发布求助
文献互助 智能选刊 最新文献

2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)最新文献

筛选
英文 中文
Research on several major diseases based on machine learning models 基于机器学习模型的几种主要疾病研究
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00080
Wentao Gao, Lijing Liu
{"title":"Research on several major diseases based on machine learning models","authors":"Wentao Gao, Lijing Liu","doi":"10.1109/AEMCSE55572.2022.00080","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00080","url":null,"abstract":"Due to the continuous growth of disease types and past cases, it is more and more difficult to diagnose diseases only by manpower. Machine learning is a model mechanism that is sensitive to data and relies on a large amount of data to complete training. It is very suitable for medical diagnosis. Many scholars have tried to use ML to develop medical diagnosis systems, but they are basically not used in the real world at this stage. This article reviews the work related to medical detection of three major diseases (heart disease, cancer, and COVID-19), aiming to summarize previous experiences to help future scholars conduct research. Specifically, this paper summarizes the research status of the prediction of these three types of diseases based on machine learning methods, evaluate the accuracy and universality of the corresponding prediction models based on time as a clue, and use a comparative method to find out the progress researchers have made in this area and limitations still exist at this stage. And at the end of the article, the results and some potential work fields of the future in these studies are summarized.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132333769","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
An Active Queue Management Algorithm to Enhance RED Stability 一种提高RED稳定性的主动队列管理算法
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00108
Debin Wei, Xuechun Zheng, Zuoren Yan, Ruivan Cai
{"title":"An Active Queue Management Algorithm to Enhance RED Stability","authors":"Debin Wei, Xuechun Zheng, Zuoren Yan, Ruivan Cai","doi":"10.1109/AEMCSE55572.2022.00108","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00108","url":null,"abstract":"RED is an active queue management algorithm to solve the end-to-end congestion problem of TCP. In order to further reduce the fluctuation of the queue length in the RED algorithm, improve the end-to-end throughput performance, and reduce the end-to-end delay jitter, an active queue management algorithm ARRED that enhances the stability of RED is proposed. The algorithm replaced the original linearly increasing packet drop probability function with the larger-scale ascending ridge function, which made the change of the packet loss probability function between the minimum and maximum queue length thresholds smoother. Considering the problem that the sharp change of the packet loss probability causes queue jitter when the maximum threshold is exceeded, a new parameter was set to adjust the packet drop probability. The simulation results show that the algorithm can effectively maintain the stability of the queue length, reduce the packet loss rate and delay jitter, and improve the network throughput performance.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116566264","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
Improvement of Collaborative Filtering Algorithm Based on University Book Recommendation System 基于高校图书推荐系统的协同过滤算法改进
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00165
Xuejing Ding, Lei Tang
{"title":"Improvement of Collaborative Filtering Algorithm Based on University Book Recommendation System","authors":"Xuejing Ding, Lei Tang","doi":"10.1109/AEMCSE55572.2022.00165","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00165","url":null,"abstract":"In view of a series of problems in college book recommendation, such as cold start of users, high proportion of popular recommendations and low recommendation accuracy, this paper improves these problems based on the problems of the existing collaborative filtering algorithm and combined with the characteristics of college book borrowing. An improved University book recommendation algorithm is proposed, in which the time attenuation factor is added when generating the user evaluation matrix, and the influence of gender and professional factors on the user feature similarity is considered. The algorithm solves the problem of insufficient score of collaborative filtering algorithm. Experiments show that this algorithm is better than the traditional collaborative filtering recommendation algorithm and can meet the actual needs.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117042726","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-step Time Series Prediction Strategy in Deep Learning: Combination of Recursive Strategy and Multi-output by Dense Layer Strategy 深度学习中的多步时间序列预测策略:递归策略与密集层多输出策略的结合
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00076
Yuxuan Liu
{"title":"A Multi-step Time Series Prediction Strategy in Deep Learning: Combination of Recursive Strategy and Multi-output by Dense Layer Strategy","authors":"Yuxuan Liu","doi":"10.1109/AEMCSE55572.2022.00076","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00076","url":null,"abstract":"In practical applications, when solving the problem of time series prediction, it is often necessary to predict the data of multiple time points in the future according to the observed data. It’s a problem called multi-step time series prediction. Now there are some solutions to handle the problem, but each solution has its own advantages and is insufficient. As a result, the goal of this paper is to combine the recursive strategy and the multi-output strategy to propose a new method for solving the multi-step time series prediction problem to gain better performance than either of them alone. In the research, the author will use House Hold Energy data from Kaggle and conduct a contrast experiment to reflect the advantages of the combined strategy. The experiment results show that the combined strategy outperforms the recursive and multi-output strategies.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"346 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132441012","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 cross-layer attack path detection method for smart grid dynamics 一种智能电网动态跨层攻击路径检测方法
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/aemcse55572.2022.00036
Binbin Wang, Yi Wu, Naiwang Guo, Lei Zhang, Changjiang Liu
{"title":"A cross-layer attack path detection method for smart grid dynamics","authors":"Binbin Wang, Yi Wu, Naiwang Guo, Lei Zhang, Changjiang Liu","doi":"10.1109/aemcse55572.2022.00036","DOIUrl":"https://doi.org/10.1109/aemcse55572.2022.00036","url":null,"abstract":"With the intelligent development of power system, due to the double-layer structure of smart grid and the characteristics of failure propagation across layers, the attack path also changes significantly: from single-layer to multi-layer and from static to dynamic. In response to the shortcomings of the single-layer attack path of traditional attack path identification methods, this paper proposes the idea of cross-layer attack, which integrates the threat propagation mechanism of the information layer and the failure propagation mechanism of the physical layer to establish a forward-backward bi-directional detection model. The model is mainly used to predict possible cross-layer attack paths and evaluate their path generation probabilities to provide theoretical guidance and technical support for defenders. The experimental results show that the method proposed in this paper can well identify the dynamic cross-layer attacks in the smart grid.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132736616","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
Design and Realization of Conductor for Spacecraft Based on Single-chip Microcomputer 基于单片机的航天器导体设计与实现
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/aemcse55572.2022.00014
Xiaohui Song, Liangbin Guo
{"title":"Design and Realization of Conductor for Spacecraft Based on Single-chip Microcomputer","authors":"Xiaohui Song, Liangbin Guo","doi":"10.1109/aemcse55572.2022.00014","DOIUrl":"https://doi.org/10.1109/aemcse55572.2022.00014","url":null,"abstract":"In equipment production and testing, various cables are inevitably used, such as power cables; signal cables, etc., which are important guarantees for the normal operation of the equipment; The continuity test is very important. The conduction device described in this article is implemented based on a single-chip microcomputer, and the structure adopts a winding storage method, which is very convenient, and a variety of interfaces are suitable for different interfaces. Functionally, the sound frequency can be set by itself, with battery protection detection, the sound is loud and clear, and it can work in noisy environments. In order to ensure the design reliability of the turner, the most advanced imported microcontroller is used in the selection of the device, and the corresponding system planning, hardware architecture and software design are carried out. Hardware redundancy design and dual filtering method are used.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128099565","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
Genomic structure variation prediction method based on convolution and recurrent network 基于卷积和递归网络的基因组结构变异预测方法
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00056
Jinqiang Li, Hai Yang, Feng Geng, Changde Wu
{"title":"Genomic structure variation prediction method based on convolution and recurrent network","authors":"Jinqiang Li, Hai Yang, Feng Geng, Changde Wu","doi":"10.1109/AEMCSE55572.2022.00056","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00056","url":null,"abstract":"Predict genomic variants from gene sequencing data is the central task in biological genome sequence analysis. It also serves as the foundation for identifying and screening pathogenic variants as well as conducting pharmaco genomics research. The data in the field of genomics is typically massive, high-dimensional, and serialized, and deep learning, as a data- driven algorithm, has strong feasibility and potential in the field of bioinformatics. Based on previous research, the goal of this study is to predict structural variation in high-throughput sequencing data from the 1000 Genome Project’s BAM file NA12878. BAM files are also combined with VCF files to improve prediction efficiency. VCF files are frequently used to store prediction results. It contains information such as the sample number, chromosome position, mutation type, and mutation breakpoint. BAM and VCF files are converted into images in this paper, and a gene structure mutation prediction method based on the fusion of the Inception-ResNet-v2 and BiLSTM algorithm models is proposed.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"47 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133018474","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
Division of dataset into training and validation subsets by the jackknife validations to predict the pH optimum for beta-cellobiosidase 将数据集划分为训练子集和验证子集，通过刀切验证来预测β -纤维素生物苷酶的最佳pH值
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/aemcse55572.2022.00136
Shaomin Yan, Guang Wu
{"title":"Division of dataset into training and validation subsets by the jackknife validations to predict the pH optimum for beta-cellobiosidase","authors":"Shaomin Yan, Guang Wu","doi":"10.1109/aemcse55572.2022.00136","DOIUrl":"https://doi.org/10.1109/aemcse55572.2022.00136","url":null,"abstract":"In modeling, it is generally to divide the dataset into training and validation sub-datasets. Although it appears simple, how to divide the dataset is still somewhat debatable. Of various methods to make the division, the jackknife method is very popular and advocated by professor Kuo-Chen Chou. However, the jackknife method is in fact mainly referenced to the delete-1 jackknife validation because the rest jackknife methods are extremely time-consuming and computationally intensive. In this study, we use the jackknife validations from delete-1 to delete- n+2 to develop a neural network model for the optimization of pH in an enzymatic reaction of beta-cellobiosidase, which gets more and more attention from biofeul industries, but has a small number of documented operational parameters. The best neural network model and the best predictor were elaborated from 31 candidates of neural network with different layers and neurons, and 11 predictors related to the amino acid primary structure. The jackknife validation was performed from delete-1 to delete- 18. The results show that the [6], [1] model provides the best performance among two-layer models, and that multi-layer models perform better than the two-layer model. The delete-6 jackknife strategy has the best performance, which suggests the division of dataset at the ratio of one third.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113965531","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 data-assisted adaptive detection algorithm for shortwave burst signals 一种数据辅助的短波突发信号自适应检测算法
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00118
Feng Yi Wei, Qu Wen Zhong, Zhao-jun Yan, Zhou Yu Mei
{"title":"A data-assisted adaptive detection algorithm for shortwave burst signals","authors":"Feng Yi Wei, Qu Wen Zhong, Zhao-jun Yan, Zhou Yu Mei","doi":"10.1109/AEMCSE55572.2022.00118","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00118","url":null,"abstract":"For shortwave signals with unique code frame structure, a data-assisted adaptive burst detection algorithm is proposed in this paper. The algorithm weakens the high bottom-noise undulation of signal correlation values due to shortwave channel fading by using a locally normalized sliding differential correlation. Also based on this, an adaptive gate limit detection strategy based on sliding window comparison judgments is used to improve the burst detection accuracy. This paper focuses on the effects of signal-to-noise ratio and shortwave channel environment on the performance of this algorithm, and simulation experiments are conducted under different conditions. The simulation results show that the algorithm has good robustness and can still achieve good detection results in the case of low signal-to-noise ratio as well as short-wave poor channels.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121292801","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 the Embedded Mathematical Model of Artificial Intelligence Measurement 人工智能测量的嵌入式数学模型研究
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) Pub Date : 2022-04-01 DOI: 10.1109/AEMCSE55572.2022.00079
Xiujian Zhang, Jing Sun, Zhonghao Cheng, Haoyi Chen
{"title":"Research on the Embedded Mathematical Model of Artificial Intelligence Measurement","authors":"Xiujian Zhang, Jing Sun, Zhonghao Cheng, Haoyi Chen","doi":"10.1109/AEMCSE55572.2022.00079","DOIUrl":"https://doi.org/10.1109/AEMCSE55572.2022.00079","url":null,"abstract":"In view of the unclear concept and weak basic theory of artificial intelligence, the bottleneck of basic measurement technology has not been solved. The relationship between AI metrics and basic cognitive quantity is extremely complex, so it is challenging and uncertain to scientifically construct its functional relationship. This article starts from revealing the internal mechanism, measurement principle and essential characteristics of artificial intelligence, the embedded physical laws are characterized, and the measurement model theory based on intelligence entropy is proposed. Multi-channel exploration of artificial intelligence measurement traceability methods provides ideas for forming the relationship model between artificial intelligence measurement indicators and benchmark quantities. The design verification method and approach of artificial intelligence measurement are established to ensure the reproducibility, accuracy and consistency of artificial intelligence measurement method and data.","PeriodicalId":309096,"journal":{"name":"2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121403173","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信