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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68880 条记录，以下是1541-1550 订阅

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Real-Time Modelling as Part of Building a Digital Substation

Real-Time Modelling as Part of Building a Digital Substation

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2023 international conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2023

作者： Kudryavtsev, Artem Pavlov, Ivan Zatsepina, Violetta Lipetsk State Technical University Automation and Computer Science Faculty Lipetsk Russia

ISBN: (纸本)9781665475952

This paper presents a methodology for verification of digital substations using real-time simulation. The behaviour of digital substations requires new forms of verification and traditional methodologies do not provide this capability. In addition, modern electrical networks impose new demands on control and protection systems, which must be much more finely tuned to meet these new challenges, achieving greater accuracy and integrity in the operation of each constituent element. The challenge of the energy transition, which includes distributed generation, electric mobility and energy storage, means that the electricity grid must be responsive and ready, becoming increasingly reliable, efficient and resilient. The proposed methodology is a verification of the implementation of digital substation automation levels for control and protection, for different architectures and communication devices based on IEC 61850, which demonstrates the need and benefits of verifying automation, control and protection in the integration of digital substations in electrical networks, using real-time modelling, reducing maintenance time and cost and improving efficiency and reliability in the operation of equipment before commissioning and future expansion. © 2023 IEEE.

关键词： automation

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Numerical and Experimental Study on the Temperature Field of Additive Friction Stir Deposition 5

Numerical and Experimental Study on the Temperature Field of...

引用

5th international conference on Robotics and computer Vision, ICRCV 2023

作者： Chen, Gang Wu, Kai Wang, Yu Sun, Wanfeng Zhu, Zhixiong Lin, Yongyong Hu, Fengfeng Nanjing University of Science and Technology Nanjing China Co.Ltd Suzhou China

ISBN: (纸本)9798350326369

Additive friction stir deposition (AFSD) is an emerging solid-state additive manufacturing technology. AFSD can create freeform and fully-dense structures without melting and solidification making it promising as an alternative to fusion-based metal additive manufacturing technology. The feedstock is plasticized by the heat of plastic deformation and friction, and the deposit layer is formed by the squeezing of the tool shoulder. The heat input during AFSD significantly affects the surface quality, microstructure, and mechanical properties of the deposited layer. Based on the temperature field variation characteristics of AFSD, which can be divided into two stages, the first stage is the preheating stage and the second stage is the steady deposition stage. As such significant differences in the heat distribution and conduction mechanisms between the two stages, the friction preheating heat source model and steady deposition heat source model are established respectively. The finite element numerical simulation method is used to calculate the AFSD temperature field and to analyze the heat generation mechanism, heat conduction pattern, and distribution characteristics of the temperature field during the preheating stage and steady deposition stages. The experiments are designed to verify the difference in the simulation and experiment temperature, where experimental and numerical results are in good agreement. © 2023 IEEE.

关键词： Additives

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A Long Distance Low Bandwidth Firmware Update process for LPWAN - Taking LoRaP2P+as example 37

A Long Distance Low Bandwidth Firmware Update process for LP...

引用

37th international conference on Information Networking (ICOIN)

作者： Khieng, Daniel Ho Teck Xie, Yu-Zhe Zhang, Jia-Cheng Huang, Nen-Fu Natl Tsing Hua Univ Hsinchu Taiwan Natl Tsing Hua Univ Dept Comp Sci Hsinchu Taiwan

ISBN: (纸本)9781665462686

The increment of IoT devices in the world due to the manpower shortage can be commonly seen around the world nowadays. In agriculture, revolutionary technologies which involve automation has been anticipated in order to face this serious issue. With LPWAN technologies, we can achieve automated mass irrigation almost without the need for manpower involvement. For most crops, production and yield are directly related to crop water use, hence resulting in the importance of precise watering. Device firmware updates for the endpoint devices play an important role to maintain the reliability and security of these system. For a system that is using LPWAN, which is commonly deployed in rural areas, the firmware update over the air(FUOTA) feature can provide the possibility of rolling out a system update without the need to have physical contact with the device while also ensuring all the devices are up-to-date. In this article, we designed a FUOTA process for LPWAN. Through FUOTA, the update patches can be deployed to the devices effortlessly and efficiently further reducing the manpower shortage problem while improving the feature and functionality of the system.

关键词： Wireless LPWAN LoRaP2P LoRaP2P+ Reliability automation Control System FUOTA Firmware Update

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computer Cursor Movement with Eye Blink for Paralyzed Individuals 2

Computer Cursor Movement with Eye Blink for Paralyzed Indivi...

引用

2nd international conference on automation, Computing and Renewable Systems, ICACRS 2023

作者： Pandian, Buvanesh V. Roupan, G. Moorthy, C. Sundara Department of EEE Kalasalingam Academy of Research and Education Krishnankoil India Biomedical Engineering Kalasalingam Academy of Research and Education Krishnankoil India

ISBN: (纸本)9798350340235

This research study addresses the challenges faced by individuals afflicted with quadriplegia, who often struggle to operate a conventional mouse. Leveraging cutting-edge technology, the system employs Canny-detection, and Face-Mesh-Facial recognition techniques to implement electronic eye movement control for paralyzed individuals. With approximately 40 cases per millions of quadriplegia reported annually, the need for innovative solutions is evident. By accurately identifying and analyzing data points such as pupil shape and size, the system enables seamless navigation of the computer interface. The implementation, executed through PYTHON serial commands in CMD, eliminates the dependency on external assistance, significantly simplifying the lives of those with limb paralysis. This pioneering approach not only offers practical convenience but also underscores the transformative potential of technology in enhancing accessibility and independence for individuals facing physical challenges. © 2023 IEEE.

关键词： Canny-detection data point Face-Mesh Facial recognition

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A Deep Learning Method with Self-Attention Mechanism for Cross-Subject Sleep Stage Classification Based on EEG and EOG

A Deep Learning Method with Self-Attention Mechanism for Cro...

引用

2023 international conference on Intelligent Supercomputing and BioPharma, ISBP 2023

作者： Huang, Jianjun Qu, Jun South China University of Technology School of Automation Science and Engineering Guangzhou China South China Brain-computer Interface Technology Co. Ltd Guangzhou China

ISBN: (纸本)9798350397789

Brain-computer interface (BCI) systems based on electroencephalography (EEG) and electrooculogram (EOG) were shown to be able to be used for automatic sleep stage classification since these two signals contain many sleep characteristics. However, EEG signal characteristics vary greatly among individuals, and manual classification is time-consuming and subjective. This paper proposes a deep learning method using a self-attention mechanism to achieve cross-subject sleep stage classification based on EEG and EOG. The method mainly consists of three parts. First, a traditional convolutional neural network is used to perform preliminary feature extraction on the information of the two channels. Then use Long Short-Term Memory (LSTM) to find the features in time series. Finally, the self-attention mechanism is used to find more mission-critical information from the high-dimensional feature information. We performed 25-fold cross-validation experiments and showed that the model achieved an average accuracy of 82.4% and 80.4 of the macro-averaging F1 Score(MF1). © 2023 IEEE.

关键词： Electroencephalography

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Enhancing detection of SSVEP-based surround suppression using canonical correlation analysis 23

Enhancing detection of SSVEP-based surround suppression usin...

引用

2023 international conference on computer, Vision and Intelligent technology, ICCVIT 2023

作者： Chen, Sicong Hu, Wen Zhang, Xin Huang, Qiyun School of Automation Science and Engineering South China University of Technology Guangzhou China Research Center for Brain-Computer Interface Pazhou Lab Guangzhou China

ISBN: (纸本)9798400708701

Canonical correlation analysis (CCA), a method for assessing inter-signal correlation that is widely used to enhance the performance of brain-computer interfaces (BCIs), can play an effective role in detecting steady-state visual evoked potentials (SSVEPs) in response to target flicker stimuli. However, it remains unclear whether CCA-based measurements can enhance the quantification of a visual perceptual process that related to human psychophysics. In this study, we used SSVEP to achieve quantitative measurements of the surround suppression effect, a visual perceptual process related to the excitation-inhibition balance in the central nervous system based on electroencephalogram (EEG). The CCA method was compared with two traditional methods for SSVEP quantifications: the power spectral density (PSD) and the signal-to-noise ratio (SNR). Our results demonstrated that CCA had the highest sensitivity among the three to enhance the quantification of SSVEP-based surround suppression effect. Thus, our work confirmed that CCA is an outstanding method for SSVEP measurements, compared to the two other commonly used SSVEP detection methods mentioned below, not only in the field of artificial intelligence, such as the development of BCIs, but also can facilitate vision studies in cognitive and perceptual neuroscience. © 2023 ACM.

关键词： Brain computer interface

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Multi-objective performance prediction based on a self-constructed Al-Si alloy dataset 11

Multi-objective performance prediction based on a self-const...

引用

11th international conference on Information Systems and Computing technology, ISCTech 2023

作者： Hu, Dan Liu, Yingli Shen, Tao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650093 China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technologies Application Kunming650500 China

ISBN: (纸本)9798350342406

The combination of data-driven approaches and machine learning techniques has changed the design approach for new materials, propelling materials science research into the realm of the fourth paradigm. Researchers in the field of materials science have increasingly focused on utilizing machine learning methods to uncover the underlying nonlinear relationships within material data. However, there is currently limited research in the field of aluminum-silicon alloys regarding the prediction of alloy performance based on the composition-process-structure relationship. Additionally, there is a lack of data sharing in the aluminum-silicon alloy domain. Therefore, this study proposes a methodology. Firstly, an aluminum-silicon alloy dataset is constructed by mining relevant information from materials literature. Then, high-dimensional features in the dataset are subjected to feature selection techniques for dimensionality reduction. Subsequently, a multilayer perceptron model is applied to investigate the relationship between input features such as alloy composition, preparation process, and microstructural parameters, and output features such as yield strength, ultimate tensile strength, and elongation, enabling performance prediction. © 2023 IEEE.

关键词： Feature Selection

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Bidirectional Training for Generating Math Word Problems Using Pre-Trained Model and Prompt 20

Bidirectional Training for Generating Math Word Problems Usi...

引用

20th international computer conference on Wavelet Active Media technology and Information Processing, ICCWAMTIP 2023

作者： Kai, Gao School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350318982

Math word problems (MWPs) are a vital type of exercise that greatly enhances students' mathematical proficiency and problem-solving abilities. This paper aims to explore the challenging task of automatically generating MWPs, which necessitates the integration of mathematical knowledge, natural language processing, and logical reasoning. We propose an innovative approach that utilizes bidirectional training and prompt construction to fine-tune pre-trained language models. We evaluate our framework on multiple datasets and metrics, demonstrating its effectiveness and superiority over baselines. Our framework introduces a novel tool and perspective for mathematical education and research, creating new possibilities for generating various types of MWPs. © 2023 IEEE.

关键词： Computational linguistics

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Design of an Electric Vehicle Modeling and Visualization System Based on Industrial CT and Mixed Reality technology 3

Design of an Electric Vehicle Modeling and Visualization Sys...

引用

2023 IEEE 3rd international conference on Data science and computer Application, ICDSCA 2023

作者： Fumin, Qin Wuhan University of Technology School of Computer and Artificial Intelligence Wuhan China

ISBN: (纸本)9798350341546

This study explores the design of an electric vehicle modeling and visualization system based on industrial CT and mixed reality technology. Firstly, the principles of CT technology and the composition and data processing methods of industrial CT systems are introduced. Then, the imaging principles and calculation methods of CT are discussed in detail, including the Beer-Lambert law and data reconstruction algorithms. Subsequently, a method utilizing OpenGL for modeling and visualization is proposed, encompassing the overall design of the visualization system and its operational workflow. Through this research, a novel approach is established, combining CT and mixed reality technology, to provide fresh insights and methods for the related field. © 2023 IEEE.

关键词： Electric Vehicle Modeling Industrial CT Mixed Reality technology Visualization System

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Advanced ML Techniques for Real-Time Air Quality Prediction in Megacities: A Comparative Study 2

Advanced ML Techniques for Real-Time Air Quality Prediction ...

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2nd international conference on automation, Computing and Renewable Systems, ICACRS 2023

作者： Vignesh, U. Elakya, R. Selvi, R. Thanga Shanthana, S. School of Computer Science and Engineering Vellore Institute of Technology VIT- Kelambakkam - Vandalur Road Tamil Nadu Chennai India Information Technology Sri Venkateswara College of Engineering Sriperumbudur Chennai India Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R & D Institute of Science and Technology Avadi Chennai India Rajalakshmi Institute of Technology Chennai India

ISBN: (纸本)9798350340235

It is impossible to imagine humans surviving without oxygen. Due to the recent developments in almost all aspects of civilization, air quality has continually decreased. The day-to-day industrial, transportation, and home activities produce harmful pollutants into our surroundings. Monitori ng and forecasting air quality have become crucial in the modern era, particularly in the developing countries like India. In comparison to more traditional methodologies, new prediction technologies based on machine learning have emerged as the most useful tools for analyzing those unique threats. The current study analyses air quality data from 23 Indian cities over a period of six years in order to make air quality projections. Correlation analysis is used to identify the most significant aspects of the dataset and to complete the preprocessing. Pollutants with a direct impact on the air quality index are identified using exploratory data analysis, which is used to identify hidden patterns in the dataset. Due to pandemic situation, almost all pollutants were greatly reduced in the year 2020. After addressing the data imbalance issue with a resampling method, five machine learning models are employed to predict air quality. There are comparisons between these models and the gold standard metrics. The Gaussi an Naive Bayes model has the highest accuracy, while the S upport Vector Machine model has the lowest. When compared to other existing models, XGBoost has the maximum linearity between the predicted and actual data. © 2023 IEEE.

关键词： Air quality prediction comparative analysis Environmental data Machine learning Real- time processing Regression algorithms Sensor data Time-series data

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