We extend the theory of boosting for regression problems to the online learning setting. Generalizing from the batch setting for boosting, the notion of a weak learning algorithm is modeled as an online learning algorithm with linear loss functions that competes with a base class of regression functions, while a strong learning algorithm is an online learning algorithm with smooth convex loss f...

Control systems require maintenance in the form of tuning their parameters order to maximize performance face process changes minerals processing circuits. This work focuses on using deep reinforcement learning train an agent perform this continuously. A generic simulation a first-order with time delay, controlled by proportional-integral controller, was used as training environment. Domain ran...

The purpose of this study was twofold: (a) to assess the retention of two word types (synonyms and homonyms) in the short term memory, and (b) to investigate the effect of these word types on word learning by asking learners to learn their Persian meanings. A total of 73 Iranian language learners studying English translation participated in the study. For the first purpose, 36 freshmen from an ...

Background. This work studied 60 university students who were registered in two handball training classes in the second year of Physical Education and Sports Science throughout the academic year 2017 to 2018. Objectives. It aims to identify the impact of two different training styles (cooperative and traditional) on players’ achievements and basic techniques in a handball learning unit. Metho...

in the process of learning basic biochemistry, as in any other area, much extra class work is required for students before basic concepts, such as those concerning protein structure and properties, are firmly settled. to reach this end we have developed a simple instruction method to teach protein structure in biochemistry courses for medical students. the objectives of this method are to illus...

fuzzy rule-based classification system (frbcs) is a popular machine learning technique for classification purposes. one of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. however many cases the minority classes are more important than the majority ones. in this paper, we have extended ...

This study investigated the relationship between student perceptions of others in an online class and both affective and cognitive learning outcomes. Data were gathered from student survey responses and instructor evaluation of performance. Results from this study indicated significant correlations between student perceptions of the presence of other students in the class and scores on an attit...