Abstract

   The method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.

In this, search th

Thermal pyrolysis kinetics of virgin high-density polyethylene (HDPE) was investigated. Thermal pyrolysis of HDPE was performed using a thermogravimetric analyzer in nitrogen atmosphere under non-isothermal conditions at different heating rates 4, 7, 10 °C/min. First-order decomposition reaction was assumed, and for the kinetic analysis Kissinger-Akahira-Sunose(KAS), Flynn-Wall-Ozawa(FWO) and Coats and Redfern(CR) method were used. The obtained values of  average activation energy by the KAS and FWO methods were equal to137.43 and 141.52 kJ/mol respectively, these values were considered in good agreement, where the  average activation energy value obtained by CR equation methods was slightly different which equal to 153.16 kJ/

      In the current study, the observations depended on some nuclear properties of Germanium isotopes that are used for multiple purposes by studying transverse sections when interacting with charged particles such as alpha and proton particles and their interaction with gamma rays of conjugal isotopes relative to the stability of the nucleus with other nuclei. By calculating the cross sections of the  (α, )   ,  (γ,x)0-NN-1, (γ,2n)  , (α,p)  reactions of  isotope. Nuclear reactions in the newer global libraries (EXFOR, ENDF, JEF, JEFF, GENDL) have been published to identify appropriate energies in calculating the inverse nuclear re

The aesthetic contents of data visualization is one of the contemporary areas through which data scientists and designers have been able to link data to humans, and even after reaching successful attempts to model data visualization, it wasn't clear how that reveals how it contributed to choosing the aesthetic content as an input to humanize these models, so the goal of the current research is to use The analytical descriptive approach aims to identify the aesthetic contents in data visualization, which the researchers interpreted through pragmatic philosophy and Kantian philosophy, and analyze a sample of data visualization models to reveal the aesthetic entrances in them to explain how to humanize them. The two researchers reached seve

A stochastic process {Xk, k = 1, 2, ...} is a doubly geometric stochastic process if there exists the ratio (a > 0) and the positive function (h(k) > 0), so that {α 1 h-k }; k ak X k = 1, 2, ... is a generalization of a geometric stochastic process. This process is stochastically monotone and can be used to model a point process with multiple trends. In this paper, we use nonparametric methods to investigate statistical inference for doubly geometric stochastic processes. A graphical technique for determining whether a process is in agreement with a doubly geometric stochastic process is proposed. Further, we can estimate the parameters a, b, μ and σ2 of the doubly geometric stochastic process by using the least squares estimate for Xk a

يرغب المرء أن يعيش في منزل يعبر عن اصالة تصميمه ذا اهداف جمالية كحاجته الى تحقيق الأهداف العملية. وعليه فمن الأهمية بمكان ان يشارك أصحابه مع المعنيين[1] بشؤون التصميم... وهنا ارتأت الباحثة ان تقوم بدراسة علمية حديثة حول ورق الجدران ثلاثي الابعاد وتوظيفة في غرفة المعيشة, وباسلوب عصري حديث يجمع بين جمالية التصميم والحداثة , إضافة الى تناول الإضاءة لما لها من دور في ابراز معالم وتفاصيل الأثاث

In this study, a mathematical model for the kinetics of solute transport in liquid membrane systems (LMSs) has been formulated. This model merged the mechanisms of consecutive and reversible processes with a “semi-derived” diffusion expression, resulting in equations that describe solute concentrations in the three sections (donor, acceptor and membrane). These equations have been refined into linear forms, which are satisfying in the special conditions for simplification obtaining the important kinetic constants of the process experimentally.

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat