Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.
As a result of the development and global openness and the possibility of companies providing their services outside their spatial boundaries that were determined by them, and the transformation of the world due to the development of the means of communication into a large global market that accommodates all products from different regions and of the same type and production field, competition resulted between companies, and the race to obtain the largest market share It ensures the largest amount of profits, and it is natural for the advertising promotion by companies for their product to shift from an advertisement for one product to a competitive advertisement that calls on the recipient to leave the competing product and switch to it
... Show MoreThe advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of state-of-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages
... Show MoreIn this paper, the methods of weighted residuals: Collocation Method (CM), Least Squares Method (LSM) and Galerkin Method (GM) are used to solve the thin film flow (TFF) equation. The weighted residual methods were implemented to get an approximate solution to the TFF equation. The accuracy of the obtained results is checked by calculating the maximum error remainder functions (MER). Moreover, the outcomes were examined in comparison with the 4th-order Runge-Kutta method (RK4) and good agreements have been achieved. All the evaluations have been successfully implemented by using the computer system Mathematica®10.
Some cases of common fixed point theory for classes of generalized nonexpansive maps are studied. Also, we show that the Picard-Mann scheme can be employed to approximate the unique solution of a mixed-type Volterra-Fredholm functional nonlinear integral equation.
In this work, calculation of pressure losses in circulating system for two drilling muds is evaluated in Noor oil field. Two types of drilling muds that were used for drilling section 12 1/4" and 8 3/4" which are Salt saturated mud and Ferro Chrome Lignosulfonate-Chrome Lignite mud. These calculations are based on field data that were gathered from the drilling site of well Noor-15, which are included, rheological data, flow data and specification of drill string. Based on the obtained results, the best rheological model that fit their data is the Herschel-Bulkley model according to correlation coefficient value for their two drilling mud. Also, the difference between the calculated pressure lo
... Show MoreOne hundred Ninty two s mples were collected from (Cooling towers) between the period 1 /l/2004-13/12/2005. The Results Rev a)ecL that physical and chemic:a) analysefor watr samples including Tempera re,, pH and cWodde concentration ranges were f01:md
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