Adaptive MOOCs Based on Intended Learning Outcomes Using Naïve Bayesian Technique

Incremental Naïve Bayesian Learning Algorithm based on Classification Contribution Degree

In order to improve the ability of gradual learning on the training set gotten in batches of Naive Bayesian classifier, an incremental Naïve Bayesian learning algorithm is improved with the research on the existing incremental Naïve Bayesian learning algorithms. Aiming at the problems with the existing incremental amending sample selection strategy, the paper introduced the concept of sample Cl...

Aims and Intended Learning Outcomes

OUTCOMES The aim of this article is to review basic and advanced methods of opening and clearing an airway and to discuss effective means of ventilation and oxygenation in A&E. As an A&E nurse, you are encouraged to look at your practice and ask yourself: ‘Am I providing the best for my patient?’ After reading this article you should be able to: Describe and perform basic airway opening devices...

Adaptive MOOCs to Foster Personalized Learning

Adaptive Naïve Bayesian Anti-Spam Engine

The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widel...

Speech Enhancement using Adaptive Data-Based Dictionary Learning

In this paper, a speech enhancement method based on sparse representation of data frames has been presented. Speech enhancement is one of the most applicable areas in different signal processing fields. The objective of a speech enhancement system is improvement of either intelligibility or quality of the speech signals. This process is carried out using the speech signal processing techniques ...