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3rd International Conference on Electronics, Communications and Information technology, CECIT 2022

作者： Ma, Mengcheng Wang, Shanshan Li, Yuehong Guangdong Polytechnic of Water Resouces and Electric Engineering Network and Cloud Computing Department Guangzhou China Guangdong Industry Polytechnic Information Technology Department Guangzhou China Harbin Engineering University College of Computer Science and Technology Harbin China

ISBN: (纸本)9798350331974

In the cross-domain authentication architecture, the current method is based on public key infrastructure (PKI) and blockchain to enhance the security of data. However, most models need to be improved about the efficiency, robustness and security in the authentication phase, and in the revocation phase the most solutions cannot meet the real-time revocation or waste storage on-chain space. To solve the problem, this paper proposes a model based on multiple intermediate entities. Simulation experiments show that the model can improves the efficiency of cross-domain authentication, improves the robustness of the system, resists single-point attacks, meet the real-time in revocation, and saves space on the chain. © 2022 IEEE.

关键词： Blockchain

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Research on sentiment analysis of weibo based on Improving Capsule Network

Research on sentiment analysis of weibo based on Improving C...

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Consumer Electronics and computer engineering (ICCECE), 2021 IEEE International Conference on

作者： Hui Shao Computer Engineering Technology College (Artificial Intelligence College) Guangdong Polytechnic of Science and Technology Zhuhai China

When conducting text sentiment analysis based on traditional deep learning models, lack of extracting deep-seated characteristics and sentence system characteristics etc. The article propose a model based on improving capsule networks. This model uses Weibo text as the research object, and uses BERT to obtain the word vector; then use CNN to extract deep phrase characteristics, LSTM networks to model the dependencies of each word in the instance, and dig out its hidden semantics; then increase attention layer is screened with effective features; finally, the improved capsule network is used to express a richer expression of text sentiment information to enhance the overall abstraction capabilities of the model. After experimenting on the dataset, it achieved good results on Weibo's sentiment analysis. The result shows that the model is better than traditional models, and it also fully shows that the model can effectively improve the accuracy of sentiment analysis.

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Research on Design and Implementation of a Virtual Real Fusion Metaverse System Based on Deep Learning

Research on Design and Implementation of a Virtual Real Fusi...

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Intelligent Management and Software engineering (IMSE), International Conference on

作者： Wenying Zeng College of Computer Engineering and Technology (College of Artificial Intelligence) Guangdong Polytechnic of Science and Technology Zhuhai China

The metaverse system is a new paradigm of the Internet that has received widespread attention and application in academia and industry. In the specific implementation, multiple comprehensive technologies are involved, facing challenges such as technology and ethics. To efficiently construct a virtual real fusion metaverse system, analyze the architecture of the metaverse system, introduce deep learning for scene construction, intelligent interaction, etc., enhance the mapping and service capabilities of the metaverse system and reality docking, and discuss the relevant social norms of the metaverse system, and make some research on related implementation path. It is expected to provide reference strategies for the construction of metaverse application systems.

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An Optimization Model for Resident Physical Health Factor Issues Based on XGBoost-SHAP

An Optimization Model for Resident Physical Health Factor Is...

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Electronics and Devices, Computational science (ICEDCS), International Conference on

作者： Banxiang Duan Wencheng Hong Zexin Lin Minxia Huang Computer Engineering Technical College Guangdong Institute of Science and Technology Zhuhai China

This paper delves into the multifaceted aspects affecting residents' physical well-being. Leveraging a combination of advanced techniques, including the XGBoost algorithm, grid search optimization, and Latent Dirichlet Allocation (LDA), alongside proficient software tools such as Matlab, Excel, and PyCharm, we meticulously scrutinized and statistically evaluated various facets of residents' lifestyle habits. These encompassed dietary compositions, food preferences, and mealtime regularities. Our investigation culminated in the development of an XGBoost regression model tailored to predict residents' physical health factors. Subsequently, the model underwent refinement utilizing the SHAP model interpreter, grid search optimization, and LDA to pinpoint the optimal parameters for XGBoost. Armed with the optimized parameters, we harnessed the model's predictive capabilities to assess the propensity of residents to have previously encountered hypertension and diabetes. Furthermore, we visualized the findings, facilitating a more comprehensive comprehension of the outcomes.

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Production model based on the combined prediction of time series and XGBoost neural networks

Production model based on the combined prediction of time se...

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Electrical engineering, Big Data and Algorithms (EEBDA), IEEE International Conference on

作者： Banxiang Duan Jingyu Zhang Zhaobin Zeng Computer Engineering Technical College Guangdong Institute of Science and Technology Zhuhai China

This paper discusses the production problem of multi-variety materials. With the continuous development of economic globalization, the production and operation mode of many varieties of small batch materials has been loved by the company, and the market demand for materials determines the quantity of our production materials. In the code of small-batch materials in the given sample, we first use Python data to analyze the trend level of the material, establish the entropy right Topsis model to objectively score the material, and screen out the six materials that should be paid attention to in the materials that meet the requirements. Secondly, with the week as the time unit, the time series and XGBoost neural network are used to establish a weekly prediction model to predict the six material demand, and the reciprocal mean square error method is used to combine the two models to ensure the accuracy of the model and improve the credibility of the model, to build the combined prediction model.

关键词： Time series analysis Neural networks Globalization Production materials Mean square error methods Predictive models Prediction algorithms

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Correlation model of maternal and infant health indicators based on random forest and TOPSIS

Correlation model of maternal and infant health indicators b...

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Electronics and Devices, Computational science (ICEDCS), International Conference on

作者： Banxiang Duan Shangchun Tang Tianci Qiu Hongpei Chen Computer Engineering Technical College Guangdong Institute of Science and Technology Zhuhai China

This paper discusses the influence of mother's physical and mental health on baby's growth. Using Spearman correlation analysis, the law is obtained; Using random forest method, the relationship model between infant behavior characteristics and mother's physical index and psychological index is constructed to judge the type of behavior characteristics. The linear programming model of disease score and treatment cost is established to solve the cost of treatment scheme to adjust behavior characteristics. The correlation model of infant's comprehensive sleep quality with mother's physical index and psychological index is constructed to predict infant's comprehensive sleep quality. In addition, we analyze the sensitivity and error of the model, and evaluate, improve and popularize it objectively and fairly.

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AIGC enables vocational education teaching- -take the course of Audio and video editing processing as an example

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Applied Mathematics and Nonlinear sciences 2024年第1期9卷

作者： Cao, Ling Hao, Gang Wu, Houmin Information Engineering School Guangzhou Vocational College of Technology & Business Guangdong Guangzhou511442 China School of Computer Science Guangdong Polytechnic Normal University Guangdong Guangzhou510665 China

The study integrates and models the PLS method in traditional structural equations, applies it to vocational education research, and constructs a vocational education model based on PLS-SEM. The model examines the factors that influence teaching quality in vocational education. Therefore, an intelligent teaching model for vocational education based on AIGC is proposed, and teaching experiments are conducted to explore the practical effects of the teaching model. The structural equation model of vocational education constructed in this paper has good reliability, validity, and predictive ability. The analysis found that vocational education has a positive effect on emotion and motivation and learning performance, and emotion and motivation have a positive effect on learning performance. The increases in the four dimensions and the overall level of the pre-and posttests of the control group were 0.10, 0.67, 0.31, -0.12, and 0.97, respectively, and the increases in the experimental group were 2.00, 3.79, 3.24, 4.25, and 15.28, respectively. The significance of each dimension of the posttest data of both groups is less than 0.05, indicating that the intelligent teaching model of vocational education based on AIGC has a significant positive effect on students’ audio-video editing and processing ability, and the teaching effect is significantly better than that of the conventional teaching mode. © 2024 Ling Cao, Gang Hao and Houmin Wu, published by Sciendo.

关键词： Apprentices

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Concentration Diagnosis in Soft Sensing Based on Bayesian T-Distribution Mixture Regression 9

Concentration Diagnosis in Soft Sensing Based on Bayesian T-...

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9th International Conference on Fuzzy Systems and Data Mining, FSDM 2023

作者： Xia, Changhai Peng, Zhiping Cui, Delong Li, Qirui Sun, Lihui School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China Jiangmen Polytechnic College Jiangmen City529090 China School of Computer Science Guangdong University of Petrochemical Technology Maoming City525000 China

ISBN: (纸本)9781643684703

This study presents a cutting-edge soft sensing approach for coke-making diagnostics, aimed at tackling the challenges posed by multifaceted, nonlinear, non-Gaussian, and noisy operational data prevalent in coke-making ovens. Our proposed method leverages a Bayesian t-distributed mixed regression model, effectively capturing the intricate nature of multivariate, nonlinear, and non-Gaussian data. The utilization of the t-distribution ensures the model's resilience to interference, with model parameter estimation achieved within a Bayesian framework. Conducting simulation experiments and real industrial experiments, as well as comparative analysis with PLSR, GMR, and GPR models, we demonstrate the model's good robustness, excellent prediction accuracy, and robustness, further confirming its potential application in coking diagnosis. © 2023 The authors and IOS Press.

关键词： Coke

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Convolutional Bi-GRU-based prediction model for Climate Indicators

Convolutional Bi-GRU-based prediction model for Climate Indi...

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7th International Conference on Electronics technology, ICET 2024

作者： Lo, Tsung-Ming Zhang, Hong-Tao He, Yun-Bing Liu, Yi-Zhi Zhang, Wan-Ying Liang, Qiong-Dan Bei, Zhen Dongguan University of Technology Guangdong-Taiwan College of Industrial Science & Technology Dongguan China Guangxi Vocational and Technical College of Communications School of Traffic Information Engineering Nanning China Nanfang College Guangzhou Department of Public administration Guangzhou China Nanfang College-Guangzhou School of Electrical and Computer Engineering Guangzhou China Dongguan University of Technology Intelligent Manufacturing Engineering Dongguan China

ISBN: (纸本)9798350363951

Climate prediction is critical to a wide range of fields, from agriculture to public health, but traditional methods face challenges due to the complexity and time-space characteristics of climate data. Machine learning techniques provide a promising solution by effectively extracting features from climate indicator data. In this study, we propose a new method for predicting climate indicators by combining CNN-Bi-GRU models with FNN networks. Through evaluation, our method demonstrates excellent prediction performance in terms of RMSE and MAE on both test and training sets, and robust convergence behavior is observed in model training. In addition, our method achieves high accuracy in predicting key climate metrics such as temperature and rain frequency, providing valuable information for understanding climate dynamics. Comparison experiments with LSTM-FNN, Double-LSTM, BiLSTM, and Bi-GRU models highlight the superiority of the CNNBi-GRU approach, especially in reducing temperature prediction errors. In conclusion, this study presents a promising approach to climate prediction that can enhance our understanding of climate variability and support informed decision making in various industries. © 2024 IEEE.

关键词： Prediction models

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Research on the reform of integrated talent cultivation of middle and high school undergraduate in the context of 1+X certificate

Research on the reform of integrated talent cultivation of m...

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作者： Desheng Zeng Xiaodan Chen Shuanglong Pang Xue Jiang Chunyang Chen Jun Nie Guangdong Innovative Technical College School of Information Engineering Guangdong Innovative Technical College Middle Vocational Department Guangdong University of Science & Technology School of Computer Science

With the deepening of industrial transformation and upgrading and reform of vocational education,the demand of society for high-level vocational technicians has *** with the "20 articles of vocational education" and "1+X" certificate system pilot project,based on the existing system of secondary and higher vocational education in our college,we jointly carry out the reform of "integration of courses and certificates" with guangdong University Of science & *** to the characteristics of the school's majors,the vocational skill level certificate of "intelligent computing platform application development" was selected as a pilot reform,and the X certificate was fully utilized as the basic measure and standard for practitioners to measure their competence,so as to build an integrated talent training system of middle and high school,and to realize the organic connection between the curriculum systems of middle school,high school and undergraduate *** will help cultivate more excellent technical skills talents for the guangdong-Hong Kong-Macao Greater Bay Area and is expected to provide a reference for building a perfect vocational education system.

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