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Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five attributes of the training process. The results of the second experiment showed improvement in the performance of the KNN and the Multilayer Perceptron. The results of the second experiment showed a slight decrease in the performance of the Random Forest with 97.5 % accuracy.

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Scientific Development For Studies And Research
The Role of E-Learning in teaching the Arabic language to non- native speakers
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After the information revolution that occurred in the Western world, and the developments in all fields, especially in the field of education and e-learning, from an integrated system based on the effective employment of information and communication technology in the teaching and learning processes through an environment rich in computer and Internet applications, the community and the learner were able to access information sources and learning at any time and place, in a way that achieves mutual interaction between the elements of the system and the surrounding environment. After the occurrence of the phenomenon of Covid 19, it led to a major interruption in all educational systems that had never happened before, and the disrupt

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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Publication Date
Tue Dec 25 2018
Journal Name
Summaries Of Working Papers, Research And Experiments
E-learning at the College of Mass Communication, subject: public relations campaigns as a model
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Publication Date
Wed Jan 01 2020
Journal Name
Systematic Reviews In Pharmacy
Anti-Oxidoreductive stress Effects of Iraqi Olea Europaea L. Leaves extract against low double doses of alloxan induced diabetes mellitus in rats
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Olive leaves extract is famous for its antioxidant and protective effects. In this study, the aqueous extract of Iraqi Olea europaea L. Leaves was investigated for its anti-diabetic effects against low double doses of alloxan induced Diabetes Mellitus in rats. Low double doses (75 mg\Kg body weight) of alloxan were injected intraperitoneally at day 1&29 of the experimental period in rats, whereas an aqueous extract of Iraqi Olea europaea L. Leaves was added continuously to their drinking water. Serum malondialdehyde concentration, total oxidative stress and oxidative stress index as oxidoreductive stress biomarker, activities of certain antioxidoreductive stress enzymes (glutathione peroxidase, super oxide dismutase and catalase) and concen

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Publication Date
Wed Sep 15 2021
Journal Name
Al-academy
The impact of e-learning on the cognitive level in the Corona crisis: أسماء غازي عبد
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E-learning is a necessity imposed by the Corona pandemic, which has disrupted various educational institutions in the world, but some of these institutions have not been affected and education has continued with them, due to their flexible educational system that was able to employ technology in the continuity of the educational process in the so-called e-learning, because It has characteristics that make it the most suitable alternative to avoid the consequences of the Corona pandemic and its damage to the educational process, as e-learning is one of the modern methods that contribute to enhancing the effectiveness of the learner, and enabling him to assume greater responsibility compared to traditional education, so the learner becomes

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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
The Counseling Needs of Behavioral Problems among Students with Academic Learning Disabilities
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Learning Disabilities are described as a hidden and puzzling disability. Children with these difficulties have the potential to hide weaknesses in their performance because they are a homogenous group of disorders that consist of obvious difficulties in acquiring and using reading, writing, Mathematical inference. Thus, the research aims to identify the disabilities of academic learning in (reading, writing, mathematics), identify the problems of behavior (general, motor, social). Identify the relationship among behaviour problems. The research also aims to identify the counseling needs to reduce the behavioral problems. The researcher adopted the analytical descriptive method by preparing two main tools for measuring learning disabiliti

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
The Philosophy of Organizational Forgetting In Frame of Learning and Organizational knowledge
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current research aims to build an intellectual framework for concept of organizational forgetting, which is considered one of the most important topics in contemporary management thought, which is gain the consideration of most scholars and researchers in field of organizational behavior, which is to be a loss of intentional or unintentional knowledge of any organizational level. It turned out that just as organizations should learn and acquire knowledge, they must also forget, especially knowledge obsolete and worn out. And represented the research problem in the absence of Arab research dealing with organizational forgetting, and highlights the supporting infrastructure core, and show a close relationship with organizational le

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
New Trends in Teaching and Learning Theory Dr. Jasim Muhammad Abdul- Slamy
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New trends in teaching and learning theory are considered a theoretical axis
from which came the background that depends on any source, or practice sample or
teaching plane, accuracy and simplicity prevent the development of the teaching
process. Many attempts have come to scene to illuminate the teaching background,
but they have not exceed those remarkable patterns and methods. Thus, the
appearance of the teaching theory have been hindered.
This led to the need for research and development in the field of teaching to
find out a specific teaching theory according to the modern trends and concepts.
Teaching is regarded a humanitarian process which aims at helping those who
want to acquire knowledge, since teach

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Publication Date
Sun Apr 02 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
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Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

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Publication Date
Mon Aug 01 2022
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
A survey of deepfakes in terms of deep learning and multimedia forensics
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Artificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfakedetection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection

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