In the present paper, by making use of the new generalized operator, some results of third order differential subordination and differential superordination consequence for analytic functions are obtained. Also, some sandwich-type theorems are presented.

The present study describes employing zero-, 1st - and 2nd -order derivative spectrophotometric methods have been developed for determination of lorazepam (LORA) and clonazepam (CLON) in commercially available tablets. LORA was determined by means of 1st (D1), 2nd (D2) derivative spectrophotometric techniques using zero cross, peak height, and Peak area. D1 used for the determination of CLON by using zero cross and peak height while D2 (zero cross) was used for the determination of CLON. The method was established to be linear in concentration containing different ratios of LORA and CLON range of (20-200 mg/L) and (5-35 mg/L) at wavelength range (250 -370 nm), (210-370nm) respectively. The proposed techniques are highly sensitive, precise a

The main work of this paper is devoted to a new technique of constructing approximated solutions for linear delay differential equations using the basis functions power series functions with the aid of Weighted residual methods (collocations method, Galerkin’s method and least square method).

Abstract The concept of quantum transition is based on the completion of a succession of time dependent (TD) perturbation theories in Quantum mechanics (QM). The kinetics of "quantum" transition, which are dictated by the coupled motions of a lightweight electrons and very massive nuclei, are inherent by nature in chemical and molecular physics, and the sequence of TD perturbation theory become unique. The first way involved adding an additional assumption into molecule quantum theory in the shape of the Franck-Condon rule, which use the isothermal approach. The author developed the second strategy, which involved injecting chaos to dampen the unique dynamically of the bonding movement of electrons and nuclei in the intermediary state of

In this paper, we deal with the problem of general matching of two images one of them has experienced geometrical transformations, to find the correspondence between two images. We develop the invariant moments for traditional techniques (moments of inertia) with new approach to enhance the performance for these methods. We test various projections directional moments, to extract the difference between Block Distance Moment (BDM) and evaluate their reliability. Three adaptive strategies are shown for projections directional moments, that are raster (vertical and horizontal) projection, Fan-Bean projection and new projection procedure that is the square projection method. Our paper started with the description of a new algorithm that is low

This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters (as done in the first edition 2019). Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. While the revised new chapters have been added (as the curr

This Book is the second edition that intended to be textbook studied for undergraduate/ postgraduate course in mathematical statistics. In order to achieve the goals of the book, it is divided into the following chapters. Chapter One introduces events and probability review. Chapter Two devotes to random variables in their two types: discrete and continuous with definitions of probability mass function, probability density function and cumulative distribution function as well. Chapter Three discusses mathematical expectation with its special types such as: moments, moment generating function and other related topics. Chapter Four deals with some special discrete distributions: (Discrete Uniform, Bernoulli, Binomial, Poisson, Geometric, Neg

This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters (as done in the first edition 2019). Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. While the revised new chapters have been added (as the curr