this study investigates the detection of the drowsiness state for a future application such as in the reduction ofthe road traffic accidents. the electroencephalography(eeg), electrooculography (eog), driving quality (dq), and karolinska sleepiness scale (kss) data of 7 male during approximately 20 hours of sleep deprivation were recorded. to reduce the eye blink artifact, an automatic mechanis...

This paper proposes a feature selection method that combines various feature selection techniques. Feature selection has been realized as one of the most important processes in various applications, especially pattern classification problems. When too many attributes are involved, training a machine to classify patterns into their respective classes is seemingly impossible. Hence, selecting goo...

A common problem in many model-building situations is to choose from a large set of covariates that should be included in the “best” model. An additional consideration in modeling epidemiological data is the inclusion of confounders, which adds a quirk in the modeling procedure in that statistical significance is not the main criteria for keeping predictors in a model. Hosmer and Lemeshow (2000...

In this paper, we perform a cross-linguistic study of prosodic features in sentence segmentation by using two different feature selection approaches: a forward search wrapper and feature filtering. Experiments in Arabic, English, and Mandarin show that prosodic features make significant contributions in all three languages. Feature selection results indicate that feature relevancy can vary grea...

Abs t rac t . In this paper we examine the edge searching problem on pseudo 3-sided solid orthoconvex grids. We obtain a closed formula that expresses the minimum number of searchers required to search a pseudo 3-sided solid orthoconvex grid. From that formula and a rather straight forward algorithm we show that the problem is in P. We obtain a parallel version of that algorithm that places the...

Feature selection, representation and extraction are integral to statistical pattern recognition systems. Usually features are represented as vectors that capture expert knowledge of measurable discriminative properties of the classes to be distinguished. The feature selection process entails manual expert involvement and repeated experiments. Automatic feature selection is necessary when (i) e...

In this paper, two strategies to compute the support sets system for the supervised classifier ALVOT (voting algorithms) using sequential floating selection are presented. ALVOT is a supervised classification model based on the partial precedence principle, therefore, it needs, as feature selection, a set of features subsets, this set is called support sets system. The sequential floating selec...

The continuous growth of the internet has led to use social media for various purposes increase. For instance, some irresponsible parties take advantage comment feature on platforms harm others by providing spam comments shared object. Furthermore, variation creates many features be processed, thereby negatively impacting performance a classification algorithm. Therefore, this study aims solve ...

Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by explo...

Smart physiological sensors embedded in an automobile aaord a novel opportunity to capture naturally occurring episodes of driver stress. In a series of ten ninety minute drives on public roads and highways, electrocardiogram, elec-tromyogram, respiration and skin conductance sensors were used to measure autonomic nervous system activation. The signals were digitized in real time and stored on ...