doi:10.24996/ijs.2022.63.7.18

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Publication Date

Sun Jul 31 2022

Journal Name

Iraqi Journal Of Science

Volume

63

Issue Number

7

DOI

10.24996/ijs.2022.63.7.18

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Influence of Fe2O3 Dust Particles on the Plasma Characteristics of D.C Sputtering System

Dust plasma

Optical emission spectroscopy

electron temperature

electron density

Plasma parameters

Shahad Emaduldeen

Qusay A.

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This work is an experimental study conducted to study the effects of iron oxide dust particles (Fe₂O₃) on the characteristics of DC discharge plasma in argon gas under vacuum. Electron temperature ( ) and electron density (n_e) were calculated by Boltzmann plots and Stark broadening, respectively. The results show that both the electron density and plasma frequency ( ) increased with the operating pressure. While, and Debye length ( ) decreased with pressure. The glow discharge is more stable with the Fe₂O₃-dust particles; all dust plasma parameters have lower values than those of the dust-free plasma.

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Publication Date

Sun Jun 01 2014

Journal Name

Journal Of Economics And Administrative Sciences

Design Sampling Plan when Life Time Follows Logistic Distribution

Design Sampling Plan

Life Time

Simulation Experiments

Logistic Distribution

Maximum Likelihood Estimation

Probability Density Function

Cumulative Distribution .

نزار مصطفى

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Design sampling plan was and still one of most importance subjects because it give lowest cost comparing with others, time live statistical distribution should be known to give best estimators for parameters of sampling plan and get best sampling plan.

Research dell with design sampling plan when live time distribution follow Logistic distribution with () as location and shape parameters, using these information can help us getting (number of groups, sample size) associated with reject or accept the Lot

Experimental results for simulated data shows the least number of groups and sample size needs to reject or accept the Lot with certain probability of

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Publication Date

Mon Sep 23 2019

Journal Name

Baghdad Science Journal

A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network

Burst Header Packet Flooding Attack

K-Means Algorithm

Machine Learning

Optical Burst Switching Network

Semi-supervised Learning.

Md. Kamrul Hossain

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Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

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Publication Date

Sun Oct 02 2022

Journal Name

Al-manhaj

Mathematical Statistics - Second Edition

Mathematical Expectation

Moment Generating Function

Cumulative Distribution Function

Probability Mass Function

Probability Density Function

Discrete Distributions

Continuous Distributions

Joint distributions

Marginal Distributions

Conditional Distributions

Transformations

Order Statistics.

Omar Abdulmohsin

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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

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