This work aims to provide a statistical analysis of metal removal during the Magnetic Abrasive Finishing process (MAF) and find out the mathematical model which describes the relationship between the process parameters and metal removal, also estimate the impact of the parameters on metal removal. In this study, the single point incremental forming was used to form the truncated cone made of low carbon steel (1008-AISI) based on the Z-level tool path. Then the finishing was accomplished using a magnetic abrasive process based on the Box-Behnken design of the experiment using Minitab 17 software was used to finish the surface of the formed truncated cone. The influences of different parameters (feed rate, machining step size, coil current, and spindle speed) on metal removal were (32.948, 21.896, 10.587, and 13.907) %, respectively.
This work presents an experimental study of heat transfer and flow of distilled water and metal oxide nanofluid Fe3O4-distilled water at concentrations of (φ = 0.3, 0.6, 0.9 %) by volume in a horizontal pipe with constant magnetic field. All the tests are carried out with Reynolds number range (2900-9820) and uniform heat flux (11262-19562 W/m2). The results show that, the nanofluid concentration and magnetic intensity increase, the Nusselt number increases. The maximum enhancement in Nusselt number with magnetic nanofluid is (5.4 %, 26.4 %, 42.7 %) for volume concentration (0.3, 0.6, 0.9 %) respectively. The enhancement is maximized with magnetic intensity (0.1, 0.2, 0.3 tesla) respectively to (43.9, 44
... Show MoreWe propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St
... Show MoreThis study was carried out to study effect of magnetic water ( M0 and M) and different concentrations of coconut extract in Fragaria x ananassa (Duch) C.V Festival. The results showed significant differences in the plants treated with magnetic water ( 0.12 Tesla) and different concentrations of coconut extract C1 (0%), C2 (2.5%), C3 (5%), C4 (7.5%) and C5 (10%) in vegetative parameters as in leaf area and chlorophyll in treatment M0C3 was (53.72 Dcm2, 50.00), respectively, highest leaf number and plant dry weight in MC4 (12.77,14.22 gm), respectively. Results recorded significant differences in fruit parameters such as weight in MC1 (18.97 gm). The maximum fruit number was in MC3 (110), the greatest fruit size was in MC4 (15.78 cm3) and the
... Show MoreThis research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram, and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods.
Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.
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This study is studied one method of estimation and testing parameters mediating variables in a structural equations model SEM is causal steps method, in order to identify and know the variables that have indirect effects by estimating and testing mediation variables parameters by the above way and then applied to Iraq Women Integrated Social and Health Survey (I-WISH) for year 2011 from the Ministry of planning - Central statistical organization to identify if the variables having the effect of mediation in the model by the step causal methods by using AMOS program V.23, it was the independent variable X represents a phenomenon studied (cultural case of the
This research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods
