STUDY OBJECTIVES To assess whether changes in psychomotor vigilance during sleep deprivation can be estimated using heart rate variability (HRV). DESIGN HRV, ocular, and electroencephalogram (EEG) measures were compared for their ability to predict lapses on the Psychomotor Vigilance Task (PVT). SETTING Chronobiology and Sleep Laboratory, Duke-NUS Graduate Medical School Singapore. PARTIC...

we used various screening techniques, clustering, decision tree and generalized rule induction (association) (gri) models and molecular phylogenic relationship to search for patterns of halophi-licy and to find features contribute to halolysin salt stability. we found met was the sole n-terminal amino acid in halolysin proteins, whereas other amino acids found at this position of oth-er proteas...

in this study, a prediction model based on support vector machines (svm) improved by introducing a volume weighted penalty function to the model was introduced to increase the accuracy of forecasting short term trends on the stock market to develop the optimal trading strategy. along with vw-svm classifier, a hybrid feature selection method was used that consisted of f-score as the filter part ...

Effective features can improve the performance of a model and help us understand characteristics underlying structure complex data. Previously proposed feature selection methods usually cannot retain more discriminative information. To address this shortcoming, we propose novel supervised orthogonal least square regression with weighting for selection. The optimization problem objective functio...

Introduction: Visual evoked potentials contain certain diagnostic information which have proved to be of importance in the visual systems functional integrity. Due to substantial decrease of amplitude in extra macular stimulation in commonly used pattern VEPs, differentiating normal and abnormal signals can prove to be quite an obstacle. Due to developments of use of machine l...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

land cover classification is one of the most important applications of polarimetric radar images, especially in urban areas. there are numerous features that can be extracted from these images for the use of their high potential, hence feature selection plays an important role in polsar image classification. in this study, three main steps are used to improve the classification: 1) feature extr...