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Object Tracking Using Adaptive Diffusion Flow Active Model
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Object tracking is one of the most important topics in the fields of image processing and computer vision. Object tracking is the process of finding interesting moving objects and following them from frame to frame. In this research, Active models–based object tracking algorithm is introduced. Active models are curves placed in an image domain and can evolve to segment the object of interest. Adaptive Diffusion Flow Active Model (ADFAM) is one the most famous types of Active Models. It overcomes the drawbacks of all previous versions of the Active Models specially the leakage problem, noise sensitivity, and long narrow hols or concavities. The ADFAM is well known for its very good capabilities in the segmentation process. In this research, it is adopted for segmentation and tracking purposes. The proposed object tracking algorithm is initiated by detecting the target moving object manually. Then, the ADFAM convergence of the current video frame is reused as an initial estimation for the next video frame and so on. The proposed algorithm is applied to several video sequences, different in terms of the nature of the object, the nature of the background, the speed of the object, object motion direction, and the inter-frame displacement. Experimental results show that the proposed algorithm performed very well and successfully tracked the target object in all different cases.

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Eliminate harmful side – effects of Controls System by designing Activity – Based Responsibility Accounting model
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This research has come out with that, function-based responsibility accounting system has harmful side – effects preventing it of achieving its controlling objective, that is, goal congruence, which are due to its un integrated measures, its focus on measuring measurable behaviors while neglecting behaviors that are hardly measured, and its dependence on standard operating procedures.

In addition, the system hypotheses and measures are designed to fit previous business environment, not the current environment.

The research has also concluded that the suggestive model, that is, activity-based responsibility accounting is designed to get ride of harmful side – effects of functi

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Publication Date
Wed Oct 28 2015
Journal Name
Journal Of Mathematics And System Science
Simulating Particle Swarm Optimization Algorithm to Estimate Likelihood Function of ARMA(1, 1) Model
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Publication Date
Wed Sep 05 2007
Journal Name
Neural Network World
A canonical generic algorithm for likelihood estimator of first order moving average model parameter
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The increasing availability of computing power in the past two decades has been use to develop new techniques for optimizing solution of estimation problem. Today's computational capacity and the widespread availability of computers have enabled development of new generation of intelligent computing techniques, such as our interest algorithm, this paper presents one of new class of stochastic search algorithm (known as Canonical Genetic' Algorithm ‘CGA’) for optimizing the maximum likelihood function strategy is composed of three main steps: recombination, mutation, and selection. The experimental design is based on simulating the CGA with different values of are compared with those of moment method. Based on MSE value obtained from bot

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Scopus
Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Some Estimation Methods Of GM(1,1) Model With Missing Data and Practical Application
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This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to

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Publication Date
Sun Jan 13 2019
Journal Name
Iraqi Journal Of Physics
Shell model and Hartree-Fock calculations of electron scattering form factors for 25Mg nucleus
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Shell model and Hartree-Fock calculations have been adopted to study the elastic and inelastic electron scattering form factors for 25Mg nucleus. The wave functions for this nucleus have been utilized from the shell model using USDA two-body effective interaction for this nucleus with the sd shell model space. On the other hand, the SkXcsb Skyrme parameterization has been used within the Hartree-Fock method to get the single-particle potential which is used to calculate the single-particle matrix elements. The calculated form factors have been compared with available experimental data.

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
PHYSICAL MODEL OF KEROSENE PLUME MIGRATION IN AN UNSATURATED ZONE OF THE SANDY SOIL
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Physical model tests were simulated non-aqueous phase liquid (NAPL) spill in two-dimensional
domain above the water table. Four laboratory experiments were carried out in the sand-filled
tank. The evolution of the plume was observed through the transparent side of this tank and the
contaminant front was traced at appropriate intervals. The materials used in these experiments
were Al-Najaf sand as a porous medium and kerosene as contaminant.
The results of the experiments showed that after kerosene spreading comes to a halt (ceased) in
the homogeneous sand, the bulk of this contaminant is contained within a pancake-shaped lens
situated on top of the capillary fringe.

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Word Cloud Model based on Hate Speech in an Online Social Media Environment
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Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq

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Publication Date
Tue May 16 2023
Journal Name
Political Sciences Journal
The Dens of Extremism and Terrorism in Syrian Camps (Al-Hol as a model)
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After the defeat of the military terrorist organization "ISIS" and the fall of the throne of its alleged state in the Iraqi city of Nineveh, in Syrian Baghouz, and the end of its control over the land, the Syrian camps, especially "Al-Hol" camp, emerge as an incubator for the ideology of the terrorist organization "ISIS" and a vital base for its consolidation and dissemination, which includes (68,000- 73,000) people. During the years following the military defeat of (ISIS), the camp witnesses the spread of extremist ideas widely at the hands of its residents, including the families of the organizations dead's, extremist detainees, and those who deal with it, taking advantage of the deterioration of the environmental, se

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Publication Date
Sat Mar 01 2025
Journal Name
Iet Conference Proceedings
Spatial quantile autoregressive model with application to poverty rates in the districts of Iraq
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This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro

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Publication Date
Mon Mar 15 2021
Journal Name
The Journal Of Legal And Social Sciences
Limitations on the authority of a judge in case-law ( France as a model )
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When exercising their authority in the jurisprudence, judges are subject to a set of restrictions that they must adhere to, as they do not want their jurisprudence to be accepted and welcomed by law practitioners in general, and legal scholars in particular, and in contrast to it, the arrows of criticism and defamation will extend to that jurisprudence, and then they will have to reverse them . Perhaps the most important of those restrictions imposed on judges is their observance of justice between the parties to the lawsuit through their lack of bias for one of the parties at the expense of the other, in addition to their observance of public order and public morals, as well as their observance of the legal texts that they work under its u

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