Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things最新文献_第9页

Design Stock Market Trading Strategy with Deep Learning: A Bi-LSTM Based Approach 用深度学习设计股票交易策略:一种基于Bi-LSTM的方法

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603934

Yanjun Long, Xiaopeng Wang, Shiman Zhang, Sicun Han, Yancong Deng

引用次数: 0

A Survey on Mechanisms for Fast Network Packet Processing 快速网络分组处理机制综述

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603792

Yimin Du, Keyang Chang, Jinglin Shi, Yiqing Zhou, Min Liu

引用次数: 0

Evaluation of The Spatial Quality of Sunken Plazas Based on Multi-source Time-spatial Data 基于多源时空数据的下沉广场空间质量评价

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603877

Tian Wang, X. Kang, Xiaojuan Li

{"title":"Evaluation of The Spatial Quality of Sunken Plazas Based on Multi-source Time-spatial Data","authors":"Tian Wang, X. Kang, Xiaojuan Li","doi":"10.1145/3603781.3603877","DOIUrl":"https://doi.org/10.1145/3603781.3603877","url":null,"abstract":"Large-scale and fine-grained evaluations of spatial quality are made possible by the introduction and growth of multi-source big data. The spatial analysis method, visual semantic segmentation method, and field measurement method are used to construct a spatial quality evaluation system for urban sunken plazas based on the multi-source Spatio-temporal data, fusing urban road network data, Baidu API data, street view image data, POI data, public review data, and field measurement data. Based on the results of the spatial quality evaluation, the spatial quality measurement and effectiveness are achieved by. The evaluation suggests optimization steps to achieve effective measurement of spatial quality based on the findings of the evaluation of spatial quality and the existing state of spatial construction. The findings demonstrate that Tianjin Mingyuan Square has some fundamental construction in terms of visual, sensory, and use experience. Its space construction is also evenly distributed, and its aesthetic, comfortable, and functional construction is better, but its construction in terms of completeness is relatively subpar. In order to improve the spatial quality of the sunken plaza and encourage its effective and healthy development, we suggest optimization approaches to enhance the spatial landscape, increase the spatial facilities, and optimize the spatial environment.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115734635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decoupling Transformer with Convolutional Fusion for Mechanical Composite Fault Diagnosis 基于卷积融合的解耦变压器机械复合故障诊断

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603810

Xia Liu, K. Feng

{"title":"Decoupling Transformer with Convolutional Fusion for Mechanical Composite Fault Diagnosis","authors":"Xia Liu, K. Feng","doi":"10.1145/3603781.3603810","DOIUrl":"https://doi.org/10.1145/3603781.3603810","url":null,"abstract":"Compound faults often occur in mechanical systems under complex and variable operating conditions, which can seriously affect the health level of mechanical systems, so it is crucial to study the decoupling diagnosis of compound faults. In addition, industrial big data can greatly boost the accuracy and reliability of fault diagnosis results. Therefore, based on data fusion and attention mechanism, we propose a new composite fault diagnosis method called decoupling Transformer with convolutional fusion (DTCF). First, we construct the input embedding sequence as the model input. Second, the multichannel sensor data are adaptively fused using a convolutional layer. Then, the encoder encodes the signal based on global self-attention, which is representation learning. Finally, the decoupler iteratively generates decoupled labels. Two compound fault datasets are used, including the gearbox dataset and the bearing dataset, experiments on which show that the proposed method has higher accuracy, better generalization ability on the smaller training dataset, and stronger robustness against noise than CNN-based or MLP-based models. In addition, the visual analysis of attention weights makes the model interpretable.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131501706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on layout optimization and positioning of LED light source based on visible light communication 基于可见光通信的LED光源布局优化与定位研究

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603787

Yufang Kang, Jinpeng Wang, Qingxue Yao, Bo Zhang, Li Liu

引用次数: 0

Transaction-aware heterogeneous graph embedding for recommendation 用于推荐的事务感知异构图嵌入

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3604320

Jie Zhou

引用次数: 0

Few-shot Question Answering with Entity-Aware Prompt 几次问题回答与实体意识提示

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603812

Yi Chen, Xingshen Song, Jinsheng Deng, Jihao Cao

{"title":"Few-shot Question Answering with Entity-Aware Prompt","authors":"Yi Chen, Xingshen Song, Jinsheng Deng, Jihao Cao","doi":"10.1145/3603781.3603812","DOIUrl":"https://doi.org/10.1145/3603781.3603812","url":null,"abstract":"Providing simple task descriptions or prompts in natural language for large pre-trained language models yields impressive few-shot learning results in different tasks, such as text classification, knowledge probing, machine translation, and named entity recognition. In this paper, we apply this idea to question-answering task to fine-tune pre-trained language models by constructing entity-type prompts. Specifically, we augment the context sequences with semantic labels to enhance the understanding of pre-trained models, and dynamically adjust the prompts via intention recognition of the questions. Our proposition is simple yet powerful over traditional fine-tune training strategies and robust under few-shot conditions. The contributions of our work are as follows: 1. We proposed a few-shot learning method with entity-aware prompts for question-answering tasks to fine-tune the pre-trained language model. 2. Based on the SQuAD dataset, we extract a subset with 1,131 samples containing different categories of answer type, in which the answers to all questions are entities. 3. Experiments on multiple pre-trained language models validate that our method can effectively improve the performance of few-shot learning of question-answering tasks over the promptless ones.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114322632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Review on Advances of Spaceborne Database 星载数据库研究进展综述

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603830

Huifang Ji, Jian Xu, Bo Liu, Chaowei Liu

引用次数: 0

RepVGGFuse: an approach for infrared and visible image fusion network based on RepVGG architecture RepVGGFuse:一种基于RepVGG架构的红外与可见光图像融合网络方法

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603847

Zhang Xiong, Xiaohui Zhang, Qingping Hu, Hongwei Han

引用次数: 0

Acoustic Pre-training with Contrastive Learning for Gunshot Recognition 基于对比学习的声预训练枪响识别

Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things Pub Date : 2023-05-26 DOI: 10.1145/3603781.3603908

Xianjie Shen, Saimin Ma, Linlin Yang, Yubo Jiang, Zhifeng Xiao, Shuren Xu

引用次数: 0