Chung Yuan Christian University

About: Chung Yuan Christian University is a education organization based out in Taoyuan City, Taiwan. It is known for research contribution in the topics: Membrane & Fuzzy logic. The organization has 9819 authors who have published 11623 publications receiving 213139 citations. The organization is also known as: Tiong-gôan-tāi-ha̍k & CYCU.

SVM and SVM Ensembles in Breast Cancer Prediction.

Abstract: Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.

Densities and refractive indices of the deep eutectic solvents (choline chloride + ethylene glycol or glycerol) and their aqueous mixtures at the temperature ranging from 298.15 to 333.15 K

Abstract: Deep eutectic solvents (DES) are new emerging alternatives to conventional ionic liquids that may find a number of interesting applications in industrial and chemical processes. In this study, the densities, ρ, and refractive indices, nD, of the DESs (choline chloride + ethylene glycol) and (choline chloride + glycerol) and their aqueous mixtures were investigated at atmospheric pressure over the temperature range 298.15–333.15 K and across a complete composition range. The excess molar volumes, VE, and refractive index deviations, ΔnD, were also calculated from experimental results. The calculated excess molar volumes were negative at all temperatures over the entire range of composition considered, suggesting the presence of strong interactions between water and the DES in the mixtures. The refractive index deviations, on the other hand, were found positive in the entire concentration range. The calculated properties were fitted to a Redlich–Kister type equation to correlate them to the temperature and composition. The correlations used satisfactorily represent the densities and refractive indices of the pure DESs and their aqueous binary mixtures as functions of temperature and composition as indicated by the low overall average absolute deviations obtained in the calculations.

Lean supply chain and its effect on product cost and quality: a case study on Ford Motor Company

Abstract: Purpose – The purpose of this paper is to address “how Toyota can continuously and consistently achieve its dramatic success through its competences ‐ continuous waste elimination and the objective of long term philosophy”; the paper aims to summarize some solid suggestions and comprehensive ideas for those industries planning to implement lean production.Design/methodology/approach – The methodology used is the case based approach (CBA), which described lean supply chain (LSC) through value stream mapping (VSM) using a case study from the Ford Motor Company in Chung Li, Taiwan. The paper follows a four‐step problem solving process to demonstrate how lean supply chain affects product cost and quality.Findings – Using VSM case study to demonstrate LSC, all the measurable indices helpful for cost reduction, quality enhancement and lead time reduction are shown. The paper also provides some recommendations and basic principles to implement VSM successfully through P‐D‐C‐A improving cycle.Research limitations...