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Spatiotemporal Prediction of Harmful Algal Blooms Based on Spatiotemporal Attention and Transformer 3rd

Spatiotemporal Prediction of Harmful Algal Blooms Based on S...

引用

3rd International conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2023

作者： Wang, Peirui Luo, Xiaoqing Zhang, Zhancheng School of Artificial Intelligence and Computer Science Jiangnan University Jiangsu Wuxi214122 China Institute of Advanced Technology Jiangnan University Jiangsu Wuxi214122 China School of Electronic and Information Engineering Suzhou University of Science and Technology Jiangsu Suzhou215000 China

ISBN: (纸本)9789819721993

Accurate HAB prediction is crucial for water pollution management, and the application of spatiotemporal prediction methods in HAB has not been fully explored. To further enhance prediction performance, considering the complex HAB motion patterns, a spatiotemporal prediction method named STA-MIMO based on spatiotemporal attention and transformer is proposed. The proposed spatiotemporal attention module (STA) comprises Temporal Attention Block (TA) and 4D Attention Block (4DA). TA is designed to select critical spatial features along the temporal dimension by assigning temporal attention weights. 4DA is designed to finely select critical spatiotemporal feature points by assigning 4D attention weights. The STA can adaptively highlight key local spatiotemporal features, benefiting the prediction of complex motion patterns. Experiment results on the Taihu HAB 2019 dataset demonstrate that the proposed method significantly outperforms the comparative methods in all metrics, validating its superior HAB prediction performance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Forecasting

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Influence Analysis and Prediction of Tunnel Excavation Based on ABAQUS 2

Influence Analysis and Prediction of Tunnel Excavation Based...

引用

2nd International conference on computer science, electronic Information engineering and Intelligent Control Technology, CEI 2022

作者： Zhang, Yongjuan Qi, Rui Guo, Renliang College of Civil Engineering and Architecture Shandong University of Science and Technology China

ISBN: (数字)9781665476164

ISBN: (纸本)9781665476164

In order to analyze and predict the influence of dynamic construction of TBM tunnel on surrounding environment, the dynamic calculation model was established by using ABAQUS finite element software, and the TBM tunnel dynamic excavation simulation was carried out. Fast Fourier Transform (FFT) with Matlab was used to obtain the frequency domain curve (Fourier spectrum) of vibration acceleration, and the variation law of ground vibration at different distances from the working surface was analyzed. At the same time, the peak value of ground vertical acceleration was effectively predicted by BP neural network. The results show that: 1) With the increase of distance, the lateral and vertical accelerations of the ground surface decrease sharply, and the longitudinal acceleration increases first and then decreases rapidly. 2) The spectral components of surface vibration wave are complex, showing obvious low frequency characteristics. 3) It is feasible to use BP neural network algorithm to predict the peak value of ground vertical acceleration caused by TBM tunnel excavation. © 2022 IEEE.

关键词： MATLAB

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SEU/SET Evaluation of Digital VLSI Design from Register Transfer Level to Layout Level 7

SEU/SET Evaluation of Digital VLSI Design from Register Tran...

引用

7th International conference on Electrical, Mechanical and computer engineering, ICEMCE 2023

作者： Chen, Xin Huo, Liangzhou Shen, Zhihao Jiang, Ziyun Zhang, Zhiwei Zhang, Ying College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9798350382877

As the feature size of integrated circuit (IC) continues to shrink, the soft failure probability induced by single event upset and single event transient (SEU/SET) for ICs exposing to space radiation is increasing. Since the soft failure probability is proportional to IC area, it is of great importance to study how to evaluate the sensitivity of very large scale integrated (VLSI) circuit to SEU/SET. In this paper, a generic fault injection simulation platform is designed to evaluate the responses of VLSI circuit to SEU/SET. Experiments show that the designed fault injection platform can cover the SEU/SET evaluation of VLSI design for the whole digital VLSI design flow, which includes original register transfer level design, logic gate-level netlist generated after synthesis and physical gate-level netlist generated after placement and routing. Furthermore, the proposed platform is able to extract the location information of utilized stand cells from the existing digital VLSI design flow, and carry out the simulation of single multiple bit upset and single event multiple transient (SMBU/SEMT) more accurately. © 2023 IEEE.

关键词： Transients

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EEG-Based Emotion Detection: A Machine Learning Approach with Multiple Classifiers

EEG-Based Emotion Detection: A Machine Learning Approach wit...

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2024 IEEE International conference on electronic Systems and Intelligent Computing, ICESIC 2024

作者： Senthil, K. Thejasree, J. Rushitha, Bathini Venkata Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331522988

The present work sought to evaluate the ability of three classification methodologies Decision Tree, Support Vector Machine (SVM), and Naive Bayes in classifying emotional states using EEG data. The models were trained and tested in a dataset that covers a broad range of emotional labels. The performance of both models was measured using quantitative measures such as accuracy, precision, recall, and F1-score. A Decision Tree Classifier that achieved 95.78% accuracy with a good set of precision and recall in all emotion categories, where particularly the Negative emotions are detected better than other classifiers. The SVM model presented improved classification ability and overall robustness regarding categorizing whether an emotion was a Neutral, Negative, or Positive category compared with the Decision Tree model doing so with 96.02% accuracy (Table 1). However, the Naive Bayes Classifier demonstrated lower overall performance, achieving an accuracy of 69.79%. It tended to over-allocate to non-positive categories, which impacted its precision in correctly predicting the exact category. Upon evaluating the confusion matrix, it is found that Decision Tree and SVM models managed to significantly reduce misclassifications. According to the result, Ensemble models are more effective in EEG-based emotion classification tasks compared with SVM and Decision Tree. On the other hand, Naive Bayes might not be an ideal choice for these kinds of tasks because it assumes a very simple model. The paper emphasizes the demand for careful selection of machine learning models to be used in recognizing emotions from EEG data. It also points to future possible directions, such as optimization of models and rich feature engineering improvements using deep learning approaches. Overall, Support Vector Machines (SVM) and Decision Trees show strong potential for practical application in emotional processing to offer fresh insights into improving the accuracy/ reliability of classification

关键词： Support vector machines

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Conversational Product Recommendation using LLM 4

Conversational Product Recommendation using LLM

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4th IEEE International conference on electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Chang, Ting-Jui Lin, Lydia Hsiao-Mei Tsai, Richard Tzong-Han National Central University Department of Computer Science and Information Engineering Taoyuan Taiwan National Taipei University of Technology Department of Interaction Design Taipei Taiwan Research Center for Humanities and Social Sciences Academia Sinica Taipei Taiwan

ISBN: (纸本)9798350360721

It is expected to deploy chatbots as sales assistants on e-commerce platforms soon. In recent years, the capabilities demonstrated by large language models (LLMs) indicate their suitability for this role. However, a dialogue process is not fully established. Most existing works concentrate on searching for ideal products, such as Retrieval-Augmented Generation (RAG) and product search. Many proposed methods rely on product reviews. However, in the case of some e-commerce platform products, valuable reviews are often lacking, rendering these approaches impractical. Thus, we studied how to assist users and select a set of candidate products. Accordingly, we simulated sales conversations based on the product features provided by the seller, using LLM and reliable content while addressing the cold-start problem. Specifically, we used product features to generate customer persona for user simulation. LLM was used to play the role of sales assistant in giving recommendations. The experimental results showed that practical conversation was created between customers and chatbots in Traditional Chinese. The code and results are available at: https://***/terryobe-ncu/CPR_LLM © 2024 IEEE.

关键词： Sales

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A PIB-Oriented Elliptic Beam Quality Calculation Based on Energy Distribution 20

A PIB-Oriented Elliptic Beam Quality Calculation Based on En...

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20th International computer conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2023

作者： Yubo, Liu Qiang, Dai Rui, Xi Bowen, Tian China Jiuyuan High-Tech Equipment Corporation Beijing100089 China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9798350318982

The precise assessment of beam quality is a fundamental element in the design and practical applications of lasers. Conventional techniques relying on optical instruments or image processing, primarily centered on circular spot analysis, encounter inherent limitations. This study addresses the pressing need for an enhanced, user-centric methodology to compute the quality factor accurately, β. Motivated by the shortcomings of established methods, particularly in dealing with intricate spot shapes and adhering to Power in the Bucket (PIB) requirements, our approach integrates image processing and computer vision for β computation. Our method commences with image preprocessing for noise reduction and precise cropping, followed by an orientation gradient to rectify skewness. This is coupled with an integration step for initial beam width estimation, culminating in the derivation of β Simultaneously, we introduce an innovative Ellipse Detection algorithm to mitigate spot deformation interference. Additionally, we devise a beamwidth tuning algorithm incorporating a bucket-type data structure to meet PIB requirements swiftly. Compared to traditional techniques, the results exhibit marked superiority in accuracy, computational speed, and user-friendliness. This novel approach presents a promising alternative for laser beamwidth determination, showcasing its potential for widespread adoption in practical applications. © 2023 IEEE.

关键词： Data structures

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Encoding Block Pixel Compensation With Motion Vector on DNN 15

Encoding Block Pixel Compensation With Motion Vector on DNN

引用

15th International conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2023

作者： Wang, Wenhao Jin, Shiyu Jiang, Yanfu Tian, Ling Zhou, Yimin University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Chengdu University of Information Technology School of Cybersecurity Chengdu610225 China

ISBN: (纸本)9798350308693

Compression efficiency is always being the engine behind video coding. Inter-frame prediction has traditionally been the focus of research as a key technology for removing temporal redundancy. However, the motion vector acquisition of the prediction block in current standards all adopts the block prediction method in order to preset the coding mode, but this does not apply to natural images, as the boundaries of natural images are random, often leading to a decrease in prediction accuracy. This article creatively proposes pixel level motion vector prediction technology, obtaining pixel motion vectors in a simple and efficient way. Firstly, the optimal motion vector of the pixel is calculated by the center template search algorithm, and the dataset is made using the motion vector of current pixel and corner pixel. Finally, a prediction model is obtained by training with a multi-layer neural network, and experimental results verify the effectiveness of the model. © 2023 IEEE.

关键词： Pixels

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MapsTP: HD Map Images Based Multimodal Trajectory Prediction for Automated Vehicles 26

MapsTP: HD Map Images Based Multimodal Trajectory Prediction...

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26th Irish Machine Vision and Image Processing conference, IMVIP 2024

作者： Sharma, Sushil Das, Arindam Sistu, Ganesh Halton, Mark Eising, Ciarán Department of Electronic & Computer Engineering University of Limerick Ireland SFI CRT Foundations in Data Science University of Limerick Ireland

ISBN: (纸本)9781837242672

Predicting ego vehicle trajectories remains a critical challenge, especially in urban and dense areas due to the unpredictable behaviours of other vehicles and pedestrians. Multimodal trajectory prediction enhances decision-making by considering multiple possible future trajectories based on diverse sources of environmental data. In this approach, we leverage ResNet-50 to extract image features from high-definition map data and use IMU sensor data to calculate speed, acceleration, and yaw rate. A temporal probabilistic network is employed to compute potential trajectories, selecting the most accurate and highly probable trajectory paths. This method integrates HD map data to improve the robustness and reliability of trajectory predictions for autonomous vehicles. © This is an open access article published by the IET under the Creative Commons Attribution License (http://***/licenses/by/3.0/)

关键词： Autonomous Vehicles HDMap Images MultiModel Trajectory Prediction Probabilistic Network

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The Inter-channel Interference Cancellation Algorithm for Wireless Magnetic Induction MIMO Communication System Based on Zero-forcing Precoding 7

The Inter-channel Interference Cancellation Algorithm for Wi...

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7th International conference on computer Network, electronic and Automation, ICCNEA 2024

作者： Zhang, Yufang Lu, Xinhang Ge, Jiahao Wang, Peng Chen, Chen Wang, Bin Li, Xiaoyan Xu, Yuntao School of Electronics and Information Engineering Xi’an Technological University Xi'an China Development Planning Service Xi'an Technological University Xi'an China

The wireless magnetic induction MIMO system can enhance the data transmission rate in near-field magnetic induction communication, but it also suffers from severe inter-channel interference issues. This paper introduces precoding techniques into the wireless magnetic induction MIMO system, employing the zero-forcing precoding algorithm to eliminate interference between different channels. Firstly, leveraging the characteristic that the channel state of magnetic induction transmit-receive coils is determined solely by the physical parameters of the coils, channel estimation is performed to obtain the channel gain matrix for wireless magnetic induction communication. Subsequently, the obtained channel matrix is subjected to zero-forcing precoding to eliminate interference caused by coupling between different channels. Simulation results indicate that the data transmission rate of the wireless magnetic induction MIMO system is significantly higher after applying zero-forcing precoding compared to the rate without it. Additionally, the system's data transmission rate decreases as the distance between the transmitting and receiving coils increases. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Channel estimation

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Semi-end-to-end Based ECG abnormality detection method 7

Semi-end-to-end Based ECG abnormality detection method

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7th International conference on computer Information science and Application Technology, CISAT 2024

作者： Zhang, Wanli Gao, Cuiyun Huang, Songqun Luo, Binwen Zhou, Yingjie Zhao, Yang Anhui Jianzhu University Power Quality Analysis and Load Detection Technology Electronic and Information Engineering School Hefei China Second Military Medical University Department of Cardiovasology Changhai Hospital Shanghai China

ISBN: (纸本)9798350375107

To solve the problem of information redundancy or loss caused by ECG abnormality detection in fixed-length samples, our team proposed a feature extraction and classification method based on 3R samples and TSL. Although this method solves the above problems, it also has two defects: the current algorithm is based on the results obtained for each 3R sample, and it does not regression to the complete sample, which will lead to multiple classification results for a complete sample in some cases. In addition, the original algorithm needs to screen high-quality signals, in which the double-threshold threshold method can not adapt to the signals from different devices. we proposes a semi-end-to-end ECG abnormality detection and quadratic modelling regression algorithm in this paper. In the pre-processing part, the high-quality screening process is omitted, and the noise samples are classified and recognized as a class of ECG samples. Meanwhile, for the problem that the original 3R classification results are not reduced to the complete samples, this study proposes a secondary modelling approach based on the 3R classification probability matrix and the complete sample labels to regress the classification results. twelve-category classification and three-category classification experiments are carried out on Cardiol Set dataset, and the results show that the method in the paper has significant improvement over the original method. © 2024 IEEE.

关键词： Long short-term memory

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