Abstract---The aim of the current research is to identify the level of logical reasoning skills in chemistry students at the Faculty of Education for Pure Sciences/ Ibn Al-Haytham for the academic year (2021-2022). The differences in their level of skills according to the gender variable (males and females) and the academic stages (first- second - third - fourth). The descriptive approach was adopted because it corresponds to the nature of the research objectives. The research sample consisted of (400 )students selected in a relatively random stratified way. The researcher constructed a logical reasoning test, which includes (6) sub-skills , which is (proportional - probabilistic- synthetic- deductive- logic- variable adjustment). The psychometric properties of the test were also verified from face validity, discriminatory power , item difficulty index , and the relationship between the items score and the total degree of the test. Statistical methods were used in the Cronbach equation, the Spearman-Brown equation, (SPSS+22) . Pearson correlation coefficient, one sample T-test, two independent samples T-test , mono-variance analysis- Chevy test). The results that were reached showed that the students of the Chemistry Department have an average level of reasoning skills (proportional- probabilistic- synthetic) more than other skills and that males are superior to females in all reasoning skills. The results also showed that fourth stage students are superior than students in other stages in all reasoning skills. In the placement of the results that have been reached, the current research recommended the need to develop the curricula in general for all stages of study and work to include various training in reasoning 7007 skills and the need for guidance by officials and supervisors on the use of modern teaching methods and to move away from methods of memorization and indoctrination that make the student a recipient of information without interest in stimulating thinking. Keywords---logical reasoning skills, piaget theory, cognitive development theory, chemistry students.
This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).
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The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita
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Gingival crevicular fluid (GCF) may reflect the events associated with orthodontic tooth movement. Attempts have been conducted to identify biomarkers reflecting optimum orthodontic force, unwanted sequallea (i.e. root resorption) and accelerated tooth movement. The aim of the present study is to find out a standardized GCF collection, storage and total protein extraction method from apparently healthy gingival sites with orthodontics that is compatible with further high-throughput proteomics. Eighteen patients who required extractions of both maxillary first premolars were recruited in this study. These teeth were randomly assigned to either heavy (225g) or light force (25g), and their site specific GCF was collected at baseline and aft
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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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This paper proposes a novel finite-time generalized proportional integral observer (FTGPIO) based a sliding mode control (SMC) scheme for the tracking control problem of high order uncertain systems subject to fast time-varying disturbances. For this purpose, the construction of the controller consists of two consecutive steps. First, the novel FTGPIO is designed to observe unmeasurable plant dynamics states and disturbance with its higher time derivatives in finite time rather than infinite time as in the standard GPIO. In the FTGPO estimator, the finite time convergence rate of estimations is well achieved, whereas the convergence rate of estimations by classical GPIO is asymptotic and slow. Secondly, on the basis of the finite and fast e
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Lower extremity exoskeletons can assist with performing particular functions such as gait assistance, and physical therapy support for subjects who have lost the ability to walk. This paper presents the analysis and evaluation of lightweight and adjustable two degrees of freedom, quasi-passive lower limb device to improve gait rehabilitation. The exoskeleton consists of a high torque DC motor mounted on a metal plate above the hip joint, and a link that transmits assistance torque from the motor to the thigh. The knee joint is passively actuated by spring installed parallel with the joint. The action of the passive component (spring) is combined with mechanical output of the motor to provide a good control on the designed exoskeleton whi
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Friction stir spot welding (FSSW) is a relatively new welding process that may have significant advantages compared to the fusion processes as follows joining of conventionally non-fusion weldable alloys, reduced distortion and improved mechanical properties of weldable alloys joints due to the pure solidstate joining of metals. In this paper, a three-dimensional model based on finite element analysis is used to study the thermal history in the spot-welding of aluminum alloy 2024. The model take place the thermomechanical property on the process of the welded metals. The thermal history and the evolution results with numerical model at the measured point in the friction stirred spot weld have a good matching, then the prediction of the t
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