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Study the Wet Region in Anbar Province by Use Remote Sensing (RS) and Geographic Information System (GIS) Techniques
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Recently, in the last years, the world interested with Ecosystem is increased, and
that is interrelation with global atmospherically, by the existence followed
continuous animate variables, that is immediately influence at ecosystem nature by
inspection systems process such as satellite imagery or aerial photographs, that can
determination the wetland regions which aid fulfillment balance globe ecosystem. In
this study a determination of wetland regions in IRAQ, was done for Anbar
province, because many of regions Saturated with water or sponge and aquatic of
plant, additionally, existence metrology factors that significant role were depended
to be as important factor to define the wetland regions as temperatures, relative
humidity, and rainfall. The ArcMap-GIS tools of interpolation tchniques of IDW
type were applied to interpolate these metrology data exact interpolation.
Also remote sensing is utilized exploitation Landsat satellite imagery production
of 2007 year for March month, and it is processing by vegetables and (water,
rainwater) regions determination, and it may processed variable factors
measurements for metrology subject at regions by determined affirmative influence
wetland activeness by using geographic information system (GIS).

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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Sun May 17 2020
Journal Name
Iraqi Journal Of Science
Multicomponent Inverse Lomax Stress-Strength Reliability
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In this article we derive two reliability mathematical expressions of two kinds of s-out of -k stress-strength model systems; and . Both stress and strength are assumed to have an Inverse Lomax distribution with unknown shape parameters and a common known scale parameter. The increase and decrease in the real values of the two reliabilities are studied according to the increase and decrease in the distribution parameters. Two estimation methods are used to estimate the distribution parameters and the reliabilities, which are Maximum Likelihood and Regression. A comparison is made between the estimators based on a simulation study by the mean squared error criteria, which revealed that the maximum likelihood estimator works the best.

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Publication Date
Sun Sep 01 2019
Journal Name
Al-dhad Book Store
Multivariate Analysis - First Edition
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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. 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. Many solved examples are intended in this book, in addition to a variety of unsolved relied pro

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Publication Date
Fri Feb 01 2019
Journal Name
Al-dhad - Book Store And Publishing
Multivariate Analysis (First Edition)
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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. 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. Many solved examples are intended in this book, in addition to a variety of unsolved relied pro

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Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Model Reference Adaptive Control based on a Self-Recurrent Wavelet Neural Network Utilizing Micro Artificial Immune Systems
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Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

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Publication Date
Sun Oct 01 2017
Journal Name
Iecon 2017 - 43rd Annual Conference Of The Ieee Industrial Electronics Society
Optimal second order integral sliding mode control for a flexible joint robot manipulator
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The flexible joint robot manipulators provide various benefits, but also present many control challenges such as nonlinearities, strong coupling, vibration, etc. This paper proposes optimal second order integral sliding mode control (OSOISMC) for a single link flexible joint manipulator to achieve robust and smooth performance. Firstly, the integral sliding mode control is designed, which consists of a linear quadratic regulator (LQR) as a nominal control, and switching control. This control guarantees the system robustness for the entire process. Then, a nonsingularterminal sliding surface is added to give a second order integral sliding mode control (SOISMC), which reduces chartering effect and gives the finite time convergence as well. S

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Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
Utilizing a Magnetic Abrasive Finishing Technique (MAF) Via Adaptive Nero Fuzzy(ANFIS)
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 Abstract

An experimental study was conducted for measuring the quality of surface finishing roughness using magnetic abrasive finishing technique (MAF) on brass plate which is very difficult to be polish by a conventional machining process where the cost is high and much more susceptible to surface damage as compared to other materials. Four operation parameters were studied, the gap between the work piece and the electromagnetic inductor, the current that generate the flux, the rotational Spindale speed and amount of abrasive powder size considering constant linear feed movement between machine head and workpiece. Adaptive Neuro fuzzy inference system  (ANFIS) was implemented for evaluation of a serie

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Publication Date
Thu Apr 28 2022
Journal Name
Iraqi Journal Of Science
A Load Balancing Scheme for a Server Cluster Using History Results
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Load balancing in computer networks is one of the most subjects that has got researcher's attention in the last decade. Load balancing will lead to reduce processing time and memory usage that are the most two concerns of the network companies in now days, and they are the most two factors that determine if the approach is worthy applicable or not. There are two kinds of load balancing, distributing jobs among other servers before processing starts and stays at that server to the end of the process is called static load balancing, and moving jobs during processing is called dynamic load balancing. In this research, two algorithms are designed and implemented, the History Usage (HU) algorithm that statically balances the load of a Loaded

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Publication Date
Tue Jan 01 2019
Journal Name
Преподаватель ХХi век
Фонограмматическая когниция в русском и арабском языках: основы флективного когнитивного строя
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В статье рассматривается вопрос о связи флективных изменений с мыслительными процессами на материале русского и арабского языков, анализируются семантические, фонетические, морфологические и синтаксические основы фонограмматической когниции. Цель статьи выявление прямой связи между количественным звуковым изменением согласного состава слова и мыслительными процессами, с помощью которых человеческ

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