The research problem can be summarized through focusing on the environment that surrounds students and class congestion, how these factors affect directly or indirectly the academic achievement of students, how these factors affect understanding the scientific material that the student receives in this physical environment, how classroom’s components such as seats, space With which the student can move, the number of students in the same class, the lighting, whether natural or artificial, and is this lighting sufficient or not enough, the nature of the wall paint old or modern, is it comfortable for sight, the blackboard if it is Good or exhausted, In addition to air-conditioning sets in summer and winter, this is on the one hand, and on the other hand, the school environment is outside the classes in general And being appropriate and encouraging for scientific and cognitive activities. All these vocabulary and others have a great impact on the authentication of the learning process and achieving its immediate and future goals. Likewise, class congestion impedes the use of educational facilities and school workshops in an appropriate manner, such as the library, laboratory, and computer, and adversely affects the implementation of practical activities accompanying some curricula, and this affects academic achievement. Therefore, the study deals with answering the following question: What is the effect of the physical environment and overcrowded classes on academic achievement? The current research aims to identify what the physical environment is in schools, whether schools provide students with a physical environment consistent with the requirements imposed by the educational process, the effect of classroom overcrowding on the academic achievement of students.
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An effort is made to study the effect of composite nanocoating using aluminum-9%wt silicon alloys reinforced with different percentage (0.5,1,2,4)wt.% of carbon nanotubes (CNTs) using plasma spraying. The effect of this composite on corrosion behavior for AA6061-T6 by extrapolation Tafel test in sea water 3.5wt% NaCl was invested. Many specimens where prepared from AA6061-T6 by the dimension (15x15x3)mm as this first set up and other steps include coating process, X-ray diffraction and SEM examination .The results show the CNTs increase the corrosion rate of the nanocomposite coatings with increasing the weight percentage of CNTs within the Al-Si matrix. Al-9wt%Si coating layer itself has less corrosion rate if compared with both n
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Molecular barcoding was widely recognized as a powerful tool for the identification of organisms during the past decade; the aim of this study is to use the molecular approach to identify the diatoms by using the environmental DNA. The diatom specimens were taken from Tigris River. The environmental DNA(e DNA) extraction and analysis of sequences using the Next Generation Sequencing (NGS) method showed the highest percentage of epipelic diatom genera including Achnanthidium minutissimum (Kützing) Czarnecki, 1994 (21.1%), Cocconeis placentula Ehrenberg, 1838 (21.3%) and Nitzschia palea (Kützing) W. Smith, 1856 (16.3%).
Five species of diatoms: Achnanthidiu
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Background: This study aimed to evaluate the outcome of long-term results of dacryocystorhinostomy (DCR) techniques in specialized eye care center in Iraq.
Subjects and Method: This is a prospective study of 650 patients from July 2014 to July 2019 with nasolacrimal duct obstruction in Ibn Al Haitham Eye Teaching Hospital. A preoperative questionnaire was done, then one month, three months, six months and one year postoperatively. The success of surgery defined as follow; Absence of epiphora completely, Resolve of dacryocele or mucocele or any new attack of daryocystitis, Appearance of fluorescein dye from nose in fluorescein disappearance test, Successful irriga
... Show MoreIn this work, Co-Y-oxide Nano Structure is successfully synthesized via hydrothermal method. The XRD analysis, SEM analysis, optical, electrical and photo sensing properties have been investigated for Co3O4 and Co-Y-oxide thin films. The X-ray diffraction (XRD) analysis reveals that all films are polycrystalline in nature, having cubic structure. The SEM images of thin films clearly indicates that Co3O4 possesses nanosphere like structure and flower like for Co-Y-oxide. The optical properties show that the optical energy gap follows allowed direct electronic transition calculated using Tauc equation and it increases for Co-Y-oxide. The photo sensing properties of thin films are investigated as a function of time at different wavelengths to
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Objective: The aim of the study to evaluate the nursing care management for diabetes mellitus patient
with total hip replacement after fractured hip.
Methodology: A field study carried out on patients with diabetes mellitus and have total hip
replacement after fractured hip in orthopedic ward at the hospital of surgical specialization (malefemale)during
January 2002 to January 2003.Physical and psychological nursing
assessment
immediately after the surgery was done for the both subjects (control and experimental) and then a
scientific management with daily nursing care were provided to the experimental subject with daily
nursing care to the patient condition by using a scientific and practical methods and leave th
ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel
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