Search

Your search keyword '"Chen, Wan‐Ping"' showing total 327 results
Start Over Author "Chen, Wan‐Ping"
327 results on '"Chen, Wan‐Ping"'

2. Determination of class-specific variables in nonparametric multiple-class classification

Author

Chen, Wan-Ping Nicole and Chang, Yuan-chin Ivan

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Computation, Statistics - Methodology
Abstract

As technology advanced, collecting data via automatic collection devices become popular, thus we commonly face data sets with lengthy variables, especially when these data sets are collected without specific research goals beforehand. It has been pointed out in the literature that the difficulty of high-dimensional classification problems is intrinsically caused by too many noise variables useless for reducing classification error, which offer less benefits for decision-making, and increase complexity, and confusion in model-interpretation. A good variable selection strategy is therefore a must for using such kinds of data well; especially when we expect to use their results for the succeeding applications/studies, where the model-interpretation ability is essential. hus, the conventional classification measures, such as accuracy, sensitivity, precision, cannot be the only performance tasks. In this paper, we propose a probability-based nonparametric multiple-class classification method, and integrate it with the ability of identifying high impact variables for individual class such that we can have more information about its classification rule and the character of each class as well. The proposed method can have its prediction power approximately equal to that of the Bayes rule, and still retains the ability of "model-interpretation." We report the asymptotic properties of the proposed method, and use both synthesized and real data sets to illustrate its properties under different classification situations. We also separately discuss the variable identification, and training sample size determination, and summarize those procedures as algorithms such that users can easily implement them with different computing languages.

Published
2022

7. Fast Multi-Class Probabilistic Classifier by Sparse Non-parametric Density Estimation

Author

Chen, Wan-Ping Nicole and Chang, Yuan-chin Ivan

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

The model interpretation is essential in many application scenarios and to build a classification model with a ease of model interpretation may provide useful information for further studies and improvement. It is common to encounter with a lengthy set of variables in modern data analysis, especially when data are collected in some automatic ways. This kinds of datasets may not collected with a specific analysis target and usually contains redundant features, which have no contribution to a the current analysis task of interest. Variable selection is a common way to increase the ability of model interpretation and is popularly used with some parametric classification models. There is a lack of studies about variable selection in nonparametric classification models such as the density estimation-based methods and this is especially the case for multiple-class classification situations. In this study we study multiple-class classification problems using the thought of sparse non-parametric density estimation and propose a method for identifying high impacts variables for each class. We present the asymptotic properties and the computation procedure for the proposed method together with some suggested sample size. We also repost the numerical results using both synthesized and some real data sets.

Published
2019

13. The Cerebral Protective Effect of Novel Erinacines from Hericium erinaceus Mycelium on In Vivo Mild Traumatic Brain Injury Animal Model and Primary Mixed Glial Cells via Nrf2-Dependent Pathways

Author

Lee, Kam-Fai, primary, Hsieh, Yung-Yu, additional, Tung, Shui-Yi, additional, Teng, Chih-Chuan, additional, Cheng, Kung-Chuan, additional, Hsieh, Meng-Chiao, additional, Huang, Cheng-Yi, additional, Lee, Ko-Chao, additional, Lee, Li-Ya, additional, Chen, Wan-Ping, additional, Chen, Chin-Chu, additional, and Kuo, Hsing-Chun, additional

Published
2024
Full Text
View/download PDF

17. Insights into Anion‐Solvent Interactions to Boost Stable Operation of Ether‐Based Electrolytes in Pure‐SiOx||LiNi0.8Mn0.1Co0.1O2 Full Cells

Author

Tian, Yi‐Fan, primary, Tan, Shuang‐Jie, additional, Lu, Zhuo‐Ya, additional, Xu, Di‐Xin, additional, Chen, Han‐Xian, additional, Zhang, Chao‐Hui, additional, Zhang, Xu‐Sheng, additional, Li, Ge, additional, Zhao, Yu‐Ming, additional, Chen, Wan‐Ping, additional, Xu, Quan, additional, Wen, Rui, additional, Zhang, Juan, additional, and Guo, Yu‐Guo, additional

Published
2023
Full Text
View/download PDF

22. Bayesian Variable Selection for Multi-response Linear Regression

Author

Chen, Wan-Ping, Wu, Ying Nian, Chen, Ray-Bin, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, Series editor, Tanaka, Yuzuru, Series editor, Wahlster, Wolfgang, Series editor, Siekmann, Jörg, Series editor, Cheng, Shin-Ming, editor, and Day, Min-Yuh, editor

Published
2014
Full Text
View/download PDF

23. Insights into Anion‐Solvent Interactions to Boost Stable Operation of Ether‐Based Electrolytes in Pure‐SiOx||LiNi0.8Mn0.1Co0.1O2 Full Cells.

Author

Tian, Yi‐Fan, Tan, Shuang‐Jie, Lu, Zhuo‐Ya, Xu, Di‐Xin, Chen, Han‐Xian, Zhang, Chao‐Hui, Zhang, Xu‐Sheng, Li, Ge, Zhao, Yu‐Ming, Chen, Wan‐Ping, Xu, Quan, Wen, Rui, Zhang, Juan, and Guo, Yu‐Guo

Subjects
ELECTROLYTES, DIPOLE moments, PERMITTIVITY, LITHIUM-ion batteries, SOLID electrolytes, FLUOROETHYLENE
Abstract

Ether solvents with superior reductive stability promise excellent interphasial stability with high‐capacity anodes while the limited oxidative resistance hinders their high‐voltage operation. Extending the intrinsic electrochemical stability of ether‐based electrolytes to construct stable‐cycling high‐energy‐density lithium‐ion batteries is challenging but rewarding. Herein, the anion‐solvent interactions were concerned as the key point to optimize the anodic stability of the ether‐based electrolytes and an optimized interphase was realized on both pure‐SiOx anodes and LiNi0.8Mn0.1Co0.1O2 cathodes. Specifically, the small‐anion‐size LiNO3 and tetrahydrofuran with high dipole moment to dielectric constant ratio realized strengthened anion‐solvent interactions, which enhance the oxidative stability of the electrolyte. The designed ether‐based electrolyte enabled a stable cycling performance over 500 cycles in pure‐SiOx||LiNi0.8Mn0.1Co0.1O2 full cell, demonstrating its superior practical prospects. This work provides new insight into the design of new electrolytes for emerging high‐energy density lithium‐ion batteries through the regulation of interactions between species in electrolytes. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

24. Mitigating Electron Leakage of Solid Electrolyte Interface for Stable Sodium‐Ion Batteries

Author

Wang, Enhui, primary, Wan, Jing, additional, Guo, Yu‐Jie, additional, Zhang, Qianyu, additional, He, Wei‐Huan, additional, Zhang, Chao‐Hui, additional, Chen, Wan‐Ping, additional, Yan, Hui‐Juan, additional, Xue, Ding‐Jiang, additional, Fang, Tiantian, additional, Wang, Fuyi, additional, Wen, Rui, additional, Xin, Sen, additional, Yin, Ya‐Xia, additional, and Guo, Yu‐Guo, additional

Published
2022
Full Text
View/download PDF

25. Revealing the High Salt Concentration Manipulated Evolution Mechanism on the Lithium Anode in Quasi‐Solid‐State Lithium‐Sulfur Batteries

Author

Liu, Gui‐Xian, primary, Tian, Jian‐Xin, additional, Wan, Jing, additional, Li, Yuan, additional, Shen, Zhen‐Zhen, additional, Chen, Wan‐Ping, additional, Zhao, Yao, additional, Wang, Fuyi, additional, Liu, Bing, additional, Xin, Sen, additional, Guo, Yu‐Guo, additional, and Wen, Rui, additional

Published
2022
Full Text
View/download PDF

29. Synthesis of BiOCl/C/g-C3N4 Z-scheme heterojunction: mercury lamp-driven heterojunction for efficient degradation of phenol.

Author

Song, Kai, Chen, Wan-ping, Wang, Run-quan, Zhang, Yue-rong, Tian, Yuan, Li, Jia-xian, Wang, Guo-ying, and Shi, Gao-feng

Subjects
*HETEROJUNCTIONS, *ELECTRON-hole recombination, *PHENOL, *MERCURY, *CHARGE carriers
Abstract

Designing photocatalysts to remove organic pollutants are of great significance in the environmental field. Herein, BiOCl/C/g-C3N4 photocatalyst was synthesized with biochar, BiOCl, and g-C3N4. Biochar was first used as an electronic medium to accelerate charge carrier separation. Moreover, the formation of the built-in electric field between BiOCl and g-C3N4 interface inhibits the electron–hole recombination during the photocatalytic process. The characterization results show that the Z-scheme heterojunction structure was successfully prepared. The BiOCl(0.5)C(0.03)g-C3N4(0.97) photocatalyst had up to 96.9% degradation of phenol under mercury lamp irradiation. The rate constant of the photodegradation reaction process is 0.38706 h−1, which is 2.1 times that of pure BiOCl. And photocatalyst has satisfactory stability, which a three-cycle retention rate was 97.6%. In addition, the reaction mechanism was studied, and the photogenerated carrier transferring pathways of BiOCl/C/g-C3N4 Z-scheme photocatalysts were proposed. The photocatalyst offers new ideas for the Z-scheme heterojunction photocatalyst. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

32. Mitigating Electron Leakage of Solid Electrolyte Interface for Stable Sodium‐Ion Batteries.

Author

Wang, Enhui, Wan, Jing, Guo, Yu‐Jie, Zhang, Qianyu, He, Wei‐Huan, Zhang, Chao‐Hui, Chen, Wan‐Ping, Yan, Hui‐Juan, Xue, Ding‐Jiang, Fang, Tiantian, Wang, Fuyi, Wen, Rui, Xin, Sen, Yin, Ya‐Xia, and Guo, Yu‐Guo

Subjects
SOLID electrolytes, ELECTRON work function, LEAKAGE, ELECTRONS, INTERFACE stability, IONIC conductivity, SODIUM ions
Abstract

The interfacial stability is highly responsible for the longevity and safety of sodium ion batteries (SIBs). However, the continuous solid‐electrolyte interphase(SEI) growth would deteriorate its stability. Essentially, the SEI growth is associated with the electron leakage behavior, yet few efforts have tried to suppress the SEI growth, from the perspective of mitigating electron leakage. Herein, we built two kinds of SEI layers with distinct growth behaviors, via the additive strategy. The SEI physicochemical features (morphology and componential information) and SEI electronic properties (LUMO level, band gap, electron work function) were investigated elaborately. Experimental and calculational analyses showed that, the SEI layer with suppressed growth delivers both the low electron driving force and the high electron insulation ability. Thus, the electron leakage is mitigated, which restrains the continuous SEI growth, and favors the interface stability with enhanced electrochemical performance. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

34. An Air‐Stable High‐Nickel Cathode with Reinforced Electrochemical Performance Enabled by Convertible Amorphous Li 2 CO 3 Modification

Author

Sheng, Hang, primary, Meng, Xin‐Hai, additional, Xiao, Dong‐Dong, additional, Fan, Min, additional, Chen, Wan‐Ping, additional, Wan, Jing, additional, Tang, Jilin, additional, Zou, Yu‐Gang, additional, Wang, Fuyi, additional, Wen, Rui, additional, Shi, Ji‐Lei, additional, and Guo, Yu‐Guo, additional

Published
2022
Full Text
View/download PDF

41. Bayesian Method for Support Union Recovery in Multivariate Multi-Response Linear Regression

Author

Chen, Wan-Ping

Subjects
Statistics, Bayesian, Multi-response Linear Regression, Multi-task Learning, Support Union Recovery
Abstract

Sparse modeling has become a particularly important and quickly developing topic in many applications of statistics, machine learning, and signal processing. The main objective of sparse modeling is discovering a small number of predictive patterns that would improve our understanding of the data. This paper extends the idea of sparse modeling to the variable selection problem in high dimensional linear regression, where there are multiple response vectors, and they share the same or similar subsets of predictor variables to be selected from a large set of candidate variables. In the literature, this problem is called multi-task learning, support union recovery or simultaneous sparse coding in different contexts.We present a Bayesian method for solving this problem by introducing two nested sets of binary indicator variables. In the first set of indicator variables, each indicator is associated with a predictor variable or a regressor, indicating whether this variable is active for any of the response vectors. In the second set of indicator variables, each indicator is associated with both a predicator variable and a response vector, indicating whether this variable is active for the particular response vector. The problem of variable selection is solved by sampling from the posterior distributions of the two sets of indicator variables. We develop a Gibbs sampling algorithm for posterior sampling and use the generated samples to identify active support both in shared and individual level. Theoretical and simulation justification are performed in the paper.The proposed algorithm is also demonstrated on the real image data sets. To learn the patterns of the object in images, we treat images as the different tasks. Through combining images with the object in the same category, we cannot only learn the shared patterns efficiently but also get individual sketch of each image.

Published
2015

48. Apoptotic mechanisms of gastric cancer cells induced by isolated erinacine S through epigenetic histone H3 methylation of FasL and TRAIL

Author

Tung, Shui-Yi, primary, Lee, Ko-Chao, additional, Lee, Kam-Fai, additional, Yang, Ya-Ling, additional, Huang, Wen-Shih, additional, Lee, Li-Ya, additional, Chen, Wan-Ping, additional, Chen, Chin-Chu, additional, Teng, Chih-Chuan, additional, Shen, Chien-Heng, additional, Hsieh, Meng-Chiao, additional, Huang, Cheng-Yi, additional, Sheen, Jiunn-Ming, additional, and Kuo, Hsing-Chun, additional

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results