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Modern Probabilistic Model: Filtering Massive Data in E-learning

So muchinformation keeps on being digitized and stored in several forms, web pages, scientific articles, books, etc. so the mission of discovering information has become more and more challenging. The requirement for new IT devices to retrieve and arrange these vastamounts of informationaregrowing step by step. Furthermore, platforms of e-learning are developing to meet the intended needsof students.
The aim of this article is to utilize machine learning to determine the appropriate actions that support the learning procedure and the Latent Dirichlet Allocation (LDA) so as to find the topics contained in the connections proposed in a learning session. Ourpurpose is also to introduce a course which moves toward the student's attempts and which reduces the unimportant recommendations (Which aren’t proper to the need of the student grown-up) through the modeling algorithms of the subjects.

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Publication Date
Thu Jul 13 2023
Journal Name
International Journal Of Research In Social Sciences & Humanities
Subject Review: Blogs as Learning Tools in EFL Classrooms

Blogs have emerged as a powerful technology tool for English as a Foreign Language (EFL) classrooms. This literature review aims to provide an overview of the use of blogs as learning tools in EFL classrooms. The study examines the benefits and challenges of using blogs for language learning and the different types of blogs that can be used for language learning. It provides suggestions for teachers interested in using blogs as learning tools in their EFL classrooms. The findings suggest that blogs are a valuable and effective tool for language learning, particularly in promoting collaboration, communication, and motivation.

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Review of Smishing Detection Via Machine Learning

     Smishing is a cybercriminal attack targeting mobile Short Message Service (SMS) devices that contains a malicious link, phone number, or email. The attacker intends to use this message to steal the victim's sensitive information, such as passwords, bank account details, and credit cards. One method of combating smishing is to raise awareness and educate users about the various tactics used by SMS phishers. But even so, this method has been criticized for becoming inefficient because smishing tactics are continually evolving. A more promising anti-smishing method is to use machine learning. This paper introduces a number of machine learning algorithms that can be used for detecting smishing. Furthermore, the differences and simil

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Publication Date
Sun Jan 14 2024
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
Using Nonparametric Procedure to Develop an OCMT Estimator for Big Data Linear Regression Model with Application Chemical Pollution in the Tigris River

Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison Between Some Estimator Methods of Linear Regression Model With Auto-Correlated Errors With Application Data for the Wheat in Iraq

This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A Suggested Model For Using Customer's Data Management Information System/ A Case Study In Al-Rasheed Bank/General Agent Office/ Nothren Reigon

This study aim to  identify the concept of  web based information systems since its one of the important topics that is  usually omitted by our organizations, in addition to,  designing a web based information system in order to manage the customers data of Al- Rasheed bank, as a unified information system that is specialized to the banking deals of the customers with the bank, and providing a suggested model to apply the virtual private network as a tool that is to protect the transmitted data through the web based information system.

This study is considered important because it deals with one of the vital topics nowadays, namely: how to make it possible to use a distributed informat

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of weighted estimated method and proposed method (BEMW) for estimation of semi-parametric model under incomplete data

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An improved neurogenetic model for recognition of 3D kinetic data of human extracted from the Vicon Robot system

These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce

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Publication Date
Tue Jan 30 2018
Journal Name
Iraqi Journal Of Science
Inversion to density and velocity model by integrated with wells data at regional area (central and southwestern Iraq)

A new derivative applied to the old gravity Bouguer map (served in 1940s and 1950s), taking regional study area covered the mid and south of Iraq. The gravity anomaly reflects a density contrast variation; therefore it is possible to use gravity inversion to the density and velocity model through layers (615m, 1100m, 1910m, 2750m and 5290m), the depth layers according to the power spectrum analysis of gravity Bouguer. The inversion is according to the integration of gravity anomalies of the each depth layer with the same depth of wells data, considered to the estimations and analysis of density and velocity scatters of the oil wells distribution with depth at the regional area. Taking the relation

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Robust Two-Step Estimation and Approximation Local Polynomial Kernel For Time-Varying Coefficient Model With Balance Longitudinal Data

      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Study of total Immunoglobulin E and Eosinophil count in allergic disease

The present study aimed to evaluate the levels of total immunoglobulin E and percentage count of eosinophil in some of allergic disease. Blood sample collected from 210 patients (110 female, 100 male) with allergic disease (allergic asthma, allergic rhinitis, and urticaria) their age between 10-70 years and 50 healthy control their age between 23-52 years. A highly significant (P<0.01) increase in the mean serum total IgE in patients with asthma (503.54 ± 63.49 IU/ml), Allergic rhinitis (442.77 ± 95.76 IU/ml) and urticaria (489.53 ± 69.68 IU/ml) as a compared with healthy controls (23.67 ± 5.81 IU/ml).There was a significant difference in percentage count of eosinophil in patients groups allergic asthma 4.37 ± 0.52% ,allergic rhinitis

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