2022 IEEE.

关键词： Errors

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An Improved YOLOv7 Model for Obstacle Recognition in Autonomous Driving

An Improved YOLOv7 Model for Obstacle Recognition in Autonom...

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robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： Zhaomin Zhu Qi Liu Lu Lin School of Electronic Information and Automation Guilin University Of Aerospace Technology Guilin Guangxi School of Machinery and Shipbuilding Beibu Gulf University Qinzhou Guangxi School of Computer and Electronic Information Guangxi University Nanning Guangxi

this paper focuses on the problem of obstacle recognition in autonomous driving. On the basis of the original YOLOv7 algorithm, we add the simAM attention mechanism and replac the original CIOU loss function with the EIOU loss function. Meanwhile our model minimizes the difference in height and width between the predicted box and the real box and accelerats the model convergence speed. the results show that on the produced dataset, when using the improved YOLOv7 algorithm for object detection, its mAP reached 82.3%, an increase of 3% compared to the original YOLOv7 algorithm.

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