The problem of slow learning in primary schools’ pupils is not a local or private one. It is also not related to a certain society other than others or has any relation to a particular culture, it is rather an international problem of global nature. It is one of the well-recognized issues in education field. Additionally, it is regarded as one of the old difficulties to which ancient people gave attention. It is discovered through the process of observing human behaviour and attempting to explain and predict it.
Through the work of the two researchers via frequent visits to primary schools that include special classes for slow learning pupils, in addition to the fact that one of the researcher has a child with slow learning issue, the researcher realized that there is a large number of pupils who suffer slow learning difficulty. The researchers carried out anexploratory experiment on over 20 teachers of special education, concluding that there is about 80% of slow learning pupils suffer from thinking skills deficiency.
The concept of thinking skills as pointed out by Debono (2003) is that they are mental skills that can be improved through exercise and learning. That can be done through preparing situations and creating a suitable system. That should lead to the acquisition og the knowledge and information on the part of the learner. This is supposed to lead the learner to the search for further knowledge of deeper nature, creating good learning. The concept of slow learning, on the other hand, is the child who suffer from a simple retardation qualification or a child of normal brain abilities, but for a certain reason takes a longer time in learning in comparison to his/her peers.
The current study aims at identifying thinking skills for fourth primary grade pupils. The study is limited to the number of 150 pupils of fourth primary grade who suffer from slow learning of male gender only. The researcher prepared a test to measure thinking skills for those pupils.
According to the results of the study the researcher reached a number of conclusions and suggestions.
Blood and urine samples were collected from 203 patients to study the relationship between Diabetes mellitus and urinary tract infections (UTI). Blood and urine specimens were subjected for estimation of random blood sugar, in addition to detection of the most pathogen bacteria which cause urinary tract infection in diabetic patients. The study included the detection of bacterial sensitivity to some antibiotics used in treating urinary tract infections, and also included the study of genetic basis which cause both types of diabetes mellitus. The results can be summarized as follows: The incidence of type ? diabetes in males was (35.8%), and (45.9%) in females . and type 2 diabetes in males was (49.6%), while in females was (40.16%).The inc
... Show Morehe public federal budget of the state includes estimated figures for state revenues and expenditures for the next fiscal year. The estimation process is one of the main parts of the preparation of the general budget of the state and the accuracy in the estimation of revenues and expenditures of the most important principles that should be based on the process of making estimates and should not overestimate the assessment process to ensure the availability of funds in the future in all cases, which lead to unfair distribution of allocations, so the research aims to study The case of preparing the budget in the Directorate and how to estimate the expenditure in, by the analysis of operating budgets and identify deviations in the implementa
... Show MoreExperimental measurements were done for characterizing current-voltage and power-voltage of two types of photovoltaic (PV) solar modules; monocrystalline silicon (mc-Si) and copper indium gallium di-selenide (CIGS). The conversion efficiency depends on many factors, such as irradiation and temperature. The assembling measures as a rule cause contrast in electrical boundaries, even in cells of a similar kind. Additionally, if the misfortunes because of cell associations in a module are considered, it is hard to track down two indistinguishable photovoltaic modules. This way, just the I-V, and P-V bends' trial estimation permit knowing the electrical boundaries of a photovoltaic gadget with accuracy. This measure
... Show MoreBackground: One of the major problems in endodontics is micro-leakage of root canal fillings which might contribute to the failure of endodontic treatment. To avoid this problem, a variety of sealers have been tested. The objective of this, in vitro, study was to evaluate the shear bond strength of four resin based sealers (AH plus, silver free AH26, RealSeal SE and Perma Evolution permanent root canal filling material) to dentin. Materials and Methods: Forty non-carious extracted lower premolars were used. The 2mm of the occlusal surfaces of teeth were sectioned, to expose the dentin surface. The exposed dentin surfaces of teeth were washed with 5ml of 2.5% NaOCl solution followed by 5ml of 17 % EDTA then rinsed by deionized water to remov
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Abstract:
We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.
In this research, I estimate the reliability function of cluster function by using the seemingly unrelate
... Show MoreThe main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model
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