In our recent work on concatenative speech synthesis, we have devised an efficient, graph-based search to perform unit selection given symbolic information. By encapsulating concatenation and substitution costs defined at the class level, the graph expands only linearly with respect to corpus size. To date, these costs were manually tuned over pre-specified classes, which was a knowledgeintensi...

In least squares, least absolute deviations, and even generalized M-estimation, outlying observations sometimes strongly influence the estimation result, masking an important and interesting relationship existing in the majority of observations. The S-estimators are a class of estimators that overcome this difficulty by smoothly downweighting outliers in fitting regression functions to data. In...

in recent years, supplier evaluation and selection, an important element in supply chain management, has been gaining attention in both academic literature and industrial practice. the mixed integer multi-objective non-linear programming model (mimonlp) presented in this paper aimed to evaluate and select the appropriate set of suppliers considering quantitative and qualitative criteria and in ...

contractor selection is one of the most important problem in supply chain and itsstrongly effect on firm`s performance. because a significant amount of auniversity`s budget assigns to construction contracts, contractor selection is animportant problem for the financial status of universities. since contractor selectionis a multi-criteria decision making problem (mcdm), lots of methods proposed ...

objective(s): this study addresses feature selection for breast cancer diagnosis. the present process uses a wrapper approach using ga-based on feature selection and ps-classifier. the results of experiment show that the proposed model is comparable to the other models on wisconsin breast cancer datasets. materials and methods: to evaluate effectiveness of proposed feature selection method, we ...

Objective(s): This study addresses feature selection for breast cancer diagnosis. The present process uses a wrapper approach using GA-based on feature selection and PS-classifier. The results of experiment show that the proposed model is comparable to the other models on Wisconsin breast cancer datasets. Materials and Methods: To evaluate effectiveness of proposed feature selection method, we ...