Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering最新文献

Dropping Fake Favorable Feedback for Better Sentiment Analysis 放弃虚假的有利反馈，以获得更好的情绪分析

Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering Pub Date : 2021-10-22 DOI: 10.1145/3501409.3501672

Qiankun Su, Zhida Feng, Wujin Sun, Lizhen Chen

引用次数: 0

FIRM: A Fused Information Re-optimization Method applied to the classification of defense science and technology indicators 企业:一种应用于国防科技指标分类的融合信息再优化方法

Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering Pub Date : 2021-10-22 DOI: 10.1145/3501409.3501548

Chengyuan Duan, Jiajun Cheng, Huachi Xu, Hongliang You, Q. Gao, Yizhuo Rao

{"title":"FIRM: A Fused Information Re-optimization Method applied to the classification of defense science and technology indicators","authors":"Chengyuan Duan, Jiajun Cheng, Huachi Xu, Hongliang You, Q. Gao, Yizhuo Rao","doi":"10.1145/3501409.3501548","DOIUrl":"https://doi.org/10.1145/3501409.3501548","url":null,"abstract":"Recent years have witnessed a growing interest in applying few-shot learning algorithms to personalized recommendation, and text classification tasks. In this paper, we propose a Fused Information Re-optimization Method based few-shot learning algorithm (FIRM) which can realize the fusion of label description information and sample instances. With the fusion strategy, FIRM can fully use the commonality between categories, the characteristic information of each category, and training model parame-ters with both generalization ability and classification characteristics. Further, to evaluate the validity of the proposed algorithm on the defense domain, a few-shot dataset (i.e., the defense science and technology indicators dataset) is constructed. Experimental results on the dataset validate our proposal and indicate the superior capability in classification tasks than a prototype network and MAML. Our main contributions are: 1) A few-shot dataset in the field of defense science and technology is con-structed by manually extracting the indicators from a large number of defense science and technology project evaluation documents. 2) A method of fusing information re-optimization is proposed to solve the indicator few-shot classification problem. 3) The effectiveness of FIRM is verified through comparative experiments on the constructed dataset, against with the prototype network, MAML algorithm.","PeriodicalId":191106,"journal":{"name":"Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115288543","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

Predicting the Power Consumption and Operating Rate of Enterprises in Major Public Events 重大公共活动中企业用电量及开工率预测

Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering Pub Date : 2021-10-22 DOI: 10.1145/3501409.3501575

Zheng Zhu, Yingjie Tian, Hongshan Yang

{"title":"Predicting the Power Consumption and Operating Rate of Enterprises in Major Public Events","authors":"Zheng Zhu, Yingjie Tian, Hongshan Yang","doi":"10.1145/3501409.3501575","DOIUrl":"https://doi.org/10.1145/3501409.3501575","url":null,"abstract":"The power consumption of enterprises in major public events may significantly different from non-event days, which brings new challenges for the existing power distribution system. Conventional approaches to predicting power consumption are mainly based on statistical learning methods, such as a particular fitted distribution, logistic regression, decision trees, etc. However, the customer's power behaviors change significantly during the major public events, which may lead to suboptimal performance for existing methods. To overcome these challenges, we propose a novel long and short-term memory-based attentional algorithm to accurately predict the power consumption and corresponding operating rate of enterprises in major public events. In particular, we firstly employ long term memory gate to learn the most important historical pattern and forget the irrelevant behaviors. Then, the short-term memory is leveraged to increase the importance of recent patterns. Lastly, compared with the conventional method that gives equal weights to different slices, we design an attentional prediction network to dynamically adjust the weights of long and short-term patterns. We optimize the proposed end-to-end deep learning model by standard stochastic gradient descent (SGD) algorithms.","PeriodicalId":191106,"journal":{"name":"Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115311325","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

Evaluation of Uncertainty in Rocket Sled Velocity Measurement Based on Hall Effect Sensor 基于霍尔效应传感器的火箭滑橇速度测量不确定度评定

Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering Pub Date : 2021-10-22 DOI: 10.1145/3501409.3501439

Wei-wei Zhang, Jun Xiao, Qiang Geng, Qiang Xue, Linrui Zhang, Biao Guo

引用次数: 0

Adaptive Neural Network Fault Tolerant Control for a Hydraulic System 液压系统的自适应神经网络容错控制

Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering Pub Date : 2021-10-22 DOI: 10.1145/3501409.3501535

Bohao Li, Dong Cheng, Xiaorui Zong, Haijie Jia

引用次数: 0

Safe operation and maintenance management and control technology based on grade protection 2.0 基于等级保护2.0的安全运维管控技术

Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering Pub Date : 2021-10-22 DOI: 10.1145/3501409.3501468

Yue Sun, Wei Chen, Qinglin Yuan, Yin Yuan

{"title":"Safe operation and maintenance management and control technology based on grade protection 2.0","authors":"Yue Sun, Wei Chen, Qinglin Yuan, Yin Yuan","doi":"10.1145/3501409.3501468","DOIUrl":"https://doi.org/10.1145/3501409.3501468","url":null,"abstract":"With the rapid development of technologies such as the Internet of Things and 5G communications, the intelligent era of the Internet of Everything is accelerating. This situation poses a huge challenge to the currently widely used cloud computing model. Edge computing is a new computing model that provides intelligent services at the edge of the network close to the source of things or data. It can save network traffic, improve response speed and protect user privacy. It shows better performance than cloud computing in IoT applications, has been highly concerned and unanimously recognized by the industry and academia. With the rapid development of my country's economy, information-based production tools have entered all aspects of people's work and life such as industry, agriculture, commerce, medical care, education, etc., and online commerce, online banking, and online medical services that involve personal private information. Services are increasing, and national military and political intelligence is transmitted more frequently through the Internet. Under this circumstance, ensuring the security of information has increasingly become the most urgent problem that needs to be solved quickly in today's society. It is occupies the most important position in the national industrial layout and even the national security strategy pattern. In this context, with \"Grade protection 2.0\" as the standard, the core content of \"Grade protection 2.0\" is \"one center, triple protection\". That is to build a security management center, do a good job in the protection of the computing environment, regional boundaries and communication networks, and form a comprehensive network security defense system.","PeriodicalId":191106,"journal":{"name":"Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117125295","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

Credibility Evaluation Method for Multidimensional Uncertain Interval Data based on the Evidence Theory 基于证据理论的多维不确定区间数据可信度评估方法

Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering Pub Date : 2021-10-22 DOI: 10.1145/3501409.3501511

Suike Li, Yongchao Zhao, Haijun Wang

引用次数: 0

Intra-Pulse Feature Extraction of Radar Emitter Signals Based on Complex Network 基于复杂网络的雷达发射信号脉冲内特征提取

Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering Pub Date : 2021-10-22 DOI: 10.1145/3501409.3501521

Yiming Ma, Taowei Chen, Huiyuan Wang, Jian Hu, Jingyi Wang, Chao Peng

{"title":"Intra-Pulse Feature Extraction of Radar Emitter Signals Based on Complex Network","authors":"Yiming Ma, Taowei Chen, Huiyuan Wang, Jian Hu, Jingyi Wang, Chao Peng","doi":"10.1145/3501409.3501521","DOIUrl":"https://doi.org/10.1145/3501409.3501521","url":null,"abstract":"The electromagnetic signal environment of the modern battlefield is complex. The radar signal recognition technology based on the traditional five parameters cannot meet the actual needs. For this reason, it is urgent to explore new identification methods to improve the technical level of existing radar countermeasure equipment in electronic warfare. Aiming at the research challenge of low-accuracy intra-pulse waveform recognition in a dense modern electronic warfare environment, In this paper, we propose a new method to extract the characteristics of radar emission signals. This method first reconstructs the radar transmitter signal into a complex network, and then extracts the characteristics of the complex network. In our algorithm, the features are extracted from network topology statistics with each vector point of the reconstructed phase space represented by a single node and edge determined by the phase space distance. Through analyzing the global properties of network nodes, we found that the network constructed by the method described in this article inherited the dynamic characteristics of all aspects of the intentional intra-pulse modulation type of radar signals in time domain. Furthermore, we investigate the stability and sensibility of feature parameters with the variation range from 5dB to 20dB. Computer simulation demonstrates how the topological indices of the network can be used to distinguish different modulation types of radar emitter signals. At the same time, the experimental results show that the extracted feature vectors have good ability of noise-resistance and good clustering quality in low SNR environment when the radar signals are corrupted by measurement noise.","PeriodicalId":191106,"journal":{"name":"Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124855141","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

Construction and Optimization of Emergency Prediction Model based on random Forest algorithm 基于随机森林算法的应急预测模型构建与优化

Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering Pub Date : 2021-10-22 DOI: 10.1145/3501409.3501707

Xiang Chen, Siyuan Gong

引用次数: 0

The Relationship between Packaging Structures, Chip Area and Thermal Resistance of NMOS Semiconductor in Transient Dual Interface Method 瞬态双界面法中NMOS半导体封装结构、芯片面积与热阻的关系

Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering Pub Date : 2021-10-22 DOI: 10.1145/3501409.3501417

Fan Chen, Dapeng Liu, Long Chen, Shuai Tao, Jun You, Zebin Kong

引用次数: 0