Transactions on Computer Science and Intelligent Systems Research最新文献_第4页

LIS-based Inspection Knowledge Graph Construction System 基于 LIS 的检测知识图谱构建系统

Transactions on Computer Science and Intelligent Systems Research Pub Date : 2023-12-21 DOI: 10.62051/qvbck941

Fengyang Fu, Shuangling Sun, Yi Liu

引用次数: 0

Preface: 5th International Conference on Computer Engineering, Information Science and Internet Technology (CII 2023) 前言：第五届计算机工程、信息科学和互联网技术国际会议（CII 2023）

Transactions on Computer Science and Intelligent Systems Research Pub Date : 2023-12-21 DOI: 10.62051/sx9w6f02

Lawrence Symons, Xiaoming Zhu

{"title":"Preface: 5th International Conference on Computer Engineering, Information Science and Internet Technology (CII 2023)","authors":"Lawrence Symons, Xiaoming Zhu","doi":"10.62051/sx9w6f02","DOIUrl":"https://doi.org/10.62051/sx9w6f02","url":null,"abstract":"The organizing Committee of CII 2023 warmly welcomes you to join the 5th International Conference on Computer Engineering, Information Science and Internet Technology (CII 2023), which was held on November 11-12, 2023 in Sanya, China. On the move towards the 21st century, Computer Engineering, Information Science and Internet Technology are the important tools to solve the global problems, e.g. the energy and environmental problems, as well as to foster the prosperities for a better life. They are created from the simple ideas that make the difference, the ideas that connect the dots of different fields of knowledge. Thus, the objective of this conference is to gather engineers, scientists and innovators to share their new findings and ideas in different fields of knowledge. This is to share their experiences in specific domains as well as across the fields with the aim at provoking emerging innovative ideas and further collaborations. Hopefully, all participants and other interested readers benefit scientifically from the proceedings and also find it stimulating in the process. Lawrence Symons, Xiaoming Zhu Conference Organizing Chair","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139167854","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 of the New Generation Marine Navigation Security Communication System 新一代海洋导航安全通信系统研究

Transactions on Computer Science and Intelligent Systems Research Pub Date : 2023-12-21 DOI: 10.62051/vvvtye15

Jingyi Qian, Huilu Zeng, Guowei Yao, Fanwei Kong

引用次数: 0

Comparative Study on BEV Vision and LiDAR Point Cloud Data Fusion Methods BEV 视觉与激光雷达点云数据融合方法比较研究

Transactions on Computer Science and Intelligent Systems Research Pub Date : 2023-12-21 DOI: 10.62051/ww28m534

Junyu Zhou

{"title":"Comparative Study on BEV Vision and LiDAR Point Cloud Data Fusion Methods","authors":"Junyu Zhou","doi":"10.62051/ww28m534","DOIUrl":"https://doi.org/10.62051/ww28m534","url":null,"abstract":"With the gradual maturity of autonomous driving technology, efficient fusion and processing of multimodal sensor data has become an important research direction. This study mainly explores the strategy of integrating BEV (Bird's Eye View) vision with LiDAR point cloud data. We evaluated the performance and applicability of each of the three main data fusion methods through in-depth comparison: early fusion, mid-term fusion, and late fusion. First of all, we summarize the working principle and data characteristics of BEV vision and LiDAR, and emphasize their key roles in auto drive system. Then, the theoretical basis and implementation methods of the three fusion strategies were described in detail. The experimental results show that different fusion strategies exhibit their own advantages in different application scenarios and requirements. For example, early fusion performs well in high-precision tasks, but has a high demand for computing resources. And mid-term fusion is more suitable in scenarios with high real-time requirements. Overall, this study provides in-depth insights and practical suggestions on the fusion of BEV vision and LiDAR data in the field of autonomous driving, laying a solid foundation for future research and applications.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139167055","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

Analysis of Navigation Aid Effectiveness of Tianjin Port Water Depth Signal Tower and Development Protection under New Technical Conditions 天津港水深信号塔助航效果分析及新技术条件下的发展保障

Transactions on Computer Science and Intelligent Systems Research Pub Date : 2023-12-21 DOI: 10.62051/b9rgpv05

Qiang Guo, Huwei Huo

引用次数: 0

Study and Application of Optimization Model on Survey Line under Multibeam Bathymetric System 多波束测深系统下勘测线优化模型的研究与应用

Transactions on Computer Science and Intelligent Systems Research Pub Date : 2023-12-21 DOI: 10.62051/qz4ejr94

Lincheng Ni

引用次数: 0

Research on Patient Information Demand Preference in Network Health Community based on TF-IDF Algorithm and BTM Model 基于 TF-IDF 算法和 BTM 模型的网络健康社区患者信息需求偏好研究

Transactions on Computer Science and Intelligent Systems Research Pub Date : 2023-12-21 DOI: 10.62051/n9p3y891

Rong Hu, Yiting Guo, Yunxia Cheng, Yuzhu Zhang, Shuang Liu

{"title":"Research on Patient Information Demand Preference in Network Health Community based on TF-IDF Algorithm and BTM Model","authors":"Rong Hu, Yiting Guo, Yunxia Cheng, Yuzhu Zhang, Shuang Liu","doi":"10.62051/n9p3y891","DOIUrl":"https://doi.org/10.62051/n9p3y891","url":null,"abstract":"With the rapid development of information technology, the network health community has become an important way of doctor-patient communication in the new era. As the starting point of the doctor-patient communication process, patient information needs are an important basis for conducting information communication research in online health communities. In this study, we take the question data of medical patients in the \"ask and answer\" community from the website called \"xunyiwenyao\" in 2022 as samples, and the TF-IDF algorithm was applied to draw word cloud map to reveal the hot spots of patient information demand in the secondary department, apply the BTM toic model to identify the information demand topic of patients in the network health community, and extract the information demand preferences of internal medicine patients. The study found that users of patients in online health communities pay more attention to the causes and countermeasures of initial symptoms and uncomfortable symptoms, and prefer to obtain relevant information about the efficacy and side effects of medical products.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139166510","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 "Colour Revolution" in Iran? Attack it with a Social Stability Model based on TOPSIS! 伊朗的 "颜色革命"？用基于 TOPSIS 的社会稳定模型应对它！

Transactions on Computer Science and Intelligent Systems Research Pub Date : 2023-12-21 DOI: 10.62051/9d7cf695

Huijun Bao

{"title":"A \"Colour Revolution\" in Iran? Attack it with a Social Stability Model based on TOPSIS!","authors":"Huijun Bao","doi":"10.62051/9d7cf695","DOIUrl":"https://doi.org/10.62051/9d7cf695","url":null,"abstract":"A \"color revolution\" achieves regime change by attacking the weakest link in society, but once the ratio of each link in society is out of balance, it will cause social deformation and thus affect social stability. To study the factors affecting social stability and avoid \"color revolutions\", it is necessary to establish an effective social stability index system, and on this basis, to build a social stability coefficient model. To establish a complete social stability index system, this paper selects population, defense science and technology, environment, education, economy, and agriculture after dimensionality reduction. The six indicators were then downscaled to obtain population, national defense, science and technology, environment, education, economy, and agriculture, and the social stability coefficient was classified into five levels from 0 to 1 using the TOPSIS evaluation algorithm, with the higher the level the worse the social stability. Using Spearman and Akaike Causality to test the indicator system, it was found that there was a significant correlation and causality between the stability coefficient and each indicator, and the indicator system was well established. For regions that failed to launch \"color revolutions\", this paper takes Iran as an example, and after bringing its 44 indicators into the social stability coefficient model in 2018, it comes out that the social stability coefficient of Iran is 0.637, and the social stability level is in the second level of stability to the third level of stability, which is a more stable state at this time. There may be some precursors of social unrest. At the same time, Iran's population development and education level are at a high level, and the general education and knowledge of the Iranian people are high, so the number of people who participate in internal conflicts and revolutions is reduced, which leads to the failure of color revolutions.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139166706","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 Adaptive Cluster Sampling Method based on PPS 基于 PPS 的自适应聚类抽样方法研究

Transactions on Computer Science and Intelligent Systems Research Pub Date : 2023-12-21 DOI: 10.62051/artkb294

Shaohua Wang, Ting Yang, Shengxiang Ouyang

引用次数: 0

Large-scale Data Mining Method based on Clustering Algorithm Combined with MAPREDUCE 基于聚类算法与 MAPREDUCE 结合的大规模数据挖掘方法

Transactions on Computer Science and Intelligent Systems Research Pub Date : 2023-12-21 DOI: 10.62051/8p9b3106

Yulun Zhang, Chenxu Zhang, Lei Yang, Hongyang Li

{"title":"Large-scale Data Mining Method based on Clustering Algorithm Combined with MAPREDUCE","authors":"Yulun Zhang, Chenxu Zhang, Lei Yang, Hongyang Li","doi":"10.62051/8p9b3106","DOIUrl":"https://doi.org/10.62051/8p9b3106","url":null,"abstract":"With the continuous deepening and development of information technology, the diversity and amount of information in data continue to grow. Effectively mining these text data to extract valuable content has become an urgent task in the field of data research. This study combines the MapReduce distributed system with the K-means clustering algorithm to meet the challenges of large-scale data mining. At the same time, the paper use a distributed caching mechanism to solve the problem of repeated application of resources for multiple MapReduce collaborative operations and improve data mining efficiency. The combination of MapReduce's distributed computing and the advantages of K-means clustering algorithm provides an efficient and scalable method for large-scale data mining. Experimental results combining internal and external indicators show that the advantage of combining K-means with MapReduce is to fully utilize the distributed and parallel computing characteristics of MapReduce, providing users with an efficient and scalable data mining tool. Through this research, the paper provide new methods and insights for large-scale data mining, improving the efficiency and accuracy of data mining.","PeriodicalId":509968,"journal":{"name":"Transactions on Computer Science and Intelligent Systems Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139166491","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