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Publication Date

Fri Feb 04 2022

Journal Name

Iraqi Journal Of Science

Volume

57

Issue Number

4A

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The State of the Main Basement Features of the Western Desert of Iraq, A New Look

Basement depth

main features

magnetic data

corrected depth estimation

Mohammed A.

Fitian R.

Dhiya A.

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The reduction to pole of the aeromagnetic map of the western desert of Iraq has been used to outline the main basement structural features. Three selected magnetic anomalies are used to determine the depths of their magnetic sources. The estimated depths are obtained by using slope half slope method and have been corrected through the application of a published nomogram. These depths are compared with previous published depth values which provide a new look at the basement of the western desert in addition to the thickness map of the Paleozoic formations. The results shed light on the important of the great depths of the basement structures and in turn the sedimentary cover to be considered for future hydrocarbon exploration

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Publication Date

Wed Aug 30 2023

Journal Name

Iraqi Journal Of Science

Linear Feedback Shift Registers-Based Randomization for Image Steganography

Information hiding

Embedding data

Image security

Spatial domain Frequency domain

LSB

DCT

Randomness

LFSR

Payload capacity

Mohammed Abod

Saad

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Steganography involves concealing information by embedding data within cover media and it can be categorized into two main domains: spatial and frequency. This paper presents two distinct methods. The first is operating in the spatial domain which utilizes the least significant bits (LSBs) to conceal a secret message. The second method is the functioning in the frequency domain which hides the secret message within the LSBs of the middle-frequency band of the discrete cosine transform (DCT) coefficients. These methods enhance obfuscation by utilizing two layers of randomness: random pixel embedding and random bit embedding within each pixel. Unlike other available methods that embed data in sequential order with a fixed amount.

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Publication Date

Wed Apr 25 2018

Journal Name

Ibn Al-haitham Journal For Pure And Applied Sciences

Using Approximation Non-Bayesian Computation with Fuzzy Data to Estimation Inverse Weibull Parameters and Reliability Function

Non-Bayesian Methods

Inverse Weibull distribution

Expectation Maximization algorithm

Newton-Raphson algorithm

Moment method

Fuzzy data.

Nadia Hashim

Shurooq A.K.

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In real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely â€œNewton-Raphsonâ€ and the â€œExpectation-Maximizationâ€ techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i

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Publication Date

Fri Jun 30 2023

Journal Name

Iraqi Journal Of Science

Satellite Image Classification using Spectral Signature and Deep Learning

Image preprocessing

Fast Fourier Transform

Spectral Signature

Deep Learning

Data set

Deep Neural Network

Artificial Neural Network

Zainab Hussain

Maisa'a Abd Ali

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When images are customized to identify changes that have occurred using techniques such as spectral signature, which can be used to extract features, they can be of great value. In this paper, it was proposed to use the spectral signature to extract information from satellite images and then classify them into four categories. Here it is based on a set of data from the Kaggle satellite imagery website that represents different categories such as clouds, deserts, water, and green areas. After preprocessing these images, the data is transformed into a spectral signature using the Fast Fourier Transform (FFT) algorithm. Then the data of each image is reduced by selecting the top 20 features and transforming them from a two-dimensiona

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Publication Date

Thu Sep 30 2021

Journal Name

Iraqi Journal Of Science

PFDINN: Comparison between Three Back-propagation Algorithms for Pear Fruit Disease Identification

Pear fruit diseases

k-means clustering

First and second order statistical features

Scaled conjugate gradient backpropagation SCG-BP

Resilient backpropagation R-BP

Bayesian regularization backpropagation BR-BP

Samar Amil

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The diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca

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Publication Date

Mon Jan 06 2025

Journal Name

Journal Of Engineering

Image Compression Using 3-D Two-Level Techniques

Image compression

3-D two level wavelet transform

3-D two level multi-wavelet transform

3-D two level hybrid technique

Image data properties.

Zainab

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In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-

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Publication Date

Mon Jun 05 2023

Journal Name

Journal Of Engineering

Image Compression Using 3-D Two-Level Technique

Image compression

3-D two level wavelet transform

3-D two level multi-wavelet transform

3-D two level hybrid technique

Image data properties

Zainab Ibraheem

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In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent r

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Publication Date

Tue Oct 20 2020

Journal Name

Ibn Al-haitham Journal For Pure And Applied Sciences

Fuzzy Semimaximal Submodules

Let R be a commutative ring with unity and an R-submodule N is called semimaximal if and only if Mâ„(Nis a semisimple R-module ).The main objective of this work is to fuzzify this concept

study the basic properties and we investigate the sufficient conditions of F-submodules to be semimaximal .Also the concepts of (simple

semisimple) F- submodules and quotient F- modules are introduced and given some properties .

Maysoun

Hatam

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Let R be a commutative ring with unity and an R-submodule N is called semimaximal if and only if

the sufficient conditions of F-submodules to be semimaximal .Also the concepts of (simple , semisimple) F- submodules and quotient F- modules are introduced and given some properties .

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Publication Date

Sat Oct 01 2016

Journal Name

Journal Of Theoretical And Applied Information Technology

Factors affecting global virtual teams’ performance in software projects

Today the trend is to perform software development work via distributed geographical area among team

individual or even as an organization. However

due to the global market and international presence of many companies

there is a need to implement a global virtual teams. The global virtual team members are gradually engaged in globalized business environments across space

time and organizational boundaries via information and communication technologies. A global virtual team relies on communication

collaboration

and information exchange are the most important criteria in global virtual teams’ operations. The purpose of this paper is to answer two research questions. The first research question is to identify the factors affecting global virtual teams’ performance. A systematic literature review was conducted to answer the first research question. The second research question is on what the rank of the factor affecting the global virtual teams’ performance according to their level of effect on global virtual teams’ performance. Online survey was conducted within 103 developers and IT managers from eight IT companies to answer the second research question. The Statistical Package for Social Science (SPSS 22) was used to analyze the collected data. In this study

we investigated factors that affect global virtual teams’ performance

factors considered include cultural differences

language problems

time-zone differences

team size

technical problems

lack of trust

lack of sufficient training

and ICT problems. Also the findings indicated that lack of sufficient training is the highest level of effect on global virtual teams’ performance. On the other hand

Ali Yahya Gheni

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