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COLLABORATIVE WRITING AS A MEANS IN DEVELOPING EFL LEARNERS’ WRITING PERFORMANCE
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Collaborative learning is a way that prepares students practically for real-world applications. Working together as teamwork to execute various writing skills is essential in most professions since it increases the level of experience. Thus, the current study aims to identify the role collaborative writing in developing students' level of performance in writing. It is qualitative in nature since the researcher depended on the extant literature in achieving the objective of the study. The researcher touched upon related theories that addressed Collaborative learning, categories, and problems .It concluded that collaborative writing increases the students’ self-confidence, self-esteem, creativity, and motivation through the interaction among students over task completion. It enables the provision of feedback between students, which enhances their vocabulary, offers them ideas, and improves their learning. Writing in groups improves students’ writing in the aspect of grammatical accuracy and vocabulary. Finally, the study came out with a number of recommendations.

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Publication Date
Mon Aug 01 2022
Journal Name
Inorganic Chemistry Communications
Assembling [email protected] nanocomposites with an enhanced photocatalytic activity
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Herein, an efficient inorganic/organic hybrid photocatalyst composed of zeolitic imidazolate framework (ZIF-67) decorated with Cd0.5Zn0.5S solid solution semiconductor was constructed. The properties of prepared ZIF- [email protected] nanocomposite and its components (ZIF-67 and Cd0.5Zn0.5S) were investigated using XRD, FESEM, EDX, TEM, DRS and BET methods. The photocatalytic activity of fabricated [email protected] nanocomposite were measured toward removal of methyl violet (MV) dye as a simulated organic contaminant. Under visible-light and specific conditions (photocatalyst dose 1 g/l, MV dye 10 mg/l, unmodified solution pH 6.7 and reaction time 60 min.), the acquired [email protected] photocatalyst showed advanced photocatalytic activity

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Publication Date
Tue Jun 30 2015
Journal Name
Al-khwarizmi Engineering Journal
Laser Peening on Aluminum Alloy 7049 Using Black Paint Surface Coating
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Abstract

Black paint laser peening (bPLP) technique is currently applied for many engineering materials , especially for aluminum alloys due to high improvement in fatigue life and strength . Constant and variable   bending fatigue tests have been performed at RT and stress ratio R= -1 . The results of the present  work observed that the significance of the surface work hardening which generated high negative residual stresses in bPLP specimens .The fatigue life  improvement factor (FLIF)  for bPLP constant fatigue behavior was from 2.543 to 3.3 compared to untreated  fatigue and the increase in fatigue strength at 107 cycle was 21% . The bPLP cumulative fatigue life behav

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Publication Date
Sat Dec 31 2022
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
PREPARATION AND STUDY OF THE PHYSICAL PROPERTIES OF SOME COMPLEXES WITH SCHIFF BASE LIGAND FOR CEFDINIR DERIVATIVE : PREPARATION AND STUDY OF THE PHYSICAL PROPERTIES OF SOME COMPLEXES WITH SCHIFF BASE LIGAND FOR CEFDINIR DERIVATIVE
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ABSTRACT

Metal (II) complexes of Co, Ni, Cu and Zn with cefdinir C14H13N5O5S2 derivative (L) were synthesized and identification by elemental analysis CHNS Uv-Vis, FTIR, TGA, metal analysis AA, magnetic susceptibility and conduct metric measurement. by analysis the ligand behaves as a bidentate. For the cobalt complex, Tetrahedral geometry shape was suggested, while other complexes that have nickel, copper and zinc ions were proposed as octahedral geometry shape. The experimental method was studied for prevention of corrosion carbon steel in 3.5% NaCl by using a novel Cefdinir derivations drugs. The results showed that metal complex was a strong corro

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Publication Date
Tue Dec 01 2020
Journal Name
Environmental Nanotechnology, Monitoring & Management
Sulfonated polyindole coated magnetic zincoxysulfide ([email protected]@SPID) core/shell nanocatalyst for simultaneous photocatalytic H2 production and BPA degradation
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Photocatalyst composed of core/shell magnetic zincoxysulfide nanocomposite coated with sulfonated polyindole ([email protected]/SPID) has been prepared and used for simultaneous photocatalytic H2 production and Bisphenol A (BPA) degradation. XRD, FE-SEM, EDX, BET surface area, UV-vis DRS and VSM were used to characterize the synthesized nanocomposites. The photocatalytic performance was evaluated using batch reactor under visible light irradiation. The photocatalytic activity of [email protected]/SPID nanocomposite was revealed to exceed that of [email protected] nanocomposite due to the heterojunctions between SPID and [email protected] species. The results exhibited that the effect of BPA initial concentration was found to be effectual on the improvement

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Publication Date
Fri Dec 31 2021
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
AN EXPERIMENTAL STUDY OF THE EFFECT OF VORTEX GENERATOR ON THE FLAT-PLATE BOUNDARY LAYER: AN EXPERIMENTAL STUDY OF THE EFFECT OF VORTEX GENERATOR ON THE FLAT-PLATE BOUNDARY LAYER
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This paper is dealing with an experimental study to show the influence of the geometric characteristics of the vortex generators VG son the thickness of the boundary layer (∂) and drag coefficients (CD) of the flat plate. Vortex generators work effectively on medium and high angles of attack, since they are "hidden" under the boundary layer and practically ineffective at low angles.

            The height of VGs relative to the thickness of the boundary layer enables us to study the efficacy of VGs in delaying boundary layer separation. The distance between two VGs also has an effect on the boundary layer if we take into

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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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
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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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
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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