This article uses coupled Eulerian–Lagrangian finite element algorithm to conduct a three-dimensional thermomechanical study to capture the shape and characteristics of defect type generated while achieving the dissimilar friction stir welding of aluminium alloys. The volume-of-fluid method is used to model the Eulerian region and predict the localised formation of process defects. Three different tool shapes are utilised to achieve the dissimilar friction stir welding joining between AA 2024-T3 on the advancing side and AA 6061-T6 on the retreating side. Process parameter effects such as rotational tool speed, traverse tool speed and tool tilt angle are also investigated. The finite element model results are validated by comparing with t

conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation. 

Logic in the philosophy of ethical behavior in business organizations

In this paper the definition of fuzzy normed space is recalled and its basic properties. Then the definition of fuzzy compact operator from fuzzy normed space into another fuzzy normed space is introduced after that the proof of an operator is fuzzy compact if and only if the image of any fuzzy bounded sequence contains a convergent subsequence is given. At this point the basic properties of the vector space FC(V,U)of all fuzzy compact linear operators are investigated such as when U is complete and the sequence ( ) of fuzzy compact operators converges to an operator T then T must be fuzzy compact. Furthermore we see that when T is a fuzzy compact operator and S is a fuzzy bounded operator then the composition TS and ST are fuzzy compact

Enamel White Spot Lesions (EWSLs) are a common dental condition characterized by being opaque or chalky white in appearance. In this review, an overview of the etiology, prevention, and treatment techniques for EWSLs is presented. Enamel demineralization caused by bacteria in dental plaque which releases acids upon the consumption of fermentable carbohydrates causing mineral loss is thought to be the main cause of those lesions, which could be predisposed through orthodontic treatment, poor diet, inadequate oral hygiene and certain medical conditions. So, sustaining an adequate carbohydrate consumption, proper fluoride exposure and good oral hygiene are some of the practices which aid in these lesions’ prevention. Although the suc

In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp