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Microarray gene expression data usually have a large number of dimensions, e.g., over ten thousand genes, and a small number of samples, e.g., a few tens of patients. In this paper, we use the support vector machine (SVM) for cancer classification with microarray data. Dimensionality reduction methods, such as principal components analysis (PCA),(More)
In this paper, we argue that for a C-class classification problem, C 2-class classifiers, each of which discriminating one class from the other classes and having a characteristic input feature subset, should in general outperform, or at least match the performance of, a C-class classifier with one single input feature subset. For each class, we select a(More)
Batch deterministic and stochastic Petri nets are introduced as a tool for modeling and performance evaluation of supply chains. The new model is developed by enhancing deterministic and stochastic Petri nets (DSPNs) with batch places and batch tokens. By incorporating stochastic Petri nets (SPNs) with the batch features, inhibitor arcs, and(More)
Protein kinase C (PKC) is a family of ten isozymes that play distinct and in some cases opposing roles in cell growth and survival. We recently reported that diamide, a diazene carbonyl derivative which oxidizes thiols to disulfides through addition/displacement reactions at the diazene bond, induces potent GSH-dependent inactivation of several PKC(More)
One hundred thirteen evaluable patients with previously untreated stage III breast carcinoma were treated with three monthly cycles of cyclophosphamide (CYC), doxorubicin (DOX), 5-fluorouracil (5-FU), vincristine (VCR), and prednisone (PRED) (CAFVP). Subsequently, 91 (81%) were deemed operable. Patients were then randomized to receive surgery or(More)
It is a great challenge to find efficient tools for shortterm scheduling of oil refinery processes. Although some, theoretical advancement has been made in this field, a gap between theory and applications exists. In practice, the short-term scheduling job of oil refinery processes is still done manually by planners, because of the lack of such tools. This(More)
Accurate classification of cancers based on microarray gene expressions is very important for doctors to choose a proper treatment. In this paper, we apply a novel radial basis function (RBF) neural network that allows for large overlaps among the hidden kernels of the same class to this problem. We tested our RBF network in three data sets, i.e., the(More)