Preferred Language
Articles
/
CBadRIgBVTCNdQwCWXaU
Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
...Show More Authors

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 based on the Spike Neural Network (SNN) called IoT-Traffic Classification (IoT-TCSNN) to classify IoT devices traffic. The model consists of four phases: data preprocessing, feature extraction, classier and evaluation. The proposed model performance is evaluated according to evaluation metrics: accuracy, precision, recall and F1-score and energy usage in comparison with two models: ML based Support Vector Machine IoT-TCSVM and ML based Deep Neural Network (IoT-TCDNN). The evaluations result has been shown that IoT-TCSNN consumes less energy in contrast to IoT-TCDNN and IoT-TCSVM. Also, it gives high accuracy in comparison with IoT-TCSVM.

Scopus Crossref
View Publication
Publication Date
Sun Jun 07 2026
Journal Name
Journal Of Physical Education
The Effect of Varied Teaching Strategies on Learning Backstroke Swimming for Students
...Show More Authors

View Publication
Publication Date
Tue Sep 23 2025
Journal Name
Journal Of Sport Science Technology And Physical Activities
The Effect of Flipped Learning on Overhand Serve Skill Acquisition in Volleyball
...Show More Authors

The study aimed to determine the effect of the flipped learning model in improving the acquisition of the overhand serve skill in volleyball among second-year students at the College of Physical Education and Sport Sciences, University of Baghdad, for the academic year 2024/2025. The study used an experimental design with a control group and pre-post testing, on a purposive sample consisting of 12 students. The model relied on watching short videos before class via the SGS application, and practical application in class at a rate of three sessions per week. The results showed a significant improvement in performance, as the calculated value (t = 5.356) exceeded the tabulated value (2.042) at a significance level of 0.05. The percentage of s

... Show More
Publication Date
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
The Impact of Transfer Learning and Pre-trained Models on Model Performance
...Show More Authors

View Publication
Scopus Crossref
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
...Show More Authors

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

... Show More
View Publication Preview PDF
Publication Date
Sat Dec 31 2022
Journal Name
Wasit Journal Of Computer And Mathematics Science
Cheating in E-learning from the perspective of lecturers within Iraqi universities
...Show More Authors

Online examination is an integral and vital component of online learning. Student authentication is going to be widely seen when one of these major challenges within the online assessment. This study aims to investigate potential threats to student authentication in the online examinations. Adopting cheating in E-learning in a university of Iraq brings essential security issues for e-exam . In this document, these analysts suggested  a model making use of a quantitative research style to confirm the suggested aspects and create this relationship between these. The major elements that might impact universities to adopt cheating electronics were declared as Educational methods, Organizational methods, Teaching methods, Technical meth

... Show More
View Publication
Crossref (1)
Crossref
Publication Date
Sun Jan 01 2023
Journal Name
Corporate And Business Strategy Review
The role of learning organizations in crisis management strategy: A case study
...Show More Authors

The problem of the paper focused on the role of the learning organization in the crisis management strategy, and the extent of the actual interest in both the learning organization and the crisis management and aimed at diagnosing and analyzing that and surrounding questions. The Statistical Package for the Social Sciences (SPSS) program was used to calculate the results and the correlation coefficient between the two main variables. The methodology was descriptive and analytical. The case study was followed by a questionnaire that was distributed to a sample of 31 teachers. The paper adopted a seven-dimensional model of systemic thinking that encourages questioning, empowerment, provision of advanced technologies, and strategic lea

... Show More
View Publication
Scopus (20)
Crossref (10)
Scopus Crossref
Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
...Show More Authors

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

... Show More
View Publication
Scopus (36)
Crossref (32)
Scopus Clarivate Crossref
Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
...Show More Authors
Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
View Publication
Scopus (47)
Crossref (36)
Scopus Clarivate Crossref
Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
...Show More Authors
Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
View Publication
Scopus (17)
Crossref (20)
Scopus Clarivate Crossref
Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
The Impact of Artificial Intelligence on English Language Learning Challenges and Opportunities
...Show More Authors

View Publication Preview PDF
Scopus Crossref