A novel technique of three-dimensional (3D) reconstruction, segmentation, display and analysis of series slices of images including microscopic wide field optical sectioning by deconvolution method, cryo-electron micr...A novel technique of three-dimensional (3D) reconstruction, segmentation, display and analysis of series slices of images including microscopic wide field optical sectioning by deconvolution method, cryo-electron microscope slices by Fou-rier-Bessel synthesis and electron tomography (ET), and a series of computed tomography (CT) was developed to perform si-multaneous measurement on the structure and function of biomedical samples. The paper presents the 3D reconstruction seg-mentation display and analysis results of pollen spore, chaperonin, virus, head, cervical bone, tibia and carpus. At the same time, it also puts forward some potential applications of the new technique in the biomedical realm.展开更多
Storm surges in the Western North Pacific cause significant economic damage and loss of life,highlighting the need for accurate storm surge predictions.This study evaluated four storm surge models:the Global Tide and ...Storm surges in the Western North Pacific cause significant economic damage and loss of life,highlighting the need for accurate storm surge predictions.This study evaluated four storm surge models:the Global Tide and Surge Model(GTSMv3.0),ERA20C neural network(ERA20C_nn),ERA20C multiple linear regression(ERA20C_ml),and 20th Century Reanalysis multiple linear regression(20CR_ml),using data from 160 tidal stations.The results show that the ERA20C_nn model outperformed others,with the highest correlation to tide-gauge observations.The GTSMv3.0 model follows closely,although slightly less accurate.The ERA20C_ml and 20CR_ml models were less effective,especially in predicting extreme surges.The ERA20C_nn model also provided more reliable estimates for 100-year return surge levels,outperforming other models.These findings suggest that neural network-based models,particularly ERA20C_nn,are better suited for assessing coastal flood risks in the region.展开更多
Attribute reduction is necessary in decision making system. Selecting right attribute reduction method is more important. This paper studies the reduction effects of principal components analysis (PCA) and system reco...Attribute reduction is necessary in decision making system. Selecting right attribute reduction method is more important. This paper studies the reduction effects of principal components analysis (PCA) and system reconstruction analysis (SRA) on coronary heart disease data. The data set contains 1723 records, and 71 attributes in each record. PCA and SRA are used to reduce attributes number (less than 71 ) in the data set. And then decision tree algorithms, C4.5, classification and regression tree ( CART), and chi-square automatic interaction detector ( CHAID), are adopted to analyze the raw data and attribute reduced data. The parameters of decision tree algorithms, including internal node number, maximum tree depth, leaves number, and correction rate are analyzed. The result indicates that, PCA and SRA data can complete attribute reduction work,and the decision-making rate on the reduced data is quicker than that on the raw data; the reduction effect of PCA is better than that of SRA, while the attribute assertion of SRA is better than that of PCA. PCA and SRA methods exhibit goodperformance in selecting and reducing attributes.展开更多
In the development research of talent resource, the most important of talent resource forecast and optimization is the structure of talent resource, requirement number and talent quality. The article establish factor ...In the development research of talent resource, the most important of talent resource forecast and optimization is the structure of talent resource, requirement number and talent quality. The article establish factor reconstruction analysis forecast and talent quality model on the method: system reconstruction analysis and ensure most effective factor level in system, which is presented by G.J.Klirti, B.Jonesque. And performing dynamic analysis of example ration.展开更多
文摘A novel technique of three-dimensional (3D) reconstruction, segmentation, display and analysis of series slices of images including microscopic wide field optical sectioning by deconvolution method, cryo-electron microscope slices by Fou-rier-Bessel synthesis and electron tomography (ET), and a series of computed tomography (CT) was developed to perform si-multaneous measurement on the structure and function of biomedical samples. The paper presents the 3D reconstruction seg-mentation display and analysis results of pollen spore, chaperonin, virus, head, cervical bone, tibia and carpus. At the same time, it also puts forward some potential applications of the new technique in the biomedical realm.
基金supported by the National Natural Science Foundation of China(Grant Nos.42176198,42176203)the National Key Research and Development Program of China(Grant No.2023YFC3008200)funding from the Taishan Scholars Program(tsqn202211252)。
文摘Storm surges in the Western North Pacific cause significant economic damage and loss of life,highlighting the need for accurate storm surge predictions.This study evaluated four storm surge models:the Global Tide and Surge Model(GTSMv3.0),ERA20C neural network(ERA20C_nn),ERA20C multiple linear regression(ERA20C_ml),and 20th Century Reanalysis multiple linear regression(20CR_ml),using data from 160 tidal stations.The results show that the ERA20C_nn model outperformed others,with the highest correlation to tide-gauge observations.The GTSMv3.0 model follows closely,although slightly less accurate.The ERA20C_ml and 20CR_ml models were less effective,especially in predicting extreme surges.The ERA20C_nn model also provided more reliable estimates for 100-year return surge levels,outperforming other models.These findings suggest that neural network-based models,particularly ERA20C_nn,are better suited for assessing coastal flood risks in the region.
基金Supported by Ministry of Education of China ( No. 02038) , Asian Research Center of Nankai University ( No. AS0405) , and Tianjin Higher Education Science Development Fund( No. 20030621 ).
文摘Attribute reduction is necessary in decision making system. Selecting right attribute reduction method is more important. This paper studies the reduction effects of principal components analysis (PCA) and system reconstruction analysis (SRA) on coronary heart disease data. The data set contains 1723 records, and 71 attributes in each record. PCA and SRA are used to reduce attributes number (less than 71 ) in the data set. And then decision tree algorithms, C4.5, classification and regression tree ( CART), and chi-square automatic interaction detector ( CHAID), are adopted to analyze the raw data and attribute reduced data. The parameters of decision tree algorithms, including internal node number, maximum tree depth, leaves number, and correction rate are analyzed. The result indicates that, PCA and SRA data can complete attribute reduction work,and the decision-making rate on the reduced data is quicker than that on the raw data; the reduction effect of PCA is better than that of SRA, while the attribute assertion of SRA is better than that of PCA. PCA and SRA methods exhibit goodperformance in selecting and reducing attributes.
文摘In the development research of talent resource, the most important of talent resource forecast and optimization is the structure of talent resource, requirement number and talent quality. The article establish factor reconstruction analysis forecast and talent quality model on the method: system reconstruction analysis and ensure most effective factor level in system, which is presented by G.J.Klirti, B.Jonesque. And performing dynamic analysis of example ration.
