The proliferation of false and redundant information on e-commerce platforms as well the prevalence ineffective recommendations other untrustworthy behaviors has seriously impeded healthy development these platforms. To address issues enhance prediction accuracy user trust, contemporary recommendation systems often utilize additional (i.e., side information). In this work, we propose a model to...

Introduction: Clinicians use several computer-aided diagnostic systems for depression to authorize their diagnosis. An electroencephalogram  (EEG) may be used as an objective tool for early diagnosis of depression and controlling it from reaching a severe and permanent state. However, artifact contamination reduces the accuracy in EEG signal processing systems. Methods: This work proposes a no...

in this paper a novel fuzzy scheme for medical x-ray image classification is presented. in this method, any image is partitioned in to 25 overlapping subimages and then shape-texture features are extracted from shape and directional information extracted from any subimage. in the classification stage, we apply a fuzzy membership to any subimage with respect to euclidean distance between feature...

Blind modulation classification is an important step in implementing cognitive radio networks. The multiple-input multiple-output (MIMO) technique widely used military and civil communication systems. Due to the lack of prior information about channel parameters overlapping signals MIMO systems, traditional likelihood-based feature-based approaches cannot be applied these scenarios directly. He...