The parameters of resistance spot welding (RSW) performed on low strength commercial aluminum sheets are investigated experimentally, the performance requirements and weldability issues were driven the choice of a specific aluminum alloy that was AA1050. RSW aluminum alloys has a major problem of inconsistent quality from weld to weld comparing with welding steel
alloys sheet, due to the higher thermal conductivity, higher thermal expansion, narrow plastic temperature range, and lower electrical resistivity. Much effort has been devoted to the study of describing the relation between the parameters of the process (welding current, welding time, and electrode force) and weld strength. Shear-tensile strength tests were performed to indicate the weld
quality. A weld lobe diagrams were constructed to evaluate the weldability of three sheet thicknesses of this alloy. Most appropriate welding time and electrode force are 5 cycles and 1.75- 2.25 kN respectively. The ranges of the weldability are 14-28, 18-30, and 22-32 kA for 0.6, 1.0, and 1.5 mm sheet thicknesses respectively. A statistical regression analysis was used to demonstrate the
relationship of the process parameters and the strength of the weldments. Two empirical equations for each thickness were proposed to estimate the shear tensile strength of the weldments, one for quadratic and the other linear relationship between the process parameters and the strength. There are no significant differences between the equations when applied to the available data.
This article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.
Abstract:
The use of economic resources enjoyed Iraq by especially oil resources, which constitute the main source of financial revenue, would the economic surplus outside the oil sector increases by mobilizing and rallying the labor power and turn it into an access capitalism, , was the cause of "the inaction of the productive sectors of the economy, made the investment planning process and even investment in human capital was not rationality with the increasing number of unemployed, particularly certificates and specializations high campaign, direction of the government towards market liberalism after 2003 through the, was focused not follow a clear economic policies, and the absence of planning
... Show MoreThis study was designed to show the advantages of using the combination of metformin and rosiglitazone over using each drug alone in treatment of women with polycystic ovary syndrome (PCOS).Forty four women with PCOS were classified into 3 groups , group 1 received rosiglitazone (4mg/day) for 3 months , group ΙΙ received metformin ( 1500 mg/day)for three months and groupΙΙΙ received the combination ( rosiglitazone 4mg/day + metformin 1500 mg/day) for the same period of treatment . The blood samples were drawn before treatment and after 3 months of treatment . The fasting serum glucose , insulin , progesterone , testosterone , leutinizing hormone were measure
... Show MoreThe auditory system can suffer from exposure to loud noise and human health can be affected. Traffic noise is a primary contributor to noise pollution. To measure the noise levels, 3 variables were examined at 25 locations. It was found that the main factors that determine the increase in noise level are traffic volume, vehicle speed, and road functional class. The data have been taken during three different periods per day so that they represent and cover the traffic noise of the city during heavy traffic flow conditions. Analysis of traffic noise prediction was conducted using a simple linear regression model to accurately predict the equivalent continuous sound level. The difference between the predicted and the measured noise shows that
... Show MoreObjective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.
Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are
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