background: numerous studies used microarray gene expression data to extract metastasis-driving gene signatures for the prediction of breast cancer relapse. however, the accuracy and generality of the previously introduced biomarkers are not acceptable for reliable usage in independent datasets. this inadequacy is attributed to ignoring gene interactions by simple feature selection methods, due...

Sediment transport constantly influences river and civil structures and the lack ofinformation about its exact amount makes management efforts less effective. Hence,achieving a proper procedure to estimate the sediment load in rivers is important. We usedsupport vector machine model to estimate the sediments of the Kakareza River in LorestanProvince and the results were compared with those obta...

Background: Multiple sclerosis (MS) is a degenerative inflammatory disease which is most commonly diagnosed by magnetic resonance imaging (MRI). But, since the MRI device uses of a magnetic field, if there are metal objects in the patient's body, it can disrupt the health of the patient, the functioning of the MRI, and distortion in the images. Due to limitations of using MRI device, screening ...

In this paper, using a personal computer (PC), the practical implementation of scalar and vector control methods on a three–phase rotor surface- type permanent magnet synchronous machine drive is discussed. Based on the machine dynamic equations and the above control strategies, two block diagrams are presented first for closed-loop speed controlling of the machine drive/system. Then, the desig...

monitoring and controlling air quality parameters form an important subject of atmospheric and environmental research today due to the health impacts caused by the different pollutants present in the urban areas. the support vector machine (svm), as a supervised learning analysis method, is considered an effective statistical tool for the prediction and analysis of air quality. the work present...

classical lbp such as complexity and high dimensions of feature vectors that make it necessary to apply dimension reduction processes. in this paper, we introduce an improved lbp algorithm to solve these problems that utilizes fast pca algorithm for reduction of vector dimensions of extracted features. in other words, proffer method (fast pca+lbp) is an improved lbp algorithm that is extracted ...

biomedical datasets usually include a large number of features relative to the number of samples. however, some data dimensions may be less relevant or even irrelevant to the output class. selection of an optimal subset of features is critical, not only to reduce the processing cost but also to improve the classification results. to this end, this paper presents a hybrid method of filter and wr...