2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC)最新文献_第5页

A Weighted Routing Protocol for Airborne Ultraviolet Communication Network Based on Link State Perception 一种基于链路状态感知的机载紫外通信网络加权路由协议

2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC) Pub Date : 2021-04-01 DOI: 10.1109/CTISC52352.2021.00027

Z. Xiwen, Wang Yuan

引用次数: 0

Improved K-means Clustering Algorithm by Combining with Multiple Factors 基于多因素的改进K-means聚类算法

2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC) Pub Date : 2021-04-01 DOI: 10.1109/CTISC52352.2021.00054

Tianqi Lei, Shuqin Li

{"title":"Improved K-means Clustering Algorithm by Combining with Multiple Factors","authors":"Tianqi Lei, Shuqin Li","doi":"10.1109/CTISC52352.2021.00054","DOIUrl":"https://doi.org/10.1109/CTISC52352.2021.00054","url":null,"abstract":"The traditional K-means clustering algorithm has the problems that the number of clusters needs to be determined artificially, the clustering results are easily affected by the initial clustering centers and isolated points, and the iterative process is computationally complicated. To address above problems, an improved K-means clustering algorithm combining multi-point optimization(MFK-means) is proposed. The proposed algorithm is improved from the following four aspects. Firstly, the number of clusters is jointly determined by combining the contour coefficient method and the elbow rule. Secondly, the optimized outlier detection algorithm is used to exclude the influence of isolated points on the clustering results. Thirdly, the initial clustering centers are gradually determined based on the outlier candidate set and the maximum-minimum distance idea. Finally, the heuristic method is used to reduce the computational effort of the iterative process. The experimental results on the UCI dataset show that the proposed improved algorithm has higher clustering accuracy and better stability than the traditional K-means algorithm and another improved algorithm.","PeriodicalId":268378,"journal":{"name":"2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114857155","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: 2

A Collaborative Recommendation Model of Agricultural Planting Technology Based on User Characteristics 基于用户特征的农业种植技术协同推荐模型

2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC) Pub Date : 2021-04-01 DOI: 10.1109/CTISC52352.2021.00055

Yinfan Hui, Shuqin Li

{"title":"A Collaborative Recommendation Model of Agricultural Planting Technology Based on User Characteristics","authors":"Yinfan Hui, Shuqin Li","doi":"10.1109/CTISC52352.2021.00055","DOIUrl":"https://doi.org/10.1109/CTISC52352.2021.00055","url":null,"abstract":"In view of the lack of informatization in the field of agricultural planting production, the traditional collaborative filtering recommendation algorithm has problems such as cold start, sparse scoring matrix, and poor scalability, resulting in poor recommendation quality. A personalized recommendation model of collaborative filtering agricultural planting technology that integrates user characteristics is proposed. First, the user’s initial characteristics are constructed according to the user’s geographic location, planting occupation, and main crops, and user behavior information is used to update user characteristics. Then combine the user characteristic similarity model and the rating matrix similarity model, and reconcile the weighting factors to form the user’s comprehensive similarity. Finally, use Top-N for personalized recommendation. By integrating user characteristics, the recommendation model is more suitable for agricultural planting scenarios, and the recommendation results are more flexible and reasonable. Experimental results show that compared with user-based collaborative filtering recommendation and user-characteristic-based recommendation, the proposed algorithm improves precision by 2% and 7%, recall rate by 2% and 9%, and F1 value is 71%. The effectiveness of the proposed method is verified.","PeriodicalId":268378,"journal":{"name":"2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116976248","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

Study on Evaluation and Optimization of Subway Train Rescue Plan Based on Game Theory and Set Pair Model 基于博弈论和集合对模型的地铁列车救援方案评价与优化研究

2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC) Pub Date : 2021-04-01 DOI: 10.1109/CTISC52352.2021.00035

Cao Jie, Wang Bo

引用次数: 0

A Probability-Based Fault Tolerance Strategy For Service-Based Systems 基于服务系统的概率容错策略

2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC) Pub Date : 2021-04-01 DOI: 10.1109/CTISC52352.2021.00025

Futian Wang, T. Hong, Dechun Wang, Cheng Zhang

{"title":"A Probability-Based Fault Tolerance Strategy For Service-Based Systems","authors":"Futian Wang, T. Hong, Dechun Wang, Cheng Zhang","doi":"10.1109/CTISC52352.2021.00025","DOIUrl":"https://doi.org/10.1109/CTISC52352.2021.00025","url":null,"abstract":"In the cloud environment, software vendors have built a large number of multi-tenant service-based systems (SBSs) by integrating distributed services to provide customers with software-as-a-service. However, when operating in the volatile cloud environment, the system components of an SBS may experience quality degradation caused by various runtime anomalies, e.g., virtual machine faults, software exceptions, etc. Handling runtime anomalies of multi-tenant SBSs timely and cost-effectively is critical to ensuring the quality of the SBS. A number of fault tolerance approaches have been proposed in recent years to tackle this problem. However, existing approaches have not properly considered the fact that the quality of a distributed system component often varies over time. In this paper, we propose PFT4MTS (Probability-based Fault Tolerance for Multi-Tenant SBSs), a novel approach for formulating cost-effective fault tolerance strategies for multi- tenant SBSs by implementing redundancy for critical system components. First, PFT4MTS evaluates the criticality of each system component by its multi-dimensional quality over time and multiple tenants sharing the system components with differentiated quality preferences. Then, it employs integer programming to formulate the optimal fault tolerance strategy based on the criticalities of different system components. As shown by the experimental results, PFT4MTS outperforms four existing representative approaches in ensuring the quality of quality of multi-tenant SBSs upon runtime anomalies.","PeriodicalId":268378,"journal":{"name":"2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133670839","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

Low-quality Video Key Frame Extraction via Affinity Propagation 通过亲和力传播提取低质量视频关键帧

2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC) Pub Date : 2021-04-01 DOI: 10.1109/CTISC52352.2021.00074

Jixin Liu, Ning Sun, G. Han, Xiaofei Li

引用次数: 0

Construction of knowledge graph of drug-action mechanism 药物作用机理知识图谱的构建

2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC) Pub Date : 2021-04-01 DOI: 10.1109/CTISC52352.2021.00038

Jie Zhao, Aiyu Wang, Fangfang Su, Yanyan Chen, Honghai Feng

{"title":"Construction of knowledge graph of drug-action mechanism","authors":"Jie Zhao, Aiyu Wang, Fangfang Su, Yanyan Chen, Honghai Feng","doi":"10.1109/CTISC52352.2021.00038","DOIUrl":"https://doi.org/10.1109/CTISC52352.2021.00038","url":null,"abstract":"Background: Medical texts contain a large amount of information on the mechanism of action of drug ingredients, and it is impossible to manually collate the massive information in dozens or millions of papers. The method of relationship abstraction in data mining can be used to extract the mechanism of drug action. Methods: First, 770000 papers’ abstracts on the mechanism of the drug in Chinese journals were collected; an algorithm to identify the sentence patterns and semantic elements of the mechanism of drug action were developed; the corresponding semantic elements were extracted by this algorithm. Finally, a knowledge graph was established by the Neo4j tool. Results: A total of 30710 mechanisms of drug action were found, and 57865 drug-action mechanism relations were established. The recall rate of the algorithm to extract semantic elements and their relations was 0.59, the accuracy is 0.86. Conclusion: The algorithm can accurately and comprehensively extract semantic elements and their relationships. Comparison with drug knowledge graphs such as DRKG, this knowledge graph of drug-action mechanism covers a large number of drugs and mechanism of action more comprehensively, which can facilitate new drug development and query of drugs-action mechanism.","PeriodicalId":268378,"journal":{"name":"2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC)","volume":"64 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114110391","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: 2

Weak Commutativity of Quantum Automata 量子自动机的弱交换性

2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC) Pub Date : 2021-04-01 DOI: 10.1109/CTISC52352.2021.00019

Feidan Huang, Fasheng Cao

引用次数: 0

Correlation between Nitrogen Pollution and WWTPs Discharge in Lake Taihu 太湖氮素污染与污水排放的相关性研究

2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC) Pub Date : 2021-04-01 DOI: 10.1109/CTISC52352.2021.00010

Z. Shan, Wen-Qi Du

引用次数: 1

Recognition of Air Traffic Controller’s Mouth State Based on Deep Convolutional Neural Network 基于深度卷积神经网络的空中交通管制员嘴态识别

2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC) Pub Date : 2021-04-01 DOI: 10.1109/CTISC52352.2021.00080

Chuxin Xu

引用次数: 0