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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

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Overhead Power Line Detection Based on Curriculum Learning Strategy 7

Overhead Power Line Detection Based on Curriculum Learning S...

引用

7th international conference on Data Science and Information technology, DSIT 2024

作者： Gefei, Zhang Quan, Chen Bingheng, Liu Hao, Ma Yihan, Zhang Zanchen, Cui Fan, Yang Ying, Tong Nanjing Institute of Technology School of Communication and Artificial Intelligence School of Integrated Circuits Nanjing China Nanjing Institute of Technology School of Electrical Power Engineering School of Shen Guorong Nanjing China

ISBN: (纸本)9798350384093

Drone inspection of overhead power lines is a crucial aspect of ensuring electrical safety. Due to the elongated shape of overhead power lines and the complex inspection backgrounds, commonly used detection networks struggle to learn the unique features of these targets. To achieve high-precision detection of overhead power lines, a detection method based on a curriculum learning strategy is proposed. First, multiple target bounding boxes are annotated for individual overhead power lines in aerial images. Next, simulating the human learning process of starting with easier tasks and progressing to more difficult ones, the wavelet-entropy algorithm is used to divide the dataset into simple and complex subsets, allowing the YOLOv5 object detection network to first learn from the simple data and then from the complex data. Finally, a false detection box removal algorithm based on directional gradient statistics is introduced to process the overhead power line images that still contain incorrect identifications after network detection, eliminating the erroneous detection boxes. Experimental results indicate that, under the same network scale, high-precision detection of overhead power lines has been achieved, with an accuracy improvement of 10.8% compared to YOLOv5 based on traditional training strategies, and mAP_0.5 reaching 78.6%. this method effectively detects slender targets like overhead power lines while minimizing background interference, advancing the development of drone-based electrical inspection technology. © 2024 IEEE.

关键词： Overhead lines

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ANN based Harmonic Extraction in DFIG Fed DSTATCOM System 7

ANN based Harmonic Extraction in DFIG Fed DSTATCOM System

引用

7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Vijayasarathi, N. Senthilkumar, Masan Ragul, S. Pandi, P. Vasanthprakash, M. Karthikeyan, D. Chettinad College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Karur India SRM Institute of Science and Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350372816

the evolution of the renewable energy is the best solution for environment to reduce the pollution. Due to the fastest development of the Wind power penetration in the power system many countries offer the stable operations of power system. the most widely installed machine in the wind farm is Doubly Fed Induction Generator (DFIG).the operation of a wind energy conversion system (WECS) is based on a DFIG which is Sensitive to unbalanced non-linear load. In the proposed system the AC source is given to the non-linear load, to reduce the fluctuation the control function Distribution Static Synchronous Compensator (DSTATCOM) is used where the Input power is fed to the DFIG, it converts the AC voltage to DC and fed to Voltage Source Invertor (VSI). the reference and actual current get combined and passes to the Proportional Integral (PI) controller which is used to adjust reference and actual values and then fed to the Pulse Width Modulation (PWM) generator. the source voltage and source current are given to the DQ theory which produce the reference current and then fed to Artificial Neural Network (ANN) classifier which is used to reduce the harmonics. the PWM generator which improve the power quality and generate pulses which is applied to VSI and thereby, the generation of an opposing current is injected to the Point of Common Coupling (PCC). the design process is accessed by the MATLAB simulation. © 2024 IEEE.

关键词： MATLAB

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AI based Automated Essay Grading System using NLP 7

AI based Automated Essay Grading System using NLP

引用

7th international conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Suresh, V. Agasthiya, R. Ajay, J. Gold, A Amrith Chandru, D. Dr. N.G.P Institute of Technology Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350397253

the goal of this proposed work is to develop an AI-powered system for automated essay grading. the system will utilize natural language processing and Graph based techniques to analyze, and grade written essays. It not only checks the syntax, semantics and grammar but also grades according to the similarity of sentences using a Graph based approach. the system will be trained on a dataset of labelled essays and will be able to accurately grade new essays based on their content and writing quality. the system can be able to integrate with existing learning management systems. the goal is to provide a more efficient and accurate essay grading process, so the teachers can provide valuable feedback to students. the proposed work aims to develop an automated essay grading system using AI technology. the system will be able to analyze, and grade written essays by using natural language processing and machine learning techniques. the system will be trained on a dataset of labelled essays, which will be used to teach the system to recognize patterns and characteristics of high-quality writing. this will enable the system to accurately grade new essays based on their content and writing quality. © 2023 IEEE.

关键词： Semantics

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Experimental and Numerical Study on the Damage Accumulation of Stainless Steel Plates due to Repeated Mass Impacts 7

Experimental and Numerical Study on the Damage Accumulation ...

引用

7th international conference on Green technology and Sustainable Development, GTSD 2024

作者： Huynh, Van-Vu Le, Cong Lap Truong, Dac Dung Nha Trang University Faculty of Transportation Engineering Nha Trang Viet Nam

ISBN: (纸本)9798350386073

this study examines the accumulation of damage in stainless steel plates found in engineering structures when they are exposed to repeated mass impacts. the loading scenario reflects multiple contacts from the structures with objects like ice floes or other floating vessels. the study involved conducting repeated mass impact tests on clamped stainless steel stiffened plates, and measuring the residual damage accumulation of the tested plates. Additionally, numerical simulations were performed using finite element package software to predict the plate damage under repeated impacts, and the numerical model incorporated strain hardening. the numerical results were well compared with the test results. A parametric study was carried out on clamped plates involving various loading cases, including different masses and impact velocities. the results indicated that residual damage accumulated due to repeated impacts. It was observed that after the first impact event, the plate was significantly deformed, and the increase in residual deflection was found to reduce in later impacts. the results of the study can be useful in the structural design and safety assessment of marine structures against repeated impacts. © 2024 IEEE.

关键词： Plates (structural components)

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Credit Card Fraud Detection Using Machine Learning, Deep Learning, and Ensemble of the both 7

Credit Card Fraud Detection Using Machine Learning, Deep Lea...

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7th international conference on Parallel, Distributed and Grid computing, PDGC 2022

作者： Kaur, Damanpreet Saini, Anjali Gupta, Deepti University Institute of Engineering and Technology Panjab University Department of Computer Science and Engineering Chandigarh India

ISBN: (纸本)9781665454018

It is the responsibility of the credit card companies to ensure that their customers are given the best security measures when it comes to fraudulent credit card transactions. the main objective of this work is to explore whether a credit card transaction (before being processed) is fraudulent or not. And if it is found out to be fraudulent, then the credit card owner must be notified of the same. the approach used is to make use of highly imbalanced and skewed transactional data and train various models available in ML as well as a DL model for the detection of frauds and finally compare their accuracies and test results and choose the most suitable model. the system currently used to detect fraud is plagued by misclassifications and highly false positives. So, our motive is to not miss any fraud cases (high recall) as well as not predict too many non-fraud cases as fraud cases (high precision) as if this happens, it will lead to poor reviews for the concerned credit card company. We demonstrate various methods to deal with the imbalance of the data such as choosing appropriate metrics for evaluation of models and resampling of data. © 2022 IEEE.

关键词： Anomaly detection

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Engagement measurement of a learner during e-learning: A deep learning architecture 7

Engagement measurement of a learner during e-learning: A dee...

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7th international conference on Parallel, Distributed and Grid computing, PDGC 2022

作者： Tanwar, Sanchit Kumar, Vinay Sharma, Shailza Thapar Institute of Engineering and Technology Electronics and Communication Engineering Department Punjab Patiala India

ISBN: (纸本)9781665454018

Teaching in online mode is challenging, but measurement of student engagement is even more challenging and complex but crucial to overall learning of the participants. Although online environment improves the overall learning and removes the barriers of time schedules, it requires a high level of self motivation from the learners. those at the brink of self motivation may perform exceedingly better under online learning if a tool can help them concentrate. these tools require the overall engagement level of the learner. the current manuscript proposes a multi module deep learning based engagement level predictor model. Basically, three modules, a convolutional neural network (CNN) module-for hierarchical feature extraction and other two modules-LSTM and attention based network, for temporal modeling of task are utilized in the proposed architecture. A dataset consisting of 9068 video sequences is used to measure the engagement level of the learners. the proposed model also introduced a novel cost function for prediction. Experimental results validate the usefulness of proposed loss function over traditional loss functions. © 2022 IEEE.

关键词： Cost functions

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Digital Imaging Analyzing and Reproducing Color, Texture, and Material Appearance 7

Digital Imaging Analyzing and Reproducing Color, Texture, an...

引用

7th international conference on Contemporary computing and Informatics, IC3I 2024

作者： Arul, Sujin Jose Suneel, Sajja Gupta, Manish Rajkumar, K. Varada Garg, Monica Hameed, Ali Abduhussien New Horizon College of Engineering Department of Automobile Engineering Engineering Bangalore India Institute of Aeronautical Engineering Dundigal Hyderabad500043 India Lovely Professional University Phagwara India Mlr Institute of Technology Department of CSE-AI&ML Telangana Hyderabad India Lloyd Law College Plot No. 11 Knowledge Park II Uttar Pradesh Greater Noida201313 India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq

ISBN: (纸本)9798350350067

Digital photography has made great strides in showing colour and texture along with specific material details. Standard approaches usually do not attain realistic representations. the Multifaceted Realism Synthesis presented in this document resolves these problems and outshines classic strategies in accuracy and realism. the MRS framework incorporates three core algorithms: With this approach we can obtain more consistent and accurate colour reproduction using the Colour Harmonisation Algorithm. the Physically Informed Material Rendering and Typical Texture Synthesis (ATS) generate more natural textures that adapt to local details rather than using median filtering or morphological methods. the MRS approach adjusts materials appearance texture and colour to deliver superior realism adaptability and precision beating current methods. this new approach can change digital photography across different areas such as entertainment and healthcare. the technique of MRS has made a substantial improvement in the quest for hyper-real visuals in digital photography. © 2024 IEEE.

关键词： Image texture

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Attributes Based Bayesian Unknown Hazards Assessment for Digital Twin Empowered Autonomous Driving 23

Attributes Based Bayesian Unknown Hazards Assessment for Dig...

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23rd IEEE international conference on High Performance computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Hou, Zhonglin Liu, Hong Zhang, Yan Software Engineering Institute East China Normal University Shanghai China University of Oslo Department of Informatics Oslo Norway

ISBN: (纸本)9781665494571

Safety of the intended functionality is an indispensable safe condition that must be considered for autonomous driving on the road. the key to study SOTIF is to construct as many hazardous scenarios as possible and accurately assess SOTIF. It is difficult to test many automated driving vehicles in the current research and discover all the unknown triggering events in the intended functionality. As a new simulation method, vehicle digital twins can simulate as many driving scenarios as possible efficiently and at a low cost in a short time. therefore, this paper proposes an algorithm to assess SOTIF with unknown hazards based on the vehicle digital twins based on a Bayesian hazard graph with attributes and Noisy-OR structures. this paper uses CARLA to build the vehicle digital twins and testing this algorithm based on these digital twins. After testing, the SOTIF quantitative assessment algorithm proposed in this paper is effective and has good performance. © 2021 IEEE.

关键词： Costs Smart cities Roads Hazards Digital twins Bayes methods Noise measurement

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Light-Field Depth Estimation Using RNN and CRF 7

Light-Field Depth Estimation Using RNN and CRF

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7th international conference on Image, Vision and computing, ICIVC 2022

作者： Shi, Zhan Zheng, Shengnan Huang, Xiaohua Xu, Mengxi Han, Lei Nanjing Institute of Technology School of Computer Engineering Nanjing China Nanjing Institute of Technology Jiangsu Province Engineering Research Center of IntelliSense Technology and System Nanjing China

ISBN: (数字)9781665467346

ISBN: (纸本)9781665467346

Convolutional Neural Networks (CNNs) have recently been successfully applied to depth estimation from light field. Different from those CNN-based methods, we utilize the sequence characteristics of Epipolar Plane Images (EPIs) and introduce a novel light-field depth estimation method based on the Recurrent Neural Network (RNN). Our network builds upon two-stages architectures, involving a local depth estimation and a depth refinement part. In the first part, we regard an EPI patch as a vector sequence which is fed into the RNN to obtain a local depth value. then, guided by the theory of Conditional Random Field (CRF), we globally optimize the depth map in the second part. Our network was trained in the disparity truth values provided by the synthetic light-field dataset. Experimental results show that our method allows to estimate high-quality disparity results. © 2022 IEEE.

关键词： Recurrent neural networks

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Construction of an Integrated Practice System for Intelligent Manufacturing engineering Based on Digital System 7

Construction of an Integrated Practice System for Intelligen...

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7th international conference on Measurement Instrumentation and Electronics, ICMIE 2023

作者： Chen, Shujun Zhang, Ziqiang Li, Jun Liu, Chunqi Beijing University of Technology Faculty of Materials and Manufacturing Beijing China

ISBN: (纸本)9798350326307

Intelligent manufacturing is a new production mode with the functions of self-perception, self-learning, self-decision, self-execution, and self-adaptation. How to highlight the technical characteristics in the practice of intelligent manufacturing engineering and to improve students' understanding of intelligent products, production, and services is a problem to be solved. therefore, an integrated practice system for intelligent manufacturing engineering based on digital system was constructed in this study. the practice content of intelligent manufacturing was divided into four modules, and each module was connected through a unified practice goal. Digital technology was used throughout the practice process, so that students can master the application of digital and information technical means in the manufacturing process. A complete practice process was given, and students' abilities were evaluated on the basis of the competency model. the analysis results showed that teachers in the field of intelligent manufacturing gave a high evaluation to the students' abilities, which proved the feasibility of the practice system. the practice system proposed in this paper has a good reference value for the establishment of similar engineering majors. © 2023 IEEE.

关键词： Students

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