Preferred Language
Articles
/
ijs-5203
Educational Data Mining For Predicting Academic Student Performance Using Active Classification
...Show More Authors

     The increasing amount of educational data has rapidly in the latest few years. The Educational Data Mining (EDM) techniques are utilized to detect the valuable pattern so that improves the educational process and to obtain high performance of all educational elements. The proposed work contains three stages: preprocessing, features selection, and an active classification stage. The dataset was collected using EDM that had a lack in the label data, it contained 2050 records collected by using questionnaires and by using the students’ academic records. There are twenty-five features that were combined from the following five factors: (curriculum, teacher, student, the environment of education, and the family). Active learning had been utilized in the classification. Four techniques had been applied for classifying the features: Random Forest (RF) algorithm, Label Propagation (LP), Logistic Regression (LR), and Multilayer Perceptron (MLP). The accuracies of prediction were 95.121%, 92.195%, 92.292%, and 93.951% respectively. Also, the RF algorithm has been utilized for assorting the features depending on their importance.

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Tue Jul 11 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Daniel's Model on the Achievement of Chemistry Among Fifth Grade Student
...Show More Authors

The aim of this research is to find out the influence of Daniel's model on the skills of the twenty-first century among the students of the scientific-fifth grade at the secondary and preparatory government morning schools for the academic year 2022- 2023. Two groups were chosen out of five groups for the fifth-scientific grade, one of which represents the experimental group that is taught by the Daniel model, and the other is the control group that is taught in the traditional method. The equivalence of the two research groups was verified with a set of variables. As for the research tool, a scale was developed by the researchers for the skills of the twenty-first century, in which they adopted the framework of the Partnership Organizat

... Show More
View Publication Preview PDF
Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Determine Nasal Carriage of Methicillin Resistant Staphylococcus aureus MRSA in Young Adult College Student
...Show More Authors

Present study was carried out to find prevalence of MRSA in healthy individual of second stage students, college of pharmacy/Baghdad University. A total of 74 student selected between age 18-23 years old were included in this study, nasal swabs collected and subjected to many diagnostic standard bacteriological identification methods. Culture, colonial morphology, Gram stain,  mannitol fermentation, coagulase ,gelatinasetest, DNAase, MR/VP and antimicrobial susceptibility test was performed on tryptic soy agar by modified Kirby-Bauer muller hinton disc diffusion method and the result show that out of 74 nasal swabs,67(90.5%) were MRSA positive isolates, 21(31.4%) of them were mannitol ferment and 46(68.6%) non mannitol fermenter, am

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Engineering
Satellite Images Classification in Rural Areas Based on Fractal Dimension
...Show More Authors

Fractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity crit

... Show More
View Publication Preview PDF
Publication Date
Sun Jan 26 2020
Journal Name
Iraqi Journal Of Science
New Updated Classification of Shallow Earthquakes Based on Faulting Style
...Show More Authors

Earthquakes occur on faults and create new faults. They also occur on  normal, reverse and strike-slip faults. The aim of this work is to suggest a new unified classification of Shallow depth earthquakes based on the faulting styles, and to characterize each class. The characterization criteria include the maximum magnitude, focal depth, b-constant value, return period and relations between magnitude, focal depth and dip of fault plane. Global Centroid Moment Tensor (GCMT) catalog is the source of the used data. This catalog covers the period from Jan.1976 to Dec. 2017. We selected only the shallow (depth less than 70kms) pure, normal, strike-slip and reverse earthquakes (magnitude ≥ 5) and excluded the oblique earthquakes. Th

... Show More
View Publication Preview PDF
Scopus (5)
Crossref (2)
Scopus Crossref
Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
A Proposed Algorithm for Encrypted Data Hiding in Video Stream Based on Frame Random Distribution
...Show More Authors

     The science of information security has become a concern of many researchers, whose efforts are trying to come up with solutions and technologies that ensure the transfer of information in a more secure manner through the network, especially the Internet, without any penetration of that information, given the risk of digital data being sent between the two parties through an insecure channel. This paper includes two data protection techniques. The first technique is cryptography by using Menezes Vanstone elliptic curve ciphering system, which depends on public key technologies. Then, the encoded data is randomly included in the frame, depending on the seed used. The experimental results, using a PSNR within avera

... Show More
View Publication Preview PDF
Scopus (1)
Scopus Crossref
Publication Date
Fri Jan 24 2025
Journal Name
Sciences Journal Of Physical Education
The relationship of future anxiety to the level of academic ambition among female students
...Show More Authors

View Publication Preview PDF
Publication Date
Sun Jul 04 2010
Journal Name
Journal Of Educational And Psychological Researches
Educational Curricula of preeminent and Talent:Enrichment Curriculum as a Model
...Show More Authors

This research aimed at recognizing the properties of curricula that fitted to preeminent and talent students. Many types of these curricula were exposed, enrichment curriculum was explained as one of alternatives of available curricula.
The research used the analytical methodology for local and international literature in the field of preeminent and talent education to meet the properties of curricula that fitted to this special group of students. Many results was obtained as:
• This type of school enrichment curriculum consists of three levels( general discovery activities, individual and groups training activities, and individual or groups real problems).
• Investigation the effectively both sides of brain: right and left,

... Show More
View Publication Preview PDF
Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Benchmarking Framework for COVID-19 Classification Machine Learning Method Based on Fuzzy Decision by Opinion Score Method
...Show More Authors

     Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing

... Show More
View Publication Preview PDF
Scopus (9)
Crossref (7)
Scopus Crossref
Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Useing the Hierarchical Cluster Analysis and Fuzzy Cluster Analysis Methods for Classification of Some Hospitals in Basra
...Show More Authors

In general, the importance of cluster analysis is that one can evaluate elements by clustering multiple homogeneous data; the main objective of this analysis is to collect the elements of a single, homogeneous group into different divisions, depending on many variables. This method of analysis is used to reduce data, generate hypotheses and test them, as well as predict and match models. The research aims to evaluate the fuzzy cluster analysis, which is a special case of cluster analysis, as well as to compare the two methods—classical and fuzzy cluster analysis. The research topic has been allocated to the government and private hospitals. The sampling for this research was comprised of 288 patients being treated in 10 hospitals. As t

... Show More
View Publication Preview PDF
Scopus (4)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
Implementation of Machine Learning Techniques for the Classification of Lung X-Ray Images Used to Detect COVID-19 in Humans
...Show More Authors

COVID-19 (Coronavirus disease-2019), commonly called Coronavirus or CoV, is a dangerous disease caused by the SARS-CoV-2 virus. It is one of the most widespread zoonotic diseases around the world, which started from one of the wet markets in Wuhan city. Its symptoms are similar to those of the common flu, including cough, fever, muscle pain, shortness of breath, and fatigue. This article suggests implementing machine learning techniques (Random Forest, Logistic Regression, Naïve Bayes, Support Vector Machine) by Python to classify a series of chest X-ray images that include viral pneumonia, COVID-19, and healthy (Not infected) cases in humans. The study includes more than 1400 images that are collected from the Kaggle platform. The expe

... Show More
View Publication Preview PDF
Scopus (36)
Crossref (18)
Scopus Crossref