This paper discusses the Sums of Squares of “m” consecutive Woodall Numbers. These discussions are made from the definition of Woodall numbers. Also learn the comparability of Woodall numbers and other special numbers. An attempt to communicate the formula for the sums of squares of ‘m’ Woodall numbers and its matrix form are discussed. Further, this study expresses some more correlations between Woodall numbers and other special numbers.

The discussion in this paper gives several theorems and lemmas on the Sums of Squares of  consecutive Carol Numbers. These theorems are proved by using the definition of carol numbers and mathematical induction method. Here the matrix form and the recursive form of sum of squares of  consecutive Carol numbers is also given. The properties of the Carol numbers are also derived.

Thisstudy aims to determine the specifications of obese women accordingto the heightand type of obesity. It also aimstoidentify the significance of differences in choosing ready-made clothes for the research sample. Finally, the significance of differences in choosing ready-made clothes according to the variable of binaryclassification ofobesity is also identified.The study sample includes obese women: employees, non-employees and students with the age group (18-50) years.The weights and lengths of the sample have been taken to suit the group of obese women.Aquestionnaire in the form of an open question was distributed among (50) obese womenso as to extract the items of the questionnaire. After that, the questionnaire was distributed amo

The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati

        A newly developed analytical method was conducted for the determination of Ketotifen fumarate (KTF) in pharmaceuticals drugs via quenching of continuous fluorescence of 9(10H)-Acridone (ACD). The method was applied using flow injection system of a new homemade ISNAG fluorimeter with fluorescence measurements at ± 90◦ via 2×4 solar cell. The calibration graph was linear in the range of 1-45 mmol/L, with correlation coefficient r = 0.9762 and the limit of detection 29.785 µg/sample from the stepwise dilution for the minimum concentration in the linear dynamic ranged of the calibration graph. The method was successfully applied to the determination of Ketotifen fumarate in two different pharma

     This research aims to investigate the color distribution of a huge sample of 613654 galaxies from the Sloan Digital Sky Survey (SDSS). Those galaxies are at a redshift of 0.001 - 0.5 and have magnitudes of g = 17 - 20. Five subsamples of galaxies at redshifts of (0.001 - 0.1), (0.1 - 0.2), (0.2 - 0.3), (0.3 - 0.4) and (0.4 - 0.5) have been extracted from the main sample. The color distributions (u-g), (g-r) and (u-r) have been produced and analysed using a Matlab code for the main sample as well as all five subsamples. Then a bimodal Gaussian fit to color distributions of data that have been carried out using minimum chi-square in Microsoft Office Excel. The results showed that the color distributions of the main sample and

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

    New class A^* (a,c,k,β,α,γ,μ)  is introduced of meromorphic univalent functions with positive coefficient f(z)=â–¡(1/z)+∑_(n=1)^∞▒〖a_n z^n 〗,(a_n≥0,z∈U^*,∀ n∈ N={1,2,3,…}) defined by the integral operator in the punctured unit disc U^*={z∈C∶0<|z|<1}, satisfying |(z^2 (I^k (L^* (a,c)f(z)))^''+2z(I^k (L^* (a,c)f(z)))^')/(βz(I^k (L^* (a,c)f(z)))^''-α(1+γ)z(I^k (L^* (a,c)f(z)))^' )|<μ,(0<μ≤1,0≤α,γ<1,0<β≤1/2 ,k=1,2,3,… ) . Several properties were studied like coefficient estimates, convex set and weighted mean.