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The effect of Daniel's model on the development of critical thinking in the subject of Arabic language among students of the College of Management and Economics
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This research aims to identify the impact of Daniel's model on the development of critical thinking. In order to achieve this objective, the following hypotheses are formulated: 1. There is no statistically significant difference at the significance level (0.05) between the average differences in the posttest scores of the experimental group taught according to Daniel's model and the control group taught according to the traditional method in the measure of critical thinking. 2. There is no statistically significant difference at the significance level (0.05) between the average differences in the preand post-tests scores of the experimental group taught according to Daniel's model in the measure of critical thinking. The current research is limited to a sample of the first stage students in the department of statistics, College of Management and Economics, Baghdad University for the academic year 2019-2020. The California critical thinking test is applied in the post-test to the control group, which consisted of (47) students, and the experimental group, which consisted of (44) students. After using Ttest for two independent and related samples, the results show that: 1. There is a statistically significant difference between the average of the scores of the two research groups in favor of the experimental group. Therefore, the null hypothesis rejected and the alternative hypothesis is accepted that there is a statistically significant difference between the average of scores of the experimental and control groups in the post-test of critical thinking. 2. There is a statistically significant difference between the average of scores of the experimental group students in the preand post-tests of the creative thinking. This refers to a development in the critical thinking among the students of the experimental group. In the light of the results, a number of conclusions, recommendations and suggestions are presented at the end of this research

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Engineering
Adding Cellulosic Ash to Composting Mix as a Soil Amendment
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Solid waste generation and composition in Baghdad is typically affected by population growth, urbanization, improved economic conditions, changes in lifestyles and social and cultural habits.

A burning chamber was installed to burn cellulosic waste only. It was found that combustion reduced the original volume and weight of cellulosic waste by 97.4% and 85% respectively.

A batch composting study was performed to evaluate the feasibility of co-composting organic food waste with the cellulosic bottom ash in three different weight ratios (w/w) [95/5, 75/25, 50/50].

The composters were kept in controlled aerobic conditions for 7 days. Temperature, moisture, and pH were measured hourly as process succe

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Publication Date
Fri Dec 08 2023
Journal Name
Iraqi Journal Of Science
Thermal Emission from Binary Millisecond Pulsar Stars (MSPs)
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Pulsar stars divided into two types depending on the periods of rotation, normal
emission Pulsar and Millisecond pulsars (MSPs). In this paper, the effect of the
strong magnetic field on the thermal emission in Millisecond pulsar stars is
concentrated. Also the luminosity spin down (Lsp) are calculated depends on the
periods (P), and Period derivative (
P
) for sample stars which were adopted. The
relation between internal and surface magnetic field is illustrated. The model that
which adopted is Hallo Cone Model (HCM)). The total magnetic dipole radiation
power (heating power Wh) of all super fluid neutrons in MSPs stars is calculated.
For sample stars of MSPs , the value of transition period (Ptr) was d

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
An Algorithm for nth Order Intgro-Differential Equations by Using Hermite Wavelets Functions
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In this paper, the construction of Hermite wavelets functions and their operational matrix of integration is presented. The Hermite wavelets method is applied to solve nth order Volterra integro diferential equations (VIDE) by expanding the unknown functions, as series in terms of Hermite wavelets with unknown coefficients. Finally, two examples are given

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detecting Textual Propaganda Using Machine Learning Techniques
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Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Hybrid CNN-SMOTE-BGMM Deep Learning Framework for Network Intrusion Detection using Unbalanced Dataset
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This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
N Sequence Prime Ideals
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    In this paper, the concepts of -sequence prime ideal and -sequence quasi prime ideal are introduced. Some properties of such ideals are investigated. The relations between -sequence prime ideal and each of primary ideal, -prime ideal, quasi prime ideal, strongly irreducible ideal, and closed ideal, are studied. Also, the ideals of a principal ideal domain are classified into quasi prime ideals and -sequence quasi prime ideals.

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Modern Mathematical Sciences
Coupled Laplace-Decomposition Method for Solving Klein- Gordon Equation
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In this paper, we consider a new approach to solve type of partial differential equation by using coupled Laplace transformation with decomposition method to find the exact solution for non–linear non–homogenous equation with initial conditions. The reliability for suggested approach illustrated by solving model equations such as second order linear and nonlinear Klein–Gordon equation. The application results show the efficiency and ability for suggested approach.

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Wavenet (FWN) classifier for medical images
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    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

&n

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

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Publication Date
Tue Jun 01 2021
Journal Name
Periodicals Of Engineering And Natural Sciences
Steganography using dual tree complex wavelet transform with LSB indicator technique
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Image steganography is undoubtedly significant in the field of secure multimedia communication. The undetectability and high payload capacity are two of the important characteristics of any form of steganography. In this paper, the level of image security is improved by combining the steganography and cryptography techniques in order to produce the secured image. The proposed method depends on using LSBs as an indicator for hiding encrypted bits in dual tree complex wavelet coefficient DT-CWT. The cover image is divided into non overlapping blocks of size (3*3). After that, a Key is produced by extracting the center pixel (pc) from each block to encrypt each character in the secret text. The cover image is converted using DT-CWT, then the p

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