The research is an attempt to investigate experimentally the influence of teacher’s errors correction and students’ errors correction on teaching English at the College of Physical Education for Women. Errors are seen as a natural way for developing any language but teachers are puzzled the way they can correct these errors. So, this research gives some idea of using two types of errors correction. The sample of the research is female students of the first year stage at the College of Physical Education for Women of the academic year 2009-2010. The whole population of the research is (94) students while the sample is (64). Thus, the sample represents 68% from the population of the research. The sample represents It is hypothesized that there are no significant differences between the experimental group which has been taught according students’ errors correction technique and the control group which has been taught according the teacher’s error correction technique in teaching English. To fulfill the aim of the research an experiment has been designed with two groups of (64) students chosen randomly from first year students. Both groups have matched in terms of age, the level of subjects’ achievement in previous year (the Baccalaureate Exam), and the academic type of study in the secondary school. The experiment lasted nine weeks. A post-test has been constructed in the last week for both groups after insuring its validity and reliability. After analyzing the results statistically, it has been found that there are significant differences between the two groups in their achievement in the test. Accordingly, the null hypothesis has been rejected. Finally, instructors are recommended to use students’ correction errors for developing their students’ achievement and knowledge in English language.
Background: Lateral sinus augmentation and simultaneous insertion of dental implants is a highlypredictable procedure and associated with high rate of implants success.Aims: To evaluate implant stability changes following maxillary sinus augmentation utilizing deproteinizedbovine bone alone or mixed with platelet-rich fibrin.Materials and Methods: A total of 34 lateral sinus augmentation procedures were performed and 50 dentalimplants simultaneously installed. The lateral sinus augmentation cases were allocated randomly into 3groups: Group A comprised 13 procedures and 21 dental implants utilizing solely deproteinized bovine bone.Group B involved 10 cases and 16 dental implants using deproteinized bovine bone mixed with leukocyteand
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In this work, multilayer nanostructures were prepared from two metal oxide thin films by dc reactive magnetron sputtering technique. These metal oxide were nickel oxide (NiO) and titanium dioxide (TiO2). The prepared nanostructures showed high structural purity as confirmed by the spectroscopic and structural characterization tests, mainly FTIR, XRD and EDX. This feature may be attributed to the fine control of operation parameters of dc reactive magnetron sputtering system as well as the preparation conditions using the same system. The nanostructures prepared in this work can be successfully used for the fabrication of nanodevices for photonics and optoelectronics requiring highly-pure nanomaterials.
In this study, the potential of adsorption of amoxicillin antibiotic (AMOX) from aqueous solutions using prepared activated carbon (AC) was studied. The used AC was prepared from an inexpensive and available precursor (sunflower seed hulls (SSH)) and activated by potassium hydroxide (KOH). The prepared AC was examined for its ability to remove AMOX from aqueous contaminated solutions and characterized with the aid of N2 -adsorption/desorption isotherm Brunauer–Emmett– Teller, scanning electron microscopy, energy-dispersive X-ray spectroscopy and Fourier-transform infrared. Zeta potential of the prepared activated carbon from sunflower seed hulls (SSHAC) were studied in relation to AMOX adsorption. The physical and chemical propert
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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The insulation system of a machine coil includes several layers made of materials with different characteristics. The effective insulation design of machine coils, especially in the machine end winding, depends upon an accurate model of the stress grading system. This paper proposes a modeling approach to predict the transient overvoltage, electric field, and heat generation in machine coils with a stress grading system, considering the variation of physical properties in the insulation layers. A non-uniform line model is used to divide the coil in different segments based on material properties and lengths: overhang, stress grading and slot. The cascaded connection of chain matrices is used to connect segments for the representation of the
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