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bsj-2553
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy logic in the estimate of reliability function for k - components systems
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Abstract:

One of the important things provided by fuzzy model is to identify the membership functions. In the fuzzy reliability applications with failure functions of the kind who cares that deals with positive variables .There are many types of membership functions studied by many researchers, including triangular membership function, trapezoidal membership function and bell-shaped membership function. In I research we used beta function. Based on this paper study classical method to obtain estimation fuzzy reliability function for both series and parallel systems.

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Publication Date
Sat Jan 01 2011
Journal Name
Journal: Ibn Al-haitham Journal For Pure And Applied Sciences
A Study the effect the direction of the distribution of lighting to improve Images in different lighting by using technique adaptive histogram equalization
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparing parameters and Reliability of two-parameters exponential
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One of the most important problems in the statistical inference is estimating parameters and Reliability parameter and also interval estimation , and testing hypothesis . estimating two parameters of exponential distribution and also reliability parameter in a stress-strength model.

This parameter deals with estimating the scale parameter and the Location parameter µ , of two exponential distribution   ,using moments estimator and maximum likelihood estimator , also we estimate the parameter R=pr(x>y), where x,y are two- parameter independent exponential random variables .

Statistical properties of this distribution and its properti

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Publication Date
Sun Dec 01 2013
Journal Name
Baghdad Science Journal
Linear Increasing in Radial Electronic Density Distribution for K and L Shells throughout Some Be-Like Ions
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Maximum values of one particle radial electronic density distribution has been calculated by using Hartree-Fock (HF)wave function with data published by[A. Sarsa et al. Atomic Data and Nuclear Data Tables 88 (2004) 163–202] for K and L shells for some Be-like ions. The Results confirm that there is a linear behavior restricted the increasing of maximum points of one particle radial electronic density distribution for K and L shells throughout some Be-like ions. This linear behavior can be described by using the nth term formula of arithmetic sequence, that can be used to calculate the maximum radial electronic density distribution for any ion within Be like ions for Z<20.

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Publication Date
Tue Oct 01 2013
Journal Name
Proceedings Of The International Astronomical Union
The infrared <i>K</i>-band identification of the DSO/G2 source from VLT and Keck data
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Abstract<p>A fast moving infrared excess source (G2) which is widely interpreted as a core-less gas and dust cloud approaches Sagittarius A* (Sgr A*) on a presumably elliptical orbit. VLT <italic>K<sub>s</sub></italic>-band and Keck <italic>K</italic>′-band data result in clear continuum identifications and proper motions of this ∼19<sup><italic>m</italic></sup> Dusty S-cluster Object (DSO). In 2002-2007 it is confused with the star S63, but free of confusion again since 2007. Its near-infrared (NIR) colors and a comparison to other sources in the field speak in favor of the DSO being an IR excess star with photospheric continuum emission at 2 microns than a</p> ... Show More
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Publication Date
Thu May 04 2023
Journal Name
Biomedicine
Relationship between cathepsin K and total oxidative state in diabetes mellitus female patients with osteoporosis in Iraq
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Introduction and Aim: Diabetes mellitus patients almost always struggle with a metabolic condition known as chronic hyperglycemia. According to the World Health Organization, osteoporosis is a progressive systemic skeletal disorder that is characterized by decreasing bone mass and microstructural breakdown of bone tissue that increases susceptibility to fracture and increased risk of breaking a bone. Here, we aimed to compare the levels of CatK and total oxidative state in patients with diabetes and osteoporosis among the female Iraqi population and study the possible relationship between them.   Materials and Methods: This study included 40 females with diabetes (Group G1), 40 with diabetes and osteoporosis (Group G2) and 40 norma

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Wed Oct 02 2013
Journal Name
Journal Of The College Of Basic Education
Excess parameters of binary mixtures of tetrahydrofurfuryl alcohol with cyclopentanol and 1-pentanol at (293.15, 303.15 and 313.15 K)
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Publication Date
Thu May 31 2018
Journal Name
International Journal Of Control And Automation
Power Flow Control of Iraqi International Super Grid with Two-Terminal HVDC Techniques Using PSS/E
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