检索结果-内蒙古大学图书馆

2024 International Symposium on Internet of Things and Smart Cities, ISITSC 2024

作者： Liu, Yunxia Li, Mingyuan Ye, Zhonglin Shi, Xiaoan Wang, Weijie Zhao, Haixing College of Computer Qinghai Normal University Xining810000 China The State Key Laboratory of Tibetan Intelligent Information Processing and Application Xining810000 China

ISBN: (纸本)9798331505516

This paper proposes an Artificial Intelligence (AI) text detection and classification model that combines Bidirectional Encoder Representations from Transformers (BERT) and Text Convolutional Neural Network (TextCNN), applicable for smart city social media monitoring. By leveraging BERT's powerful contextual semantic understanding capabilities and TextCNN's local feature extraction abilities, the model achieves efficient text detection and classification. The model first utilizes BERT to perform semantic representation of the input text, capturing rich contextual features. These features are then fed into the TextCNN model, where multiple convolutional and pooling operations extract and compress the features. Finally, a fully connected layer converts the extracted features into fixed-length vectors for precise classification prediction. Experimental results show that this hybrid model significantly outperforms traditional baseline models on two public datasets, Human ChatGPT Comparison Corpus (HC3) and sharegpt_gpt4. The hybrid model demonstrates notable improvements in key metrics such as Accuracy (ACC), Precision (PREC), Recall (REC), and F1-score (F1). For example, on the sharegpt_gpt4 dataset, the accuracy reaches 0.8490, making a significant improvement over the baseline model. This validates the effectiveness and superiority of combining BERT and TextCNN in text classification tasks. The innovation of this paper lies in the novel integration of BERT and TextCNN, harnessing the contextual semantic understanding of BERT with the local feature extraction of TextCNN, resulting in enhanced text classification performance. The use of diverse datasets such as HC3 and sharegpt_gpt4 showcases the model's robustness across various text types. Additionally, the model's application in smart city social media monitoring demonstrates its practical relevance, providing accurate and efficient text detection crucial for monitoring public sentiment and emerging issues in real-t

关键词： Smart city

来源：评论

学校读者我要写书评

暂无评论

A zeroing neurodynamics‐based location method for nodes in underwater acoustic sensor network

引用

CAAI Transactions on Intelligence Technology 2023年第3期8卷 661-669页

作者： Shuqiao Wang Xiujuan Du Tiantai Deng College of Computer Qinghai Provincial Key Laboratory of loTQinghai Normal UniversityXiningChina The State Key Laboratory of Tibetan Intelligent Information Processing and Application XiningChina The Department of Electronics and Electrical Engineering The University of SheffieldSheffieldEnglandUnited Kingdom

Zeroing neurodynamics methodology,which dedicates to finding equilibrium points of equations,has been proven to be a powerful tool in the online solving of problems with considerable *** this paper,a method for underwater acoustic sensor network(UASN)localisation is proposed based on zeroing neurodynamics methodology to preferably locate moving underwater nodes.A zeroing neurodynamics model specifically designed for UASN localisation is constructed with rigorous theoretical analyses of its *** proposed zeroing neurodynamics model is compatible with some localisation algorithms,which can be utilised to eliminate error in non‐ideal situations,thus further improving its ***,the effectiveness and compatibility of the proposed zeroing neurodynamics model are substantiated by examples and computer simulations.

关键词： artificial neural network internet of things underwater acoustic sensor network

来源：评论

学校读者我要写书评

暂无评论

Using Hybrid Penalty and Gated Linear Units to Improve Wasserstein Generative Adversarial Networks for Single-Channel Speech Enhancement

引用

Computer Modeling in Engineering & Sciences 2023年第6期135卷 2155-2172页

作者： Xiaojun Zhu Heming Huang School of Computer Science Qinghai Normal UniversityXining810008China The State Key Laboratory of Tibetan Intelligent Information Processing and Application Xining810008China School of Electronic and Information Engineering Lanzhou City UniversityLanzhou730000China

Recently,speech enhancement methods based on Generative Adversarial Networks have achieved good performance in time-domain noisy ***,the training of Generative Adversarial Networks has such problems as convergence difficulty,model collapse,*** this work,an end-to-end speech enhancement model based on Wasserstein Generative Adversarial Networks is proposed,and some improvements have been made in order to get faster convergence speed and better generated speech ***,in the generator coding part,each convolution layer adopts different convolution kernel sizes to conduct convolution operations for obtaining speech coding information from multiple scales;a gated linear unit is introduced to alleviate the vanishing gradient problem with the increase of network depth;the gradient penalty of the discriminator is replaced with spectral normalization to accelerate the convergence rate of themodel;a hybrid penalty termcomposed of L1 regularization and a scale-invariant signal-to-distortion ratio is introduced into the loss function of the generator to improve the quality of generated *** experimental results on both TIMIT corpus and tibetan corpus show that the proposed model improves the speech quality significantly and accelerates the convergence speed of the model.

关键词： Speech enhancement generative adversarial networks hybrid penalty gated linear units multi-scale convolution

来源：评论

学校读者我要写书评

暂无评论

Detecting Social Robots Based on Multi-view Graph Transformer 1

引用

11th CCF Big Data Conference, BigData 2023

作者： Li, Mingyuan Ye, Zhonglin Zhao, Haixing Xiao, Yuzhi Cao, Shujuan College of Computer Qinghai Normal University Xining China The State Key Laboratory of Tibetan Intelligent Information Processing and Application Xining China Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province Xining China Key Laboratory of Tibetan Information Processing Ministry of Education Xining China

ISBN: (数字)9789819989799

ISBN: (纸本)9789819989782

With the development of social media, social robots are increasingly interfering in political elections and economic issues, and detecting social robots has become a long-standing but unresolved problem. Traditional machine learning models or methods have gradually become ineffective with the evolution of social robots. In contrast, analyzing the social network structure where social robots are located has become a more effective method. However, at present, most of these methods are based on a single view, ignoring the importance of multi-view information in social networks. At the same time, existing methods have not considered the influence of potential topic structures. Therefore, to solve the above problems, this paper proposes a new framework based on multi-view (Multi-View Graph Transformer, MV-GT). Specifically, MV-GT includes a topic module, a graph enhancement module, a multi-view Graph Transformer module, and a multi-view attention module, which can explore the complementarity, consistency, and semantic relevance of multiple different views in online social networks. Experimental results show that MV-GT outperforms many existing methods and also demonstrates the effectiveness of multi-view and topic structures in detecting social robots. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Detecting Social Robots Graph Transformer Multi-View Topic Structures

来源：评论

学校读者我要写书评

暂无评论

Multi Strategy Improvement of Newton-Raphson-Based Optimizer and Engineering application 6

Multi Strategy Improvement of Newton-Raphson-Based Optimizer...

引用

6th International Conference on Machine Learning, Big Data and Business Intelligence, MLBDBI 2024

作者： Cheng, Shaogang Yin, Jun Liu, Tingting College of Computing Qinghai Normal University Xining China Qinghai Normal University The State Key Laboratory of Tibetan Intelligent Information Processing and Application Xining China

ISBN: (纸本)9798331541798

A multi strategy improved Newton- Raphson-Based Optimizer (NRBO) is proposed to address the problem of slow convergence speed in the later stage of algorithm iteration and difficulty in finding the global optimal solution when facing complex functions. Firstly, using a set of best points instead of randomly generated initial populations to evenly distribute individuals in the optimization space improves the efficiency of the algorithms global and local search. Secondly, based on the idea of differential evolution, the initial population is mutated and crossed to accelerate the iteration speed. Then, in the optimal update stage, the Levi flight strategy is introduced to enhance the algorithms ability to jump out of local optima. The effectiveness of the proposed algorithm was tested on the CEC2005 test set, and compared with other algorithms on two test sets. The results showed that the convergence speed and accuracy of the algorithm were significantly improved. Finally, the proposed algorithm was applied to two practical engineering optimization problems, and simulation results showed that the algorithm proposed in this paper has better practicality and robustness compared to other algorithms. © 2024 IEEE.

关键词： Swarm intelligence

来源：评论

学校读者我要写书评

暂无评论

Research on Emotional Analysis of tibetan Short Text Based on Fusion Sentiment Lexicon 1

引用

1st International Artificial Intelligence Conference, IAIC 2023

作者： Ji, Wan Ma Dao Rang, An Jian Cai Cuo, Jan Yang Jia, Gong Bao Cuo, De Ji Gong, Zan La Qin, Yang School of Computer Science Qinghai University for Minzu Xining810007 China State Key Laboratory of Intelligent Information Processing and Application of Tibetan Language Jointly Constructed By the Ministry of Provincial Affairs and the Ministry of Education of China Xining China Qinghai Key Laboratory of Tibetan Information Processing and Machine Translation Item No. 2021-Z-001 Xining China

ISBN: (数字)9789819712779

ISBN: (纸本)9789819712762

Short-text sentiment analysis plays an integral role in predicting sentiment polarity. The current tibetan short-text sentiment analysis model applies deep neural networks to learn some local grammatical structure information but ignores known sentiment lexicon information in modeling. Aiming at the above problems, this paper proposes a method for sentiment analysis of tibetan short-text that incorporates sentiment lexicon information. The method firstly uses the word features extracted by Word2vec and Glove to fuse with the sentiment dictionary information, and inputs them into CNN & BiLSTM networks to extract text context features;secondly, adjusts the weights of the sentiment features through the self-attention mechanism;and finally, uses Softmax to infer the sentiment categories. The experimental results show that the accuracy of this method can reach 93.18% on the self-built sentiment analysis corpus. In addition, compared with the methods of extracting syllable features and word features, the accuracy of this paper's method can be improved by 4.92 and 3.43% respectively, which proves the effectiveness of the fused sentiment lexicon. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

The application of Generative Artificial Intelligence in the Teaching of Engineering Courses in Chinese Universities 24

The Application of Generative Artificial Intelligence in the...

引用

7th International Conference on Educational Technology Management, ICETM 2024

作者： Zhao, Dong Zhang, Dan Ma, Xiujuan School of Computer Qinghai Normal University Qinghai Xining China The State Key Laboratory of Tibetan Intelligent Information Processing and Application Qinghai Normal University Qinghai Xining China

ISBN: (纸本)9798400717468

Generative Artificial Intelligence (GenAI) is revolutionizing the field of higher education by leveraging deep learning models to generate human-like content. However, the use of GenAI in education raises ethical concerns such as the potential impact on critical thinking skills and the unethical or dishonest use by students. This paper analyzed the main problems existing in engineering courses in Chinese universities firstly and then proposed corresponding teaching reform measures based on the comprehensive consideration of the benefits and threats of GenAI. We applied the proposed teaching reform measures in the teaching of engineering courses, which greatly improved the teaching quality. © 2024 Copyright held by the owner/author(s).

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Qinghai Embroidery Classification System and intelligent Classification Research 9th

Qinghai Embroidery Classification System and Intelligent Cla...

引用

9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023

作者： Lin, Xiaofei Ye, Zhonglin Zhao, Haixing College of Computer Qinghai Normal University Xining810008 China The State Key Laboratory of Tibetan Intelligent Information Processing and Application Xining810008 China Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province Xining810008 China Key Laboratory of Tibetan Information Processing Ministry of Education Xining810008 China

ISBN: (纸本)9789819959709

Qinghai embroidery is an artistic treasure of folk embroidery in Qinghai Province. Classifying them to understand the differences between them is an important task. However, currently, there is a lack of a systematic classification method for Qinghai embroidery. First, by studying the history of Qinghai embroidery and a large number of Qinghai embroidery patterns, this paper divides Qinghai embroidery patterns into three categories: animals and plants, auspicious meanings, and geometric decoration. This method breaks through the regional classification system for the Qinghai embroidery. Second, this article utilizes four CNN models to classify the Qinghai embroidery datasets, exploring the differences in the classification of Qinghai embroidery by different models and finding the optimal classification model. The results show that the GoogLeNet model performs the best in the classification of Qinghai embroidery images, achieving the highest accuracy rate. This is mainly due to the small size of the Qinghai embroidery datasets and the application of the Inception structure and batch normalization technology in the GoogLeNet model, enabling it to better extract features and classify Qinghai embroidery images. Through this research, we can provide a certain reference and assistance for the classification of Qinghai embroidery images and provide technical support for the protection and inheritance of cultural heritage. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Improved YOLOv6s Algorithm for Automatic Detection of Elements of Qinghai Farmer Painting and Thangka 5

Improved YOLOv6s Algorithm for Automatic Detection of Elemen...

引用

5th International Conference on Electronic Engineering and Informatics, ICEEI 2023

作者： Guo, Shaodong Peng, Chunyan Zhang, Xiaojuan School of Computer Science Qinghai Normal University Xining810016 China State Key Laboratory of Intelligent Processing and Application of Tibetan Language Qinghai Normal University Xining810016 China

ISBN: (纸本)9781643685021

Qinghai Farmer Painting and Thangka are important intangible cultural heritages in Qinghai province, and the elements in the picture have the characteristics of abstract, dense and clutter. In order to quickly and accurately understand the meanings of the elements in the images, the Qinghai Farmer Painting dataset and the Thangka dataset are constructed, their element characteristics are analyzed. An improved algorithm based on YOLOv6s is proposed in this study to achieve accurate and fast detection of traditional painting elements of Qinghai Farmer Painting and Thangka. The algorithm incorporates a coordinate attention module into the YOLOv6s to enhance the emphasis on the location information of the object. Experimental results demonstrate that the improved algorithm yields an increase in mAP of 2.1% and 1.1% in the Qinghai Farmer Painting dataset and the Thangka dataset, respectively., compared with YOLOv6s. To verify the generality of the improved algorithm, the training was validated in the PASCAL VOC2012 dataset, and the calculated mAP was improved by 0.3% compared to YOLOv6s. © 2024 The Authors.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Research on Link Prediction Algorithms Based on Multichannel Structure Modelling 9th

Research on Link Prediction Algorithms Based on Multichannel...

引用

9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023

作者： Li, Gege Zhou, Lin Ye, Zhonglin Zhao, Haixing College of Computer Qinghai Normal University Qinghai Xining China The State Key Laboratory of Tibetan Intelligent Information Processing and Application Qinghai Xining China Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province Qinghai Xining China Key Laboratory of Tibetan Information Processing Ministry of Education Qinghai Xining China

ISBN: (纸本)9789819959709

Today's link prediction methods are based on the network structure using a single-channel approach for prediction, and there is a lack of link prediction algorithms constructed from a multichannel approach, which makes the features monotonous and noncomplementary. To address this problem, this paper proposes a link prediction algorithm based on multichannel structure modelling (MCLP). First, the network is sampled three times to construct its three subgraph structures. Second, the node representation vectors of the network are learned separately for each subgraph on a single channel. Then, the three node representation vectors are combined, and the similarity matrix is calculated for the combined vectors. Finally, the performance of the MCLP algorithm is evaluated by calculating the AUC using the similarity matrix and conducting multiple experiments on three citation network datasets. The experimental results show that the proposed link prediction algorithm has an AUC of 98.92%, which is better than the performance of the 24 link prediction comparison algorithms used in this paper. The experimental results sufficiently prove that the MCLP algorithm can effectively extract the relationships between network nodes, and confirm its effectiveness and feasibility. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：