Preferred Language
Articles
/
ijs-3556
Learning Evolution: a Survey
...Show More Authors

     Learning is the process of gaining knowledge and implementing this knowledge on behavior. The concept of learning is not strict to just human being, it expanded to include machine also. Now the machines can behave based on the gained knowledge learned from the environment. The learning process is evolving in both human and machine, to keep up with the technology in the world, the human learning evolved into micro-learning and the machine learning evolved to deep learning. In this paper, the evolution of learning is discussed as a formal survey accomplished with the foundation of machine learning and its evolved version of learning which is deep learning and micro-learning as a new learning technology can be implemented on human and machine learning. A procedural comparison is achieved to declare the purpose of this survey, also a related discussion integrates the aim of this study. Finally a concluded points are illustrated as outcome which summarized the practical evolution intervals of the machine learning different concepts.

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Mon Jan 16 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Association between Enhancing Learning Needs and Demographic Characteristic of Patients with Myocardial Infarction: العلاقة بين تعزيز احتياجات التعلم والخصائص الديموغرافية لمرضى احتشاء عضلة القلب
...Show More Authors

Abstract

Objectives: To find out the association between enhancing learning needs and demographic characteristic of (gender, education level and age).

Methods: This study was conducted on purposive sample was selected to obtain representative and accurate data consisting of (90) patients who are in a peroid of recovering from myocardial infarction at Missan Center for Cardiac Diseases and Surgery, (10) patients were excluded for the pilot study, Data were analyzed using descriptive statistical data analysis approach of frequency, percentage,  and analysis of variance (ANOVA).

Results: The study finding shows, there was sign

... Show More
View Publication Preview PDF
Publication Date
Sun Sep 03 2023
Journal Name
Iraqi Journal Of Computers, Communications, Control & Systems Engineering (ijccce)
Efficient Iris Image Recognition System Based on Machine Learning Approach
...Show More Authors

HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

View Publication
Publication Date
Fri Dec 03 2021
Journal Name
International Journal Of Recent Contributions From Engineering, Science & It
The Influence E-Learning Platforms of Undergraduate Education in Iraq
...Show More Authors

Crossref
Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
...Show More Authors

    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

... Show More
View Publication Preview PDF
Crossref
Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
...Show More Authors

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

... Show More
View Publication
Scopus (1)
Scopus Crossref
Publication Date
Tue May 07 2019
Journal Name
Acm Journal On Emerging Technologies In Computing Systems
Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis
...Show More Authors

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

... Show More
View Publication
Scopus (12)
Crossref (12)
Scopus Clarivate Crossref
Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
...Show More Authors

View Publication
Crossref (13)
Scopus Clarivate Crossref
Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
...Show More Authors

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

... Show More
View Publication
Scopus Crossref
Publication Date
Wed May 01 2013
Journal Name
2013 Fourth International Conference On E-learning "best Practices In Management, Design And Development Of E-courses: Standards Of Excellence And Creativity"
Students' Perspectives in Adopting Mobile Learning at University of Bahrain
...Show More Authors

View Publication
Scopus (10)
Crossref (7)
Scopus Clarivate Crossref
Publication Date
Tue Dec 28 2021
Journal Name
2021 2nd Information Technology To Enhance E-learning And Other Application (it-ela)
Pedestrian and Objects Detection by Using Learning Complexity-Aware Cascades
...Show More Authors

View Publication Preview PDF
Scopus (5)
Crossref (2)
Scopus Clarivate Crossref