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jperc-177
Teaching techniques due to the Brain-based learning theory among math teachers
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The purpose of the study is to identify the teaching techniques that mathematics' teachers use due to the Brain-based learning theory. The sample is composed of (90) teacher: (50) male, (40) female. The results have shown no significant differences between male and female responses' mean. Additionally, through the observation of author, he found a lack of using Brain-based learning techniques. Thus, the researcher recommend that it is necessary to involve teachers in remedial courses to enhance their ability to create a classroom that raise up brain-based learning skills.  

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Publication Date
Mon Dec 26 2022
Journal Name
Arab Science Heritage Journal
قيود الختام او حرود المتن دراسة تطبيقية بالاستناد على نماذج مختارة من المخطوطات الاسلامية من القرن(10-13هـ/ 16-19م) في المكتبة المركزية بأربيل:
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     Islamic manuscripts are considered an identity for the civilizational, cognitive and cultural development of nations and the Islamic world as a whole, and to identify this identity, the closing statement usually written at the end of the manuscript helps us with this, meaning that the closing entries serve as the identity document of the manuscript

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Publication Date
Sun Jan 13 2019
Journal Name
Arab Science Heritage Journal
استخلاص عامل التلزن ( اللكتين ) من بكتريا لخلايا Enterococcus faecalis EM1 وتأثير العوامل البيئية المختلفة عليه ودوره في تلزن أنواع من البكتريا السالبة لملون غرام
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استخلص عامل التلزن من E. faecalis EM1 بعد تكسير الخلايا بعدة طرق واختيار الطريقة التي تعطي اعلى قيمة تلزن والترسيب بالكحول الاثيلي , واجري فحص التلزن وقياسه للمستخلص  مع انواع من البكتريا السالبة لملون غرام تضمنت     Escherichia coli  و Klebsiella  pneumoniae  و Serratia

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
In Situ Hybridization for Molecular Detection of Human Papilloma Viral 6 / 11 DNA in Adenoctomized Tissues from A group of Iraqi Pediatric Patients
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Among more than 200 different human papilloma viral genotypes, the association of low oncogenic risk-HPV genotypes have been recognized with a variety of oral, oropharyngeal, nasopharyngeal benign tumors as well as non-neoplastic polyposis and papillomas and adenoid hypertrophy. This prospective case- control study aims to determine the rate of DNA detection of HPV genotype 6/11 in nasopharyngeal adeno- tonsillar tissues from a group of patients subjected to adenoctomy for adenoid hypertrophy . A total number of nasopharyngeal adeno-tonsillar tissue specimens from pediatric patients with adenoid hypertrophy were enrolled; 40 nasopharyngeal adeno-tonsillar tissues from patients with adenoid hypertrophy, and 20 normal nasal tissue specimen

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Publication Date
Fri Dec 15 2023
Journal Name
Full Text Book Of Minar Congress10
مستوى الافصاح عن المعلومات المالية المتعلقة بالاستدامة على وفق معيار (IFRS-S1) وتأثير على أداء الشركة - بحث تطبيقي في عينة عن المصارف الاسلامية العراقية
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Publication Date
Mon Sep 20 2021
Journal Name
Key Engineering Materials
Effect of Partial Substitution of Sr by Ba on the Structural Properties of Tl<sub>0.8</sub>Ni<sub>0.2</sub>Sr<sub>2-x</sub>Br<sub>x</sub>Ca<sub>2</sub>Cu<sub>3</sub>O<sub>9-δ</sub> System
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In this manuscript, the effect of substituting strontium with barium on the structural properties of Tl0.8Ni0.2Sr2-xBrxCa2Cu3O9-δcompound with x= 0, 0.2, 0.4, have been studied. Samples were prepared using solid state reaction technique, suitable oxides alternatives of Pb2O3, CaO, BaO and CuO with 99.99% purity as raw materials and then mixed. They were prepared in the form of discs with a diameter of 1.5 cm and a thickness of (0.2-0.3) cm under pressures 7 tons / cm2, and the samples were sintered at a constant temperature o

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Publication Date
Fri May 01 2020
Journal Name
International Journal Of Advanced Science And Technology
Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
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Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

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Publication Date
Fri Feb 17 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deploying Facial Segmentation Landmarks for Deepfake Detection
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Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

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Publication Date
Sat Mar 28 2020
Journal Name
Iraqi Journal Of Science
Effect of levels in Dual Tree Complex Wavelet Transform when design Universal image stego-analytic
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Universal image stego-analytic has become an important issue due to the natural images features curse of dimensionality. Deep neural networks, especially deep convolution networks, have been widely used for the problem of universal image stegoanalytic design. This paper describes the effect of selecting suitable value for number of levels during image pre-processing with Dual Tree Complex Wavelet Transform. This value may significantly affect the detection accuracy which is obtained to evaluate the performance of the proposed system. The proposed system is evaluated using three content-adaptive methods, named Highly Undetetable steGO (HUGO), Wavelet Obtained Weights (WOW) and UNIversal WAvelet Relative Distortion (UNIWARD).
The obtain

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Human Pose Estimation Algorithm Using Optimized Symmetric Spatial Transformation Network
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Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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