This study focuses on the writing skill which is a social act .Students need to express
themselves in writing, but students of History and Geography departments are poor in
writing. This study aims at identifying and classifying the errors committed by the
students, and then giving remedies.
Writing can be considered as a channel or as a goal of language learning.
Students learn to write in a foreign language. Writing as a goal basically focuses on
the development of writing skills to fulfill such purposes as note-taking, summarizing,
narrating, reporting and replying required for various real-life situation
(Mechalakelli,2007)
Students at Departments of Geography and History study English as a part of
their syllabus requirement in the College of Education for Women. The researcher
realizes that it is important to improve students' skills in writing because it is an
important tool to their profession and for further education in the future. Therefore,
this study is an attempt to evaluate the writing skills of the second class evening
students (History and Geography)Departments.
The students are asked to write a paragraph on topics based on their reading
passages, chosen from their prescribed textbooks. They had been trained to construct
a well- organized paragraph in their preparatory schools for three years until their
graduation. Hence, the study attempts to find the students' errors in their writing in
English.
In order to scrutinize the impact of the decoration of Sc upon the sensing performance of an XN nanotube (X = Al or Ga, and XNNT) in detecting sarin (SN), the density functionals M06-2X, τ-HCTHhyb, and B3LYP were utilized. The interaction of the pristine XNNT with SN was a physical adsorption with the sensing response (SR) of approximately 5.4. Decoration of the Sc metal into the surface of the AlN and GaN led to an increase in the adsorption energy of SN from −3.4 to −18.9, and −3.8 to −20.1 kcal/mol, respectively. Also, there was a significant increase in the corresponding SR to 38.0 and 100.5, the sensitivity of metal decorated XNNT (metal@XNNT) is increased. So, we found that Sc-decorating more increases the sensitivity of GaNN
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Background: Painful elbow joint over the lateral epicondyle especially with resisted wrist extension are common signs of lateral epicondyle tendinopathy, also called tennis elbow.
Objective: To evaluate the clinical outcome of local platelet rich plasma (PRP) injection in patients with chronic tennis elbow compared with a steroid (Depomedrol 40 mg) injection.
Methods: A total of 88 patients with chronic tennis elbow were treated at Al-Kindy Teaching Hospital and private clinics. All patients had chronic pain for about 24 weeks or more and had failed first line treatment. The patients dividing into two groups, Group A injected with PRP (n = 44), and group B injected with d
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In the present work the Buildup factor for gamma rays were studied in shields from epoxy reinforced by lead powder and by aluminum powder, for NaI(Tl) scintillation detector size ( ×? ), using two radioactive sources (Co-60 and Cs-137). The shields which are used (epoxy reinforced by lead powder with concentration (10-60)% and epoxy reinforced by aluminum powder with concentration (10-50)% by thick (6mm) and epoxy reinforced by lead powder with concentration (50%) with thick (2,4,6,8,10)mm. The experimental results show that: The linear absorption factor and Buildup factor increase with increase the concentration for the powders which used in reinforcement and high for aluminum powder than the lead powder and decrease with inc
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This study presents a practical method for solving fractional order delay variational problems. The fractional derivative is given in the Caputo sense. The suggested approach is based on the Laplace transform and the shifted Legendre polynomials by approximating the candidate function by the shifted Legendre series with unknown coefficients yet to be determined. The proposed method converts the fractional order delay variational problem into a set of (n ＋ 1) algebraic equations, where the solution to the resultant equation provides us the unknown coefficients of the terminated series that have been utilized to approximate the solution to the considered variational problem. Illustrative examples are given to show that the recommended appro
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This paper is concerned with combining two different transforms to present a new joint transform FHET and its inverse transform IFHET. Also, the most important property of FHET was concluded and proved, which is called the finite Hankel – Elzaki transforms of the Bessel differential operator property, this property was discussed for two different boundary conditions, Dirichlet and Robin. Where the importance of this property is shown by solving axisymmetric partial differential equations and transitioning to an algebraic equation directly. Also, the joint Finite Hankel-Elzaki transform method was applied in solving a mathematical-physical problem, which is the Hotdog Problem. A steady state which does not depend on time was discussed f
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This paper deals with the modeling of a preventive maintenance strategy applied to a single-unit system subject to random failures.
According to this policy, the system is subjected to imperfect periodic preventive maintenance restoring it to ‘as good as new’ with probability
p and leaving it at state ‘as bad as old’ with probability q. Imperfect repairs are performed following failures occurring between consecutive
preventive maintenance actions, i.e the times between failures follow a decreasing quasi-renewal process with parameter a. Considering the
average durations of the preventive and corrective maintenance actions a
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In this work, a novel design for the NiO/TiO2 heterojunction solar cells is presented. Highly-pure nanopowders prepared by dc reactive magnetron sputtering technique were used to form the heterojunctions. The electrical characteristics of the proposed design were compared to those of a conventional thin film heterojunction design prepared by the same technique. A higher efficiency of 300% was achieved by the proposed design. This attempt can be considered as the first to fabricate solar cells from highly-pure nanopowders of two different semiconductors.
Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
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