Investigating the strength and the relationship between the Self-organized learning strategies and self-competence among talented students was the aim of this study. To do this, the researcher employed the correlation descriptive approach, whereby a sample of (120) male and female student were selected from various Iraqi cities for the academic year 2015-2016.  the researcher setup two scales based on the previous studies: one to measure  the Self-organized learning strategies which consist of (47) item and the other to measure the self-competence that composed of (50) item. Both of these scales were applied on the targeted sample to collect the required data

Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

AO Dr. Ali Jihad, Journal of Physical Education, 2021

First: the definition searchEnsure the definition Introduction of research and its importance, as it was addressed to the importance of the importance of training in the development of people and institutions and the importance of diversifying the training vocabulary and a lot of relevant courses for its role to develop work and get away from the routine work, and was put up for the importance of research to identify the problems and obstacles facing the process of providing training as the best in order to access to the ambition sought by workers on training and even the trainees while defined research problem that was observed weak performance and cost-effective training through the study of some of the questionnaires distributed

The present study was conducted to determine the pathogenicity of Paecilomyces farinosus as biocontrol agents against Tragoderma granarium (khapra) under laboratory conditions with three concentrations ( 2.8 x 108 , 2.8 x 106 ,2.8 x104 spores/ ml). The laboratory results revealed that fungi showed it's higher pathogencity to larve stage on 2nd instar and 6th instar , although their capability differs according to the fungi concentrations this fungi caused higher mortality of 2nd larval instar 70% and 60% ,55% when it was used at concentrations 2 .8 x 106 ,2.8 x104 spores/ ml respectively. On the other hand on 6th larval instars 55% , 35% , 30% at concentrations ( 2.8 x 108 , 2.8 x 106 ,2.8 x104 spores/ ml) respectively, and the h

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep