Background: Obesity represents a clear and
present danger to the health of children and
adolescents. Its prevalence among American
youth has doubled in the past 3 decades, and
there are now more overweight and obese
adults in the United States than adults of
normal weight.
Objectives of the study:
1- Finding whether screen watching among
adolescents has an effect on increasing
prevalence overweight and obesity.
2- The effect of other variables like physical
activity, eating in front of screen, eating under
stress on obesity and overweight among the
subjects sample.
Patients &Methods: During 3 months period a
cross sectional survey was conducted on 4
high schools at Baghdad with total sample of
500 subjects using time table to assess screen
watching hours per week,
Results:Higher percentagesof overweight &
obesity were found among female adolescents
than males, significant associations was
obvious among total sample & male sample
betweenthe level of physical activity &
BMI,while there was no significant
association among female sample for the same
variables , There was obvious significant
association between BMI a time spending in
screen watching, eatingin front of screen, ,
eating under stressin the total & male samples.
Conclusion: Increased levels of physical
activity are associated with a lower BMI and
less time spent on screen watching .in addition
.stress-induced eating may be one factor
contributing to the development of obesity;
furthermore habits like eating in front of
screen could increase BMI of an adolescent.
A cantilever beam is made from composite material which is consist of (matrix: polyester) and (particles: Silicon-Carbide) with different volume fraction of particles. A force is applied at the free end of beam with different values. The experimental maximum deflection of beam which occurs at the point of the applied load is recorded. The deflection and slope of beam are analyzed by using FEM modeling. MATLAB paltform is built to assemble the equations, vector and matrix of FEM and solving the unknown variables (deflection and slope) at each node. Also ANSYS platform is used to modeling beam in finite element and solve the problem. The numerical methods are used to compare the results with the theoretical and experimental data. A good ag
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Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of
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