this paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. in this method, mammograms are segmented into regions of interest (roi) in order to extract features including geometrical and contourlet coefficients. the extracted features benefit from...

In this present paper it deals with the Gender Classification from ECG signal using Least Square Support Vector Machine (LS-SVM) and Support Vector Machine (SVM) Techniques. The different features extracted from ECG signal using Heart Rate Variability (HRV) analysis are the input to the LS-SVM and SVM classifier and at the output the classifier, classifies whether the patient corresponding to r...

background: this paper proposes a new emotional stress assessment system using multi-modal bio-signals. electroencephalogram (eeg) is the reflection of brain activity and is widely used in clinical diagnosis and biomedical research. methods: we design an efficient acquisition protocol to acquire the eeg signals in five channels (fp1, fp2, t3, t4 and pz) and peripheral signals such as blood volu...

estimation of the conceptual costs in construction projects can be regarded as an important issue in feasibility studies. this estimation has a major impact on the success of construction projects. indeed, this estimation supports the required information that can be employed in cost management and budgeting of these projects. the purpose of this paper is to introduce an intelligent model to im...

finding repetitive subsequences in genome is a challengeable problem in bioinformatics research area. a lot of approaches have been proposed to solve the problem, which could be divided to library base and de novo methods. the library base methods use predetermined repetitive genome’s subsequences, where library-less methods attempt to discover repetitive subsequences by analytical approaches. ...

a quantitative structure–activity relationship (qsar) study is suggested for the prediction of biological activity (pic 50 ) of 3, 4-dihydropyrido [3 ,2-d] pyrimidone derivatives as p38 inhibitors. modeling of the biological activities of compounds of interest as a function of molecular structures was established by means of principal component analysis (pca) and least square support vector mac...

Weighted least squares support vector machine (WLSSVM) is a robust version of least squares support vector machine (LS-SVM). It adds weights on error variables to eliminate the influence of outliers. But the weights, which largely depend on the original regression errors from unweighted LS-SVM, might be unreliable for correcting the biased estimation of LS-SVM, especially for the training data ...

support vector regression (svr) solves regression problems based on the concept of support vector machine (svm). in this paper, a new model of svr with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions. using the new proposed method, the optimal hyperplane regression can be obtained by solving a quadrati...