IRAQI JOURNAL OF STATISTICAL SCIENCES

In this research we studied flow of fluid in an cross section under the effect of electromagnetic field , we build a mathematical model which is represented by system of two dimensional non-linear partial differential equations and we solve that system by using alternating directions implicit method (ADI) which is one of the finite differences methods after we get the numerical solution and we explain the behavior of temperature distribution inside the cross section, we studied the influence ofRayleigh number and the Prandtl number and also the influence of Eckert number uponthe behavior of temperature distribution and all this done through the energy equation,
we arrived to steady state from unsteady state, we found the behavior of fluid flow inside the cross section and we studied the influence of Hartmann number upon the behavior of fluid flow in cross sectionand all this done through the motion equation.

The main object of this article is to study the subclasses of
multivalent meromorphic functions by using a linear operator in
punctured unit disk. Some geometric properties like coefficients bound,
distortion theorems and convolutions property
are investigated.

For each commutative ring we associate a graph

In this article,for a positive integer n ,the concept of n-locally split
homomorphism relative to a sub module has been introduced and
studied,which will turn out to be most useful in the studying and providing
characterizations of local projectivity, local-regularity in the sense of
(Zelmanowitz, Field house and Ware) relative to a sub module.They present
generalization of projectivity and the three types of regularity which have
been mentioned respectivily.
Keywords: n-locally(T)-split homomorphisms,n-locally(T)-projective modules, n-(T)-
regular modules,(T)-pure sub modules and Zelmanowitz (Field house) (T)-regular
modules.

In this paper we solved Burger’s_Fisher equation numerically with two dimensions by using three finite differences methods which are the explicit method, exponential method and DuFort_Frankel method, after comparing numerical results which have been obtained by using those methods with the exact solution for the equation, there has been found an approximation between exact solution and Numerical solutions for those methods.

In the literature there are some links between the notions of
directsummands, purity and projectivity. In this paper, we study these
links among the notions but relative to an arbitrary submodules, also a
partial links are consider. Properties and characterizations of these
notions which are correspondence, have been given.Among others, the
following have been proved. If M is a projective module, every pure
submoduleN relative to a submodule T is projective relative to N

It is well known that the circumstances experienced in Iraq since (1991) led to the smashing infrastructure and the deterioration of public services, especially energy services National Electric, which led to the spread of electric generators dramatically across Iraq, including the city of Mosul, and hence the large number of emission of gaseous pollutants
to the air, here came this research to study the effect of pollution on the lives of people in the city of Mosul This estimate because of persistent contamination of a significant impact on the health of members of the community and supply only through statistical analyzes Using cluster analysis might identify the most polluted areas in the city and a link to that population density and the other side of study of explanatory variables (predictive) on each contaminated with pollutants, To identify the variables that if controller, pollution control by using regression analysis, after treatment the problem of multi-linear using principal component analysis, we get see oils and ability.
The researchers found that the most polluted areas are the most densely populated, as well as the control of the explanatory variables, the number of generators, gas oil, diesel oil and the ability Controls to led the pollutants carbon monoxide(Co) and sulfur dioxide(So2), Alheidrokabonat(Hc) and nitrogen oxides(No) and particulate matter.

In this paper we investigated new algorithm of Augmented
Lagrang-method to solve constrained optimization. The new
proposed method satisfied global convergence and it is too
effective when compared with other established algorithm to solve
standard constrained problem.

we suppose in this paper a new scalar *

In this paper, persistence, fractal dimension, and predictability index a discrete-time food chain characterized by three species is modeled by a system of three nonlinear difference equations have been studied, where to find the time series of chain food by numerical iterations, stability analysis, identify equilibrium, and fixed points of this dynamic system. The values of modified Hurst exponent (H), fractals dimension (D), and predictability index (PIF) for a food chain were calculated. To know the regularity of the chain by phase space, bifurcation diagrams, and the binary (0-1) test for chaos have been analyzed the basic characteristics of the system. Where modern programming languages Version )maple(16.1) and matlab(7.14) ( used.
The results of analysis show that the values of modified Hurst exponent is anti-persistent in most cases the food chain, and that some of the values of the parameters internal equilibrium point loses its stability through bifurcation diagrams

In this paper, a modified formula for

Time series analysis gives a great importance to predict and many of the methods proposed for the purpose of forecasting. In view of the importance of accession deviation it was different of the goal of this research for a comparison between the Box-Jenkins method and Exponential Smoothing methods and compare the standard based on the mean square error(MSE) and mean absolute error (MAE) and mean absolute percentage error (MAPE), to assume the future values of the seasonal time series models and the model of suggested and fitting for time series data is ARIMA (0,1,2)(0,1,1) and has been applied to the observations represent daily of peak load for electric power in Mosul.

In this paper, we have derived anew proposed algorithm for conjugate
gradient method based on a projection matrix. This Algorithm satisfies the
sufficient descent condition and the globally converges . Numerical
comparisons with a standard conjugate gradient algorithm show that this
algorithm very effective depending on the number of iterations and the
number of functions evaluation.

The difference between the desired output and the actual output of
an multi-layers feed forward neural network produces an error value can
be expressed it as a function of the network weights. Therefore training
the network becomes an optimization problem to minimize the error
function.
This search suggests a new formula for computing learning rate
based on Meyers formula to modify conjugate gradient algorithm (MCG)
for training the FFNN. Typically this method accelerate the method of
Fletcher–Reeves (FRCG) and Polak–Ribere (PRCG) when using it to
solve three different types problems well known in the artificial neural
network (namely, XOR problem, function approximation, and the
Monk1 problem ) with 100 simulations.

In this paper, we study the effect of using two independent stratifying
variables on the approximate value of the variance of the stratified sample
mean obtained by Al-Kassab and Al-Elemat [1]. Ten special cases are
obtained and a comparison between these special cases is given using four
probability distributions.

In this paper, a proposed method for hiding secret data in audio
file (.WAV) is introduced. Genetic algorithm has been hybridized with
conjugate gradient algorithm which is one of the methods for solving
nonlinear unconstrained minimization problem, the hybrid genetic
algorithm is used to determine the optimum positions for Least
significant bit (LSB) by substituting the least significant bit of each
sampling point with a binary message.
Numerical results for the proposed hybrid genetic algorithm on
three test function were reported and compared with the results of
genetic algorithm, also two measures were used such as BER (Bit Error
Rate) and MSE (Mean Square Error) in order to access the performance
of the proposed steganography method.

The noise have so many effects on secret message embedded on
cover image, which cause a high distortion it could reach not to retrieve
or difficult to recognize in case of image.
In this research a study of noise effect on the image watermark
when it embedded on the image contourlet coefficients (contourlet
transformation was used as a recent transform for image), so the
watermark was embedded in the coefficients which has the low energy to
make less effect on the layout as much as possible in addition to give
wide area.
Different type of noise were added (Gaussain, Salt&Pepper and
Speckle Noise) on the practical application shows a clear effect for
Gaussain Noise and low effect for Speckle Noise in addition to high
security robustness plus difficulty to attacked by hackers.

Regression is one of the statistical methods and widely used in various fields of science in terms of defining clearly the relationship between the variables in the form of an equation to estimate the parameters and the strength and direction of this relationship , also , shows the estimate and predict response. Some nonparametric methods are used for estimating the model parameters of the multivariate linear regression when explanatory variables are ranked , methods and comparisons among them is done using the sum of mean squares error , Data are generated using simulation. The results showed that the method of least squares was better way at increase the sample size in the distributions of Normal and Exponential,where in the Uniform distribution was not affected by not rank and the size of the sample ,but affected variance in the distribution Gamma, the method of Linear ranks was
the best in the distribution of the Gamma, but influenced by variance, the method of median weighted was good when the sample size and rank lower only in the normal distribution.

The determination of the asphalt content of asphalt paving mixtures is a
fundamentally important test for many authorities and researchers in
highways field . This study seek to examined the application and use of
radial basis function artificial neural network with Gaussian activation
function by MATLAB software for predicting the asphalt content of the
hot mix asphalt paving mixtures using their properties of Marshall test.
The architecture of the study developed network consist of five input
nodes representing five properties of Marshall test, with six hidden nods,
while the output consist of one output node representing the asphalt
content percent.
The study results have show that the radial basis function network can
be applied as a recommended and appropriate computational tool to
accurately and quickly determine the asphalt content of asphalt mixtures
as alternative to using traditional techniques.

Studies of ant colonies have contributed in abundance to the set of
intelligent algorithms. The modeling of pheromone depositing by ants in
their search for the shortest paths to food sources resulted in the
development of shortest path optimization algorithms. Ant colony
optimization (ACO) algorithms have been successfully applied to
combinatorial optimization tasks especially to data mining classification
problem.
Internet and local networks have become everywhere. So
organizations are increasingly employing various systems that monitor
IT security breaches because intrusion events are growing day by day.
Ant-based algorithms or ant colony optimization (ACO) algorithms
can be applied to the data mining field to extract rule-based classifiers
and have been applied successfully to combinatorial optimization
problems. More recently, researches applied ACO to data mining
classification problems, where they introduced a classification algorithm
called Ant-Miner algorithm. The Ant-Miner algorithm is based on the
behavior of ants in searching of food. The aim of this paper is to use an
Ant Colony-based classification system (Ant_Miner algorithm) to extract
a set of rules for detection and classification, and it obtained a hopeful
classification accuracy.

In this research, we compared the geometric stochastic process with a related process ( -series stochastic process), in order to reach to the best process used to analyze monotone trend data, by using the modified moments and the maximum likelihood methods to estimate the parameters of the geometric stochastic process and -series stochastic process, on the assumption that the probability distribution for the first stop is lognormal. The comparison between these two processes, depending on the criteria proposed in the search.
Keyword: geometric process, modified moment, α –Series Process, maximum likelihood, Cement factory.
We also studied the successive inter arrival between failures of the General Company of Northern Cement and test whether the data follow processes or not, as well as estimating the parameters of the processes and compared them.

Conjugate Gradient (CG) methods are widely used for large scale unconstrained optimization problems. Most of CG-methods don’t always generate a descent search direction, so the descent condition is usually assumed in the analysis and implementations. In this paper, we have studied several modified CG-methods based on the famous CD (CG-method), and show that our new proposed CG-methods produces sufficient descent and converges globally if the Wolfe conditions are satisfied. Moreover, they produces the original version of the CD (CG-method), if the line searches are exact. The numerical results show that the new methods are more effective and promising by comparing with the standard CD and DY (CG-methods).

This paper is concerned with the prediction ofnonstationaryspatial stochastic process by the multivariate approach which is known as universal cokriging.
This approach is a generalization of kriging because universal cokriging depends on the underlying variable as well as other variables named as the secondary variables. These variables have a considerable effect on the process of prediction.
In this work we obtained the final formulas of the prediction equations system through the derivation of universal cokriging equations in the form of matrices. The obtained universal cokriging equations are quiet similar to the known equations system, and summarise clearly the spatial weights and prediction error variance. The obtained equations system is applied to a real data which represent two variables which areelevation of water(primary variable) and depth of well(secondary variable)in Wana district in Ninavah governorate in north of Iraq.The results obtained are very encouraging, very near to the real values, and with minimum cokriging variance. We compute eight spatial predictions together with error variance of prediction. All algorithms are programmed by Matlab_7.12 package.

Unemployment is one of the most serious problems facing the Iraqi economy, because of its economical, social and political effects, as well as it represents a waste of the human been. And unemployment threatens the existence of the defect in the social and political system and considered as a clear index of the inability of the government to perform its duties towards its citizens under its fragile construction and endangered sovereignty. For this reason, the idea of this paper comes to present the individuals distribution that are economically inactive (unemployed) according to the main reason for not working in the provinces of Iraq, for both genders, and analyzing these indexes by using one of the statistical methods to reach the most important one and comparing between them.

This paper is concerned with the estimation and statistical tests of hypothesises around parameters of generalized modified Bessel linear regression model by Non-Bayesian (classical) techniques under the assumption that the shape parameters ( ) are known . We used the maximum likelihood method in estimation and using the likelihood ratio criterion for structure statistical hypothesis tests around parameters of the Regression model .Also we noted that probability distribution for estimator of the vector of parameters , is following the generalized multivariate modified Bessel distribution and the statistic test for the vector of parameters under the null hypothesis and alternative hypothesis are following the central F distribution and the non-central F-Bessel distribution respectively.

Factor analysis model belongs to a family of linear models and because the multivariate data sets do not vacate outliers . For this reason , this paper is concerned with Bayesian analysis of mixed normal factor analysis model . The mixture normal distribution treats the observations of a sample as they are taken from two different populations and none from single population . The model is analyzed when the common factor is (stochastic and non-stochastic) variable . We suppose that all the parameters of the model are unknown , some of them have prior distributions belong to the conjugate family.

This study found out a method derived from ridge regression and restricted least-squares methods to solve the problem of multicollinearity and restricted data at the same time.
A simulation study including these problems was carried out . The study used the mean squares error (MSE) to test the efficiency of the Proposedformula. The study concludes that the Proposed formula results in the lowest mean squares error compared with other methods.

The Quadratic Assignment Problem (QAP) is one of the Combinatorial Optimization Problems that has wide popular and attention from researchers because simple formulation and important applications, it is based on finding the best assignment of sites with available facilities. In This research, we use the Simulated Annealing Algorithm (SA) to solve the Quadratic Assignment Problem with apply on the Al-Salam hospital in Mosul In order to find Better distribution of advisory services Inside the hospital building to curb the effort by
patients while moving the patient from the advisory service to another and thus minimize the total distance for transmission patients, The new distribution showed an improvement by ratio 7.38%.

In this research we find an optimal solutions for traveling salesman problem (TSP) using Branch and Bound method as well as we use an intelligence techniques represented by ant colony optimization (ACO) and applied them on the DNA chain data, where the technique method give an optimal solution with high efficiency.

This research attempts to find answers to a number of research questions, the most important of which: is it possible to use business & technological architecture of Dashboards-based BI systems in reinforcing the discovering & sharing of knowledge in context of Informatics? In the light of that, Researchers seek to build the proposed Business Dashboards in the context of the file of self-evaluation of the Union of the Arab Universities in the College of Administration & Economics in University of Mosul. The research has reached several conclusions, the most important of which:
the proposed Dashboards achieve the efficiency & effectiveness in the performance of college through the delivery of Information & Knowledge at the right time to End Users, which accomplishes savings in time & effort. Also, the proposed Dashboards are connected through Electronic Collaboration Systems, one of which is the Electronic Mail.

This paper aims to use Particle Swarm Optimization (PSO) to solve multi-objective master production schedule problems, which is one of the NP-Hard problems, in addition to apply the MPS in the Northern General Company for Cement with his five plants. The application involves determination of the available energy of each plant by calculating the availability,
in addition to the determine the overall requirements by demand forecasting using neural networks. The PSO proved its efficiency in solving MPS problem compared with the genetic algorithm, as the results clearly showed the superiority of the PSO on genetic algorithm in all targets. and we write the programs using (Matlab R2012a) language for this purpose.

In this paper we deal with the optimal solution for linear fractional programming problem . our idea is based on transforming the objective function and constraints with applying the genetic algorithm to find maximum number of units with maximum value of the objective function which represent a ratio between profit and cost, then we applied it in the Spinning and weaving factory.

This paper presents a method mixes encryption technique with hiding. In which a text encrypted and then hid in an image by using colors, for the reason that the transferred data to be away from doubt and to be difficult to analyze if there is doubt about it. The proposed method depends on secret key in a table and a color value of the text in Microsoft word 2007. In the recovery step, depending on the secret key and by using digital image processing methods, letters of the hidden message converted to a text to extract the message from the digital image.
Various text length and various color values were applied in the proposed method.Results show that the values of the PSNR were (∞), and the values of correlation coefficient were equal to (1) for all applied images. That proves that message hidden by using this method is above suspicion for analysts, which means the proposed method is very efficient.

In recent years , The use of concealment techniques that include audio files has been increased due to the fact that the tools available to analyze sound fail when applied .
Another reason is the popularity of MP3 and WAV files , especially on the Internet, the purpose of this research is to shed light on one of the latest of these techniques which is M16MA that is used to hide data within the Audio Files .
As well as give a general view on the audio formats that have been used as a cover for the data and identify some of the characteristics and advantages of those formats, the purpose of this research is to apply the algorithm above to the audio files of type WAV and MP3.

Due to the evolution of massive means of communication and the exchange of information has become personal privacy vulnerable to abuse more easily than ever before, so there is a need to adopt the technology more sophisticated and more secret and preserve the information,
Steganography was used. Steganography is a science hide confidential data in the carrier task inoffensive manner embeds the existence of hidden data without raising suspicion in order to keep the contact between the two callers confidential. The mobile phone is considered as wireless means of communication as the evolution of this amazing device quickly. In addition to being a means of voice communication, there were many uses and functions, to make it a computer for saving a lot of and multiple information, surf the Internet web sites, a camera and a tool to play and entertainment, .. etc.
This paper provided new method to hide using Steganography to include secret information (voice) in images with different sizes as a cover for such secret information without getting any distortion brings attention. The operation of selecting sites to hide it has by generating random numbers using a private key, which is also used in the recovery operation. It also adopted the Bluetooth transmission operations. Experiments proved the modalities through performance measures (MSE, PSNR, NC). As the results showed the effectiveness and durability. The implementation was done using J2ME language.

Singled out for this research study the issue of fuzzy logic and use in the medical field to set the values estimated for the data thalassemia patients, as well as the research involved a study hybridization fuzzy logic with artificial neural networks and the application form hybrid data and note the accuracy of the results between the two systems, which proved to form hybrid superiority

The research aims to find ways computerized to encode Arabic numbers by the English alphabet , and merges the simple methods with the old ideas and modern techniques to get the encoding process consistent with the intrusion techniques on the information stored or traded via networking site. Search sought to recruit the properties of Arabic numbers and the Vegener table to train artificial neural network on the encoding process.
Several artificial neural networks was build using the possibilities available in the (MATLAB R2012b) program to process the encoding for saving time and effort when conducting these operations by conventional ways, neural networks have shown the ability and high portability on the implementation of the encoding process after passing a series of steps.