On Kolmogorov Complexity of Unitary Transformations in Quantum Computing

A Second Derivative Block Method Derived from a Family of Modified Backward Differentiation Formula (BDF) Type for Solving Stiff Ordinary Differential Equations

Equiprime Ideals and Equiprime Semimodules in Boolean Like Semirings

Numerical Solution of Temperature Profile in Annulus

Mathematical Modelling of EOR Methods

An Introduction to Various Types of Mathematics Teaching Aids

A Simple Method of Numerical Integration for a Class of Singularly Perturbed Two Point Boundary Value Problems

A New Approach to Variant Assignment Problem

A Homotopy Based Method for Nonlinear Fredholm Integral Equations

Proof of Beal's Conjecture and Fermat Last Theorem using Contra Positive Method

Trichotomy–Squared – A Novel Mixed Methods Test and Research Procedure Designed to Analyze, Transform, and Compare Qualitative and Quantitative Data for Education Scientists who are Administrators, Practitioners, Teachers, and Technologists

Algorithmic Triangulation Metrics for Innovative Data Transformation: Defining the Application Process of the Tri–Squared Test

A New Hilbert-Type Inequality In Whole Plane With The Homogeneous Kernel Of Degree 0

Surfaces in R

^{3}with densityIntroducing Trinova: “Trichotomous Nomographical Variance” a Post Hoc Advanced Statistical Test of Between and Within Group Variances of Trichotomous Categorical and Outcome Variables of a Significant Tri–Squared Test

Associate Professor, Department of Curriculum and Instruction, North Carolina Central University, USA.

This monograph provides an epistemological rational for novel “Trichotomous Covariance” statistic represented by the acronym [“TRICOVA”]. This new statistic is an innovative in depth way of investigating a Post Hoc Tri–Squared Test as an advanced data analytical methodology. TRICOVA is a detailed statistical procedure for the internal testing of the outcomes of a significant transformation of qualitative data into quantitative outcomes through the Tri–Squared Test (first introduced in the i-manager’s Journal on Mathematics, and detailed further in the Journal on Educational Technology, Journal on School Educational Technology, and in the Journal on Educational Psychology). TRICOVA as an advanced statistical procedure; is designed to measure the overall size of the movement (or change) between inputted and outputted Tri–Squared variables. It is also designed to identify the magnitude and type of covariant relationship in existence between Tri–Squared Test qualitative and quantitative variables. This new innovative approach to the advanced statistical post hoc metrics of the Tri–Squared Test adds an additional layer of richness and insight into the inner workings of the Tri–Squared Test. It also adds considerable value to the mixed methods approach of research design that involves the holistic combination and comparison of qualitative and quantitative data outcomes. Two TRICOVA equations are presented as well as the entire process of advanced statistical Tri–Covariance analytics that display how to conduct Trichotomous Covariance inquiry.

* Assistant Professor, Department of General Requirements, College of Applied Sciences, Nizwa, Oman.

** Lecturer, Department of Information Technology, College of Technology, Nizwa ,Oman.

In this computational research paper, the authors have synchronized the Three Dimensional Cancer Model (TDCM) with Chen System (CS) using a Robust Adaptive Sliding Mode Controller (RASMC) together with uncertainties, external disturbances and fully unknown parameters. A simple suitable sliding surface, which includes synchronization errors, is constructed and appropriate update laws are used to tackle the uncertainties, external disturbances and unknown parameters. All simulations to achieve the synchronization for the proposed technique for the two non-identical systems under consideration are being done using Mathematica. Furthermore, application to secure communication is also demonstrated on tumor cells.

* Professor, Foshan University, Foshan, Guangdong, China.

** Professor and Executive Director, Foshan University, Foshan, Guangdong, China.

Hilbert-type inequalities are important in analysis and its applications. In recent years, some authors have studied and published a few Hilbert-type multiple integral inequalities, which are hard and interesting. In this paper, by estimating the weight function and technique of real analysis, the authors give a new multiple Hilbert-type integral inequality with a non-Homogeneous form as, F(x,y) f(x)g(y)dxdy < K f g (p >1). The best possible Rn+ x Rn+ p,w q,w constant factor is given, and the equivalent form is also considered. Many particular cases of Hilbert-type integral inequality with a non-homogeneous form are included. As its applications, the authors have considered some particular results.

Lecturer, Department of Mathematics, Government Degree College, Kadapa, Andhra Pradesh, India.

Free convective oscillatory mass transfer flow past an infinite vertical porous plate with heat and mass fluxes in the presence of uniform magnetic field and heat generation through porous medium is analytically investigated. Effects of radiation and viscous dissipation on the unsteady two-dimensional flow of a viscous incompressible, electrically conducting with optical thin gray fluid are considered. Approximate solutions have been derived from the velocity, temperature and concertation fields, coefficient of skin-friction, Nusselt number and Sherwood number using multi-parameter perturbation technique. It is observed that the increase in radiation parameter decreases the both velocity and temperature.

** Accademic Consultant, Department of Statistics, Sri Venkadeswara University, Tirupati, India.

*** Assistant Professor, Department of Statistics, Sri Venkadeswara University, Tirupati, India.

**** Vice Principal, Department of Statistics, Sri Venkadeswara University, Tirupati, India

Now-a-days intraday time series models are playing a wide role in various sectors like wind speed data, temperature data, sensex data etc. In this paper, the authors have introduced a new exponential smoothing model and Auto Regressive Moving Average (ARMA) models for intraday data. These two models are empirically tested using wind speed data of Gadanki, Chittoor District. Between these two models which model is better performed and the wind speed data is tested using Root Mean Square Error (RMSE). Kolmogorov Smirnov test is used for goodness of fit. Among the compared 25 ARMA models and new exponential smoothing model, RMSE of new exponential smoothing model is low. Therefore, the authors have concluded that, the new exponential smoothing model is the best model for wind speed data of Gadanki.