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A Study to Compare YOLO Family Models for Metal Surface Anomaly Detection

A Study to Compare YOLO Family Models for Metal Surface Anom...

引用

2023 IEEE international conference on Big Data, BigData 2023

作者： Koc, Abdusselam Albayrak, Ozlem Kurt, Yasar Unal, Perin Ted University Faculty of Computer Engineering Ankara Turkey Research and Development Teknopar Industrial Automation Ostim Technical University Graduation School of Engineering and Sciences Ankara Turkey Ostim Technical University Graduation School of Engineering and Sciences Turkey

ISBN: (纸本)9798350324457

Anomaly detection is an important process that needs to be automated. Metal is an essential material that is heavily used in manufacturing of many different products. Automated detection of anomalies on metal surfaces is a topic that has been widely studied both by the researchers in the academia and by the practitioners. In the recent years, many studies have been conducted that apply deep learning for anomaly detection on metal surfaces. In this study, using NEU-DET data set, we have applied YOLO family models (YOLOv4, YOLOv5, YOLOv6, YOLOv7 and YOLOv8) in order to classify defects of images of steel. The results presented that with respect to mAP50 YOLOv8 has outperformed the other models. In the short term, we aim to utilize real images taken from home appliances products and perform a replication study. As for the long-term research we aim to develop and test our model based on real data set belonging to a Horizon Europe project. YOLOv8 has presented the best performance. © 2023 IEEE.

关键词： Anomaly Detection computer Vision Deep Learning

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A QoE-Aware Adaptive Energy-Efficient Transmission Scheduling Method 30

A QoE-Aware Adaptive Energy-Efficient Transmission Schedulin...

引用

30th IEEE international conference on Parallel and Distributed Systems, ICPADS 2024

作者： Yuan, Yankun Wang, Lin Xiao, Chonghui Liu, Zijuan Dang, Fan Wang, Xu Zhao, Haitian Miao, Xin Yanshan University School of Information Science and Engineering China National Computer Network Emergency Response Technical Team/Coordination Center of China China Tsinghua University Department of Automation and BNRist China Tsinghua University Global Innovation Exchange China Tsinghua University School of Software and BNRist China

ISBN: (纸本)9798331515966

In this paper, we propose a dynamic data transmission strategy for smart home environments that aims to optimize the Quality of Experience (QoE) by adaptively adjusting the data upload frequency based on the predicted trends in sensor data. Using the home wireless sensors monitoring dataset, we implement a deep learning model for accurate time series forecasting. In addition, an anomaly detection mechanism is used to identify critical events, requiring more frequent data uploads when important changes are detected. The QoE is quantified through a weighted average of several influencing factors, including data timeliness, timely upload of critical events, and transmission frequency. Our optimization objective is to maximize QoE while minimizing the number of transmissions, with an emphasis on reducing energy consumption through intelligent scheduling. The results demonstrate that our approach effectively balances data timeliness, transmission efficiency, and energy savings, leading to improved user satisfaction in smart home applications. © 2024 IEEE.

关键词： Adaptive algorithm Anomaly detection Energy conservation IoT LSTM Models QoE

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Balancing Real-world Interaction and VR Immersion with AI Vision Robotic Arm 20

Balancing Real-world Interaction and VR Immersion with AI Vi...

引用

20th IEEE international conference on Mechatronics and automation, ICMA 2023

作者： Yang, Xiaoran Zhan, Yang Iwasaki, Yukiko Shi, Miaohui Tang, Shijie Iwata, Hiroyasu Waseda University Dept. Modern Mechanical Engineering 3-4-1 Ookubo Shinjuku-ku Tokyo169-8555 Japan Waseda University Dept. Computer Science and Engineering 3-4-1 Ookubo Shinjuku-ku Tokyo169-8555 Japan

ISBN: (纸本)9798350320831

With the widespread adoption of Virtual Reality (VR) technology, VR devices can be more realistic and make the tasks they perform feel real to the user. It is this sense of realism that makes more and more people are using VR headsets. While using VR devices, the need to interact with the real world will also exist. For example, when people are using a VR headset to study and work, they have a physiological need (thirst, hunger, etc.), and need to interact with reality. But the closed nature of the VR headset causes this interaction to be very disruptive to the immersion of the user's current task. To address this issue, we propose an interaction method that combines an AI vision algorithm and a robotic arm to preserve immersion during task performance in VR. This method addresses the challenge of interacting with the real world while using closed VR devices. Our experiments show that our method outperforms see-through and mapping methods, allowing users to quickly re-immerse themselves after interruptions and reducing interruptions during real-world task performance. Future research will focus on improving this method without sensitization and expanding the range of real-world operations that can be performed. © 2023 IEEE.

关键词： Virtual reality

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Research on Digital Twin-Oriented UAV Data Chain Communication 7

Research on Digital Twin-Oriented UAV Data Chain Communicati...

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7th international conference on computer Network, Electronic and automation, ICCNEA 2024

作者： Chen, Zhang Liu, Lijun Zhang, Hui Dai, Xueya Fu, Yanfang Nanjing Panda Handa Technology Co. Nanjing Nanjing China School of Computer Science and Engineering Xi’an Technological University Xi’an China

In this paper, for the problems of low utilization of link resources, poor flexibility, poor adaptability, and low accuracy and difficulty in verification and assessment of traditional network modelling technology in Link-16 data chain time slot allocation research, digital twin technology is introduced to combine digital twin with data chain modelling to build a digital twin-oriented data chain verification platform. And through the OPNET simulation platform, the UAV data chain simulation model of multiple terrain scenarios is established. The influence of terrain on UAV communication is explored, focusing on the irregular terrain model, including the consideration of electromagnetic wave propagation and multipath effect, and the data chain performance indexes under different terrain conditions are compared through simulation. It is found that marine terrain has a significant impact on latency and communication, while mountainous terrain results in higher latency due to complex terrain structure and vegetation cover. Digital twin oriented UAV data chain modelling is characterized by high accuracy and low latency. Therefore, the research in this paper can provide guidance for designing a more reliable and efficient Link-16 data chain communication system and provide substantial insights for military communication network planning. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Digital elevation model

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automation for Requirements engineering: Opportunities and Pitfalls — RE '24 Keynote

Automation for Requirements Engineering: Opportunities and P...

引用

IEEE international conference on Requirements engineering

作者： Jan Mendling Department of Computer Science Humboldt-Universität zu Berlin Germany

ISBN: (数字)9798350395112

ISBN: (纸本)9798350395129

Recent technologies like ChatGPT inspire ideas of increasing automation for professional tasks in various domains. This includes among others requirements engineering. So far, however, the divide between useful and harmful automation has been blurry and in flux. In this keynote, I will discuss foundational concepts with which automation has been analyzed. Using these concepts, I will discuss the opportunities arising for requirements engineering from the advent of natural language processing, image processing, and event sequence analysis techniques. Furthermore, I will discuss important pitfalls that have been well documented for other automation technologies in the past.

关键词： automation Sequences Image processing Chatbots Requirements engineering Task analysis

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AI and IoT in Digital Marketing: Enhancing automation, Personalization, and Consumer Interaction

AI and IoT in Digital Marketing: Enhancing Automation, Perso...

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2025 international conference on Pervasive Computational Technologies, ICPCT 2025

作者： Naredla, Suman Singh, Madhulika Chaturvedi, Nidhi Banerjee, Devleena Gobinath, V.M. Anil Tiwari, Dr. Sr University School of Business Telangana Warangal India Quantum University Computer Science and Engineering Uttarakhand Roorkee India Emirates Aviation University Faculty of Business Management Dubai United Arab Emirates Christ University India Rajalakshmi Institute of Technology Mechanical Engineering Department Tamilnadu Chennai India Rnb Global University Bikaner Department of Commerce and Management India

ISBN: (纸本)9798331508685

An interconnected system of Internet-enabled devices that can collect and transmit statistics via a wireless connection without the assistance of people is known as the Internet of Things (IoTs). Accordingly, the IoT's seductive power is causing significant shifts in the current corporate environment. The digital marketing industry stands to gain the most from this innovation, which is currently causing major shifts in many other sectors. Using a variety of digital marketing strategies, this innovation gathers numerous types of consumer statistics. IoT technological advancements' impact on digital marketing tactics and customer interaction has emerged as a crucial research topic as it begins to pervade many facets of everyday existence. This investigation examines the application of IoT-based machine learning (ML) in digital marketing for the food business. To give ML-based suggestions, consumer data is analyzed, interests are identified, and conduct is predicted using ML approaches. The ensemble technique aggregates the results of multiple ML techniques to produce an individual forecast. The accuracy matrices graphs for the K-nearest neighbor and decision trees produced excellent estimations, with 100% accuracy and 0.0 error, correspondingly. The naïve Bayes method achieved 97.2% accuracy with a 0.029 error, successfully identifying the right tags across every category. The guided ensemble of 3 ML methods is demonstrated by effectively enhancing digital marketing tactics in the food distribution industry by reducing duration and expenses. © 2025 IEEE.

关键词： Decision trees

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Theoretical and Computational Investigation on Aerospike Nozzle Equipped with Exhaust Plumes for Supersonic Flow Regimes 1

引用

international conference on Mechanical engineering, INCOME 2023

作者： Bindal, Rohi Kattyayan, Shivansh Sonawane, Chandrakant R. Dhanwani, Payal Thombre, Simran Joshi, Vedant Mishra, Ankit Kumar Department of Computer Science Engineering Symbiosis Institute of Technology Maharashtra Pune India Department of Mechanical Engineering Symbiosis Institute of Technology Maharashtra Pune India Department of Aeronautical Engineering Bhagwan Arihant Institute of Technology Gujarat Surat India Department of Aerospace Engineering Sastra University Tamil Nadu Thanjavur India Department of Robotics and Automation Symbiosis Institute of Technology Maharashtra Pune India Department of Research and Development ASTROEX RESEARCH ASSOCIATION Uttar Pradesh Deoria India

ISBN: (数字)9789819738748

ISBN: (纸本)9789819738731

Aerospike nozzles are widely used in aerospace applications due to their high performance, low cost, and low maintenance. They have been widely used to improve the performance of aerospike engines. This paper presents a computational and numerical analysis of the flow behavior of an aerospike nozzles equipped with exhaust plumes under different operating conditions, contributing to the better study and understanding of fluid dynamics for the aerospike nozzles in the field of aerospace engineering. The study uses a three-dimensional, axisymmetric model to simulate the flow within the nozzle, and the results are later used in order to generate better contours and performance. An iterative test has been carried out which in turn used for optimization loop which involves changes in contour shape, spike height, or spike angle to achieve better flow expansion and reduce pressure losses. The paper also discusses the potential future research directions, such as investigating unsteady flow phenomena or exploring advanced turbulence models for more accurate predictions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Aerospace applications

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Network Traffic Prediction with Decomposition and Multi-Scale Autocorrelation in Large-Scale Cloud Data Centers 21

Network Traffic Prediction with Decomposition and Multi-Scal...

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21st international conference on Networking, Sensing and Control, ICNSC 2024

作者： Wang, Meijia Yuan, Haitao Kuang, Zhenwei Ma, Hanbo Bi, Jing Zhang, Jia Zhou, MengChu School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing University of Technology Faculty of Information Technology Beijing100124 China Southern Methodist University Dept. of Computer Science DallasTX75275 United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (纸本)9798350365221

As the Internet and big data technologies advance, a tremendous amount of data is generated daily. Efficient network operations are essential for handling such data. Accurately predicting future network traffic in real-time enables prompt response from cloud infrastructure and efficient traffic scheduling and allocation, ultimately reducing costs, preventing economic losses, and optimizing the performance of downstream facilities. However, predicting network traffic in large-scale data centers is challenging due to the multidimensional, nonlinear, and high-volatility nature of the time series. Traditional prediction methods, e.g., regression algorithms, struggle to capture non-linear features effectively. Many deep learning models face issues such as gradient explosion or vanishing during their training. Current commonly used prediction methods fail to fully uncover vital information about the frequency domain features in the time series. To do so, this work proposes a novel network traffic prediction model that combines a Savitzky Golay filter, sequence decomposition, multi-scale attention, a temporal convolutional network, an autocorrelation mechanism, and bidirectional long short-term memory. It can accurately predict future network traffic by adaptively extracting important features without requiring excessive feature engineering of the original data. It performs end-to-end sequence prediction, feature selection, and automatic learning of data features and temporal dependencies to achieve accurate time series prediction and avoid redundant data processing. Experiments involving ablation studies and comparisons with advanced prediction models are performed with the Google cluster trace. Experimental results show that the proposed model improves the prediction accuracy by at least 38.52% over the state-of-the-art models. © 2024 IEEE.

关键词： Autocorrelation

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Analysis of Doubly-fed Wind Turbines Oscillation Considering the Influence of Wind Speed 7

Analysis of Doubly-fed Wind Turbines Oscillation Considering...

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2022 7th international Seminar on computer Technology, Mechanical and Electrical engineering, ISCME 2022

作者： Yang, Dongju School of Electrical and Automation Engineering Shandong University of Science and Technology Shandong Province Qingdao266590 China

The accepted models of wind turbine and generator, respectively, were used to investigate how wind speed affected the subsynchronous oscillation of Double-fed wind turbine. Secondly, the oscillation characteristics of output are analyzed in the model/simulation of the PSCAD / EMTDC platform. The energy consumed when the wind speed changes are mainly affected by the subsystem of wind turbine. Below rated wind speed, increasing wind speed can inhibit subsynchronous oscillation, and increase the stability of the unit. The wind speed on the sub-synchronous oscillation is small as higher than normal wind speed. © Published under licence by IOP Publishing Ltd.

关键词： Wind turbines

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Design and Calibration of Dual Sensor: Towards Simultaneous Instrument Tracking and Deformable Shape Sensing in computer-Integrated Surgery 46

Design and Calibration of Dual Sensor: Towards Simultaneous ...

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46th Annual international conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Jeon, Sangseo Hnin, Khaing Thandar Jung, Yong Gi Lim, Sunghwan Korea Institute of Science and Technology Center for Healthcare Robotics Artificial Intelligence and Robotics Institute Seoul02792 Korea Republic of Sungkyunkwan University School of Medicine Samsung Medical Center Department of Otorhinolaryngology - Head and Neck Surgery Seoul06351 Korea Republic of

ISBN: (纸本)9798350371499

We introduce a novel integration of vision sensors in the form of a dual sensor system. The dual sensor system combines three distinct units: an optical localizer and two RGB-D sensors. This system is uniquely capable of concurrently providing real-time 3D shape information for deformable objects and accurate pose tracking data for medical instruments. This capability positions the dual sensor with immense potential for application in image-guided surgical navigation, robotic systems, and robot-assisted automation for surgical procedures involving deformable target objects. This paper provides an overview of the design, fabrication and a one-time calibration methodology of the dual sensor. An experiment was performed to assess the calibration accuracy of the dual sensor. Experimental results indicated that the dual sensor system delivers a level of accuracy that renders it suitable for deployment within the envisioned scope of *** relevance - The presented dual sensor provides real-time shape scanning of intra-operatively deforming objects and instrument tracking capabilities simultaneously, contributing to successful outcomes of diverse computer-integrated surgeries dealing with non-rigid surgical targets such as breast, face, and incised skin area © 2024 IEEE.

关键词： Robotic surgery

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