Applied Mathematics-A Journal of Chinese Universities Series B最新文献_第10页

Laguerre reproducing kernel method in Hilbert spaces for unsteady stagnation point flow over a stretching/shrinking sheet 非定常滞止点流动的Hilbert空间中的Laguerre再现核方法

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2021-09-20 DOI: 10.1007/s11766-021-3761-2

M. R. Foroutan, A. S. Gholizadeh, Sh. Najafzadeh, R. H. Haghi

引用次数: 0

On complete convergence in Marcinkiewicz-Zygmund type SLLN for random variables 关于随机变量Marcinkiewicz-Zygmund型SLLN的完全收敛性

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2021-09-20 DOI: 10.1007/s11766-021-3816-4

Anna Kuczmaszewska, Ji-gao Yan

引用次数: 4

Fractal interpolation: a sequential approach 分形插值：一种顺序方法

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2021-09-20 DOI: 10.1007/s11766-021-3635-7

N. Vijender, M. A. Navascués

引用次数: 0

A multiplicative Gauss-Newton minimization algorithm: Theory and application to exponential functions 一种乘法高斯-牛顿最小化算法:理论及其在指数函数中的应用

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2021-09-20 DOI: 10.1007/s11766-021-3814-6

Anmol Gupta, Sanjay Kumar

{"title":"A multiplicative Gauss-Newton minimization algorithm: Theory and application to exponential functions","authors":"Anmol Gupta, Sanjay Kumar","doi":"10.1007/s11766-021-3814-6","DOIUrl":"10.1007/s11766-021-3814-6","url":null,"abstract":"<div><p>Multiplicative calculus (MUC) measures the rate of change of function in terms of ratios, which makes the exponential functions significantly linear in the framework of MUC. Therefore, a generally non-linear optimization problem containing exponential functions becomes a linear problem in MUC. Taking this as motivation, this paper lays mathematical foundation of well-known classical Gauss-Newton minimization (CGNM) algorithm in the framework of MUC. This paper formulates the mathematical derivation of proposed method named as multiplicative Gauss-Newton minimization (MGNM) method along with its convergence properties. The proposed method is generalized for <i>n</i> number of variables, and all its theoretical concepts are authenticated by simulation results. Two case studies have been conducted incorporating multiplicatively-linear and non-linear exponential functions. From simulation results, it has been observed that proposed MGNM method converges for 12972 points, out of 19600 points considered while optimizing multiplicatively-linear exponential function, whereas CGNM and multiplicative Newton minimization methods converge for only 2111 and 9922 points, respectively. Furthermore, for a given set of initial value, the proposed MGNM converges only after 2 iterations as compared to 5 iterations taken by other methods. A similar pattern is observed for multiplicatively-non-linear exponential function. Therefore, it can be said that proposed method converges faster and for large range of initial values as compared to conventional methods.</p></div>","PeriodicalId":55568,"journal":{"name":"Applied Mathematics-A Journal of Chinese Universities Series B","volume":"36 3","pages":"370 - 389"},"PeriodicalIF":0.0,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11766-021-3814-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46990594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Degree sum conditions for hamiltonian index 哈密顿指标的度和条件

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2021-09-20 DOI: 10.1007/s11766-021-3885-4

Ze-meng Liu, Li-ming Xiong

引用次数: 1

The rate of convergence on fractional power dissipative operator on some sobolev type spaces 一类sobolev型空间上分数阶幂耗散算子的收敛速度

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2021-09-20 DOI: 10.1007/s11766-021-3901-8

Zhen-bin Cao, Meng Wang

引用次数: 0

Parametric estimation for the simple linear regression model under moving extremes ranked set sampling design 移动极值排序集抽样设计下简单线性回归模型的参数估计

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2021-06-18 DOI: 10.1007/s11766-021-3993-1

Dong-sen Yao, Wang-xue Chen, Chun-xian Long

引用次数: 4

Automatic liver and tumor segmentation based on deep learning and globally optimized refinement 基于深度学习和全局优化细化的肝脏和肿瘤自动分割

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2021-06-18 DOI: 10.1007/s11766-021-4376-3

Yuan Hong, Xiong-wei Mao, Qing-lei Hui, Xiao-ping Ouyang, Zhi-yi Peng, De-xing Kong

{"title":"Automatic liver and tumor segmentation based on deep learning and globally optimized refinement","authors":"Yuan Hong, Xiong-wei Mao, Qing-lei Hui, Xiao-ping Ouyang, Zhi-yi Peng, De-xing Kong","doi":"10.1007/s11766-021-4376-3","DOIUrl":"10.1007/s11766-021-4376-3","url":null,"abstract":"<div><p>Automatic segmentation of the liver and hepatic lesions from abdominal 3D computed tomography (CT) images is fundamental tasks in computer-assisted liver surgery planning. However, due to complex backgrounds, ambiguous boundaries, heterogeneous appearances and highly varied shapes of the liver, accurate liver segmentation and tumor detection are still challenging problems. To address these difficulties, we propose an automatic segmentation framework based on 3D U-net with dense connections and globally optimized refinement. Firstly, a deep U-net architecture with dense connections is trained to learn the probability map of the liver. Then the probability map goes into the following refinement step as the initial surface and prior shape. The segmentation of liver tumor is based on the similar network architecture with the help of segmentation results of liver. In order to reduce the influence of the surrounding tissues with the similar intensity and texture behavior with the tumor region, during the training procedure, <i>I</i> × <i>liver</i><sub><i>label</i></sub> is the input of the network for the segmentation of liver tumor. By doing this, the accuracy of segmentation can be improved. The proposed method is fully automatic without any user interaction. Both qualitative and quantitative results reveal that the proposed approach is efficient and accurate for liver volume estimation in clinical application. The high correlation between the automatic and manual references shows that the proposed method can be good enough to replace the time-consuming and non-reproducible manual segmentation method.</p></div>","PeriodicalId":55568,"journal":{"name":"Applied Mathematics-A Journal of Chinese Universities Series B","volume":"36 2","pages":"304 - 316"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s11766-021-4376-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50036283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Rearrangement and the weighted logarithmic Sobolev inequality 重排与加权对数Sobolev不等式

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2021-06-18 DOI: 10.1007/s11766-021-3755-z

Ming-hong Jiang, Jian-miao Ruan, Xiang-rong Zhu

引用次数: 0

Central limit theorem for linear processes generated by IID random variables under the sub-linear expectation 次线性期望下IID随机变量生成的线性过程的中心极限定理

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2021-06-18 DOI: 10.1007/s11766-021-3882-7

Wei Liu, Yong Zhang

引用次数: 15