2021 International Conference on Management Science and Software Engineering (ICMSSE)最新文献_第6页

GIS-based analysis and optimization of TCM medical resources in China 基于gis的中国中医药资源分析与优化

2021 International Conference on Management Science and Software Engineering (ICMSSE) Pub Date : 2021-07-01 DOI: 10.1109/ICMSSE53595.2021.00022

Lan Ding, Jun-yong Wagn, N. Tian

{"title":"GIS-based analysis and optimization of TCM medical resources in China","authors":"Lan Ding, Jun-yong Wagn, N. Tian","doi":"10.1109/ICMSSE53595.2021.00022","DOIUrl":"https://doi.org/10.1109/ICMSSE53595.2021.00022","url":null,"abstract":"Objective-To analyze the current situation and changing trend of the total medical resources of TCM, and to provide reference for the development of TCM service. Methods-Collect the 2012–2019 Health Statistics Yearbook of China, analyze the quantity and changing trend of health resources of TCM by using descriptive statistics, and make a visual analysis of the distribution health resources of TCM in various provinces by using GIS technology. Results-By the end of 2019,the total number of TCM personnel, the number of beds in TCM medical and health institutions and the number of TCM medical and health institutions in China were 767239,1328752 and 65809 respectively, an increase of 57.10 percent over 2012,211.23 percent over 2009 and 1979.93 percent over 2009. In 2019,seven provinces, including Sichuan, Guangdong and Shandong, ranked first in terms of the number of TCM personnel in China, while eight provinces, including Shandong, Henan and Sichuan, ranked first in terms of the number of TCM medical institutions, and Shandong, Sichuan and Guangdong ranked first in terms of TCM medical institutions. In general, the geographical distribution of TCM personnel, beds in TCM medical institutions and TCM medical institutions in each province is basically the same, and there is an obvious gap between TCM health resources in central and eastern China and that in western China, presenting a polarization.","PeriodicalId":331570,"journal":{"name":"2021 International Conference on Management Science and Software Engineering (ICMSSE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124551431","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

The Influence of Tourists' Experience Quality on Loyalty of Baotu Spring Scenic Spot on SPSS 24 Software 利用SPSS 24软件研究游客体验质量对包图温泉景区忠诚度的影响

2021 International Conference on Management Science and Software Engineering (ICMSSE) Pub Date : 2021-07-01 DOI: 10.1109/ICMSSE53595.2021.00045

Yan Li, Xiao Zhou

引用次数: 0

Research and Design of L-Band High Power Miniaturized N-Channel Power Synthesizer l波段大功率小型化n通道功率合成器的研究与设计

2021 International Conference on Management Science and Software Engineering (ICMSSE) Pub Date : 2021-07-01 DOI: 10.1109/ICMSSE53595.2021.00037

Daoling Shi, Ling Yao, Yizhi Zhu, Mingming Wang, Jing Wang, Xiaofei Peng

引用次数: 0

Research on demand management of spare parts replenishment purchase for Power Grid Companies based on the maximum failure probability method 基于最大失效概率法的电网公司备件补充采购需求管理研究

2021 International Conference on Management Science and Software Engineering (ICMSSE) Pub Date : 2021-07-01 DOI: 10.1109/ICMSSE53595.2021.00062

He Shixuan, Liu Zhiwei, Yang Chen, He Xiaodong, Zhang Jia, Zhao Shuai

引用次数: 0

Evaluation of credit risk on pharmaceutical supply chain finance based on KMV model 基于KMV模型的医药供应链金融信用风险评价

2021 International Conference on Management Science and Software Engineering (ICMSSE) Pub Date : 2021-07-01 DOI: 10.1109/ICMSSE53595.2021.00030

Yixin Dou, Zi Ye

{"title":"Evaluation of credit risk on pharmaceutical supply chain finance based on KMV model","authors":"Yixin Dou, Zi Ye","doi":"10.1109/ICMSSE53595.2021.00030","DOIUrl":"https://doi.org/10.1109/ICMSSE53595.2021.00030","url":null,"abstract":"During the period of the epidemic, uncertain factors intensified the problem of credit risk in the pharmaceutical supply chain. This paper selects the stock data of 292 listed companies in the nodes of the pharmaceutical supply chain from January 20, 2020 to January 19, 2021 and uses Python software and KMV model for quantitative research. Then it obtains that the average expected default frequencies of supplier class, core manufacturing class, pharmaceutical circulation class and logistics class are 7.57%,4.59%,5.73%and 0.39% respectively. The average default distances of traditional Chinese medicine industry, chemical pharmacy industry, biological product industry, medical device industry, medical service industry and pharmaceutical business industry are 2.4363, 2.0418, 1.9911, 1.9006, 1.8341 and 1.4070 respectively. The results show that the default probability of core manufacturing enterprises is higher than that of logistics enterprises and lower than that of upstream and downstream enterprises and there is a certain gap in the credit quality of various industries in both pharmaceutical core manufacturing class and pharmaceutical circulation class.","PeriodicalId":331570,"journal":{"name":"2021 International Conference on Management Science and Software Engineering (ICMSSE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129978623","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 market-oriented business insights from the perspective of improving quality and efficiency based on quantitative analysis 基于定量分析的提质增效视角下的市场化商业洞察研究

2021 International Conference on Management Science and Software Engineering (ICMSSE) Pub Date : 2021-07-01 DOI: 10.1109/ICMSSE53595.2021.00015

Lu Liu, Chuanping Zhang

引用次数: 0

Study on Image recognition based on computer visual angle point detection 基于计算机视角点检测的图像识别研究

2021 International Conference on Management Science and Software Engineering (ICMSSE) Pub Date : 2021-07-01 DOI: 10.1109/ICMSSE53595.2021.00014

S. Zhou

引用次数: 0

A Web Simulation Training System for Earthquake Intensity Assessment and Disaster Damage Evaluation 地震烈度评估与灾害损失评估Web模拟训练系统

2021 International Conference on Management Science and Software Engineering (ICMSSE) Pub Date : 2021-07-01 DOI: 10.1109/ICMSSE53595.2021.00041

Zhu Damiao, Wang Dongming

{"title":"A Web Simulation Training System for Earthquake Intensity Assessment and Disaster Damage Evaluation","authors":"Zhu Damiao, Wang Dongming","doi":"10.1109/ICMSSE53595.2021.00041","DOIUrl":"https://doi.org/10.1109/ICMSSE53595.2021.00041","url":null,"abstract":"A quick, accurate and comprehensive grasp of the damages of the disaster-stricken area after the earthquakes and a timely release of earthquake intensity maps are of great value for planning of emergency rescue initiatives, post-disaster reconstruction, earthquake prevention and disaster relief. To make the earthquake intensity assessment, disaster damage investigation and evaluation more timely, scientific and accurate, this study proposed a simulation training system for earthquake intensity assessment and disaster damage evaluation. Through computer technologies, Web technique, and database technologies, the actual earthquake disaster scenarios were simulated for earthquake rescue workers so that they could perform earthquake intensity assessment and disaster damage investigations through the Internet in a virtual manner. The proposed system would not only provide a set of new training modes for rescue workers, but also improve the emergency training, and enhance the overall quality of the disaster evaluation team. It could increase the fidelity of training and raise the tensity for training, test the rationality of the content and procedures of disaster evaluation, effectively assess the details of disaster evaluation, which could help the rescue team better fulfill on-site earthquake evaluation and disaster damage evaluation in the future.","PeriodicalId":331570,"journal":{"name":"2021 International Conference on Management Science and Software Engineering (ICMSSE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131964897","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

High Resolution Remote Sensing Image Classification Based on Deep Learning U-Net Model 基于深度学习U-Net模型的高分辨率遥感图像分类

2021 International Conference on Management Science and Software Engineering (ICMSSE) Pub Date : 2021-07-01 DOI: 10.1109/ICMSSE53595.2021.00012

Chengye Li, Hao Bai

{"title":"High Resolution Remote Sensing Image Classification Based on Deep Learning U-Net Model","authors":"Chengye Li, Hao Bai","doi":"10.1109/ICMSSE53595.2021.00012","DOIUrl":"https://doi.org/10.1109/ICMSSE53595.2021.00012","url":null,"abstract":"The higher the resolution, the clearer the content of the image will be. With the continuous improvement of remote sensing image(RSI) resolution in recent years, the detailed information contained in the image becomes clearer and richer, which is an important breakthrough for remote sensing research. Deep learning U-Net model(DLUM) can build training model from shallow level to deep level in data learning, increase model training parameters, and guide classification decision more efficiently and accurately. This paper studies the classification method of high-resolution RSI based on DLUM, which can reduce the network computing time, improve the classification accuracy, and then improve the classification results of high-resolution RSI. This paper designs the DLUM, understands the high-resolution RSI solution of u-net model classification, and preprocesss the experimental high-resolution remote sensing data. Firstly, the experiment carries on coordinate system transformation and visualization processing, then normalizes the data, then enhances the data by some image processing methods, and finally transforms the data into mask to express the characteristics of each kind of figure. This paper studies the advantages of the high-resolution RSI classification method based on DLUM through experiments, and compares it with the traditional RSI classification method intuitively through chart analysis method to analyze its accuracy. The experimental results show that the classification method of high-resolution RSI which is added by DLUM has obvious superiority. On the ground samples, the accuracy of high-resolution RSI classification of basic DLUM is 89.10%, while the accuracy of traditional classification method is 79.80%.","PeriodicalId":331570,"journal":{"name":"2021 International Conference on Management Science and Software Engineering (ICMSSE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133142788","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

Research on ISO's Impact Evaluation Based on Factor Analysis 基于因子分析的ISO影响评价研究

2021 International Conference on Management Science and Software Engineering (ICMSSE) Pub Date : 2021-07-01 DOI: 10.1109/ICMSSE53595.2021.00052

Yunpeng Chen, Feng Qing, Haozhan Li

引用次数: 0