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

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Promoting STEM Education through the Preparation of Multicultural National robotics Teams in Qatar (Evaluation)

Promoting STEM Education through the Preparation of Multicul...

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2023 ASEE Annual conference and Exposition - The Harbor of engineering: Education for 130 Years, ASEE 2023

作者： Katbeh, Tala Cieslinski, G. Benjamin Bazzi, Hassan Texas A&M University Qatar

In recent years, university outreach programs have increased as an effective method of imparting a comprehensive perspective into science, technology, engineering, and mathematics (STEM) careers and disciplines to school students. Different models of STEM education exist and the implementation of educational robotics to pre-college students has been deemed impactful in influencing the students' interest in STEM fields. This is due to the accessibility of educational robotics as well providing an engaging, hands-on method of combining technology, engineering, and design. Therefore, with the increase in educational robotics programs, having an end goal for the students is necessary for learning motivation. That is why involvement in international robotics competitions would meet this component. Moreover, combining the multicultural aspect that has been increasingly predominant in STEM helps raise the educational structure to a melting pot pedagogy. This provides a solid foundation for the students' development as they experience diversity consciousness even in a technical setting. This paper highlights the importance and the techniques behind joining groups of multicultural backgrounds in Qatar to represent national teams in international competitions - notably the well-renowned FIRST Global Challenge, an Olympics-style robotics competition that brings teams from different countries to solve the challenges facing our world. Preparing for the FIRST Global Challenge includes gaining effective communication and problem-solving skills as the students work as a team to devise creative solutions to real-world engineering problems. The approach with which the students representing two different nations - Afghanistan and Qatar - were trained in a shared workspace will be presented. Qatar is known for its cultural diversity, and the schools across Qatar include students from over 100 nationalities. Therefore, determining a technique to be delivered to a multicultural environme

关键词： Students

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Analysis of YouTube Video Comments with NLP Methods 16

Analysis of YouTube Video Comments with NLP Methods

引用

16th international conference on Electronics, Computers and Artificial Intelligence, ECAI 2024

作者： Mironela, Pirnau Iustin, Priescu Mihaela, Priescu Catalina Claudiu, Pirnau Daniel, Ghiculescu Liviu 'Titu Maiorescu' University Faculty of Informatics Department of Informatics Bucharest Romania National University of Science and Technology Politehnica Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania National University of Science and Technology Politehnica Bucharest Faculty of Industrial Engineering and Robotics Manufacturing Engineering Department Bucharest Romania

ISBN: (纸本)9798350371154

This study proposes methods that can be used to examine and interpret comments that users have made after watching videos on YouTube on a particular topic. YouTube tutorials are very popular among young people. They have become an important pillar in informal education, thus contributing to the rapid acquisition of skills and knowledge. Under these circumstances, we were interested in analysing the YouTube videos comments, knowing that the platform has a continuous increase in popularity, which is also due to the opportunities of sharing them. Since ChatGPT-themed YouTube videos have seen a significant surge in popularity since 2022, we were interested to analyse some videos that approach the topics of 'ChatGPT, AI clone, AI robot and Deep Learning.' © 2024 IEEE.

关键词： Deep learning

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Robust Real-Time PCB Defect Detection Using Improved DETR

Robust Real-Time PCB Defect Detection Using Improved DETR

引用

2024 IEEE international conference on robotics and Biomimetics, ROBIO 2024

作者： Wu, Qingtian Yang, Jinfeng Yang, Ou Zhang, Liming Guan, Yisheng Institute of Applied Artificial Intelligence Guangdong-Hong Kong-Macao Greater Bay Area School of Artificial Intelligence Shenzhen Polytechnic University Shenzhen China University of Macau Faculty of Sciences and Technology Department of Computer and Information Science SAR Macau China School of Mechanical and Electrical Engineering Guangdong University of Technology Guangzhou Guangdong China

ISBN: (纸本)9781665481090

This paper presents a PCB defect detection system utilizing the Real-Time Detection Transformer (RT-DETR) model. Originally designed for general object detection, we adapt RT-DETR for the specific task of PCB defect detection, achieving both high accuracy and rapid inference. Building on this baseline, we introduce re-parameterization techniques to further enhance the model's performance with less parameters computational cost. Additionally, we employ data augmentation strategies to enrich the diversity of the dataset, thereby improving the model's robustness and generalization capability. Through these efforts, the developed PCB defect detection system based on the RT-DETR model meets the expected requirements in terms of high accuracy and real-time inference speed. The code and models will be made publicly available. © 2024 IEEE.

关键词： Object detection

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Developing a Digital Twin Framework for Monitoring the Trajectory of the UR10 Robot Using an Extended Kalman Filter 6

Developing a Digital Twin Framework for Monitoring the Traje...

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6th international conference on robotics, Control and Automation engineering, RCAE 2023

作者： Alham, Ramy Hammadi, Moncef Université de Toulon La Garde France Norwegian University of Science and Technology Trondheim Norway QUARTZ Lab EA7393 ISAE-SUPMECA Saint-Ouen93400 France

ISBN: (纸本)9798350315301

In the era of modern robotics and Industry 4.0, integrating advanced state estimation techniques with digital twin technology is crucial for enhancing robotic system performance and safety. This study presents a pioneering Digital Twin framework to monitor the trajectory of Universal Robots' UR10 robotic arm. We address challenges such as system uncertainties, sensor noise, and environmental factors by combining a Kalman Filter-based state estimation with a Digital Twin approach. By creating a virtual replica that accurately mimics the UR10's physical properties and dynamics, our method enables realtime tracking and prediction of the robot's states, improving control and operational efficiency. The Digital Twin incorporates the robot's kinematics and dynamics to compute the Jacobian matrix for EKF estimation. Through extensive simulations, we demonstrate a significant increase in accuracy in position (approximately 90.14%) and velocity (approximately 85.10%) estimations after introducing noise to the UR10 robot simulation. This approach paves the way for advanced control strategies, fault detection systems, and virtual testing platforms in industries like manufacturing, healthcare, and research, where precision and performance are critical. © 2023 IEEE.

关键词： Extended Kalman filters

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CTA Measurement on the Frequency Response of a Grid Turbulence Fluctuation Measurement with a Focus on Bispectrum 2

CTA Measurement on the Frequency Response of a Grid Turbulen...

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2nd international conference on Automation, robotics and Computer engineering, ICARCE 2023

作者： Yamaguchi, Hiroto Suzuki, Hiroki Fujita, Kyosuke Kouchi, Toshinori Graduate School of Natural Science and Technology Okayama University Okayama City Japan Graduate School of Environmental Life Natural Science and Technology Okayama University Okayama City Japan Okayama University Faculty of Engineering Okayama City Japan

ISBN: (纸本)9798350308341

The aim of this study is to investigate a triple correlation function and a bispectrum of a turbulent voltage fluctuation obtained by a constant-temperature hot-wire anemometer (CTA) in terms of frequency response adjustment. The triple correlation function of a velocity fluctuation is included in the Kármán-Hawarth equation, which is the governing equation for an autocorrelation function. The bispectrum is obtained by Fourier transforming this triple correlation function. The velocity fluctuations in this experiment are obtained for multi-scale grid turbulence, and time series of these voltage fluctuations are measured by the constant-temperature hot-wire anemometer based on a 5μm tungsten wire I probe. The sampling frequency is 50kHz and an analogue low-pass filter of 20kHz is used. Firstly, two cases are set up using a square wave where the frequency response is adjusted or unadjusted and oscillating. The effect of the unadjusted response is seen in the power spectrum of the voltage fluctuations. The distributions of the triple correlation function are then compared with and without this response adjustment. The bispectrum of the voltage fluctuations is then shown to be insensitive to the presence or absence of the response adjustment. © 2023 IEEE.

关键词： Frequency response

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Handwritten Digits Prediction System using Convolution Neural Network for MINIST Dataset 1

Handwritten Digits Prediction System using Convolution Neura...

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1st IEEE international conference on advances in Computing, Communication and Networking, ICAC2N 2024

作者： Chauhan, Shweta Kumar, Rahul Kumar, Bibek Apex Institute of Technology CSE University Centre for Research and Development Chandigarh University Mohali140413 India GLA University Mathura ECE Deaprtment Uttar Pardesh 281406 India Symbiosis University of Applied Sciences School of Data Science Madhya Pradesh Indore India

ISBN: (纸本)9798350356816

A dramatic change has been occurred in machine learning with the development of Artificial Neural Network (ANN), making it more artificially intelligent in recent years. In addition to surveillance, health, medicine, sports, robotics, and drones, deep learning is used in many other fields as well due to its diverse range of applications. The Convolutional Neural Network (CNN), which blends Artificial Neural Networks and current deep learning strategies, is at the center of phenomenal advances in deep learning. Using varying numbers of hidden layers and epochs, we investigate the variation in accuracy of CNN to classify handwritten numbers and make comparisons between the different accuracy levels. A stochastic gradient descent algorithm and backpropagation has been used to train the network model. This experiment has been designed to evaluate the performance of CNN using the MNIST dataset. © 2024 IEEE.

关键词： Convolutional neural networks

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A Control Algorithm for an Aerial Co-Manipulation System 4

A Control Algorithm for an Aerial Co-Manipulation System

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4th international conference on Industrial Automation, robotics and Control engineering, IARCE 2024

作者： Chen, Fan Zhang, Xinyue Li, Yuxin Wang, Yixin Southwest University of Science and Technology Mianyang China Southwest University of Science and Technology Mianyang China Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9798350380323

During aerial co-manipulation, addressing the disturbances caused by the motion of the lower UAV on the aerial dexterous manipulation platform and the perturbations induced by the manipulation platform's own movement, as well as the issue of the inadequate number of existing simulation platforms, this study introduces an adaptive sliding mode control approach that leverages radial basis function neural networks and establishes a simulation platform for aerial comanipulation within the Gazebo environment. In the control method, the Lagrangian equation is employed for standardized modeling, and the model is simplified through projection. The universal approximation property of neural networks is utilized for adaptive rate optimization. Additionally, a sliding mode algorithm grounded on the exponential reaching law is implemented to bolster robustness. To further mitigate chattering, the hyperbolic tangent function is employed. Finally, the results were verified through trajectory tracking in Matlab/Simulink, ensuring that the system converged in about 1 second and achieved micron-level multi-channel tracking error accuracy, effectively reducing chatter. The Gazebo simulation platform sets up three aerial dexterous manipulation platforms capable of performing basic aerial tasks, and control stability is verified using PID algorithms. © 2024 IEEE.

关键词： Radial basis function networks

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Design and Simulation of a New Quality Underwater Swarm Inspired by Biological Models 24

Design and Simulation of a New Quality Underwater Swarm Insp...

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3rd international Symposium on robotics, Artificial Intelligence and Information engineering, RAIIE 2024

作者： Huang, Silun Wang, Xingbo Wang, Chuyan Zhang, Jiwen Xu, Bo School of Future Technology Harbin Engineering University Harbin150001 China School of Intelligent Science and Engineering Harbin Engineering University Harbin150001 China

ISBN: (纸本)9798400718311

To solve the problem of underwater multi-target group search and enable the group system to conduct low-volume agile regulation through implicit communication, thereby promoting the development of new-quality underwater group cooperative technology, a new-quality group search model was established based on biological inspiration models within the framework of traditional artificial fish swarm algorithm, starting from the characteristics of the new-quality underwater group system. The model was then validated through simulation of multi-thermal vent search mission. To enhance the reliability of the model, temperature field models, sea current models, and biomimetic fish movement models of thermal vents in the three-dimensional underwater environment were established to improve system parameters. Ultimately, compared with the traditional artificial fish swarm model, the new-quality group search model improved search efficiency, stability, and global convergence. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Fish

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Evaluation of Supply Chain Design Decisions under Uncertainty - A Case Study Analysis

Evaluation of Supply Chain Design Decisions under Uncertaint...

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2024 international conference on advances in Modern Age Technologies for Health and engineering science, AMATHE 2024

作者： Joe Prathap, P.M. Beevi, L. Sherin Dani, W. Vinil Vivek, Panguluri Venkata Jubilson, E. Ajith R.M.D. Engineering College Department Of Computer Science And Engineering Kavaraipettai India St. Peter's College Of Engineering And Technology Department Of Eee Chennai India School Of Computer Science And Engineering VIT-AP University Andhrapradesh India

ISBN: (纸本)9798350371567

This study digs into the strategic supply chain decision-making process of Bridgestone Tires, a global tyre manufacturing leader, demonstrating the effectiveness of decision tree analysis in dealing with complex uncertainty. Bridgestone Tires has a variety of problems, including fluctuating exchange rates and uncertain demand patterns, demanding strategic plant placement across its global network. Using decision tree methodology, this study examines optimal choices under various current and future situations, providing light on the importance of addressing demand unpredictability and economic variables in financial supply chain design decisions. The findings emphasise the importance of thoroughly integrating financial data, identifying risks, calculating cash flows, and considering alternative scenarios. While decision tree tools are cost-effective, simulation models enable nuanced assessments of complex scenarios, but at a greater setup and operating cost. Finally, this study explains how firms can use decision tree analysis and simulation modelling to effectively manage uncertainties, allowing for more informed and optimised supply chain design decisions in dynamic global environments. © 2024 IEEE.

关键词： Decision trees

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Innovation in Finance: Machine Learning Algorithms for Predicting Loan Eligibility

Innovation in Finance: Machine Learning Algorithms for Predi...

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2024 international conference on advances in Computing Research on science engineering and technology, ACROSET 2024

作者： Didolkar, Amey Lokulwar, Prasad Turankar, Aditya G.H. Raisoni College of Engineering Compter Science and Engineering Nagpur India G. H. Raisoni College of Engineering Computer Science and Engineering Nagpur India

ISBN: (纸本)9798350388800

The financial industry is examined in this research paper, with a particular emphasis on risk management and loan prediction. Three well-known machine learning algorithms-Random Forest, Support Vector Machine, and Gradient Boosting Machine-are compared in this study in order to identify the best model for loan eligibility prediction. Based on performance parameters like accuracy, precision, and recall, each algorithm was thoroughly assessed. According to the results, the Gradient Boosting Machine performed better than the other models on a regular basis and had more robustness and predictive power. Using FastAPI, a high-performance web framework renowned for its effectiveness and simplicity of use, an API for the Gradient Boosting Machine model was created in order to operationalize these insights. Real-time loan eligibility assessments are made easier by the API's smooth connection with a variety of financial platforms. Concurrently, Angular was used to create a user-friendly interface that makes it simple for users to explore and engage with the application. A wide spectrum of users, including financial experts and prospective loan applicants, can access this interface due to its streamlined experience. In order to improve accessibility and usefulness in financial services, the research highlights the significance of combining open-source technologies with user-centric design. The research intends to protect the integrity of risk management procedures in the banking industry while promoting the normalization of financial services by democratizing access to sophisticated predictive technologies. This method encourages more inclusion in financial decision-making processes in addition to increasing the accuracy of loan estimates. © 2024 IEEE.

关键词： Risk management

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