This paper reports an experimental study of welding of dissimilar materials between transparent Polymethylmethacrylate (PMMA) and stainless steel 304 sheets using a pulsed mode Nd:YAG laser. The process was carried out for two cases; laser transmission joining (LTJ) and conduction joining (CJ). The former is achieved when the joint is irradiated from the polymer side and the latter when the joint is irradiated from the opposite side (metal side). The light and process parameters represented by the peak power (Pp), pulse duration (τ), pulse repetition rate (PRR), scanning speed (ν) and pulse shape have a significant effect on the joint strength (Fb), joint bead width (b), joint quality and appearance. The optimum parameters were determined

BACKGROUND: Diabetes Mellitus is a complex chronic illness that has increased significantly around the world and is expected to affect 628 million in 2045. Undiagnosed type 2 diabetes may affect 24% - 62% of the people with diabetes; while the prevalence of prediabetes is estimated to be 470 million cases by 2030. AIM OF STUDY: To find the percentage of undiagnosed diabetes and prediabetes in a slice of people aged ≥ 45years, and relate it with age, gender, central obesity, hypertension, and family history of diabetes. METHODS: A cross sectional study that included 712 healthy individuals living in Baghdad who accepted to take part in this study and fulfilling the inclusion and exclusion criteria.

The current study aims to assess the ethical behavior among female students who are using a social media network in addition to describe the variables of interest (social media use and ethical behavior) among participants, in which to find out the effects of social media on the ethical behavior of high school female students. A quantitative approach was adopted to collect the relevant data for the study, six schools included in this study from the six directorates of education in Baghdad city. Subsequently, SPSS software was applied to analyze the relevant data of the study. To achieve the research objectives, a questionnaire was composed of three sections: Part I: deals with the student's demographic information. Part II: deals with inf

This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to

ABSTRUCT

In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

The research aimed to modeling a structural equation for tourist attraction factors in Asir Region. The research population is the people in the region, and a simple random sample of 332 individuals were selected. The factor analysis as a reliable statistical method in this phenomenon was used to modeling and testing the structural model of tourism, and analyzing the data by using SPSS and AMOS statistical computerized programs. The study reached a number of results, the most important of them are: the tourist attraction factors model consists of five factors which explain 69.3% of the total variance. These are: the provision of tourist services, social and historic factors, mountains, weather and natural parks. And the differenc