Introduction: This study aims to compare the effectiveness of mindfulness-based cognitive therapy and meta-cognitive therapy based on training on emotion regulation and anxiety sensitivity in elderly with precedent heart disease in Tehran city.  Methods: This was an experimental study with pre-test & post-test and statistical population consisted of all elderly with precedent heart disease liv...

A wide selection of standard statistical pattern classification algorithms can be applied as trainable fusion rules while designing neural network ensembles. A focus of the present two-part paper is finite sample effects: the complexity of base classifiers and fusion rules; the type of outputs provided by experts to the fusion rule; non-linearity of the fusion rule; degradation of experts and t...

In this paper, intelligent perception-based systems are proposed in application to medical diagnosis problems. The systems are created by use of connectionist neurofuzzy architectures that reflect fuzzy IFTHEN rules. The perception-based rules can be generated from examples by the system. Fuzzy reasoning, according to these rules, is considered within the framework of the computational theory o...

The purpose of this paper is to present a genetic learning process for learning fuzzy control roles from examples. It is developed in three stages: the first one is a fuzzy rule genetic generating process based on a rule learning iterative approach, the second one combines two kinds of rules, experts rules if there are and the previously generated fuzzy control rules, removing the redundant fuz...

Classification of underwater acoustic signal is one of the important fields of pattern recognition. Inspired by the experience of training man experts in sonar, we propose a two-phase training algorithm to exploit the association rules to reveal the understandable intrinsic rules contributing to correct classification in the known misclassification datasets in this paper. Preliminary experiment...

When combining outputs from multiple classifiers, many combination rules are available. Although easy to implement, fixed combination rules are optimal only in restrictive conditions. We discuss and evaluate their performance when the optimality conditions are not fulfilled. Fixed combination rules are then compared with trainable combination rules on real data in the context of face-based iden...

Background: Academic motivation in students is one of the essential factors for academic achievement and growth of societies, which emphasizes the importance of examining academic motivation correlations. Therefore, this research aimed to evaluate the structural equation model of explaining academic motivation in students based on emotion regulation with the mediating role of academic self-effi...