2022 The 6th International Conference on Compute and Data Analysis最新文献

Green Warehouse Intelligent Lighting Optimization Design Strategy 绿色仓库智能照明优化设计策略

2022 The 6th International Conference on Compute and Data Analysis Pub Date : 2022-02-25 DOI: 10.1145/3523089.3523110

Yunna Liu, Pei Yang, Yihe Bai

{"title":"Green Warehouse Intelligent Lighting Optimization Design Strategy","authors":"Yunna Liu, Pei Yang, Yihe Bai","doi":"10.1145/3523089.3523110","DOIUrl":"https://doi.org/10.1145/3523089.3523110","url":null,"abstract":"Under the guidance of the National Development and Reform Commission of China, the Ministry of Natural Resources, the Ministry of Ecology and Environment, the National Energy Administration and other departments responded positively, and finally proposed \"green storage\" as one of the contents of \"green upgrade of infrastructure\" in the notice of \"Green Industry Guidance Directory\". Thus, more and more attention has been paid to energy saving in the storage industry at the national level. In this paper, through reading the domestic and foreign research theories and relevant practical information about intelligent lighting system, we understand the brightness requirements of logistics warehouse for lighting system, and comprehensively consider the operational lighting requirements of logistics warehouse personnel. On how to optimize the normal logistics warehouse space lighting design strategy is put forward, this design with zigbee technology as the core of logistics warehouse wireless lighting control, and through the sensing function of unmanned in warehouse and a period of time without homework personnel to return to the lighting system will automatically enter a dormant state in order to reduce unnecessary power consumption, Achieve the effect of energy saving and environmental protection. This paper hopes to lay a foundation for the improvement of the lighting system of logistics warehousing by optimizing the intelligent lighting system of green warehousing, and make a contribution to the realization of green warehousing as soon as possible.","PeriodicalId":131654,"journal":{"name":"2022 The 6th International Conference on Compute and Data Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129357342","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: 1

Shadow Detection for Remote Sensing Images 遥感图像的阴影检测

2022 The 6th International Conference on Compute and Data Analysis Pub Date : 2022-02-25 DOI: 10.1145/3523089.3523101

Yu Guan, Xi’ai Chen, Jiandong Tian, Yandong Tang

引用次数: 1

Multivariate Time Series Imputation Based on Residual GRU and AANN 基于残差GRU和AANN的多元时间序列插值

2022 The 6th International Conference on Compute and Data Analysis Pub Date : 2022-02-25 DOI: 10.1145/3523089.3523098

Jianming Yang, Xiaochen Lai, Liyong Zhang

引用次数: 0

Chip-Firing Reservoir Computing 芯片发射油藏计算

2022 The 6th International Conference on Compute and Data Analysis Pub Date : 2022-02-25 DOI: 10.1145/3523089.3523102

Liying Liu, Yang Zheng, Ye Luo

{"title":"Chip-Firing Reservoir Computing","authors":"Liying Liu, Yang Zheng, Ye Luo","doi":"10.1145/3523089.3523102","DOIUrl":"https://doi.org/10.1145/3523089.3523102","url":null,"abstract":"Spike neural networks (SNNs), as a network structure closer to biological neurons, have been applied to many machine learning fields because of their high computing capability. However, due to its high hardware requirements and difficulty in training, the application cost of SNNs in practice is higher than that of traditional artificial neural networks and the accuracy is usually lower. In order to build a brain-like neural network with lower hardware requirements and reduce training requirements, we propose a new computing network structure called chip-firing reservoir (CFR), which can be considered as a type of more discretized SNNs. CFR computing (CFRC) can extract spatiotemporal information to improve computing capability as SNNs, while only the output layer is trained as in conventional reservoir computing (RC), reducing the difficulty of training. Furthermore, since CFRC only use integer calculations, we hope that the computational cost can be significantly reduced compared to SNNs based on floating-point computations. In the experiment, we test and analyze the CFRC for image classification tasks. The results show that CFRC has functional performance on the MNIST image data set.","PeriodicalId":131654,"journal":{"name":"2022 The 6th International Conference on Compute and Data Analysis","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132504183","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

A Multi-feature Fusion Method with Attention Mechanism for Long Text Classification 基于注意机制的长文本分类多特征融合方法

2022 The 6th International Conference on Compute and Data Analysis Pub Date : 2022-02-25 DOI: 10.1145/3523089.3523093

Tian-jian Luo, Yuqi Liu, Tianning Li

{"title":"A Multi-feature Fusion Method with Attention Mechanism for Long Text Classification","authors":"Tian-jian Luo, Yuqi Liu, Tianning Li","doi":"10.1145/3523089.3523093","DOIUrl":"https://doi.org/10.1145/3523089.3523093","url":null,"abstract":"As for the situation that the text content is long and contains much information irrelevant to the subject, which affects the performance of text classification. This paper proposes a multi-feature fusion method with attention mechanism for long text classification. Long text can be regarded as a hierarchical structure of sentences composed of words and paragraphs composed of sentences. Firstly, sentences are encoded and attention mechanism is introduced to aggregate into sentence level representation according to the different contributions of words. Then, based on the contribution of sentence level, aggregate the representation of growing text level. In sentence coding, based on the global target vector, convolutional neural network is used to extract the local features of words and average representation features of words, so as to further enhance the semantic representation of text. Finally, the important information features of long text content are fused and classified in the linear layer. The experimental results on manually processed THUCNews data show that the model has excellent classification performance in long text data with hierarchical structure, and the classification accuracy can reach 0.952.","PeriodicalId":131654,"journal":{"name":"2022 The 6th International Conference on Compute and Data Analysis","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126215430","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

Effective DemeapexNet: Revealing Spontaneous Facial Micro-Expressions 有效的DemeapexNet:揭示自发的面部微表情

2022 The 6th International Conference on Compute and Data Analysis Pub Date : 2022-02-25 DOI: 10.1145/3523089.3523103

Md. Sajjatul Islam, Weiqiang Jiang, Jiancheng Lv, A. Mohammed, Yongsheng Sang

{"title":"Effective DemeapexNet: Revealing Spontaneous Facial Micro-Expressions","authors":"Md. Sajjatul Islam, Weiqiang Jiang, Jiancheng Lv, A. Mohammed, Yongsheng Sang","doi":"10.1145/3523089.3523103","DOIUrl":"https://doi.org/10.1145/3523089.3523103","url":null,"abstract":"In affective computing, several deep learning-based strategies have been developed to classify facial micro-expression (ME), but the high recognition accuracy is yet to achieve due to some inherent challenges such as the low intensity of facial micro movement, region-specific changes, fraction second longevity, and inconsistency and a limited number of samples in publicly available spontaneous datasets. In this paper, we attempt to address these issues and propose a highly effective end-to-end deep model to recognize micro-expressions based on apex frames. Two-stage transfer learning through Image-Net and four macro expression datasets, and fine-tuning on four spontaneous micro-expression benchmark datasets, namely CASME, CASMEII, CAS(ME)2, and SAMM with four validation protocols have been implemented. Our experimental results surpass the effectiveness of the state- of-the-art methods and express the higher model generalization, which subsequently can expedite the applications such as lie catching, homeland securities, criminal detections, business deal negotiations, and clinical diagnosis through psychoanalysis.","PeriodicalId":131654,"journal":{"name":"2022 The 6th International Conference on Compute and Data Analysis","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122003825","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: 1

Intelligent Operation and Maintenance Knowledge Graph in Electric-Power Industry: Construction and Applications 电力工业智能运维知识图谱的构建与应用

2022 The 6th International Conference on Compute and Data Analysis Pub Date : 2022-02-25 DOI: 10.1145/3523089.3523105

Chao Ma, Shengya Han, Yin Liu, Z. Zhao, Dequan Gao, Haomin Gu, Hongbo Lu, Yiyou Yuan

{"title":"Intelligent Operation and Maintenance Knowledge Graph in Electric-Power Industry: Construction and Applications","authors":"Chao Ma, Shengya Han, Yin Liu, Z. Zhao, Dequan Gao, Haomin Gu, Hongbo Lu, Yiyou Yuan","doi":"10.1145/3523089.3523105","DOIUrl":"https://doi.org/10.1145/3523089.3523105","url":null,"abstract":"As the basic support for the efficient operation and maintenance of the production and management information business in the electric-power industry such as State Grid Corporation of China (short for State Grid), the construction, operation and maintenance of data centers at all levels have always been the key tasks. Recent years have witnessed many approaches to solve the intelligent operation and maintenance problems for complex network systems in all level data centers of electric-power industry. However, most existing methods utilized the operation and maintenance data in a common way, which might ignore the specialization and particularity of data in State Grid. To address this problem, in this paper, firstly, we described the main problems of existing intelligent operation and maintenance systems. Secondly, we proposed the construction method of intelligent operation and maintenance knowledge graph for cloud data center in State Grid. Finally, we proposed decision analysis and information scheduling methods for intelligent operation and maintenance based on knowledge graph in State Grid.","PeriodicalId":131654,"journal":{"name":"2022 The 6th International Conference on Compute and Data Analysis","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133862877","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

Text Messages with Emoticons Analysis on Sentiment Tools 基于情感工具的短信表情分析

2022 The 6th International Conference on Compute and Data Analysis Pub Date : 2022-02-25 DOI: 10.1145/3523089.3523091

P. Teh, Wei Yek Lim

引用次数: 0

Local Correspondence Clustering, Global Pose Verification: Efficient and Robust 3D Object Recognition 局部对应聚类、全局姿态验证:高效鲁棒的三维目标识别

2022 The 6th International Conference on Compute and Data Analysis Pub Date : 2022-02-25 DOI: 10.1145/3523089.3523100

Xi Li, Lang-Long Wu, Kai Zhong, Zhongwei Li

引用次数: 0

Online Shopping Behavior during Pandemic 疫情期间的网上购物行为

2022 The 6th International Conference on Compute and Data Analysis Pub Date : 2022-02-25 DOI: 10.1145/3523089.3523106

P. Teh, A. Lee, J. Teo

引用次数: 0